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Health Qual Life OutcomesHealth and Quality of Life Outcomes1477-7525BioMed Central London 1477-7525-2-541538504910.1186/1477-7525-2-54ResearchAge related differences in individual quality of life domains in youth with type 1 diabetes Wagner Julie A 1juwagner@uchc.eduAbbott Gina 1gabbott@uchc.eduLett Syretta 1syrettal@hotmail.com1 Department of Behavioral Sciences and Community Health, University of Connecticut Health Center, 263 Farmington Avenue, Farmington, CT 06030, USA2004 22 9 2004 2 54 54 5 4 2004 22 9 2004 Copyright © 2004 Wagner et al; licensee BioMed Central Ltd.2004Wagner 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
Investigating individual, as opposed to predetermined, quality of life domains may yield important information about quality of life. This study investigated the individual quality of life domains nominated by youth with type 1 diabetes.
Methods
Eighty young people attending a diabetes summer camp completed the Schedule for the Evaluation of Individual Quality of Life-Direct Weighting interview, which allows respondents to nominate and evaluate their own quality of life domains.
Results
The most frequently nominated life domains were 'family', 'friends', 'diabetes', 'school', and 'health' respectively; ranked in terms of importance, domains were 'religion', 'family', 'diabetes', 'health', and 'the golden rule'; ranked in order of satisfaction, domains were 'camp', 'religion', 'pets', and 'family' and 'a special person' were tied for fifth. Respondent age was significantly positively associated with the importance of 'friends', and a significantly negatively associated with the importance of 'family'. Nearly all respondents nominated a quality of life domain relating to physical status, however, the specific physical status domain and the rationale for its nomination varied. Some respondents nominated 'diabetes' as a domain and emphasized diabetes 'self-care behaviors' in order to avoid negative health consequences such as hospitalization. Other respondents nominated 'health' and focused more generally on 'living well with diabetes'. In an ANOVA with physical status domain as the independent variable and age as the dependent variable, participants who nominated 'diabetes' were younger (M = 12.9 years) than those who nominated 'health' (M = 15.9 years). In a second ANOVA, with rationale for nomination the physical status domain as the independent variable, and age as the dependent variable, those who emphasized 'self care behaviors' were younger (M = 11.8 years) than those who emphasized 'living well with diabetes' (M = 14.6 years). These differences are discussed in terms of cognitive development and in relation to the decline in self-care and glycemic control often observed during adolescence.
Conclusions
Respondents nominated many non-diabetes life domains, underscoring that QOL is multidimensional. Subtle changes in conceptualization of diabetes and health with increasing age may reflect cognitive development or disease adjustment, and speak to the need for special attention to adolescents. Understanding individual quality of life domains can help clinicians motivate their young patients with diabetes for self-care. Future research should employ a larger, more diverse sample, and use longitudinal designs.
diabeteschildrenadolescentsquality of life
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Background
Quality of life (QOL) is now recognized as an important outcome for people with diabetes. In general, diabetes has been shown to negatively impact QOL [1]. Tighter glycemic control is associated with better QOL, despite the increased treatment demands it commonly requires [2]. As standards for optimal glycemic control get more rigorous, and as medical treatments for diabetes develop, a better understanding of the personal meaning of disease and related QOL would be beneficial.
The measurement of QOL is evolving, and a state of the art review identified numerous different QOL measures [3]. Most QOL measures ask individuals to assess their QOL using predetermined items. This is true for both generic measures such as the Medical Outcome Study Short Form (SF-36) [4], and disease specific measures such as the Diabetes Quality of Life for Youth questionnaire (DQOLY) [5,6] and the Audit of Diabetes Dependent Quality of Life (ADDQoL) [7]. A more recent approach to QOL assessment is the development of individualized, or patient generated, measures that use an open ended question format. These measures allow respondents, from their own perspective, to identify the life domains that contribute most to their overall quality of life. This complimentary approach allows respondents to paint a fuller picture of their quality of life focusing on the domains that they consider important. The ADDQoL approaches this technique, in that it allows patients to indicate items on the measure that are 'not applicable' to their quality of life and weights remaining responses appropriately. Its paper and pencil format allow for its wider use than an interview format. However, it does not allow respondents to generate their own domains.
By pre-selecting life domains, and/or limiting items to those that are diabetes relevant, we limit our breadth and depth of understanding of youth with diabetes. While diabetes impacts nearly all aspects of a young person's life, it may not be the central, organizing construct under which all other domains fall. If a child with diabetes was asked "What is important to you?" and "How is that important thing going for you right now?" diabetes may or may not be mentioned. For example, in a sample of adolescents with type 1 diabetes, fewer than 1/3 of participants ranked diabetes as the most important life domain, the remainder rated it much lower [8]. And when diabetes is considered important, the rationale for its importance may vary between respondents or by developmental stage. Furthermore, we know very little about the developmental aspect of QOL. Do QOL domains differ by age? Does the importance attributed to the domains differ? Does the rationale for their importance differ?
These questions are not of solely theoretical interest. On an individual patient basis, such information may be clinically useful. Understanding the QOL domains that are important to an individual patient gives a provider information about how to motivate that individual for improved self-care. This is true for diabetes-related life domains and those domains that are not directly diabetes-related. For example, a provider treating a child who values athletics could use this information to motivate the child to improve diabetes self-care by demonstrating to him that improved glycemia could enhance his athletic performance. Using a patient's own value system to promote healthy behavior has been advocated by others [9] and is consistent with a patient centered approach to medical care. But, the tools to assess the life domains of importance for a given individual are required for such an approach. Walker and Bradley [8] found that diabetes nurse specialists who had considerable knowledge and experience of individual patients, were unable to predict accurately patients' ratings of their own QOL, nor the relative importance of the domains that constitute it, because of the subjective and complex nature of QOL.
The Schedule for the Evaluation of Individual Quality of Life-Direct Weight (SEIQoL-DW) is a theory based [10] structured interview during which respondents nominate 5 life domains that are most important to their own QOL [11]. The SEIQoL-DW has been used with a variety of adult and geriatric medical populations including patients with HIV/AIDS [12], cancer [13], amyotrophic lateral sclerosis [14], psychiatric diagnoses [15], multiple sclerosis [16], motor neuron disease [17], Hodgkins lymphoma [18], and stem cell recipients [19]. In the only other study using the SEIQoL in youth with diabetes, Walker and Bradley [8] administered it to 15 adolescents with type 1 diabetes. What is reported here is a descriptive, exploratory study of individual quality of life in young people with diabetes. It is not the intention to advocate the use of the SEIQoL-DW in place of standard measures such as the DQOLY. Rather, the SEIQoL-DW interview was used to provide a window into the lives children and young people with diabetes beyond what is typically assessed with paper and pencil measures. Such an understanding helps us view the patient as a whole person, and approach them from their own unique perspective. Previously, we reported the appropriateness of using the SEIQoL-DW in the children from this sample under age 18 years [20]. This article reports age related differences in individual quality of life domains in an expanded sample that includes college-aged respondents.
Methods
Sample
Participants were campers, and young counselors who had previously been campers, at an overnight summer camp for children with diabetes. The camp serves children with diabetes in northern New England. One hundred and twenty campers from 8–15 years old attend a 2-week session. The majority of the staff has diabetes.
Measures
Demographic and disease variables
For campers, parents completed a survey of demographic and disease variables for themselves, their family, and their child with diabetes. Counselors who participated in the study completed the survey of demographic and disease variables themselves. Demographic variables included family structure, socioeconomic status, school performance, and race/ethnicity. Disease variables included disease duration, treatment regimen, HbA1c (gold standard measure of glycemic control), frequency of complications, and emergent use of health care services.
Schedule for the Evaluation of Individual Quality of Life-Direct Weighting
As described by Browne et al [19], there are three stages to administration of the SEIQoL-DW. In the first stage respondents nominate five life domains that they consider most important to their overall quality of life. Instructions were modified only slightly for youth, with an emphasis on making the language easy to understand and examples age appropriate. Participants were asked "For each of us, happiness and satisfaction in life depends on the areas of life which are important to us. When these important areas are going well, we are happy, but when they are going badly, we feel worried or unhappy. What is considered important varies from person to person. What is most important to you may not be so important to me or to your parents or friends and vice versa. I am interested in knowing what the most important areas of your life are at the moment. What are the five most important areas of your life at present – the things which make your life happy or sad at the moment?" If participants are unable to volunteer domains, examples are read from a standard list that is included in the SEIQoL-DW administration manual, and responses are noted as such. To assess a child's understanding of these directions, each participant was asked to "retell" the directions to the interviewer. If the child was unable to repeat the directions in basic terms and show understanding, they were excluded from the study. The appropriateness of the SEIQoL-DW in youth has been described elsewhere [20]. The authors took great care to ensure that those who were included yielded valid data, and those who did not were excluded.
In the second stage, the respondents rate each domain on a 0–100 mm vertical visual analogue scale anchored at the two extremes by the terms 'best possible' and 'worst possible'. These anchors are designed to allow individuals to use their own criteria when assessing their status within each domain.
The third stage involves a weighting procedure wherein the respondent judges the relative importance of each domain. In the original version of the SEIQoL a technique known as judgment analysis was used. Because of practical limitations of judgment analysis, a direct weighting procedure has been developed [21]. The direct weighting (DW) procedure of the SEIQoL-DW consists of asking participants to manipulate five stacked, centrally mounted, interlocking laminated disks. Each disk is a different color and is labeled with one of the five domains nominated by the individual. The disks can be rotated over each other to produce a dynamic pie chart where the relative size of each sector represents the weight the respondent attaches to a QOL domain. The proportion of the chart that each sector represents can be scored from a 100-point scale on the circumference. See figure 1 for example of the weighting instrument. Total quality of life is then calculated by multiplying each domain importance rating by the domain weighting and then summing the products. Examples of this scoring have been previously published [20].
Figure 1 A representative distribution of life domains on the weighting instrument.
Studies have shown the SEIQoL to have good internal consistency, ranging from .6 to .9 [21-26]. It has also been shown to have adequate test-retest reliability, with Pearson's correlation >.70 [27]. The newer SEIQoL-DW has been shown to be sensitive to change, to have good construct validity [27,28], and to be psychometrically comparable to the SEIQoL [21,26]. A recent review concluded that the SEIQoL is superior to other patient generated QOL measures [29].
Procedures
This project was carried out in accordance with the American Psychological Association guidelines for ethical conduct of research. It was approved by the University of Connecticut Health Center's institutional review board. One week prior to the two-week camp session, a letter was sent to the parents of campers, describing the study. Parents were sent a consent form for themselves, an assent form for their child, and a survey of disease and demographic data. Upon their arrival at camp, the materials were collected from parents and reviewed for completeness. Sixty one percent (n = 73) of campers and parents handed in completed questionnaires on the first day of camp. The most common reason given for not participating was lack of interest on the part of the child. During the 2-week camp session children were pulled one at a time from regular camp activities and administered the SEIQOL-DW. Participants were allowed to choose a sugar free treat (soda, gum, or mints) for their participation.
During the one-week of pre-camp (when counselors are preparing for arrival of campers), counselors with diabetes who had previously been campers were approached and invited to participate in the study. Informed consent was obtained, and staff members were administered the SEIQoL-DW individually at their convenience. All eligible staff chose to participate (n = 17).
Two interviewers completed all 90 interviews. They were the first author who is a clinical psychologist, and the third author who is a medical student with an M.P.H. in health behavior. Both interviewers studied the SEIQoL-DW manual, role-played giving the SEIQoL-DW, and conferred about validity, boredom, and fatigue scoring.
Results
Participants
Consenters were compared to the total camp population for systematic differences. Results of a chi square test show no significant differences in gender. Results of an ANOVA show no significant differences in age, HbA1c, or duration of diabetes. Likewise, there were no significant differences between campers and counselors for quality of life total scores, gender, type of diabetes, age of diagnosis, number of daily injections, hypoglycemic episodes in the previous month, as well as number of sick days, hospitalizations, ketoacidosis episodes, and emergency room visits in the previous year.
On average, participants were 13 years old, came from 2-adult homes (74%) with 1 or 2 siblings. All but one participant were European American. Most did "well" or "very well" in school (69%), and had parents with at least 2 years education beyond high school. Participants had diabetes for an average of about 6 years and had been attending diabetes camp for an average of 4 years. All were on multiple injection regimens or insulin pumps (n = 29), and their average glycemic control was fair (mean HbA1c = 8.02). Participants had missed an average of 3 days of school in the last year due to their diabetes, and had experienced about 6 episodes of hypoglycemia in the previous month.
Table 1 Demographic and diabetes descriptive findings, n = 80 (numerical discrepancies reflect missing values)
Mean (SD)
Sex
Male 47.5% (n = 38)
Female 52.5% (n = 42)
Age 14.0 (3.4)
Age at diagnosis 7.1 (3.1)
Years since diagnosis 7.0 (4.3)
Most recent HbA1c 8.1 (1.8)
# Injections/day 2.2 (2.1)
# Children on CSII (n) 29
Diabetes sick days from school in last year 3.3 (5.4)
Diabetes hospitalizations in last year
0 79.5 % (n = 61)
1–2 18.2% (n = 15)
>2 2.2% (n = 2)
DKA episodes in last year
0 72.9% (n = 53)
1–2 15.3% (n = 12)
>2 11% (n = 10)
Hypoglycemic episodes in last month 6.2 (6.5)
Years at diabetes camp 4.6 (3.6)
# of siblings 1.8 (1.4)
Parent education (in years) 14.4 (2.6)
Parent marital status
Single/separated/divorced & living alone 16% (n = 12)
Single/separated/divorced & cohabitating 17% (n = 14)
Married 66% (n = 52)
School performance
Very poorly 1% (n = 1)
Poorly 4% (n = 4)
Ok 26% (n = 19)
Well 33% (n = 26)
Very well 36% (n = 30)
Data from ten children were deemed invalid due to interviewers' judgment that the participant was unable to understand the SEIQoL-DW task. For example, one child did not understand the concept of 'importance', and instead only rated domains in terms of his happiness with them. All children whose data were deemed invalid were under 12 years old, with a mean age of 9.25. The data from these ten children (1/3 of those children under 12) are deleted from the following results. Table 1 presents these descriptive findings.
Domain nomination
Of the 400 total domains nominated by the 80 participants with valid data, only 21 domains (5%) were nominated with the assistance of the standard list. These 21 were for the third, fourth, and fifth domains. Thus, every respondent could nominate at least 2 domains without suggestion, and only a handful needed help with the additional 3 domains. Table 2 displays the domains and the frequency with which they were nominated.
Table 2 SEIQoL-DW domains, with importance and satisfaction ratings
Domain Number of times domain was nominated Mean importance rating out of 100 Mean satisfaction rating out of 100
Family 76 27.9 79.8
Friends 62 18.0 76.8
Diabetes 49 27.7 75.0
School 46 17.7 65.5
Health 30 22.9 80.1
Hobbies 26 15.3 66.2
Sports 17 14.2 67.6
Camp 14 15.5 89.9
Religion 12 30.6 83.8
Special person, such as a teacher 11 19.8 79.8
Approach to life, or mental attitude 10 20.0 69.6
Significant other (boyfriend/girlfriend) 9 19.0 62.5
Golden rule (treating others as would like to be treated) 9 20.1 64.7
The basics (housing, food, safety) 9 17.8 71.5
Career/future 7 15.5 62.8
Pet 7 18.3 82.1
Work 5 11.5 69.5
Nature 1 14.5 70.0
The most frequently nominated domain was 'family'. Family was nominated by 76/80 respondents. Answers were coded 'family' if the participant used the terms 'family' or 'parents'. Reasons given tended to involve either instrumental support (e.g., they provide me with clothes and a place to live) or emotional support (they love me and I can go to them with problems). Many respondents stated that their families were important because they helped with diabetes, e.g., purchased diabetes supplies, drove them to doctor's appointments, cooked nutritious food, and helped with treatment decisions. Results of a bivariate correlation indicate a significant negative correlation between age of respondent and the importance rating given to the 'family' domain, r = -.34, *p < .01. There was no relationship between respondent age and 'family' satisfaction.
The second most frequently nominated domain was 'friends'. Respondents tended to refer to a group of friends, rather than an individual friend. Friends were generally valued for their emotional support, their companionship, and the participant's ability to relax and have fun with them. The ability to "be myself" and still be accepted by friends was a common theme. Results of a bivariate correlation indicate a significant positive correlation between age of respondent and the importance rating given to the 'friends' domain, r = .35, *p < .01. There was no relationship between respondent age and 'friends' satisfaction.
School was nominated by many respondents as an important life domain. School was deemed important for a variety of reasons. Some respondents stated that school was important because learning is important in its own right. Some stated that school performance was important to assure acceptance to a good college and have a good job, or because their school performance was important to their parents. Age was not related to 'school' importance or satisfaction.
The nomination of 'diabetes' as an important life domain was common. However, respondents' explanations for its nomination were varied. One type of response referred to taking proper care of diabetes in order to avoid negative consequences. These responses included things like eating well, self-monitoring blood glucose, keeping active, and taking injections on time to avoid medical complications, hospitalization, or death. Respondents who gave this sort of answer were fairly concrete and said things such as "I have to take my shots or I will end up in the hospital". Thirty four responses fell into this diabetes 'self-care behaviors' category. Another type of diabetes response referred to living well with diabetes. These responses included things like doing enjoyable activities despite diabetes, successfully negotiating diabetes treatment with parents, feeling proud of self when diabetes is controlled, receiving emotional support for diabetes, and keeping self, friends and family from worrying about diabetes. Respondents who gave this sort of answer provided more abstract explanations, and said things such as "I can't let diabetes stop me" and "It's important that people around me understand what it's like for me to have diabetes". Eleven responses were of this type. Results of an ANOVA with rationale for diabetes nomination (self care vs. living well with diabetes) as the independent variable, and age as the dependent variable revealed that those who provided 'self care behaviors' as a rationale were younger (M = 11.8 years) were than those who provided living well with diabetes as a rationale (M = 14.6 years) F (3, 40) = 2.88, p < .05. There were no group differences for age of diagnosis, number of daily injections, hypoglycemic episodes in the previous month, as well as number of sick days, hospitalizations, ketoacidosis episodes, and emergency room visits in the previous year. Among those who nominated 'diabetes' as a domain, age was not related to 'diabetes' satisfaction.
Respondents who nominated 'diabetes' as a domain were asked whether or not they would do so if they were in a non-diabetic environment such as school, as opposed to a diabetes summer camp. All respondents stated yes, they would nominate diabetes. However, some went on to say that they might not use the word 'diabetes' per se, and instead might use the word 'health'. Twenty four respondents did in fact nominate 'health' as a domain (but not diabetes). Explanations for 'health' focused on what might be considered more general wellness. Individuals who nominated 'health' said things like "I have to be healthy in order to do the things I enjoy", "I like staying fit", "you can't be happy without good health", and "when I don't feel well I'm in a bad mood". Six other respondents nominated both 'diabetes' and 'health' as separate domains. Results of a one-way ANOVA reveal that respondents who nominated 'diabetes' only were significantly younger (M = 12.9 years) than respondents who nominated 'health' only (M = 15.9 years) F (3, 75) = 4.53, p < .01. There were no group differences for age of diagnosis, number of daily injections, hypoglycemic episodes in the previous month, as well as number of sick days, hospitalizations, ketoacidosis episodes, and emergency room visits in the previous year. Among those who nominated 'health' as a domain, age was not related to 'health' satisfaction.
Domains nominated that are not on the standard list
Many domains were nominated by this sample that are not included in the standard list. They include 'diabetes', 'school', and 'camp', all of which clearly reflect that this was a sample of school aged young people attending a camp for children with diabetes. Some respondents nominated a 'special person' in their lives, such as a teacher or a coach. Other novel domains were nominated the explanations for which are less obvious. One domain involved 'mental attitude' and referred to taking the right approach to life and maintaining a positive outlook. Another involved 'the golden rule' and referred to treating others as one wants to be treated, with fairness and respect.
As stated above, the most frequently nominated domains were 'family', 'friends', 'diabetes', 'school', and 'health'. Domains ranked by importance were 'religion', 'family', 'diabetes', 'health', and 'the golden rule'. Domains ranked by satisfaction were 'camp', 'religion', 'pets', 'health', and 'family' and 'a special person' tied for fifth.
Quality of Life
Total SEIQoL-DW scores ranged from 34.9 – 97.7, M = 78.1, SD = 11.2. Normative data for children are not available. However, these values are similar to those of a small clinic sample of adolescents with type 1 diabetes that reported SEIQoL satisfaction data only [8]. This and other clinical samples (adults with cancer, with mental illness, transplant recipients) are shown in Table 3.
Table 3 Means and SDs for the SEIQoL-DW for the study and comparison samples
Sample Mean SD
Youth with diabetes 78.1 11.2
Adolescents with diabetes (satisfaction ratings only) [8] 75.3 N/A
Adult HIV/AIDS patients [12] 58.4 21.59
Adult community serious mental illness [15] 69.04 24.58
Adult advanced cancer patients [26] 50.9 17.8
Adult stem cell transplant recipients [19] 63.21 17.55
Discussion
The purpose of this study was to explore the individual QOL domains of youth with diabetes. Consistent with previous findings [8] results indicate that life domains nominated by individuals were thematic and shared many common characteristics, but varied substantially across respondents. Moreover, even when different respondents nominated identical life domains, their rationales for the importance of those domains varied. These findings underscore the personal nature of QOL, and highlight the benefit of allowing individuals to express their views of the life domains that determine it.
The young people in this sample nominated nearly all the life domains that are offered on the SEIQoL-DW standard list (with the exception of finances). They also went on to nominate additional domains, notably what we have termed 'mental attitude' and 'the golden rule'. These domains are some of the more fundamental aspects of quality of life but are not typically nominated in adult samples. Their nomination raises interesting questions. It is possible that youth are more concerned with these life domains than adults. This may be particularly true for children at overnight summer camp where community living and group cooperation is fundamental and continually reinforced. It is also possible that people with diabetes are more concerned with these life domains than their non-diabetic counterparts. Perhaps these respondents, who have experienced a major negative life event with their diabetes diagnosis and may also have suffered teasing or rejection due to this diagnosis, are more sensitive to issues of positive thinking and treating others with respect. Because this was an uncontrolled study, these are, of course, hypotheses that can only be tested with further investigation of controls.
Nearly all respondents nominated a domain that reflected physical status. Younger respondents (who were on average 12 years old) were more likely to focus specifically on diabetes, and emphasize the importance of diabetes self-care behaviors. These respondents stressed adherence to the diabetes treatment regimen in order to avoid medical complications. Older respondents (who were on average 15 years old) were more likely to focus on general health and emphasize the need to live well despite the difficulties of diabetes. These age related data need to be interpreted cautiously due to small sample size, homogeneity of the respondents, and the cross sectional design of the study. The literature would benefit from further use of individual QOL measures with children and with chronic illness populations such as diabetes, in longitudinal designs. Nonetheless, these data do suggest a change in how diabetes is conceptualized during adolescence.
There are several possible explanations for these age differences. First, Piaget proposed that formal cognitive operations begin in adolescence. With formal operations, adolescents gain the ability to think about their own thinking, to imagine many possibilities, and to mentally generate possible outcomes and thus rely less on real objects and events. Abstract thought becomes possible. The observed shift in focus from the concrete to the abstract – from 'diabetes' to 'health' and from 'self-care behaviors' to 'living well' – may be a reflection of the cognitive development that occurs with formal operations. Studies have demonstrated a systematic progression of children's understanding of illness that corresponds to Piaget's framework [30,31]. Other research has shown that the growth of children's conceptualization of illness paralleled, but lagged behind, conceptual development of physical causality [32]. Indeed, cognitive development may explain some children under 12 were not able to comprehend the SEIQoL-DW instructions.
Second, as they go through adolescence, youth with diabetes may view their physical well being differently due to more extensive and broadened life experience. Older youth may realize that strict adherence to the medical regimen comes at a cost of an inflexible lifestyle, and may value quality of life over strict medical management. They may become more willing to make compromises in self-care in order to participate more fully in normal activities. They may also, for the first time, be in a position to make these compromises as parental control of day-to-day diabetes management wanes in adolescence. Third, this shift may reflect adolescents desire to fit in with peers, normalize their disease experience, and assimilate their illness. Viewing physical status in terms of health, rather than diabetes, and diabetes in terms of living well, rather than disease management behaviors, serves these functions.
This shift in diabetes conceptualization could serve to be adaptive, or conversely it may herald the poor self-care and decreased glycemic control that is often noted in adolescence and young adulthood. Wysocki, Hough, Ward and Green [33] found that adolescents with diabetes are at risk of various unfavorable behavioral and health outcomes and that adjustment to the disease during earlier adolescence may be a predictor of subsequent health-related behavior and health status. We did not find a relationship between glycemic control and specific life domains nominated; this could be a result of low statistical power or a true lack of relationship. Also, we did not measure psychological adjustment to diabetes, and it remains an empirical question whether the conceptual shift observed in the present study is related to adjustment, and if so, the direction of the relationship. Furthermore, this shift in itself may be less important than host variables such as health beliefs and social support. Perhaps for a well adjusted, well supported individual, the shift toward general health may indicate disease assimilation, where as in less adjusted, less supported adolescents, the shift away from diabetes may indicate a denial of the disease and a withdrawal from appropriate self-care.
In addition to differences in domain nomination, we also observed age effects for the importance assigned to domains. As would be expected, age was significantly positively associated with the reported importance of friends, and a significantly negatively associated with the reported importance of family. As young people grow older, the value they place on family and friends changes, and peers become increasingly important. These data are consistent with previous findings that children with diabetes find friends more helpful in diabetes management than many adults [34]. Interventions that include peers, or a 'diabetes buddy' may be complimentary to those that target the family. A clinician who knows what a patient values can use that information to build rapport and to promote healthy behaviors. For example, while only 12 respondents nominated religion as a domain, it was given a higher importance rating than any other domain. Asking "how would God want you to care for your diabetes?" may be more fruitful with these children than a discussion of, say, the benefits of glycemic control for sports performance.
These data should be interpreted cautiously for several reasons. First, they reflect a select sample of white, higher socioeconomic status, high academic achieving children, many of whom have had several years of diabetes camp experience. This group may nominate different life domains, and endorse a higher QOL, than children who come from more impoverished environments without disease specific psychosocial experiences. These findings should be viewed tentatively until findings are replicated with larger and more diverse samples, in longitudinal designs that employ controls.
Conclusions
This article reports age-related differences in health related quality of life domains in youth with type 1 diabetes. It was found that younger respondents nominated 'diabetes' as a domain and focused on 'self-care behaviors', whereas older respondents nominated 'health' and focused more on 'living well with diabetes'. Although limited by sample size and homogeneity, these findings point to age related differences that may help explain deteriorating glycemic control during adolescence. What is clear is that development into maturity is a difficult task made more difficult by diabetes, and that special attention must be given to this population. The Society for Adolescent Medicine [35] and the American Academy of Pediatrics [36] have both issued statements stressing the importance of transitional care from pediatrics to adult medicine for youth with special health care needs. Grey et al. [37] conclude that diabetes treatment teams need to pay attention to the psychosocial needs of all adolescent patients. As the medical management of youth with diabetes improves, so must the understanding of behavioral and psychosocial status. These data shed light on the quality of life domains valued by youth with diabetes.
Authors' contributions
JW conceived of the study, and was responsible for design, analysis, and manuscript preparation. GA assisted with data analysis, and manuscript preparation and revision. SL carried out many of the interviews, assisted with data recording, data entry, and study coordination.
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| 15385049 | PMC523859 | CC BY | 2021-01-04 16:38:12 | no | Health Qual Life Outcomes. 2004 Sep 22; 2:54 | utf-8 | Health Qual Life Outcomes | 2,004 | 10.1186/1477-7525-2-54 | oa_comm |
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Reprod HealthReproductive Health1742-4755BioMed Central London 1742-4755-1-41546181310.1186/1742-4755-1-4Case ReportIdiopathic isolated clitoromegaly: A report of two cases Copcu Eray 1ecopcu@adu.edu.trAktas Alper 2aaktas@msn.comSivrioglu Nazan 1nsivrioglu@adu.edu.trCopcu Ozgen 3copcu@mailcity.comOztan Yucel 4oztany@yahoo.com1 Plastic and Reconstructive Surgery Department, Medical Faculty, Adnan Menderes University, Aydin, TURKEY2 Plastic and Reconstructive Surgery Department, Samsun State Hospital, Samsun, Turkey3 Anesthesiology and Reanimation Department, Aydin State Hospital, Aydin, Turkey4 Plastic and Reconstructive Surgery Department, Ataturk Training and Research Hospital, Izmir, TURKEY2004 4 10 2004 1 4 4 17 6 2004 4 10 2004 Copyright © 2004 Copcu et al; licensee BioMed Central Ltd.2004Copcu 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
Clitoromegaly is a frequent congenital malformation, but acquired clitoral enlargement is relatively rare.
Methods
Two acquired clitoromegaly cases treated in Atatürk Training Hospital, Izmir, Turkey are presented.
Results
History from both patients revealed clitoromegaly over the last three years. Neither gynecological nor systemic abnormalities were detected in either patient. Karyotype analyses and hormonal tests were normal. Abdominal and gynaecological ultrasound did not show any cystic lesion or other abnormal finding. Computerized tomography scan of the adrenal glands was normal. Clitoroplasty with preservation of neurovascular pedicles was performed for the treatment of clitoromegaly.
Conclusion
The patients were diagnosed as "idiopathic isolated" clitoromegaly. To the best of our knowledge, there has been no detailed report about idiopathic clitoromegaly in the literature.
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Case reports
Two cases with clitoromegaly were treated in Atatürk Training Hospital, Izmir, Turkey.
A 22-year-old gravida 0 (case 1) and 19-year-old gravida 0 (case 2) presented with acquired clitoromegaly, leading to psychological distress. Histories taken from both patients revealed a gradually growing clitoris in the last three years, no history of drug abuse or family history of clitoromegaly and no clitoral irritation secondary to masturbation or other sexual functions. Case one had a phallus 20 mm in length that increased to 30 mm on arousal (Figure 1) and case two had a phallus 30 mm in length, which increased to 40 mm with arousal (Figure 2). Secondary sexual features were normal in both cases. Sexual hair was normal and there were no signs of hirsutism. The patients were not obese, weighing 65 and 68 kg, respectively. Neither patient had any sign of polycystic ovaries. No gynaecological or systemic abnormalities were detected in either patient. The only clinical finding was 'isolated clitoromegaly' on physical examination.
Figure 1 View of the Case 1.
Figure 2 View of the Case 2.
Karyotype analysis was done in both cases and reported as 46, XX. Results of routine laboratory tests were normal. In addition, serum electrolytes, oestradiol, sex hormone binding globulin (SHBG), testosterone, androstenedione, dehydroepiandrosterone sulphate (DHEA-S), follicule stimulating hormone (FSH), luteinizing hormone (LH), 17 hydroxy progesterone (17-OH-P), prolactin, adrenocorticotropic hormone (ACTH), cortisol, placental lactogen (PL), deoxycorticosterone, deoxycortisol 11, triiodothyronine (T3), thyroxine (T4), thyroid stimulating hormone (TSH), beta-human chorionic gonadotrophin (β-hCG), carcinoembryonic antigen (CEA) were measured before the operations and the results were normal. 17-ketosteroid output in 24-hour-urine specimen was normal in both patients. Abdominal and gynecological ultrasound did not show any cystic lesion or abnormal finding. Computed tomography scan of the adrenal glands was normal.
No abnormality suggestive of a possible relation to clitoromegaly was found in all laboratory and radiological tests.
Both patients underwent clitoroplasty with preservation of the neurovascular pedicles under general anesthesia. A traction suture of 3/0 nylon was placed in the glans of clitoris (Figure 3). An incision was made on the lateral phallus perpendicular to the axis of the clitoral shaft, and carried through a 270 degree semicircular arc to the base of the glans as described by Papageorgoiou et al [1]. Two longitudinal incisions were made lateral to the dorsal neurovascular bundle. Two crura were identified, clamped and the mid-body of the clitoris was resected. The base of the glans was sutured to the divided corpora with 4/0 vicryl, and proximal and distal ends of the corpora were closed with 4/0 vicryl. The skin was closed with 4/0 vicryl sutures as well. Histopathological examinations of the resected specimens showed "normal corporal tissue". There was no abnormal finding on microscopic examination of the specimen obtained from clitoral and submucosal tissue.
Figure 3 Traction of the clitoris per-operatively.
Patients were followed up for one year after the operation. There was no early or late post-operative complication. Sensation was normal and patients were satisfied with the aesthetical and functional results.
Discussion
Clitoromegaly is a frequently seen congenital malformation, but acquired clitoral enlargement is rarely detected [2]. A detailed history and physical examination are required for the evaluation of clitoral enlargement because clitoromegaly may result from a variety of conditions [3]. The causes of clitoromegaly can be classified into four groups; hormonal conditions, non-hormonal conditions, pseudoclitoromegaly and idiopathic clitoromegaly (Table 1).
Table 1 Classification of the clitoromegaly based on causative factors
Causative factors of clitoromegaly
A. Hormonal conditions
1. Endocrinopathies
2. Masculinizing tumors
3. Exposure to the androgens
4. Syndromes
B. Non-Hormonal conditions
1. Neurofibromatosis
2. Epidermoid cysts
3. Syndromes
4. Nevus
C. Pseudoclitoromegaly
D. Idiopathic
Endocrinopathies, masculinizing tumors, exposure to the androgens and various syndromes are the main hormonal causes of clitoromegaly. The most common cause is female pseudohermaphroditism secondary to congenital adrenal hyperplasia (CAH) or adrenogenital syndrome, caused by an enzyme defect in the normal pathway of steroid biosynthesis [4]. Virilization of the external genitalia may cause profound clitoromegaly but rarely causes formation of a true penile urethra. However, clitoromegaly may be accompanied by fusion of the labioscrotal folds and perineoscrotal hypospadias, and a persistence of the urogenital sinus closing the external opening of the vagina [5].
Bilateral hilus cell tumors of the ovary, steroid producing gonadal tumors, adrenal androgen-secreting carcinoma, Leydig cell tumor of the ovaries and metastatic carcinosarcoma of the urinary bladder have been reported to cause clitoromegaly [6-9].
Fetal exposure to danazol has been described as cause for clitoromegaly [10]. An interesting case was reported by Akcam and Topaloglu of clitoromegaly possibly following blood transfusion from an adult in a premature infant [11].
Among the non-hormonal conditions are neurofibromatosis (NF)[12], epidermoid cysts[3], various syndromes and nevus lipomatous cutaneous superficialis. The majority of clitoromegaly cases related to NF are congenital.
Clitoral cysts arise from epidermis displaced into the dermis or the subcutaneous tissue either during the prenatal period or after a trauma.
Various syndromes resulting from non-hormonal conditions may cause clitoromegaly. Kazlauskaite et al reported a case diagnosed as congenital generalized lipodystrophy (CGL) presenting with generalized body-fat loss, prominent musculature, hepatomegaly, clitoromegaly and mild hirsutism [13]. CGL is an autosomal recessive disorder characterized by severe metabolic derangement associated with the absence of subcutaneous adipose tissue and clitoromegaly. Turner syndrome (TS) is a chromosomal disorder in females and results from a partial or complete loss of an X chromosome. Abnormalities include short stature and gonadal dysgenesis. Haddad et al presented a case of clitoromegaly and TS [15]. Fraser syndrome is another rare cause of clitoromegaly [14].
Androgen insensitivity syndrome is a heterogeneous disorder with a wide spectrum of phenotypic abnormalities, ranging from a complete female phenotype to ambiguous forms that more closely resemble males. The primary abnormality is a defective androgen receptor protein due to mutation of the androgen receptor gene.
Nevus lipomatous cutaneous superficialis (NLCS) is a relatively rare condition characterized by groups of ectopic fat cells dispersed in various parts of the body [16] that may cause clitoromegaly when located on the clitoris.
Pseudohypertrophy of the clitoris has been reported in small girls due to masturbation: manipulations of the skin of prepuce leads to repeated mechanical trauma, which expands the prepuce and labia minora, thus imitating true clitoral enlargement [2].
The objectives of clitoroplasty are preservation of sexual arousal function and sensation, and cosmetic. Historically, until 1960s, clitoral hypertrophy was treated surgically by amputation (clitoridectomy)[4]. Surgical methods for correction of clitoral hypertrophy were first described in 1934 by Young, who performed an operation for clitoral reduction in a child with CAH [17]. Several clitoroplasty methods have been reported, but few describe preservation of dorsal and ventral neurovascular bundles in sexually mature women. Clitoroplasty with preservation of the neurovascular pedicle may be the optimal operative technique for the treatment of clitoromegaly.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
EC conceived the study and prepared the manuscript draft for submission. AA, NS, OC and YO did the literature search and participated in the preparation of the manuscript.
All authors read and approved the final manuscript.
Acknowledgements
Written informed consent was obtained from both patients
==== Refs
Papageorgiou T Hearns-Stokes R Peppas D Segars JH Clitoroplasty with preservation of neurovascular pedicles Obstet Gynecol 2000 96 821 823 11094221 10.1016/S0029-7844(00)01031-0
Horejsi J Acquired clitoral enlargement. Diagnosis and treatment Ann N Y Acad Sci 1997 816 369 372 9238289
Linck D Hayes MF Clitoral cyst as a cause of ambiguous genitalia Obstet Gynecol 2002 99 963 966 11975977 10.1016/S0029-7844(02)01967-1
Bellinger MF Ehrlich RM, Alter GJ Feminizing genitoplasty and vaginoplasty Reconstructive and Plastic Surgery of the External Genitelia 1999 1 Philadelphia, WB Saunders 263
Wilson JD Formation of sexual phenotypes The Endocrinologist 2003 13 205 207
Baramki TA Leddy AL Woodruff JD Bilateral hilus cell tumors of the ovary Obstet Gynecol 1983 62 128 131 6856214
Castelazo-Ayala L Zarate A Mac Gregor C Soria J Dominguez O Steroid production by gonadal tumors in male pseudo-hermaphroditism with isolated clitoromegaly. Biochemical studies in vivo Steroidologia 1971 2 138 142 4336062
Falsetti L Salinaro F Chiaramonte M Adrenal androgen-secreting carcinoma in a fertile woman Acta Eur Fertil 1995 26 117 121 9098472
Ichinohasama R Teshima S Kishi K Mukai K Tsunematsu R Ishii-Ohba H Shimosato Y Leydig cell tumor of the ovary associated with endometrial carcinoma and containing 17 beta-hydroxysteroid dehydrogenase Int J Gynecol Pathol 1989 8 64 71 2707954
Brunskill PJ The effects of fetal exposure to danazol Br J Obstet Gynaecol 1992 99 212 215 1606119
Akcam M Topaloglu A Extremely immature infant who developed clitoromegaly during the second month of her postnatal life probably due to frequent whole blood transfusion from an adult male Pediatr Int 2003 45 347 348 12828595
Yuksel H Odabasi AR Kafkas S Onur E Turgut M Clitoromegaly in type 2 neurofibromatosis: a case report and review of the literature Eur J Gynaecol Oncol 2003 24 447 451 14584669
Kazlauskaite R Santomauro AT Goldman J Silver K Snitker S Beamer BA Yen CJ Shuldiner AR Wajchenberg BL A case of congenital generalized lipodystrophy: metabolic effects of four dietary regimens. Lack of association of CGL with polymorphism in the lamin A/C Gene Clin Endocrinol (Oxf) 2001 54 412 414 11298098 10.1046/j.1365-2265.2001.1216c.x
Chattopadhyay A Kher AS Udwadia AD Sharma SV Bharucha BA Nicholson AD Fraser syndrome J Postgrad Med 1993 39 228 230 7996504
Haddad NG Vance GH Eugster EA Davis MM Kaefer M Turner syndrome (45x) with clitoromegaly J Urol 2003 170 1355 1356 14501769 10.1097/01.ju.0000085983.81063.3f
Hattori R Kubo T Yano K Tanemura A Yamaguchi Y Itami S Hosokawa K Nevus lipomatosus cutaneous superficialis of the clitoris Dermatol Surg 2003 29 1071 1072 12974709 10.1046/j.1524-4725.2003.29306.x
Young HH Genital abnormalities, hermaphroditism and related adrenal disease 1937 Baltimore, MD: Williams & Wilkins 103 105
| 15461813 | PMC523860 | CC BY | 2021-01-04 16:38:10 | no | Reprod Health. 2004 Oct 4; 1:4 | utf-8 | Reprod Health | 2,004 | 10.1186/1742-4755-1-4 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1552605610.1371/journal.pmed.0010008Research ArticleRespiratory MedicineChronic Obstructive Airways DiseaseImmunology and AllergyAn Immune Basis for Lung Parenchymal Destruction in Chronic Obstructive Pulmonary Disease and Emphysema Th1 Immune Cells in Human EmphysemaGrumelli Sandra
1
Corry David B
1
2
Song Li-Zhen
1
Song Ling
1
Green Linda
3
Huh Joseph
4
Hacken Joan
5
Espada Rafael
6
Bag Remzi
1
Lewis Dorothy E
2
Kheradmand Farrah
1
*1Department of Medicine, Section of Pulmonary and Critical Care, Baylor College of MedicineHouston, TexasUnited States of America2Department of Immunology, Baylor College of MedicineHouston, TexasUnited States of America3Department of Pathology, Michael E. DeBakey Veterans Affairs Medical CenterHouston, TexasUnited States of America4Department of Surgery, Michael E. DeBakey Veterans Affairs Medical CenterHouston, TexasUnited States of America5Department of Radiology, Michael E. DeBakey Veterans Affairs Medical CenterHouston, TexasUnited States of America6Department of Surgery, Baylor College of MedicineHouston, TexasUnited States of AmericaBarnes Peter J Academic EditorNational Heart and Lung InstituteUnited Kingdom
Competing Interests: The authors have declared that no competing interests exist.
Author Contributions: D. B. Corry, D. E. Lewis, and F. Kheradmand designed the study. S. Grumelli, L.-Z. Song, L. Green, L. Song, J. Hacken, and F. Kheradmand analyzed the data. J. Huh, R. Espada, R. Bag, and F. Kheradmand enrolled patients. D. B. Corry, D. E. Lewis, and F. Kheradmand contributed to writing the paper.
* To whom correspondence should be addressed. E-mail: farrahk@ bcm.tmc.edu10 2004 19 10 2004 1 1 e828 5 2004 2 8 2004 Copyright: © 2004 Grumelli 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.
Characterization of T Lymphocytes in Chronic Obstructive Pulmonary Disease
T Cells Cause Lung Damage in Emphysema
ABSTRACT
Background
Chronic obstructive pulmonary disease and emphysema are a frequent result of long-term smoking, but the exact mechanisms, specifically which types of cells are associated with the lung destruction, are unclear.
Methods and Findings
We studied different subsets of lymphocytes taken from portions of human lungs removed surgically to find out which lymphocytes were the most frequent, which cell-surface markers these lymphocytes expressed, and whether the lymphocytes secreted any specific factors that could be associated with disease. We found that loss of lung function in patients with chronic obstructive pulmonary disease and emphysema was associated with a high percentage of CD4+ and CD8+ T lymphocytes that expressed chemokine receptors CCR5 and CXCR3 (both markers of T helper 1 cells), but not CCR3 or CCR4 (markers of T helper 2 cells). Lung lymphocytes in patients with chronic obstructive pulmonary disease and emphysema secrete more interferon gamma—often associated with T helper 1 cells—and interferon-inducible protein 10 and monokine induced by interferon, both of which bind to CXCR3 and are involved in attracting T helper 1 cells. In response to interferon-inducible protein 10 and monokine induced by interferon, but not interferon gamma, lung macrophages secreted macrophage metalloelastase (matrix metalloproteinase-12), a potent elastin-degrading enzyme that causes tissue destruction and which has been linked to emphysema.
Conclusions
These data suggest that Th1 lymphoctytes in the lungs of people with smoking-related damage drive progression of emphysema through CXCR3 ligands, interferon-inducible protein 10, and monokine induced by interferon.
The underlying changes that cause smoking-related damage are unclear. This paper suggests that there is a skew towards increased T helper 1 lymphocytes, which may drive progression of this damage
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Introduction
Chronic inhalation of tobacco smoke causes progressive lung destruction in susceptible individuals, resulting in chronic obstructive pulmonary disease (COPD) and emphysema, two well-described clinical syndromes with poorly understood pathogenesis [1,2,3]. A role for T helper cells in the pathogenesis of obstructive lung disease has been established with asthma, where T helper 2 (Th2) cells are strongly linked to both human and experimental disease [4,5,6,7]. A potential role for T cells in COPD has also been suggested in several recent studies that show CD8+ T cells are increased in the lungs of people who smoke [8,9,10,11]. T cells cause tissue injury through their secreted products such as cytokines; in mice, overexpression of interleukin (IL)-13, a T cell cytokine that is strongly implicated in the pathogenesis of experimental asthma, resulted in increased production of proteases and enlargement of airspaces reminiscent of emphysema [12]. Further, airway limitation, another characteristic of human asthma, is clinically linked to an accelerated rate of loss of lung function in smoker individuals [13]. It has been suggested, therefore, that asthma and COPD may involve the same type of recruited inflammatory cells, differing only in their location within the lung [14].
Chemokines, their receptors, and cell adhesion molecules regulate migration of immune cells into inflamed tissue [15,16,17,18]. T helper 1 (Th1) cells have been shown to secrete interleukin 2 and interferon gamma (IFN-γ), and express a distinct repertoire of chemokine receptors such as CCR5 and CXCR3 [19,20,21]. In contrast, Th2 cells that are biased to produce IL-4 and IL-5 express mainly CCR4 and CCR3 [22,23,24,25]. Immunofluorescent analysis of airway mucosal biopsies in patients with asthma showed that most T cells co-express IL-4 and CCR4, but, in contrast, T cells in airways of patients with COPD and pulmonary sarcoidosis produce IFN-γ and express high levels of CXCR3, while lacking CCR4 expression [26]. In addition to T cells, a wide variety of other inflammatory cells have been shown to express distinct chemokine receptors that are critical for their homing, suggesting a universal mechanism for regulating immune responses. Interferon-inducible protein 10 (IP-10), monokine induced by interferon gamma (MIG), and interferon-inducible T cell alpha chemoattractant (I-TAC) are three known ligands for CXCR3 produced by normal and injured epithelial cells and T cells that are required for homing of Th1 cells [27,28,29]. In addition to regulation of chemotaxis and homing, other functions have been ascribed to chemokines, including modulation of T cell fate by direct effects on differentiating T cells, and regulation of proteolysis in blood monocytes [19,30].
In this study we determined the dominant T helper phenotype in lung samples from ex-smoker individuals with moderate to severe COPD and emphysema and control individuals with no evidence of smoking-related lung disease. Analysis of chemokine receptor expression on isolated peripheral lung lymphocytes from ex-smokers with COPD/emphysema indicated that both CD4 and CD8 T helper cells are strongly polarized to the Th1 phenotype compared to T cells isolated from lung tissue of normal individuals or individuals with non-smoking-related obstructive lung disease. The same cells spontaneously secreted more IFN-γ and CXCR3 receptor ligands MIG and IP-10 in the COPD and emphysema group than in the group without emphysema. Further, IP-10 and MIG, but not IFN-γ, upregulated macrophage metalloelastase (matrix metalloproteinase [MMP]-12) from isolated lung macrophages. Together, our findings reveal the strong association between COPD/emphysema- and Th1-driven adaptive immunity, suggesting a link to lung destruction mediated by IFN-γ, MIG, and IP-10.
Methods
Participants
Twenty-eight non-atopic ex-smoker individuals (see Table 1) undergoing medically necessary lung resection were serially entered into the study: ten individuals with no COPD and no evidence of emphysema (control group) and eighteen individuals (diseased group) with moderate to severe COPD and evidence of emphysema as determined by pulmonary function tests, high-resolution computed tomography (CT), or conventional CT scan. All participants were ex-smokers who had quit smoking for a mean (SD) of 7 (2) y and 4 (2) y in COPD/emphysema and control groups, respectively. COPD was diagnosed according to the criteria recommended by the National Institutes of Health/World Health Organization workshop summary [31]. Participants in the control and COPD/emphysema groups had similar (mean [SD] of 54 [6] and 45 [5], respectively) “pack-year” smoking histories, where smoking one pack of cigarettes per day each year is defined as one pack-year.
Table 1 Clinical and Demographic Characteristics of Participants
a p-Values are for the comparison of emphysema with control participants (Student's T test)
b Histological diagnoses included lipoma, papiloma, and benign scar
LVRS, lung volume reduction surgery; SE, Standard Error; percent FEV1 l/s, percent predicted FEV1 in liters/second; QT, the number of years since the individuals had stopped smoking
All participants were recruited from the surgical clinic at the Michael E. DeBakey Veterans Affairs Medical Center and the Methodist Hospital, and were undergoing lung resection for diagnostic or therapeutic purposes (Table 1). Study protocols were approved by the institutional review board for human studies, and informed consent was obtained from all participants. Participants had no history of allergy or asthma and had not received oral/systemic corticosteroids during the last 6 mo. At the time of study, all participants had been free of acute symptoms suggestive of upper or lower respiratory tract infection for the 6 wk preceding the study.
CT-Based Evaluation for Emphysema
High-resolution CT (two in emphysema group and two in control group) or conventional CT analysis was used to detect emphysema, characterized by the presence of areas of low attenuation contrasted with surrounding normal lung parenchyma [32,33]. CT scans were used by a radiologist to separate participants on the basis of the presence or the absence of any objective evidence for centrilobular, panacinar, or paraseptal emphysema with a detection limit of greater than 3-mm low attenuation density [34].
Isolation of Lung Lymphocytes
Lung lymphocytes were isolated by modifying established protocols, using a combination of mechanical fragmentation, enzyme digestion, and centrifugation procedures described previously [35,36,37]. Viable lymphocytes were separated from whole lung inflammatory cells (macrophages, eosinophils, and neutrophils) using an immunomagnetic positive separation technique (autoMACS, Miltenyi Biotec, Auburn, California, United States). Briefly, lung leukocytes were labeled with paramagnetic bead-conjugated anti-CD3, -CD19, and -CD56 to positively select T, B, and NK cells, according to the manufacturer's instructions. Each of the harvested cell populations was used directly for in vitro assays or was cryopreserved in aliquots of 1 × 107 cells for future analysis.
Antibodies
The following monoclonal antibodies were purchased from BD Biosciences Pharmingen (San Diego, California, United States): FITC-, Cy5-, and PE-conjugated anti-CD4, -CD8, -CD3, -CD14, -CD69, -CXCR3, -CCR3, -CCR4, and -CCR5. For enzyme-linked immunosorbent assay studies, anti-human antibodies to IFN-γ, IL-4, IP-10, MIG, I-TAC, and the appropriate secondary reagents were purchased from R&D Systems (Minneapolis, Minnesota, United States).
Quantification of Polarized Peripheral Blood and Lung Lymphocyte Subsets
Phenotypic characterization of T cells was done by two-color flow cytometry (Epic XL FL, Beckman Coulter, Allendale, New Jersey, United States) using combinations of the following monclonal antibodies: FITC-conjugated anti-CD4, -CD8, and -CD14; PE- and Cy5-conjugated anti-CCR4, -CCR3, -CCR5, and -CXCR3. Freshly isolated lung lymphocytes were resuspended to 1 × 107 cells/ml, and 50 μl of cells was incubated with antibodies to CD3 and CD4 or CD8.
Intracytoplasmic Cytokine Staining
Lung lymphocytes were cultured in the presence or absence of phorbol myristate acetate (PMA)/ionomycin and brefeldin A for 12 h. Cells were harvested, fixed with formaldehyde, permeabilized with saponin, and intracellularly labeled for IFN-γ and IL-4, in addition to staining for surface CD69, CD4, and CD8 according to the manufacturer's recommendations (Fastimmune, BD Biosciences Pharmingen).
In Vitro T Cell Culture and Cytokine Assay
Lung lymphocytes were isolated from surgical tissue and cultured in vitro in triplicate for 4 d. Supernatants were collected and stored at –80 °C for future analysis. Standard antibody-based enzyme-linked immunosorbent assay was used to measure supernatant concentrations of IP-10, MIG, IL-4, and IFN-γ according to the manufacturer's instructions (R&D Systems and BD Biosciences Pharmingen).
Detection of MMP12 by Western Blotting, and Real-Time PCR
Peripheral blood mononuclear cells and lung macrophages were isolated by positive selection using immunomagnetic beads conjugated with anti-CD14, and cultured in serum-free medium (RPMI, L-glutamine, and Pen/Strep) prior to overnight stimulation with 0, 50, 250, or 500 ng/ml of IFN-γ, IL-4, MIG, I-TAC, and IP-10. Supernatants were collected, and MMP12 was detected using anti-human MMP12 (R&D Systems) by Western blotting according to the manufacturer's instructions.
Total cellular RNA was extracted from CD14+ lung macrophages stimulated overnight with rIP-10 (500 ng/ml) in the presence or absence of blocking anti-CXCR3 antibodies (5 μg/ml, R&D Systems). Two-step real-time reverse transcription PCR was used to determine the relative expression of mRNA using the ABI Perkin Elmer Prism 5700 Sequence Detection System (Applied Biosystems, Foster City, California, United States) as described previously [38].
Immunostaining and Histopathology
Paraffin-embedded, and fresh-frozen lung sections (5 μm) were immunostained using monoclonal antibodies against human MMP12 (R&D Systems) or non-immune antisera by an immunoperoxidase protocol (Vectastain Elite, Vector Labs, Burlingame, California, United States) and counterstained with hematoxylin as recommended by the manufacturer.
Statistical Analysis
The Mann-Whitney test (non-parametric, two-tailed) and Student's T test (two-tailed) were used to compare differences between the two groups of subjects. p < 0.05 was considered statistically significant.
Results
Th1 Immune Bias of Peripheral Lung Lymphocytes in Emphysema
Inflammatory chemokines, cytokines, and their receptors are upregulated at sites of inflammation and play a key role in the recruitment of leukocytes to peripheral tissues in response to injury [17,39]. To detect Th1 polarization, we assessed lung lymphocytes for expression of CCR5 (a receptor for several Th1 chemokines) and CXCR3 (the receptor for IP-10, I-TAC, and MIG). We screened for the presence of Th2 cells by assessing T cell expression of CCR4—a receptor for eotaxin/CCL11, macrophage chemoattractant protein 3 (CCL7), and thymus- and activation-regulated chemokine (CCL17) [40,41]—and CCR3, a receptor for eotaxin and related chemokines. Flow cytometry revealed very low expression of CCR3 and CCR4 (1%–3%) in control (n = 10) and emphysema (n = 18) groups, and did not discriminate between these populations (Figure 1A and 1B; data not shown). These findings were in sharp contrast to the enhanced expression of both CCR5 and CXCR3, as shown in representative histograms (Figure 1A). These Th1-specific chemokine receptors were expressed prominently on lung lymphocytes from all participants, but their expression was significantly enhanced in the setting of emphysema (Figure 1A–1C). Further, both CD4 and CD8 T cells expressed CCR5 at the same level (Figure 1C). In contrast, we found highly variable expression (0.5%–30%) of CCR4, CXCR3, and CCR5 on peripheral blood lymphocytes isolated from the same participants, and this variation did not correlate with the presence of disease in either group (data not shown). Furthermore, we compared the lung lymphocyte CCR5 and CXCR3 profiles among the eight participants with emphysema alone (lung volume reduction surgery for emphysema; non-cancer) and ten participants with emphysema and accompanying cancer (lung resection for treatment of small peripheral cancer), and found that these two groups cannot be distinguished based on these indices (Figure 1D; data not shown).
Figure 1 Chemokine Receptor Expression on Peripheral Lung Lymphocytes
(A) Single color histograms showing expression of chemokine receptors CCR4, CCR5, and CXCR3 from representative control and emphysema participants.
(B) Pooled data from all participants (control, n = 10; emphysema, n = 18) showing percent (median ± SD) of total lung lymphocytes expressing CCR4 and CCR5.
(C) Pooled data from same participants showing percent (median ± SD) CCR5 expression on CD4 (top) and CD8 (middle) T cells, and CXCR3 expression on unfractionated T cells (bottom) from the same participant groups.
(D) Analysis of total lung lymphocyte chemokine receptor (median ± SD) profiles among participants with emphysema. Participants had either (1) lung volume reduction surgery for emphysema (non-cancer, n = 8) or (2) lung resection for treatment of small peripheral cancer (n = 10). Participants showed similar inflammatory indices as determined by CCR5 expression.
In (B) and (C), *, p < 0.001; †, p = 0.01; ‡, p = 0.02; ∫, p = 0.007 (Mann-Whitney test) for the comparison of emphysema and control groups.
Although human lung macrophages are not known to express CXCR3, we suspected based on the immunohistochemical localization of this chemokine receptor that CD14+ cells in the lungs of ex-smoker individuals with emphysema accounted for much of the total lung CXCR3+ immunoreactivity (Figure 2A; data not shown). To confirm this, we determined the percent of total lung cells expressing CD14 and CD11b—which are both markers of monocytes/macrophages—and CXCR3. We found that over 40% of CD14+ cells from participants with emphysema but not control participants were also positive for CXCR3 (Figure 2). In addition, there was a significant negative association between CXCR3 expression on lung T cells and the percent of predicted forced expiratory volume in 1 s (FEV1), based on an R2 goodness-of-fit statistic of 0.27 (Figure 2C; p = 0.0089, r = −0.52). Together, these data indicate that a strong type 1 bias is characteristic of the T cells isolated from the peripheral lung of participants with COPD and emphysema and that this immune phenotype correlates with the lung destruction that is characteristic of this disease. Further, we have shown for the first time, to our knowledge, that CXCR3 expression, a marker of Th1 inflammation, extends to lung monocytes and macrophages.
Figure 2 Expression of CXCR3 in Lungs of Control and Emphysematous Smoker Individuals
(A) Representative forward and side-scatter characteristics of whole lung cells from a participant with COPD and emphysema. Anti-CD11b PE-conjugated and anti-CD14 FITC-conjugated antibodies detect lung macrophages (middle), and histogram of mean fluorescence intensity showing anti-CXCR3-Cy5 and control antibodies (cIg) detects lung macrophages in the patient with emphysema.
(B) Pooled data from control individuals without (n = 5) and with (n = 8) emphysema. Columns are median, bars represent SD. *, p = 0.009 (Mann-Whitney test) for the comparison of emphysema and control participants.
(C) Negative association between CXCR3 expression on CD3+ T cells and FEV1 percentage predicted based on an R2 goodness-of-fit statistic of 0.27 (p = 0.0089, r = −0.52, n = 24).
IFN-γ, IP-10, and MIG But Not IL-4 Are Expressed by Lung Lymphocytes
We sought additional functional data to confirm the apparent Th1 bias of peripheral lung inflammatory cells isolated from ex-smoker individuals. Freshly isolated lung lymphocytes that were not otherwise manipulated secreted high levels of IFN-γ, MIG, and IP-10, with significantly greater secretion of both cytokines from lymphocytes of participants with emphysema (Figure 3A–3C). Interestingly, we could not detect appreciable amounts of I-TAC, another known ligand for CXCR3, in lung lymphocytes of control participants or those with emphysema (data not shown). Similar results were obtained using intracytoplasmic cytokine staining of the same cells (Figure 3D), in which PMA/ionomycin stimulation strongly induced IFN-γ production from CD69+/CD8+ lung lymphocytes. Surface staining for CD4 was not feasible with this protocol; however, the percentage of CD8−/IFN-γ+ cells was approximately equal to that of CD8+/IFN-γ+ cells (median [SD], 19[6] versus 16[4], respectively). Because total numbers of CD4+ and CD8+ T cells were approximately equivalent, this suggests that non-CD8+/IFN-γ+ cells are largely CD4+, and therefore Th1 cells. Finally, the typical Th2 cytokine, IL-4, was not detected in either group, as determined by enzyme-linked immunosorbent assay or intracytoplasmic cytokine staining (Figure 3E; data not shown), confirming the marked Th1 bias of the immune response that underlies smoking-related lung inflammation and emphysema.
Figure 3 IFN-γ, MIG, and IP-10 Production by Isolated Lung Lymphocytes
(A–C) Lung lymphocytes from control individuals and participants with emphysema were cultured without additional stimulation for 3 or 4 d and assessed for secretion of (A) IFN-γ, (B) MIG, and (C) IP-10 (control, n = 8; emphysema, n = 12). Columns are median, bars represent SD. *, p= 0.007; †, p = 0.01; ‡, p = 0.02 for the comparison of emphysema and control participants.
(D) The same cells from a representative ex-smoker individual with emphysema were either left unstimulated (No ST) or treated with PMA/ionomycin (PMA/I) for 24 h and assessed for surface CD8 and CD69 expression and the intracytoplasmic accumulation of IFN-γ by flow cytometry.
(E) Production of IL-4 by lung lymphocytes. Lung lymphocytes from a representative ex-smoker individual with emphysema were cultured for 24 h with or without PMA/ionomycin stimulation (PMA/I) and assessed for intracytoplasmic IL-4 and IFN-γ accumulation by flow cytometry.
IP-10 and MIG But Not IFN-γ Directly Upregulate MMP12 through CXCR3
Emphysema and irreversible airway limitation that is characteristic of chronic tobacco smoking are related to the destruction of elastin and the resulting loss of lung elastic recoil. Therefore, to be relevant to the pathogenesis of airway obstruction, type 1 inflammation must be shown to promote lung elastolysis. Because loss of elastin is regulated by proteinases [42], we next determined if expression of MMPs, in particular the elastases MMP9 and MMP12, was regulated by IP-10, MIG, and IFN-γ, the principal cytokines detected in emphysematous lung. Indeed, isolated peripheral lung macrophages, but not isolated blood monocytes, secreted MMP12 in response to IP-10 and MIG, but not IFN-γ (Figure 4A; data not shown). These findings reflect a specific receptor–ligand interaction because in the presence of a CXCR3 function-blocking antibody, IP-10 failed to induce MMP12 (Figure 4B). Furthermore, immunohistochemical studies revealed that lung macrophages of participants with emphysema, but not control participants, specifically express MMP12 (Figure 4C and 4D). Together, these findings indicate that Th1, but not Th2, cytokines and related chemokines are required for establishing the pro-elastolytic lung environment that underlies human emphysema.
Figure 4 Regulation of MMP12 by Type 1 Cytokines
(A) CD14+, lymphocyte-depleted lung leukocytes were cultured with and without the indicated amounts of recombinant human IP-10 and IFN-γ, and supernatants were assessed for the presence of MMP12 by Western blotting.
(B) Fold increase relative to unstimulated of MMP12 mRNA from lung macrophages stimulated without (–) and with (+) 500 ng/ml of IP-10 in the presence or absence of a function-blocking antibody to CXCR3 as determined by real-time PCR.
(C and D) Lung tissue from a participant with emphysema (C) shows strong immune staining for MMP12 localized to macrophages (arrows), and (D) shows lung tissue from a control participant without emphysema and with undetectable MMP12. The insets show a high-power view of lung macrophages staining positive (C) and negative (D) for MMP12 (×60) *, p = 0.04.
Discussion
In this investigation, we characterized T cells and lung macrophages isolated from emphysematous and non-emphysematous human lungs. Three principal findings emerge from our study. First, rather than being functionally diverse, as suggested by the heterogeneous nature of humans, lung T cells of ex-smoker individuals with emphysema are relatively homogeneous and characterized by a marked Th1 bias. Second, the principal Th1 chemokines, MIG and IP-10, are linked to a pro-elastolytic lung environment because these cytokines upregulate the elastase MMP12, which is associated with emphysema. Finally, we found no significant expression of Th2 chemokine receptors, such as CCR3 and CCR4, or IL-4 production in lung lymphocytes. Together, our findings demonstrate the role of the adaptive immune response in COPD and suggest a primary role for Th1 cells in controlling the main smoking-related physiologic and structural changes of the lung.
Upregulation of CCR5 and CXCR3 on T cells and accumulation of these cells in the lung periphery suggest that aberrant, unremitting pulmonary recruitment of these activated T cells is unique to people with smoking-related lung disease, despite cessation of exposure to the inciting agent, tobacco smoke. We showed that ex-smoker individuals without obstructive lung disease or emphysema have comparatively little Th1-biased inflammation in their lungs; thus, our findings reflect the inflammatory changes that are unique to the COPD microenvironment. Additionally, lung lymphocytes isolated from four lifelong non-smoker individuals with severe obstructive lung disease due to cystic fibrosis or bronchiolitis obliterans did not show a Th1 inflammatory bias of the lung (S. Grumelli, F. Kheradmand, D. B. Corry, unpublished data). This information confirmed our finding that the predominant Th1 bias in COPD/emphysema reflects the microenvironment unique to the lungs of ex-smoker individuals. The prevalence of asthma among people who smoke is currently not known, but in order to study COPD/emphysema in a population without other confounding variables, people who might have had asthma were excluded, and thus our findings are restricted to non-asthmatic individuals with emphysema.
Our use of T cell chemokine receptor expression analysis to determine recruitment of lung T cells is not without precedent. Analysis by immunohistochemistry of airway mucosa of people with atopic asthma after antigen challenge revealed that large numbers of CCR4+ and CCR8+ T cells express IL-4, and CCR4 expression was prominent in people with severe atopic dermatitis, which decreased upon abatement of disease activity [26,43]. Immunostaining of T cells in synovial fluid from individuals with rheumatoid arthritis showed that virtually all of the T cells associated with inflamed joints expressed CXCR3 and CCR5, representing significant enrichment compared to blood T cells from the same participants. Furthermore, previous studies of smoker individuals with COPD and normal lung function showed the presence of CD8+/CXCR3+ T cells in the airway epithelium and submucosa [44]. We extend these findings by showing CXCR3 expression on lung macrophages and CD4+ T cells in emphysema patients and the functional interplay between Th1-related chemokines and elastolytic MMPs.
In addition to detailing surface chemokine receptor expression, we have functionally confirmed the marked Th1 bias of peripheral lung T cells, demonstrating that either at rest or following stimulation, these cells secrete IFN-γ and not IL-4. Our findings therefore confirm the utility of chemokine receptor expression patterns in the initial assessment of T cell effector phenotype.
Destruction of lung parenchyma in emphysema is thought to occur through excessive proteolysis mediated by the elastin-degrading enzymes MMP2, MMP9, and MMP12 from the MMP family, and by neutrophil elastase from the serine proteinase family [45,46]. Cytokines and chemokines are substrates for MMPs, but they also regulate expression of MMPs under pathological conditions [47,48]. We have shown here that IP-10 and MIG, two chemokines that are secreted from lung lymphocytes of participants with emphysema, upregulate specifically MMP12 and thus favor a proteolytic microenvironment that facilitates lung destruction. Strengthening the association between lung macrophages and IP-10/MIG-dependent MMP12 secretion is the fact that we have demonstrated that in humans macrophages, like T cells, express CXCR3 and that this receptor is required for MMP12 secretion in response to IP-10/MIG stimulation. In addition to defining the predominant immune phenotype of emphysematous lung, these additional findings implicate the principal cell (macrophage), MMP (MMP12), and effector cytokines (IFN-γ, IP-10, and MIG) as likely underlying smoking-induced lung destruction. We have further shown that these enzymes may be regulated by proximal immune events driven by Th1 cells or Th1-associated cytokines. A question of major importance for future study is, therefore, the nature of the antigens and adjuvant factors that ultimately drive this inflammatory response.
Although this was an entirely human study, our findings show remarkable parallels with studies performed in mice. MMP12 deficiency has been shown to protect mice against emphysema after chronic exposure to cigarette smoke, implying that MMP12 may be the key proteinase in the development of emphysema in this species [49,50]. Studies from both humans and mice therefore firmly suggest the importance of MMP12 in the pathogenesis of emphysema. Interestingly, in addition to solubilizing elastin, MMP12 is the MMP most efficient at degrading α1-antitrypsin, the primary physiological inhibitor of human leukocyte elastase [51,52]. Thus, chemokine-induced upregulation of MMP12 may orchestrate lung matrix degradation both directly and indirectly through inactivation of α1-antitrypsin. The therapy of COPD and emphysema is currently limited to pharmacologic bronchodilation to relieve dyspnea, antibiotics for intercurrent respiratory tract infection, and vaccination against prominent respiratory pathogens. Aside from efforts to prevent smoking or encourage cessation, there exist no measures that prevent development of emphysema or treat the specific causes of airway obstruction. By providing insight into the immunopathogenesis of COPD, our findings provide genuine hope that future therapies capable of preventing or halting smoking-related lung disease may be possible.
Patient Summary
Background
Many people develop long-term lung problems after smoking, including a condition called emphysema. At the very end of the airways are tiny air sacs. In healthy people, the air sacs stretch and relax easily on breathing in and out. But in people with emphysema, the air sacs fill up with air but can't empty out properly, so air gets trapped, making breathing difficult. While the symptoms of emphysema can be treated, there are no treatments that can reverse the damage to the lung.
What Did the Researchers Find?
The researchers studied two groups of patients, all ex-smokers who had been admitted to a hospital to have part of their lung removed—some because of cancer, some for other reasons. The researchers studied the lung samples and looked to see exactly what type of immune cells the patients with emphysema had in their lungs and found that most of the immune cells were of one particular type. The researchers also showed that the immune cells could tell other lung cells to produce chemicals that can damage the lung.
What Does This Mean for Patients?
Lung damage in emphysema may not be caused directly by toxins in cigarette smoke. Instead, if you have emphysema, your body may react to the toxins and produce a special kind of immune cell that is key in causing the lung damage. So perhaps if doctors can find a way to change how this cell behaves, it might be possible to reduce or limit the lung damage. Obviously, not smoking, or stopping smoking, is the best way to prevent COPD or emphysema.
What Are the Problems with the Study?
The study is quite small, which means that the results may not be completely accurate; in particular, the study did not include detailed information from patients who had never smoked. So it is too soon to say for sure whether these special immune cells really are the link between smoking and lung damage in emphysema. Researchers will need to study many more patients with emphysema as well as people who have never smoked.
Where Can I Find More Information?
Two places to start are the patient Web pages of the following professional organizations.
American Association for Respiratory Care: http://www.yourlunghealth.org/diseases_conditions/copd/
The British Thoracic Society: http://www.brit-thoracic.org.uk/public_content.asp?pageid=9&catid=21&subcatid=177
We thank Dr. A. Clinton White for critical review of the manuscript, Mr. Jeff Scott for technical assistance with flow cytometry, Ms. Pamela Smithwick, Ms. Rose Baglia, clinical research coordinator Dr Michael Reardon, and all the individuals who generously participated in this study. This work was supported by grants from the National Heart Lung and Blood Institute (64061, 72419, 69585) and Baylor College of Medicine (AI 36211). The funding provided by the National Hearth Lung and Blood Institute made our study possible, but it had no impact on any other matters such as study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Citation: Grumelli S, Corry DB, Song LZ, Song L, Green L, et al. (2004) An immune basis for lung parenchymal destruction in chronic obstructive pulmonary disease and emphysema. PLoS Med 1(1): e8.
Abbreviations
COPDchronic obstructive pulmonary disease
CTcomputed tomography
FEV1forced expiratory volume in 1 s
ILinterleukin
INF-γinterferon gamma
IP-10interferon-inducible protein 10
I-TACinterferon-inducible T cell alpha chemoattractant
MIGmonokine induced by interferon
MMPmatrix metalloproteinase
PMAphorbol myristate acetate
Th1T helper 1
Th2T helper 2
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| 15526056 | PMC523885 | CC BY | 2021-01-05 10:37:59 | no | PLoS Med. 2004 Oct 19; 1(1):e8 | utf-8 | PLoS Med | 2,004 | 10.1371/journal.pmed.0010008 | oa_comm |
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CytojournalCytoJournal1742-6413BioMed Central London 1742-6413-1-11550070110.1186/1742-6413-1-1EditorialCytoJournal joins 'open access' philosophy Shidham Vinod B 1vshidham@mcw.eduCafaro Anthony 2acafaro@mcw.eduAtkinson Barbara F 3batkinson@kumc.edu1 Co-Editor-in-chief, CytoJournal, Associate Professor, Medical College of Wisconsin, Milwaukee, WI, USA2 Assistant editor, CytoJournal, Assistant Professor, Medical College of Wisconsin, Milwaukee, WI, USA3 Co-Editor-in-chief, CytoJournal, Executive Dean, Kansas University Medical Center, Kansas City, KS, USA2004 29 7 2004 1 1 1 8 7 2004 29 7 2004 Copyright © 2004 Shidham et al; licensee BioMed Central Ltd.2004Shidham 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.
Welcome to CytoJournal! We would like to introduce you to your journal, one that is run by and for the scientific cytopathology community with incontestable benefits of Open Access, and support from Cytopathology Foundation, Inc. CytoJournal is a peer-reviewed, PubMed indexed, online journal, publishing research in the field of cytopathology and related areas, with world wide free access. Authors submitting to CytoJournal retain the copyright to their hard earned work.
CytopathologycytojournalOpen AccessBioMed Centralcytopathology foundation
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Welcome to CytoJournal ! We would like to introduce you to your journal, one that is run by and for the scientific cytopathology community with incontestable benefits of Open Access . CytoJournal is a peer-reviewed cytopathology journal is owned and supported by Cytopathology Fondation, Inc. It is a PubMed indexed, online journal, publishing research in the field of cytopathology and related areas with world wide free access. Authors submitting to CytoJournal retain the copyright to their hard earned work.
Why CytoJournal is needed
One could argue whether we need more journals in cytopathology, but without a shadow of doubt there is a global need for greater access to scientific information in this field. As an Open Access journal CytoJournal will meet this need, by removing subscription barriers.
Communication in general has been revolutionized in the last decade. With the emergence of the internet, entire libraries of scientific information are potentially just a mouse click away. Open Access to quality controlled, scientific information to the general public and scientific community alike is extremely valuable for harvesting the fruits of hard work by academicians.
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The traditional model for journal publication has performed an admirable job of disseminating research and advancing science. Unfortunately, it neither can fully utilize recent technology nor extend its benefits to the scientific community and the general public. Principally, why should scientific information generated by academicians and published without charge, not be freely available? Giving away the copyrights to the original research reports and then paying for access of the same material is paradoxically anachronistic.
With the advent of the internet and image digitization, the time has come for the development and implementation of a new model – a model beneficial to the scientific community and general public, alike. The recent adoption of an Open Access model by the Public Library of Science (PLoS) [1] and its recognition by other scientific organizations, including the National Institute of Health (NIH), has generated significant community interest. This has provided impetus for the creation of new journals such as CytoJournal with increasing support to open access philosophy by some of the existing leading journals.
The benefits of an online journal can include rapid turnaround time, real time publication, significant cost savings, and a reduction in the environmental burden engendered in the production and disposal of a print publication. Presumably in the future, the majority of research publications will be of this type [2].
Free flow of scientific information is crucial for advancements in diagnosis and management of diseases in both the developed and developing world. Simply providing a conduit of information is not enough. There is one matter involving the human element that must be dealt with – peer review. We do not see a future where authors post their manuscripts on the web without peer-review. Science requires that publications be properly vetted (peer-reviewed) and experimental findings logically presented.
In brief, standards must be maintained! This critical role is played by peer review. Acting on behalf of the scientific community, it is peer review that helps the scientific community distinguish between legitimate scientific work and quackery [3-7]. Thus, to maintain the quality and confidence, peer review will continue to be the keystone of scientific publishing.
The peer-review process at CytoJournal combines the expertise of both professional editors, who are available to survey the broad landscape of cytopathology, and academic editors, who understand deeply the strengths and limitations of their specific area of research. Every article that is published in CytoJournal will be reviewed carefully by selected reviewers, in addition to evaluation by a managing/academic editor and professional editor, who work together throughout the editorial process. A summary of your peer review process is illustrated in Figure 1.
Figure 1 CytoJournal's online peer review process.
Definition of Open Access
CytoJournal's Open Access policy changes the way in which articles are published. First, all articles become freely and universally accessible online, and so an author's work can be read by anyone, free of charge. Second, the authors hold copyright for their work and grant anyone the right to reproduce and disseminate the article, provided that it is correctly cited and no errors are introduced [8]. Third, a copy of the full text of each Open Access article is permanently archived in an online repository separate from the journal. CytoJournal's articles are archived in PubMed Central [9], the US National Library of Medicine's full-text repository of life science literature, and also in repositories at the University of Potsdam [10] in Germany, at INIST [11] in France and in e-Depot, the National Library of the Netherlands' digital archive of all electronic publications [12].
Benefits of Open Access
Open Access has four broad benefits for science and the general public. First, authors are assured that their work is disseminated to the widest possible audience, given that there are no barriers to their work. This is accentuated by the authors being free to reproduce and distribute their work, for example by placing it on their institution's website. It has been suggested that free online articles are more highly cited because of their easier availability [13]. Second, the information available to researchers will not be limited by their library's budget, and the widespread availability of articles will enhance literature searching [14]. Third, the results of publicly funded research will be accessible to all taxpayers and not just those with access to a library with a subscription. As such, Open Access could help to increase public interest in, and support of, research. Note that this public accessibility may become a legal requirement in the USA if the proposed Public Access to Science Act is made law [15]. Fourth, a country's economy will not influence its scientists' ability to access articles because resource-poor countries (and institutions) will be able to read the same material as wealthier ones (although creating access to the internet is another matter) [16].
Open Access Publishing Model and Finance
Open Access facilitates the transformation of scientific literature from rows of printed journals on library shelves to an instantly searchable archive of data. Liberating scientific literature from the vestiges of paper publication introduces the potential of various opportunities such as navigating, integrating, mining, annotating, and mapping connections in the high-dimensional space of scientific knowledge.
To provide Open Access, CytoJournal will use a new business model. Our editorial expenses (managing peer review, providing editorial insight, and ensuring the highest production standards) will be supported by corporate sponsors through Cytopathology Foundation, Inc. and honorary pro bono services by the academicians (Figure 2). The publication cost for our publishers, BioMed Central, will be recovered by imposing a modest charge (currently US$ 525) to authors for each article accepted for publication after peer review. There is no charge for the submission of a manuscript and therefore, if the manuscript is submitted but not accepted for publication, the authors will not be charged.
Figure 2 Core Principles of 'CytoJournal' and 'Cytopathology-Foundation'
Our sponsors do not influence in any way the content of CytoJournal and it's editorial and publication decisions. However, they will be acknowledged and their links will be displayed on the home page of CytoJournal as a thank you note.
Fee Waivers
We understand that there are many scientists who might wish to publish in our journal but do not have access to grant funds or institutional support. For such authors, a decision can be made by the Editors-in-Chief to waive publication fees. Furthermore, the fee will automatically be waived for authors from institutes that are members of BioMed Central . We never want our publication charges to be a barrier to publication and are committed to publishing any manuscript that our editors and reviewers deem to be appropriate for the journal; we will treat the costs of handling these papers as a fundamental expense of running a high-quality journal through support from Cytopathology Foundation Inc.
Joining Forces
CytoJournal is your journal and you can lead the way. However, we have to face and overcome a few traditional obstacles. First, an unfamiliarity to the Open Access model. Second, lack of the benefits of an established "brand name" aura. Because of this, despite stringent standards and an extraordinary editorial team, CytoJournal may have an uphill task.
Private foundations with a commitment to science and education have contributed generously to the cause. Like any new business, Cytopathology Foundation Inc. needed to raise funds to cover our startup costs. Initial support from Cytopathology Foundation Inc. and the publisher, BioMed Central, has enabled us to launch CytoJournal. Other individuals and organizations have also provided generous and welcome support. The start-up support made it possible to assemble an outstanding editorial board and staff, who have accomplished an extraordinary feat of launching this new premiere journal in cytopathology.
We wish to thank and applaud the efforts and spirit of the pioneering authors who chose to send their articles to CytoJournal. In the end, it is the contributions by authors like you that will make CytoJournal a collective success. We encourage you to participate in the future of CytoJournal by reading, citing, submitting manuscript, sending any suggestions, and joining the panel of core reviewers.
Bookmark the home page of Cytojournal for your quick reference! You may also link CytoJournal web site or recommend its linking through various other web sites.
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| 15500701 | PMC524023 | CC BY | 2021-01-04 16:36:21 | no | Cytojournal. 2004 Jul 29; 1:1 | utf-8 | Cytojournal | 2,004 | 10.1186/1742-6413-1-1 | oa_comm |
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CytojournalCytoJournal1742-6413BioMed Central London 1742-6413-1-21550070210.1186/1742-6413-1-2ResearchOptimization of an immunostaining protocol for the rapid intraoperative evaluation of melanoma sentinel lymph node imprint smears with the 'MCW melanoma cocktail' Shidham Vinod B 1vshidham@mcw.eduKomorowski Richard 1rkomorow@mcw.eduMacias Virgilia 1vmacias@mcw.eduKaul Sushma 1skaul@mcw.eduDawson Glen 1gdawson@milw.dynacare.comDzwierzynski William W 2billd@mcw.edu1 Department of Pathology, Medical College of Wisconsin, Milwaukee, WI, USA2 Department of Plastic Surgery, Medical College of Wisconsin, Milwaukee, WI, USA2004 6 8 2004 1 2 2 9 7 2004 6 8 2004 Copyright © 2004 Shidham et al; licensee BioMed Central Ltd.2004Shidham 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 the management of cutaneous melanoma, it is desirable to complete the regional lymphadenectomy during the initial surgical procedure for wide excision of biopsy site and sentinel lymph node (SLN) biopsy. In this study, we optimized and evaluated a rapid 17 minutes immunostaining protocol. The discriminatory immunostaining pattern associated with the 'MCW Melanoma Cocktail' (mixture of Melan- A, MART- 1, and tyrosinase) facilitated the feasibility of intraoperative evaluation of imprint smears of SLNs for melanoma metastases.
Methods
Imprint smears of 51 lymph nodes from 25 cases (48 SLNs and 3 non-SLNs, 1 to 4 SLNs/case) of cutaneous melanoma were evaluated.
Results
Sixteen percent, 8/51 lymph nodes (28%, 7/25 cases) were positive for melanoma metastases in immunostained permanent sections with the 'MCW melanoma cocktail'. All of these melanoma metastases, except 1 SLN from 1 case, were also detected in rapidly immunostained wet-fixed and air-dried smears (rehydrated in saline and postfixed in alcoholic formalin). The cytomorphology was superior in air-dried smears, which were rehydrated in saline and postfixed in alcoholic formalin. Wet-fixed smears frequently showed air-drying artifacts, which lead to the focal loss of immunostaining. None of the 5 SLNs from 5 cases exhibiting capsular nevi showed a false positive result with immunostained imprint smears.
Conclusions
Melanoma metastases can be detected intraoperatively in both air-dried smears and wet-fixed smears immunostained with the MCW Melanoma cocktail. Air-dried smears rehydrated in saline and postfixed in alcoholic formalin provide superior results and many practical benefits.
ImmunocytochemistryMelanomaSentinel lymph nodeMCW melanoma cocktailMelan- AMART- 1TyrosinaseIntraoperative cytologyMicrometastasisLymphadenectomy
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Background
What is already known on this topic?
A rapid intraoperative evaluation of sentinel lymph nodes (SLNs) for melanoma metastases during the interval between the SLN biopsy and the wide excision of the melanoma biopsy site may eliminate the need of an additional surgery for completion of regional lymphadenectomy.
What this study adds?
Air-dried imprint smears which were postfixed in alcoholic formalin following saline rehydration were optimal for immunocytochemical evaluation with the 'MCW melanoma cocktail'. The rapid evaluation of imprint smears immunostained with the 'MCW melanoma cocktail' is reliable for the intraoperative evaluation of cutaneous melanoma SLNs for melanoma metastases.
The prevailing trend in the management of cutaneous melanoma supports the sentinel lymph node (SLN) biopsy as a standard of care [1-16], but a few authors regard it as controversial [17,18]. In a given case where the SLN biopsy is performed and is positive for melanoma metastases, it is usually followed by additional surgery for regional lymphadenectomy. A rapid intraoperative evaluation of SLNs for melanoma metastases during the interval between the SLN biopsy and the wide excision of the melanoma biopsy site may eliminate the need for an additional regional lymphadenectomy surgery. Previously evaluated approaches such as fluorodeoxyglucose-positron emission tomography [19,20], morphological evaluation of frozen sections [21-24], intraoperative morphological evaluation of imprint cytology [25,26], and immunostaining of frozen sections [27] are not sufficiently sensitive.
Imprint smears of lymph nodes can be prepared rapidly. When compared to frozen sectioning, imprint smears are more desirable due to lower cost, quicker process, avoidance of tissue loss in the cryostat, prevention of freezing artifact in the tissue, and the elimination of problems associated with cryo-sectioning of fatty lymph nodes. These advantages have resulted in a preference for imprint smears over frozen sections by many investigators for the evaluation of SLNs in breast carcinoma [28,29].
Although relatively specific, the morphological interpretation of imprint smears alone used for the evaluation of melanoma metastases in SLNs is not very sensitive [25]. This is predominantly because of the inherent limitations associated with morphological interpretation. Singly scattered cells of melanoma metastases in a sea of numerous other cells are difficult to differentiate from reactive histiocytes, endothelial cells, and other cells with morphology alone.
At the current time, frozen-section examination (with or without immunohistochemical evaluation) and the morphological evaluation of imprint cytology smears are the methods available for intraoperative evaluation of SLN in cutaneous melanoma. However, these studies have demonstrated relatively low sensitivity and specificity, discouraging the practical application [22-27].
Conventional immunomarkers such as the S-100 protein and HMB45 suffer a significant drawback because of interference by non-melanoma cells resulting in high signal to noise ratio [28]. Because of this, rapid and accurate intraoperative evaluation of SLN with immunostained imprint smears was not previously possible.
In our previous study, the 'MCW Melanoma Cocktail'- a mixture of monoclonal antibodies- MART-1 {1:500}, Melan- A {1:100}, and Tyrosinase {1:50} (Table 1) demonstrated a highly discriminatory immunostaining pattern [28]. This observation suggested the feasibility of rapid intraoperative evaluation by examining the imprint smears of SLNs immunostained with the cocktail [28-30]. In the current study, we have optimized a protocol for the rapid intraoperative immunostaining of SLN imprint smears from patients with cutaneous melanoma utilizing the 'MCW melanoma cocktail'. Our previous experience suggested that air-dried smears postfixed in alcoholic formalin after saline rehydration demonstrated optimal results for immunostaining [31]. In this study, in addition to air-dried smears we also evaluated wet-fixed smears for further confirmation.
Table 1 The composition of the 'MCW Melanoma Cocktail'¶
Marker Clone Source *Final Dilution in the cocktail
MART-1 M2-7C10 Signet Laboratories, Inc. Dedham, MA 1:500
Melan-A A103 Dako Corporation, Carpinteria, CA 1:100
Tyrosinase T311 Novocastra Laboratories Ltd Newcastle upon Tyne, UK 1:50
* Optimum dilution for each antibody was standardized individually for that batch of antibodies with the sections of known melanoma positive control. The standardized dilution was achieved as final titer in the cocktail by adding 20 μl MART-1, 100 μl Melan-A, and 200 μl Tyrosinase to 9.68 ml of DAKO Antibody diluent (Dako Corporation, Carpinteria, CA). ¶ Adopted from Shidham et al [28].
Material and methods
Patients
We prospectively studied 51 lymph nodes (48 SLNs and 3 non-SLNs) from 25 patients (range- 1–4 SLNs per patient, mean- 2 per patient) under an IRB approved protocol at Froedtert Memorial Lutheran Hospital / Medical College of Wisconsin, Milwaukee, WI. A standard surgical protocol was used to identify the SLN [32]. The SLNs were harvested and submitted fresh to pathology for intraoperative and permanent section evaluation.
Pathologic Examination (Figure 1)
Figure 1 Pathological evaluation of sentinel lymph nodes for melanoma metastases. Section number 2, 5, & 8- stained with H & E; 4- immunostained with `MCW melanoma cocktail'; 6- negative control; 1, 3, 7, & 9- unstained. Number of slices of SLN shown (a,b,c) is just for illustration and would vary according to the size of the lymph node. (FPTS, formalin-fixed paraffin-embedded tissue sections; H & E, hematoxylin and eosin stain)
For the evaluation of the maximum surface area of the lymph node and most of the capsular area, the lymph nodes were transected perpendicular to the long axis as thin (not thicker than 2 mm) cross sections. Two pairs of imprint smears (one test and one negative control in each pair) were made by gently touching the cut surfaces to glass slides without allowing the imprint to be smeared. One of the pairs (1 test and 1 negative control) was air-dried, rehydrated in saline, and post-fixed in 'alcoholic formalin' [31] (see video clips as Additional file 1 Higher resolution- (for high speed connection); or Additional file 2 Low resolution- (for low speed connection), the screen shots in PDF file are available as Additional file 3 Screenshots). The other pair was wet-fixed by immersing the imprint smears in 95% ethanol before drying. Fixed smears were rinsed with 95% ethanol and then immunostained with 'MCW melanoma cocktail' (Table 1) using a rapid immunostaining protocol (Table 2). This rapid protocol required 17 minutes. Additional time required for smear preparation, smear processing, and evaluation of immunostained imprint smears may vary depending on the number of slides controlled by some variables such as the size and the number of SLNs submitted for evaluation.
Table 2 Rapid immunostaining protocols.
Entirely manual Partially manual and with Autostainer†
1. Re-hydrate air- dried imprint smear with 0.9% saline- 15 seconds (slow~10 dips) 1. Re-hydrate air- dried imprint smear with 0.9% saline- 15 seconds (slow~10 dips)
2. Post-fix the re-hydrated smear in 'alcoholic formalin'*- 5 slow dips and then 1 minute 2. Post-fix the re-hydrated smear in 'alcoholic formalin'*- 5 slow dips and then 1 minute
3. Rinse the post-fixed smear with 95% ethanol: 5 dips 3. Rinse the post-fixed smear with 95% ethanol: 5 dips
4. Hydrate the smear in DW- 30 sec 4. 100% ethanol: 10 dips
5. 3% H2O2 in DW- 1 mt 5. 100% ethanol: 10 dips
6. Protein blocking solution- 1 mt 6. Methanol: 10 dips
7. 'MCW melanoma cocktail'**- 5 mt 7. 50%¶ H2O2inMethanol: 1 mt with agitation
8. Rinse in 0.2% Tween 20 in DW 8. Deionized water: 10 dips
9. HRP-linker Antibody***- 5 mt 9. Tris buffer (ph 7.6): 10 dips
10. Rinse in tap water 10. Place smear on Dako Autostainer which automatically applies-
11. Chromogen (DAB)- 3 mt a. Envision blocking Solution††- 1 mt
12. Rinse in tap water b. 'MCW melanoma cocktail'**- 5 mt
13. Azure B (Blue solution of Diff-Quik®)- 1 mt c. Envision+ Monoclonal HRP†††- 5 mt
14. Rinse in tap water d. Chromogen (DAB)- 3 mt
15. Harris Hematoxylin- 30 sec 11. Remove the smear(s) and proceed with the following steps
16. Rinse in tap water 12. Deionized water: 10 dips
17. Dehydrate in ascending concentration of ethanol 13. Azure B- (Blue solution of Diff-Quik®)- 1 mt
18. Clear in xylene 14. Rinse in tap water
19. Coverslip the smear with the mounting medium 15. Harris Hematoxylin- 30 sec
16. Rinse in tap water
17. Dehydrate in ascending concentration of ethanol
18. Clear in xylene
19. Coverslip the smear with the mounting medium
mt, minute; sec, seconds; DW- Distilled water *Alcohol formalin was prepared by adding 50 ml of formalin (38–40% formaldehyde) to 350 ml of 95% ethanol and 100 ml of distilled water [modified and simplified from [31]; **'MCW melanoma cocktail'- Mixture of Melan- A, MART-1, & tyrosinase [28]; *** PowerVision™ Poly-AP anti-Mouse IgG (ImmunoVision Technologies, Co; Daly City, CA); †DakoAutostainer; ††Dako Corporation, Carpinteria, CA; †††Dako Envision+ (Dako Corporation, Carpinteria, CA); ¶ 3% 10 volume Hydrogen peroxide, USP (Hydrox Laboratories, Elgin, IL, USA). Positive controls were prepared from unfixed fresh melanoma tumor, which was immunoreactive for each of the individual components of the cocktail. The cut surface of the tumor was scraped with one end of glass slide and the scraped material accumulated at the end of the slide was spread between two glass slides similar to the spreading of bone marrow smears [32]. The air-dried smears were processed similar to 'test' slides. They were rehydrated in saline (10 to 20 seconds) and postfixed in alcoholic formalin (1 minute) [30]. The post-fixed smears were rinsed in 95% ethanol and then dehydrated by taking the smears through absolute ethanol, cleared in xylene, and cover-slipped with mounting medium. The cover-slip of positive control was removed by keeping the slide in xylene overnight (for this reason a formal communication to pathology and immunochemistry lab at least 24 hours before the SLN surgery is required). After removing the coverslip the smear was passed through absolute ethanol, 95% ethanol, and then joined with the protocol for immunostaining mentioned above. These coverslipped smears of positive control could be archived at room temperature for long periods of time (personal experience). We have used such smears after removing the coverslip as positive controls up to 1 year later without loosing immunoreactivity for most of the commonly used immunomarkers.
The first imprint smears from each pair were used as a 'test' and were immunostained with the 'MCW melanoma cocktail' by rapid protocol. The second imprint smear was used as a 'negative control' and processed in the same manner as the test slide except that Dako diluent® was used in place of 'the cocktail'.
Numerous smears of positive controls (both air-dried and wet-fixed smears) were prepared previously from a melanoma tumor with a known immunoreactivity for each of the three components of 'the cocktail'. These smears were prepared by scraping the cut surface of the fresh melanoma tumor and spreading the scraped material between two slides as described previously [33]. The air-dried smears were fixed in alcoholic formalin after saline rehydration. Both smears (air-dried, saline rehydrated smears, post-fixed in alcoholic formalin and wet-smears fixed in 95% ethanol) were stored after processing them through ascending grades of alcohol and xylene, followed by mounting with a glass coverslip using mounting medium (Table 2).
Both air-dried and wet-fixed positive control smears were used during immunostaining for each batch of test smears by removing the coverslip following immersion of the slide in xylene for about 24 hours. This dissolves the mounting medium and separates the coverslip. After removal of the coverslip, the smears were put through absolute ethanol and then descending grades of ethanol to water to be combined with the respective step in the rapid immunostaining protocol (Table 2).
The immunostained imprint smears were evaluated for melanoma micrometastases. The test smears were compared with corresponding positive controls (air-dried versus wet-fixed). The wet-fixed test smear from a given SLN was compared with a respective air-dried test smear by evaluating the sharpness of immunostaining, morphological details of the immunostained tumor cells, frequency of staining of non-melanoma structures such as mast cells and erythrocytes, air-drying artifact, deterioration in the immunostaining of the cells with unequivocal features of tumor cells, and nonspecific background staining. The results were interpreted by pathologists as positive, indeterminate, or negative for melanoma metastases. For statistical analysis, indeterminate interpretations of immunostained imprint smears were considered negative. This was based on the clinical significance with reference to the intraoperative decision algorithm for the completion of regional lymphadenectomies in SLN positive cases.
After the preparation of imprint smears, the slices of SLNs were fixed in 10% formalin and processed for formalin-fixed paraffin-embedded tissue sectioning. These sections were evaluated according to the melanoma protocol (Figure 1) and immunostained by the avidin-biotin-peroxidase complex (ABC) method described previously [28].
Results
Wet-fixed smears were difficult to prepare without focal air-drying artifact (Figure 2, Table 3). This difficulty was due to the time required to transfer each of the SLN slices on the glass slide one by one and then immersing the slide (with some of the imprints already dried) in 95% ethanol for wet fixation. This was not a concern while preparing the air-dried smears, as all the imprints were ultimately dried before processing (see Additional files 1,2,&3). The turnaround time for processing, immunostaining, and evaluating the smears was approximately 28 (range, 24–37) minutes.
Figure 2 Comparison of cytomorphological features of immunostained, air-dried smears postfixed in alcoholic formalin after saline rehydration (ADS, 'a') versus wet-fixed smears fixed in 95% ethanol (WFS, 'b' through 'd'). The cytoplasmic immunostaining for the 'MCW melanoma cocktail' does not obscure the nuclei in 'a'. In contrast, immunostaining of shrunken cytoplasm around nuclei in wet-fixed smears obscures the nuclear details (arrows in 'b'). Air-drying artifact is present focally (arrows in 'c') with the presence of non-specific background staining (arrows in 'd').
Table 3 Comparison of air-dried versus wet-fixed imprint smears.
S.No. Feature Air-dried imprint smears Wet-fixed imprint smears
1 Ease of preparing imprint smears of SLNs Easy Challenging
2 Air-drying artifact Not applicable Frequent
3 Non-specific background staining Rare Frequent
4 Immunostaining of non-melanoma structures Rare Common
5 Ease of processing, handling, and transporting the smears Easy Difficult
6 Loss of immunoreactivity of melanoma tumor cells due to air-drying artifact Not applicable Possible with potential for false negativity.
7 Sharpness of immunostaining Present Present
8 Shrinkage artifacts Absent Frequent
9 Morphological details of immunostained smears Good Poor
10 Potential loss of sample material on slide during immersion of slide in the fixative Rare Frequent
The immunostained tumor cells of melanoma metastases demonstrated a high nuclear/cytoplasmic ratio. The immunostaining was non-granular and cytoplasmic. The cytoplasmic immunostaining pattern facilitated the evaluation of the nuclear details. The cell margins were usually well defined. Unlike the chromatin of mast cells, the nuclear chromatin was not clumped and did not resemble the chromatin of the lymphocytes in the background. Nucleoli were usually prominent (Figure 3).
Figure 3 Cytomorphological spectrum of tumor cells (arrows) of melanoma metastases from different cases in rapidly immunostained air-dried imprint smears with the 'MCW melanoma cocktail' after saline rehydration and postfixation in alcoholic formalin. The tumor cells are large with well defined borders and show high nuclear to cytoplasmic ratio with non-granular cytoplasmic staining with clear nuclear details. The nuclear chromatin does not resemble the chromatin of adjacent lymphocytes in the background.
Because of the brief peroxidase blocking step, the endogenous peroxidase could not be blocked entirely in some cases, leading to the staining of some non-melanoma cells such as mast cells. These were detectable in both test smears and negative control smears. The mast cells showed smaller round nuclei with clumped chromatin. This clumped chromatin was comparable to the nuclear chromatin of adjacent lymphocytes in the background. The staining was coarsely granular. The cell margins of mast cells were usually hazy and ill-defined (Figure 4).
Figure 4 Morphological spectrum of non-tumor structures in rapidly immunostained air-dried imprint smears with 'MCW melanoma cocktail' after saline rehydration and postfixation in alcoholic formalin. a through e: Mast cells (brown arrows) show low nuclear/cytoplasmic ratio with granular staining of cytoplasm and fuzzy cell borders. The nuclear chromatin is clumped and resembled the chromatin of lymphocytes in the background. f: Non-nucleated ill defined structures (black arrow). g & h: Cells with immunoreactive nucleus (blue arrow). Insets of both g & h- zoomed cells with unequivocally negative cytoplasm but with brown staining of nucleus.
Rarely some nuclei demonstrated brown staining (the cocktail immunostaining is cytoplasmic and is not nuclear). The cells with such brown stained nuclei were morphologically consistent with histiocytes (Figure 4f &4g). Unequivocal nuclear staining without cytoplasmic immunostaining should be interpreted as negative in immunostained imprint smears. Brown non-nucleated round to irregular material (probably erythrocytes with unblocked endogenous peroxidase) was observed in a few cases (Figure 4h).
The non-specific staining was relatively frequent in wet-fixed smears (versus alcoholic formalin fixed saline rehydrated air-dried smears) and in manually immunostained smears (versus smears immunostained with Autostainer). These structures were usually interpreted as negative with ease. However, this factor could increase the interpretation time for negative cases due to the distraction effect and could prolong the crucial turn around time for intraoperative consultation.
Seventeen percent (8 out of 48) lymph nodes (28%, 7/25 cases) were positive for melanoma metastases in immunostained permanent sections. All melanoma metastases, except 1 SLN from 1 case, were demonstrated in both wet-fixed and air-dried imprint smears immunostained with the rapid protocol (sensitivity 89% and specificity 100%). On a case by case basis, 86% (6/7) of positive cases showed metastases in imprint smears immunostained with the 'MCW melanoma cocktail'; and demonstrated a sensitivity of 86%, a specificity of 100%, a negative predictive value of 95%, and a positive predictive value of 100%.
Imprint smears, immunostained with the rapid protocol, showed unequivocal melanoma metastases in 1 SLN which was negative by immunohistochemical evaluation of permanent sections. This was one of the SLN from a case with two other unequivocally positive SLNs in permanent sections and rapid immunostained imprint smears. This unequivocal positivity with immunostained imprint smears alone underscored the sampling benefit with imprint cytology.
Two SLNs (from 2 patients) interpreted as negative for melanoma metastases by immunohistochemical evaluation of permanent sections, were interpreted as indeterminate with the rapid protocol in both wet-fixed and air-dried smears. After retrospective evaluation, the rare doubtful cells observed in immunostained imprint smears were consistent with mast cells (Figure 4 a through 4e).
In 2 SLNs from 2 other cases, some scattered cells with non-granular immunostaining but with small, inconspicuous nuclei were observed. These cells were not mast cells and were absent in negative controls. They were also present as scattered single cells in permanent sections immunostained with 'the cocktail'. They were interpreted as benign and negative.
Discussion
Metastases of melanoma tumor cells in SLN could be detected in imprint smears immunostained with the 'MCW melanoma cocktail'. The air-dried imprint smears from different SLNs were easier to prepare than wet-fixed smears. As reported previously, air-dried smears have numerous advantages [34]. Because of the shrinkage factor associated with wet-fixation, the cellular details are less distinct in wet-fixed smear as compared to air-dried smears. The wet-fixed smears frequently showed non-specific background staining. They also showed air-drying artifact, which frequently compromised the immunoreactivity, resulting in multifocal faint or false negative immunostaining (Table 3). Wet-fixed smears with a scant number of tumor cells may be translated into a false negative result because of air-drying artifacts.
Imprint smears (both air-dried and wet-fixed) immunostained with the 'MCW melanoma cocktail' showed excellent sensitivity and specificity (the indeterminate interpretations were equivalent to negative results). As compared to this, the alternative intraoperative approaches such as frozen-section alone [22], immunostaining of frozen sections with a cocktail of Melan- A, HMB-45, & tyrosinase [27], and the morphological evaluation of imprint smears alone [25,35] demonstrated relatively poor results. This is of practical significance. It facilitates the intraoperative decision to proceed with regional lymphadenectomy during the same anesthetic procedure.
Immunostained imprint smears unequivocally showed melanoma metastases in one SLN, but these melanoma metastases were not detected in permanent sections immunostained with 'the cocktail'. Two other SLNs from this case showed melanoma metastases in both immunostained permanent sections and imprint smears. This unequivocally positive result with immunostained imprint smears highlights the benefit of the enhanced sampling with imprint cytology.
Imprint smearing facilitates the sampling of two surfaces from each slice, except for the first and the last slice, as compared to only one surface of all slices by any sectioning method (Figure 1). In contrast to a sectioning method yielding 3–4 micron sections, which represent a tiny fraction of the lymph node slice, immunostained imprint smears facilitate the evaluation of the entire material sampled as an imprint on the glass slide from the cut surface of the lymph node.
The possibility of false positive results due to the cells of capsular nevi was disproved by the negativity of all immunostained imprint smears from 5 SLNs (5 cases) with capsular nevi. The cells in capsular melanocytic nevi located in the capsule and fibrous septa of lymph node did not exfoliate and adhere to slides during preparation of imprint smears. This appears to be due to the greater cohesiveness of the cells in capsular melanocytic nevi than the cells of malignant melanoma.
However, scattered cells with non-granular cytoplasmic brown staining which masked the small and inconspicuous nucleus were observed in 2 SLN of 2 cases. Such cells exhibiting benign morphology were also observed as scattered single cells in permanent sections immunostained with 'the cocktail'. These cells were interpreted as negative without significant challenge, but their exact nature could not be established. The possibility of singly scattered nevus cells was considered. Contrary to capsular nevus cells, such cells may be detached easily and picked up by the glass slide during the preparation of imprint smears. In some cases, they may cause an interpretation dilemma leading to indeterminate results even with permanent sections.
In 2 patients, 2 SLNs were interpreted as indeterminate with immunostained imprint smears. They were interpreted as negative by the immunohistochemical evaluation of permanent sections. Cytomorphologically, the rare doubtful cells present in immunostained imprint smears were consistent with mast cells. They were also present in the respective negative controls (Figure 4).
As endogenous peroxidase activity could not be blocked completely during the short endogenous peroxidase blocking step in the rapid protocol, non-melanoma cells such as mast cells may show brown staining in some cases. Familiarity with the morphological spectrum of immunostained tumor cells (Figure 3) and other non-specifically stained cells including mast cells (Figure 4) in immunostained imprint smears should prevent the indeterminate interpretation of these cells in future.
The positive control smears may be prepared from time to time utilizing fresh, unfixed melanoma tumors for long term availability. Alternatively, the smears of melanoma tumor cell lines immunoreactive to individual components of the cocktail may be used after processing and fixing similar to test smears. These smears may be dehydrated and coverslipped (Table 2). Coverslipped positive control smears could be archived at room temperature for extended time periods. Coverslips can be removed by immersing the slides in xylene (usually 24 hours) to dissolve the mounting medium and to loosen the glass coverslip from the slide. We have used such smears after removing the coverslip as positive controls up to 1 year after they were originally prepared without affecting immunoreactivity for most of the commonly used immunomarkers including the 'MCW melanoma cocktail' (personal experience). Since a positive control had to be processed in advance by removing the coverslip in xylene, a notice at least one day prior to the intraoperative evaluation was required routinely as a part of the protocol.
Imprint smears are easy and quick to make without incurring significant expense. They are faster than frozen sectioning and help prevent the loss of tissue associated with cryosectioning. Frozen-sectioning of lymph nodes is frequently problematic because of fat, either adjacent to or in the lymph node. These problems are circumvented with imprint smears, which would also prevent problems associated with the interpretation of final permanent sections of frozen tissue.
For billing and reimbursement purpose, the rapid intraoperative evaluation of immunostained imprint smears may be coded with existing CPT (Current Procedural Terminology) codes- 88329 for the intraoperative consultation, 88161 for the preparation and processing of the imprint smears, and 88342 for the immunostaining of the imprint smears with interpretation [36].
As a future prospect, a 'cocktail' of directly conjugated individual antibodies (with a peroxidase or similar indicator system) used for a one step immunostaining method resulting in a significant reduction in immunostaining time (up to 6 minutes) with fewer staining steps would simplify the procedure [37]. As discussed above, the rapid protocol may not block the endogenous peroxidase. Rapid blocking of endogenous peroxidase with specific inhibitors / blocking agents, without affecting the cytomorphology, could prevent the non-specific staining of mast cells. This would improve the interpretation speed and confidence by eliminating the distraction factor of non-specifically stained cells thus reducing the chances of indeterminate interpretations and simplify the learning curve.
In summary, air-dried imprint smears which were postfixed in alcoholic formalin following saline rehydration were optimal for immunocytochemical evaluation with the 'MCW melanoma cocktail'. Wet-fixed smears did not compromise the immunoreactivity of 'the cocktail', but they were difficult to prepare without air drying artifact and non-specific background staining. Capsular melanocytic nevi did not show false positive results. The rapid evaluation of imprint smears immunostained with the 'MCW melanoma cocktail' is reliable for the intraoperative evaluation of cutaneous melanoma SLNs for melanoma metastases.
List of abbreviations
ABC, avidin-biotin-peroxidase complex; DAB, Diaminobenzidine Hydrochloride; H&E, hematoxylin and eosin; MCW, Medical College of Wisconsin; SLNs, Sentinel Lymph Nodes.
Competing interests
None.
Authors' contributions
VS conceived, designed, carried out the entire study in addition to the standardization of MCW melanoma cocktail protocol and preparation of manuscript. RK participated in its design and coordination. GD performed the immunohistochemical staining including standardization of the MCW melanoma cocktail with VS and SK. WD organized the clinical participation including recruiting of cases and arranging patients consent. All authors read and approved the final manuscript.
Supplementary Material
Additional file 1
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Acknowledgements
Authors thank Aurora Kallenbach, HT(ASCP) and Jerome Jacobson, HT(ASCP) for their expert technical assistance in immunohistochemistry.
This study was supported by the Cancer Center Research Multidisciplinary Grant from the Medical College of Wisconsin, Milwaukee, WI and by the Armour family grant through Chicago Marathon. It was presented in part at The 51st Annual Scientific Meeting, American Society of Cytopathology, 7–12 November 2003, Orlando, FL.
Editors thank the academic editor
Santo V. Nicosia, MD, Professor & Chair, Dept of Pathology, University of South Florida Health Science Center, Tampa FL 33612 snicosia@hsc.usf.edu for organizing and completing the peer-review process for this manuscript.
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| 15500702 | PMC524024 | CC BY | 2021-01-04 16:36:21 | no | Cytojournal. 2004 Aug 6; 1:2 | utf-8 | Cytojournal | 2,004 | 10.1186/1742-6413-1-2 | oa_comm |
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Biomed Digit LibrBiomedical Digital Libraries1742-5581BioMed Central London 1742-5581-1-21550715810.1186/1742-5581-1-2ResearchA knowledgebase system to enhance scientific discovery: Telemakus Fuller Sherrilynne S 1sfuller@u.washington.eduRevere Debra 1drevere@u.washington.eduBugni Paul F 1pbugni@u.washington.eduMartin George M 2gmmartin@u.washington.edu1 Telemakus Research Program, Division of Biomedical & Health Informatics, University of Washington, Seattle, WA, USA2 Department of Pathology, School of Medicine, University of Washington, Seattle, WA, USA2004 21 9 2004 1 2 2 6 7 2004 21 9 2004 Copyright © 2004 Fuller et al; licensee BioMed Central Ltd.2004Fuller 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
With the rapid expansion of scientific research, the ability to effectively find or integrate new domain knowledge in the sciences is proving increasingly difficult. Efforts to improve and speed up scientific discovery are being explored on a number of fronts. However, much of this work is based on traditional search and retrieval approaches and the bibliographic citation presentation format remains unchanged.
Methods
Case study.
Results
The Telemakus KnowledgeBase System provides flexible new tools for creating knowledgebases to facilitate retrieval and review of scientific research reports. In formalizing the representation of the research methods and results of scientific reports, Telemakus offers a potential strategy to enhance the scientific discovery process. While other research has demonstrated that aggregating and analyzing research findings across domains augments knowledge discovery, the Telemakus system is unique in combining document surrogates with interactive concept maps of linked relationships across groups of research reports.
Conclusion
Based on how scientists conduct research and read the literature, the Telemakus KnowledgeBase System brings together three innovations in analyzing, displaying and summarizing research reports across a domain: (1) research report schema, a document surrogate of extracted research methods and findings presented in a consistent and structured schema format which mimics the research process itself and provides a high-level surrogate to facilitate searching and rapid review of retrieved documents; (2) research findings, used to index the documents, allowing searchers to request, for example, research studies which have studied the relationship between neoplasms and vitamin E; and (3) visual exploration interface of linked relationships for interactive querying of research findings across the knowledgebase and graphical displays of what is known as well as, through gaps in the map, what is yet to be tested. The rationale and system architecture are described and plans for the future are discussed.
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Background
An unfortunate consequence of specialization in the sciences is poor communication across research domains – which can hamper the knowledge discovery process. Research findings in one area may be pertinent to another, researchers may be unaware of relevant work by others that could be integrated into their work and important findings just outside a researcher's focus can be overlooked. Compounding this problem is the difficulty of keeping current with new research findings that continue to grow at an exponential rate.
Reliance on keywords and/or subject indexing to find relevant literature limits the researcher's ability to precisely search for and locate specific research findings. For example, a typical database query to locate all research articles reporting a statistically significant relationship between caloric restriction and cancer would retrieve articles reporting both concepts as represented by the indexing and keyword search – but not necessarily linked together as a research finding, with information regarding reported statistical significance of the finding, nor, perhaps most importantly, lacking representation of the linkages among the retrieved document sets.
This lack of "interactivity" among retrieved citations is a critical limitation of traditional search and retrieval systems. As stated by Swanson (1986) in his examination of "mutually isolated literatures:"
"Knowledge can be public, yet undiscovered, if independently created fragments are logically related but never retrieved, brought together, and interpreted [..] This essential incompleteness of search and retrieval therefore makes possible, and plausible, the existence of undiscovered public knowledge [1]."
In addition to this limitation of search and retrieval, there are questions about representing a set of documents: What format or display of the retrieval set most enhances users' ability to identify which documents need to be examined in more detail? How can users navigate across document sets (i.e., to explore linkages) to enhance the discovery process? The bibliographic citation format is used by virtually all bibliographic databases today to report the results of database searches. However, it does not provide a way for the user to quickly review retrieved results for research methods and findings or to quickly view the relationships among the documents in the document set. Abstracts, even structured abstracts, simply do not provide a format conducive to rapid review of retrieved citations. In fact, the bibliographic citation format itself has changed little for the past two hundred years – even though it does not present an accurate representation of either the research methods or the research findings in a document [2].
In spite of great improvements in document retrieval over the past twenty years, most information systems developed to promote scientific discovery (e.g., [3-6]), are based on traditional search and retrieval approaches and the tools for locating and inter-relating research methods and findings are imprecise. This is the impoverished state Nobel laureate economist Herbert Simon described in his oft-cited remark on information as a commodity: "What information consumes is rather obvious: it consumes the attention of its recipients. Hence, a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it" [7]. For researchers, such a poverty of attention can translate into delays in the progress of scientific discovery.
A comprehensive approach to these challenges is the goal of the Telemakus research program. Telemakus was named for the son of Odysseus who went searching for his father, the legendary Greek hero of Troy. Similarly, the Telemakus research program is developing approaches and tools for searching, knowledge discovery and mapping domain knowledge. The overall vision is to enhance the knowledge discovery process through retrieval, visual and interactive interfaces and tools. In close collaboration with researchers in the biology of aging, a working knowledgebase system has been designed to present aggregated citation information and research methods and findings for display in a conceptual schema.
The Telemakus KnowledgeBase System provides the user with both a macro- and micro-view of domain knowledge. The macro-view facilitates identification of patterns – both expected and unexpected occurrences of relationships among research concepts – and permits visualization and dynamic navigation of scientific domains. The resulting maps are analogous to citation mapping work done by Small [8] but, instead of citations, rely on reported research findings. The micro-view presents consistent and detailed document attributes including research methods and findings for each document in the database.
This article describes the theories underlying the Telemakus KnowledgeBase System, provides an overview of its implementation, reports initial user feedback and explores future directions. Telemakus system builds on prior research in the areas of: (1) schema theory, (2) concept representation and (3) information visualization.
Schema Theory
Schemas are generalized mental models that provide a guide for structuring the process of production and comprehension of texts: "...at the simplest level, a schema is a description of a complex object, situation, process or structure. It is a collection of knowledge related to the concept [9]." According to schema theory, we understand the world in terms of prototypical patterns: people capture global coherence or structure their knowledge of the world based on scripts, schemas and narratives in which are embedded a vast array of relationships, concepts and vocabulary words. Individuals not only think and store knowledge in terms of scripts, frames and schemas but they also produce texts this way. Schema theory originated in linguistics and cognitive psychology as a model for holistically representing texts; it is primarily concerned with the "glue" which holds texts together, i.e., grammatical markers that allow texts to be cohesive as well as coherent [10].
"The crucial fact is that the cognitive constraints on information processing which require the formation of semantic macro-structures and which organize acts and speech acts in global units, at the same time have social implications: they determine how individuals wish, decide, intend and plan, execute and control, "see" and understand their own and others' speaking and acting in the social context. Without them the individual would be lost among a myriad of detailed incoherent pieces of visual, actional and prepositional information [10]."
Research on the application of schema theory to scientific research includes the schematic representation of psychological reports [11], clinical trials [12,13] and, more recently, Dillon's work on the superstructure and predictability of text [14]. An elaboration and refinement of schemas are frames [15]. Like schemas, a frame is a data-structure for representing a stereotyped situation, a remembered framework to be adapted to fit reality by changing details as necessary. When one encounters a new situation (or makes a substantial change in one's view of a problem) one selects from a memory structure called a frame. "Attached to each frame are a number of kinds of information. Some of this information is about how to use the frame. Some of it is about what one can expect to happen next. Some is about what to do if expectations are not confirmed [15]." The example commonly used is entering a restaurant: If the tables have checkered tablecloths and paper napkin dispensers, we assume that the prices on the menu will be lower than at a restaurant with white linen tablecloths and napkins rolled around polished silverware.
Understanding a written text is a process of fitting it into a larger schema known to reader as part of their previous knowledge about the world. It is reasonable to expect that presenting written texts in familiar formats can enhance and potentially speed up an individual's ability to review and analyze large document sets rapidly.
Fuller [13] investigated the application of schema theory in the symbolic representation of full-text research reports to improve representation of research findings. She concluded that schema analysis offered promise for representing the document structure above the level of individual words and sentences and that such schemas, "...offer a means of writing precise computer programs in terms of the specific schema elements, based on the portions of the document where they are most likely to occur. [..] Schema theory appears to offer a paradigm or framework for indexing which provides a means of capturing both the intra-document (i.e., research design, methods and outcomes) and inter-document relationships. [..] It seems likely that the schema will prove effective as a means of improving the retrieval of documents both in terms of precision and relevance [13]."
The predictability provided by schemas also applies to a document's metastructure. For example, Dillon [16] has proposed a model of navigation in electronic environments which assumes that experienced users of information form schematic representations of a document that in part represent its layout and structure. The Telemakus system utilizes the inherent and predictable research report layout and structure to create schematic representations or surrogates of research studies with extracted representations of research environment, methods and outcomes [17,18].
A second core component of the Telemakus system is based on concept representation.
Concept Representation
Concept representation is an important component in accurately representing facts from the document. Characterizing the location of concepts in a scientific document can greatly facilitate accurate document representation.
Indexing a document – using a vocabulary or thesaurus of terms to represent the document – is a standard method employed to improve retrieval of relevant documents. Yet traditional approaches to indexing fall short of true document representation: reducing the words found in the abstract, title or full-text of the document may be suggestive of the content but are not truly representative of the methods and research findings. The indexing literature is replete with studies documenting interindexer inconsistency, even among experienced professionals using familiar well-documented systems [19]. Studies indicate that human indexers usually select the most frequently occurring words in a document, yet they will disagree on the terms used and the same indexer will use different terms to index the same document at different times [20]. Many current automated retrieval programs also rely on word frequency, thus equating frequency with importance for retrieval purposes, which may be a faulty assumption [21].
"The information retrieval (IR) problem can be described as a quest to find the set of relevant information objects (i.e., documents D) corresponding to a given information need, represented by a query Q. The assumption is that the query Q is a good description of the information need N. An often used premise in IR is the following: if a given document D is about the request Q, then there is a high likelihood that D will be relevant with respect to the associated information need. Thus the information retrieval problem is reduced to deciding the aboutness relation between documents and queries [22]."
Another problem with current indexing practice lies in the way the unique structure of the information elements in the document is obscured. Scientific research reports have a highly predictable structure, with an introduction, methods, results and conclusion. Concepts mentioned in the introduction or conclusion section of a scientific article may not be the primary focus of the research described within the document. For example, the Introduction may include discussion of research among several animal models whereas the target of the research study itself is a specific breed of mouse. However, current indexing processes (whether human or automated) rarely discriminate between locations of concepts in the document for indexing purposes. In addition, index terms do not represent the connections between the various elements in the document; thus, a significant amount of critical information for the scientist is lost.
For example, it is not possible to unambiguously retrieve citations from PubMed® or any other bibliographic database today that will answer the question: "Has anyone ever published data that supports a connection between cancer and caloric restriction? If so, what was the intervention, what type of experiments were done and what were the findings?" A successful response to a query of this type is extremely difficult or impossible in traditional information retrieval systems because: " [..] conventional IR systems that employ isolated term assignments seem inadequate for queries which are specific and empirical in nature. If, on the other hand, retrieval systems provide a link to represent the relationships between the variables of interest as reported in the documents, queries [..] would be better answered. That is, precision might be enhanced for specific and empirical queries when the relationships between the index terms were specified in retrieval systems [23]."
In other words, the researcher asking the questions above can retrieve a set of citations that contain both topics but still must go through the full-text of each document to determine if the research specifically answers the question.
Several research studies have explored the utility of relationships captured from data tables and figures in scientific research studies. Fuller, et. al. [24] described the application of the relationship analysis process for quality filtering of the scientific literature and found it compared favorably with other measures of quality, including the Science Citation Index Impact Factor. Weiner, et. al. [25,26] applied relationship analysis and a mapping method to represent research findings from a database of cancer studies and found they could identify directions for new research studies. And Yamaguchi, et. al. [27] studied the relative importance of quantitative ideas as expressed in sentences in the text of the Results sections of research reports and in the data tables and concluded that the text ideas were more difficult to find and extract and were found to be less important when compared with ideas derived from the data tables.
The importance of data tables for expert decision-making was underscored by Malogolowkin, et. al. who found that cancer researchers rely on ideas presented in numerical displays in published research studies for much of their design of new research protocols [28]. Malogolowkin, et. al. concluded that innovative aspects of the design can be traced and better understood by mapping the numeric relationships [28].
Oh [23,29,30] investigated the utility of empirical variables and their associated statistical relationships in document representation and retrieval and designed an empirical fact retrieval system (EMFRS). Results of the evaluation indicated that the EMFRS generally outperformed the traditional retrieval system in terms of precision, search effort and measures of user satisfaction.
Identifying semantic relationships in text involves looking for certain linguistic patterns in the text that indicate the presence of a particular relationship (or research finding) using pattern-matching to identify the segments of the text or the parts of the sentence that match with each pattern: "If semantic relationships can be identified accurately in the text, retrieval results can be improved by eliminating documents containing the required concepts but not the desired relationships between the concepts [31]."
The third component of the Telemakus system is based on visual mapping of reported research findings.
Mapping Inter- and Intra-document Relationships
As previously mentioned, indexing strategies rely on "isolated term assignments." This approach leads to the loss of two important sources of information: (1) intra-document information, i.e., the research relationships studied and tested and (2) cross-document information, which captures and links research relationships across groups of documents or domains. This loss is the result of breaking apart the context of clearly linked in research findings in the data tables and figures, concepts typically linked together (the x-y axes of the tables and graphs).
Once the research relationships have been extracted, concept mapping, a means of spatially representing knowledge in a visual format, provides a potential solution to the challenge of maintaining the inter-relationships between documents and reported research findings. Spatial representations can assist in understanding conceptual relationships across a domain. They can also assist in identifying previously overlooked potential research connections.
Numerous approaches to visualizing an information retrieval space have been explored (e.g., [8,32,33]), all seeking to capitalize on the natural strength people have for rapid visual pattern recognition. Most mapping work to date has focused on similarity between journal articles using citation analysis [8], co-occurrence or co-classification using keywords, topics, or classification schemes [34-36], or journal citation patterns [37]. Latent semantic analysis (LSA) has been used to map co-occurrence of words (or authors) in titles, abstracts, or full-text sources [33] and domain maps have been used to visualize author co-citation analysis [32].
While a review of information visualization strategies is outside the scope of this paper, there is a growing body of work related to mapping metaphors and visualizing large document sets and database search results to provide the user with the ability to visualize relationships among documents and their contents [38,39]. In addition, several tools have been developed that graphically present inter-document relationships, most commonly using some form of link-node diagram [40,41].
Concept mapping represents knowledge graphically through networks of ideas. Such networks consist of nodes (points) and links (arcs/edges). Nodes represent concepts and links represent connections between concepts. Concept mapping has been used for a variety of purposes, including to communicate complicated ideas and, as in the Telemakus system, to demonstrate connections among research findings.
Methods
How might one apply the theories previously described in developing a comprehensive "real world" information retrieval and knowledge discovery system? As reviewed in the previous section, the Telemakus system is built on and extends prior research in the areas of concept representation, schema theory and information visualization. Work on components of what has become the Telemakus system has been underway for many years with a particular emphasis on the importance and utility of relationships extracted from data tables and figures [24,42-44]. Fuller [12,13] identified key objective elements important in representing a clinical research report and developed a schematic representation. The clinical trials schema has been adapted for representing basic sciences research reports in the Telemakus system.
Based on how scientists use and want to use the research literature, Telemakus brings together three innovations in analyzing, displaying and summarizing research reports across a domain:
1. Research Report Schema: Research methods and findings are extracted and presented in a consistent, coherent and structured schema format which mimics the research process itself and provides a high-level research report surrogate to facilitate searching as well as rapid review of retrieved documents.
2. Research Findings extracted from data tables and figures are used to index the documents, allowing searchers to request research studies which report a relationship between two concepts of interest.
3. Visual Exploration Interface provides a dynamic map of extracted research findings to graphically display what is known as well as, through gaps in the map, what is yet to be tested.
Knowledgebase Creation & Components
The Telemakus system consists of a database, research report schema and tools to create relationship maps among concepts across documents. The research report schema serves as a surrogate for the study, methods and research findings for each document as well as providing an interactive search interface. The schematic representations include standard bibliographic information (author, title, journal), information about the research design and methods (age, sex, number of subjects, pre-treatment and treatment regimen, organism and source of organism) and, most importantly, research findings derived from data tables and figures.
The elements extracted by the Telemakus system from full-text documents are listed in Table 1. There are 22 fields for each document, with 12 routinely obtained from PubMed. Of the remaining fields, entries to 4 are controlled by thesauri. Two fields, Authors and SourceOfOrganisms use customized thesauri developed specifically for the Telemakus system. Two additional fields, the ResearchFindings and Organism fields, use the Unified Medical Language System® (UMLS®) Metathesaurus® as the basis for creating a controlled vocabulary.
Table 1 Research report schema database fields
FieldName Source Comment Thesaurus?
RecordID system provided unique identifier
Author bibliographic database Y
Year bibliographic database
Title bibliographic database
AuthorAddress bibliographic database author's email address
Journal bibliographic database
Volume bibliographic database
Issue bibliographic database
Pages bibliographic database
Keywords bibliographic database subject headings
Abstract bibliographic database entire abstract
Tables Figures document extracted captions & URLs of tables/figures
ResearchFindings document extracted pairs of related concepts Y (UMLS)
Organism document extracted type of experimental subject Y (UMLS)
Age document extracted
Sex document extracted
Pre-Treatment Characteristics document extracted
NumberOfSubjects document extracted
TreatmentRegimen document extracted
SourceOfOrganisms document extracted Y
AbstractURL bibliographic database
FullTextURL bibliographic database URL of online article
The UMLS Metathesaurus is a rich database of information on concepts that appear in one or more of a number of different controlled vocabularies and classifications used in the field of biomedicine. It provides a uniform, integrated distribution format of over 95 biomedical vocabularies and classifications and contains syntactic information. All Metathesaurus concepts are assigned to specific types or categories – e.g., "Disease or Syndrome," "Virus" – and the Semantic Network contains information about the permissible relationships among these types – e.g., "Virus" causes "Disease or Syndrome" [45]. The 2004 edition of the UMLS Metathesaurus includes over 1 million biomedical concepts and 2.8 million concept names in its source vocabularies [46].
The thesauri are reviewed (curated by expert indexers) in order to create a consistent controlled vocabulary structure. As indicated in Table 1, research concepts and organism type thesauri are derived from the UMLS. As new concepts are identified from the document's data tables and figures, the UMLS is used to identify preferred terms that are added to the controlled vocabulary database. In addition to the preferred term, its synonyms, semantic type, broader and narrower terms and Unique Identifier are captured. The UMLS provides a very powerful approach to rapidly creating a robust scientific thesaurus in support of consistent and precise searching. Further, the semantic type descriptors for each concept and semantic network may offer some interesting opportunities for intelligent searching and mapping of research findings and their relationships in the future.
At present, data extraction utilizes systems with both manual and automated processes. An evolving thesauri-building and revising approach are important components of the Telemakus system to ensure that vocabulary identification and management reflect the specialized needs of the knowledge domain as new research concepts are identified and reported.
The knowledgebase construction process begins with an Internet search of a bibliographic database (e.g., PubMed, Web of Science®, etc.). Database elements are extracted and verified against the relevant thesaurus. As new concepts are identified the UMLS is checked for the preferred term and it is added to the appropriate Telemakus thesaurus – along with synonyms, narrower and broader terms.
One of the key innovations in the Telemakus system is the use of the data tables and figures for locating the concepts studied (and tested) by the researchers. Concentrating on the legends from data tables and figures focuses the extraction process and reduces the background noise of the full-text document, making the process tractable. In general, the information content of data tables and figures can be broken into two types: "facts" and "findings." Facts include reporting experimental design and comparative characteristics of animals in the study group (e.g., weight, age, pre-existing conditions, etc.). Findings are the results of the study (the research findings). Research findings are extracted from each of the "findings" data tables in a process described in Figure 1.
Figure 1 Process for deriving research relationships from data tables
Table 2 provides a list of legends (the descriptions of content) from data tables and figures from a single research report and the end results of the extraction process. The legends are categorized into information content type (Fact or Research Finding), extracted concept relationships and concept relationships normalized (preferred terms) using the UMLS tools. In Table 2, the first two legends report "facts" (the experimental design and the composition of the diets of the research animals) while "findings" are reported in the remaining legends. The third column displays the noun phrases extracted from the legends which are then mapped to their corresponding UMLS preferred terms, as seen in the fourth column. When mapped, the term "dietary intake" maps to "energy intake" and "mammary gland carcinomas" maps to "mammary neoplasms." This provides a "controlled vocabulary" which enhances the consistency of retrieval from the knowledgebase.
Table 2 Information content type categorization and relationship concept candidates for a sample of table/figure legends Extracted from – Zhu Z, Haegele AD, Thompson HJ: Effect of caloric restriction on pre-malignant and malignant stages of mammary carcinogenesis. Carcinogenesis 1997, 18(5):1007–12
Table/Figure Legend Type Extracted Concept Relationships Concept Relationships (after Normalization using UMLS tools)
Table I. Sequence of events that comprised the experimental design FACT None none
Table II. Composition of diets FACT None none
Fig 1. Effect of caloric restriction on dietary intake, body weight gain and the ratio of cumulative body weight/cumulative diet intake. FINDING • dietary intake – caloric restriction
• body weight – caloric restriction • energy intake – caloric restriction
• body weight – caloric restriction
Table III. Effect of calorie restriction on the proportion of intraductal proliferations, ductal carcinoma in situ and carcinomas in mammary glands FINDING • intraductal proliferations – caloric restriction
• ductal carcinoma in situ – caloric restriction
• mammary gland carcinomas – caloric restriction • intraduct carcinoma of breast – caloric restriction
• mammary neoplasms – caloric restriction
Fig 2. Effect of calorie restriction on cumulative and final incidences of mammary carcinomas. FINDING • mammary carcinomas – caloric restriction • mammary neoplasms – caloric restriction
Fig 3. Percentage distribution of lesions in a dietary group that were: intraductal proliferations, ductal carcinoma in situ and adenocarcinoma. FINDING • lesions – dietary group
• dietary group – intraductal proliferations
• dietary group – ductal carcinoma in situ
• dietary group – adenocarcinoma • lesions – energy intake
• intraduct carcinoma of breast – energy intake
• adenocarcinoma – energy intake
Fig 4. Effect of caloric restriction on urinary excretion of immunoreactive cortical steroid. FINDING • immunoreactive cortical steroid – caloric restriction • adrenal cortex hormones – caloric restriction
A current focus is the application of natural language processing (NLP) techniques to assist in the automation of concept extraction process. MetaMap, a program developed by the National Library of Medicine®, (NLM®) is being tested as a means of automatically parsing the legends from the data tables and figures to identify preferred UMLS concepts for addition to the Telemakus thesauri. MetaMap maps arbitrary text to concepts in the UMLS Metathesaurus; or, equivalently, it discovers Metathesaurus concepts in text. With this software, text is processed through a series of modules. First it is parsed into components including sentences, paragraphs, phrases, lexical elements and tokens. Variants are generated from the resulting phrases. Candidate concepts from the UMLS Metathesaurus are retrieved and evaluated against the phrases. The best of the candidates are organized into a final mapping in such a way as to best cover the text [47].
Telemakus KnowledgeBase System Architecture
The Telemakus system architecture centers on: a relational database; a set of tools used to populate the knowledgebase with data extracted from bibliographic databases and full-text research reports; and several server side tools and programs responsible for delivering the content of the database to the public via the WWW. The entire system is built from open-source components, leveraging standard protocols and tools whenever possible.
The document processing system is initiated by an analyst who runs, reviews and edits as necessary extractions from the document being processed. It currently consists of a number of discrete phases to download, extract and analyze each document. These services are built primarily in Java running behind Tomcat and Apache and accessed by the analyst through the browser.
For the public Telemakus website interface, a number of open-source solutions have been selected and configured. An Apache web server intercepts all requests and delegates them to surrogate processes dedicated to each respective task. For requests to display the data from the database, the request is delegated to Zope, a content management service, for responding to the user's request. This typically includes running SQL queries against a PostgreSQL database and rendering the results in the conceptual schema that serves as a surrogate for each document. For tasks beyond simple queries and HTML requests, a Java Servlet™ is employed. As plain HTML is insufficient to effectively display and interact with the relationship map, a Java™ applet, TouchGraph, is used.
TouchGraph is an open-source concept-mapping tool for creating and navigating links between information sources. The tool was chosen for Telemakus because of its flexibility, customizing capabilities, high quality source code and compatibility with most browsers and operating systems (OS). The TouchGraph visualization package serializes maps to and from XML. By using Java, HTTP and XML, TouchGraph makes it easy to dynamically feed content to generate interactive nodes-and-edges maps.
Database Query and Navigation: How Does it Work?
Figure 2 shows the initial search screen – the starting point for a search of a knowledgebase. The user can search using Boolean logic on a number of fields, including the abstract, keywords, full-text, title, research findings, etc. Each of the thesauri – Author, Research Findings, Organisms and Source of Organisms – are also available for browsing and are directly searchable. Sorting is supported by year, first author, journal title.
Figure 2 Telemakus search screen
Figures 3 and 4 show the results of the search. Clicking on the first listing (Chung) results in the retrieval of the complete record for that item in the research report schema format (Figure 5), a rapid summary of research methods and organism characteristics that provides quick links to a variety of types of information including the full-text of the research article. Clicking on any blue highlighted item under "Table/Figure" takes the searcher to the respective figure in the full-text article.
Figure 3 Display of retrieval set for a search on "neoplasms" (part 1)
Figure 4 Display of retrieval set for a search on "neoplasms" (part 2)
Figure 5 Research report schema Schema for one of the retrieved scientific reports from a search on caloric restriction and neoplasms
The research report schema also serves as a convenient interface for searching for related research concepts, offering a rapid way of following research connections through the database. For instance, clicking on "killer cells, natural – ad libitum" would retrieve additional articles that present data tables linking those two concepts.
The "map it" function, at the bottom of the retrieval set (Figure 4) provides access to the visualized maps of research findings connections for the current retrieval set. Examples of the concept maps generated by clicking on "map it" from Figure 4 are presented in Figures 6 and 7. Figure 6 presents a subset, more focused, map of research findings relating to the research concept of interest. Blue links highlight a reported (by the authors of the research report) statistically significant finding. The visualization tool permits moving from link to link and expanding the view to include a map of all research relationships reported in the retrieved set of documents (Figures 3 and 4). The user can also initiate a new search of a research term or link of interest (e.g., the relationship between survival rate and antioxidants) to retrieve all research papers which have reported this linkage. The iterative nature of the search process and ability to explore research connections from both the research schema as well as the research concept map supports the process of hypothesis exploration in a way that mimics the way many scientists work-by providing a means of exploring a variety of types of connections.
Figure 6 Concept map of research findings linked to neoplasms
Figure 7 Expanded concept map of research findings relationships
Results
The first completed Telemakus knowledgebase focuses on caloric restriction in aging and is freely available at . Caloric restriction was an ideal starting point for Telemakus because it is an important and rapidly expanding specialized area of the biology of aging that is also highly interdisciplinary. Telemakus is a component of the Science of Aging (SAGE) project funded by the Ellison Medical Foundation. Other SAGE partners include the American Association for the Advancement of Science and Highwire Press, Stanford University (SAGE Knowledge Environment web site: ).
Formal usability testing of Telemakus is underway and will be the subject of a future article. Because a major goal of the Telemakus research program is to study scientists' approaches and preferences for accessing and using the scientific literature in order to create models and approaches for user-centered knowledgebases, researchers have been involved in the iterative design and testing of the system from its inception. The primary goals of this evaluation are to:
1. Determine scientists' preferences for working with the research literature.
2. Model preferred features based on those preferences.
3. Test the completeness of schema elements and structure as a document surrogate.
4. Experiment with and identify optimal visual representations to meet user needs.
5. Iteratively review/evaluate/test for improved performance in response to user feedback.
6. Identify domain(s) for future knowledgebase creation.
In general, response to each successive iteration of Telemakus has been positive and included constructive feedback for system enhancements and expansions. User feedback affirms that retrieval based on research findings is a unique and highly desirable core function. Further, the Telemakus schematic document surrogate has been enthusiastically received as a major improvement over the traditional citation format with abstract. As one researcher stated (and several others have echoed), "The strengths of Telemakus are doing what PubMed does not do, which is to give an outline of the main points and to allow searching off the figure/table legends, organisms/sources and outcome fields."
Additional feedback relates to the labeling of concept relationships as "statistically significant." Some researchers are interested in knowing the level of reported significance (i.e., p value) and asked for a detailed labeling to document this. In addition, there have been requests to consider labeling the relationships (i.e., directionality, type, etc.). Early testing of the mapping function resulted in the observation that color-blind individuals would not be able to see lines that were labeled with red or green, which led to a change in the mapping color scheme.
There have been many additional suggestions for improving the visualization, including addition of three-dimensional representations and allowing more user control of the presentation itself. Some researchers have expressed interest in being able to build maps based on the date a particular research finding was reported. This functionality would create time sequence maps that show the progression of research over time and, perhaps, will demonstrate paths of research that have been discarded prematurely and may be worth re-visiting. A number of researchers have indicated the utility of this approach for teaching purposes – for a student to quickly get a sense of the research "facts" in a domain. There have also been requests for tools to support downloading subsets of the knowledgebases, as well as tools to allow individuals to manipulate maps and add their own research findings and ideas to the concept maps.
Discussion
While initial Telemakus development has focused on the research literature related to caloric restriction and the biology of aging, the goal is to expand into additional domains. For example, tables of genetic sequence information, which display reported relationships between gene sequences and diseases, are a natural area of expansion for Telemakus. There is great potential for building linkages between Telemakus knowledgebases and other factual databases, e.g., NCBI entrez resources. In addition, scientists from other domains beyond biomedicine (statistics, environmental research) have indicated that a customized schematic representation of research findings could be very useful in their domains.
Speeding up document processing so Telemakus can easily and efficiently scale for comprehensive treatment of domains is a key priority. As discussed previously, the UMLS Metathesaurus resources (in particular, MetaMap) are proving extremely useful. In addition, the Semantic Network will be tested for enhancing searching and visualization of research findings.
We will continue to utilize an iterative development method so that results of usability evaluation can immediately inform development of additional features. In particular, we want to test our hypothesis that the mapping feature will promote knowledge discovery by showing graphically what is known as well as, through lack of links, what research linkages have not yet been tested.
Since basic sciences researchers tend to initially focus on the data found within a report's tables and figures (sometimes before or instead of actually reading the article), extracting the headings and providing linked research concepts mimics a researcher's traditional approach to reading the research literature [42,48]. When users understand regularities in information spaces (layout, structure, landmarks, etc.) as schemata they acquire navigational knowledge in the form of a cognitive map of the information space. By providing the conceptual schema based on the scientist's own view of scientific research as a document surrogate, Telemakus provides a roadmap for reading and rapidly browsing through numerous research reports and aids in acquisition of the navigational knowledge required for a user to successfully explore complex information spaces [49].
One of the long-term goals of the Telemakus system is not to build knowledgebases "ad infinitum" but rather to create flexible tools for users to quickly and efficiently locate and visualize aggregate research findings from any domain which reports research findings as data. As more and more full-text research reports are available on the Internet, we believe the tools we are developing will provide an important approach for focusing on research findings and providing visual cues for quick review and assimilation.
Conclusions
The Telemakus KnowledgeBase System builds on a good deal of prior research in a variety of domains. It provides a flexible new approach for creating knowledgebases to facilitate retrieval and review of scientific research reports. In formalizing the representation of the research methods and results of scientific reports, Telemakus offers a potential strategy to enhance the scientific discovery process. While other research has demonstrated that aggregating and analyzing research findings across domains augments knowledge discovery, the Telemakus system is unique in combining informative document representations with interactive concept maps of linked relationships across groups of research reports. Telemakus presents a novel approach to creating useful and precise document surrogates and may re-conceptualize the way we currently represent, retrieve and assimilate research findings from the published literature.
Competing interests
None declared.
Authors' contributions
SF conceived the study and contributed to its design, coordination and evaluation. DR and PB participated in the design of the study. DR led the overall coordination and drafted the manuscript. PB led the technical implementation. GMM contributed to the design, coordination and evaluation. All authors read and approved the final manuscript.
Acknowledgements
We gratefully acknowledge support of the Telemakus team, including Craig Benson, Heather Fuller, David Owens, Lucas Reber and Lisa Tisch. We wish to thank our anonymous testers for their time and helpful feedback and our reviewers for their comments and suggestions. We gratefully acknowledge funding provided by the Ellison Medical Foundation and the assistance provided by its Executive Director, Dr. Richard Sprott. We also want to thank the National Library of Medicine for making the UMLS and MetaMap freely available to researchers.
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Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-1-11550714610.1186/1743-7075-1-1EditorialWhat is Nutrition & Metabolism? Feinman Richard D 1rfeinman@downstate.eduHussain M Mahmood 12mhussain@downstate.edu1 Department of Biochemistry, State University of New York Downstate Medical Center, Brooklyn, NY 11203 USA2 Department of Anatomy and Cell Biology, State University of New York Downstate Medical Center, Brooklyn, NY 11203 USA2004 17 8 2004 1 1 1 2 8 2004 17 8 2004 Copyright © 2004 Feinman and Hussain; licensee BioMed Central Ltd.2004Feinman and Hussain; 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.
A new Open Access journal, Nutrition & Metabolism (N&M) will publish articles that integrate nutrition with biochemistry and molecular biology. The open access process is chosen to provide rapid and accessible dissemination of new results and perspectives in a field that is of great current interest. Manuscripts in all areas of nutritional biochemistry will be considered but three areas of particular interest are lipoprotein metabolism, amino acids as metabolic signals, and the effect of macronutrient composition of diet on health. The need for the journal is identified in the epidemic of obesity, diabetes, dyslipidemias and related diseases, and a sudden increase in popular diets, as well as renewed interest in intermediary metabolism.
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Editorial
Recent events that provide the rationale for a new Open Access journal, Nutrition & Metabolism (N&M) include 1) an awareness of an epidemic of obesity, diabetes, dyslipidemias and related diseases, 2) a sudden increase in the popularity of diets, such as low carbohydrate diets, to achieve weight loss and combat diabetes, and 3) a renewed interest in intermediary metabolism accompanied by the development of new tools and techniques for genomic and metabolic analysis.
With the considerable activity shown in these areas, rapid and easily accessible dissemination of new information is clearly valuable. Whereas articles in existing journals do discuss intermediary metabolism in a nutritional context, there is a need for a unique and explicit focus for this discipline. In addition, it is precisely because publications in nutritional biochemistry are spread over such a large number of existing journals, few libraries and almost no individual can subscribe to all. It is in areas like this that free, open access becomes important. There is a large published debate on open access (see, e.g. [1]). Most recently, the UK House of commons issued a report encouraging open access publishing of government-funded research (available with comments through ) and similar motions exist in the US congress [2,3]. The editors of N&M feel that, at this point, the burden of proof is on proponents of perpetuating the current system. We are, however, not doctrinaire on this point and believe one should pay for a service if it is valuable. Beyond information, printed collections provide convenience and we intend to offer bound copies of articles on individual topics as the journal proceeds.
Nutrition and metabolism is a broad field and we welcome submissions from all areas of nutrition and related biochemistry. Like any journal, however, N&M has its own strengths and interests as indicated by the board of editors . Three areas of particular interest are lipoprotein metabolism, amino acids as metabolic signals, and the effect of macronutrient composition of diet on health. This is reflected in our opening research articles by Darimont, et al. on the control of obesity and lipid structure by adrenergic systems, and by Volek, et al. on the effectiveness of low carbohydrate diets, and differential effects on fat and lean mass.
The sudden popularity of low carbohydrate diets is one of the most remarkable phenomena in nutrition today. A recent editorial by Walter Willett points out how important it is that we understand them [4]. Similarly, the recent conference on Nutritional and Metabolic Aspects of Low Carbohydrate Diets , while not recommending any particular diet, highlighted many of the relevant issues in macronutrient control of metabolism. In our initial publications, contributors to the conference will provide reviews of the various topics covered. In the first posting, Klaas Westerterp summarizes the importance of macronutrient composition in thermogenesis, and Stephen Phinney discusses the impact of ketogenic diets on physical performance. Kimball and Jefferson review the regulation of mRNA translation in general. The article provides a nice overview of various mechanisms involved in the control of protein synthesis when amino acids become limiting. Perhaps the most important from a practical standpoint, Nuttall and Gannon summarize potential benefits of higher protein diets in diabetes.
Nutrition & Metabolism welcomes contributions in all areas of research in which nutrition interacts with biochemistry and molecular biology. Emphasis will be on the molecular, biochemical, and physiologic understanding of various metabolic pathways. The journal will publish Original Research, Reviews, Commentaries and Perspectives, Brief Communications, Methods and Book Reviews. Access to all articles in N&M is free. Articles are included in PubMed and archived in PubMed Central. Online submissions can be made at .
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Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-1-21550714810.1186/1743-7075-1-2ReviewKetogenic diets and physical performance Phinney Stephen D 1sdphtb@earthlink.net1 6108 Boothbay Court, Elk Grove, CA 95758, United States of America2004 17 8 2004 1 2 2 29 7 2004 17 8 2004 Copyright © 2004 Phinney; licensee BioMed Central Ltd.2004Phinney; 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.
Impaired physical performance is a common but not obligate result of a low carbohydrate diet. Lessons from traditional Inuit culture indicate that time for adaptation, optimized sodium and potassium nutriture, and constraint of protein to 15–25 % of daily energy expenditure allow unimpaired endurance performance despite nutritional ketosis.
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Introduction
In the opinion of most physicians and nutrition scientists, carbohydrate must constitute a major component of one's daily energy intake if optimum physical performance is to be maintained [1]. This consensus view is based upon a long list of published studies performed over the last century that links muscle glycogen stores to high intensity exercise. It has also been reinforced by the clinical experience of many physicians, whose patients following low carbohydrate formula or food diets frequently complain of lightheadedness, weakness, and ease of fatigue.
During the time that this consensus view of the necessity of carbohydrate for vigorous exercise was forming, the last pure hunting cultures among the peoples of North America finally lost out in competition with expanding European cultural influences. Between 1850 and 1930, the routine consumption of carbohydrates spread north from the U.S. Plains States through central Canada, where the indigenous peoples had heretofore made at most seasonal use of this nutrient class. However the last of these groups to practice their traditional diet, the Inuit people of the Canadian and Alaskan Arctic regions, were luckily observed by modern scientists before their traditional dietary practices were substantially altered. The reports of these early scientists imply that the Inuit people were physically unhampered despite consuming a diet that was essentially free of identifiable carbohydrate.
Given this juxtaposition of clinical research results favoring carbohydrate against observed functional well-being in traditional cultures consuming none, it is an interesting challenge to understand how these opposing perspectives can be explained. This paper will review the observations of early explorer scientists among the Inuit, track the controversy that they stimulated among nutritionists in the last century, and utilize some of the forgotten lessons from the Inuit culture to explain how well-being and physical performance can be maintained in the absence of significant dietary carbohydrate.
The origins of carbohydrate supremacy
Until the development of agriculture over last few millennia, our human ancestors' consumption of dietary carbohydrate was opportunistic. As some groups adapted to hunting and fishing for their sustenance, they were able to move into temperate and then arctic regions, where limited access to wild grain, nuts, and fruit dictated sustained dependence upon fat and protein as primary sources of dietary energy.
With the development of agriculture came the ability to grow and store grain, allowing societies to remain in a stable physical location, build permanent dwellings, and potentially stimulating the development of written language (those early stone tablets would have been difficult to transport from camp to camp on a dog sled). Starting from locations in the Middle East and Asia, cultures based upon agricultural wheat and rice spread over 5 millennia to dominate Europe, Africa, and the Americas.
With its ability to support a non-nomadic life style, greater population density, and permanent communities; there were clear advantages of agriculture-based societies over those based upon hunting and fishing, particularly as agricultural communities built the infrastructure to support trade and transport. Given its success in this competition of cultures (and by implication, the competition of their diets), it is an easy assumption that a grain-based diet is functionally superior to one based upon the meat and fish (fat and protein) of the hunting societies that they superseded.
As the science of nutrition developed in the early 20th Century, numerous comparative studies were undertaken to assess differences between diets. Although there were some advocates of low carbohydrate diets (eg, the Banting diet of the 19th Century, promoted for weight loss and diabetes control), the prevailing premise for these studies was that carbohydrate was a necessary nutrient for optimum human health and function. Among studies confirming this view, a classic was the 1939 study by two Danish scientists, Christensen and Hansen [2]. They did a crossover study of low carbohydrate, moderate carbohydrate, and high carbohydrate diets, each lasting one week. At the end of each diet, the subjects' endurance time to exhaustion on a stationary bicycle was assessed. Compared to the mean endurance time on the low carb diet of 81 minutes, the subjects were able to ride for 206 minutes after the high carb diet.
During the Second World War, another oft-cited study was performed, this time examining the practicality of pemmican (a mixture of dried meat and fat) as a light-weight emergency ration for soldiers. This experiment by Kark et al [3] involved abruptly switching soldiers in winter training in the Canadian Arctic from standard carbohydrate-containing rations to pemmican. This study only lasted 3 days, as the soldiers rapidly became unable to complete their assigned tasks, which included pulling loaded sleds 25-miles per day through deep snow.
With the resurgence of biomedical science in the 1960's came development of the percutaneous needle biopsy, facilitating assessment of intra-muscular fuel stores and metabolism. This led to the concept of muscle glycogen as the limiting fuel for high intensity exercise [4] and to the nutritional strategy of carbohydrate loading [5]. The clear consensus that developed from this research was that fat had limited utility as a fuel for vigorous exercise, and that humans are physically impaired if given a low carbohydrate diet.
The hunter's counterpoint – practical observations on ketogenic diets
Although high-carbohydrate diets might be more effective in short-term tests of high-intensity exercise, there are multiple clues in the published literature that the debilitating effects of ketogenic diets are overstated. Not only is there the demographic evidence that whole populations of people lived for millennia as hunters, but there are many reports of Europeans crossing over to live within the cultures of these hunting societies without apparent impediment.
One of the earliest documented demonstrations of physical stamina during a ketogenic diet was the Schwatka 1878–80 expedition in search of the lost Royal Navy Franklin expedition. The Schwatka expedition, sponsored by the New York Herald and the American Geographical Society, departed from the west coast of Hudson's Bay in April of 1879 with 4 Caucasians, 3 families of Inuits, and 3 heavily laden dog sleds. Totaling 18 people, they started out with a month's supply of food (mostly walrus blubber) and a prodigious supply of ammunition for their hunting rifles. After covering over 3000 miles on foot over ice, snow and tundra, all 18 members of the original party plus their 44 dogs returned to Hudson's Bay in March of 1880. Once their initial provisions were depleted, the expedition's only source of additional food was hunting and fishing, as there were no other sources of supply along their route.
The leader of this expedition, Lt. Frederick Schwatka, was a graduate of both West Point and Bellevue Hospital Medical College. His summary of the expedition was published as a news article in the New York Herald in the Fall of 1880, but his written diary was lost for 85 years until its discovery and publication by the Marine Historical Association of Mystic CT in 1965 [6]. This fascinating 117-page saga describes how Schwatka, a frontiersman and U.S. Army surgeon, collaborated with his Inuit guides to accomplish a remarkable feat of physical endurance.
In one notation, Schwatka provides an interesting insight into his weaning from their initial supply of carbohydrate-containing food.
"When first thrown wholly upon a diet of reindeer meat, it seems inadequate to properly nourish the system, and there is an apparent weakness and inability to perform severe exertive fatiguing journeys. But this soon passes away in the course of two or three weeks."
This observation, written a century before the current author first came to grips with the issue of "keto-adaptation", offers an early clue to resolve the dichotomy between impaired performance with low carbohydrate diets in the laboratory and their lack of debilitating effects when taken among people practiced in their use. That Schwatka was not impaired by his prolonged experience eating meat and fat is evidenced by his diary entry for the period 12–14 March 1880, during which he and an Inuit companion walked the last 65 miles in less than 48 hours to make a scheduled rendezvous with a whaling ship and complete his journey home.
Twenty-six years later, a Harvard-trained anthropologist named Vilhjalmur Stefansson entered the Arctic with the purpose of studying the Inuit language and culture. Having been born in 1879 in Manitoba and grown up in North Dakota, it is unlikely that Stefansson was aware of the Schwatka expedition or its reported technique of extended dogsled travel while living by hunting. However when separated from his expedition and thus his source of supply over the winter of 1906–7, Stefansson was taken in by a group of Inuit on the Canadian Arctic coast. With the arrival of spring in June of 1907, he both spoke their language and had acquired their skill of living and traveling by dogsled on a hunter's diet.
For the next decade, Stefansson traveled extensively over the arctic mainland and among the islands to the north. During this period, he was away from the outposts of European settlement for periods of up to 18 months at a time, and in the remote regions of the Canadian Arctic he lived with groups of Inuit for whom he was the first European they had met.
Stefansson wrote extensively about these experiences in both the scientific literature and in books for the lay public [7]. One of the main themes of his writing was the adaptation of the Inuit culture to survive as nomadic groups in the arctic on a diet consisting solely of the products of hunting and fishing. Coming as it did in the same time period that the science of nutrition was blossoming with the discovery and characterization of vitamins (eg, the first vitamin to be chemically defined was thiamin by Funk in 1911), Stefansson's claim that one could live and function well on the products of just one food group caused tremendous controversy [8].
Subjected to great criticism and even scorn, Stefansson agreed to recreate the Inuit diet under scientific observation. Therefore, for the calendar year of 1929 he and a colleague from his arctic explorations ate a diet consisting of meat and fat for 12 months. This experiment, supervised by Dr. Eugene DuBois, was conducted at Bellevue Hospital in New York. For the first 3 months of this study, the two explorers were under constant observation to guarantee dietary compliance, after which they were allowed more freedom of movement but with frequent tests to document that they remained in ketosis. This study was reported in multiple peer-reviewed publications, the primary reports being published in the Journal of Biological Chemistry in 1930 [9,10], As noted by DuBois [8], the study results were essentially "negative", in that both subjects survived the 12 months in apparent good health, having no signs of scurvy (which was predicted to occur within the first 3 months) or other deficiency diseases.
It is interesting to note from the careful observations published from the Bellevue study that Stafansson ate relatively modestly of protein, deriving between 80–85% of his dietary energy from fat and only 15–20% from protein [9]. This was, and still remains, at odds with the popular conception that the Inuit ate a high protein diet, whereas in reality it appears to have been a high fat diet with a moderate intake of protein. In his writings, Stefansson notes that the Inuit were careful to limit their intake of lean meat, giving excess lean meat to their dogs and reserving the higher fat portions for human consumption [11].
It is also interesting to conjecture that the vigorous defense of his arctic observations by Stefansson may have led indirectly to the development of the carbohydrate loading hypothesis. Stefansson was a polarizing influence in the field of nutrition, and his advocacy of pemmican as an emergency ration for troops during the Second World War led directly to the Kark study quoted above, which in turn was a predecessor to many comparative dietary trials performed in Europe and the U.S. in later decades.
Modern ketogenic diet performance studies
There was a resurgence of interest in very low calorie ketogenic diets for weight loss in the 1970's, followed closely by the complications (including sudden death) associated with the Liquid Protein diet popularized in 1976. However, the fatigue and apparent cardiac dysfunction caused by this collagen-based fad diet stood in stark contrast to the published experience of arctic explorers such as Schwatka and Stefansson. In addition, physicians who monitored patients following very low calorie diets observed wide variations between the exercise-tolerance of these individuals.
Given that the elegant research on the metabolism of total fasting by Dr. George Cahill and colleagues had demonstrated that full adaptation of nitrogen, fat, and carbohydrate metabolism required a number of weeks [12], it seemed reasonable to hypothesize that exercise tolerance would take more than a week to recover after removal of carbohydrate from the diet. This view was supported by the subsequent discovery of the prescient adaptation quote from Schwatka's diary [6] noted above.
To test this hypothesis, the current author (under the mentorship of Drs. Ethan Sims and Edward Horton at the University of Vermont) undertook a study of subjects given a very low calorie ketogenic diet for 6 weeks in a metabolic research ward [13]. The protein for this diet, along with a modicum of inherent fat, was provided by lean meat, fish, and poultry providing 1.2 grams of protein per kg of reference ("ideal") body weight daily. In addition, mindful that the natriuresis of fasting could reduce circulating blood volume and cause secondary renal potassium wasting, the subjects were prescribed 3 grams of supplemental sodium as bouillion and 25 mEq (1 g) of potassium as bicarbonate daily.
Treadmill performance testing of these subjects included determinations of peak aerobic power (VO2max) after a 2-week weight maintenance baseline diet, and again after 6 weeks of the ketogenic weight loss diet. Endurance time to exhaustion was quantitated at 75% of the baseline VO2max. This endurance test was repeated again after one week of weight loss and finally after 6 weeks of weight loss. Other than these tests, the subjects did no training exercise during their participation in this study. To compensate for the fact that the average subject had lost over10 kg, the final endurance treadmill test was performed with the subject carrying a backpack equivalent in weight to the amount lost.
The energy expenditure data (expressed as oxygen consumption) and exercise times across this 8-week inpatient study are shown in Table 1. That these subjects'peak aerobic power did not decline despite 6 weeks of a carbohydrate-free, severely hypocaloric diet implies that the protein and mineral contents of the diet were adequate to preserve functional tissue. As can be noted, endurance time to exhaustion was reduced after one week of the ketogenic diet, but it was significantly increased over the baseline value by the 6-week time point. However the interpretation of this endurance test is confounded by the fact that the oxygen cost (ie, energy cost) of the treadmill exercise had significantly decreased following the weight loss, and this occurred despite the subjects being made to carry a backpack loaded to bring them back to their initial exercise test weight.
Table 1 Exercise parameters of Vermont study [13]
Baseline Week 1 Week 6
VO2max (LPM) 2.49 -- 2.49
Exercise VO2(LPM) 1.88* 1.71 1.50*
Endurance time (min) 168+ 130 249+
LPM, liter per minute *week 6 < baseline, P < 0.05 +week 6 > baseline, P < 0.01
This question of improved efficiency notwithstanding, it is clear that our subjects experienced a delayed adaptation to the ketogenic diet, having reduced endurance performance after one week followed by a recovery to or above baseline in the period between one and six weeks. Given the reduced energy cost of the exercise despite the backpack, the extent of this adaptation cannot be determined from this study. To explain this improved exercise efficiency, we can speculate that humans are more efficient carrying weight in a modern backpack than under their skin as excess body fat. It is also possible that these untrained subjects became more comfortable with prolonged treadmill walking by their third test, and therefore improving their overall efficiency.
Given the uncertainties of this study caused by the subject's weight loss and potential for improved technique with multiple tests, the current author undertook a second study under the mentorship of Dr. Bruce Bistrian at MIT in Cambridge MA [14,15]. The diet employed in this followup study was patterned after that consumed by Stefansson during his year in the Bellevue study (and thus presumably close to that traditionally consumed by the Inuit) with the intention that the subjects would be in ketosis without weight loss.
This second study utilized competitive bicycle racers as subjects, confined to a metabolic ward for 5 weeks. In the first week, subjects ate a weight maintenance (eucaloric) diet providing 67% of non-protein energy as carbohydrate, during which time baseline performance studies were performed. This was followed by 4 weeks of a eucaloric ketogenic diet (EKD) providing 83% of energy as fat, 15% as protein, and less than 3% as carbohydrate. The meat, fish, and poultry that provided this diets protein, also provided 1.5 g/d of potassium and was prepared to contain 2 g/d of sodium. These inherent minerals were supplemented daily with an additional 1 g of potassium as bicarbonate, 3 grams of sodium as bouillon, 600 mg of calcium, 300 mg of magnesium, and a standard multivitamin.
The bicyclist subjects of this study noted a modest decline in their energy level while on training rides during the first week of the Inuit diet, after which subjective performance was reasonably restored except for their sprint capability, which remained constrained during the period of carbohydrate restriction. On average, subjects lost 0.7 kg in the first week of the EKD, after which their weight remained stable. Total body potassium (by 40K counting) revealed a 2% reduction in the first 2 weeks (commensurate with the muscle glycogen depletion documented by biopsy), after which it remained stable in the 4th week of the EKD. These results are consistent with the observed reduction in body glycogen stores but otherwise excellent preservation of lean body mass during the EKD.
The results of physical performance testing are presented in Table 2. What is remarkable about these data is the lack of change in aerobic performance parameters across the 4-week adaptation period of the EKD. The endurance exercise test on the cycle ergometer was performed at 65% of VO2max, which translates in these highly trained athletes into a rate of energy expenditure of 960 kcal/hr. At this high level of energy expenditure, it is notable that the second test was performed at a mean respiratory quotient of 0.72, indicating that virtually all of the substrate for this high energy output was coming from fat. This is consistent with measures before and after exercise of muscle glycogen and blood glucose oxidation (data not shown), which revealed marked reductions in the use of these carbohydrate-derived substrates after adaptation to the EKD.
Table 2 Exercise parameters of MIT EKD study [15]
VO2max (LPM) Exercise VO2(LPM) Exercise RQ Endurance time (min)
Baseline 5.1 3.18 0.83* 147
EKD-4 5.0 3.21 0.72* 151
LPM, liter per minute * P < 0.01
Examining the results of these two ketogenic diet performance studies together indicates that both groups experienced a lag in performance across the first week or two of carbohydrate restriction, after which both peak aerobic power and sub-maximal (60–70% of VO2max) endurance performance were fully restored. In both studies, one with untrained subjects and the other with highly trained athletes who maintained their training throughout the study, there was no loss of VO2max despite the virtual absence of dietary carbohydrate for 4–6 weeks. This whole-body measure of oxidative metabolism could not be maintained unless there was excellent preservation of the full complement of functional tissues including skeletal muscle (and mitochondrial) mass, circulating red cell mass, and cardiopulmonary functions.
The possibility raised by the first study of improved endurance time after keto-adaptation was not substantiated by the second study employing highly trained athletes without the complicating variable of major weight loss. It is thus likely that the increased endurance time in the Vermont study was due to improved efficiency (ie, less hobbling from a backpack than from an equal weight of internal body fat) and/or improved acclimation to the endurance test procedure. Such acclimation would not be expected in the second study, as the highly trained bicycle racers were well conditioned to the stationary ergometer at the start of the study. It is also worth noting that the bicycle racers remained weight stable (excepting the half kilogram of reduced muscle glycogen) across the 4 weeks of the EKD, which was equi-caloric with the baseline diet. Although 4 weeks is a relatively short period to assess small differences in energy efficiency between diets, this observation implies that there was no great reduction in the efficiency of energy metabolism after keto-adaptation.
As a final note in this section, neither the Vermont study nor the MIT study has been refuted in the 2 decades since their publication. Understandably given the expense of human metabolic ward studies and the orthogonal conclusions of these two studies, neither study has been corroborated by a similar human study. However two subsequent animal studies examining physical performance after keto-adaptation have yielded results consistent with those presented above [16,17].
Resolving the performance paradox
There are three factors that can help us explain the paradox presented by studies showing superior performance with high carbohydrate diets versus the present author's two studies noted above.
Adaptation
The most obvious of these is the time allotted (or not) for keto-adaptation. In this context, the prescient observation of Schwatka (that adaptation to "a diet of reindeer meat" takes 2–3 weeks) says it all. None of the comparative low-carbohydrate versus high-carbohydrate studies done in support of the carbohydrate loading hypothesis sustained the low carbohydrate diet for more than 2 weeks [5], and most (including the classic report of Christensen and Hansen [2]) maintained their low-carbohydrate diets for 7 days or less.
There are to date no studies that carefully examine the optimum length of this keto-adapataion period, but it is clearly longer than one week and likely well advanced within 3–4 weeks. The process does not appear to happen any faster in highly trained athletes than in overweight or untrained individuals. This adaptation process also appears to require consistent adherence to carbohydrate restriction, as people who intermittently consume carbohydrates while attempting a ketogenic diet report subjectively reduced exercise tolerance.
Sodium and potassium
The second factor differentiating the author's studies from many others is optimized mineral nutriture, which has benefits for both cardiovascular reserve in the short term and preservation of lean body mass and function over longer time periods. The Inuit people lived much of the year on coastal ice (which is partially desalinated sea water), and much of their food consisted of soup made with meat in a broth from this brackish source of water. When they went inland to hunt, they traditionally added caribou blood (also a rich source of sodium) to their soup. With these empirically derived techniques, the Inuit culture had adapted the available resources to optimize their intakes of both sodium and potassium.
When meat is baked, roasted, or broiled; or when it is boiled but the broth discarded, potassium initially present in the meat is lost, making it more difficult to maintain potassium balance in the absence of fruits and vegetables. Because our research subjects were accustomed to eating meat, fish, and poultry prepared as something other than soup, we chose to give them most of their sodium separately as bouillon and a modest additional supplement of potassium as potassium bicarbonate. With these supplements maintaining daily intakes for sodium at 3–5 g/d and total potassium at 2–3 g/d, our adult subjects were able to effectively maintain their circulatory reserve (ie, allowing vasodilatation during submaximal exercise) and effective nitrogen balance with functional tissue preservation.
An example of what happens when these mineral considerations are not heeded can be found in a study prominently published in 1980 [18]. This was a study designed to evaluate the relative value of "protein only" versus "protein plus carbohydrate" in the preservation of lean tissue during a weight loss diet. The protein only diet consisted solely of boiled turkey (taken without the broth), whereas the protein plus carbohydrate consisted of an equal number of calories provided as turkey plus grape juice. Monitored for 4 weeks in a metabolic ward, the subjects taking the protein plus carbohydrate did fairly well at maintaining lean body mass (measured by nitrogen balance), whereas those taking the protein only experienced a progressive loss of body nitrogen.
A clue to what was happening in this "Turkey Study" could be found in the potassium balance data provided in this report. Normally, nitrogen and potassium gains or losses are closely correlated, as they both are contained in lean tissue. Interestingly, the authors noted that the protein only diet subjects were losing nitrogen but gaining potassium. As noted in a rebuttal letter published soon after this report [19], this anomaly occurred because the authors assumed the potassium intake of their subjects based upon handbook values for raw turkey, not recognizing that half of this potassium was being discarded in the unconsumed broth. Deprived of this potassium (and also limited in their salt intake), these subjects were unable to benefit from the dietary protein provided and lost lean tissue. Also worthy of note, although this study was effectively refuted by a well-designed metabolic ward study published 3 years later [20], this "Turkey Study" continues to be quoted as an example of the limitations of low carbohydrate weight loss diets.
Protein dose
The third dietary factor potentially affecting physical performance is adjusting protein intake to bring it within the optimum therapeutic window for human metabolism. The studies noted herein [13-15,20] demonstrate effective preservation of lean body mass and physical performance when protein is in the range of 1.2 – 1.7 g/kg reference body weight daily, provided in the context of adequate minerals. Picking the mid-range value of 1.5 g/kg-d, for adults with reference weights ranging from 60–80 kg, this translates into total daily protein intakes 90 to 120 g/d. This number is also consistent with the protein intake reported in the Bellevue study [9]. When expressed in the context of total daily energy expenditures of 2000–3000 kcal/d, about 15% of ones daily energy expenditure (or intake if the diet is eucaloric) needs to be provided as protein.
The effects of reducing daily protein intake to below 1.2 g/kg reference weight during a ketogenic diet include progressive loss of functional lean tissue and thus loss of physical performance, as demonstrated by Davis et al [21]. In this study, subjects given protein at 1.1 g/kg-d experienced a significant reduction in VO2max over a 3 month period on a ketogenic diet, whereas subjects given 1.5 g/kg-d maintained VO2max.
At the other end of the spectrum, higher protein intakes have the potential for negative side-effects if intake of this nutrient exceeds 25% of daily energy expenditure. One concern with higher levels of protein intake is the suppression of ketogenesis relative to an equi-caloric amount of fat (assuming that ketones are a beneficial adaptation to whole body fuel homeostasis). In addition, Stefansson describes a malady known by the Inuit as rabbit malaise [8]. This problem would occur in the early spring when very lean rabbits were the only available game, when people might be tempted to eat too much protein in the absence of an alternative source of dietary fat. The symptoms were reported to occur within a week, and included headache and lassitude. Such symptoms are not uncommon among people who casually undertake a "low carbohydrate, high protein" diet.
Conclusions
Both observational and prospectively designed studies support the conclusion that submaximal endurance performance can be sustained despite the virtual exclusion of carbohydrate from the human diet. Clearly this result does not automatically follow the casual implementation of dietary carbohydrate restriction, however, as careful attention to time for keto-adaptation, mineral nutriture, and constraint of the daily protein dose is required. Contradictory results in the scientific literature can be explained by the lack of attention to these lessons learned (and for the most part now forgotten) by the cultures that traditionally lived by hunting. Therapeutic use of ketogenic diets should not require constraint of most forms of physical labor or recreational activity, with the one caveat that anaerobic (ie, weight lifting or sprint) performance is limited by the low muscle glycogen levels induced by a ketogenic diet, and this would strongly discourage its use under most conditions of competitive athletics.
List of abbreviations
VO2max – maximum aerobic capacity
RQ – respiratory quotient
EKD – eucaloric ketogenic diet
Competing interests
None declared.
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| 15507148 | PMC524027 | CC BY | 2021-01-04 16:37:45 | no | Nutr Metab (Lond). 2004 Aug 17; 1:2 | utf-8 | Nutr Metab (Lond) | 2,004 | 10.1186/1743-7075-1-2 | oa_comm |
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Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-1-31550715110.1186/1743-7075-1-3ReviewAmino acids as regulators of gene expression Kimball Scot R 1skimball@psu.eduJefferson Leonard S 1jjefferson@psu.edu1 Department of Cellular and Molecular Physiology, The Pennsylvania State University College of Medicine, Hershey, PA 17033, USA2004 17 8 2004 1 3 3 29 6 2004 17 8 2004 Copyright © 2004 Kimball and Jefferson; licensee BioMed Central Ltd.2004Kimball and Jefferson; 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 role of amino acids as substrates for protein synthesis is well documented. However, a function for amino acids in modulating the signal transduction pathways that regulate mRNA translation has only recently been described. Interesting, some of the signaling pathways regulated by amino acids overlap with those classically associated with the cellular response to hormones such as insulin and insulin-like growth factors. The focus of this review is on the signaling pathways regulated by amino acids, with a particular emphasis on the branched-chain amino acid leucine, and the steps in mRNA translation controlled by the signaling pathways.
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Introduction
Recent advances in biomedical research reveal a key role for amino acids as nutritional signals in the regulation of a number of cellular processes. Studies employing a variety of cell types and different tissues demonstrate that one such process affected is the regulation of gene expression through modulation of the translation of messenger RNA (mRNA). The studies show that cells recognize changes in amino acid availability and generate alterations in signal transduction pathways that are also regulated by hormones and growth factors. The cells then respond to the integrated signaling input by either upregulating or downregulating translation initiation, i.e., the process during which initiator methionyl-tRNA (met-tRNAi) and mRNA bind to a 40S ribosomal subunit followed by the joining of a 60S ribosomal subunit to form a translationally competent 80S ribosome. The response of translation initiation to a change in amino acid and/or hormone availability can be general, i.e., affecting the translation of most if not all mRNAs, and/or specific, i.e., affecting the translation of a single class or subset of mRNAs. Both the general and specific responses can be mediated through regulation of either the met-tRNAi and/or mRNA binding steps. The specific response may also involve an additional regulatory site, i.e., the phosphorylation status of ribosomal protein rpS6, one of the proteins composing the 40S ribosomal subunit. Learning how the cell recognizes a sufficiency of amino acids is presently the objective of intense research. Present evidence, however, suggests multiple recognition sites and multiple signaling pathways. Below, we summarize our current knowledge of the signaling pathways known to respond to changes in amino acid availability. In addition, the translation initiation factors and mRNA structural elements that are involved in changes in both global and specific modulation of mRNA translation are discussed.
mRNA translation initiation
The first step in translation initiation involves the binding of met-tRNAi to the 40S ribosomal subunit, a reaction mediated by the eIF2•GTP complex [reviewed in [1]]. In a subsequent step, the GTP bound to eIF2 is hydrolyzed to GDP and eIF2 is released from the 40S subunit complexed with GDP, leaving met-tRNAi behind. Exchange of GDP bound to eIF2 for GTP is mediated by the guanine nucleotide exchange factor eIF2B, and as described below, there are at least three known mechanisms for modulating eIF2B activity in vivo.
The second step in translation initiation involves the binding of mRNA to the 40S ribosomal subunit containing the eIF2•GTP•met-tRNAi complex and eIF3 [1]. The protein that mediates this step is a heterotrimeric complex referred to as eIF4F which consists of the initiation factors eIF4A, eIF4E, and eIF4G. eIF4A is an RNA helicase that serves to unwind secondary structure in the 5'-untranslated region (5'-UTR) of the mRNA, allowing the 40S ribosomal subunit to migrate from the 5'-m7GTP cap to the AUG start codon. The helicase activity of eIF4A is stimulated by eIF4B and eIF4H. eIF4E binds to the m7GTP cap at the 5'-end of the mRNA and thus plays a crucial role in the binding of the mRNA to the ribosome. eIF4G is a scaffolding protein that binds to eIF4A, eIF4E, and eIF3. Thus, eIF4G is a molecular bridge that links the mRNA, which is bound by eIF4E, to the 40S ribosomal subunit, which is bound by eIF3. Assembly of the eIF4F complex is regulated in part through the reversible association of eIF4E with the translational repressors, eIF4E-binding proteins 4E-BP1, 4E-BP2, and 4E-BP3. The domain on eIF4E to which eIF4G binds overlaps with the binding domain for the 4E-BPs, such that either eIF4G or 4E-BP can bind to eIF4E, but both cannot bind at the same time. Thus, association of eIF4E with a 4E-BP precludes the binding of mRNA to the 40S ribosomal subunit by preventing the binding of the eIF4E•mRNA complex with eIF4G. Association of eIF4E with the 4E-BPs is regulated by phosphorylation of 4E-BP, whereby hypophosphorylated 4E-BPs bind to eIF4E but the hyperphosphorylated proteins do not.
Regulation of mRNA translation through Phosphorylation of eIF2 or eIF2B
Of the three known mechanisms for regulating eIF2B activity, the best characterized involves phosphorylation of eIF2 on Ser51 of its α-subunit. Phosphorylation of eIF2α converts eIF2 from a substrate into a competitive inhibitor of eIF2B and represses the translation of most mRNAs, but paradoxically enhances the translation of mRNAs containing multiple upstream open reading frames (uORF) and internal ribosome entry sites (IRESs). Phosphorylation of eIF2α is mediated by any of four known eIF2α kinases in mammalian cells: the mammalian ortholog of the yeast general control non-derepressing kinase-2 (mGCN2), the heme-regulated inhibitor (HRI), the protein kinase dsRNA-activated (PKR), and the PKR-like endoplasmic reticulum kinase [PERK, reviewed in [2]] (Fig. 1). In both cells in culture [e.g. [3]] and livers perfused in situ [4], deprivation of single essential amino acids promotes phosphorylation of eIF2α with a concomitant inhibition of eIF2B. The phosphorylation of eIF2α that occurs in vivo [5], in perfused rat liver [6], and in cells in culture [7] in response to altered amino acid availability is mediated by the eIF2α protein kinase referred to as mGCN2. In yeast deprived of amino acids, uncharged tRNA accumulates and binds to a domain on Gcn2p that exhibits sequence homology to histidyl-tRNA synthetase resulting in its activation [reviewed in [5]]. In fasted rats, feeding a meal containing a complete mixture of essential amino acids stimulates protein synthesis in the liver and skeletal muscle, but has no effect on eIF2α phosphorylation or eIF2B activity [8]. In contrast, feeding a diet lacking a single essential amino acid results in both an increase in eIF2α phosphorylation and a reduction in eIF2B activity in liver [9], suggesting that an imbalance in plasma concentrations of essential amino acids results in activation of signaling pathways within the liver that result in increased phosphorylation of eIF2α. The enhanced phosphorylation of eIF2α that occurs in response to an imbalanced amino acid mixture is mediated by the eIF2α kinase mGCN2, because in mice lacking the kinase, feeding a diet lacking leucine does not promote eIF2α phosphorylation or inhibition of eIF2B [5]. However, the mechanism through which severe amino acid deprivation activates mGCN2 in cells in culture, i.e. accumulation of uncharged tRNA, probably isn't relevant in vivo because plasma amino acids are typically maintained at concentrations well above the Km of the aminoacyl-tRNA synthetases, even during fasting, and therefore significant amounts of uncharged tRNA are unlikely to accumulate. Modulation of eIF2α phosphorylation also occurs in response to changes in the availability of nutrients other than amino acids. For example, either hypoglycemia or hyperglycemia promotes eIF2α phosphorylation. Hypoglycemia is thought to activate the endoplasmic reticulum-associated eIF2α kinase termed PERK through induction of the ER stress response [10]. However, the kinase that phosphorylates eIF2α in response to hyperglycemia is unknown. In vivo, the transient hypoglycemia that occurs shortly after birth results in altered translation of mRNAs encoding several transcription factors such as C/EBPβ that induce the transcription of a number of genes involved in gluconeogenesis and glucose storage such as PEPCK, glucose-6-phosphatase, pyruvate carboxylase, and glycogen synthetase [11]. A recent study using mice containing a homozygous mutation in the gene encoding eIF2α that replaces Ser51 with an unphosphorylatable Ala residue (eIF2S51A) demonstrated that phosphorylation of eIF2α is a critical component in the response of the newborn to hypoglycemia [12]. Thus, in neonatal eIF2S51A mice, the activity of PEPCK in the liver is significantly reduced compared to wildtype mice and its induction immediately after birth is severely attenuated. The mechanism through which eIF2α phosphorylation might promote induction of PEPCK gene transcription is as yet unexplored, but has been postulated to be a consequence of altered translation of mRNAs encoding specific transcription factors, e.g. C/EBPα and C/EBPβ.
Figure 1 Regulation of eIF2α phosphorylation. Phosphorylation of eIF2α is mediated by four known protein kinases that are regulated by diverse cellular stresses. Phosphorylation of eIF2α inhibits eIF2B which can have both general and specific effects on mRNA translation as described in detail in the text.
HRI was first identified in rabbit reticulocytes and shown to be activated in response to hyperoxia and iron and heme deficiency [13]. Subsequent studies have shown that HRI is also expressed in multiple tissues and is activated by heavy metals and nitric oxide (NO). In fact, NO binds directly to HRI [14]. Because non-erythroid cells seldom experience large fluctuations in heme content, it has been suggested that NO may be a principle regulator of HRI in such cells [14].
PKR is a ubiquitously expressed serine-threonine protein kinase that is activated by double-stranded RNA and is induced by interferon [reviewed in [15]]. PKR is also activated by lipopolysaccharide and cytokines such as IL-1 and TNF-α, and is a key component of the proinflammatory response to bacterial infection. It is a potent inhibitor of cell growth when over-expressed in yeast, mammalian, or insect cells, an effect that is mediated by eIF2α phosphorylation because co-expression of a non-phosphorylatable eIF2α prevents the growth repressive effect [16]. Unlike the other three eIF2α kinases, eIF2α is not the only substrate for PKR; for example, PKR is reported to phosphorylate the regulatory subunit of protein phosphatase 2A [17]. PKR also binds to the IκB kinase complex and is involved in NF-κB signaling.
In addition to changes in eIF2α phosphorylation, eIF2B activity can be altered through changes in expression of the catalytic ε-subunit. Knockdown of the catalytic ε-subunit using RNAi essentially halts cell growth and triggers apoptosis [18]. In contrast, overexpression of eIF2Bε, as occurs in many transformed cells, results in increased growth [19]. Because the ε-subunit alone is not inhibited by phosphorylated eIF2, overexpression of eIF2Bε provides a means of enhancing mRNA translation under stress conditions that promote eIF2α phosphorylation. The mechanism(s) through which eIF2Bε expression is regulated are unknown, but our laboratory has found that a preferential increase in eIF2Bε expression occurs in response to acute resistance exercise and is blocked by pre-treatment with rapamycin, a specific inhibitor of the mammalian target of rapamycin (mTOR) (unpublished observation). Because both nutrients and growth-promoting hormones stimulate the mTOR signal transduction pathway (see the next section for further discussion of mTOR signaling), it is tempting to speculate that expression of eIF2Bε might be enhanced by such stimuli.
The guanine nucleotide exchange activity of eIF2B may also be subject to regulation through phosphorylation of its ε-subunit. In vitro, at least four kinases phosphorylate eIF2Bε including casein kinases (CK)-I and -II, glycogen synthase kinase (GSK)-3, and DYRK. Phosphorylation of eIF2Bε by either CK-I [20] or CK-II [20,21] reportedly stimulates the activity of eIF2B, although this conclusion has been questioned by another group [22]. Whether or not phosphorylation by GSK-3 alters the activity of eIF2B is likewise controversial. One study [20] reports that phosphorylation by GSK-3 has no direct effect on eIF2B activity, even though phosphorylation by GSK-3 prevents the subsequent phosphorylation, and thus activation, by CK-I. In contrast, other studies suggest that phosphorylation of Ser535 in rat eIF2Bε (Ser540 in the human sequence) by GSK-3 is required, but not sufficient, for inhibition of eIF2B activity by insulin [23].
Regulation of mRNA translation through downstream targets of the mTOR signaling pathway
The protein kinase mTOR is a common intermediate in both nutrient and hormone signal transduction pathways (Fig. 2). Signaling through mTOR is enhanced by nutrients and anabolic hormones, such as insulin or IGF-I [24,25], and repressed by elevation of cAMP [25-27] or activation of AMPK [28-30], suggesting that one function of mTOR is to integrate the anabolic response to nutrients and insulin and the catabolic response to counter-regulatory hormones, such as glucagon. However, mTOR may not be a direct target of nutrient and hormone signaling. Instead, a number of recent studies have identified TSC1•TSC2 as a potential branch point in the nutrient, insulin, and AMPK signaling pathways to mTOR [31,32]. The results of these studies support a model wherein insulin and leucine would repress the inhibitory action of TSC1•TSC2 on mTOR signaling whereas glucagon would stimulate it. In this model, insulin stimulates signaling to mTOR through Akt-mediated phosphorylation of TSC2. Leucine would also modulate signaling through mTOR through the TSC1•TSC2 complex. However, the mechanism through which leucine signals to TSC1•TSC2 is unknown, but is distinct from Akt. Leucine may also modulate signaling through mTOR by altering the association of the kinase with one or more regulatory proteins, such as the regulatory associated protein of mTOR (raptor) and G protein β-subunit-like protein (GβL). In the paragraphs that follow, the evidence supporting these various mechanisms for regulating mTOR is discussed.
Figure 2 Regulation of the mTOR signaling pathway. The mTOR signaling pathway is controlled through various upstream kinases (e.g. AMPK, AKT, and MK2) that converge on the tuberous sclerosis complex, TSC1•TSC2. TSC2 is a GTPase-activator protein for Rheb which is a positive effector of signaling through mTOR. mTOR signals to downstream targets such as 4E-BP1 and S6K1 as a complex with the regulatory proteins raptor and GβL as described in detail in the text.
The activity of mTOR toward downstream targets such as 4E-BP1 and S6K1 is controlled in part through the interaction of mTOR with the regulatory proteins raptor and GβL. Evidence linking raptor with nutrient signaling through mTOR is provided by studies wherein raptor expression was downregulated using siRNA [33,34]. In such studies, leucine-induced phosphorylation of S6K1 is greatly repressed to an extent similar to that observed in cells in which mTOR expression is reduced. In part, leucine may modulate signaling through mTOR by altering the stability of the mTOR•raptor complex. In this regard, in one study the stability of the mTOR•raptor complex was found to be enhanced in cells subjected to amino acid deprivation [33]. However, a study by another group [35] failed to observe a change in binding of raptor to mTOR in cells starved for amino acids. In part, this discrepancy may be explained by the identification of GβL as a second mTOR-interacting protein [34]. Like raptor, GβL has been shown to co-immunoprecipitate with mTOR [34]. GβL is a positive regulator of mTOR because co-expression of GβL with mTOR results in greatly increased kinase activity of mTOR toward 4E-BP1 and S6K1 compared to expression of mTOR alone [34]. Moreover, reducing GβL expression using siRNA represses leucine- and serum-induced phosphorylation of S6K1 [34], suggesting that GβL is involved in hormone and amino acid signaling though mTOR. Importantly, GβL is necessary for leucine-mediated changes in mTOR•raptor association. In cells deprived of leucine, the binding of both raptor and GβL is high and readdition of leucine to leucine-deprived cells decreases the amount of raptor, but not GβL, associated with mTOR [34]. However, leucine-induced changes in mTOR•raptor association requires GβL, suggesting that the binding of GβL to mTOR renders the binding of raptor to mTOR sensitive to changes in amino acid availability.
The most proximal upstream protein that has been identified in the mTOR signaling pathway is the Ras homolog enriched in brain (Rheb). Rheb is a small G protein that enhances phosphorylation of S6K1, rpS6, and 4E-BP1 in an mTOR-dependent fashion when overexpressed [reviewed in [31,36]]. Moreover, in cells overexpressing Rheb, S6K1 phosphorylation is maintained during starvation for amino acids, suggesting that Rheb is involved in transducing signals from amino acids through mTOR [37,38]. Rheb activity is controlled in part by a GTPase activating protein (GAP) referred to as TSC2 or tuberin. TSC2, and its binding partner TSC1 (a.k.a. harmartin) were originally identified as the product of two genes that are causative in the autosomal dominant syndrome tuberous sclerosis [reviewed in [39-43]]. Mutations in either gene are associated with the widespread development of benign growths in multiple organs and tissues, suggesting that the normal role of these proteins is to restrict cell size and proliferation. This idea has been confirmed in studies in which the Drosophila orthologs of TSC1 and TSC2, dTsc1 and dTsc2, respectively, were shown to function in a complex that acts downstream of AKT but upstream of Drosophila TOR (dTOR) to restrict cell growth and proliferation [44-46]. Studies in both Drosophila [47] and mammalian cells [48] have implicated TSC1 and TSC2 in amino acid signaling through TOR. In Drosophila, downregulated expression of either protein causes cells to become resistant to amino acid deprivation [47]. Thus, S6K phosphorylation is largely maintained during amino acid starvation in cells with reduced expression of either dTsc1 or dTsc2 [47]. Similarly, in mammalian cells lacking either TSC1 or TSC2, S6K1 phosphorylation is resistant to amino acid deprivation [49]. Moreover, in mammalian cells in culture, co-overexpression of TSC1 and TSC2 prevents amino acid-dependent activation of S6K1 [48]. Together, these studies strongly suggest that TSC1 and TSC2 are required for amino acid induced signaling through mTOR.
The mechanism(s) involved in the regulation of TSC2 GAP activity are poorly understood, but likely involve phosphorylation of the protein by multiple upstream protein kinases. For example, TSC2 has been shown to be directly phosphorylated by AKT on multiple serine and threonine residues and phosphorylation by AKT represses the inhibitory action of the TSC1/TSC2 complex on signaling through mTOR to 4E-BP1 and S6K1 [50-53]. Likewise, phosphorylation of TSC2 by the MAP kinase regulated protein, MK2, reportedly inhibits TSC2 and leads to activation of mTOR [54]. In contrast, phosphorylation by the AMP-activated protein kinase (AMPK) on distinct residues activates TSC2 and results in repressed signaling through mTOR, suggesting that the GAP activity of TSC2 is enhanced by AMPK [55]. Until recently, the kinase that regulates AMPK was unknown. However, a recent study reports that LKB1 phosphorylates AMPK on the activating residue, Thr172, and likely represents an authentic AMPK kinase [56]. LKB1 was originally identified as a tumor suppressor that functions to limit cell growth, and is ubiquitously expressed in mammalian tissues [57,58]. Alone, LKB1 does not phosphorylate AMPK, but when complexed with two adapter proteins, STRAD and MO25, it exhibits potent AMPK activity [56]. Two isoforms (α and β) of each protein exist in human cells, and the complex of LKB1 with the α-isoform of each protein, i.e. LKB1•STRADα•MO25α, exhibits greater AMPK kinase activity compared to other permutations of the complex [56]. In addition to enhancing its AMPK kinase activity, STRAD and MO25 also target LKB1 to the cytoplasm; LKB1 normally is found primarily in the nucleus [59]. LKB has multiple phosphorylation sites and mutation of either Thr336 or Ser431 prevents LKB1 from inhibiting cell growth [60]; Thr336 is an autophosphorylation site, whereas Ser431 is phosphorylated by both PKA and p90rsk [61]. These studies provide a possible mechanism by which glucagon might downregulate mTOR activity, i.e. phosphorylation of LKB1 by PKA might repress the AMPK kinase activity of LKB1. However, such an idea is still speculative at this point as the effect of LKB1 phosphorylation by PKA on its ability to phosphorylate AMPK has yet to be investigated.
mRNA cis-acting elements mediating translational control
Changes in translation initiation can manifest as either altered translation of most or all mRNAs (i.e. global changes) or as altered translation of mRNAs encoding specific proteins. The mRNAs that encode proteins whose expression are specifically regulated through changes in mRNA translation (as opposed to changes in global mRNA translation) typically have one or more structural elements within the 5'-untranslated region (5'-UTR) that mediate translational control. Examples of such elements include multiple upstream open reading frames (uORF), internal ribosome entry sites (IRES), highly structured 5'-UTRs, terminal oligopyrimidine (TOP) tracts immediately downstream of the 5'-m7GTP cap, and binding domains for specific regulatory proteins (e.g. the iron-responsive element in the ferritin mRNA). Each of these elements serves to modulate the translation of a subset of mRNAs in response to various stimuli. For example, uORF elements repress the translation of most mRNAs under normal growth conditions. The translation of mRNAs bearing multiple uORFs is paradoxically enhanced in response to phosphorylation of the α-subunit of eIF2, an event that is associated with repressed translation of most mRNAs. The mechanism through which eIF2α phosphorylation enhances the translation of mRNAs containing multiple uORFs is complex and involves inhibition of the guanine nucleotide exchange activity of a second translation initiation factor, eIF2B, by phosphorylated eIF2. Examples of enhanced translation of mRNAs containing uORFs concomitant with eIF2α phosphorylation include the induction of the transcription factors ATF4 in mouse embryo fibroblasts deprived of amino acids (5) and CD36 in response to hyperglycemia (6) and the induction of the cationic amino acid transporter (CAT-1) in response to deprivation of amino acids [62] or glucose [63]. However, although enhanced translation of mRNAs with uORF sequences has been demonstrated in yeast and in cell lines, a similar phenomenon has not been demonstrated in an intact tissue.
A second 5'-UTR structure that allows preferential translation when eIF2α is phosphorylated is an IRES. An IRES allows the ribosome to bind to an internal site in the 5'-UTR and bypass the normal route of association with the mRNA, i.e. binding to the 5'-cap structure [reviewed in [64,65]]. The best characterized IRES-containing mRNA that is regulated by eIF2 phosphorylation is that encoding CAT-1 [62]. Like many IRES-containing mRNAs, the 5'-UTR of the CAT-1 mRNA has both an IRES and uORFs, and both elements are required for optimal regulation of CAT-1 mRNA translation. Thus, translation of an uORF adjacent to the IRES promotes a rearrangement of the IRES structure, resulting in its activation. However, this mechanism alone is unlikely to account completely for the enhanced translation of the CAT-1 mRNA because enhanced CAT-1 synthesis is delayed several hours after induction of eIF2α phosphorylation, suggesting that synthesis of another protein might be required for translation of the CAT-1 mRNA. Proteins that bind to IRES elements and modulate their function are referred to as IRES-transacting factors (ITAFs). Although poorly characterized, it has been suggested that ITAFs function as RNA chaperones that, upon binding to the IRES, promote refolding of the domain into the correct structure for 40S ribosome binding. Examples of ITAFs include the polypyrimidine tract binding protein (PTB) and upstream of N-ras (unr) that activate the Apaf-1 IRES [66].
Although eIF2α phosphorylation is one mechanism for enhancing the translation of mRNAs containing an IRES element(s), it is not unique. For example, during apoptosis or infection by certain types of viruses, eIF4G is cleaved. The normal function of eIF4G is to assemble the translation initiation factors eIF4A and eIF4E and the poly(A) binding protein into a complex that mediates the binding of mRNA to the 40S ribosomal subunit. Cleavage of eIF4G during apoptosis or viral infection separates the binding domain for PABP and the mRNA cap binding protein, eIF4E, from the domains that bind eIF4A and allow ribosome attachment (referred to as the middle fragment of eIF4G or M-FAG). A recent study reported that M-FAG generated in etoposide-treated cells M-FAG promotes the preferential translation of certain, but not all, IRES-containing mRNAs including Apaf-1 and death-associated protein (DAP)-5 [67]. Moreover, a number of IRES-containing mRNAs are preferentially translated under conditions that promote dephosphorylation or decreased function of eIF4E, for example when eIF4E is associated with one of the eIF4E binding proteins such as 4E-BP1. Thus, IRES function can be regulated through multiple mechanisms.
Another structural element within the 5'-UTR of some mRNAs that is involved in selective mRNA translation is an oligopyrimidine tract, referred to as a TOP sequence, immediately downstream of the 5'-cap structure [68,69]. Messages containing a TOP sequence include those encoding the ribosomal proteins, eukaryotic elongation factors-1A and 2, PABP, and eIF4G; in other words, proteins involved in protein synthesis. Thus, enhanced translation of TOP mRNAs is one mechanism for increasing ribosome biogenesis and the long-term capacity to synthesize protein. In liver of fasted rats, inhibition of mTOR by rapamycin prevents completely the leucine-induced phosphorylation of S6K1 and rpS6 as well as the increased association of TOP mRNAs with polysomes, suggesting an important role for S6K1 activation in the regulation of TOP mRNA translation [70]. Similarly, rapamycin prevents the feeding-induced increase in S6K1 phosphorylation in liver and skeletal muscle of neonatal pigs [71]. However, recent studies [72-74] suggest that activation of S6K1 may not be the only mechanism for enhancing translation of TOP mRNAs, although possible alternatives have not been identified.
Most mRNAs that are efficiently translated, e.g. GAPDH and β-actin, have 5'-UTRs that are short (<200 nt), have a low content of G and C residues, and are relatively unstructured [75]. In contrast, other mRNAs contain long, highly-structured 5'-UTRs. It isn't surprising that in order for the 40S ribosome to reach the AUG start codon of mRNAs with highly-structured 5'UTRs, the RNA helicase activity of eIF4A is essential. However, the results of a recent study suggest that both eIF4A and the eIF4A enhancer eIF4B are required for optimal translation of most mammalian mRNAs, including those such as the β-actin mRNA [76]. Although little is known about the mechanism(s) through which eIF4A and eIF4B might be regulated, eIF4B is phosphorylated on Ser422 in vitro by S6K1 and leucine-deprivation of cells in culture promotes dephosphorylation of eIF4B [77]. Thus, eIF4B phosphorylation by S6K1 provides a possible link between hormone and nutrient signaling through mTOR and eIF4A/eIF4B function.
Secondary structure may also function as a cis-acting regulatory element through the binding of specific trans-acting factors. A well-characterized example of such regulation is the modulation of ferritin and δ-aminolevulinate (ALA) synthase mRNA translation in response to changes in iron availability [78]. Both the ferritin and ALA synthase mRNAs contain hairpin structures near the 5'-end of their mRNAs, termed an iron-responsive element (IRE), that specifically binds to the IRE-binding proteins IRP1 and IRP2. Low intracellular iron enhances the IRE binding activity of IRP1 and the stability of IRP2 allowing them to bind to the IRE structure and stabilize it. Because of its proximity to the 5'-cap structure, the IREIRP1/2 complex blocks the binding of the 40S ribosome to the mRNA, thereby preventing translation of the ferritin and ALA synthase mRNAs.
Conclusions
Nutrients, and in particular certain amino acids, play important roles in the control of gene expression through their ability to modulate the initiation phase of mRNA translation. All essential amino acids have the potential to globally regulate mRNA translation through the eIF2α kinase mGCN2. In addition, changes in eIF2α phosphorylation can selectively modulate the translation of mRNAs encoding particular proteins if the 5'UTR of the mRNA contains uORFs and/or IRES elements. Selective control of mRNA translation can also occur through changes in signaling through mTOR. Activation of S6K1 by mTOR leads to phosphorylation of rpS6 and eIF4B which is thought to promote preferential translation of TOP mRNAs and mRNAs with highly structured 5'-UTRs, respectively. In addition, mTOR phosphorylates the eIF4E binding proteins leading to enhanced assembly of the eIF4F complex. In combination with eIF4B phosphorylation, enhanced eIF4F assembly leads to preferential translation of mRNAs with highly structured 5'-UTRs. Although other amino acids have been shown to increase signaling through mTOR, leucine is arguably the most potent of the amino acids in activating the pathway.
Authors' contributions
Both authors contributed equally to the writing of this manuscript.
Competing interests
None declared.
Acknowledgements
The studies described in this article that were performed in the laboratories of the authors were supported by research grants DK13499 and DK15658 from the National Institutes of Health.
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| 15507151 | PMC524028 | CC BY | 2021-01-04 16:37:45 | no | Nutr Metab (Lond). 2004 Aug 17; 1:3 | utf-8 | Nutr Metab (Lond) | 2,004 | 10.1186/1743-7075-1-3 | oa_comm |
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Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-1-41550714910.1186/1743-7075-1-4Researchβ3-adrenoceptor agonist prevents alterations of muscle diacylglycerol and adipose tissue phospholipids induced by a cafeteria diet Darimont Christian 1christian.darimont@rdls.nestle.comTurini Marco 1marco.turini@rdls.nestle.comEpitaux Micheline 1micheline.epitaux@rdls.nestle.comZbinden Irène 1irene.zbinden@rdls.nestle.comRichelle Myriam 1myriam.richelle@rdls.nestle.comMontell Eulàlia 2emontell@bio.ub.esFerrer-Martinez Andreu 2aferrer@bio.ub.esMacé Katherine 1catherine.mace@rdls.nestle.com1 Nestlé Research Center, P.O. Box 44, Vers-Chez-Les-Blanc, 1000 Lausanne 26, Switzerland2 Department de Bioquimica i Biologia Molecular, Universitat de Barcelona, Barcelona, Spain2004 17 8 2004 1 4 4 27 7 2004 17 8 2004 Copyright © 2004 Darimont et al; licensee BioMed Central Ltd.2004Darimont 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
Insulin resistance induced by a high fat diet has been associated with alterations in lipid content and composition in skeletal muscle and adipose tissue. Administration of β3-adrenoceptor (β3-AR) agonists was recently reported to prevent insulin resistance induced by a high fat diet, such as the cafeteria diet. The objective of the present study was to determine whether a selective β3-AR agonist (ZD7114) could prevent alterations of the lipid profile of skeletal muscle and adipose tissue lipids induced by a cafeteria diet.
Methods
Male Sprague-Dawley rats fed a cafeteria diet were treated orally with either the β3-AR agonist ZD7114 (1 mg/kg per day) or the vehicle for 60 days. Rats fed a chow diet were used as a reference group. In addition to the determination of body weight and insulin plasma level, lipid content and fatty acid composition in gastronemius and in epididymal adipose tissue were measured by gas-liquid chromatography, at the end of the study.
Results
In addition to higher body weights and plasma insulin concentrations, rats fed a cafeteria diet had greater triacylglycerol (TAG) and diacylglycerol (DAG) accumulation in skeletal muscle, contrary to animals fed a chow diet. As expected, ZD7114 treatment prevented the excessive weight gain and hyperinsulinemia induced by the cafeteria diet. Furthermore, in ZD7114 treated rats, intramyocellular DAG levels were lower and the proportion of polyunsaturated fatty acids, particularly arachidonic acid, in adipose tissue phospholipids was higher than in animals fed a cafeteria diet.
Conclusions
These results show that activation of the β3-AR was able to prevent lipid alterations in muscle and adipose tissue associated with insulin resistance induced by the cafeteria diet. These changes in intramyocellular DAG levels and adipose tissue PL composition may contribute to the improved insulin sensitivity associated with β3-AR activation.
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Background
Dietary fatty acids are known to influence the composition of stored triacylglycerol (TAG) and membrane phospholipids (PL) in adipose tissue [1]. More recently, it was demonstrated that the lipid profile in skeletal muscle reflected dietary lipids [2-4]. Furthermore, the modifications of fatty acid concentrations and composition in tissue lipids induced by a high fat diet has been associated with alterations in lipid metabolism and insulin sensitivity [5,6]. Indeed, enrichment of membrane PL with saturated fatty acids (SFA) was able to impair insulin action in skeletal muscle and adipose tissue, whereas a higher proportion of polyunsaturated fatty acids (PUFA) improved insulin sensitivity in these tissues [7-9]. TAG accumulation in skeletal muscle was also correlated with the development of insulin resistance, independent to the degree of obesity [10-13]. Intramyocellular TAG could represent only a marker of insulin resistance whereas intracellular accumulation of long chain acyl-coenzyme A, ceramide or diacylglycerol (DAG) were reported to directly alter the insulin action [14].
Chronic activation of the β3-adrenoceptor (β3-AR), which is predominantly expressed in white and brown adipose tissue, by selective agonists exerts both anti-obesity and anti-diabetic effects in rodent models of obesity [15,16]. Activation of this receptor has been reported to enhance energy expenditure via stimulation of thermogenesis in brown adipose tissue [16]. The improvement in glucose homeostasis induced by β3-AR agonists appears to be a consequence of increased insulin sensitivity in peripheral tissues rather than stimulation of insulin secretion by the pancreas [17]. Although, the expression of β3-AR in myocytes is still a matter of debate [18-20], obese rats treated with β3-AR agonists demonstrated an improvement of insulin sensitivity in brown and white adipose tissue as well as in skeletal muscle [17,21,22]. In adipose tissue this effect is believed to be mediated by the conversion of large adipocytes into small adipocytes, which are more sensitive to insulin [21]. In skeletal muscle, it seems more likely that the effects of β3-AR agonists on insulin sensitivity are mediated by alternate indirect mechanisms.
The objective of the present study was to determine whether a selective β3-AR agonist could prevent alterations in the profile of skeletal muscle and adipose tissue lipids induced with the consumption of the cafeteria diet, previously reported to induce weight gain and hyperinsulinemia [22,23]. The selective β3-AR agonist ZD7114 was used in this study. When administered at 1 mg/kg/day, this compound has been shown to increase thermogenesis in rodents and dogs without increasing heart rate or β2-AR-mediated effects such as tremor [24]. ZD7114 pharmacological specificity was also demonstrated in brown adipocytes and smooth muscles [25,26]. As expected, we observed that a chronic treatment with the ZD7114 prevented the development of excessive fat mass and hyperinsulinemia induced by this diet. These preventive beneficial effects exerted by the β3-AR agonist were associated with a reduction of muscle DAG accumulation. In adipose tissue, ZD7114 treatment was able to limit the proportional reduction of PUFA into the PL pool, induced by the cafeteria diet. Our results indicate that a β3-AR agonist prevents some cafeteria diet-induced alterations of the fatty acid profile of lipids in skeletal muscle and adipose tissue. Furthermore, we propose that these changes may contribute to the improved of insulin sensitivity observed in rats treated with a β3-AR agonist during the development of obesity.
Methods
Animal study
Male Sprague-Dawley rats were purchased from Charles River (L'arbesles, France) at 5–6 weeks of age. Animals were individually housed in temperature-controlled rooms (22°C) with a 12-h light-dark cycle. Ten days before the beginning of the study, 30 rats were provided a normal chow diet (Kliba-Nafalg, Switzerland) and free access to drinking water. At the end of this period, rats were weighed and pre-selected for their sensitivity to weight gain (i.e. rat presenting at least 35% weight gain after a 10-day selection period). The selected rats (n = 15) were equally randomized into 3 groups. A reference group, consisted of rats fed for 60 days with a standard pellet chow diet containing 28, 57 and 15% E from protein, carbohydrate and fat, respectively (REF group). The remaining rats were fed for 60 days with a cafeteria diet composed of 30 g of a mix containing salami, cookies, cheese, sausage, chips, chocolate and almonds in a proportion of 2:2:2:1:1:1:1 and 30 g of the reference group chow diet. This mixed diet contained 26, 27 and 47% energy as protein, carbohydrate and fat, respectively. At the beginning of the dietary intervention, both groups fed the cafeteria diet received daily, by gavage (0.5 ml/100 g body weight), either the selective β-3AR agonist ZD7114 at 1 mg/kg per day (CAF-ZD group) or water alone (CAF group) until day 60. Rats from the REF group (chow diet) also received a daily gavage of water (0.5 ml/100 g body weight).
Body weight and food intake were recorded daily. Rats were fasted for 8 hours before sacrifice, performed under isoflurane anaesthesia. Tissues were immediately collected, weighed, frozen in liquid nitrogen and kept at -80°C until analysed.
All procedures in the study were in compliance with the ethical committee of the "Service vétérinaire du canton de Vaud".
Estimation of the proportions of the different lipid classes contained in the cafeteria diet (see Discussion) was performed using the USDA Nutrient Database.
Lipid fatty acid composition
Adipose tissue
Fatty acid composition of lipids in adipose tissue was performed by Lipomics Technologies (West Sacramento, USA). Briefly, lipids were extracted from 30 mg of frozen epididymal adipose tissue in the presence of authentic internal standards by the method of Folch et al. [27] using chloroform:methanol (2:1, by vol.). After separation of individual lipid classes by preparative thin-layer chromatography, the TAG and PL were scraped and trans-esterified; the resulting fatty acid methyl esters were then separated and quantified by capillary gas chromatography as previously described [28].
Muscle
The frozen gastrocnemius muscle was thawed and thoroughly dissected under stereomicroscope to remove extramyocellular adipose tissue. Lipids from lyophilized, finely powdered, dissected muscle (50 mg) were extracted according to the method of Folch [27]. PL (19:0), TAG (17:0) and DAG (15:0) internal standards (Varian; Zug, Switzerland) were added prior to lipid extraction. The lipids were loaded on a Chromabond NH2 cartridge (Varian; Zug, Switzerland), and neutral lipids were separated from free fatty acids and PL by sequential elution with chloroform/2-Propanol (2:1), 2% acetic acid in diethylether and methanol, respectively [29]. The neutral lipids were subjected to thin-layer chromatography using hexane:diethylether:acetic acid (70:30:1, by vol.) as solvent system to separate DAG from TAG [30]. The hydrolysis of TAG into DAG during sample analysis has been assessed and represented less than 0.5% of total DAG. The fatty acids from the phospholipids, TAG and DAG were converted to their methyl esters. Fatty acid methyl-ester separation was performed by automated gas-liquid chromatography (HP 6890 series) with FID detection (280°C); authentic standard mixtures of fatty acid methyl-esters (Nu-Chek-Perp; Lowell Mutter, USA) were injected to identify fatty acid methyl-ester peaks. Results are expressed in μmol fatty acids per gram lyophilised muscle.
Plasma metabolites
Plasma glucose and insulin were determined with commercially available kits purchased from Sigma (Buchs, Switzerland) and Crystal Chem Inc. (Downers Grove, USA), respectively. Plasma triglycerides and free fatty acids concentrations were analysed using kits from Roche Diagnostic (Basel, Switzerland) and Wako Chemicals (Richmond, USA), respectively.
Statistical analysis
Comparisons of the means of the dependent variables of each group were performed using a one-way ANOVA.
Results
Body weight and fat mass
Male Sprague-Dawley rats were fed, during 60 days, either a chow diet used as a reference group (REF group), a cafeteria diet (CAF rats) or a cafeteria diet plus a daily gavage of the β3-AR agonist ZD7114 (CAF-ZD rats).
At day 60, the mean body weight of CAF rats was significantly greater than that of REF rats (Table 1). On the other hand, CAF-ZD rats presented a significant reduction in mean body weight when compared with CAF rats (Table 1). Similar effects were observed on weight gain which was 46% greater in CAF rats than in REF rats (Figure 1; 213.2 ± 12.2 g vs. 312.3 ± 19.2 g in REF and CAF rats, respectively; p < 0.01), and reduced by 17% in CAF-ZD rats as compared to CAF rats (258.70 ± 12.70 g in CAF-ZD rats, p < 0.05). The enhancement of body weight in CAF rats was strongly associated with the weight increase of two main deep adipose depots, confirming the obesigenic properties of the cafeteria diet. Indeed, the epididymal and retroperitoneal fat pads in CAF rats were respectively 131% and 185% heavier than those of REF rats (Table 1). ZD7114 treatment decreased the weight of the two adipose tissue depots by about 45%, compared to CAF rats (Table 1). The weights of gastrocnemius skeletal muscle, liver and heart were not different between groups (Table 1). As expected, CAF rats had a higher energy intake compared with REF animals (106.03 ± 7.25 vs 78.49 ± 2.96 kcal/day). However, the anti-obesity effect of ZD7114 was not attributed to a reduction of energy intake (107.70 ± 7.30 kcal/day in CAF-ZD rats).
Table 1 Body weight, tissues and fasting plasma metabolites
REF CAF CAF-ZD
Final body weight (g) 443.78 ± 21.42 540.20 ± 16.69 * 477.82 ± 12.09 +
Retroperitoneal (g) 3.73 ± 0.44 10.65 ± 0.48 ** 5.78 ± 0.23 +
Epididymal (g) 4.65 ± 0.41 10.73 ± 0.43 ** 5.96 ± 0.30 +
Gastrocnemius (g) 2.69 ± 0.13 2.78 ± 0.01 2.79 ± 0.03
Heart (g) 1.25 ± 0.07 1.48 ± 0.01 1.46 ± 0.02
Liver (g) 13.53 ± 0.79 16.69 ± 0.15 15.47 ± 0.12
Glucose (mmol/l) 12.80 ± 1.51 12.10 ± 1.02 14.78 ± 1.11
Insulin (μU/ml) 19.75 ± 2.05 98.04 ± 16.01 ** 43.27 ± 8.26 +
Fatty acid (mmol/l) 0.47 ± 0.22 0.42 ± 0.68 0.30 ± 0.39 **
Triacylglycerol (mmol/l) 2.27 ± 0.30 4.59 ± 0.58 ** 4.11 ± 0.95
Data are the mean ± SEM. Values significantly different from those obtained in the group of rats fed a chow diet (REF) are indicated by * (p < 0.05) and ** (p < 0.01). Data measured in the group of rats treated with ZD7114 (CAF-ZD) and significantly different from those in the group of rats fed a cafeteria diet (CAF) are shown by + (p < 0.05).
Figure 1 Individual weight changes. Body weight was measured in rats (n = 5) fed a chow diet (REF) or a cafeteria diet alone (CAF) or treated with 1 mg/kg/day ZD7114 (CAF-ZD) at the beginning and at the end of the different interventions (day 60). Data are represented as individual values.
Glucose and insulin plasma concentrations
Measurement of insulin and glucose concentrations in plasma of fasted animals showed that CAF rats presented a marked hyperinsulinemia with a 4.6 fold increase in insulin concentration as compared to REF animals whereas the glucose level was not changed (Table 1). ZD7114 treatment limited the hyperinsulinemia induced by the cafeteria diet, as demonstrated by the 2.3 fold decrease in plasma insulin concentrations in CAF-ZD rats compared with the CAF group (Table 1). No significant changes in plasma glucose concentrations were observed between these two groups (Table 1).
Adipose tissue lipids
Lipid content
PL and TAG contents per gram of tissue were measured in epididymal adipose tissue of rats fed with a chow diet or a cafeteria diet treated or not with ZD7114. No significant change was observed in the concentration of PL and TAG in adipose tissue of CAF rats when compared with REF animals (Table 2). Furthermore, ZD7114 treatment did not affect adipose tissue lipid content of CAF rats.
Table 2 Adipose tissue lipid content
μmole/g tissue REF CAF CAF-ZD
Phospholipids 8.29 ± 1.28 10.59 ± 1.06 8.65 ± 0.87
Triacylglycerol 2476.34 ± 68.31 2462.63 ± 41.33 2271.57 ± 122.46
Data are the mean ± SEM. REF: rats fed a chow diet; CAF: rats fed a cafeteria die, CAF-ZD: rats fed a cafeteria diet and treated with ZD7114
Fatty acid composition
Analysis of the fatty acid profile shows that cafeteria diet induced an increase in the proportion of monounsaturated fatty acids (MUFA), which was compensated for by a reduction in the percentage of PUFA in both adipose PL and TAG (Figure 2). Changes in the proportion of MUFA in PL and TAG were mainly due to the increase of oleic acid (1.7 and 2.0 fold increase in PL and TAG, respectively; Table 3). Reduction in the percentage of linoleic acid was mainly responsible for the decrease in proportion of PUFA in both PL and TAG (1.6 and 2.3 fold decrease for PL and TAG, respectively; Table 3). The proportions of arachidonic and α-linolenic acids were also slightly decreased in PL and TAG, respectively (Table 3). Although the global proportion of SFA was not modified in adipose tissue PL and TAG of CAF rats when compared with REF animals, the percentage of myristic and stearic acids were respectively enhanced in PL and TAG of CAF animals.
Figure 2 Proportion of the different lipid classes in adipose tissue. Saturated (SFA), monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA) were measured in epididymal adipose tissue phospholipid (PL) and triacylglycerol (TAG) of rats fed a chow diet (empty bars) or a cafeteria diet (black bars) alone or treated with ZD7114 (grey bars). Data are represented as mean ± SEM, and values significantly different to data measured in rats fed the chow or cafeteria diets are indicated by * (p < 0.05), ** (p < 0.01) or + (p < 0.05), respectively.
Table 3 Composition of adipose tissue lipids
% mole fatty acids REF CAF CAF-ZD
Phospholipids
Myristic acid (14:0) 3.04 ± 0.16 3.81 ± 0.19 * 2.96 ± 0.15 ++
Palmitic acid (16:0) 28.70 ± 3.10 30.72 ± 1.83 26.22 ± 1.70
Stearic acid (18:0) 15.99 ± 1.19 16.10 ± 0.75 16.93 ± 0.50
Palmitoleic acid (16:1n-7) 1.17 ± 0.28 1.35 ± 0.31 1.16 ± 0.29
Oleic acid (18:1n-9) 10.74 ± 0.94 18.17 ± 1.60 ** 16.26 ± 1.39 *
Vaccenic acid (18:1n-7) 1.24 ± 0.12 0.89 ± 0.07 * 0.98 ± 0.10
Linoleic acid (18:2n-6) 21.21 ± 1.98 13.27 ± 1.20 ** 16.41 ± 1.55 *
Eicosadienoic acid (20:2n-6) 2.16 ± 1.37 0.92 ± 0.92 0.37 ± 0.37
Arachidonic acid (20:4n-6) 7.69 ± 0.73 4.47 ± 1.23 * 8.90 ± 1.35 +
Triacylglycerol
Myristic acid (14:0) 1.23 ± 0.03 1.33 ± 0.08 1.39 ± 0.28
Palmitic acid (16:0) 21.80 ± 0.29 21.48 ± 0.63 21.02 ± 0.65
Stearic acid (18:0) 3.35 ± 0.15 5.27 ± 0.35 ** 4.84 ± 1.68 *
Palmitoleic acid (16:1n-7) 2.50 ± 0.27 2.29 ± 0.34 2.44 ± 0.46
Oleic acid (18:1n-9) 24.37 ± 1.04 48.87 ± 1.35 ** 47.09 ± 0.20 **
Vaccenic acid (18:1n-7) 1.98 ± 0.12 1.59 ± 0.12 1.73 ± 1.20
Linoleic acid (18:2n-6) 38.22 ± 1.36 16.59 ± 0.72 ** 18.37 ± 0.16 **
α-linolenic acid (18:3n-3) 2.85 ± 0.16 0.67 ± 0.06 ** 0.71 ± 0.20 **
Data are the mean ± SEM. Values significantly different from those obtained in the group of rats fed a chow diet (REF) are indicated by * (p < 0.05) and ** (p < 0.01). Data measured in the group of rats treated with ZD7114 (CAF-ZD) and significantly different from those in the group of rats fed a cafeteria diet (CAF) are shown by + (p < 0.05) and ++ (p < 0.05). Only main fatty acids are presented. CAF-ZD: rats fed a cafeteria diet and treated with ZD7114.
ZD7114 treatment did not change the proportions of any lipid classes measured in adipose TAG of CAF rats (Figure 2). However, in PL, the percentage of PUFA was significantly increased by 1.3 fold in CAF-ZD rats compared to CAF animals. This change was essentially due to a two-fold increase in the proportion of arachidonic acid measured in CAF-ZD rats (Table 3). A slight reduction in the percentage of myristic acid (1.2 fold decrease) was measured in CAF-ZD rats compared to CAF animals.
Skeletal muscle lipids
Lipid content
PL, diacylglycerol (DAG) and TAG contents were measured in the gastrocnemius of REF animals and CAF rats with or without ZD7114 treatment (Table 4).
Figure 3 Proportion of the different lipid classes in muscle. Saturated (SFA), monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA) were measured in muscle phospholipid (PL), triacylglycerol (TAG) and diacylglycerol (DAG) of rats fed a chow diet (empty bars), a cafeteria diet (black bars) alone or treated with ZD7114 (grey bars). Data are represented as mean ± SEM, and values significantly different to data measured in rats fed the chow or cafeteria diet are indicated by * (p < 0.05), ** (p < 0.01) or + (p < 0.05), ++ (p < 0.01), respectively.
The cafeteria diet clearly induced TAG and DAG accumulation in the gastrocnemius, as demonstrated by the respective 3.4 and 2.0 fold increases observed in CAF vs. REF rats (Table 4). Chronic treatment with ZD7114 did not significantly reduce the cafeteria diet induced-accumulation of TAG in muscle. In contrast, DAG accumulation was prevented as indicated by a 1.5 fold reduction of DAG levels in CAF-ZD when compared with CAF rats (Table 4). Values of intramyocellular TAG and DAG obtained in the present study (TAG: between 1 to 4 μmol/g fresh muscle; DAG: between 0.5 to 1 μmol/g fresh muscle) were similar to those previously described in rat skeletal muscles [31] (TAG: between 4 to 5 μmol/g fresh muscle; DAG: between 0.5 to 2.5 μmol/ g fresh muscle).
Table 4 Muscle lipid content
μmole/g tissue REF CAF CAF-ZD
Phospholipids 60.31 ± 4.28 65.62 ± 1.26 70.80 ± 2.77
Triacylglycerol 5.40 ± 0.98 18.63 ± 3.24 ** 15.65 ± 2.57 **
Diacylglycerol 2.07 ± 0.32 4.08 ± 0.24 ** 2.66 ± 0.25 ++
Data are the mean ± SEM. Values significantly different from those obtained in the group of rats fed a chow diet (REF) are indicated by ** (p < 0.01). Data measured in the group of rats treated with ZD7114 (CAF-ZD) and significantly different from those in the group of rats fed a cafeteria diet (CAF) are shown by ++ (p < 0.05).
Fatty acid composition
Fatty acid profiles were determined in muscle PL, TAG and DAG. The gastrocnemius of CAF rats, compared with the REF group, presented an increase in the percentage of MUFA and a decrease in the proportion of PUFA in both TAG and DAG and to a lesser extent in PL (Figure 3). Variations in the percentage of oleic and linoleic acids were, respectively, responsible for the changes in the proportions of MUFA and PUFA in muscle TAG and DAG (Table 5). Modifications of the proportions of PUFA observed in muscle PL of CAF rats were due to slight decreases of both linoleic (1.4 fold increase) and docosahexaenoic (22:6 n-3) acids (1.3 fold increase), whereas the percentage of arachidonic acid (20:4 n-6) was increased by 1.2 fold.
Table 5 Composition of muscle lipids
% mole fatty acids REF CAF CAF-ZD
Phospholipids
Palmitic acid (16:0) 27.87 ± 0.50 26.17 ± 0.29 26.44 ± 0.57
Stearic acid (18:0) 20.21 ± 0.64 22.37 ± 0.54 * 21.64 ± 0.58
Oleic acid (18:1n-9) 6.84 ± 0.21 9.13 ± 0.48 ** 9.12 ± 0.24 **
Linoleic acid (18:2n-6) 13.09 ± 0.65 8.98 ± 0.51** 9.02 ± 0.28 **
Arachidonic acid (20:4n-6) 11.64 ± 0.46 15.07 ± 0.53** 14.11 ± 0.22 **
Docosatetraenoic acid (22:4n-6) ND 0.61 ± 0.04 0.51 ± 0.02
Adrenic acid (22:5n-3) 2.04 ± 0.07 2.44 ± 0.18 2.10 ± 0.09
Docosahexaenoic acid (22:6n-3) 18.30 ± 0.95 15.23 ± 0.52 * 16.09 ± 0.35
Triacylglycerol
Myristic acid (14:0) ND 1.66 ± 0.08 1.53 ± 0.06
Palmitic acid (16:0) 37.13 ± 2.06 25.26 ± 0.95 ** 25.15 ± 0.81 **
Stearic acid (18:0) 7.94 ± 0.31 9.36 ± 0.45 * 9.38 ± 0.65
Palmitoleic acid (16:1n-7) ND 1.51 ± 0.14 1.31 ± 0.13
Oleic acid (18:1n-9) 29.00 ± 0.94 51.36 ± 1.83 ** 50.14 ± 0.93 **
Linoleic acid (18:2n-6) 25.00 ± 1.98 10.86 ± 0.83 ** 12.47 ± 0.66 **
Diacylglycerol
Myristic acid (14:0) 1.92 ± 0.09 1.75 ± 0.07 1.85 ± 0.05
Palmitic acid (16:0) 25.55 ± 0.86 22.42 ± 1.22 24.88 ± 0.62
Stearic acid (18:0) 6.71 ± 0.45 8.74 ± 0.63 * 9.71 ± 0.08 **
Palmitoleic acid (16:1n-7) 2.58 ± 0.20 1.59 ± 0.14 ** 1.26 ± 0.07 **
Oleic acid (18:1n-9) 28.90 ± 1.24 52.88 ± 1.25 ** 46.45 ± 1.61 ** ++
Nervonic acid (24:1n-9) 3.92 ± 1.93 1.24 ± 0.42 2.71 ± 0.88
Linoleic acid (18:2n-6) 26.96 ± 2.22 10.14 ± 2.04 ** 8.05 ± 0.69 **
α-linolenic acid (18:3n-3) 1.12 ± 0.18 ND ND
Stearidonic acid (18:4n-3) ND ND 1.90 ± 0.41
Arachidonic acid (20:4n-6) 0.78 ± 0.06 0.46 ± 0.06 ** 0.26 ± 0.04 ** +
Data are the mean ± SEM. Values significantly different from those obtained in the group of rats fed a chow diet (REF) are indicated by * (p < 0.05) and ** (p < 0.01). Data measured in the group of rats treated with ZD7114 (CAF-ZD) and significantly different from those in the group of rats fed a cafeteria diet (CAF) are shown by + (p < 0.05) and ++ (p < 0.05). Fatty acids representing more than 1% in at least one group are presented.
The influence of ZD7114 on the cafeteria-induced modification of fatty acid composition in the three lipid species was evaluated by comparing CAF rats with CAF-ZD rats. While ZD7114 did not affect the fatty acid profile of either TAG or PL in muscle of CAF rats, it induced changes in the fatty acid composition of muscle DAG. Indeed, the proportion of SFA was slightly (1.2 fold increase), but significantly, elevated in DAG of CAF-ZD rats with an increase in the proportion of palmitic and stearic acids (Table 5). Furthermore, the proportion of MUFA in DAG of CAF-ZD rat muscles was decreased compared with DAG of CAF rats. This change was essentially attributed to a decrease in the proportion of oleic acid (Table 5). Stearidonic acid (18.4 n-3) was only detected in DAG accumulated in muscles of ZD-CAF rats. No differences in the proportion of PUFA between DAG stored in muscles of CAF-ZD or CAF rats were observed (Figure 3).
Discussion
The present study demonstrates that feeding the cafeteria diet to rats not only promotes weight gain, hyperinsulinemia and hypertriglyceridemia, but also accumulation of lipids in skeletal muscle. Although TAG levels per gram of adipose tissue was not affected by the cafeteria diet, this dietary intervention strongly enhanced TAG accumulation in skeletal muscle, as previously described [4,5]. We show that this intramyocellular accumulation of TAG was associated with an increase in skeletal muscle DAG content. This finding is in agreement with the accumulation of DAG observed in human skeletal muscle cells incubated with saturated fatty acids in vitro [12]. DAG mass was also described to be increased in skeletal muscle biopsies obtained from normal volunteers in whom insulin resistance was produced by raising FFA levels during a lipid infusion [32]. However, to our knowledge, the present study demonstrates for the first time that a high fat diet, resembling the human Western diet, was able to increase DAG storage in skeletal muscle. Although both TAG and DAG accumulations in skeletal muscle were reported to be correlated with insulin resistance [4,5,33], DAG (a precursor of TAG synthesis) is proposed to directly impair insulin sensitivity by inactivating insulin receptor activity through activation of the protein kinase C [34].
The fatty acid composition of TAG stored in muscle was previously shown to be affected by dietary lipids [2]. Interestingly, we also find that the fatty acid composition of muscle DAG was modified by the cafeteria diet. Indeed, the increase in MUFA and the reduction of PUFA proportions, measured in both DAG and TAG, reflected the difference in lipid composition of the two diets (+ 19% MUFA and -28% PUFA in cafeteria diet vs. chow diet). It is noteworthy that qualitative changes in DAG were reported to affect the activity of DAG as a secondary messenger, since specificity of its fatty acyl moieties for the activation of protein kinase C has been described [35,36]. Although measurements of insulin sensitivity were not directly accessed in this study, our observation suggests that diet may regulate insulin response in muscle by modifying DAG composition.
Fatty acid compositions of muscle and adipose tissue PL were also modified by the cafeteria diet. More specifically, the proportion of PUFA in PL was decreased and MUFA was increased in both tissues. These differences were more pronounced in PL from adipose tissue than from gastrocnemius, indicating that membrane phospholipids in adipose tissue are more susceptible to variations in dietary composition than skeletal muscle. Interestingly, reductions in the proportion of PUFA in PL from myocytes [7] and adipocytes [8] were reported to impair insulin action.
As previously reported with Trecadrine, a selective β3-AR agonist [22], chronic administration of ZD7114 prevented the excess weight gain and fat accumulation induced by a cafeteria diet. This present report demonstrates that ZD7114 treatment reduced the hyperinsulinemia elicited by the cafeteria diet (by 2.3 fold), thereby suggesting an improvement of insulin sensitivity in the treated rats. This observation was associated with a significant reduction in the accumulation of skeletal muscle DAG, and a slight, non-significant decrease in TAG. It is tempting to suggest that the decrease in muscle DAG accumulation induced by the chronic administration of a β3-AR agonist could participate in the prevention of hyperinsulinemia. β3-AR agonist treatment significantly modified the fatty acid composition of DAG, causing a 1.2 fold reduction in the proportion of oleic acid. As mentioned before, these modifications in DAG composition could directly regulate insulin action in muscles. Since the presence of a β3-AR in skeletal muscle is still a subject of debate, it is difficult to elucidate the mechanism(s) by which the β3-AR agonist lowers DAG content in muscle and modifies its fatty acid composition.
Although the content and the fatty acid composition of TAG stored in adipose tissue was not affected by β3-AR agonist administration, the fatty acid profile of adipose PL was modified by the treatment. The β3-AR agonist was able to restore the proportion of PUFA to a level similar to the REF rats by increasing the percentage of arachidonic acid by 2 fold. As mentioned above, a greater percentage of PUFA in PL has been reported to enhance insulin sensitivity in adipose tissue. The changes in PL composition induced by the β3-AR agonist may be associated with the previously reported improved insulin sensitivity in adipose tissue [8], and the decrease of hyperinsulinemia measured in the present study.
Conclusions
Whilst the effectiveness of β3-AR agonists is limited in humans, understanding the metabolic changes affected in rodents will provide insights into mechanisms, underlying insulin responsiveness in humans. The present study demonstrates that β3-AR agonist treatment not only limits the hyperinsulinemia induced by a cafeteria diet, but also partially prevents the associated alterations in adipose and muscle lipid composition. Particularly, activation of the β3-AR limits the intramyocellular DAG accumulation and the decrease in the proportion of PUFA in adipose tissue PL. This combined action may contribute to the beneficial effect of β3-AR agonists on insulin sensitivity.
List of abbreviations
CAF rats: Rats fed with a cafeteria diet; DAG: Diacylglycerol; MUFA: Monounsaturated fatty acid; PKC: Protein kinase C; PUFA: Polyunsaturated fatty acid; REF rats: Rats fed with a chow diet; SFA: saturated fatty acid. TAG: Triacylglycerol; ZD-CAF rats: Rats fed with a cafeteria diet and treated with the β3-AR agonist ZD7114.
Acknowledgments
The authors are grateful to Dr. K. Acheson and D. M. Mutch (Nestlé Research Center, Lausanne, Switzerland) for critically reading the manuscript.
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| 15507149 | PMC524029 | CC BY | 2021-01-04 16:37:45 | no | Nutr Metab (Lond). 2004 Aug 17; 1:4 | utf-8 | Nutr Metab (Lond) | 2,004 | 10.1186/1743-7075-1-4 | oa_comm |
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Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-1-41550714910.1186/1743-7075-1-4Researchβ3-adrenoceptor agonist prevents alterations of muscle diacylglycerol and adipose tissue phospholipids induced by a cafeteria diet Darimont Christian 1christian.darimont@rdls.nestle.comTurini Marco 1marco.turini@rdls.nestle.comEpitaux Micheline 1micheline.epitaux@rdls.nestle.comZbinden Irène 1irene.zbinden@rdls.nestle.comRichelle Myriam 1myriam.richelle@rdls.nestle.comMontell Eulàlia 2emontell@bio.ub.esFerrer-Martinez Andreu 2aferrer@bio.ub.esMacé Katherine 1catherine.mace@rdls.nestle.com1 Nestlé Research Center, P.O. Box 44, Vers-Chez-Les-Blanc, 1000 Lausanne 26, Switzerland2 Department de Bioquimica i Biologia Molecular, Universitat de Barcelona, Barcelona, Spain2004 17 8 2004 1 4 4 27 7 2004 17 8 2004 Copyright © 2004 Darimont et al; licensee BioMed Central Ltd.2004Darimont 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
Insulin resistance induced by a high fat diet has been associated with alterations in lipid content and composition in skeletal muscle and adipose tissue. Administration of β3-adrenoceptor (β3-AR) agonists was recently reported to prevent insulin resistance induced by a high fat diet, such as the cafeteria diet. The objective of the present study was to determine whether a selective β3-AR agonist (ZD7114) could prevent alterations of the lipid profile of skeletal muscle and adipose tissue lipids induced by a cafeteria diet.
Methods
Male Sprague-Dawley rats fed a cafeteria diet were treated orally with either the β3-AR agonist ZD7114 (1 mg/kg per day) or the vehicle for 60 days. Rats fed a chow diet were used as a reference group. In addition to the determination of body weight and insulin plasma level, lipid content and fatty acid composition in gastronemius and in epididymal adipose tissue were measured by gas-liquid chromatography, at the end of the study.
Results
In addition to higher body weights and plasma insulin concentrations, rats fed a cafeteria diet had greater triacylglycerol (TAG) and diacylglycerol (DAG) accumulation in skeletal muscle, contrary to animals fed a chow diet. As expected, ZD7114 treatment prevented the excessive weight gain and hyperinsulinemia induced by the cafeteria diet. Furthermore, in ZD7114 treated rats, intramyocellular DAG levels were lower and the proportion of polyunsaturated fatty acids, particularly arachidonic acid, in adipose tissue phospholipids was higher than in animals fed a cafeteria diet.
Conclusions
These results show that activation of the β3-AR was able to prevent lipid alterations in muscle and adipose tissue associated with insulin resistance induced by the cafeteria diet. These changes in intramyocellular DAG levels and adipose tissue PL composition may contribute to the improved insulin sensitivity associated with β3-AR activation.
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Background
Dietary fatty acids are known to influence the composition of stored triacylglycerol (TAG) and membrane phospholipids (PL) in adipose tissue [1]. More recently, it was demonstrated that the lipid profile in skeletal muscle reflected dietary lipids [2-4]. Furthermore, the modifications of fatty acid concentrations and composition in tissue lipids induced by a high fat diet has been associated with alterations in lipid metabolism and insulin sensitivity [5,6]. Indeed, enrichment of membrane PL with saturated fatty acids (SFA) was able to impair insulin action in skeletal muscle and adipose tissue, whereas a higher proportion of polyunsaturated fatty acids (PUFA) improved insulin sensitivity in these tissues [7-9]. TAG accumulation in skeletal muscle was also correlated with the development of insulin resistance, independent to the degree of obesity [10-13]. Intramyocellular TAG could represent only a marker of insulin resistance whereas intracellular accumulation of long chain acyl-coenzyme A, ceramide or diacylglycerol (DAG) were reported to directly alter the insulin action [14].
Chronic activation of the β3-adrenoceptor (β3-AR), which is predominantly expressed in white and brown adipose tissue, by selective agonists exerts both anti-obesity and anti-diabetic effects in rodent models of obesity [15,16]. Activation of this receptor has been reported to enhance energy expenditure via stimulation of thermogenesis in brown adipose tissue [16]. The improvement in glucose homeostasis induced by β3-AR agonists appears to be a consequence of increased insulin sensitivity in peripheral tissues rather than stimulation of insulin secretion by the pancreas [17]. Although, the expression of β3-AR in myocytes is still a matter of debate [18-20], obese rats treated with β3-AR agonists demonstrated an improvement of insulin sensitivity in brown and white adipose tissue as well as in skeletal muscle [17,21,22]. In adipose tissue this effect is believed to be mediated by the conversion of large adipocytes into small adipocytes, which are more sensitive to insulin [21]. In skeletal muscle, it seems more likely that the effects of β3-AR agonists on insulin sensitivity are mediated by alternate indirect mechanisms.
The objective of the present study was to determine whether a selective β3-AR agonist could prevent alterations in the profile of skeletal muscle and adipose tissue lipids induced with the consumption of the cafeteria diet, previously reported to induce weight gain and hyperinsulinemia [22,23]. The selective β3-AR agonist ZD7114 was used in this study. When administered at 1 mg/kg/day, this compound has been shown to increase thermogenesis in rodents and dogs without increasing heart rate or β2-AR-mediated effects such as tremor [24]. ZD7114 pharmacological specificity was also demonstrated in brown adipocytes and smooth muscles [25,26]. As expected, we observed that a chronic treatment with the ZD7114 prevented the development of excessive fat mass and hyperinsulinemia induced by this diet. These preventive beneficial effects exerted by the β3-AR agonist were associated with a reduction of muscle DAG accumulation. In adipose tissue, ZD7114 treatment was able to limit the proportional reduction of PUFA into the PL pool, induced by the cafeteria diet. Our results indicate that a β3-AR agonist prevents some cafeteria diet-induced alterations of the fatty acid profile of lipids in skeletal muscle and adipose tissue. Furthermore, we propose that these changes may contribute to the improved of insulin sensitivity observed in rats treated with a β3-AR agonist during the development of obesity.
Methods
Animal study
Male Sprague-Dawley rats were purchased from Charles River (L'arbesles, France) at 5–6 weeks of age. Animals were individually housed in temperature-controlled rooms (22°C) with a 12-h light-dark cycle. Ten days before the beginning of the study, 30 rats were provided a normal chow diet (Kliba-Nafalg, Switzerland) and free access to drinking water. At the end of this period, rats were weighed and pre-selected for their sensitivity to weight gain (i.e. rat presenting at least 35% weight gain after a 10-day selection period). The selected rats (n = 15) were equally randomized into 3 groups. A reference group, consisted of rats fed for 60 days with a standard pellet chow diet containing 28, 57 and 15% E from protein, carbohydrate and fat, respectively (REF group). The remaining rats were fed for 60 days with a cafeteria diet composed of 30 g of a mix containing salami, cookies, cheese, sausage, chips, chocolate and almonds in a proportion of 2:2:2:1:1:1:1 and 30 g of the reference group chow diet. This mixed diet contained 26, 27 and 47% energy as protein, carbohydrate and fat, respectively. At the beginning of the dietary intervention, both groups fed the cafeteria diet received daily, by gavage (0.5 ml/100 g body weight), either the selective β-3AR agonist ZD7114 at 1 mg/kg per day (CAF-ZD group) or water alone (CAF group) until day 60. Rats from the REF group (chow diet) also received a daily gavage of water (0.5 ml/100 g body weight).
Body weight and food intake were recorded daily. Rats were fasted for 8 hours before sacrifice, performed under isoflurane anaesthesia. Tissues were immediately collected, weighed, frozen in liquid nitrogen and kept at -80°C until analysed.
All procedures in the study were in compliance with the ethical committee of the "Service vétérinaire du canton de Vaud".
Estimation of the proportions of the different lipid classes contained in the cafeteria diet (see Discussion) was performed using the USDA Nutrient Database.
Lipid fatty acid composition
Adipose tissue
Fatty acid composition of lipids in adipose tissue was performed by Lipomics Technologies (West Sacramento, USA). Briefly, lipids were extracted from 30 mg of frozen epididymal adipose tissue in the presence of authentic internal standards by the method of Folch et al. [27] using chloroform:methanol (2:1, by vol.). After separation of individual lipid classes by preparative thin-layer chromatography, the TAG and PL were scraped and trans-esterified; the resulting fatty acid methyl esters were then separated and quantified by capillary gas chromatography as previously described [28].
Muscle
The frozen gastrocnemius muscle was thawed and thoroughly dissected under stereomicroscope to remove extramyocellular adipose tissue. Lipids from lyophilized, finely powdered, dissected muscle (50 mg) were extracted according to the method of Folch [27]. PL (19:0), TAG (17:0) and DAG (15:0) internal standards (Varian; Zug, Switzerland) were added prior to lipid extraction. The lipids were loaded on a Chromabond NH2 cartridge (Varian; Zug, Switzerland), and neutral lipids were separated from free fatty acids and PL by sequential elution with chloroform/2-Propanol (2:1), 2% acetic acid in diethylether and methanol, respectively [29]. The neutral lipids were subjected to thin-layer chromatography using hexane:diethylether:acetic acid (70:30:1, by vol.) as solvent system to separate DAG from TAG [30]. The hydrolysis of TAG into DAG during sample analysis has been assessed and represented less than 0.5% of total DAG. The fatty acids from the phospholipids, TAG and DAG were converted to their methyl esters. Fatty acid methyl-ester separation was performed by automated gas-liquid chromatography (HP 6890 series) with FID detection (280°C); authentic standard mixtures of fatty acid methyl-esters (Nu-Chek-Perp; Lowell Mutter, USA) were injected to identify fatty acid methyl-ester peaks. Results are expressed in μmol fatty acids per gram lyophilised muscle.
Plasma metabolites
Plasma glucose and insulin were determined with commercially available kits purchased from Sigma (Buchs, Switzerland) and Crystal Chem Inc. (Downers Grove, USA), respectively. Plasma triglycerides and free fatty acids concentrations were analysed using kits from Roche Diagnostic (Basel, Switzerland) and Wako Chemicals (Richmond, USA), respectively.
Statistical analysis
Comparisons of the means of the dependent variables of each group were performed using a one-way ANOVA.
Results
Body weight and fat mass
Male Sprague-Dawley rats were fed, during 60 days, either a chow diet used as a reference group (REF group), a cafeteria diet (CAF rats) or a cafeteria diet plus a daily gavage of the β3-AR agonist ZD7114 (CAF-ZD rats).
At day 60, the mean body weight of CAF rats was significantly greater than that of REF rats (Table 1). On the other hand, CAF-ZD rats presented a significant reduction in mean body weight when compared with CAF rats (Table 1). Similar effects were observed on weight gain which was 46% greater in CAF rats than in REF rats (Figure 1; 213.2 ± 12.2 g vs. 312.3 ± 19.2 g in REF and CAF rats, respectively; p < 0.01), and reduced by 17% in CAF-ZD rats as compared to CAF rats (258.70 ± 12.70 g in CAF-ZD rats, p < 0.05). The enhancement of body weight in CAF rats was strongly associated with the weight increase of two main deep adipose depots, confirming the obesigenic properties of the cafeteria diet. Indeed, the epididymal and retroperitoneal fat pads in CAF rats were respectively 131% and 185% heavier than those of REF rats (Table 1). ZD7114 treatment decreased the weight of the two adipose tissue depots by about 45%, compared to CAF rats (Table 1). The weights of gastrocnemius skeletal muscle, liver and heart were not different between groups (Table 1). As expected, CAF rats had a higher energy intake compared with REF animals (106.03 ± 7.25 vs 78.49 ± 2.96 kcal/day). However, the anti-obesity effect of ZD7114 was not attributed to a reduction of energy intake (107.70 ± 7.30 kcal/day in CAF-ZD rats).
Table 1 Body weight, tissues and fasting plasma metabolites
REF CAF CAF-ZD
Final body weight (g) 443.78 ± 21.42 540.20 ± 16.69 * 477.82 ± 12.09 +
Retroperitoneal (g) 3.73 ± 0.44 10.65 ± 0.48 ** 5.78 ± 0.23 +
Epididymal (g) 4.65 ± 0.41 10.73 ± 0.43 ** 5.96 ± 0.30 +
Gastrocnemius (g) 2.69 ± 0.13 2.78 ± 0.01 2.79 ± 0.03
Heart (g) 1.25 ± 0.07 1.48 ± 0.01 1.46 ± 0.02
Liver (g) 13.53 ± 0.79 16.69 ± 0.15 15.47 ± 0.12
Glucose (mmol/l) 12.80 ± 1.51 12.10 ± 1.02 14.78 ± 1.11
Insulin (μU/ml) 19.75 ± 2.05 98.04 ± 16.01 ** 43.27 ± 8.26 +
Fatty acid (mmol/l) 0.47 ± 0.22 0.42 ± 0.68 0.30 ± 0.39 **
Triacylglycerol (mmol/l) 2.27 ± 0.30 4.59 ± 0.58 ** 4.11 ± 0.95
Data are the mean ± SEM. Values significantly different from those obtained in the group of rats fed a chow diet (REF) are indicated by * (p < 0.05) and ** (p < 0.01). Data measured in the group of rats treated with ZD7114 (CAF-ZD) and significantly different from those in the group of rats fed a cafeteria diet (CAF) are shown by + (p < 0.05).
Figure 1 Individual weight changes. Body weight was measured in rats (n = 5) fed a chow diet (REF) or a cafeteria diet alone (CAF) or treated with 1 mg/kg/day ZD7114 (CAF-ZD) at the beginning and at the end of the different interventions (day 60). Data are represented as individual values.
Glucose and insulin plasma concentrations
Measurement of insulin and glucose concentrations in plasma of fasted animals showed that CAF rats presented a marked hyperinsulinemia with a 4.6 fold increase in insulin concentration as compared to REF animals whereas the glucose level was not changed (Table 1). ZD7114 treatment limited the hyperinsulinemia induced by the cafeteria diet, as demonstrated by the 2.3 fold decrease in plasma insulin concentrations in CAF-ZD rats compared with the CAF group (Table 1). No significant changes in plasma glucose concentrations were observed between these two groups (Table 1).
Adipose tissue lipids
Lipid content
PL and TAG contents per gram of tissue were measured in epididymal adipose tissue of rats fed with a chow diet or a cafeteria diet treated or not with ZD7114. No significant change was observed in the concentration of PL and TAG in adipose tissue of CAF rats when compared with REF animals (Table 2). Furthermore, ZD7114 treatment did not affect adipose tissue lipid content of CAF rats.
Table 2 Adipose tissue lipid content
μmole/g tissue REF CAF CAF-ZD
Phospholipids 8.29 ± 1.28 10.59 ± 1.06 8.65 ± 0.87
Triacylglycerol 2476.34 ± 68.31 2462.63 ± 41.33 2271.57 ± 122.46
Data are the mean ± SEM. REF: rats fed a chow diet; CAF: rats fed a cafeteria die, CAF-ZD: rats fed a cafeteria diet and treated with ZD7114
Fatty acid composition
Analysis of the fatty acid profile shows that cafeteria diet induced an increase in the proportion of monounsaturated fatty acids (MUFA), which was compensated for by a reduction in the percentage of PUFA in both adipose PL and TAG (Figure 2). Changes in the proportion of MUFA in PL and TAG were mainly due to the increase of oleic acid (1.7 and 2.0 fold increase in PL and TAG, respectively; Table 3). Reduction in the percentage of linoleic acid was mainly responsible for the decrease in proportion of PUFA in both PL and TAG (1.6 and 2.3 fold decrease for PL and TAG, respectively; Table 3). The proportions of arachidonic and α-linolenic acids were also slightly decreased in PL and TAG, respectively (Table 3). Although the global proportion of SFA was not modified in adipose tissue PL and TAG of CAF rats when compared with REF animals, the percentage of myristic and stearic acids were respectively enhanced in PL and TAG of CAF animals.
Figure 2 Proportion of the different lipid classes in adipose tissue. Saturated (SFA), monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA) were measured in epididymal adipose tissue phospholipid (PL) and triacylglycerol (TAG) of rats fed a chow diet (empty bars) or a cafeteria diet (black bars) alone or treated with ZD7114 (grey bars). Data are represented as mean ± SEM, and values significantly different to data measured in rats fed the chow or cafeteria diets are indicated by * (p < 0.05), ** (p < 0.01) or + (p < 0.05), respectively.
Table 3 Composition of adipose tissue lipids
% mole fatty acids REF CAF CAF-ZD
Phospholipids
Myristic acid (14:0) 3.04 ± 0.16 3.81 ± 0.19 * 2.96 ± 0.15 ++
Palmitic acid (16:0) 28.70 ± 3.10 30.72 ± 1.83 26.22 ± 1.70
Stearic acid (18:0) 15.99 ± 1.19 16.10 ± 0.75 16.93 ± 0.50
Palmitoleic acid (16:1n-7) 1.17 ± 0.28 1.35 ± 0.31 1.16 ± 0.29
Oleic acid (18:1n-9) 10.74 ± 0.94 18.17 ± 1.60 ** 16.26 ± 1.39 *
Vaccenic acid (18:1n-7) 1.24 ± 0.12 0.89 ± 0.07 * 0.98 ± 0.10
Linoleic acid (18:2n-6) 21.21 ± 1.98 13.27 ± 1.20 ** 16.41 ± 1.55 *
Eicosadienoic acid (20:2n-6) 2.16 ± 1.37 0.92 ± 0.92 0.37 ± 0.37
Arachidonic acid (20:4n-6) 7.69 ± 0.73 4.47 ± 1.23 * 8.90 ± 1.35 +
Triacylglycerol
Myristic acid (14:0) 1.23 ± 0.03 1.33 ± 0.08 1.39 ± 0.28
Palmitic acid (16:0) 21.80 ± 0.29 21.48 ± 0.63 21.02 ± 0.65
Stearic acid (18:0) 3.35 ± 0.15 5.27 ± 0.35 ** 4.84 ± 1.68 *
Palmitoleic acid (16:1n-7) 2.50 ± 0.27 2.29 ± 0.34 2.44 ± 0.46
Oleic acid (18:1n-9) 24.37 ± 1.04 48.87 ± 1.35 ** 47.09 ± 0.20 **
Vaccenic acid (18:1n-7) 1.98 ± 0.12 1.59 ± 0.12 1.73 ± 1.20
Linoleic acid (18:2n-6) 38.22 ± 1.36 16.59 ± 0.72 ** 18.37 ± 0.16 **
α-linolenic acid (18:3n-3) 2.85 ± 0.16 0.67 ± 0.06 ** 0.71 ± 0.20 **
Data are the mean ± SEM. Values significantly different from those obtained in the group of rats fed a chow diet (REF) are indicated by * (p < 0.05) and ** (p < 0.01). Data measured in the group of rats treated with ZD7114 (CAF-ZD) and significantly different from those in the group of rats fed a cafeteria diet (CAF) are shown by + (p < 0.05) and ++ (p < 0.05). Only main fatty acids are presented. CAF-ZD: rats fed a cafeteria diet and treated with ZD7114.
ZD7114 treatment did not change the proportions of any lipid classes measured in adipose TAG of CAF rats (Figure 2). However, in PL, the percentage of PUFA was significantly increased by 1.3 fold in CAF-ZD rats compared to CAF animals. This change was essentially due to a two-fold increase in the proportion of arachidonic acid measured in CAF-ZD rats (Table 3). A slight reduction in the percentage of myristic acid (1.2 fold decrease) was measured in CAF-ZD rats compared to CAF animals.
Skeletal muscle lipids
Lipid content
PL, diacylglycerol (DAG) and TAG contents were measured in the gastrocnemius of REF animals and CAF rats with or without ZD7114 treatment (Table 4).
Figure 3 Proportion of the different lipid classes in muscle. Saturated (SFA), monounsaturated (MUFA) and polyunsaturated fatty acids (PUFA) were measured in muscle phospholipid (PL), triacylglycerol (TAG) and diacylglycerol (DAG) of rats fed a chow diet (empty bars), a cafeteria diet (black bars) alone or treated with ZD7114 (grey bars). Data are represented as mean ± SEM, and values significantly different to data measured in rats fed the chow or cafeteria diet are indicated by * (p < 0.05), ** (p < 0.01) or + (p < 0.05), ++ (p < 0.01), respectively.
The cafeteria diet clearly induced TAG and DAG accumulation in the gastrocnemius, as demonstrated by the respective 3.4 and 2.0 fold increases observed in CAF vs. REF rats (Table 4). Chronic treatment with ZD7114 did not significantly reduce the cafeteria diet induced-accumulation of TAG in muscle. In contrast, DAG accumulation was prevented as indicated by a 1.5 fold reduction of DAG levels in CAF-ZD when compared with CAF rats (Table 4). Values of intramyocellular TAG and DAG obtained in the present study (TAG: between 1 to 4 μmol/g fresh muscle; DAG: between 0.5 to 1 μmol/g fresh muscle) were similar to those previously described in rat skeletal muscles [31] (TAG: between 4 to 5 μmol/g fresh muscle; DAG: between 0.5 to 2.5 μmol/ g fresh muscle).
Table 4 Muscle lipid content
μmole/g tissue REF CAF CAF-ZD
Phospholipids 60.31 ± 4.28 65.62 ± 1.26 70.80 ± 2.77
Triacylglycerol 5.40 ± 0.98 18.63 ± 3.24 ** 15.65 ± 2.57 **
Diacylglycerol 2.07 ± 0.32 4.08 ± 0.24 ** 2.66 ± 0.25 ++
Data are the mean ± SEM. Values significantly different from those obtained in the group of rats fed a chow diet (REF) are indicated by ** (p < 0.01). Data measured in the group of rats treated with ZD7114 (CAF-ZD) and significantly different from those in the group of rats fed a cafeteria diet (CAF) are shown by ++ (p < 0.05).
Fatty acid composition
Fatty acid profiles were determined in muscle PL, TAG and DAG. The gastrocnemius of CAF rats, compared with the REF group, presented an increase in the percentage of MUFA and a decrease in the proportion of PUFA in both TAG and DAG and to a lesser extent in PL (Figure 3). Variations in the percentage of oleic and linoleic acids were, respectively, responsible for the changes in the proportions of MUFA and PUFA in muscle TAG and DAG (Table 5). Modifications of the proportions of PUFA observed in muscle PL of CAF rats were due to slight decreases of both linoleic (1.4 fold increase) and docosahexaenoic (22:6 n-3) acids (1.3 fold increase), whereas the percentage of arachidonic acid (20:4 n-6) was increased by 1.2 fold.
Table 5 Composition of muscle lipids
% mole fatty acids REF CAF CAF-ZD
Phospholipids
Palmitic acid (16:0) 27.87 ± 0.50 26.17 ± 0.29 26.44 ± 0.57
Stearic acid (18:0) 20.21 ± 0.64 22.37 ± 0.54 * 21.64 ± 0.58
Oleic acid (18:1n-9) 6.84 ± 0.21 9.13 ± 0.48 ** 9.12 ± 0.24 **
Linoleic acid (18:2n-6) 13.09 ± 0.65 8.98 ± 0.51** 9.02 ± 0.28 **
Arachidonic acid (20:4n-6) 11.64 ± 0.46 15.07 ± 0.53** 14.11 ± 0.22 **
Docosatetraenoic acid (22:4n-6) ND 0.61 ± 0.04 0.51 ± 0.02
Adrenic acid (22:5n-3) 2.04 ± 0.07 2.44 ± 0.18 2.10 ± 0.09
Docosahexaenoic acid (22:6n-3) 18.30 ± 0.95 15.23 ± 0.52 * 16.09 ± 0.35
Triacylglycerol
Myristic acid (14:0) ND 1.66 ± 0.08 1.53 ± 0.06
Palmitic acid (16:0) 37.13 ± 2.06 25.26 ± 0.95 ** 25.15 ± 0.81 **
Stearic acid (18:0) 7.94 ± 0.31 9.36 ± 0.45 * 9.38 ± 0.65
Palmitoleic acid (16:1n-7) ND 1.51 ± 0.14 1.31 ± 0.13
Oleic acid (18:1n-9) 29.00 ± 0.94 51.36 ± 1.83 ** 50.14 ± 0.93 **
Linoleic acid (18:2n-6) 25.00 ± 1.98 10.86 ± 0.83 ** 12.47 ± 0.66 **
Diacylglycerol
Myristic acid (14:0) 1.92 ± 0.09 1.75 ± 0.07 1.85 ± 0.05
Palmitic acid (16:0) 25.55 ± 0.86 22.42 ± 1.22 24.88 ± 0.62
Stearic acid (18:0) 6.71 ± 0.45 8.74 ± 0.63 * 9.71 ± 0.08 **
Palmitoleic acid (16:1n-7) 2.58 ± 0.20 1.59 ± 0.14 ** 1.26 ± 0.07 **
Oleic acid (18:1n-9) 28.90 ± 1.24 52.88 ± 1.25 ** 46.45 ± 1.61 ** ++
Nervonic acid (24:1n-9) 3.92 ± 1.93 1.24 ± 0.42 2.71 ± 0.88
Linoleic acid (18:2n-6) 26.96 ± 2.22 10.14 ± 2.04 ** 8.05 ± 0.69 **
α-linolenic acid (18:3n-3) 1.12 ± 0.18 ND ND
Stearidonic acid (18:4n-3) ND ND 1.90 ± 0.41
Arachidonic acid (20:4n-6) 0.78 ± 0.06 0.46 ± 0.06 ** 0.26 ± 0.04 ** +
Data are the mean ± SEM. Values significantly different from those obtained in the group of rats fed a chow diet (REF) are indicated by * (p < 0.05) and ** (p < 0.01). Data measured in the group of rats treated with ZD7114 (CAF-ZD) and significantly different from those in the group of rats fed a cafeteria diet (CAF) are shown by + (p < 0.05) and ++ (p < 0.05). Fatty acids representing more than 1% in at least one group are presented.
The influence of ZD7114 on the cafeteria-induced modification of fatty acid composition in the three lipid species was evaluated by comparing CAF rats with CAF-ZD rats. While ZD7114 did not affect the fatty acid profile of either TAG or PL in muscle of CAF rats, it induced changes in the fatty acid composition of muscle DAG. Indeed, the proportion of SFA was slightly (1.2 fold increase), but significantly, elevated in DAG of CAF-ZD rats with an increase in the proportion of palmitic and stearic acids (Table 5). Furthermore, the proportion of MUFA in DAG of CAF-ZD rat muscles was decreased compared with DAG of CAF rats. This change was essentially attributed to a decrease in the proportion of oleic acid (Table 5). Stearidonic acid (18.4 n-3) was only detected in DAG accumulated in muscles of ZD-CAF rats. No differences in the proportion of PUFA between DAG stored in muscles of CAF-ZD or CAF rats were observed (Figure 3).
Discussion
The present study demonstrates that feeding the cafeteria diet to rats not only promotes weight gain, hyperinsulinemia and hypertriglyceridemia, but also accumulation of lipids in skeletal muscle. Although TAG levels per gram of adipose tissue was not affected by the cafeteria diet, this dietary intervention strongly enhanced TAG accumulation in skeletal muscle, as previously described [4,5]. We show that this intramyocellular accumulation of TAG was associated with an increase in skeletal muscle DAG content. This finding is in agreement with the accumulation of DAG observed in human skeletal muscle cells incubated with saturated fatty acids in vitro [12]. DAG mass was also described to be increased in skeletal muscle biopsies obtained from normal volunteers in whom insulin resistance was produced by raising FFA levels during a lipid infusion [32]. However, to our knowledge, the present study demonstrates for the first time that a high fat diet, resembling the human Western diet, was able to increase DAG storage in skeletal muscle. Although both TAG and DAG accumulations in skeletal muscle were reported to be correlated with insulin resistance [4,5,33], DAG (a precursor of TAG synthesis) is proposed to directly impair insulin sensitivity by inactivating insulin receptor activity through activation of the protein kinase C [34].
The fatty acid composition of TAG stored in muscle was previously shown to be affected by dietary lipids [2]. Interestingly, we also find that the fatty acid composition of muscle DAG was modified by the cafeteria diet. Indeed, the increase in MUFA and the reduction of PUFA proportions, measured in both DAG and TAG, reflected the difference in lipid composition of the two diets (+ 19% MUFA and -28% PUFA in cafeteria diet vs. chow diet). It is noteworthy that qualitative changes in DAG were reported to affect the activity of DAG as a secondary messenger, since specificity of its fatty acyl moieties for the activation of protein kinase C has been described [35,36]. Although measurements of insulin sensitivity were not directly accessed in this study, our observation suggests that diet may regulate insulin response in muscle by modifying DAG composition.
Fatty acid compositions of muscle and adipose tissue PL were also modified by the cafeteria diet. More specifically, the proportion of PUFA in PL was decreased and MUFA was increased in both tissues. These differences were more pronounced in PL from adipose tissue than from gastrocnemius, indicating that membrane phospholipids in adipose tissue are more susceptible to variations in dietary composition than skeletal muscle. Interestingly, reductions in the proportion of PUFA in PL from myocytes [7] and adipocytes [8] were reported to impair insulin action.
As previously reported with Trecadrine, a selective β3-AR agonist [22], chronic administration of ZD7114 prevented the excess weight gain and fat accumulation induced by a cafeteria diet. This present report demonstrates that ZD7114 treatment reduced the hyperinsulinemia elicited by the cafeteria diet (by 2.3 fold), thereby suggesting an improvement of insulin sensitivity in the treated rats. This observation was associated with a significant reduction in the accumulation of skeletal muscle DAG, and a slight, non-significant decrease in TAG. It is tempting to suggest that the decrease in muscle DAG accumulation induced by the chronic administration of a β3-AR agonist could participate in the prevention of hyperinsulinemia. β3-AR agonist treatment significantly modified the fatty acid composition of DAG, causing a 1.2 fold reduction in the proportion of oleic acid. As mentioned before, these modifications in DAG composition could directly regulate insulin action in muscles. Since the presence of a β3-AR in skeletal muscle is still a subject of debate, it is difficult to elucidate the mechanism(s) by which the β3-AR agonist lowers DAG content in muscle and modifies its fatty acid composition.
Although the content and the fatty acid composition of TAG stored in adipose tissue was not affected by β3-AR agonist administration, the fatty acid profile of adipose PL was modified by the treatment. The β3-AR agonist was able to restore the proportion of PUFA to a level similar to the REF rats by increasing the percentage of arachidonic acid by 2 fold. As mentioned above, a greater percentage of PUFA in PL has been reported to enhance insulin sensitivity in adipose tissue. The changes in PL composition induced by the β3-AR agonist may be associated with the previously reported improved insulin sensitivity in adipose tissue [8], and the decrease of hyperinsulinemia measured in the present study.
Conclusions
Whilst the effectiveness of β3-AR agonists is limited in humans, understanding the metabolic changes affected in rodents will provide insights into mechanisms, underlying insulin responsiveness in humans. The present study demonstrates that β3-AR agonist treatment not only limits the hyperinsulinemia induced by a cafeteria diet, but also partially prevents the associated alterations in adipose and muscle lipid composition. Particularly, activation of the β3-AR limits the intramyocellular DAG accumulation and the decrease in the proportion of PUFA in adipose tissue PL. This combined action may contribute to the beneficial effect of β3-AR agonists on insulin sensitivity.
List of abbreviations
CAF rats: Rats fed with a cafeteria diet; DAG: Diacylglycerol; MUFA: Monounsaturated fatty acid; PKC: Protein kinase C; PUFA: Polyunsaturated fatty acid; REF rats: Rats fed with a chow diet; SFA: saturated fatty acid. TAG: Triacylglycerol; ZD-CAF rats: Rats fed with a cafeteria diet and treated with the β3-AR agonist ZD7114.
Acknowledgments
The authors are grateful to Dr. K. Acheson and D. M. Mutch (Nestlé Research Center, Lausanne, Switzerland) for critically reading the manuscript.
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Marignani PA Epand RM Sebaldt RJ Acyl chain dependence of diacylglycerol activation of protein kinase C activity in vitro Biochem Biophys Res Commun 1996 225 469 473 8753785 10.1006/bbrc.1996.1196
Madani S Hichami A Legrand A Belleville J Khan NA Implication of acyl chain of diacylglycerols in activation of different isoforms of protein kinase C Faseb J 2001 15 2595 2601 11726535 10.1096/fj.01-0753int
| 15507147 | PMC524030 | CC BY | 2021-01-04 16:37:45 | no | Nutr Metab (Lond). 2004 Aug 18; 1:5 | latin-1 | Nutr Metab (Lond) | 2,004 | 10.1186/1743-7075-1-5 | oa_comm |
==== Front
Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-1-61550715710.1186/1743-7075-1-6ReviewMetabolic response of people with type 2 diabetes to a high protein diet Nuttall Frank Q 12nutta001@umn.eduGannon Mary C 123ganno004@umn.edu1 Metabolic Research Laboratory, Endocrine, Metabolism & Nutrition Section, Minneapolis VA Medical Center, Minneapolis, USA2 Department of Medicine, University of Minnesota, USA3 Department of Food Science and Nutrition, University of Minnesota, USA2004 13 9 2004 1 6 6 3 8 2004 13 9 2004 Copyright © 2004 Nuttall and Gannon; licensee BioMed Central Ltd.2004Nuttall and Gannon; 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 major interests in our laboratory has been to develop a scientific framework for dietary advice for patients with diabetes. Knowledge regarding the metabolic consequences and potential effects on health of protein in people with type 2 diabetes has been a particular interest.
Results
We recently have completed a study in which dietary protein was increased from 15% to 30% of total food energy. The carbohydrate content was decreased from 55% to 40%, i.e. dietary protein replaced part of the carbohydrate. This resulted in a significant decrease in total glycohemoglobin, a decrease in postprandial glucose concentrations and a modest increase in insulin concentration. Renal function was unchanged.
Currently we also are determining the metabolic response to a diet in which the carbohydrate content is further decreased to 20% of total food energy. The %tGHb decrease was even more dramatic than with the 40% carbohydrate diet.
Conclusion
From these data we conclude that increasing the protein content of the diet at the expense of carbohydrate can reduce the 24-hour integrated plasma glucose concentration, at least over a 5-week period of time. The reduction was similar to that of oral agents. Renal function was not affected significantly. Thus, increasing the protein content of the diet with a corresponding decrease in the carbohydrate content potentially is a patient empowering way of reducing the hyperglycemia present with type 2 diabetes mellitus, independent of the use of pharmaceutical agents.
==== Body
Background
Our research group has been and continues to be interested in the metabolic response of people with type 2 diabetes to macronutrients in the diet in general. More recently, we have been particularly focused on the metabolic response to a high protein diet. The reason for this is three fold: First, for several years, one of our major goals has been to develop a scientific framework for dietary advice based on sound metabolic principles. Second, we have data that suggest that an increase in dietary protein may be salutary for people with diabetes. And lastly, knowledge regarding the metabolic consequences and potential effects on health of dietary protein has lagged far behind that of dietary fats and carbohydrates.
In this paper we will focus on the concept that an increase in dietary protein may be salutary for people with diabetes, and particularly for the control of blood glucose.
Results
The concept that an increase in dietary protein may be useful in controlling the blood glucose would appear to be counterintuitive, since amino acids derived from ingested or endogenous proteins are major net gluconeogenic substrates.
The first step in the metabolism of amino acids is the removal of the amino group. This is condensed with CO2 to form urea. The remaining deaminated product is largely converted into glucose through gluconeogenesis, although a small amount is converted into other products. (Figure 1).
Figure 1 The α amino group from an amino acid is condensed with CO2 to form urea. The remaining carbon skeleton can be used to synthesize glucose.
Indeed, in 1915, Dr. Janney [1] reported that 3.5 g glucose can be obtained from 6.25 g of ingested meat or beef protein. Thus, theoretically for every 100 g of protein ingested, 56 g of glucose can be produced. For other proteins this varies between 50 and 84 grams. Thus when developing a dietary regimen for diabetic patients, dietitians were taught to count not only carbohydrate, but also to count 56% of the protein as carbohydrate. The rationale behind this recommendation was that carbohydrates raised blood glucose, proteins are converted to glucose, therefore, dietary proteins will raise blood glucose.
However, in 1924, Dr. MacLean [2] reported that when a man with diabetes, and a fasting blood glucose of 280 mg/dl, ingested 250 g of meat, which is the equivalent of 50 grams of protein, and which should result in the production of ~25 g of glucose, there was no change in blood glucose over the 5 hours of the study. When the same subject ingested 25 g of glucose, there was a very large increase in blood glucose; indeed, it increased up to 600 mg/dl.
This lack of increase in blood glucose concentration following the ingestion of protein was confirmed by Conn and Newburgh in 1936 [3]. These investigators fed a relatively enormous amount of beef, i.e. 1.3 pounds of beef, which is the equivalent of ~136 g of protein and which should yield 68 g of glucose, to a normal subject with a fasting blood glucose of 65 mg/dl and to a subject with diabetes whose fasting blood glucose concentration was 150 mg/dl. In neither case was there an increase in blood glucose concentration over the 8 hours of this study. However, when the same subjects were given 68 g of glucose, there clearly was an increase in glucose concentration in both cases.
That ingested protein did not raise the blood glucose was largely ignored, in spite of this evidence in the scientific literature. Indeed, in his textbook in 1945 [4], Dr. Joslin, one of the most influential diabetologists at that time, was still counseling dietitians and patients to consider 56% of dietary protein as if it were carbohydrate.
Single meal studies done in our laboratory
With this background information, we decided to do a study expanding on these early observations. Seven subjects with type 2 diabetes [5], and 8 subjects without diabetes [6] ingested 50 g of protein in the form of very lean beef. In the non-diabetic subjects, there was no change in blood glucose concentration over the 4 hours of the study, as had been noted previously. However, in the subjects with type 2 diabetes, the glucose concentration actually decreased over the 5 hours of that study (Figure 2).
Figure 2 Glucose (left panel) and insulin (right panel) response to ingestion of 50 g of protein in the form of lean beef. Data from 8 non-diabetic subjects (white lines, bottom) and 7 subjects with type 2 diabetes (yellow lines, top). (From [5,6])
We also determined the serum insulin response to the ingested protein and in confirmation of the studies of Berger [7], Fajans [8] and others, we observed a modest increase in the insulin concentration in the non-diabetic subjects [6]. However, there was a relatively large increase in insulin concentration in the subjects with type 2 diabetes [5]. Indeed, it was about four-fold greater than in the non-diabetic subjects (Figure 2). We also determined that the rise in insulin following the ingestion of 50 g of beef protein was just as potent in raising the insulin concentration as was the ingestion of 50 g of glucose [5]. That is, meat protein and glucose were equipotent in stimulating insulin secretion. In addition, we also demonstrated a linear dose-response relationship between the amount of beef ingested and the insulin response [5].
Since beef protein strongly stimulated insulin secretion, we next determined whether the simultaneous ingestion of protein with glucose would stimulate even more insulin and thus reduce the rise in glucose expected when glucose alone is ingested. We also were interested in determining if all common protein sources were equal in this regard. Therefore, we designed a study in which 9 – 15 males with untreated type 2 diabetes were given 50 g of glucose with or without 25 g of protein [9]. Seven protein sources were used: beef, turkey, gelatin, egg white, cottage cheese, fish and soy. The rationale behind giving 25 g of protein with 50 g of glucose, was that this ratio more closely resembles the ratio of protein to carbohydrate typically found in the diet. The plasma glucose and serum insulin concentrations were determined over a 5-hour period and the areas under the curves were calculated.
The glucose area response clearly was decreased when glucose was ingested with 25 g of protein as beef, turkey, gelatin, cottage cheese, fish and soy. Only egg white did not result in a significant decrease in glucose area response when compared to the response to ingestion of glucose alone (Figure 3).
Figure 3 Five hour integrated glucose area response to ingestion of 50 g glucose alone (pink bar) or 50 g glucose + 25 g protein in the form of beef, turkey, gelatin, egg white, cottage cheese, fish or soy (yellow bars, left to right). (From [9])
When any of the proteins was added to the ingested glucose, the insulin area response was greatly increased (Figure 4). The smallest response was obtained with egg white, which was 190% or 1.9 fold over the response to glucose ingested alone. The greatest increase was with cottage cheese, which was 360% or 3.6 fold.
As indicated previously, beef protein, on a weight basis, was just as potent as glucose in raising the insulin concentration. Since only 25 g of beef protein was ingested in the present study, the expected response would be 150% of that observed with just glucose ingestion [5]. With beef and every other protein source studied, the insulin response was greater than the theoretical expected response (Figure 4), strongly suggesting that there is a synergistic insulin response when protein is ingested with glucose [9].
In summary, in single meal studies in people with type 2 diabetes, dietary protein strongly stimulated insulin secretion and decreased the plasma glucose response to ingested glucose.
Figure 4 Five hour integrated insulin area response to ingestion of 50 g glucose alone (pink bar) or 50 g glucose + 25 g protein in the form of beef, turkey, gelatin, egg white, cottage cheese, fish or soy (yellow bars, left to right). The horizontal line indicates the expected insulin area response. (From [9])
Insulin and Glucose Response to Mixed Meals
Based on the above observations, we decided to determine whether an increase in dietary protein in association with a decrease in carbohydrate would decrease the 24 hour integrated plasma glucose concentration, increase the 24 hour integrated insulin concentration and decrease the % total glycohemoglobin in people with type 2 diabetes ingesting mixed meals over an extended period of time.
We designed a study in which the protein content of the diet was increased from 15% of total food energy in a standard diet, to 30% protein in the experimental diet [10]. The carbohydrate content was decreased from 55% carbohydrate to 40% carbohydrate. However, it should be understood that since the additional protein can result in an increase in glucose production, the actual carbohydrate available theoretically would be about 48%, or a decrease in potential carbohydrate of only 7%. The fat content remained the same in both diets. Monounsaturated, polyunsaturated and saturated fat ratios were 10:10:10, respectively.
Twelve people with untreated type 2 diabetes were studied using a randomized, crossover design. The subjects received each diet for 5 weeks with a washout period in between. The diets were isocaloric, and all food was provided. The subjects came to the Special Diagnostic and Treatment Unit 2–3 times each week to pick up the food, to be weighed, and to provide a urine specimen for creatinine and urea nitrogen determination.
The major end-point of the study was to determine if there was a significant decrease in % total glycohemoglobin (%tGHb).
The reason that 5 weeks was chosen for the study is because this is the time required for the % total glycohemoglobin to decrease 50% of its ultimate value after a rapid stable decrease in blood glucose concentration (Figure 5), [11], i.e. the results obtained should represent 50% of the ultimate % total glycohemoglobin response.
Figure 5 Rate of change in % tGHb
The subjects were weight stable on both diets. We considered this to be a very important aspect of the study because we wanted to attribute any metabolic changes to the diet per se, and not to be confounded by weight loss (or gain) [10].
Urine urea, normalized to the urine creatinine, was measured as an index of compliance. Since the protein content of the diet was doubled, one would expect that the urine urea:creatinine ratio also would approximately double if the subjects were compliant. The ratio on the standard diet was ~7 and was stable throughout the 5 weeks. When the same subjects were given the 30% protein diet, the urine urea:creatinine ratio was ~13–14, i.e. a value that one would expect with good compliance with the diet.
The fasting glucose concentration did not change when the subjects received the 30% protein diet. However, the postprandial glucose concentrations were lower throughout the day [10].
Although the differences in postprandial glucose values were not very large, when integrated over the 24-hour period, there was a 38% decrease in postprandial glucose area response. If the 24-hour integrated area is considered to be 100% when the subjects ingested the 15% protein diet, when they ingested the 30% protein diet it was 62% (Figure 6).
Figure 6 24-hr integrated plasma glucose area response in 12 subjects with type 2 diabetes after ingesting the 15% protein or the 30% protein diet for 5 weeks. (From [10])
Even though the postprandial glucose concentration was decreased on the 30% protein diet, the insulin area response was modestly increased (Figure 7).
Figure 7 24-hr integrated serum insulin area response in 12 subjects with type 2 diabetes after ingesting the 15% or the 30% protein diet for 5 weeks. (From [10])
The % total glycohemoglobin decreased slightly from 8% to 7.7% during the 5 weeks of the study when the subjects were ingesting the 15% protein diet. When the subjects ingested the 30% protein diet, it decreased from 8.1 to 7.3%, i.e. the decrease was 0.8 (Figure 8).
Figure 8 %tGHb response in 12 subjects with type 2 diabetes at weekly intervals while ingesting a 15% or a 30% protein diet. (From [10])
To put this decrease in % glycohemoglobin into perspective, the Physicians Desk Reference for 2003 [12] was consulted in regard to the decrease in %HbA1c or %glycohemoglobin when subjects with type 2 diabetes were given rosiglitazone or metformin, drugs commonly used to treat people with type 2 diabetes. In subjects receiving 4 mg rosiglitazone twice a day, which is a maximal dose, the mean decrease in HbA1c was 0.7% over a 16-week period of time (Table 1). For metformin, at a maximum dose of 2500 mg daily, the decrease was 1.4% over a 29-week period.
Table 1 Comparison of treatment
Agent Dose Duration of Treatment Decrease in %tGHb or %HbA1c
Rosiglitizone 4 mg bid 16 weeks 0.7%
Metformin 2500 mg 29 weeks 1.4%
30% Protein Diet 5 weeks 0.8% (1.6%)
PDR 2003 [12]
With the 30% protein diet, the decrease was 0.8% over the 5 weeks of our study. The ultimate decrease could be 1.6%, since at 5 weeks (35 days) the %tGHb would have decreased by only 50% of the expected final decrease (see Figure 5). Thus, the decrease would be similar to that obtained using either of the above two medications.
Since there has been concern that a high protein diet may impair renal function, the creatinine clearance was determined at the end of the period of time the subjects ingested the 15% protein diet and at the end of the period of time that the subjects ingested the 30% protein diet. There was essentially no difference. The microalbumin excretion also did not change (Table 2).
Table 2 Renal data
15% Protein Diet 30% Protein Diet
Creatinine Clearance (ml/min) 122 ± 11 113 ± 27
Microalbumin (mg) 7.8 ± 1.7 7.0 ± 0.8
Also the differences in total cholesterol, HDL-cholesterol, LDL-cholesterol were not significant. The fasting triacylglycerol concentration decreased significantly when the subjects were on the 30% protein diet (Table 3).
Table 3 Lipid data
15% Protein Diet 30% Protein Diet
Total Cholesterol (mg/dl) 181 ± 15 171 ± 12
HDL-Cholesterol (mg/dl) 38 ± 3 39 ± 3
LDL-Cholesterol (mg/dl) 100 ± 12 101 ± 12
Triacylglycerol (mg/dl) 199 ± 20 161 ± 21*
* P < 0.05
Discussion
In summary, the integrated postprandial glucose area response was 38% less following ingestion of the 30% compared to the 15% protein diet. Total glycohemoglobin decreased significantly from 8.1 to 7.3% and potentially could result in a decrease to 6.5%. The integrated insulin concentration increased modestly. Renal function, LDL, HDL, and total cholesterol were unchanged. The triacylglycerol concentration decreased.
Conclusions
From these data we conclude that increasing the protein content of the diet at the expense of carbohydrate can reduce the 24-hour integrated plasma glucose concentration, at least over a 5-week period of time. The reduction was similar to that of oral agents and renal function was not affected significantly. Thus, increasing the protein content of the diet with a corresponding decrease in the carbohydrate content potentially is a patient empowering way of reducing the hyperglycemia present in people with type 2 diabetes mellitus, independent of the use of pharmaceutical agents.
Results of a further modification in macronutrient content
More recently we have completed study comparing an experimental diet to the standard diet, over a 5-week period of time. In the experimental diet, the protein was increased from 15% to 30% as in the above study. However, in this study the carbohydrate content was decreased from 55% to 20% of total food energy and the fat content was increased from 30% to 50%. The subjects studied were people with untreated type 2 diabetes. It was a weight maintenance diet, with a randomized crossover design. The %tGHb decrease was even more dramatic (9.8 to 7.6%) [13].
Competing interests
None declared.
Authors' contributions
Both authors were equally responsible for designing the experiments, evaluating the statistics, interpreting the data, writing the manuscript, and organizing the figures and tables.
Acknowledgements
We would like to acknowledge the American Diabetes Association, the Minnesota Beef Council, the Nebraska and Colorado Beef Councils for financial support for these studies. Most importantly, we would like to thank the volunteers who made the studies possible. We also would like to thank Jennifer Nuttall Martenson, Kelly Jordan Schweim, Heidi Hoover, Mary Adams, and the SDTU staff for their vital technical assistance in these studies.
==== Refs
Janney NW The metabolic relationship of the proteins to glucose. J Biol Chem 1915 20 321 350
MacLean H Modern Methods in the Diagnosis and Treatment of Glycosuria and Diabetes 1924 2nd edition London, Constable & Co. Ltd. 1 52
Conn JW Newburgh LH The glycemic response to isoglucogenic quantities of protein and carbohydrate J Clin Invest 1936 15 665 671 16694439
Joslin EP Diabetic Manual of the Doctor and Patient. 1945 Philadelphia, Lea & Febinger
Nuttall FQ Mooradian AD Gannon MC Billington CJ Krezowski PA Effect of protein ingestion on the glucose and insulin response to a standardized oral glucose load Diabetes Care 1984 7 465 470 6389060
Krezowski PA Nuttall FQ Gannon MC Bartosh NH The effect of protein ingestion on the metabolic response to oral glucose in normal individuals. Am J Clin Nutr 1986 44 847 856 3538843
Berger S Vongaraya M Insulin response to ingested protein in diabetes. Diabetes 1966 15 303 306 5936455
Fajans SS Floyd JC Pek S Knopf RF Jacobson M Conn JW Effect of protein meals on plasma insulin in mildly diabetic patients. (Abstract #1). Diabetes 1968 17 297 5651713
Gannon MC Nuttall FQ Neil BJ Westphal SA The insulin and glucose responses to meals of glucose plus various proteins in type 2 diabetic subjects Metabolism 1988 37 1081 1088 3054432 10.1016/0026-0495(88)90072-8
Gannon MC Nuttall FQ Saeed A Jordan K Hoover K An increase in dietary protein improves the blood glucose response in people with type 2 diabetes Amer J Clin Nutr 2003 78 734 741 14522731
Rech ME Observations on the decay of glycated hemoglobin HbA1c in diabetic patients. Exp Clin Endocrinol Diabetes 1996 104 102 105 8740932
Physicians' Desk Reference
Gannon MC Nuttall FQ Effect of a high-protein, low-carbohydrate diet on blood glucose control in people with type 2 diabetes Diabetes 2004 53 2375 2382 15331548
| 15507157 | PMC524031 | CC BY | 2021-01-04 16:37:45 | no | Nutr Metab (Lond). 2004 Sep 13; 1:6 | utf-8 | Nutr Metab (Lond) | 2,004 | 10.1186/1743-7075-1-6 | oa_comm |
==== Front
Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-1-61550715710.1186/1743-7075-1-6ReviewMetabolic response of people with type 2 diabetes to a high protein diet Nuttall Frank Q 12nutta001@umn.eduGannon Mary C 123ganno004@umn.edu1 Metabolic Research Laboratory, Endocrine, Metabolism & Nutrition Section, Minneapolis VA Medical Center, Minneapolis, USA2 Department of Medicine, University of Minnesota, USA3 Department of Food Science and Nutrition, University of Minnesota, USA2004 13 9 2004 1 6 6 3 8 2004 13 9 2004 Copyright © 2004 Nuttall and Gannon; licensee BioMed Central Ltd.2004Nuttall and Gannon; 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 major interests in our laboratory has been to develop a scientific framework for dietary advice for patients with diabetes. Knowledge regarding the metabolic consequences and potential effects on health of protein in people with type 2 diabetes has been a particular interest.
Results
We recently have completed a study in which dietary protein was increased from 15% to 30% of total food energy. The carbohydrate content was decreased from 55% to 40%, i.e. dietary protein replaced part of the carbohydrate. This resulted in a significant decrease in total glycohemoglobin, a decrease in postprandial glucose concentrations and a modest increase in insulin concentration. Renal function was unchanged.
Currently we also are determining the metabolic response to a diet in which the carbohydrate content is further decreased to 20% of total food energy. The %tGHb decrease was even more dramatic than with the 40% carbohydrate diet.
Conclusion
From these data we conclude that increasing the protein content of the diet at the expense of carbohydrate can reduce the 24-hour integrated plasma glucose concentration, at least over a 5-week period of time. The reduction was similar to that of oral agents. Renal function was not affected significantly. Thus, increasing the protein content of the diet with a corresponding decrease in the carbohydrate content potentially is a patient empowering way of reducing the hyperglycemia present with type 2 diabetes mellitus, independent of the use of pharmaceutical agents.
==== Body
Background
Our research group has been and continues to be interested in the metabolic response of people with type 2 diabetes to macronutrients in the diet in general. More recently, we have been particularly focused on the metabolic response to a high protein diet. The reason for this is three fold: First, for several years, one of our major goals has been to develop a scientific framework for dietary advice based on sound metabolic principles. Second, we have data that suggest that an increase in dietary protein may be salutary for people with diabetes. And lastly, knowledge regarding the metabolic consequences and potential effects on health of dietary protein has lagged far behind that of dietary fats and carbohydrates.
In this paper we will focus on the concept that an increase in dietary protein may be salutary for people with diabetes, and particularly for the control of blood glucose.
Results
The concept that an increase in dietary protein may be useful in controlling the blood glucose would appear to be counterintuitive, since amino acids derived from ingested or endogenous proteins are major net gluconeogenic substrates.
The first step in the metabolism of amino acids is the removal of the amino group. This is condensed with CO2 to form urea. The remaining deaminated product is largely converted into glucose through gluconeogenesis, although a small amount is converted into other products. (Figure 1).
Figure 1 The α amino group from an amino acid is condensed with CO2 to form urea. The remaining carbon skeleton can be used to synthesize glucose.
Indeed, in 1915, Dr. Janney [1] reported that 3.5 g glucose can be obtained from 6.25 g of ingested meat or beef protein. Thus, theoretically for every 100 g of protein ingested, 56 g of glucose can be produced. For other proteins this varies between 50 and 84 grams. Thus when developing a dietary regimen for diabetic patients, dietitians were taught to count not only carbohydrate, but also to count 56% of the protein as carbohydrate. The rationale behind this recommendation was that carbohydrates raised blood glucose, proteins are converted to glucose, therefore, dietary proteins will raise blood glucose.
However, in 1924, Dr. MacLean [2] reported that when a man with diabetes, and a fasting blood glucose of 280 mg/dl, ingested 250 g of meat, which is the equivalent of 50 grams of protein, and which should result in the production of ~25 g of glucose, there was no change in blood glucose over the 5 hours of the study. When the same subject ingested 25 g of glucose, there was a very large increase in blood glucose; indeed, it increased up to 600 mg/dl.
This lack of increase in blood glucose concentration following the ingestion of protein was confirmed by Conn and Newburgh in 1936 [3]. These investigators fed a relatively enormous amount of beef, i.e. 1.3 pounds of beef, which is the equivalent of ~136 g of protein and which should yield 68 g of glucose, to a normal subject with a fasting blood glucose of 65 mg/dl and to a subject with diabetes whose fasting blood glucose concentration was 150 mg/dl. In neither case was there an increase in blood glucose concentration over the 8 hours of this study. However, when the same subjects were given 68 g of glucose, there clearly was an increase in glucose concentration in both cases.
That ingested protein did not raise the blood glucose was largely ignored, in spite of this evidence in the scientific literature. Indeed, in his textbook in 1945 [4], Dr. Joslin, one of the most influential diabetologists at that time, was still counseling dietitians and patients to consider 56% of dietary protein as if it were carbohydrate.
Single meal studies done in our laboratory
With this background information, we decided to do a study expanding on these early observations. Seven subjects with type 2 diabetes [5], and 8 subjects without diabetes [6] ingested 50 g of protein in the form of very lean beef. In the non-diabetic subjects, there was no change in blood glucose concentration over the 4 hours of the study, as had been noted previously. However, in the subjects with type 2 diabetes, the glucose concentration actually decreased over the 5 hours of that study (Figure 2).
Figure 2 Glucose (left panel) and insulin (right panel) response to ingestion of 50 g of protein in the form of lean beef. Data from 8 non-diabetic subjects (white lines, bottom) and 7 subjects with type 2 diabetes (yellow lines, top). (From [5,6])
We also determined the serum insulin response to the ingested protein and in confirmation of the studies of Berger [7], Fajans [8] and others, we observed a modest increase in the insulin concentration in the non-diabetic subjects [6]. However, there was a relatively large increase in insulin concentration in the subjects with type 2 diabetes [5]. Indeed, it was about four-fold greater than in the non-diabetic subjects (Figure 2). We also determined that the rise in insulin following the ingestion of 50 g of beef protein was just as potent in raising the insulin concentration as was the ingestion of 50 g of glucose [5]. That is, meat protein and glucose were equipotent in stimulating insulin secretion. In addition, we also demonstrated a linear dose-response relationship between the amount of beef ingested and the insulin response [5].
Since beef protein strongly stimulated insulin secretion, we next determined whether the simultaneous ingestion of protein with glucose would stimulate even more insulin and thus reduce the rise in glucose expected when glucose alone is ingested. We also were interested in determining if all common protein sources were equal in this regard. Therefore, we designed a study in which 9 – 15 males with untreated type 2 diabetes were given 50 g of glucose with or without 25 g of protein [9]. Seven protein sources were used: beef, turkey, gelatin, egg white, cottage cheese, fish and soy. The rationale behind giving 25 g of protein with 50 g of glucose, was that this ratio more closely resembles the ratio of protein to carbohydrate typically found in the diet. The plasma glucose and serum insulin concentrations were determined over a 5-hour period and the areas under the curves were calculated.
The glucose area response clearly was decreased when glucose was ingested with 25 g of protein as beef, turkey, gelatin, cottage cheese, fish and soy. Only egg white did not result in a significant decrease in glucose area response when compared to the response to ingestion of glucose alone (Figure 3).
Figure 3 Five hour integrated glucose area response to ingestion of 50 g glucose alone (pink bar) or 50 g glucose + 25 g protein in the form of beef, turkey, gelatin, egg white, cottage cheese, fish or soy (yellow bars, left to right). (From [9])
When any of the proteins was added to the ingested glucose, the insulin area response was greatly increased (Figure 4). The smallest response was obtained with egg white, which was 190% or 1.9 fold over the response to glucose ingested alone. The greatest increase was with cottage cheese, which was 360% or 3.6 fold.
As indicated previously, beef protein, on a weight basis, was just as potent as glucose in raising the insulin concentration. Since only 25 g of beef protein was ingested in the present study, the expected response would be 150% of that observed with just glucose ingestion [5]. With beef and every other protein source studied, the insulin response was greater than the theoretical expected response (Figure 4), strongly suggesting that there is a synergistic insulin response when protein is ingested with glucose [9].
In summary, in single meal studies in people with type 2 diabetes, dietary protein strongly stimulated insulin secretion and decreased the plasma glucose response to ingested glucose.
Figure 4 Five hour integrated insulin area response to ingestion of 50 g glucose alone (pink bar) or 50 g glucose + 25 g protein in the form of beef, turkey, gelatin, egg white, cottage cheese, fish or soy (yellow bars, left to right). The horizontal line indicates the expected insulin area response. (From [9])
Insulin and Glucose Response to Mixed Meals
Based on the above observations, we decided to determine whether an increase in dietary protein in association with a decrease in carbohydrate would decrease the 24 hour integrated plasma glucose concentration, increase the 24 hour integrated insulin concentration and decrease the % total glycohemoglobin in people with type 2 diabetes ingesting mixed meals over an extended period of time.
We designed a study in which the protein content of the diet was increased from 15% of total food energy in a standard diet, to 30% protein in the experimental diet [10]. The carbohydrate content was decreased from 55% carbohydrate to 40% carbohydrate. However, it should be understood that since the additional protein can result in an increase in glucose production, the actual carbohydrate available theoretically would be about 48%, or a decrease in potential carbohydrate of only 7%. The fat content remained the same in both diets. Monounsaturated, polyunsaturated and saturated fat ratios were 10:10:10, respectively.
Twelve people with untreated type 2 diabetes were studied using a randomized, crossover design. The subjects received each diet for 5 weeks with a washout period in between. The diets were isocaloric, and all food was provided. The subjects came to the Special Diagnostic and Treatment Unit 2–3 times each week to pick up the food, to be weighed, and to provide a urine specimen for creatinine and urea nitrogen determination.
The major end-point of the study was to determine if there was a significant decrease in % total glycohemoglobin (%tGHb).
The reason that 5 weeks was chosen for the study is because this is the time required for the % total glycohemoglobin to decrease 50% of its ultimate value after a rapid stable decrease in blood glucose concentration (Figure 5), [11], i.e. the results obtained should represent 50% of the ultimate % total glycohemoglobin response.
Figure 5 Rate of change in % tGHb
The subjects were weight stable on both diets. We considered this to be a very important aspect of the study because we wanted to attribute any metabolic changes to the diet per se, and not to be confounded by weight loss (or gain) [10].
Urine urea, normalized to the urine creatinine, was measured as an index of compliance. Since the protein content of the diet was doubled, one would expect that the urine urea:creatinine ratio also would approximately double if the subjects were compliant. The ratio on the standard diet was ~7 and was stable throughout the 5 weeks. When the same subjects were given the 30% protein diet, the urine urea:creatinine ratio was ~13–14, i.e. a value that one would expect with good compliance with the diet.
The fasting glucose concentration did not change when the subjects received the 30% protein diet. However, the postprandial glucose concentrations were lower throughout the day [10].
Although the differences in postprandial glucose values were not very large, when integrated over the 24-hour period, there was a 38% decrease in postprandial glucose area response. If the 24-hour integrated area is considered to be 100% when the subjects ingested the 15% protein diet, when they ingested the 30% protein diet it was 62% (Figure 6).
Figure 6 24-hr integrated plasma glucose area response in 12 subjects with type 2 diabetes after ingesting the 15% protein or the 30% protein diet for 5 weeks. (From [10])
Even though the postprandial glucose concentration was decreased on the 30% protein diet, the insulin area response was modestly increased (Figure 7).
Figure 7 24-hr integrated serum insulin area response in 12 subjects with type 2 diabetes after ingesting the 15% or the 30% protein diet for 5 weeks. (From [10])
The % total glycohemoglobin decreased slightly from 8% to 7.7% during the 5 weeks of the study when the subjects were ingesting the 15% protein diet. When the subjects ingested the 30% protein diet, it decreased from 8.1 to 7.3%, i.e. the decrease was 0.8 (Figure 8).
Figure 8 %tGHb response in 12 subjects with type 2 diabetes at weekly intervals while ingesting a 15% or a 30% protein diet. (From [10])
To put this decrease in % glycohemoglobin into perspective, the Physicians Desk Reference for 2003 [12] was consulted in regard to the decrease in %HbA1c or %glycohemoglobin when subjects with type 2 diabetes were given rosiglitazone or metformin, drugs commonly used to treat people with type 2 diabetes. In subjects receiving 4 mg rosiglitazone twice a day, which is a maximal dose, the mean decrease in HbA1c was 0.7% over a 16-week period of time (Table 1). For metformin, at a maximum dose of 2500 mg daily, the decrease was 1.4% over a 29-week period.
Table 1 Comparison of treatment
Agent Dose Duration of Treatment Decrease in %tGHb or %HbA1c
Rosiglitizone 4 mg bid 16 weeks 0.7%
Metformin 2500 mg 29 weeks 1.4%
30% Protein Diet 5 weeks 0.8% (1.6%)
PDR 2003 [12]
With the 30% protein diet, the decrease was 0.8% over the 5 weeks of our study. The ultimate decrease could be 1.6%, since at 5 weeks (35 days) the %tGHb would have decreased by only 50% of the expected final decrease (see Figure 5). Thus, the decrease would be similar to that obtained using either of the above two medications.
Since there has been concern that a high protein diet may impair renal function, the creatinine clearance was determined at the end of the period of time the subjects ingested the 15% protein diet and at the end of the period of time that the subjects ingested the 30% protein diet. There was essentially no difference. The microalbumin excretion also did not change (Table 2).
Table 2 Renal data
15% Protein Diet 30% Protein Diet
Creatinine Clearance (ml/min) 122 ± 11 113 ± 27
Microalbumin (mg) 7.8 ± 1.7 7.0 ± 0.8
Also the differences in total cholesterol, HDL-cholesterol, LDL-cholesterol were not significant. The fasting triacylglycerol concentration decreased significantly when the subjects were on the 30% protein diet (Table 3).
Table 3 Lipid data
15% Protein Diet 30% Protein Diet
Total Cholesterol (mg/dl) 181 ± 15 171 ± 12
HDL-Cholesterol (mg/dl) 38 ± 3 39 ± 3
LDL-Cholesterol (mg/dl) 100 ± 12 101 ± 12
Triacylglycerol (mg/dl) 199 ± 20 161 ± 21*
* P < 0.05
Discussion
In summary, the integrated postprandial glucose area response was 38% less following ingestion of the 30% compared to the 15% protein diet. Total glycohemoglobin decreased significantly from 8.1 to 7.3% and potentially could result in a decrease to 6.5%. The integrated insulin concentration increased modestly. Renal function, LDL, HDL, and total cholesterol were unchanged. The triacylglycerol concentration decreased.
Conclusions
From these data we conclude that increasing the protein content of the diet at the expense of carbohydrate can reduce the 24-hour integrated plasma glucose concentration, at least over a 5-week period of time. The reduction was similar to that of oral agents and renal function was not affected significantly. Thus, increasing the protein content of the diet with a corresponding decrease in the carbohydrate content potentially is a patient empowering way of reducing the hyperglycemia present in people with type 2 diabetes mellitus, independent of the use of pharmaceutical agents.
Results of a further modification in macronutrient content
More recently we have completed study comparing an experimental diet to the standard diet, over a 5-week period of time. In the experimental diet, the protein was increased from 15% to 30% as in the above study. However, in this study the carbohydrate content was decreased from 55% to 20% of total food energy and the fat content was increased from 30% to 50%. The subjects studied were people with untreated type 2 diabetes. It was a weight maintenance diet, with a randomized crossover design. The %tGHb decrease was even more dramatic (9.8 to 7.6%) [13].
Competing interests
None declared.
Authors' contributions
Both authors were equally responsible for designing the experiments, evaluating the statistics, interpreting the data, writing the manuscript, and organizing the figures and tables.
Acknowledgements
We would like to acknowledge the American Diabetes Association, the Minnesota Beef Council, the Nebraska and Colorado Beef Councils for financial support for these studies. Most importantly, we would like to thank the volunteers who made the studies possible. We also would like to thank Jennifer Nuttall Martenson, Kelly Jordan Schweim, Heidi Hoover, Mary Adams, and the SDTU staff for their vital technical assistance in these studies.
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Conn JW Newburgh LH The glycemic response to isoglucogenic quantities of protein and carbohydrate J Clin Invest 1936 15 665 671 16694439
Joslin EP Diabetic Manual of the Doctor and Patient. 1945 Philadelphia, Lea & Febinger
Nuttall FQ Mooradian AD Gannon MC Billington CJ Krezowski PA Effect of protein ingestion on the glucose and insulin response to a standardized oral glucose load Diabetes Care 1984 7 465 470 6389060
Krezowski PA Nuttall FQ Gannon MC Bartosh NH The effect of protein ingestion on the metabolic response to oral glucose in normal individuals. Am J Clin Nutr 1986 44 847 856 3538843
Berger S Vongaraya M Insulin response to ingested protein in diabetes. Diabetes 1966 15 303 306 5936455
Fajans SS Floyd JC Pek S Knopf RF Jacobson M Conn JW Effect of protein meals on plasma insulin in mildly diabetic patients. (Abstract #1). Diabetes 1968 17 297 5651713
Gannon MC Nuttall FQ Neil BJ Westphal SA The insulin and glucose responses to meals of glucose plus various proteins in type 2 diabetic subjects Metabolism 1988 37 1081 1088 3054432 10.1016/0026-0495(88)90072-8
Gannon MC Nuttall FQ Saeed A Jordan K Hoover K An increase in dietary protein improves the blood glucose response in people with type 2 diabetes Amer J Clin Nutr 2003 78 734 741 14522731
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| 15507150 | PMC524032 | CC BY | 2021-01-04 16:38:32 | no | Virol J. 2004 Aug 26; 1:1 | latin-1 | Virol J | 2,004 | 10.1186/1743-422X-1-1 | oa_comm |
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Virol JVirology Journal1743-422XBioMed Central London 1743-422X-1-21550715410.1186/1743-422X-1-2ResearchGenetically distant American Canine distemper virus lineages have recently caused epizootics with somewhat different characteristics in raccoons living around a large suburban zoo in the USA Lednicky John A 1jlednic@lumc.eduDubach Jean 2JEDUBACH@BrookfieldZoo.orgKinsel Michael J 3MKINSEL@lumc.eduMeehan Thomas P 4TOMEEHAN@BrookfieldZoo.orgBocchetta Maurizio 5MBOCCHE@lumc.eduHungerford Laura L 6LHUNGERF@epi.umaryland.eduSarich Nicolene A 1nsarich@lumc.eduWitecki Kelley E 1kelley@uchicago.eduBraid Michael D 1michaelbraid@yahoo.comPedrak Casandra 1CPedrak@perilous.es.anl.govHoude Christiane M 1christyhoude@yahoo.com1 Department of Pathology, Loyola University Medical Center, Maywood, Illinois 60153, USA2 Animal Molecular Genetics, Brookfield Zoo, Brookfield, Illinois 60513, USA3 Zoological Pathology Program, University of Illinois at Urbana-Champaign, Loyola University Medical Center, Maywood, Illinois 60513, USA4 Department of Animal Health, Veterinary Services, Brookfield Zoo, Brookfield, Illinois 60513, USA5 Cancer Immunology Program, Cardinal Bernardin Cancer Center, Department of Pathology, Loyola University Medical Center, Maywood, Illinois 60513, USA6 Department of Epidemiology and Preventive Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA2004 2 9 2004 1 2 2 6 7 2004 2 9 2004 Copyright © 2004 Lednicky et al; licensee BioMed Central Ltd.2004Lednicky 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
Mortality rates have differed during distemper outbreaks among free-ranging raccoons (Procyon lotor) living around a large Chicago-area zoo, and appeared higher in year 2001 than in 1998 and 2000. We hypothesized that a more lethal variant of the local Canine distemper virus (CDV) lineage had emerged in 2001, and sought the genetic basis that led to increased virulence. However, a more complex model surfaced during preliminary analyses of CDV genomic sequences in infected tissues and of virus isolated in vitro from the raccoons.
Results
Phylogenetic analyses of subgenomic CDV fusion (F) -, phosphoprotein (P) -, and complete hemagglutinin (H) – gene sequences indicated that distinct American CDV lineages caused the distemper epizootics. The 1998 outbreak was caused by viruses that are likely from an old CDV lineage that includes CDV Snyder Hill and Lederle, which are CDV strains from the early 1950's. The 2000 and 2001 viruses appear to stem from the lineage of CDV A75/17, which was isolated in the mid 1970's. Only the 2001 viruses formed large syncytia in brain and/or lung tissue, and during primary isolation in-vitro in Vero cells, demonstrating at least one phenotypic property by which they differed from the other viruses.
Conclusions
Two different American CDV lineages caused the raccoon distemper outbreaks. The 1998 viruses are genetically distant to the 2000/2001 viruses. Since CDV does not cause persistent infections, the cycling of different CDV lineages within the same locale suggests multiple reintroductions of the virus to area raccoons. Our findings establish a precedent for determining whether the perceived differences in mortality rates are actual and attributable in part to inherent differences between CDV strains arising from different CDV lineages.
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Background
Canine distemper virus (CDV) (family Paramyxoviridae, genus Morbillivirus) is a single-stranded (negative-sense) enveloped RNA virus that is highly contagious and transmitted predominantly by aerosols [1]. Long known to cause potentially lethal disease among members of the Canidae, Mustelidae, and Procyonidae, CDV has recently been detected as a cause of morbidity and mortality in large felids [2], fresh-water seals (Phoca sibirica) [3], and various other animals. CDV killed more than 10,000 Caspian seals (Phoca caspica) in year 2000 [4], and decimated an African wild dog (an endangered species) breeding pack [5], demonstrating that CDV epidemics can be catastrophic. It also killed 1/3 of the Serengeti lions (Panthera leo) in 1994, whereas mortality due to CDV had not been previously described in large felids [6]. However, CDV is not uniformly lethal in related species; unlike the situation with lions, house cats (Felis sylvestris catus) can be infected by CDV wherein pathogenesis is unclear [7,8].
The increased importance of emerging pathogens has been most commonly attributed to changes in interactions between species or other ecological parameters [9], though changes in the pathogens or host susceptibility could also play a role. Closely related genomic variants of a particular RNA virus can arise within a host, forming a population of viruses referred to as quasispecies [10,11]. Viral quasispeciation can generate new disease patterns and broaden host ranges [10-12]. It is possible that CDV quasispeciation may account for the increasing number of clinically typical distemper cases in dogs [including those vaccinated against CDV). This implies the emergence of CDVs with different antigenic properties from the vaccine strains [5,13-15,23].
Serological tests of various captive carnivores in 1997 indicated seroconversion to CDV occurred among 28% of large felids after they were housed in outdoor exhibits at a large zoo located near Chicago (Illinois, USA) (T. Meehan and L. Hungerford, unpublished). The animals were CDV seronegative prior to outdoor display, and had not been vaccinated against CDV. Seroconversion did not occur among large felids kept indoors. It was thus apparent that the large felids acquired CDV infections during outdoor display. Distemper epizootics occur sporadically among area raccoons (Procyon lotor), and free-ranging raccoons were implicated as the source of CDV to the susceptible animals of the zoo, as large numbers of raccoons from adjoining forest preserves forage on the zoo grounds. The raccoons potentially transmit CDV to zoo animals indirectly through droplet infection and perhaps also through contact infection of nasal and oropharyngeal mucosa, since they are sometimes caught and consumed by zoo carnivores. Although CDV can cause high mortality in raccoons [16,17], it can also circulate widely in a population with many survivors, as documented by seroprevalence studies [18]. This suggests not only a substantial disease reservoir, but also the possibility of CDV strains with different levels of virulence. The latter notion cannot be readily resolved by current serology approaches, especially considering that CDV is presently considered monotypic by serology. For zoos where free-ranging raccoons can regularly be found, there is concern that CDV carried by raccoons might pose a health risk to susceptible collection species for two reasons: (a) CDV is highly infectious and an acknowledged lethal pathogen of many carnivores, and (b) CDV might mutate into a variant capable of broad-spectrum lethality. Wild raccoons were previously incriminated as the source of epizootics in captive carnivores in zoological collections and conservation parks [2,19]. Also, clinically apparent CDV infections occur in some omnivores such as Japanese snow monkeys (Macaca fuscata) [20] and collared peccaries (Tayassu tajacu) [21], raising the possibility that CDV might also cause lethal epidemics among non-carnivores.
Live raccoons are trapped on zoo grounds. Those with clinical neurologic signs are euthanized, necropsied, and examined for evidence of distemper or other infections. Dead raccoons found on-site are similarly evaluated whenever possible [22]. These procedures are routinely conducted as part of disease surveillance initiatives of the zoo and local and state agencies, especially because rabies is a major concern, and neurological signs that occur in distemper sometimes mimic rabies [22].
Distemper was detected in raccoons on zoo grounds in years 1998, 2000, and 2001 but not in 1999, 2002, and 2003. A total of 9/25 (36%) of the animals submitted for necropsy in 1998 and 1/14 (7%) in 2000 had lesions consistent with CDV infection. The number of animals submitted in 2001 was higher (n = 49) than for years 1998 and 2000, as was the percentage positive for CDV: 26/49 (45%). Precise data about the number of animals living within the forest preserve was not available. It was also not known whether significantly different numbers of animals utilized the zoo during the time line of this study (1998–2002). Nevertheless, there appeared to be a surge in distemper mortality in 2001, and comprehensive necropsy evaluations (performed by the same pathologist) revealed that the CDV lesions of the 2001 animals differed somewhat from those seen in the 1998 and 2000 animals. Since phylogenetic analyses suggest that wild-type CDVs differ according to geographical distribution rather than to host species [6,23], we asked whether a local CDV strain had mutated into a more virulent variant in 2001, causing the perceived rise in mortality and differences in histological presentation.
We first sought to identify the local lineage of CDV through direct sequence analysis of viral RNA (vRNA) in infected raccoon tissues and also attempted virus isolation from the specimens. Virus isolation was important not only to confirm direct sequence analyses but also: (a) because it was possible that direct sequence analyses might not work for various technical reasons, and (b) for future vaccine development in the event that unusual viral variants were detected for which current vaccines were ineffective. Following the example of previous investigators, we tried to obtain the identity of the circulating local CDV by determining the sequence of a subsection of the CDV phosphoprotein (P) gene, since the P-gene tends to remain conserved within clades of a given CDV lineage [24], and is useful for phylogenetic analysis [5,24,25]. To reduce the risk of bias arising from analysis of only one section of the CDV genome, we also examined a subsection of the CDV fusion (F) gene sequence that encodes a protein cleavage site [subtilisin-like endoprotease motif (-R-X-K/R-R-)] and the fusion domain [26]. The F-protein is the most conserved among morbilliviruses [27], and the F-gene sequence can be used to determine phylogenetic relationships between different morbillivirus species, such as the relationship between CDV and the closely related morbillivirus of salt-water seals called Phocine distemper virus-1 (PDV-1) [28]. F-gene analysis would thus help establish whether the virus was authentic CDV and not a related raccoon morbillivirus. Finally, the entire CDV receptorbinding hemagglutinin (H) gene was analyzed, since the H protein is the major determinant of tropism and cytopathogenicity [29], and is useful for phylogenetic analyses [6,23].
Whereas all the viruses were related to American CDV strains, the 1998 and 2001 viruses were clearly resolved by phylogenetic analyses into two genetically distant CDV clusters (lineages). The 2000 virus apparently stems from a sublineage related to the 2001 viruses.
Results
Pathology evaluation
In general, the results obtained from gross and histologic examinations of the animals were typical for CDV-induced distemper. Major findings included non-suppurative encephalitis and necrotizing bronchointerstitial pneumonia of variable severity (Table 1). As expected for wild raccoons of this area, multicentric parasitism was common, but additional underlying diseases were generally not noted. The presence of Encephalomyocarditis virus (EMCV) in animals 01-2641 and 01-2690, however, was unexpected.
Table 1 Histologic lesions of CDV-infected raccoons.
Raccoon Sex M/Ya Siteb Presentation Encephalitisf Pneumoniah Other findings EMCVk
98-2645 F 8/98 FPc Euthanized ++; Demyelination; axonal loss; few IBg +++; Chronic; no IB Lymphoid depletion (LNi); IB – other sites -
98-2646 M 8/98 ZGd Dead - ++; Sub-acute to chronic; no IB IB – other sitesj -
98-2654 M 10/98 ZG Euthanized Rare axonal loss ++ Ocular discharge; CDV in footpad ("Hardpad" disease); lymphoid depletion (LN and spleen) -
98-2655 F 10/98 ZG Dead ++; IB common None Lymphoid depletion (LN and spleen); IB – other sites -
98-2666 F 12/98 ZG Euthanized ++; Axonal loss; rare neuronal IB ++; Chronic; no IB Lymphoid depletion (LN and spleen); IB – other sites -
00-2601 M 1/00 ZG Euthanized ++; Rare neuronal IB; severe axonal loss None IB – other sites -
01-2641 M 5/01 OFPe Euthanized +; IB; syncytia in hippocampus +++ with syncytia; IB Lymphoid depletion (LN and spleen); IB – other sites + brain, LN, spleen)
01-2663 F 6/01 ZG Euthanized None +++ with syncytia; IB Lymphoid depletion (LN and spleen); IB – other sites -
01-2676 F 7/01 ZG Euthanized +; Axonal loss; neuronal necrosis; IB; syncytia in hippocampus +++; IB Lymphoid depletion (LN); IB – other sites -
01-2689 F 8/01 ZG Euthanized +; IB ++ with syncytia; IB Lymphoid depletion (LN and spleen); IB – other sites; rhinitis; purulent conjunctivitis -
01-2690 M 8/01 ZG Euthanized Rare neuronal necrosis; IB None Lymphoid depletion (LN); IB – other sites + (spleen)
aM/Y; Month and year animal examined by necropsy and specimens frozen.
bSite; Location where animal was trapped or found dead.
cFP; Forest preserve at border of zoo.
dZG; Zoo grounds.
eOFP; Off-site forest preserve
fEncephalitis: -, none; +, mild; ++, moderate.
gIB; Characteristic intracytoplasmic or intranuclear inclusion bodies formed by Canine distemper virus.
hPneumonia: +, mild; ++, moderate; +++, severe.
iLN; Lymph node.
JIB – other sites: Inclusion bodies in other epithelial sites.
kEMCV, Encephalomyocarditis virus.
Histologic differences in the CDV lesions were apparent. While lymphoid depletion and characteristic eosinophilic intracytoplasmic inclusions in various epithelial tissues were observed in all years, inclusion bodies were more plentiful in the brain and lung tissues of raccoons examined in year 2001 than those of years 1998 and 2000. Of note, small and large (multinucleated) syncytia were present in the central nervous system and (Fig. 1A) and lung (Fig. 1B) of some raccoons from year 2001 but not in animals from 1998 and 2000 (Table 1).
Figure 1 Panel A. Hematoxylin and eosin (H & E) – stained thin section of hippocampus tissue from raccoon 01-2676. Syncytia are identified by large arrows. Some CDV inclusion bodies are indicated (small arrows). Original magnification × 200. Panel B. Thin section (H & E-stained) of lung tissue from raccoon 01-2663. Syncytia and CDV inclusion bodies are identified as in panel A.
Isolation of virus from infected tissues
Virus was isolated from the tissues of 11/11 animals (Table 2) [22]. Viral cytopathic effects (CPE) in Vero cells consisted of the formation of granular-appearing cytoplasm with vacuolization (small vacuoles), followed by rounding of the cells and detachment, and rare formation of small stellate syncytia (consisting of 2–3 cells fused together) for viruses isolated from year 1998 and 2000 specimens or frequent larger rounded syncytia typically containing >8 nuclei in viruses from year 2001 [22]. Thus, the 2001 viruses appeared to form large syncytia in vivo (Table 1) and in vitro [22].
Table 2 CDV detection by direct RT-PCR of tissue and by virus isolation.
Raccoon Tissue Direct RT-PCR of Tissue Virus isolation
98-2645 brain - +
98-2646 brain - +
98-2654 brain + +
98-2655 brain - +
98-2666 brain + +
00-2601 brain + +
01-2641 brain + +
lung + +
lymph node - +
spleen + +
01-2663 brain + +
lung + +
lymph node - +
spleen + +
01-2676 lung + +
lymph node + +
01-2689 brain + +
lymph node + +
spleen + +
01-2690 brain + +
kidney - -
liver - -
lung + +
spleen - +
RT-PCR and nucleotide sequence analyses
Where direct comparisons were possible, viral genomic sequence analyses indicated that the subgenomic viral F- and P- and full-genomic H-gene sequences did not change during primary isolation in three different cell lines (MDCK, MV1 Lu, and Vero [22]. Thus, for viruses from animals 98-2645, 98-2646, and 98-2655, for which direct RT-PCR from infected tissues failed (Table 2), it was likely that the sequences obtained were authentic.
The subgenomic F- and P- gene of this study were previously reported [22] and deposited at GenBank (Table 3). The full-genomic H-gene sequences are available at GenBank (Table 3); since the H-gene sequences are relatively long (1,824 bp), only the deduced aa sequences are shown (Fig. 2). As for the P-gene, virus CDV 98-2666 had two slightly different H-gene sequences that were detected in vRNA in infected tissues; the same H-gene sequences were detected in corresponding virus isolates. The dominant H-gene sequence determined directly from infected tissues is labelled 98-2666 (Fig. 2, and H-gene sequence 98-2666 in Table 3), and is identical to the sequence of variant 98-2666-1 (Fig. 2, and H-gene sequence 98-2666-1 in Table 3), whereas the H-gene sequence of the second variant is labelled 98-2666-2. An example of RT-PCR for the CDV H-gene of a primary virus isolate in Vero cells is shown in figure 3.
Figure 2 Deduced H-protein amino acid sequences of raccoon CDVs. Numbers above the sequences identify aa positions in the H-protein of CDV reference strain Onderstepoort.
Table 3 GenBank accession numbers of raccoon CDVsequences.
Virus F-gene H-gene P-gene
98-2645 AY445077 (entire genome)
98-2646 AY542312 (entire genome)
98-2654-1 AY466011 (entire genome)
98-2654-2 AY289612 (AY466011)d AY286485
98-2655 (AY289612)a AY548109 AY263373
98-2666-1 (AY289612)a AY548110 AY286486
98-2666-2 (AY289612)a AY548111 AY286487
00-2601 AY443350 (entire genome)
01-2641-1 AY289614 AY526496 AY288310
01-2641-2 (AY289614)b (AY526496)e AY321298
01-2663 AY289615 NDf AY288308
01-2676 (AY289615)c AY498692 AY288309
01-2689 (AY289615)c AY465925 AY286488
01-2690 (AY289615)c (AY465925)g AY264266
aIdentical to the sequence of AY289612.
bIdentical to the sequence of AY289614.
cIdentical to the sequence of AY289615.
dIdentical to the sequence of AY466011.
eIdentical to the sequence of AY526496.
fND, Not determined.
gIdentical to the sequence of AY465925.
Figure 3 Ethidium-bromide gel electrophoresis analysis of subgenomic H-gene RT-PCR amplicons. For CDV-2676, shown are the 1104 bp product (lane 1) using primers CDV-HforD and CDV-Hrev75, and the 1026 bo product (lane 2) using primers CDVH-forB and CDV-HrevC (29). A 2% agarose gel was used. Molecular weight markers are loaded in the lane marked "M". Positive and negative controls were run separately and are not shown.
Phylogenetic analyses
The 70% majority-rule consensus parsimony (Fig. 4) and neighbor-joining (not shown) cladograms for the P-gene sequences are almost identical. Both analyses grouped the 1998 sequences together in a single clade with CDV-Lederle and -Snyder Hill with high bootstrap support. These viruses have P-gene sequences similar to those of CDVs Onderstepoort and Rockport, from S. Africa and Sweden, respectively. The cluster of the 2001 sequences (01-2663, -2676, -2689, -2690) was also the same in both cladograms. However, while parsimony joined the 01-2641 sequence from an offsite raccoon to the base, the distance based tree grouped this sequence with CDV A75/17. The 2000 virus was also not resolved by either method of analysis. Of the 390 bases, 34 were informative. Derivatives of the 1998 cluster form a distantly related lineage to that of 2001 cluster that is nevertheless rooted in the CDV group when compared to PDV-1 as an outgroup. CDV Lederle appears to be more derived than A9224/14b (detected in 1992 in a California (USA) raccoon [6]).
Figure 4 P-gene 70% majority rule parsimony consensus tree. Viruses from this study are high-lighted by a grey background. The animal source and GenBank numbers from top to bottom are: (1) (South African dog) AF305419, (2) (Swedish dog) AF181446, (3) (American dog) AY286480, (4) (American dog) AY286481, (5 – 17) Illinois raccoons, GenBank numbers in Table 3, (18) (German dog) AY386315, (19) (Bulgarian dog) AF259549, (20) (American dog) AF164967, (21) (German ferret) AF259550, (22) (Siberian seal) AF259551, (23) (Japanese dog) AB028916, (24) (Californa raccoon A9224/14b, reference 6), (25) (Phocine distemper virus) D10371.
There were a total of 335 nucleotides in the F-gene and 32 of these were parsimony informative. Both parsimony (Fig. 5) and distance based (not shown) analyses produced the same topology. The off-site raccoon 01-2641 failed to group with any other sequences, joining at the base. The 1998 sequences formed a single cluster within a clade that included Lederle, Snyder Hill, and vaccine strains Onderstepoort and Bul. 170 (originally isolated from a Bulgarian dog) [30]. This clade also included the 00-2601 sequence. The remaining 2001 viruses formed a single clade with high bootstrap support.
Figure 5 F-gene 70% majority rule parsimony consensus tree. Viruses from this study are high-lighted by a grey background. GenBank accession numbers are: (1) CDV Lederle (AY288311); (2) Snyder Hill (AY288312); (3 – 10, Illinois raccoons, Table 3); (11) Onder., Onderstepoort (AF378705); (12) Bul. 170, Bulgarian dog (AF259549); (13 – 17, Illinois raccoons, Table 3); (18) CDV A75/17 (AF164967); (19) PDV2, Phocine distemper virus 2 (L07075); (20) Danish dog (AF355188); (21) CDV 5804 (from German dog) (AF026241); (22) Hyena (AF026233); (23) Marten (AF026230); (24) PDV-1 (L07075).
The H-gene parsimony (Fig. 6) and neighbor-joining (not shown) topologies were identical with respect to the clades that include the raccoon viruses from this study. Out of 1,824 nucleotides, 420 of these were parsimony informative. As with the previous genes, the 1998 isolates and the 2000/2001 viruses formed separate clusters. The 1998 sequences joined the tree at a basal position in both analyses. The 2000 and off-site raccoon 01-2641 sequences grouped with the large felids from another zoo in Illinois.
Figure 6 H-gene 70% majority rule parsimony consensus tree. Arrows or boxes demarcate locations of viruses from this study. GenBank accession numbers are: (1) CDV 00-2601 (Illinois raccoon, Table 3); (2) Chinese leopard (Z54156); (3) 01-2641 (Illinois raccoon, Table 3); (4) black leopard (Z47763); (5) black panther (Z54166); (6 – 8, Illinois raccoons, Table 3); (9) raccoon (Z47765); (10) A75/17 (AF164967); (11) dog (USA) (Z47762); (12) javelina (Z47764); (13) raccoon dog Tanu (AB016776); (14) dog (Taiwan) (AY378091); (15) dog Hamam (D85754); (16) dog KDK1 (AB025271); (17) dog Ueno (D85753); (18) dog Yanaka (D85755); (19) giant panda (AF178038); (20) dog 5804 (AY386315); (21) dog Denmark (Z47761); (22) dog 91A (AF478544); (23) dog isolate A (AF478543); (24) dog 91B (AF478546); (25) dog 91C (AF478548); (26) dog 91D (AF478550); (27) dog isolate C (AF478547); (28) dog isolate B (AF478545); (29) dog isolate D (AF478549); (30) dog isolate 2544 (Z77672); (31) dog isolate 404 (Z77671); (32) dog isolate 4513 (Z77673); (33) dog (Turkey) (AY093674); (34) ferret (X84999); (35) mink (Z47759); (36) lesser panda (AF178039); (37) Siberian seal (X84998); (38) dog (China) (AF172411); (39) dog (Greenland) (Z47760); (40) dog 26D (AB040766); (41) dog 5B (AY297453); (42) dog 5VD (AY297454); (43) dog 98-002 (AB025270); (44) dog HM-3 (AB040767); (45) dog HM-6 (AB040768); (46 – 54, Illinois raccoons, Table 3), (55) Snyder Hill (AF259552); (56) Onderstepoort (AF378705); (57) PDV-1 (AF479274).
Noteworthy, P-, F- and H- gene analyses indicate that the CDV sequences segregate according to geography and not to species. Since the H gene had the largest number of nucleotides, pairwise genetic distances were calculated. The 1998 isolates were most similar to the Onderstepoort and Snyder Hill (D = 4% and 1% respectively) while the 2001 isolates were most distant (D = 9% and 10% respectively). Distances within 1998 viruses were low (D ≤ 0.2%); within 2001, distances were slightly higher (D = 1%); and comparing years 1998 with 2000 and 2001, distances were highest (D = 7% to 9% respectively).
When the P-, F- and H- genes were combined into a single linear sequence and analyzed using parsimony and neighbor-joining algorithms with only PDV-1 as an outgroup, two independent clades are formed, the 1998 clade and the 2000/2001 clade (data not shown). In the later group, both methods join the 2000 sequence (00-2601) at a basal position to the 01-2641 off-site raccoon followed by the 2001 isolates.
Discussion
This report shows that different CDV sublineages stemming from at least two genetically distant CDV lineages recently circulated through the local raccoon population. Our conclusion is based on numerous observations: differences in the lesions observed in animal tissues, possible dissimilarities of virulence between the viruses, variation in one viral phenotype in tissue culture (formation of large syncytia by the 2001 viruses), and from the results of nucleotide sequence and phylogenetic analyses. CDV is not maintained in hosts that recover from distemper, and persistent CDV infections do not occur. However, CDV infects a wide range of genera, and though each individual population may be small, the number of alternative host species may be substantial [1]. Forest preserves around the zoo contain many species susceptible to CDV, and it appears by inference there are separate reservoirs of different CDV lineages within the area of this study.
Since past studies indicated that wild-type CDVs differed according to geographical distribution [6,23], we initially surmised that the local CDV occasionally formed clades of highly virulent CDV variants, resulting in periodic high mortality distemper outbreaks. We also speculated that over time, highly virulent viruses would undergo extinction, and ensuing epizootics would arise from less virulent CDV variants that could affect most of the hosts without killing them. Thus, there would be an apparent oscillation (periodicity) of the mortality rates. The situation is not as straightforward, however. As shown in figures 4,5,6, at least two different CDV lineages circulated in the raccoons from 1998 – 2001. Our findings thus suggest that the outcomes of distemper might also be influenced by properties unique to different CDV lineages and their genetic variants ("strains").
The viruses from year 2001 formed syncytia in vivo and in vitro. Previously, an inverse relationship between the proficiency of syncytium formation and the level of CDV virulence was reported: the more attenuated a strain is, the higher its fusogenicity, and fusogenicity was attributed to the viral H-protein [31-34]. Therefore, the findings of this study may appear antidogmatic because increased mortality was associated with the 2001 viruses, which formed large syncytia in vivo and in vitro. However, past notions concerning the inverse relationship between fusogenicity and virulence may be imprecise. Indeed, virulent wild-type CDVs that formed syncytia in Vero cells were recently reported; the same study demonstrated that genetic changes within the H-gene were not required for CDV growth in Vero cells [35], as was found in this and our previous study [22]. Also, newer studies indicate that syncytium formation by CDV requires the concerted activities of both the H- and F- proteins [36-38], and that CDV virulence is the combined affect of various proteins including the F- and H- proteins [39]. Thus, whereas animal studies were not performed with the virus isolates of this study to directly test whether they differ in virulence, the formation of large syncytia does not rule out the possibility that the 2001 viruses are highly virulent. Noteworthy, the 2001 viruses were detected in the hippocampus and alveoli of the raccoons. Both sites were considered unusual targets of a CDV variant that was lethal to Serengeti lions, whereas CDV in dogs was said to most frequently target the brain stem and bronchi [40,41]. It is possible that tissue localization, especially with regard to the hippocampus, correlates with virus strain. In our experience, CDV in raccoons does not preferentially target the brain stem but rather infects all portions of the brain, with the possible exception of the hippocampus. We will be able to address the question whether specific CDV strains localize in the hippocampus of raccoons as we accumulate additional data from future outbreak, and after we conduct animal tests with the viruses we isolated. In contrast, CDV targets epithelial cells, and the presence of CDV in the alveoli of raccoons with distemper is common.
H-gene phylogenetic analyses (figure 6) suggest that a viral lineage that includes CDV A75/17 (isolated in 1975) [32] and the 2000 and 2001 viruses had infected various species including large felids [Fig. 6 and reference 6] for at least 28 years on both coasts and a midwestern state (and thus presumably throughout the continental USA). The seemingly widespread distribution suggests that viruses stemming from this lineage may be the dominant "American" CDV currently in circulation in the continental USA. The F -, H-, and P-gene sequence analyses (figures 4,5,6) indicate that the 1998 viruses stem from a different CDV lineage that includes American CDV strains Lederle and Snyder Hill. A recent phylogenetic analysis of the P-gene by an independent laboratory that utilized some of our P-gene data generated similar results [42]. Because they were isolated before CDV Lederle and Snyder Hill were acquired from the ATCC for this study and have distinguishable F- and H-gene sequences [22], it is certain that the 1998 CDV isolates are not due to laboratory contamination. Yet, phylogenetic analyses indicate that the CDV Lederle and Snyder Hill sequences are distant to, and in the case of the H-gene, ancestral to, those of the 2000 and 2001 viruses, which are as genetically distant from the 1998 viruses as they are from Snyder Hill. The source of the 1998 viruses is thus intriguing. Prior to 1997, some area raccoons were trapped, vaccinated against CDV, then released in an attempt to curtail CDV epidemics within the local raccoon population. CDV Lederle has been used as a vaccine strain in the past [3]. The vaccine used for the raccoons, (Galaxy-D, from Schering-Plough, Kenilworth, NJ), though, was made with CDV Onderstepoort, which is easily distinguished from the 1998 viruses by F-, H-, and P-gene analyses. However, we still could not rule out the possibility that the 1998 viruses are vaccine escape viruses from a dog vaccinated with CDV Lederle. Dogs and raccoons often frequent the same feeding sites (such as refuse disposal zones) in urban areas. The possibility of reversion to virulence of attenuated CDV exists [43], and a vaccine escape virus was proposed as a cause of distemper in a dog in Belfast, Northern Ireland [3]. We could not find a current manufacturer of anti-CDV vaccine in the USA that uses CDV Lederle. However, such vaccines were in distribution overseas around 1998 [22], and the Chicago area undergoes constant population flux, including translocation of inhabitants (and their pets) from outside of the continental USA. Related to this, the live attenuated CDV vaccine (Galaxy-D) used by the zoo up to 1997 caused vaccine-mediated distemper in different species at the zoo that had been vaccinated. For this reason, use of that particular vaccine was discontinued; instead, Purevax™, a recombinant CDV-canary pox virus vaccine (Merial, Duluth, GA) is used; the CDV insert in the canary pox virus genome is incomplete and cannot be infectious. CDV-Lederle was isolated in 1951 from a dog with encephalitis (information provided by ATCC). An alternative interpretation of our findings is that the CDV lineage that gave rise to CDV Lederle has stabilized in the local animals and is still actively circulating; more studies are needed to resolve this matter.
EMCV has been isolated or detected in raccoons before [44,45]. However, pathogenesis was uncertain, and it was thought that raccoons are a dead-end host for this virus [45]. It is known that mortality during an active case of distemper is increased in the presence of polymicrobial disease [46]. For example, a lethal outcome occurs in dogs co-infected with CDV, Bordetella bronchiseptica, and Toxoplasma gondii. It is possible that the increased mortality in 2001 was due to secondary infections with EMCV; however, no lesions attributable to EMCV were observed in pathology exams of the animals of this study, and EMCV was not isolated from all of the 2001 specimens. The significance of isolating EMCV from the brain tissue of animal 01-2641 is thus uncertain.
Our findings are especially useful for the molecular epidemiology of CDV in local wildlife, as they provide a molecular basis for CDV surveillance in area wildlife. Whereas it is considered difficult to obtain field isolates of CDV, we succeeded and can now obtain complete viral genomic sequence data (it would be difficult to do so relying solely on the limited amount of archived CDV-infected tissues from the animals of this work). Taken together, we can now monitor viral genetic drift during a long-term study of CDV in local raccoons, and will be able to conduct animal studies with the newly isolated viruses. We can also clone relevant CDV virulence genes, and express and study the biochemical properties of their specific products in vitro. The baseline genetic values established here will be helpful toward the development of a contemporary field-based model (since the animals are free-ranging) for studies on the emergence, evolution, maintenance, and transmission of morbilliviruses, and the efficacy of vaccines against changing viruses.
Conclusions
The 1998 and 2001 distemper outbreaks were caused by two genetically distant American CDV lineages. Since CDV does not cause persistent infections, the cycling of different CDV lineages within the same locale suggests multiple reservoirs were responsible for the reintroduction of the virus to area raccoons. Whereas different susceptible species of the forest preserves and perhaps also some caged animals of the zoo are the most likely reservoirs, our study raises the possibility that vaccines might also be a source of CDV. The perceived differences in mortality rates that occur during intermittent distemper epizootics may be attributed in part to inherent differences between CDV strains.
Methods
Raccoon tissues
The raccoon tissues used in this study were described previously [22]; relevant clinical and histologic findings are presented in Table 1. Brain tissue was available for animals 98-2645, -2646, -2654, -2655, -2666 (n = 5, each collected in year 1998) and 00-2601 (n = 1, from year 2000) (Table 1). Additional tissues were available for animals 01-2641, -2663, -2676, -2689, and -2690 (n = 5, each collected in year 2001) (Table 2).
Virus isolation
Detailed virus isolation procedures were described previously [22]. Briefly, CDV was isolated in vitro in MDCK, MV1-Lu, and Vero cells, eliminating the need for virus isolation in specific pathogen-free animals or in primary macrophages or other suitable cells derived thereof [29].
RNA purification and RT-PCR
RNA purification and RT-PCR methods were previously detailed [22]. Briefly, vRNA was extracted directly from infected tissues when possible, as well as from CDV-infected tissue culture cells or from liberated CDV virions in spent cell growth media, using dedicated commercial kits (Qiagen Inc., Valencia, CA). For the American CDV strains of this work, many RT-PCR primers based on the sequence of American CDV isolate A75/17 (GenBank No. AF164967) were more effective than primers described for foreign CDV strains [22].
Nucleic acid sequencing
Methods used for nucleic acid sequencing were previously described [22]. Briefly, all sequences were determined at least twice, starting from the purification of new RNA samples from each specimen, and both strands of each PCR amplicon were sequenced. Slab-gel sequencing utilizing dye-terminator chemistries (LI-COR, Lincoln, NE) was used at the inception of the project, then replaced by capillary sequencing using ABI-PRISM technology (Applied Biosystems, Foster City, CA). The CDV gene sequences in infected tissues were exactly like those in matched primary viral isolates [22]. The GenBank accession numbers for all the virus sequences of this work are given in Table 3.
Phylogenetic analyses
Phylogenetic trees of the P-, F-, and H-gene sequences were constructed using the maximum-parsimony and neighbor-joining algorithms in Phylogeny Analysis Using Parsimony (PAUP) Beta Version 4.0B10 for Macintosh [47]. Heuristic searches were conducted with "simple" addition and the tree-bisection-reconnection method of branch swapping. Distance-based analyses using the minimum-evolution criterion were also conducted within PAUP using Kimura's-two-parameter model [48]. Phylogenetic tree reliability was estimated with 1000 bootstrap replications [49,50]. The appropriate Phocine distemper virus sequence (PDV-1) was included for outgroup rooting.
P-gene phylogenetic analyses were performed after an alignment of 25 P-gene sequences. Each P-gene sequence consisted of 390 ungapped positions (nucleotides 2154 to 2543 of CDV reference strain Onderstepoort) within the P-gene PCR amplicon. Only the internal 390 bp section of the P-gene PCR amplicon (432 bp) was analyzed because many relevant GenBank entries did not include the entire sequence amplified by the P-gene primers of this study. An additional P-gene sequence for raccoon A9224/14b was obtained from published data currently not deposited at GenBank [6]. Similarly, 24 ungapped F-gene sequences corresponding to nt 5399–5733 (335 bp) of CDV Onderstepoort were analyzed. Unlike the P- and F-genes, the entire H-gene was analyzed since many complete H-gene sequences were available at GenBank. Phocine distemper virus 1 (PDV1) sequences were included in the analyses for outgroup rooting.
Competing interests
None declared.
Authors' contributions
JAL co-conceived, designed, and coordinated the study, isolated virus, participated in the molecular genetic studies and sequence alignment, interpreted data, oversaw the training of technicians, and drafted the manuscript; JD performed phylogenetic analyses, interpreted data, and helped draft the manuscript; MJK performed pathology examinations, provided tissue specimens, helped draft the manuscript, and interpreted data; TPM co-conceived the study, provided serology data, helped draft the manuscript, and interpreted data; MB performed phylogenetic analyses, interpreted data, and helped draft the manuscript; LLH provided serology data and epidemiology perspectives, and helped draft the manuscript; NAS participated in virus isolation, molecular genetic studies, sequence alignment, and proofreading of the manuscript; KEW participated in virus isolation and molecular genetic studies, and MDB, CP, and CMH performed molecular genetic studies. All authors read and approved the final manuscript
Acknowledgements
The authors thank Chris Anchor and the Wildlife Division of the Forest Preserve District of Cook County for assisting with sample acquisition. Andrea Guido provided excellent technical assistance. We thank Dr. K. MacClatchey for critical review of this manuscript. Partial funding for necropsy evaluations was obtained from the Department of Animal Control Environmental Impact Program, Cook County, Illinois. Molecular and viral tests were funded by grant no. 0023 from the Conservation Medicine Center of Chicago to J.A.L.
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| 15507154 | PMC524033 | CC BY | 2021-01-04 16:38:32 | no | Virol J. 2004 Sep 2; 1:2 | utf-8 | Virol J | 2,004 | 10.1186/1743-422X-1-2 | oa_comm |
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Virol JVirology Journal1743-422XBioMed Central London 1743-422X-1-31550715210.1186/1743-422X-1-3ResearchRegulation of FeLV-945 by c-Myb binding and CBP recruitment to the LTR Finstad Samantha L 1sfinsta1@tulane.eduPrabhu Sudha 1sndprabhu@yahoo.comRulli Karen R 12rullik@saic.comLevy Laura S 1llevy@tulane.edu1 Department of Microbiology and Immunology, Program in Molecular and Cellular Biology and Tulane Cancer Center, Tulane University Health Sciences Center, New Orleans, Louisiana, USA2 Science Applications International Corporation, Frederick, Maryland, USA2004 3 9 2004 1 3 3 6 7 2004 3 9 2004 Copyright © 2004 Finstad et al; licensee BioMed Central Ltd.2004Finstad 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
Feline leukemia virus (FeLV) induces degenerative, proliferative and malignant hematologic disorders in its natural host, the domestic cat. FeLV-945 is a viral variant identified as predominant in a cohort of naturally infected animals. FeLV-945 contains a unique sequence motif in the long terminal repeat (LTR) comprised of a single copy of transcriptional enhancer followed by a 21-bp sequence triplicated in tandem. The LTR is precisely conserved among independent cases of multicentric lymphoma, myeloproliferative disease and anemia in animals from the cohort. The 21-bp triplication was previously shown to act as a transcriptional enhancer preferentially in hematopoietic cells and to confer a replicative advantage. The objective of the present study was to examine the molecular mechanism by which the 21-bp triplication exerts its influence and the selective advantage responsible for its precise conservation.
Results
Potential binding sites for the transcription factor, c-Myb, were identified across the repeat junctions of the 21-bp triplication. Such sites would not occur in the absence of the repeat; thus, a requirement for c-Myb binding to the repeat junctions of the triplication would exert a selective pressure to conserve its sequence precisely. Electrophoretic mobility shift assays demonstrated specific binding of c-Myb to the 21-bp triplication. Reporter gene assays showed that the triplication-containing LTR is responsive to c-Myb, and that responsiveness requires the presence of both c-Myb binding sites. Results further indicated that c-Myb in complex with the 21-bp triplication recruits the transcriptional co-activator, CBP, a regulator of normal hematopoiesis. FeLV-945 replication was shown to be positively regulated by CBP in a manner dependent on the presence of the 21-bp triplication.
Conclusion
Binding sites for c-Myb across the repeat junctions of the 21-bp triplication may account for its precise conservation in the FeLV-945 LTR. c-Myb binding and CBP recruitment to the LTR positively regulated virus production, and thus may be responsible for the replicative advantage conferred by the 21-bp triplication. Considering that CBP is present in hematopoietic cells in limiting amounts, we hypothesize that FeLV-945 replication in bone marrow may influence CBP availability and thereby alter the regulation of CBP-responsive genes, thus contributing to altered hematopoiesis and consequent hematologic disease.
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Background
Feline leukemia virus (FeLV) is a simple gammaretrovirus that induces degenerative, proliferative and malignant hematologic disorders in its natural host, the domestic cat. Like other natural retroviruses, FeLV is not a single genomic species but is a genetically complex family of closely related viruses subject to selective pressures in the host. Variant genomes are generated during virus replication as a result of both error-prone reverse transcription and recombination. The consequence of this variation is a diverse population that is continuously shaped in vivo and from which variants with selective advantages arise as predominant species. The variable clinical outcome of FeLV infection is thought to reflect this genetic diversity [1,2]. FeLV-945, a natural FeLV variant, was originally identified as the predominant species in a temporal and geographic cohort of infected cats. FeLV-945 was originally derived from a multicentric lymphoma of unknown phenotype and subsequently identified in degenerative and proliferative diseases of myeloid and erythroid origin from the cohort. FeLV-945 contains a unique sequence motif in the long terminal repeat (LTR) comprised of a single copy of transcriptional enhancer followed 25-bp downstream by a 21-bp sequence triplicated in tandem. The sequence and position of the 21-bp triplication in the FeLV-945 LTR was observed to be precisely conserved among eight independent multicentric lymphomas and in cases of myeloproliferative disease and anemia in animals from the cohort [[3,4], Chandhasin et al., manuscript submitted].
The 21-bp triplication was previously shown to provide transcriptional enhancer function to the LTR that contains it, and to function preferentially in primitive hematopoietic cells [5]. In K-562 cells, a human leukemia cell line considered to be primitive and multipotential [6,7], the FeLV-945 LTR was 12-fold more active than other naturally occurring FeLV LTRs examined. Further, the FeLV-945 LTR was preferentially active in K-562 cells, 4.2-fold more active than in FEA feline embryo fibroblasts [5]. Interestingly, when the U3 region of the LTR containing the 21-bp triplication was placed downstream of a heterologous promoter, the preferential activity in K-562 cells was lost. These findings suggest that the ability of the 21-bp triplication to enhance transcription preferentially in hematopoietic cells depends on the presence of the adjacent LTR binding sites in their natural array, a possibility examined further in the present study. Previous studies also showed that the 21-bp triplication in the FeLV-945 LTR confers a replicative advantage to the virus that contains it, preferentially in hematopoietic cells [8]. This growth advantage may account for the induction of tumors of the type in which FeLV-945 was identified, and may represent a selective advantage that contributes to precise conservation of the unusual LTR sequence.
Regarding the molecular mechanism by which the 21-bp triplication functions in the context of the LTR, at least two possibilities have been considered. One possibility is that the 21-bp triplication functions to maintain the appropriate spacing in the LTR between the enhancer and the promoter. A spacer function might be particularly relevant in an LTR like FeLV-945 in which the enhancer is not tandemly repeated. Substitution of the 21-bp repeat element with unrelated sequence of the same length, however, was observed to ablate the replicative advantage, thus indicating that the 21-bp triplication does not perform solely a spacer function [8]. An alternative mechanism may be that the 21-bp triplication contributes genuine enhancer function, perhaps via the binding of nuclear transcription factors. Indeed, electrophoretic mobility shift assay demonstrated that the 21-bp triplication contains binding sites for specific nuclear proteins. These observations suggested that preserving the protein binding sites may confer a selective advantage that accounts for the precise sequence conservation of the 21-bp triplication in this natural FeLV isolate [8]. The present study examined this possibility further. Binding sites were identified for the transcription factor, c-Myb, that crossed the repeat junctions of the triplication. Further, once c-Myb was bound to the triplication, the transcriptional co-activator CBP was recruited and was shown to positively regulate virus production. Considering that CBP is present in hematopoietic cells in limiting amounts, these observations suggest that FeLV-945 replication in bone marrow may influence CBP availability and thereby alter the regulation of CBP-responsive genes, thus contributing to altered hematopoiesis and consequent hematologic disease.
Results
As described above, previous studies suggested that preserving the protein binding sites may confer a selective advantage that accounts for the precise sequence conservation of the 21-bp triplication in the FeLV-945 LTR [8]. In the present study, the sequence of the 21-bp triplication was compared to a transcription factor binding site database (TFSEARCH, based on TRANSFAC; [9]) in order to identify potential binding proteins. This analysis identified two putative binding sites for the transcription factor c-Myb formed across the repeat junctions of the triplication (Figure 1). The sequence of those sites, 5'-AAACTG, closely matched the consensus c-Myb binding sequence, YAACG/TG (Y = pyrimidine; [10,11]). Mismatch between the putative binding site and the consensus sequence was observed at position 1, a position whose change from T to A is known to have little effect on binding affinity [12]. To determine whether c-Myb binds to the FeLV-945 21-bp triplication, EMSA was performed by reacting a radiolabeled triplication-containing probe with nuclear extracts from K-562 cells in the presence of increasing amounts of a known high-affinity c-Myb binding site as competitor. K-562 cells were chosen because c-Myb is known to be expressed and is thought to be a regulator of their differentiation along multiple hematopoietic lineages [13]. The results demonstrated a significant reduction in complex formation in the presence of the c-Myb site competitor, especially at amounts in ≥ 100-fold molar excess. In contrast, 250-fold molar excess of the unrelated CREB binding site had no effect (Figure 2). To confirm the presence of c-Myb in the specific protein-DNA complex formed on the 21-bp triplication, supershift EMSA was performed using nuclear extracts from K-562 cells in the presence of a monoclonal anti-c-Myb antibody. The results clearly showed decreased mobility of the specific complex in the presence of the c-Myb antibody (Figure 3A), but not in the presence of an isotype control antibody (Figure 3B). As a control to confirm that c-Myb binding required repetition of the 21-bp element, EMSA was repeated with a homologous probe derived from FeLV-A/61E, a natural isolate that contains only a single copy of the 21-bp sequence in the LTR. The results demonstrated no specific complex formation on the FeLV-A/61E-derived probe (Figure 3C), confirming that the specific complex formed on the FeLV-945-derived probe is attributable to the 21-bp triplication.
Figure 1 Diagram of the U3 region of the FeLV-945 LTR, indicating the transcriptional enhancer (hatched box), 21-bp triplication (open boxes) and transcriptional promoter (Pro). Below the diagram is shown the sequence of the 21-bp triplication, indicating putative binding sites for the c-Myb transcription factor formed across the repeat junctions. The c-Myb binding site consensus occurs in the negative strand.
Figure 2 Electrophoretic mobility shift assays (EMSA) performed using a radiolabeled probe representing the 21-bp triplication from the FeLV-945 LTR. Nuclear extracts (3.5 μg) from K-562 cells were incubated with the radiolabeled probe (1 ng). Double-stranded competitor oligonucleotides were omitted from the reaction (lanes 0), or were included in increasing amounts from 10-fold to 250-fold molar excess (10-, 25-, 50-, 100- and 250-fold excess shown). The competitors used contained a c-Myb consensus binding site (5'-TACAGGCATAACGGTTCCGTAGTGA) or a CREB consensus binding site (5'-AGAGATTGCCTGACGTCAGAGAGCTAG). Also indicated is the migration of the radiolabeled probe without the addition of nuclear extract (lanes C).
Figure 3 Supershift EMSA in the presence of a c-Myb-specific antibody. (A). Nuclear extracts (5 μg) from K-562 cells were incubated with the radiolabeled GS945 probe (2.4 ng) representing the 21-bp triplication from the FeLV-945 LTR. Shown are probe only (lane 1), complex formation in the presence of nuclear extract (lane 2), and complex formation in the presence of 200-fold molar excess of non-specific (lane 3) or specific competitor (lane 4). Reaction performed in the presence of monoclonal antibody to c-Myb (4 μg) resulted in supershift of the specific complex (lane 5) which was not observed in the presence of 200-fold molar excess of specific competitor (lane 6). (B). Lanes 1, 2 and 3 represent repetitions of lanes 1, 2 and 5 of (A). Reaction with a isotype control antibody (lane 4) did not result in supershift. Indicated are the specific complex (solid arrow), non-specific complexes (open arrows), and the supershifted complex (asterisk). (C). EMSA performed using the radiolabeled GS61E probe, which contains only a single copy of the 21-bp element. Shown are probe only (lane 1), reaction performed in the presence of K-562 nuclear extract (5 μg; lane 2), and reaction performed in the presence of 100-fold molar excess of unlabeled GS945 (lane 3), GS61E (lane 4) or non-specific competitor (lane 5). The absence of complex formation using the GS61E probe demonstrates the requirement for the 21-bp triplication.
To evaluate whether c-Myb binding to the 21-bp triplication regulates LTR function, reporter plasmids were constructed in which expression of the firefly luciferase gene was driven by the U3 region of an FeLV LTR containing one, two or three copies of the 21-bp element. Reporter gene constructs were introduced by lipid-mediated transfection into feline embryonic fibroblasts (FEA) along with increasing amounts of a c-Myb expression vector. Fibroblasts were selected because the level of endogenous c-Myb expression in those cells is low or absent [14,15]. The results (Figure 4) demonstrated that the FeLV-945 LTR (3 × 21) responds to increasing levels of c-Myb expression to an extent statistically indistinguishable from the positive control, i.e., a reporter plasmid containing five tandem Myb-responsive elements (5X MRE). In contrast, an FeLV LTR containing only a single 21-bp element was unresponsive to c-Myb. The responsiveness of an LTR containing two 21-bp elements was also examined, since the 21-bp duplication would be predicted to encode one c-Myb binding site across the repeat junction. Interestingly, this LTR responded to increasing c-Myb expression to a low but statistically significant extent (p < 0.05 as compared to 1 × 21; Figure 4). These data show that the triplication-containing LTR is responsive to c-Myb in a dose-dependent manner and suggest that full responsiveness requires the presence of both c-Myb binding sites. To confirm the latter finding, a point mutation previously shown to ablate c-Myb binding [16] was introduced alternately into each of the sites (Figure 5A). Synthetic oligonucleotides containing the respective mutations were substituted into the LTR, and luciferase reporter gene constructs containing the mutant LTRs were introduced into FEA cells along with increasing concentrations of a c-Myb expression vector. LTRs in which either c-Myb binding site was ablated were observed to respond only weakly to increasing levels of c-Myb, and to significantly lower levels than the wild type LTR containing both binding sites (p < 0.05; Figure 5B).
Figure 4 Response to exogenous c-Myb expression of FeLV LTRs containing variable numbers of the 21-bp element. Recombinant FeLV LTRs were constructed that contained 1, 2 or 3 copies of the 21-bp element and were cloned into a firefly luciferase reporter plasmid. LTR reporter plasmids or a 5X MRE positive control plasmid (500 ng) were introduced by lipid-mediated transfection in triplicate into feline embryonic fibroblasts (FEA) together with the Renilla luciferase reporter plasmid pRL-SV40 (5 ng) and a c-Myb expression plasmid in increasing concentrations (0 – 500 ng). Cell lysates were harvested 24 hours later and luciferase activity was quantified. Data are reported as a ratio of firefly to Renilla luciferase activity. Shown are data from a representative experiment repeated three times independently.
Figure 5 Response to exogenous c-Myb expression of FeLV LTRs containing c-Myb binding site mutations. (A). Diagram of the 21-bp triplication as contained in the FeLV-945 LTR, indicating the sequence of c-Myb binding sites across the repeat junctions of the triplication (+/+). LTRs were constructed in which the first (-/+) or second (+/-) binding site was mutated. (B). Firefly luciferase reporter gene plasmids containing the FeLV LTR with wild type or mutant c-Myb binding sites (500 ng) were introduced by lipid-mediated transfection in triplicate into feline embryonic fibroblasts (FEA) together with the Renilla luciferase reporter plasmid pRL-SV40 (5 ng) and a c-Myb expression plasmid in increasing concentrations (0 – 500 ng). Cell lysates were harvested 24 hours later and luciferase activity was quantified. Data are reported as a ratio of firefly to Renilla luciferase activity. Shown are data from a representative experiment repeated three times independently.
Previous studies had shown that the 21-bp triplication contributes enhancer function to the LTR in a cell type-specific manner, and that it is significantly more active in K-562 cells as compared to a fibroblast line [5]. In hindsight, these results may be explained by the relatively high levels of c-Myb expression in K-562 cells and its relative absence in fibroblasts [14,15]. When the U3 region of the FeLV-945 LTR was placed downstream of a heterologous promoter, however, the cell type-specific preference for enhancer function was lost [5]. One explanation for these findings is that c-Myb bound to the 21-bp triplication may function through interactions with other proteins bound to the LTR, and that such interactions require the LTR binding sites to be present in their natural array. Indeed, c-Myb is known to function in a combinatorial manner with other transcription factors and co-activators to activate target gene expression [14]. Studies were performed in the present study to evaluate this possibility further. First, an oligonucleotide containing only the 21-bp triplication was cloned into a luciferase reporter plasmid upstream of a heterologous SV40 promoter. This construct, when introduced into FEA cells, was observed to be unresponsive to increasing levels of c-Myb expression (data not shown). Thus, the presentation of c-Myb binding sites through the 21-bp triplication is apparently insufficient to regulate transcription in the absence of the normally adjacent LTR enhancer and promoter. These findings are consistent with the possibility that c-Myb binding to the 21-bp triplication functions to activate transcription by interacting with proteins bound to adjacent sites on the LTR. c-Myb is known to interact directly with a number of different proteins, including the transcriptional co-activator CREB-binding protein (CBP) [14,15]. Indeed, CBP is thought to act as a bridge that physically connects c-Myb to the promoter-bound basal transcription machinery, thus stabilizing the transcription-preinitiation complex [14,15,17]. Experiments were therefore performed in the present study to examine the possibility that c-Myb bound to the 21-bp triplication interacts with CBP.
Supershift EMSA was used to evaluate whether c-Myb and CBP might be present in the specific complex that forms on the 21-bp triplication. Specific complex formation was observed using a radiolabeled probe representing the 21-bp triplication in the presence of nuclear extracts from either K-562 cells or feline 3201 T-cells. In both cases, mobility of the complex was reduced (supershifted) when reacted with antibody to c-Myb. When the same reaction was performed in the presence of an antibody to CBP, an identical supershift was observed (Figure 6A,6B). No complex formation was observed when the probe was reacted with nuclear extracts from FEA cells (Figure 6C), consistent with the lack of c-Myb expression in fibroblasts [14,15]. CBP is ubiquitously expressed [14]; therefore, this observation indicates that CBP does not participate in complex formation on the 21-bp triplication in the absence of c-Myb. When c-Myb was expressed exogenously in FEA cells, specific complex formation and supershift were observed in the presence of antibody to either c-Myb or CBP (Figure 6D). Finally, analysis of FeLV-945 replication indicated a regulatory role for c-Myb binding and recruitment of CBP to the 21-bp triplication. K-562 cells were infected with recombinant FeLV [8] containing the LTR of either FeLV-945 or FeLV-A/61E, the latter having only a single copy of the 21-bp element. A CBP expression vector was introduced into cells chronically infected with either virus, and virus production was measured three days later by quantifying reverse transcriptase activity in the culture supernatants. The results showed significantly increased levels of production of virus containing the FeLV-945 LTR. In contrast, virus containing the FeLV-A/61E LTR was unaffected (Figure 7). These findings indicate that the 21-bp triplication in the LTR renders the virus responsive to the amount of available CBP.
Figure 6 Supershift EMSA in the presence of antibody specific for c-Myb or CBP. (A – C). Nuclear extracts (5 μg) from K-562, 3201 or FEA cells were incubated with the radiolabeled GS945 probe (2.4 ng) representing the 21-bp triplication from the FeLV-945 LTR. Shown in each panel is specific complex formation in the presence of nuclear extract (closed circle), and with the addition of monoclonal antibody to c-Myb or CBP (4 μg). Reduced mobility of the complex (supershift) is indicated (asterisk). (D) shows the same reactions performed with nuclear extracts from FEA cells in which c-Myb was exogenously overexpressed.
Figure 7 Regulation of FeLV replication in response to exogenous overexpression of CBP. K-562 cells were chronically infected with recombinant FeLV containing the LTR of FeLV-945 or FeLV-A/61E. A CBP expression plasmid was then introduced by lipid-mediated transfection. Culture supernatants were collected 3 days later and reverse transcription activity was quantified as a measure of virus production. Results are reported as cpm/ml of 3H-TTP incorporated. The data shown were pooled from two independent experiments each performed in triplicate.
Discussion
The natural FeLV isolate, FeLV-945, was originally identified from lymphoid and other hematopoietic disorders in a geographic and temporal cohort. A unique 21-bp repeat motif in the FeLV-945 LTR was observed to be precisely conserved among animals in the cohort that exhibited malignant, proliferative or degenerative hematopoietic diseases of non-T-cell origin [[3,4], Chandhasin et al., manuscript submitted]. The 21-bp triplication was shown to enhance transcription from the FeLV LTR and to confer a replicative advantage to the virus, at least in part through the specific binding of unidentified nuclear proteins to the repeat motif [5,8]. In the present study, sequence analysis revealed two potential c-Myb binding sites formed across the repeat junctions of the 21-bp triplication (Figure 1). While the sequence of the potential binding sites (AAACTG) did not match the consensus c-Myb binding site precisely (YAACG/TG; Y = pyrimidine; [10,11]), the sequence was observed to be as closely related to the consensus binding site as are several sites in the HTLV-I LTR that are known to bind c-Myb [18,19]. Indeed, electrophoretic mobility shift assays indicated the specific binding of c-Myb to the 21-bp triplication by showing that a known high-affinity c-Myb binding site competed for DNA-protein complex formation but an unrelated site did not. It was noteworthy in these assays that significant competition for complex formation occurred only when the competitor was present at relatively high amounts (≥ 100-fold molar excess; Figure 2). By comparison, c-Myb binding to a consensus sequence in the bcl-2 promoter was shown to be effectively competed by 50-fold molar excess of a cold oligonucleotide carrying a high affinity c-Myb binding site [20]. A possible explanation for this difference may be that, while c-Myb can recognize a single consensus binding site such as that found in the competitor oligonucleotide we used, the natural recognition sites are generally found in multiple, closely aligned copies as in the 21-bp triplication. Thus, the affinity of binding to the triplication may be higher than to the competitor. It is further known that sequences flanking the consensus binding site may also be important in determining c-Myb binding affinity [21]. Electrophoretic mobility shift assays performed in the presence of an antibody to c-Myb confirmed the presence of c-Myb in the specific DNA-protein complex (Figure 3A,3B), and confirmed that repeat of the 21-bp element was required for complex formation (Figure 3C).
The c-Myb transcription factor is a critical regulator of gene expression, proliferation and differentiation in early hematopoietic progenitors [14,15,22] and has been exploited as a transcriptional regulator by many viruses that infect bone marrow cells [19,23-25]]. Considering that FeLV is known to replicate in the bone marrow [26,27], and that FeLV-945 infection was associated with various diseases of hematopoietic origin [Chandhasin et al., manuscript submitted], it is likely that the tropism of FeLV-945 in vivo included the hematopoietic progenitors in which c-Myb is expressed. Considering this possibility, we hypothesized that c-Myb may act as a transcriptional regulator of FeLV-945. In support of this hypothesis, reporter gene assays showed that an LTR containing the triplication was responsive to c-Myb in a dose-dependent manner (Figure 4), and that optimal responsiveness required the presence of both c-Myb binding sites (Figure 5). The identification of c-Myb binding sites that spanned the repeat junctions of the 21-bp triplication was particularly noteworthy because such sites would not occur in the absence of the repeat. Thus, a requirement for c-Myb binding to the repeat junctions of the triplication would exert a selective pressure to conserve its sequence precisely. Results indicated further that when c-Myb binds to the 21-bp triplication, it interacts with the transcriptional co-activator CBP, a critical regulator of normal hematopoiesis [17]. Identical electrophoretic mobility supershifts were observed when protein-DNA complexes were formed in the presence of antibody either to c-Myb or CBP, consistent with the hypothesis that both proteins are present in the same complex (Figure 6A,6B). The data further indicated that c-Myb recruits CBP to the 21-bp triplication, since no CBP-containing complex formation could be demonstrated unless c-Myb was also expressed (Figure 6C,6D). Finally, virus production was shown to be positively regulated by CBP in a manner dependent on the presence of the 21-bp triplication (Figure 7). These results indicated that the interaction between c-Myb and CBP is functional, and suggest that the c-Myb-mediated recruitment of CBP to the FeLV-945 LTR could be responsible for the previously reported replicative advantage conferred by the 21-bp triplication [8].
CBP and c-Myb are thought to activate target genes in hematopoietic progenitors through various mechanisms of interaction. One of those mechanisms involves a bridging function in which CBP links c-Myb with components of the basal transcription machinery, thereby establishing and/or stabilizing the transcription complex [14,15,17]. While the mechanism of interaction was not investigated in the present study, the bridging function is an intriguing possibility because it might explain the observed requirement of the 21-bp triplication for an intact LTR enhancer and promoter. Specifically, when the isolated 21-bp triplication was positioned upstream of a heterologous promoter, it did not confer responsiveness to exogenously supplied c-Myb (data not shown). Previous studies had similarly shown that the 21-bp triplication could not exert its influence when placed downstream of a heterologous promoter [5]. These observations indicated that transcriptional activation of the FeLV-945 LTR through c-Myb/CBP interaction requires that the LTR binding sites be present in their natural array. The possibility that CBP exerts its influence on the FeLV-945 LTR through a bridging function is significant because it implies that CBP acts stoichiometrically. CBP is known to be present in bone marrow cells in limiting amounts, playing a major role in hematopoiesis through competitive utilization on target promoters [17,28-31]]. Considering the competitive utilization of limiting amounts of CBP in hematopoiesis, its stoichiometric recruitment to the FeLV-945 LTR might interfere with CBP availability and thereby alter the regulation of CBP-responsive genes. Such alteration might then contribute to altered hematopoiesis and consequent hematologic disease.
Conclusions
FeLV-945 contains a unique 21-bp triplication in the LTR, conserved among animals in a geographic cohort with multicentric lymphoma, myeloproiferative disease or anemia. Binding sites for the c-Myb transcription factor were identified across the repeat junctions of the 21-bp triplication. Optimal responsiveness of the FeLV-945 LTR to c-Myb was shown to require the presence of both c-Myb binding sites. Since the binding sites would not occur in the absence of the repeat, a requirement for c-Myb binding would be predicted to exert a selective pressure for conserving the 21-bp triplication precisely. c-Myb binding to the 21-bp triplication was shown to recruit CBP, a transcriptional co-activator essential for hematopoiesis and known to be present in limiting amounts. Interaction of c-Myb and CBP with the 21-bp triplication was shown to positively regulate virus production, and thus may be responsible for the replicative advantage conferred by the repeat sequence. Considering that CBP is present in hematopoietic cells in limiting amounts, we hypothesize that FeLV-945 replication in bone marrow may influence CBP availability and thereby alter the regulation of CBP-responsive genes, thus contributing to altered hematopoiesis and consequent hematologic disease.
Methods
Cell lines and viruses
K-562, a malignant multipotential human hematopoietic cell line, was obtained from the American Type Culture Collection (CCL-243) and was maintained in RPMI 1640 medium with 10% FBS. The FEA cell line, a continuous line of feline embryonic fibroblasts, was obtained from Dr. Jennifer Rojko and was grown in Eagle minimal essential culture medium supplemented with 10% fetal bovine serum (FBS), 0.1 mM non essential amino acids and 50 μg/ml gentamicin reagent solution (Invitrogen, Carlsbad, CA,). 3201 is an FeLV-negative thymic lymphoma cell line of feline origin [32] and was maintained in 50% Leibovitz L-15 medium/50% RPMI 1640 supplemented with 15% FBS. Infectious recombinant FeLVs GA-945L and GA-61EL were constructed from an infectious molecular clone of FeLV-B/Gardner-Arnstein into which was substituted the LTR of FeLV-945 or of FeLV-A/61E, respectively, between EcoRV and Hinc II restriction enzyme sites [5,8]. The FeLV-A/61E LTR was selected because it represents a naturally occurring isolate of FeLV typical of those horizontally transmitted among cats in nature, and it contains only a single copy of the 21-bp element [33].
Electrophoretic mobility shift assays
A double-stranded oligonucleotide probe containing the 21-bp triplication and 40 bp of flanking sequence from the FeLV-945 LTR was radiolabeled using the synthetic oligonucleotide GS945 as template (5'- GCTGAAACAGCAGAAGTTTCAAGGCCACTGCCAGCAGTTTCAAGGCCACTGCCAGCAGTTTCAAGGCCACTGCCAGCAGTCTCCAGGCTCCCCAGTTGAC -3'), the filling primer (5'-CTGGTCAACTGGGGAGCCT-3') and the Klenow fragment of DNA polymerase (Invitrogen, Carlsbad, CA) to complete the duplex. A homologous probe containing only a single copy of the 21-bp element was similarly synthesized using the oligonucleotide GS61E as template (5'-GCTGAAACAGCAGAAGTTTCAAGGCCACTGCCAGCAGTCTCCAGG CTCCCCAGTTGAC-3'). Nuclear extract from K-562 cells was obtained from Active Motif (Carlsbad, CA). Nuclear extracts from FEA and 3201 cells were prepared using the Nuclear Extract Kit from Active Motif (Carlsbad, CA) according to manufacturer specifications. Nuclear extracts were also prepared from FEA cells following the lipid-mediated transfection (Lipofectamine Plus reagent; Invitrogen, Carlsbad, CA) of FL-Myb, a c-Myb expression vector in which full length murine c-Myb cDNA was inserted into the multiple cloning site of pcDNA3.1 (a gift of Dr. Linda Wolff, National Cancer Institute). DNA-protein binding reactions included 5 μg of nuclear extract and 2.4 ng of radiolabeled probe in a 20 μl reaction containing 1 mM Tris pH 7.5, 7.5 mM NaCl, 1 mM EDTA, 0.7% glycerol, 0.1 mM DTT and 2 μg poly(dI-dC). Reactions containing nuclear extracts from K-562 cells were incubated at 4°C for 30 minutes. Reactions containing nuclear extracts from 3201 or FEA cells were incubated at 30°C for 30 minutes. In some reactions, unlabeled probe was added to the reaction as a specific competitor, or HindIII/HaeIII-digested bacteriophage lambda DNA was included as non-specific competitor. Some reactions included as competitor a double-stranded oligonucleotide containing a known high-affinity c-Myb consensus binding site (5'-TACAGGCATAACGGTTCCGTAGTGA) or a CREB consensus binding site (5'-AGAGATTGCCTGACGTCAGAGAGCTAG). Protein-DNA complexes were resolved by 6% polyacrylamide gel electrophoresis in 0.25X TBE buffer (1X TBE buffer is 89 mM Tris base, 89 mM Boric acid and 2 mM EDTA). Gels were then dried at 80°C and exposed to radiographic film for varying periods of time. In some reactions, monoclonal antibody (4 μg) to either c-Myb or CBP, or isotype control antibody, was added after the 30-minute incubation period and incubated overnight at 4°C. Complexes were then resolved by 6% polyacrylamide gel electrophoresis as described above. The mouse monoclonal IgG1 antibody to c-Myb was raised against a recombinant protein corresponding to amino acids 500–640 of the human protein (Santa Cruz Biotechnology, Santa Cruz, CA). The mouse monoclonal IgG1 antibody to CBP was raised against a peptide corresponding to amino acids 2422–2441 of CBP of human origin (Santa Cruz Biotechnology, Santa Cruz, CA).
Reporter gene constructs and luciferase expression assays
Luciferase reporter plasmids were constructed to contain the U3 region of an FeLV LTR containing one, two or three copies of the 21-bp element. The U3 region of the FeLV-A/61E LTR, containing one copy of the 21-bp element, was cloned into the firefly luciferase reporter plasmid pGL2-Basic (Promega Corp., Madison, WI). The LTR was then substituted between PstI and HincII restriction sites with homologous sequences from a naturally occurring LTR containing two 21-bp elements [Chandhasin et al., manuscript submitted] or from FeLV-945, which contains three 21-bp elements. Luciferase reporter plasmids were also constructed in which point mutations were introduced into either the first or second c-Myb binding site in the 21-bp triplication of the FeLV-945 LTR. Binding site mutants were constructed by designing synthetic oligonucleotides -/+ (5'-GCTGAAACAGCAGAAGTTTCAAGGCCACTGCCAGCAGATTCAAGGCCACTGCCAGCAGTTTCAAGGCCACTGCCAGCAGTCTCCAGGCTCCCCAGTTGAC-3') and +/- (5'-GCTGAAACAGCAGAAGTTTCAAGGCCACTGCCAGCAGTTTCAAGGCCACTGCCAGCAGATTCAAGGCCACTGCCAGCAGTCTCCAGGCTCCCCAGTTGAC-3') that contained a point mutation in the first or second binding site, respectively (mutated base indicated by boldface and underline). The indicated point mutation had previously been shown to ablate c-Myb binding [16]. A double-stranded form of each sequence was generated using the filling primer (5'-GAACTCTGGTCAACTGGGGAGCCTGGAGACTGCTG-3') and the Klenow fragment of DNA polymerase. The resulting double stranded oligonucleotides were digested with AluI/HincII and substituted into the LTR of FeLV-A/61E. The KpnI/PstI fragment of the resulting recombinant LTR was then excised and cloned into the pGL2-Basic luciferase reporter plasmid. Finally, a luciferase reporter plasmid was developed that contained the isolated 21-bp triplication cloned upstream of the SV40 promoter in pGL2-Promoter (Promega Corp., Madison, WI). A double-stranded DNA fragment containing the 21-bp triplication was generated by PCR amplification using the oligonucleotide GS945 (described above) as template and primers fw945-kpn1 (5'- GCTCGGTACCAGCTGAAACAGCAGAAGTTTC) and rv945-sac1 (5'- ATGCTGAGCTCAACTGGGGAGCCTGGAGACT). The resulting amplification product was digested with KpnI/SstI and inserted into the multiple cloning site upstream of the SV40 promoter in the reporter plasmid.
For reporter gene assays, 2 × 105 cells were seeded in triplicate into 6-well tissue culture plates. The next day, reporter plasmids (500 ng) were introduced into cultured cells by lipid-mediated transfection (Lipofectamine Plus; Invitrogen, Carlsbad, CA) in the presence of pRL-TK (5 ng) in a 100:1 ratio. pRL-TK encodes Renilla luciferase and was used as an internal control for transfection efficiency. Firefly and Renilla luciferase activities were quantified 24 hours later using the Dual-Luciferase Reporter Assay System (Promega Corp., Madison, WI). Data from triplicate wells were analyzed statistically using one-way ANOVA and Bonferroni post test. Statistical significance was considered as p < 0.05. In some assays, the c-Myb expression vector FL-Myb (described above) was added to the transfection in increasing amounts (50 ng – 500 ng). The 5XMRE plasmid was used in reporter gene assays as a positive control. This plasmid contains five tandem c-Myb binding sites cloned upstream of a luciferase gene (a gift of Dr. Linda Wolff, National Cancer Institute).
Virus Replication Assay
5 × 105 K-562 cells, uninfected or chronically infected with recombinant FeLVs GA-945L and GA-61EL (described above) were seeded in triplicate into 24-well tissue culture plates. A full-length CBP expression vector (4 μg; a gift from Dr. Matthew Burow, Tulane University Medical School) was introduced into the cells by lipid mediated transfection using Lipofectamine 2000 reagent (Invitrogen, Carlsbad, CA). Culture supernatants were collected three days later and reverse transcriptase activity was quantified as previously described [8]. Data from triplicate wells were analyzed statistically using one-way ANOVA and Bonferroni post test. Statistical significance was considered as p < 0.05.
Competing interests
None declared.
Authors' contributions
SLF developed reporter gene constructs and performed binding assays, gene expression and virus replication assays. SP identified and initially demonstrated c-Myb binding sites. KRR developed the reporter gene assays. LSL directed the experimental design, implementation and interpretation of data. All authors read and approved the final manuscript.
Acknowledgements
This work was supported by PHS grant CA83823 and by Development Funds of the Tulane Cancer Center. SLF was supported in part by a grant from the Cancer Association of Greater New Orleans. The authors gratefully acknowledge Drs. Matthew Burow and Linda Wolff for helpful discussions and for the gift of reagents. Patricia Lobelle-Rich is gratefully acknowledged for valuable technical assistance.
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Tanikawa J Yasukawa T Enari M Ogata K Nishimura Y Ishii S Sarai A Recognition of specific DNA sequences by the c-myb protooncogene product: role of three repeat units in the DNA-binding domain Proc Natl Acad Sci U S A 1993 90 9320 9324 8415700
Rosson D O'Brien T Constitutive c-myb expression in K-562 cells inhibits induced erythroid differentiation but not tetradecanoyl phorbol acetate-induced megakaryoctyic differentiation Mol Cell Biol 1995 15 772 779 7823945
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Oh IH Reddy EP The myb gene family in cell growth, differentiation and apoptosis Oncogene 1999 18 3017 3033 10378697 10.1038/sj.onc.1202839
Guehmann S Vorbrueggen G Kalkbrenner F Moelling K Reduction of a conserved Cys is essential for Myb DNA-binding Nucleic Acids Res 1992 20 2279 2286 1594446
Blobel GA CBP and p300: versatile coregulators with important roles in hematopoietic gene expression J Leukoc Biol 2002 71 545 556 11927640
Bosselut R Lim F Romond P Frampton J Brady J Ghysdael J Myb protein binds to multiple sites in the human T cell lymphotropic virus type I long terminal repeat and transactivates LTR-mediated expression Virology 1992 186 764 769 1733110 10.1016/0042-6822(92)90044-P
Dasgupta P Reddy CD Saikumar P Reddy EP The cellular proto-oncogene product Myb acts as transcriptional activator of the long terminal repeat of human T-lymphotropic virus type I J Virol 1992 66 270 276 1727489
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J Exp Clin Assist ReprodJournal of Experimental & Clinical Assisted Reproduction1743-1050BioMed Central London 1743-1050-1-11550715310.1186/1743-1050-1-1EditorialJournal of Experimental & Clinical Assisted Reproduction: shaping the future of research and practice in reproductive endocrinology/infertility Sills E Scott 123dr.sills@ivf.comWinston Robert M 45r.winston@imperial.ac.ukPalermo Gianpiero D 67gdpalerm@med.cornell.edu1 Editor-in-Chief, Journal of Experimental and Clinical Assisted Reproduction2 Division Director, Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Atlanta Medical Center, Atlanta, Georgia USA3 Director for Oocyte Donation, Georgia Reproductive Specialists LLC, Atlanta, Georgia USA4 Senior member, Editorial Board, Journal of Experimental and Clinical Assisted Reproduction5 Professor of Fertility Studies, Imperial College, London, United Kingdom6 Editor-in-Chief, Journal of Experimental and Clinical Assisted Reproduction7 Director of Assisted Fertilization, Cornell Institute of Reproductive Medicine and Infertility and Associate Professor, Weill Medical College of Cornell University, New York, New York USA2004 2 9 2004 1 1 1 17 7 2004 2 9 2004 Copyright © 2004 Sills et al; licensee BioMed Central Ltd.2004Sills 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.
Journal of Experimental & Clinical Assisted Reproduction is an open access, online, peer-review journal publishing papers on all aspects of research into reproductive endocrinology, infertility, bioethics and the advanced reproductive technologies. The journal reports on important developments impacting the field of human reproductive medicine and surgery. The field exists as a sub-specialty of obstetrics & gynecology, focusing on the diagnosis and treatment of complex human reproductive problems. The continued growth of this relatively new field depends on quality research by proven scientists as well as junior investigators who, together, make contributions to this area of medical and surgical practice. The publishing revolution made possible by internet technology presages a bright future for continued interdisciplinary collaboration among researchers. Against this background, Journal of Experimental & Clinical Assisted Reproduction exists for the scientific community to facilitate this scholarly dialogue.
publishingreproductive medicineinternetresearchtrends
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Introduction
In early 2002, planning for Journal of Experimental & Clinical Assisted Reproduction began in Atlanta after discussions with London-based publisher BioMed Central to develop a new electronic peer-reviewed journal reporting on the rapidly growing field of reproductive endocrinology and infertility. Working with colleagues who shared this vision, an exploratory organizational group was established to design a journal that would not only meet the current demands of the specialty, but also anticipate its challenges and needs for the future.
By the time of its formal launch in July 2004, Journal of Experimental & Clinical Assisted Reproduction already had received submissions and inquiries from authors seeking to publish manuscripts in the categories of original research, review, case report, opinion/debate, medical history, and letters. Although column space does not constrain electronic publishing in the same way as traditional print journals, our peer-review process determined that not every submission was appropriate for publication. Hence, from the first instance the journal has pledged to observe a peer-review policy that ensures only the best quality manuscripts are published.
Our editorial board membership reflects a depth of expertise required to guide editorial policies of a journal that aspires to join the top tier of selective scientific journals. Journal of Experimental and Clinical Assisted Reproduction is fully committed to the philosophy of Open Access as articulated in the following policies:
Free, full-text access for all articles
While the availability of published articles on the journal's homepage provides high and unrestricted visibility for accepted articles, contents of Journal of Experimental & Clinical Assisted Reproduction (ISSN 1743-1050) are also accessioned in PubMed Central, maintained by the U.S. National Library of Medicine – the world's largest medical library. Accordingly, all journal publications are available free and without password requirements to anyone with internet access. Furthermore, the platform provided by our publisher, BioMed Central (NLMID b101153627), allows author(s) to track how frequently their manuscript has been accessed and viewed by the public at no charge.
Journal scope and article categories
The journal reports on important developments impacting the field of human reproductive medicine and surgery. We accept manuscripts describing research in reproductive endocrinology, infertility, bioethics and the advanced reproductive technologies. At the discretion of the Editors, conference proceedings may be considered for publication by special arrangement.
Rapid publication
After a manuscript is received via the journal's on-line electronic submission system, selection of referees and editorial review is underway within a few business days. Our peer review process evaluates the appropriateness and suitability of all submitted manuscripts, as well as supplying authors with any additional requirements or modifications needed before the article can be published. We seek to reach an editorial decision on a manuscript within three weeks of its initial receipt, although author delays in addressing referees' comments are likely to extend this timeline. Questions regarding the suitability of a proposed submission may be sent to the journal office at , although this is not a requirement
Formal peer-review policy
The abstract of each manuscript is reviewed by two internal referees, which may include members of the Editorial Board. Authors can expect a response regarding this preliminary review within one week, and manuscripts judged outside the scope of the journal are identified accordingly. Submissions considered to be appropriate for the journal are reviewed by at least one independent referee. Referees' comments are relayed to corresponding authors in a confidential/anonymous manner, and all communication regarding submissions is through the journal's editorial office. The Editorial Office will review commentaries, together with input from an Editorial Board member with the relevant expertise. It may be necessary to enlist additional reviewers and/or statisticians in certain cases to assure the highest quality manuscripts are chosen for publication.
Monetary author costs
For the first six months, no author charges will apply to any work accepted for publication in Journal of Experimental & Clinical Assisted Reproduction. However, for each manuscript accepted thereafter, our publisher will charge a modest fee comparable to the cost of a single color page charge in a print journal (see ). This fee may be waived in hardship cases or for selected authors without budget support, provided that such a waiver request is made at the time of manuscript submission. These policies assure no publishing bias will exist against residents, fellows, or other investigators with little or no research funding.
Copyright retained by authors
We do not require authors to assign their copyright claim to the publisher as a condition of publishing any article. This means that our authors keep the copyright to their article with the freedom to include article components in subsequent published work, to submit the article in full to colleagues, or to include the work in their own homepage(s) without the publisher's prior authorization or permission.
Conclusion
With the beginning of a new century of medical research, library privileges and institutional journal holdings will continue to be eclipsed by electronic publishing and unrestricted access to the internet. The publishing revolution made possible by such technology presages a bright future for continued interdisciplinary collaboration among researchers. Against this background, Journal of Experimental & Clinical Assisted Reproduction exists for the scientific community to facilitate this scholarly dialogue.
Author contributions
ESS, RMW, and GDP drafted and reviewed the manuscript.
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Epidemiol Perspect InnovEpidemiologic perspectives & innovations : EP+I1742-5573BioMed Central London 1742-5573-1-11550715510.1186/1742-5573-1-1EditorialLead editorial: The need for greater perspective and innovation in epidemiology Phillips Carl V 12carl.v.phillips@cphps.orgGoodman Karen J 1kgoodman@sph.uth.tmc.eduPoole Charles 3cpoole@unc.eduthe editors of Epidemiologic Perspectives & Innovations 1 University of Texas Health Science Center Houston 1200 Herman Pressler Dr., Houston, Texas 77030 USA2 Center for Philosophy, Health, and Policy Sciences, Inc., Houston, USA3 Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA2004 3 9 2004 1 1 1 13 8 2004 3 9 2004 Copyright © 2004 Phillips et al; licensee BioMed Central Ltd.2004Phillips 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.
This editorial introduces the new online, open-access, peer-reviewed journal, Epidemiologic Perspectives & Innovations. Epidemiology (which we define broadly, to include clinical research and various approaches to studying the health of populations) is a critically important field in informing decisions about the health of individuals and populations. But the desire for new information means that the health science literature is overwhelmingly devoted to reporting new findings, leaving little opportunity to improve the quality of the science. By creating a journal dedicated to all topics of and about epidemiology, except standard research reports, we hope to encourage authors to write more on the neglected aspects of the field. The journal will publish articles that analyze policy implications of health research, present new research methods and better communicate existing methods, reassess previous results and dogma, and provide other innovations in and perspectives on the field. Online publishing will permit articles of whatever length is required for the work, speed the time to publication and allow free access to the full content.
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Epidemiology is a critically important field in informing decisions about the health of individuals and populations. It is also a young field, with the potential for seeing fundamental improvements in the conduct of the science every year. But the desire for new information means that the health science literature is overwhelmingly devoted to reporting new findings, leaving little opportunity to improve the quality of the science. Epidemiologic Perspectives & Innovations (EP&I) was created to provide a forum for efforts to improve the quality of health science research and its applications.
Successful enterprises know they must devote a substantial portion of their resources – at least a few percent and often ten percent or more – to assessing whether the rest of their resources are being optimally directed. Such efforts include research and development, which improves the quality of products, and outcomes research, which assesses the impact of those products. In an applied science like epidemiology, these efforts should be devoted to designing new methods for conducting studies and interpreting results, translation of research into effective policy recommendations, critical review of past findings and current practice, and improvement of teaching the next generation of scientists.
Given the resources expended by the health science research enterprise, epidemiology (which we define broadly, including both population health and clinical research, and covering biological, behavioral, and economic dimensions) is characterized by remarkably little innovation, let alone critical review of existing dogma. A well-educated epidemiologist transported forward in time from 1980 would probably be able to read (and participate in) most current research and would find few surprises other than a few specific study results. Yet a substantial portion of all the epidemiology ever conducted has been carried out since 1980 – probably more than half, even including in the count all medical literature back to the dawn of literacy. The outputs of the science have increased to a torrent; research to improve the quality of the science is a trickle.
It can hardly be argued that this slow innovation and lack of perspective is because current approaches offer little room for improvement. Current discussions of advanced statistical methods, the nature of random error, sensitivity analysis and uncertainty quantification, and proper interpretation of results, to name just a few, show that most current epidemiologic research uses methodology in need of improvement. Granting that many problems would be eliminated if health researchers – who often have minimal training in epidemiology – just followed the dictates of a good basic epidemiology textbook, there are still major problems that lack simple solutions. It is troubling that we plow ahead with billions of dollars worth of research every year while making minimal effort to answer fundamental questions about what that research is really telling us. Epidemiology is far too important to our society to be treated as an exercise in uncritically following existing formulae.
The limitations of the field become even more apparent after the research is conducted. Results are cast out into the world as if they speak for themselves, forcing policy makers, clinicians, and interested lay people to interpret them, despite their lack of expertise in the topic area and analytic methods, and lack of necessary context.
A missing marketplace for ideas
These problems leave plenty of blame to go around, but a fair amount of it rests with the lack of opportunity to publish scholarly analytic work aimed at solving the problems. While some health researchers might be guilty of not giving the field's limitations a second thought, most probably can envision contributions they would like to make to improve it. Every conclusions section containing a single paragraph of policy discussion suggests that researchers would like to contribute to policy analysis, but have exhausted their paltry word limit. Every dissertation that reflects upon and challenges standard methods shows fresh analytic thinking, but the innovations might be read by just the half dozen people who view the actual dissertation, since the resulting publications will likely be limited to a brief recounting of the methods and results (narrowly defined). Every time a professor explains to her students that something they learned in a previous class or from reading the literature is wrong, there is a lesson that should be getting out to everyone in the field, not just the ten students in that room.
These scenarios call for full-length, analytically complete presentations (see endnote 1). Such analysis cannot be grafted onto a paper primarily focused on presenting numerical results from a study, given the severe length limitations in print journals in the health sciences. Indeed, such analyses must usually be longer than typical word limits allow, even without the study results or applications that are needed to illustrate them or provide background. A researcher who writes such a paper has a very difficult time getting it published. Moreover, it is easy to anticipate that difficulty and never even try to write the paper. The founding editors of this journal were inspired by their own experiences with these difficulties.
There are journals that cover some of these areas, but to a remarkably limited extent. "Health policy" (and more so, "health economics") journals focus on the financial side of health care, rather than more general health policy or economic issues. Statistics journals, and even the research methodology slots available in the health research journals, favor mathematically complicated advances over more practical advice. With the exception of occasional relevant entries in medical journal education series, articles devoted to improving the teaching or understanding of epidemiologic research have no clear venue. Even with some niches for certain methods, policy, overview, or perspectives articles, it is difficult to be enthusiastic about writing in these areas with no clear idea of where the results are likely to be published.
Epidemiologic Perspectives & Innovations (EP&I) was created to provide this forum, taking advantage of the greater visibility and article length offered by open-access online publishing.
Article topics
The following are areas of inquiry EP&I will publish. (An accompanying editorial [1] presents a more specific "wish list" of some of the particular analyses the editors would like to see.)
Policy: Policy recommendations do not flow simply and directly from health research results, and educated recommendations demand more than a few sentences of analysis at the end of a research report. A good policy recommendation requires high-quality analysis of a nature and quantity that does not fit in standard health research journals. At the same time, health researchers cannot leave policy analysis of their results for other people to do and publish in policy journals because there are very few such people or journals. If health researchers do not take the lead on policy analyses based on their research, the analyses will likely never be done. EP&I fills the gap by providing a forum for policy analysis in the context of health research. Policy analysis articles can be free-standing or specifically based on research reports published elsewhere. Submissions in this area should be analytic (addressing policy/decision analysis, economics, ethics, or other areas of analytic inquiry), rather than commentary.
Methodologic Innovation and Communication: EP&I welcomes submissions in all areas of epidemiologic research methodology, from study design to data analysis and reporting, including new tools, simple but important observations, and widely understandable applications of existing tools. The strength of our editorial board in this area means that submissions will be reviewed by experts who understand and appreciate new methods. Unlike most other journals publishing methods articles, EP&I welcomes submissions that are not necessarily at the technological cutting edge (though such submissions are also encouraged), but that contain lessons that are not widely known. We will spare authors the all-too-common experience of being told "everyone already knows that" when they submit a paper that calls for the use of methods or practices that are widely overlooked. Research articles are needed to translate methodological findings that are "known" (in the sense of having been discovered and understood by methods specialists), to make them known (in the sense of being understood and usable by most researchers in the field).
Ethics, Philosophy, and Critical Analysis of the Field: In most of the health research literature, any discussion of philosophical points or assessments of the quality of research is labeled "commentary" and restricted to the opinions of a few luminaries. But carefully reasoned ethical analysis, epistemology, analysis of quality, and the like are not mere commentary, and often come from junior researchers or outsiders. Our accompanying "wish list" editorial provides some examples of these types of analysis.
Re-analyses: The deluge of research results in health science means that few study results are ever carefully re-analyzed, even when their implications are quite important. When such re-analyses do occur, they are often limited to letters or perfunctory assessments in systematic reviews. EP&I offers a forum for publishing full-length re-analyses (which might use different analytic approaches, start with different premises, or report different results) of important previous research.
Teaching Methods and Innovations: Many fields have a dedicated teaching section in one or more journals. EP&I will include articles that provide teaching tools, innovations, and methods. Online publishing allows authors to include computer code, spreadsheets, datasets, and other tools that will allow readers to make use of the teaching tools. Teaching articles will be peer reviewed by experienced teachers and at least one current student at the appropriate level to judge the material. The ideal teaching articles will present an approach or method, the specific tools necessary for a reader to implement it, and a report of the authors' experience in using the material. Review will be based primarily on the apparent usefulness of the presented approach.
Multidisciplinary Research: This category is somewhat redundant, given that many of the aforementioned article types necessarily draw upon knowledge from multiple disciplines. But it is worth mentioning specifically because it is often difficult to publish work that is based in multiple fields of inquiry and thus does not fit easily into any one of them, or that is squarely in another discipline but is intended for an audience of health scientists. EP&I encourages such submissions and will review them based on their analytic merits in the fields in which they are based and their potential usefulness to health researchers.
More generally, EP&I is a home for all articles of and about epidemiology, with the exception of standard research reports. (Reporting research results as part of one of the above article types is, of course, welcome.) This includes many types of papers that are not themselves epidemiologic analysis, but inform epidemiology or are about epidemiology. We suspect that many papers of the above types exist on paper or in researchers' heads, but have previously been difficult to get published. Many more will be written when they are appreciated as analytic work that is central to the field.
Flexible format
To provide maximum flexibility for these kinds of articles, we worked with BioMed Central to create the "Analytic Perspectives" article type. We expect most submissions to EP&I to be this article type, which allows authors to create a structure that fits their analysis (as opposed to methods-results-discussion, which generally would not fit) and is labeled to emphasize that the article is analytic (as opposed to commentary).
We are also taking the unusual (for a health science journal) step of encouraging the use of endnotes. We believe that the lack of substantive endnotes or footnotes – to provide important asides, definitions, or clarifications, to note exceptions to general rules, or provide other elaboration – is a major detriment to the content of health research papers, making it difficult to present certain analytic points. For example, an interesting statistical claim or policy observation that is almost always true can either be made without further elaboration (in which case the exceptions make the claim incorrect), can include a paragraph of caveats (which is awkward and distracting), or left out (see endnote 2). Often the latter is the author's choice, which impoverishes the literature. An endnote could solve the problem. In other cases, endnotes could include short derivations of calculations that will be obvious to some readers and uninteresting to others, but may be of interest to some. Anyone familiar with the social science literature or many other fields will understand the beneficial uses to which such notes can be put (see endnote 3). Authors should consult the instructions for submissions for mechanical details of endnote use.
Target audience and authors
We hope that many readers will read EP&I from virtual cover to virtual cover. Most readers of most health science journals scan the table of contents and read the one or two articles that report results in their subspecialty, or never even see a table of contents, but merely a list of search hits on PubMed. Most articles in EP&I should be of some interest to researchers who are serious about understanding analytic health research and its implications.
We welcome submissions from researchers with all levels of experience in the field, and from experts in other fields writing for health researchers. Great innovations and critical analysis often come from senior scholars in a field, but they also often come from graduate students, outsiders, and others who are not heavily invested in the status quo of a field of inquiry.
Conclusions
In 1995, Science published the controversial article, "Epidemiology Faces its Limits" [2], which suggested that the field had already gathered all the low-hanging fruit and was not able to do much more. The premise implied by the title was dead wrong and still is: epidemiologic research (whether defined broadly or more narrowly) is no where near the limits of its technology or potential contribution to our knowledge. But nearly a decade later, the criticisms that rang true when that article was published still ring true; the progress toward "breakthroughs in the methodological tools of epidemiology" called for in that article has been limited. EP&I hopes to encourage the pursuit of breakthroughs (or, better still, a slow and steady flow of new innovations and perspectives) by providing a ready home for publishing a broad collection of such material.
Endnotes
1. "Analytic" should not be confused with quantitative calculations and results, which seldom contain much actual analysis. Analysis can be thought of as the intellectual process of systematic inquiry aimed at understanding, explaining, or characterizing phenomena or concepts.
2. For example, authors might want to point out that nondifferential misclassification error that they suspect exists most likely biased a result toward the null. However, an unqualified statement to this effect will likely generate criticism that such error is not always toward the null and that believing so is a sure sign of methodological naivete. An endnote in which the authors point out that there are exceptions, but the bias is still usually toward the null, would allow them to make their point without a long awkward caveat breaking up the main text.
3. The literature in most of these fields uses footnotes, conveniently located at the bottom of the page. Online publishing leaves us without a bottom of the page, but allows for convenient opening of multiple windows, offering the opportunity to have the endnotes open in a separate browser window. Readers of printed PDF versions will, alas, have to flip to the end.
==== Refs
Maldonado G Phillips CV Lead editorial: Wishful thinking Epidemiologic Perspectives & Innovations 2004 1 2 15507156 10.1186/1742-5573-1-2
Taubes G Epidemiology faces its limits Science 1995 269 164 9 7618077
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Epidemiol Perspect InnovEpidemiologic perspectives & innovations : EP+I1742-5573BioMed Central London 1742-5573-1-11550715510.1186/1742-5573-1-1EditorialLead editorial: The need for greater perspective and innovation in epidemiology Phillips Carl V 12carl.v.phillips@cphps.orgGoodman Karen J 1kgoodman@sph.uth.tmc.eduPoole Charles 3cpoole@unc.eduthe editors of Epidemiologic Perspectives & Innovations 1 University of Texas Health Science Center Houston 1200 Herman Pressler Dr., Houston, Texas 77030 USA2 Center for Philosophy, Health, and Policy Sciences, Inc., Houston, USA3 Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, USA2004 3 9 2004 1 1 1 13 8 2004 3 9 2004 Copyright © 2004 Phillips et al; licensee BioMed Central Ltd.2004Phillips 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.
This editorial introduces the new online, open-access, peer-reviewed journal, Epidemiologic Perspectives & Innovations. Epidemiology (which we define broadly, to include clinical research and various approaches to studying the health of populations) is a critically important field in informing decisions about the health of individuals and populations. But the desire for new information means that the health science literature is overwhelmingly devoted to reporting new findings, leaving little opportunity to improve the quality of the science. By creating a journal dedicated to all topics of and about epidemiology, except standard research reports, we hope to encourage authors to write more on the neglected aspects of the field. The journal will publish articles that analyze policy implications of health research, present new research methods and better communicate existing methods, reassess previous results and dogma, and provide other innovations in and perspectives on the field. Online publishing will permit articles of whatever length is required for the work, speed the time to publication and allow free access to the full content.
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Epidemiology is a critically important field in informing decisions about the health of individuals and populations. It is also a young field, with the potential for seeing fundamental improvements in the conduct of the science every year. But the desire for new information means that the health science literature is overwhelmingly devoted to reporting new findings, leaving little opportunity to improve the quality of the science. Epidemiologic Perspectives & Innovations (EP&I) was created to provide a forum for efforts to improve the quality of health science research and its applications.
Successful enterprises know they must devote a substantial portion of their resources – at least a few percent and often ten percent or more – to assessing whether the rest of their resources are being optimally directed. Such efforts include research and development, which improves the quality of products, and outcomes research, which assesses the impact of those products. In an applied science like epidemiology, these efforts should be devoted to designing new methods for conducting studies and interpreting results, translation of research into effective policy recommendations, critical review of past findings and current practice, and improvement of teaching the next generation of scientists.
Given the resources expended by the health science research enterprise, epidemiology (which we define broadly, including both population health and clinical research, and covering biological, behavioral, and economic dimensions) is characterized by remarkably little innovation, let alone critical review of existing dogma. A well-educated epidemiologist transported forward in time from 1980 would probably be able to read (and participate in) most current research and would find few surprises other than a few specific study results. Yet a substantial portion of all the epidemiology ever conducted has been carried out since 1980 – probably more than half, even including in the count all medical literature back to the dawn of literacy. The outputs of the science have increased to a torrent; research to improve the quality of the science is a trickle.
It can hardly be argued that this slow innovation and lack of perspective is because current approaches offer little room for improvement. Current discussions of advanced statistical methods, the nature of random error, sensitivity analysis and uncertainty quantification, and proper interpretation of results, to name just a few, show that most current epidemiologic research uses methodology in need of improvement. Granting that many problems would be eliminated if health researchers – who often have minimal training in epidemiology – just followed the dictates of a good basic epidemiology textbook, there are still major problems that lack simple solutions. It is troubling that we plow ahead with billions of dollars worth of research every year while making minimal effort to answer fundamental questions about what that research is really telling us. Epidemiology is far too important to our society to be treated as an exercise in uncritically following existing formulae.
The limitations of the field become even more apparent after the research is conducted. Results are cast out into the world as if they speak for themselves, forcing policy makers, clinicians, and interested lay people to interpret them, despite their lack of expertise in the topic area and analytic methods, and lack of necessary context.
A missing marketplace for ideas
These problems leave plenty of blame to go around, but a fair amount of it rests with the lack of opportunity to publish scholarly analytic work aimed at solving the problems. While some health researchers might be guilty of not giving the field's limitations a second thought, most probably can envision contributions they would like to make to improve it. Every conclusions section containing a single paragraph of policy discussion suggests that researchers would like to contribute to policy analysis, but have exhausted their paltry word limit. Every dissertation that reflects upon and challenges standard methods shows fresh analytic thinking, but the innovations might be read by just the half dozen people who view the actual dissertation, since the resulting publications will likely be limited to a brief recounting of the methods and results (narrowly defined). Every time a professor explains to her students that something they learned in a previous class or from reading the literature is wrong, there is a lesson that should be getting out to everyone in the field, not just the ten students in that room.
These scenarios call for full-length, analytically complete presentations (see endnote 1). Such analysis cannot be grafted onto a paper primarily focused on presenting numerical results from a study, given the severe length limitations in print journals in the health sciences. Indeed, such analyses must usually be longer than typical word limits allow, even without the study results or applications that are needed to illustrate them or provide background. A researcher who writes such a paper has a very difficult time getting it published. Moreover, it is easy to anticipate that difficulty and never even try to write the paper. The founding editors of this journal were inspired by their own experiences with these difficulties.
There are journals that cover some of these areas, but to a remarkably limited extent. "Health policy" (and more so, "health economics") journals focus on the financial side of health care, rather than more general health policy or economic issues. Statistics journals, and even the research methodology slots available in the health research journals, favor mathematically complicated advances over more practical advice. With the exception of occasional relevant entries in medical journal education series, articles devoted to improving the teaching or understanding of epidemiologic research have no clear venue. Even with some niches for certain methods, policy, overview, or perspectives articles, it is difficult to be enthusiastic about writing in these areas with no clear idea of where the results are likely to be published.
Epidemiologic Perspectives & Innovations (EP&I) was created to provide this forum, taking advantage of the greater visibility and article length offered by open-access online publishing.
Article topics
The following are areas of inquiry EP&I will publish. (An accompanying editorial [1] presents a more specific "wish list" of some of the particular analyses the editors would like to see.)
Policy: Policy recommendations do not flow simply and directly from health research results, and educated recommendations demand more than a few sentences of analysis at the end of a research report. A good policy recommendation requires high-quality analysis of a nature and quantity that does not fit in standard health research journals. At the same time, health researchers cannot leave policy analysis of their results for other people to do and publish in policy journals because there are very few such people or journals. If health researchers do not take the lead on policy analyses based on their research, the analyses will likely never be done. EP&I fills the gap by providing a forum for policy analysis in the context of health research. Policy analysis articles can be free-standing or specifically based on research reports published elsewhere. Submissions in this area should be analytic (addressing policy/decision analysis, economics, ethics, or other areas of analytic inquiry), rather than commentary.
Methodologic Innovation and Communication: EP&I welcomes submissions in all areas of epidemiologic research methodology, from study design to data analysis and reporting, including new tools, simple but important observations, and widely understandable applications of existing tools. The strength of our editorial board in this area means that submissions will be reviewed by experts who understand and appreciate new methods. Unlike most other journals publishing methods articles, EP&I welcomes submissions that are not necessarily at the technological cutting edge (though such submissions are also encouraged), but that contain lessons that are not widely known. We will spare authors the all-too-common experience of being told "everyone already knows that" when they submit a paper that calls for the use of methods or practices that are widely overlooked. Research articles are needed to translate methodological findings that are "known" (in the sense of having been discovered and understood by methods specialists), to make them known (in the sense of being understood and usable by most researchers in the field).
Ethics, Philosophy, and Critical Analysis of the Field: In most of the health research literature, any discussion of philosophical points or assessments of the quality of research is labeled "commentary" and restricted to the opinions of a few luminaries. But carefully reasoned ethical analysis, epistemology, analysis of quality, and the like are not mere commentary, and often come from junior researchers or outsiders. Our accompanying "wish list" editorial provides some examples of these types of analysis.
Re-analyses: The deluge of research results in health science means that few study results are ever carefully re-analyzed, even when their implications are quite important. When such re-analyses do occur, they are often limited to letters or perfunctory assessments in systematic reviews. EP&I offers a forum for publishing full-length re-analyses (which might use different analytic approaches, start with different premises, or report different results) of important previous research.
Teaching Methods and Innovations: Many fields have a dedicated teaching section in one or more journals. EP&I will include articles that provide teaching tools, innovations, and methods. Online publishing allows authors to include computer code, spreadsheets, datasets, and other tools that will allow readers to make use of the teaching tools. Teaching articles will be peer reviewed by experienced teachers and at least one current student at the appropriate level to judge the material. The ideal teaching articles will present an approach or method, the specific tools necessary for a reader to implement it, and a report of the authors' experience in using the material. Review will be based primarily on the apparent usefulness of the presented approach.
Multidisciplinary Research: This category is somewhat redundant, given that many of the aforementioned article types necessarily draw upon knowledge from multiple disciplines. But it is worth mentioning specifically because it is often difficult to publish work that is based in multiple fields of inquiry and thus does not fit easily into any one of them, or that is squarely in another discipline but is intended for an audience of health scientists. EP&I encourages such submissions and will review them based on their analytic merits in the fields in which they are based and their potential usefulness to health researchers.
More generally, EP&I is a home for all articles of and about epidemiology, with the exception of standard research reports. (Reporting research results as part of one of the above article types is, of course, welcome.) This includes many types of papers that are not themselves epidemiologic analysis, but inform epidemiology or are about epidemiology. We suspect that many papers of the above types exist on paper or in researchers' heads, but have previously been difficult to get published. Many more will be written when they are appreciated as analytic work that is central to the field.
Flexible format
To provide maximum flexibility for these kinds of articles, we worked with BioMed Central to create the "Analytic Perspectives" article type. We expect most submissions to EP&I to be this article type, which allows authors to create a structure that fits their analysis (as opposed to methods-results-discussion, which generally would not fit) and is labeled to emphasize that the article is analytic (as opposed to commentary).
We are also taking the unusual (for a health science journal) step of encouraging the use of endnotes. We believe that the lack of substantive endnotes or footnotes – to provide important asides, definitions, or clarifications, to note exceptions to general rules, or provide other elaboration – is a major detriment to the content of health research papers, making it difficult to present certain analytic points. For example, an interesting statistical claim or policy observation that is almost always true can either be made without further elaboration (in which case the exceptions make the claim incorrect), can include a paragraph of caveats (which is awkward and distracting), or left out (see endnote 2). Often the latter is the author's choice, which impoverishes the literature. An endnote could solve the problem. In other cases, endnotes could include short derivations of calculations that will be obvious to some readers and uninteresting to others, but may be of interest to some. Anyone familiar with the social science literature or many other fields will understand the beneficial uses to which such notes can be put (see endnote 3). Authors should consult the instructions for submissions for mechanical details of endnote use.
Target audience and authors
We hope that many readers will read EP&I from virtual cover to virtual cover. Most readers of most health science journals scan the table of contents and read the one or two articles that report results in their subspecialty, or never even see a table of contents, but merely a list of search hits on PubMed. Most articles in EP&I should be of some interest to researchers who are serious about understanding analytic health research and its implications.
We welcome submissions from researchers with all levels of experience in the field, and from experts in other fields writing for health researchers. Great innovations and critical analysis often come from senior scholars in a field, but they also often come from graduate students, outsiders, and others who are not heavily invested in the status quo of a field of inquiry.
Conclusions
In 1995, Science published the controversial article, "Epidemiology Faces its Limits" [2], which suggested that the field had already gathered all the low-hanging fruit and was not able to do much more. The premise implied by the title was dead wrong and still is: epidemiologic research (whether defined broadly or more narrowly) is no where near the limits of its technology or potential contribution to our knowledge. But nearly a decade later, the criticisms that rang true when that article was published still ring true; the progress toward "breakthroughs in the methodological tools of epidemiology" called for in that article has been limited. EP&I hopes to encourage the pursuit of breakthroughs (or, better still, a slow and steady flow of new innovations and perspectives) by providing a ready home for publishing a broad collection of such material.
Endnotes
1. "Analytic" should not be confused with quantitative calculations and results, which seldom contain much actual analysis. Analysis can be thought of as the intellectual process of systematic inquiry aimed at understanding, explaining, or characterizing phenomena or concepts.
2. For example, authors might want to point out that nondifferential misclassification error that they suspect exists most likely biased a result toward the null. However, an unqualified statement to this effect will likely generate criticism that such error is not always toward the null and that believing so is a sure sign of methodological naivete. An endnote in which the authors point out that there are exceptions, but the bias is still usually toward the null, would allow them to make their point without a long awkward caveat breaking up the main text.
3. The literature in most of these fields uses footnotes, conveniently located at the bottom of the page. Online publishing leaves us without a bottom of the page, but allows for convenient opening of multiple windows, offering the opportunity to have the endnotes open in a separate browser window. Readers of printed PDF versions will, alas, have to flip to the end.
==== Refs
Maldonado G Phillips CV Lead editorial: Wishful thinking Epidemiologic Perspectives & Innovations 2004 1 2 15507156 10.1186/1742-5573-1-2
Taubes G Epidemiology faces its limits Science 1995 269 164 9 7618077
| 15507156 | PMC524037 | CC BY | 2021-01-04 16:36:33 | no | Epidemiol Perspect Innov. 2004 Sep 6; 1:2 | latin-1 | Epidemiol Perspect Innov | 2,004 | 10.1186/1742-5573-1-2 | oa_comm |
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BMC Med EducBMC Medical Education1472-6920BioMed Central London 1472-6920-4-141537738610.1186/1472-6920-4-14Research ArticleConsumers as tutors – legitimate teachers? Owen Cathy 123cathy.owen@anu.edu.auReay Rebecca E 3rebecca.reay@act.gov.au1 Medical Education Unit, Medical School Australian National University, Australian Capital Territory, Australia2 Frank Fenner Blg 42, Canberra ACT 0200 Australia3 Academic Unit of Psychological Medicine, Blg 15, Level 2 The Canberra Hospital, WODEN ACT 2605 Australia2004 20 9 2004 4 14 14 2 6 2004 20 9 2004 Copyright © 2004 Owen and Reay; licensee BioMed Central Ltd.2004Owen and Reay; 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 aim of this study was to research the feasibility of training mental health consumers as tutors for 4th year medical students in psychiatry.
Methods
A partnership between a consumer network and an academic unit in Psychological Medicine was formed to jointly develop a training package for consumer tutors and a curriculum in interviewing skills for medical students. Student attitudes to mental health consumers were measured pre and post the program. All tutorial evaluation data was analysed using univariate statistics. Both tutors and students evaluated the teaching program using a 4 point rating scale. The mean scores for teaching and content for both students and tutors were compared using an independent samples t-test.
Results
Consumer tutors were successfully trained and accredited as tutors and able to sustain delivery of tutorials over a 4 year period. The study found that whilst the medical students started with positive attitudes towards consumers prior to the program, there was a general trend towards improved attitude across all measures. Other outcomes for tutors and students (both positive and negative) are described.
Conclusions
Consumer tutors along with professional tutors have a place in the education of medical students, are an untapped resource and deliver largely positive outcomes for students and themselves. Further possible developments are described.
==== Body
Background
Interview skills, while important in all areas of medicine, are a prime focus of educational endeavour in the teaching of psychiatry. The interview is the cornerstone of psychiatric investigation and the scene for the establishment of rapport and therapeutic engagement. The importance of effective skills training in interviewing for medical students was highlighted in the core curriculum in psychiatry published by The World Psychiatric Association and the World Federation for Medical Education [1]. An additional perspective on this issue has come from consumers who report a distinct difference between effective and ineffective interviewing styles, highlighting the hindering effect of bored, impersonal interviewers who make judgemental assumptions about an individual's behaviour [2].
Moving beyond the traditional teaching of interview skills by psychiatrists in the "see one, do one, teach one" mode, we report the development of an innovative approach to the teaching of psychiatric interview skills. This approach began four years ago as a partnership between mental health consumers and academic psychiatry to examine the ongoing feasibility of training mental health consumers as tutors for 4th year medical students in psychiatry. The idea is based on the belief that consumers have a legitimate experience to share and a rich skill base on which to draw. The purpose of this ongoing project is to contribute to the ultimate development of a workforce of medical practitioners with clinical assessment skills that are better tailored to the needs of mental health consumers. More immediate potential benefits are the promotion of an engaging curriculum in psychiatry for students, offering direct meaningful contact with mental health consumers.
Literature review
Consumers and patients are not new to medical education, offering a unique perspective on their experiences with the health system. There are 3 levels of consumer participation in education. Consumers may be the subject of teaching tutorials (a demonstration), a visitor to a tutorial (sharing their experiences with few guidelines) or a paid trained tutor delivering an agreed curriculum (a 'consumer tutor'). Consumer tutors are distinct from 'professional tutors' (those with a career obligation to teach) a distinction that does not imply a lack of professionalism regarding the consumer tutor. The issue of language is not trivial: the local user support network was committed to the term 'consumer' rather than other common labels like client or patient. The language used was chosen for the perception of action and autonomy and to reflect respect for the role and to make it clear to students and staff that these people were a committed part of the teaching workforce, not visitors only present to tell of their (often negative) experiences.
This work drew on the Partners in Arthritis project [3] that demonstrated that arthritis patients are at least equal to Consultant Rheumatologists in the teaching of examination techniques for arthritis. Related work included the use of families with experience of paediatric illness in the growth of communication skills for medical students [Reynolds 2003: personal communication] and the use of clinical teaching assistants in pap smear training [Vivienne O'Brien 2003: Personal communication]. Consumer and carer involvement in mental health education has been documented: nurse education by a consumer academic [4] with largely positive outcomes, user and carer involvement in curriculum development and delivery in interprofessional postgraduate mental health education [5], a randomised trial of brief mental health staff training by consumers with positive post-training attitudes from those taught by consumers [6] and a reminder that there are few published examples of the translation of policy rhetoric regarding consumer and carer involvement in education into teaching reality [7]. In the local area, consumers are involved in Mental Illness Education ACT (MIEACT), a national non-profit outreach education project to high school students and community groups, which aims to reduce stigma and improve mental health literacy of young people [8]. In all these projects consumers were trained, assisted in ongoing curriculum review and contributed their lived experience in the domain of interest. Despite this fertile environment for the establishment of this project and the growing consumer and carer action in psychiatry in general, there was no literature identified using trained consumers in teaching psychiatry to medical students.
In summary this project set out to train and support mental health consumers as consumer tutors for the delivery of a jointly developed curriculum for 4th year medical students in effective approaches to interviewing. There was commitment to evaluate the effectiveness of the teaching in terms of (i) changing student attitudes towards consumers, (ii) preparing students for a common examination in psychiatry, (iii) monitoring consumer tutor involvement and feedback.
The Setting
The project was set in a medical school (University of Sydney) undergoing transition to graduate entry, with adult self-directed and problem based learning models providing an opportunity to students keen to explore new ways of learning. This environment of educational change added to student and staff enthusiasm to trial new ideas. There was recognition that carers and consumers required the same respect and courtesy as professional tutors, and inequities such as only being paid travel expenses were unsatisfactory [9]. Consumer consultant positions were established to improve the relevance and user friendliness of psychiatry services using trained, paid and supervised staff [10].
Methods
Phase 1: Curriculum development
The Academic Unit of Psychological Medicine approached consumers from the local mental health consumer network seeking expressions of interest to join a steering committee to oversee the project. Consumers were involved at all stages including planning, development, implementation and evaluation. The steering committee met weekly to determine an approach to consumer tutor recruitment and training, and to author the student curriculum for delivery.
Consumer tutor development
Consumer tutors were recruited, trained in small group methods and assessed. The assessment task was a nine-item quiz. Typical questions included "List three strengths of working in small groups" and "List three strategies to get a discussion going amongst students". Those who wished to teach were then allocated in pairs to a consistent student group of six to eight students for weekly tutorials over seven weeks. Consumer tutors conducted the planned curriculum, provided feedback on each tutorial and contributed to curriculum review.
Evaluation of the content of the curriculum, the quality of the teaching and handouts was measured using a 4-point Likert scale (4 = excellent, 3 = good, 2 = fair, 1 = poor) followed by an open comment item. After each tutorial consumer tutors were debriefed by academic staff and arrangements for the following tutorials confirmed. An expedient payment method was established. Over time, consumer tutors and academic staff periodically reviewed tutor and student feedback and decided on tutorial modification.
Partnership establishment
The steering committee comprised six consumers, three with previous teaching experience at secondary or tertiary level. Professional approaches were adopted for recruitment, training, assessment, graduation and payment. Academic staff drafted a structure for consumer tutor training completed by the committee. The committee determined the priorities for the student curriculum and each oversaw the writing of a tutorial in conjunction with academic staff. Consumer input was central and meaningful rather than at the level of editing academic staff work. The committee were paid regular sitting rates for committee attendance. The steering committee met during the first trial to review progress, an overseeing role replaced later by the consumer tutors themselves.
Consumer tutor recruitment and training
Expressions of interest from potential consumer tutors were sought through the consumer network against selection criteria. These included the essential criteria of being a current consumer of mental health services and having an interest in the development of medical student interviewing skills. Desirable criteria included previous experience in teaching. Applications were reviewed by the steering committee and all applications for training were accepted. Payment for training and tutoring was set at the current university casual tutor rates appropriate to qualifications.
Recruitment resulted in a cross section of consumers including several 'marginalised consumers' who are usually under represented in such activities Three training cycles have occurred with 20 consumers (12 women, 8 men) commencing training and 18 consumers graduating from training. Fifteen consumer tutors have taught over the four years, whilst three decided after graduation that they did not wish to teach. Drop out occurred because of illness, disinterest or realising that tutoring was more difficult than first imagined.
The tutor training program comprised six weekly, one and a half hour tutorials delivered by academic staff encouraging discussion, controversy and practice in a supportive environment. See Table 1 for a summary of the consumer tutor training program. A graduation ceremony was conducted and the Dean of the clinical school awarded university badged completion certificates, although the university did not formally accredit the course. Trainee tutor evaluations revealed they valued the training experience, reporting a sense of initial nervousness later replaced by a sense of assurance of their own abilities.
Table 1 Content of 'consumers tutor' training program
Session Topic Content
1 Orientation to 4th year medical students What have they learnt so far? What other teaching and experiences do they receive during the psychiatry term? What are the characteristics of medical students?
2 Working in small groups Why are groups effective learning settings? How do groups work? How do you manage dominant and quiet group members?
3 Giving effective feedback Strategies to improve giving and receiving feedback with hands on practice
4 Review of the student curriculum Practice delivery of the planned student material through small group role-play
5 Review of the student curriculum Practice delivery of the planned student material through small group role-play
6 Trouble shooting, problem solving and tutor assessment Common fears amongst the trainee tutors? What will go wrong? How to deal with inability to attend? Completing the written assessment
Phase 2: Curriculum delivery
Student participation
Students in one of four teaching centres of the University of Sydney participated in the consumer tutor-led tutorials. Students were oriented by academic staff and completed a pre-participation measure. This measured student attitudes to mental health consumers adapted from work on the 'hated patient' [11]. Five statements were rated on a five point Likert scale (strongly agree to strongly disagree). Typical items included "I value learning from consumers" and "I would like mental health consumers as part of my practice." The final item was an open-ended question about concerns in interviewing.
Students were then introduced to their consumer tutors and participated in an 'ice breaker' session involving an interactive board game designed to sensitise medical students to the experience of being a mental health consumer. This was followed by six tutorials which both consumer tutors and medical students evaluated using the same measure. Students repeated the attitude measure at the end of the program and completed assessment tasks as per the university requirements. Students also participated in a seminar series (including didactic teaching on interview content) with professional tutors similar to that delivered in the other teaching centres. All tutorial evaluation data was analysed using univariate statistics. The pre and post attitude measure was compared using term group means (as completion was anonymous) using an independent samples t-test. The mean scores for teaching and content for both students and tutors were compared using an independent samples t-test.
Results
Delivery of the student curriculum
The student curriculum was developed as six one-hour tutorials (see Table 2 for a summary).
Table 2 Content of Consumer tutor-led tutorials for medical students.
Session Title of session Content
"Ice breaker" Lemon Looning Board Game An interactive game designed to simulate the experience of a mental health consumer.
1 'Person centred interviewing' Discussion about medical student concerns re interviewing, dealing with fears and previous experience of psychiatric contact.
Role play- Practicing sensitive interviewing styles
2 'Dealing with sensitive issues' Further developing effective interviewing styles for the purpose of exploring social and family circumstances, talking about lifestyle including sexuality, drug use, relationships and parenting.
3 "Reality Check" Dealing with fixed beliefs and delusions. Using the therapeutic relationship to enhance understanding of patients affected by delusions and hallucinations.
4 "Art Express" Developing skills in talking about self harm.
Activity: using an art therapy exercise to more effectively respond to people who are depressed.
5 "Bringing it all together" Practice interviews with volunteer in-patients and using peer discussion for feedback.
Aims: practicing sensitive interview skills for history taking.
6 "Dealing with the unexpected" Practice interviews with volunteer in-patients and using peer discussion for feedback.
Aims: dealing with time constraints, dealing with challenging or unexpected behaviour, effectively closing an interview
The tutorials were delivered by pairs of consumer-tutors to small groups of six to eight medical students. The tutorials were graded in terms of level of difficulty beginning with general discussion of sensitive interviewing styles, role playing with tutors, followed by live interviews with volunteer inpatients from the psychiatric unit. Each tutorial included discussion of the pertinent issues, practice, review by the practicing student and feedback from peers and consumer tutors. The consumer tutors independently facilitated and participated in the tutorial without the involvement of academic staff who was available to assist if needed. They were rarely required (usually to resolve room double bookings). The curriculum and written materials underwent several revisions in response to feedback aimed at improving interactivity and clarity. Consumer tutors used the ground rules set out in training for dealing with absences. Reserve tutors were introduced at the start of the term so they were familiar to students if required. Tutor pairs were able to support each other and compensate for ebbs and flows in performance.
The consumer tutors debriefed following each tutorial with academic staff. These meetings were an important opportunity for tutors to give positive and constructive feedback to each other as well as addressing ways to improve their delivery of the tutorials. They discussed problems and obstacles and brainstormed effective solutions. The larger consumer tutor group contributed to successfully resolving most conflict. Discussions were frank. Formal mediation was used to resolve a conflict between two tutors, in dispute over matters beyond teaching. Mediation was successful in terms of allowing ongoing involvement in teaching for both people. Academic staff informally debriefed the students during other tutorials. While a few students complained about the whole experience of being taught by a consumer, most students were positive. Indeed many reported they used the consumer tutors as a sounding board for other interview-related experiences during the week, seeking advice about alternative styles and approaches.
Tutor maintenance
Like all tutors, the consumer tutors required support, stimulation and refreshment. This happened in the tutorial debriefs outlined and in occasional workshops to review feedback, revise curriculum and refresh skills. Consumer tutors were encouraged to present reports of their experiences at appropriate meetings and received a national award for consumer research. Consumer tutors' motivation particularly increased when clinical mental health staff asked them about their teaching experiences and recognised that the individual had made many gains since the last episode of acute care.
Consumer and professional tutors were commonly concerned about intervening illness and the impact on teaching. Some consumer tutors became acutely unwell during the term and required care. As a result they developed an agreement to postpone their involvement in the tutoring whilst they received necessary treatment. Consumer tutors and students were understanding of this and students had a rare experience of the longitudinal patterns of an illness and the person.
Student attitudes
Out of a total cohort of 104 medical students, students completed the pre (n = 72) and post (n = 68) attitudes questionnaire using a 5 point scale (5 = strongly agree, 4 = agree, 3 = uncertain, 2 = disagree, 1 = strongly agree). A comparison of mean scores on 3 items reflecting student attitudes towards consumers was conducted using an independent samples t-test. Results showed that prior to the program the medical students began with positive attitudes towards learning from consumers (n = 57, x = 3.89, s.d. = .865) and working with mental health clients (n = 72, x = 3.68, s.d. = 747). Whilst there was a general trend towards further improvement in their attitudes, their mean scores pre and post the program were not significantly different. However, the medical students did show a significant improvement in their belief that "clients in psychiatric units give reliable histories" (n = 72, x = 3.07, s.d. = .657, p < .005) (see Table 3). This general improvement in attitudes to learning from and working with consumers was reflected in the open comments (see sample of comments in Table 4).
Table 3 Comparison of mean scores of student attitudes pre and post the program.
Statement Pre and Post N= Mean Std. Deviation Sig. (2-tailed t-test)
"I value learning from mental health clients" Pre 72 3.89 .865 .731
Post 68 3.94 .929
"Clients in psychiatric units give reliable histories" Pre 72 3.07 .657 .005
Post 66 3.42 .805
"As a doctor I would like mental health clients as part of my continuity of care practice" Pre 72 3.68 .747 .084
Post 68 3.91 .824
Total Pre 72 10.64 1.550 .063
Post 68 11.18 1.836
Table 4 Sample of medical students' open comments pre and post program
Pre training Post training
"For our purposes, consumers lack the ability to instruct us with relevant information." "The consumers give us insight into what it is like to be on the other side of the mental health system. This is invaluable in helping us to be better doctors and increase our empathy."
In addition, students' greatest concern regarding interviewing mental health consumers changed before and after the teaching. Before, students were preoccupied with violence in the interview. At the conclusion of the program, students remained concerned about violence and unpredictable reactions. However, they reported increased concern with their ability to build rapport, engage and understand the client. The program has since been modified to address their concerns about violence early on in the training.
Tutorial evaluations
Tutor and medical student evaluations using a 4-point Likert scale (4=excellent, 3=good, 2=fair, 1=poor) were returned on 452 occasions. Analysis of the mean scores of students on the quality of the 'teaching' and 'content' of the program revealed favourable ratings ('teaching' n = 450, x = 2.81, sd.76; 'content': n = 451, x = 2.82, sd= .689). Whereas, tutors tended to rate the program even higher ('teaching': n = 372, x = 3.08, sd = .510; 'content': n = 369, x = 3.14, sd=.496). A comparison of the mean scores of students and tutors using an independent samples t-test showed that this difference was statistically significant (p < 0.001), see Table 5. Open comments about the program varied as shown in Table 6.
Table 5 Analysis of mean scores on the quality of the 'consumers as tutors' program.
Tutor/student N= Mean Std. Deviation Sig. (2-tailed t-test)
Content Student 451 2.82 .689 .000
Tutor 369 3.14 .496
Teaching Student 450 2.81 .760 .000
Tutor 372 3.08 .510
Table 6 Open comments about the quality of teaching:
I am impressed with the astute feedback which is encouraging and critical"- Medical student.
"It was helpful. The tutors explained that even if the interview was going nowhere to keep persisting gently as the patient is just sizing you up"- Medical Student.
"The consumers are a valuable source of encouragement and feedback"- Medical student.
"The students interviewed a patient and showed warmth, good questions and rapport. He did not press when the patient did not want to divulge"- Consumer- tutor.
Assessment
All medical students who participated in the consumers as tutors program passed the university wide assessment of an observed psychiatric interview rated against defined criteria.
Discussion
This project established the feasibility of training and supporting mental health consumers as tutors for delivery of a jointly developed curriculum for 4th year medical students in effective approaches to interviewing. Training and delivery has continued requiring modest maintenance, perhaps in keeping with sustaining professional tutors. Consumer tutors have shown themselves to be reliable, professional in approach and amenable to feedback. Benefits for students (as measured in their open evaluations) included the extended experience of working with a consumer of health services, the development of a clearer perspective regarding consumer views and an opportunity to see people with mental illness in recovery. Students were at least as well prepared as their peers for a structured assessment in interviewing (from the combined effect of traditional and novel teaching). Students largely reported positive experiences, found the curriculum and delivery acceptable and saw tutor experience and knowledge as legitimate and valuable. Ideally it would have been useful to follow up medical students over a longer term to assess their psychiatric interviewing skill, however, this was not practically possible within this study.
The attempt to measure attitudes deserves discussion. Attitudes are recognised as an important component of curriculum development yet remain the personal business of each of us. It would be reasonable to see education as a means of working past one's own attitudes rather than seeking to refine or replace student attitudes. Guidelines for working with consumers in health care assume that "for consumer participation to be effective, all participants in the process need to respect the different skills and expertise of the other participants" [12]. In this study, student attitudes to consumers had a tendency to improve across all dimensions measured. On average the medical students began the program with largely positive attitudes to working with and learning from consumers which may explain the lack of statistically significant difference in their attitudes pre and post the program. In addition, a finding of lack of significance using a pre and post test design with a small sample of subjects is not usual. The one attitude measured that did improve throughout the program and reached statistical significance was towards mental health clients in psychiatric wards. This finding is understandable in light of the fact that the training took place within a psychiatric unit and the program incorporated practice at live interviews with clients from the unit. In addition, the study found a change in the primary focus of medical student concerns regarding interviewing which moved from issues focused on the consumer (such as violence or unpredictability) to those focused on improving their skills in interviewing and seeing this as a worthwhile activity. In terms of their satisfaction with the training program, based on their open comments, the few students who objected at least had the challenge of working in an educational model they did not admire. This was thought provoking and engaging even if the response produced was negative.
Benefits for consumer tutors (as measured by their open evaluations) included enhanced self esteem and financial reward for work done. Consumer tutor curriculum development was novel such as utilising an art therapy vehicle to experience a non-pharmaceutical therapeutic device. Most consumer tutors have continued to teach, with appropriate breaks, and have mentored new tutors. Some have used this experience to step further into paid employment and to rehabilitate previous work skills. Consumer tutors have remained resilient and episodes of relapse appear to be multifactorial in origin (with teaching perhaps one of the factors). This robustness was also found in a study of psychological impact on consumers working in a peer support role in an acute care setting [13]. Consumer presentations have centred on the powerful personal effects of participation in learning new skills and gaining confidence. The largely positive ratings of tutors about the program was not as positive as the medical students, highlighting the need to evaluate both groups to adequately measure the effectiveness of the program.
Benefits for the health system included the placement of consumers in a 'professional' light. Consumer tutors shared the staff tearoom, were paid as other casual tutors and were seen as well contributors rather than being in the sick role. Professional tutors were aware of the consumer tutor teaching and perhaps viewed it as 'politically correct' rather than educationally effective. Dissemination of findings via service and conference presentations has helped address this common view.
Tutoring medical students is a skilful and potentially stressful role, and is not suitable for all mental health consumers. Following the training program some trained tutors realised that teaching was not their interest or strength (a proportion of whom did not teach at all). This was anticipated and should be factored into training plans. Some consumer tutors realised their tolerance level was insufficient to manage student junior skill level and found it hard to resist retelling their 'war stories' of difficult clinical encounters. This was a common theme in debriefing and required active refocusing on the curriculum of effective and ineffective interview techniques. The occasional protesting student required gentle persuasion to see that ongoing participation was a way of exploring contact with consumers. Like most education programs this approach did not run itself. Tutors required sustenance; feedback needed action and materials needed review. New tutors needed to be trained to add to the growing pool of available people. Despite these issues, our experience was that this was manageable and in keeping with maintenance of quality teaching by professional tutors.
We believe this model is another valuable option in a range of consumer involvement programs and could be replicated in health, emergency services and support agency education. Discussions have occurred with carers about possible involvement. At this stage it was decided to invite carers to speak about specific topics in the mainstream program as consumers see their expertise as fundamentally different to that of a carer. Despite the potential for use with other groups, our attempt to use this experience in refreshing interview skills in general practitioners was unsuccessful. Notwithstanding the diligent work by all parties, local general practitioners held fast to the view that consumer tutors would lack the emotional robustness to survive teaching. They were welcome to come and talk of their experience but were not seen as competent to deliver a curriculum. This may well have been shorthand for more complex issues of concerns about confidentiality, power and autonomy. This example reminds us, however, that health education is in change and that new strategies are required to engage today's students in experiences that will produce clinicians skilled to support effective consumer participation in healthcare.
Conclusions
We have detailed a feasibility study which demonstrates a new level of consumer participation in the design, implementation and evaluation of a medical student training program. The effort has been sustained over four years with appropriate maintenance. Largely positive outcomes were seen for students, consumer tutors and the health care system. These included raising the profile of consumers as 'legitimate teachers' in medical education and contributing to an improvement in the attitude of medical students towards mental health consumers. Together the joint partners in the program were able to manage obstacles, such as, pessimistic attitudes towards the involvement of consumers and difficulties adhering to the curriculum. Adopting a continuous review of the feedback from both medical students and consumer tutors has helped to further refine our ability to deliver the curriculum and better support the participants. Lastly, our experience has been that consumer tutors are an untapped resource offering a richness of experience and a professional approach to teaching that deserves closer examination in other health settings.
Competing interests
Pfizer funded the initial pilot in the first year of the study.
Authors' contributions
CO conceived of the study, participated in the design of both the consumer tutor curriculum and medical student curriculum and performed the data analysis. CO and RR participated in the training of consumers, monitored the implementation and evaluation phases and coordinated the program. Both authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Thank you to Mental Health ACT who funded the participation of consumers in this program. All consumer tutors are thanked for their involvement and enthusiasm.
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| 15377386 | PMC524164 | CC BY | 2021-01-04 16:30:53 | no | BMC Med Educ. 2004 Sep 20; 4:14 | utf-8 | BMC Med Educ | 2,004 | 10.1186/1472-6920-4-14 | oa_comm |
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BMC Evol BiolBMC Evolutionary Biology1471-2148BioMed Central London 1471-2148-4-341538315410.1186/1471-2148-4-34Research ArticleEvolution of sexual asymmetry Czárán Tamás L 1czaran@ludens.elte.huHoekstra Rolf F 2Rolf.Hoekstra@wur.nl1 Theoretical Biology and Ecology Research Group of the Hungarian Academy of Sciences and Eötvös University, H-1117 Budapest, Pázmány Péter sétány 1/c, Hungary2 Laboratory of Genetics, Department of Plant Sciences, Wageningen University, Arboretumlaan 4, 6703 BD Wageningen, The Netherlands2004 21 9 2004 4 34 34 24 2 2004 21 9 2004 Copyright © 2004 Czárán and Hoekstra; licensee BioMed Central Ltd.2004Czárán and Hoekstra; 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 clear dominance of two-gender sex in recent species is a notorious puzzle of evolutionary theory. It has at least two layers: besides the most fundamental and challenging question why sex exists at all, the other part of the problem is equally perplexing but much less studied. Why do most sexual organisms use a binary mating system? Even if sex confers an evolutionary advantage (through whatever genetic mechanism), why does it manifest that advantage in two, and exactly two, genders (or mating types)? Why not just one, and why not more than two?
Results
Assuming that sex carries an inherent fitness advantage over pure clonal multiplication, we attempt to give a feasible solution to the problem of the evolution of dimorphic sexual asymmetry as opposed to monomorphic symmetry by using a spatial (cellular automaton) model and its non-spatial (mean-field) approximation. Based on a comparison of the spatial model to the mean-field approximation we suggest that spatial population structure must have played a significant role in the evolution of mating types, due to the largely clonal (self-aggregated) spatial distribution of gamete types, which is plausible in aquatic habitats for physical reasons, and appears to facilitate the evolution of a binary mating system.
Conclusions
Under broad ecological and genetic conditions the cellular automaton predicts selective removal from the population of supposedly primitive gametes that are able to mate with their own type, whereas the non-spatial model admits coexistence of the primitive type and the mating types. Thus we offer a basically ecological solution to a theoretical problem that earlier models based on random gamete encounters had failed to resolve.
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Background
One of the most general rules in biology seems to be that sex involves the fusion of gametes (sometimes of other specialised structures) of different type. In most taxa this sexual asymmetry is reflected in the male / female distinction between mating partners and/or between mating sex cells. This paper aims to help understand why sex is asymmetric.
The primary difference between male and female is anisogamy, the differential size and mobility of gametes. Anisogamy is thought to have evolved from a more primitive condition of isogamy (for reviews see [1]; [2] see also [3]).
In isogamous species without apparent male-female differentiation, like unicellular green algae (e.g. Chlamydomonas) and fungi (e.g. yeast), the asymmetry in sexual fusion and subsequent development are regulated by a binary mating type system. Mating is only possible between cells of different mating type. Molecular analysis has revealed a remarkable and complex genetic mating type structure [4,5]. The two mating types in a species consist of so-called idiomorphs [6], non-homologous complexes of closely linked genes that occupy homologous positions at the same chromosomal locus. They behave as alleles in being mutually exclusive in meiotic segregation. A similar binary mating type system exists in many filamentous ascomycetous fungi [7], which however often also exhibit male / female differentiation. Only matings between individuals of different mating type are allowed. Thus in mycelia that can function both as male and as female self-mating is prevented. Mating in such species is heterothallic, that is, always between different individuals. However, many ascomycetes are homothallic, i.e. can complete the sexual cycle in a single individual. Homothallic species may lack mating types, such as Aspergillus nidulans, or may consist of individuals that are heterokaryotic for mating type (carry nuclei of both mating types) such as Podospora anserina. In the latter case sexual fusion is between different mating types at the nuclear level, but can occur within a single individual mycelium.
In basidiomycetous fungi, morphological sexual differentiation is absent, but mating is regulated by complex mating systems, generating in some cases large numbers of different mating types. Also here, the mating type genes control sexual fusion and post-fusion development [8]. Again, mating cannot occur between individuals of the same mating type.
In other taxa still other genetic systems exist that control sexual fusion, sometimes in addition to the male-female difference. In monoecious higher plants often self-incompatibility systems occur that effectively exclude self-mating [9,10]. Among ciliates, several variations on the theme of mating type differentiation exist, which are not further detailed here.
All these different mating systems have one characteristic in common: mating is always asymmetric. When gender differences exist, mating involves the fusion of a male and a female cell; this may occur when the male and female functions are in different individuals, or when a single individual possesses both male and female functions. When gender differentiation is absent, mating type systems guarantee that sexual fusions are between different types. However, the absence of both gender and mating type differentiation has never been observed. This would imply symmetric sexual fusion: a species in which every sex cell could potentially fuse with any other sex cell. Because gender differences starting with anisogamy most likely evolved from pre-existing isogamy, we should consider the evolution of mating types in an isogamous species to understand why sex is asymmetric.
Functional explanations of the evolution of a binary mating type system have been explored in theoretical models by [11-13] and [14]. These models differ in their biological assumptions. According to [12] and [13], mating types have evolved to suppress harmful conflicts between cytoplasmic elements, while [11] suggests that mating type loci have evolved in response to polymorphisms for genes involved in gamete recognition. It is still not possible to conclusively decide between the alternative biological scenario's [15]. However, all models envisage as a starting point an initially undifferentiated population in which every gamete can mate with any other gamete, and derive conditions for the evolution of two mating types that exclusively mate with each other and have lost the ability to mate with their own type. A general conclusion emerging from the models is that mating types may invade the initially undifferentiated population under fairly broad conditions, but that the removal of the undifferentiated type requires very strong selective forces. It is this latter aspect which in our view still forms a problem, because it is difficult to see why the original type should be so disadvantageous compared to the differentiated mating types. The mentioned models assume a homogeneous population in which random encounters lead to mating. However, this assumption is likely to be very unrealistic if vegetative reproduction is much more frequent than sexual reproduction, like it is in present-day protists, and if the mobility of the cells is low. Since the motion of cells or gametes in water is characterized by a Reynolds number (the ratio of the inertial forces to the viscous forces) smaller than one [16], clonally related cells will tend to remain in each others vicinity, and therefore a clonal distribution of cells and gametes is expected, rather than a well-mixed homogeneous population. This implies that mating types will have a smaller chance of finding a suitable mating partner than in a homogeneous population, since they are unable to mate within their clone, while the undifferentiated gamete type has no reduced opportunity for mating, although most matings will be intra-clonal. As shown in a theoretical study by [17] the "mating kinetics" may strongly influence the optimality of a sexual system.
In order to investigate the effects of spatial population structure on the evolution of mating types, we have analysed this process in a cellular automaton model and compared the results it yields to those of the corresponding non-spatial (mean-field) approximation. Such a comparison allows precise consideration of the kinetics of gamete encounters in the model system and emphasizes the role that spatial aspects of the kinetics might have played in mating type evolution. For detailed descriptions of both models see the Methods section.
Results
The specific questions we address with both the mean-field model and the cellular automaton are the following:
a) Are there reasonable parameter values that allow the coexistence of the mating types and the pan-sexual type?
b) Under what (if any) circumstances is it possible that the mating types exclude the pan-sexual type?
c) Does spatial structure play an important role in the outcome of the mating type competition system?
Coexistence of the two Mating Types and the Pan-Sexual Type
Numerical solutions to the mean-field model and simulations with the cellular automaton reveal that the system admits a single stable equilibrium state both in the non-spatial and in the spatial setting (see eg. Fig. 1). The actual equilibrium densities depend on the parameters, i.e., on the vegetative growth rates r, R, R', the vegetative death rates d, D, D', the germination rate g, the sex rate σ and the finess erosion rate φ in the mean-field, and the corresponding probability parameters in the cellular automaton model. Having explored a broad range of the parameter space – with straightforward constraints on the fitness parameters (birth and death rates), i.e., with D ≤ D' ≤ d <r ≤ R' ≤ R – we found that it is the strength of the inbreeding effect (the difference of D and D' and that of R' and R) and the rate of fitness erosion φ that has the most interesting effects on coexistence. Changing the remaining parameters – the sex rate and the germination rate – within reasonable limits (σ > 0, g > 0) does not affect the results in a qualitative sense.
Figure 1 Mating type, pan-sexual and zygote abundances in time, at zero fitness erosion rate (φ = 0)) and zero inbreeding effect (ξ = 0). Other parameters (in all simulations): Mean-field (upper-panel): birth rate of pre-zygote cells: 0.001; birth rate of post-zygote cells: 0.0015; death rate of pre-zygote cells: 0.12; death rate of post-zygote cells: 0.08; sex rate: 0.0003; germination rate: 15.0; grid size: 90.000. Cellular automaton (lower-panel): birth probability of pre-zygote cells: 0.8; birth probability of post-zygote cells: 0.9; death probability of pre-zygote cells: 0.3; death probability of post-zygote cells: 0.2; sex probability: 0.8; germination probability: 0.8; grid size: 300 × 300 (= 90.000) See the Methods section for details.
We have scaled the inbreeding effect into a single parameter ξ, defined by the equations
D' and R' have been replaced by Dξ and Rξ both in the mean-field model and in the spatial simulations, with ξ changing from 0 to 1 along the "inbreeding effect" axis of the graphs in Fig. 2 and Fig. 3. ξ = 0 represents no inbreeding effect (i.e., the vegetative cells germinated from outbred zygotes have the same fitness as those produced by inbred zygotes), and ξ > 0 means a fitness difference in favour of outbred offspring.
Figure 2 Simulation results: A) mean-field: fitness erosion rate range φ : 0.0 → 20.0; inbreeding effect range ξ : 0.0 → 1.0; abundance range N : 0 → 90.000. B) cellular automaton: fitness erosion probability range φ : 0.0 → 1.0; inbreeding effect range ξ : 0.0 → 1.0; abundance range N : 0 → 90.000
Figure 3 Simulation results with 40% sex rate (sex probability) reduction in the pan-sexual strain. Scales as in Fig. 2. A) mean-field B) cellular automaton
Fig. 2 shows the equilibrium densities of the mating types and the pan-sexual type, the zygotes and the empty cells across a range of the ξ – φ projection of the parameter space, for both the mean-field model (Fig. 2a) and the cellular automaton (Fig. 2b). It is obvious from the graphs that the sum of mating types, pan-sexual and zygote equilibrium densities (and thus the equilibrium density of empty sites) is almost unaffected by the focal parameters, but the relative frequencies of the mating types and the pan-sexual type vary across the ξ – φ plane. This applies to both the mean-field and the spatial model.
Role of space
Fig. 2a and Fig. 2b might look quite alike at first sight, suggesting that spatial constraints like short-range interactions and limited dispersion might not play a decisive role in the dynamics of the gamete type competition system. Upon closer inspection of the data, however, this impression turns out to be wrong. Even though the general shapes of the 3D graphs are similar for the non-spatial and the spatial model, there are important differences between them affecting mainly the persistence of the pan-sexual population.
One of these differences shows up in the biologically significant case of very small ξ and φ values. In the mean-field model, at ξ = 0, that is, at no fitness advantage for outbreeding, the pan-sexual strain excludes the mating types for any positive rate of fitness erosion (φ > 0). At φ = 0 (no fitness loss during vegetative multiplications), on the other hand, it is the mating types who win for any ξ > 0. At ξ = 0 = φ, the mating types and the pan-sexual type coexist, and the same applies to any parameter combination satisfying ξ ≠ 0 ≠ φ. Thus we can say that the non-spatial (mean-field) model allows coexistence for almost any parameter combination, except for the biologically less feasible margins of the parameter plane. It predicts in general that both the mating types and the pan-sexual type should have persisted, even if at variable relative frequencies. The cellular automaton model yields a different prediction, admitting the exclusion of the pan-sexual type, i.e., the victory of the two mating types on a considerable section of the parameter plane, including the ξ = 0 = φ point and its close (and biologically the most realistic) neighbourhood (cf. Fig. 1).
Alternative adaptations?
One might guess that in the spatial model the ultimate exclusion of the pan-sexual strain – wherever it happens – is the result of its producing too many dormant zygotes. This would mean that the pan-sexual cells are too frequently induced to become sexually competent and that the resulting high mating frequency impairs their ecological competitiveness. With this hypothesis, a logical next question to ask is: can the pan-sexual strain prevent its elimination by lowering its sensitivity to the induction of sexual competence? With modified versions of both the mean-field model and the cellular automaton we have simulated the effect of such an "adaptation" (Fig. 3). The only modification made to the original models was the reduction by 40 percent of the chance that a pan-sexual cell gets induced by a neighbouring gamete resulting in mating. As it is obvious from a comparison of Figs. 2 and 3, this does not solve the problem of the pan-sexual strain – to the contrary, the chances of the mating types to displace the pan-sexual are even slightly better in the modified models for the largest part of the parameter space. In the mean-field model the relative frequency of the pan-sexual population at equilibrium is smaller almost everywhere except for small nonzero values of the inbreeding effect (compare Figs. 2a and 3a). In the cellular automaton the pan-sexual strain does a little better for very high values of both the inbreeding effect and the fitness erosion rate, but suffers more everywhere else compared to the original model without sex rate reduction (compare Figs. 2b and 3b).
Discussion
There are a few conclusions that apply to any simulation regardless of its being non-spatial or spatial. Not surprisingly, increasing the fitness advantage of outbreeding ξ favours the mating types, because all their sexual interactions produce outbred offspring, while part of the matings of pan-sexual gametes always produces inbred offspring with a smaller fitness. Less obviously, increasing the fitness erosion rate φ benefits the pan-sexual type in general, because its effective sex rate is higher: every mating attempt of a pan-sexual gamete can be successful, unlike for the mating types which refuse inbreeding. Therefore the pan-sexual type has more chance than the mating types to reset its eroded fitness to the post-zygote level through mating. The faster the fitness erosion, the more pronounced the advantage of being pan-sexual, hence the more frequent the pan-sexual strain becomes.
In the mean-field model the coexistence of mating types and the pan-sexual type at ξ = 0 = φ is a spatially unrobust phenomenon. It is highly dependent on the assumption that the system is well-mixed, i.e., each cell encounters other cells of each type with a probability exactly proportional to the relative frequency of that particular type within the whole habitat. It is the breaking of this interaction symmetry in the cellular automaton that gives the mating types a definite advantage compared to the pan-sexuals, even at ξ = 0 = φ (see Fig. 1). The detailed mechanism is as follows: At ξ = 0 it makes no difference whether the mating is inbred or outbred, and at φ = 0 the fitness advantage once obtained in a single event of sex cannot be lost. Since dormant zygotes do not die, empty sites can only be produced by the death of vegetative cells, but the death rates are all equal and independent of gamete type, because (after a short transient period) every vegetative cell is in the post-zygote state. For the same reason the birth rates are also equal for all the vegetative cells, so the only factor that can make a difference between the cell types is the availability of empty sites: the limiting "resource" for reproduction. In the mean-field model the empty sites are equally available to any cell, so the growth rates of the pan-sexual and the mating type strains are identical in the long run, hence their coexistence. In the cellular automaton, however, each strain develops patches. The mating type strains do not have sex at all within their own patch, only at the interface with the patches of other strains. The pan-sexual strain has sex all the time everywhere in the habitat, therefore a larger part of its population is in the dormant zygote state. It is for this reason that at the interface with the mating type patches the pan-sexual strain has a smaller supply of vegetative invaders and thus a smaller chance to capture an empty site there. This results in a travelling front between a mating type patch and a pan-sexual patch and ultimately in the demise of the pan-sexual population altogether. This effect can even overcompensate a small disadvantage for the mating types arising from increasing the rate of fitness erosion φ slightly above 0, therefore the close neighbourhood of the ξ = 0 = φ point on the parameter plane belongs to the mating types as well. We think that it is exactly this mechanism that makes the mating types victorious in the spatial model at many parameter combinations that allowed for coexistence in the mean-field approximation. The elementary events at the interfaces between patches of different gamete types have a profound effect on the ultimate outcome of their competition at the larger spatial scale of the whole habitat.
An alternative explanation for the difference of mean-field and cellular automaton results could be that it is the finite size effect that kills off the pan-sexual population from the spatial model at many parameter combinations. Indeed, the cellular automaton is a finite system, the margins of the state space of which are sinks, but looking at the striking difference of the behaviours of the frequency trajectories at ξ = 0 = φ for example (or anywhere else where the mating types take over) in the two models proves that it is not stochastic drift but a real dynamical trend that eliminates the pan-sexual strain in the cellular automaton (see Fig. 1). The equilibrium value for the pan-sexual type is so far from zero in the mean-field model and its decrease to zero so steady in the cellular automaton that drift as the cause of the difference can be safely ruled out. Moreover, if the pan-sexual strain could be drifted to extinction, so could the mating types, but in fact we have never obtained ambiguous outcomes: sufficiently long replicate simulations always yield the same result. This applies to the whole range of the parameter space.
In order to explain the net effect of sex rate reduction on the fitness, and thus on the survival chances of the pan-sexual population one has to consider two different aspects. On the one hand, sex rate reduction decreases the relative fitness of the pan-sexual strain, because it decreases the frequency of both its inbred and outbred matings, the means of keeping fitness high. This negative fitness effect is most pronounced at high rates of fitness erosion φ. On the other hand, less frequent sex yields fewer zygotes, i.e., fewer dormant cells with 0 growth rate (recall that zygotes do not multiply and do not die). If the populations are viable, i.e., if they have a vegetative growth rate higher than 0, then less frequent mating (dormancy) is beneficial in terms of the average fitness of the pan-sexual population. This effect dominates at low values of φ, where the fitness advantage of sex does not vanish too fast. A comparison of Figs. 2 and 3 shows that neither these effects are strong, but both are detectable. The net influence on the mean-field model is quantitative, the size of the parameter domain of coexistence is not much affected. In the cellular automaton model the overall effect of sex rate reduction is a slightly larger domain of coexistence: the pan-sexual strain cannot exclude the mating types at high fitness erosion rates, and it is somewhat more persistent at medium values of φ. In all, it is quite obvious that sex rate reduction is not an efficient strategy for the pan-sexual strain to avoid exclusion by the mating types.
There is a logical possibility that asymmetric cell fusion has evolved for other reasons than and prior to sex and has subsequently been incorporated in the evolution of a full sexual cycle (the sequence of syngamy, karyogamy and meiosis). In that case sex would have been asymmetric from the start. This speculative idea has been analysed theoretically by [18] (see also [19]). The present analysis clearly does not apply to that scenario, but implicitly explains why sexual asymmetry did not disappear once evolved.
Conclusions
Assuming that sexual reproduction confers some average fitness advantage compared to simple clonal multiplication, and also supposing that the more genetically different the fusing gametes are the bigger the fitness benefit of the offspring can be, we show that a population consisting of two mating types can displace a pan-sexual population which is otherwise similar to the mating types in all other respects. In the most realistic domain of its parameter space (i.e., at low rates φ of the erosion of sexually gained fitness, and very slight extra fitness benefits for heterothallic – outbred – matings, ξ) our spatial (cellular automaton) model shows the evolution towards exclusively two mating types, whereas the non-spatial model of the same system with the same parameters predicts the coexistence of the mating types and the pan-sexuals. Thus, taking for granted that sex is profitable in evolutionary terms, we offer a basically ecological answer to the question why two mating types can be better than just one. This is, however, only a solution to half of the problem of the optimal number of mating types. Could a third, a fourth, a fifth etc. mating type invade the same system? These questions arise on a very general level in relation to the origin of sexual asymmetry, and they call for a more extended theoretical approach in the future.
Methods
The Mating Type Competition System
The basic setup of our model is similar to that of [11]. The model organism is an aquatic unicellular 'alga' with a haplontic life cycle. Three different types of haploid cells compete for space and reproduce both vegetatively and sexually. During the periods between instances of sexual reproduction, the cells multiply vegetatively, producing genetically identical daughter cells. When entering the sexual cycle, a vegetative cell turns into a gamete that can fuse with another gamete. In their gamete stage the three types of cells differ in their mating capacities as represented by different configurations of recognition molecules on the cell surface, as shown on Fig. 4.
Figure 4 Supposed recognition molecules on the cell surface of the "pan-sexual" type (G1) and the two mating types (G2 and G3)
The first gamete type G1 is 'pan-sexual' and can mate with any potential partner including its own type, while the other two, G2 and G3, are mating types, unable to mate with their own kind. Thus the system allows four kinds of matings: G1.G1, G1.G2, G1.G3 and G2.G3 of which only the last one involves both mating types.
In this basic model we furthermore specify the following assumptions. The fitness of a vegetatively produced daughter cell is equal to (or lower than, see below) that of its parent. Sexual fusion produces a dormant zygote which upon germination gives rise to haploid vegetative cells through meiotic division, in which the parental gamete types segregate as if determined by a mendelian pair of alleles. To these meiotic products – "post-zygote" vegetative cells -a higher fitness, i.e., a higher division rate and/or a lower death rate, is attributed than to "pre-zygote" vegetative cells not having gone through a sexual cycle in the near past. That is, we assume that sexual offspring have an immediate short-term fitness advantage over asexually derived daughter cells. The actual advantage may be dependent on whether the zygote has been produced by "outbreeding" (with at least one of the gametes involved belonging to one of the two mating types) or "inbreeding" (both gametes pan-sexual). In general we may, but need not, assume that inbred zygotes yield vegetative cells of somewhat less (but still positive) fitness advantage than outbred zygotes. Note that here "outbreeding" and "inbreeding" mean mating between different and identical gamete types, respectively, i.e., we assume – without specifying the precise nature of this outbreeding advantage – that mating between different gamete types may result in fitter offspring on average than mating between cells of the same (pan-sexual) gamete type. The simplest possible genetic mechanism with this effect might be the production of recombinant offspring carrying fewer (slightly) deleterious alleles than both parental genotypes. This mechanism will be operative more often in heterotypic than in homotypic matings, because among the latter a larger proportion will involve selfing (mating between genetically (almost) identical genotypes). The fitness advantage of sexually derived vegetative cells fades away in time during successive rounds of vegetative reproduction (fitness erosion due to the accumulation of harmful mutations), but it can be re-gained through another sexual event. This means that post-zygote cells return to the pre-zygote state when they are not involved in a new sexual cycle for a sufficiently long time.
As for the ecology of the system, we assume that the habitat consists of a limited amount of sites that cells can occupy, and that the three cell types are competing for these sites. Death events leave empty sites behind, which can be occupied later by new offspring. The chance of a newborn cell to settle is proportional to its division rate and the number of empty sites available. In accordance with what has been said earlier about the fitness advantages of sex, three different division rates and death rates are possible: one for pre-zygote, the second for inbred post-zygote, and the third for outbred post-zygote vegetative cells. The straightforward fitness order of these three types is: Wpre-zygote <Wpost-zygote,inbred ≤ Wpost-zygote,outbred.
The fusion of two gametes produces a zygote of double size compared to a gamete, and the zygote enters a dormant state with zero rates of division and death. Zygotes leave dormancy at a constant rate, giving rise to post-zygote vegetative cells which inherit the mating type of the gametes they are produced by, and gain fitness according to whether the mating was of the inbreeding or the outbreeding type.
Fig. 5 is a diagram of the possible state transitions in the mating type system. The number of possible states for a site is 12 (including the empty state), according to the type of the cell occupying the site. Thus a site can be in any one of the 3 types of pre-zygote vegetative, 4 types of different zygote, 4 types of post-zygote vegetative, and the empty state.
Figure 5 Box diagram of the mean-field model. Box arrows: death of vegetative cells; loop arrows: clonal division; full arrows: sexual fusion; dot-headed arrows: germination; dashed arrows: fitness erosion
The Nonspatial Model
Based on Fig. 5, the mathematical formulation of the nonspatial (mean-field) model for the competitive mating type system is straightforward; the differential equations for the 12 site-states are:
where x, y and p are the numbers of sites occupied by pre-zygote vegetative cells (x and y: mating types, p: pan-sexual type), Zxy, Zxp, Zyp are the sites of outbred, and Zpp are those of inbred zygotes. Similarly, X, Y and P are sites of outbred, Q are those of inbred post-zygote vegetative cells. E is the number of empty sites within the habitat. The parameters of the model are listed and described in Table 1.
The right-hand side of the differential equations for the sites occupied by pre-zygote vegetative cells (x, y and p) has three terms. The first defines the vegetative fitness of the corresponding cell type (divisions and deaths under the competitive effect of all cell types present in the habitat), the second is the outflow from the pre-zygote vegetative state due to sex, and the third is the inflow due to the fitness erosion of post-zygote vegetative cells. Zygotes have no vegetative fitness; the first term in their differential equations is the inflow due to sex, the second is the outflow due to germination. Post-zygote vegetative cells have a vegetative fitness different from that of pre-zygotes (first term); they form zygotes fusing (after induction to sexual competence) with both pre- and post-zygote cells matching in mating type (second term); their fitness advantage erodes at a constant rate resulting in an outflow into the pre-zygote state (third term), and the germination of dormant zygotes maintains an inflow from the zygote states (fourth term). The number of empty sites is increased by the deaths of vegetative cells (first three terms) and decreased by the number of sites taken by newborn vegetative offspring (fourth term). The total number of sites does not change in time, so the 12 time derivatives sum up to zero.
Table 1 Parameters of the non-spatial model:
r pre-zygote birth rate
R post-zygote birth rate (outbred)
R' post-zygote birth rate (inbred)
d pre-zygote death rate
D post-zygote death rate (outbred)
D' post-zygote death rate (inbred)
σ sex rate
g germination rate
φ erosion rate of post-zygote fitness advantage
Analytical solutions to this nonlinear model are out of question. We have chosen to find equilibria via numerical solutions, in order to be able to compare the results to those of the spatial model (see below). In all numerical calculations the initial populations were 10 pre-zygote vegetative cells of both mating types and the pan-sexual type, all other states had 0 initial abundances.
The Spatial Simulation Model
With assumptions as similar to the nonspatial system as possible, we have implemented a site-based (cf. [20]), spatially explicit stochastic cellular automaton model to which the nonspatial system above is a mean-field approximation. The arena of the spatial model is a set of sites arranged in a 300 × 300 square grid of toroidal topology to avoid edge effects. Each site can be occupied by any one of the 11 cell types (3 pre-zygote, 4 post-zygote vegetative types and 4 types of zygote) or it can be empty. Zygotes occupy two adjacent sites.
The pattern is updated one randomly chosen site at a time, i.e., we use an asynchronous random updating algorithm. Any site chosen for update can be empty, occupied by a vegetative cell, or occupied by a zygote. We specify the algorithm for each of these cases in turn. A schematic diagram of a single step of updating is given in Fig. 6.
Figure 6 Flow chart of a single site update of the cellular automaton algorithm
Empty site update
After updating, an empty site can be occupied by one (and only one) of the vegetatively produced offspring of the cells in the 8 neighbouring sites (i.e., the Moore neighbourhood of the focal site), or it remains empty. Each vegetative neighbour i has a chance pi to put a daughter cell into the empty site. pi depends on the vegetative reproduction parameter βI (0 ≤ βI ≤ 1)of neighbour i. βI is the spatial analogon of ri in the mean-field model, and it takes one of three possible values depending on whether i is in the pre-zygote, the inbred or the outbred post-zygote state.
Specifically, the chance of the empty site to remain empty is
so the probability that the offspring of neighbour i takes the site is
The rationale behind this formalism is that each neighbour attempts putting an offspring into the empty site with a probability βi, but only one of the candidate offspring survives. The chance of survival is proportional to the reproduction parameter of the mother cell.
Vegetative site update
Updating a site occupied by a vegetative cell may result in four possible outcomes: turn the site into the empty state (death), leave it as it was (survival maintaining fitness), change the vegetative status of the resident cell from post-zygote to pre-zygote (survival with fitness erosion), or produce a zygote (sex). The probability of a death event depends on the death probability δ of the cell occupying the site, which in turn depends on its vegetative status (pre-zygote, inbred or outbred post-zygote). With a mating partner in one of the neighbouring sites, a surviving vegetative cell may enter the sexual cycle with probability s turning itself and a randomly chosen, suitable neighbour into gametes, and mate. The result is a dormant zygote occupying the two neighbouring sites of the fused gametes. A survivor skipping sex may keep its original fitness, or – if it was a post-zygote cell – it can lose its fitness advantage with a probability f (which is the spatial analogon of the fitness erosion rate φ in the mean-field model).
Zygote site update
A zygote can do two things: remain dormant (with probability 1 – γ) or germinate (with probability γ). A germinated zygote yields two vegetative cells, the mating types of which are the same as those of the gametes which produced the zygote. The vegetative status of the cells thus obtained is post-zygote, and they can be either inbred or outbred, depending on the parental gamete type combination. The daughter cells are positioned at random into the two sites the zygote had occupied.
At time 0 we have populated 2% of the sites by pre-zygote vegetative individuals of both mating types and the pan-sexual type, assigning individuals to sites at random. All other sites were empty at time 0. The simulations were run for 10.000 generations.
Authors' contributions
RH organized and coordinated the project, collected most of the literature and drafted parts of the manuscript. TC designed and built the models, drafted parts of the manuscript and the figures.
Acknowledgements
Support from grant no. T 037726 from the Hungarian Scientific Research Fund (OTKA) and a Visiting Scientist Grant from Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) to Tamás Czárán are gratefully acknowledged.
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| 15383154 | PMC524165 | CC BY | 2021-01-04 16:29:01 | no | BMC Evol Biol. 2004 Sep 21; 4:34 | utf-8 | BMC Evol Biol | 2,004 | 10.1186/1471-2148-4-34 | oa_comm |
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BMC GastroenterolBMC Gastroenterology1471-230XBioMed Central London 1471-230X-4-221538505310.1186/1471-230X-4-22Research ArticleCyclin A and cyclin D1 as significant prognostic markers in colorectal cancer patients Bahnassy Abeer A 1chaya2000@hotmail.comZekri Abdel-Rahman N 2ncizakri@starnet.com.egEl-Houssini Soumaya 1chaya2000@hotmail.comEl-Shehaby Amal MR 3chaya2000@hotmail.comMahmoud Moustafa Raafat 1ncizakri@starnet.com.egAbdallah Samira 4chaya2000@hotmail.comEl-Serafi Mostafa 5melserafi@starnet.com.eg1 Pathology Department, National Cancer Institute, Cairo University, Cairo, Egypt2 Virology and Immunology Unit, Cancer Biology Department, National Cancer Institute, Cairo University, Cairo, Egypt3 Biochemistry Department, Kasr El-Eini School of Medicine, Cairo University, Cairo, Egypt4 Pathologyy Department, Kasr El-Eini School of Medicine, Cairo University, Cairo, Egypt5 Medical Oncology Department, National Cancer Institute, Cairo University, Cairo, Egypt2004 23 9 2004 4 22 22 25 4 2004 23 9 2004 Copyright © 2004 Bahnassy et al; licensee BioMed Central Ltd.2004Bahnassy 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
Colorectal cancer is a common cancer all over the world. Aberrations in the cell cycle checkpoints have been shown to be of prognostic significance in colorectal cancer.
Methods
The expression of cyclin D1, cyclin A, histone H3 and Ki-67 was examined in 60 colorectal cancer cases for co-regulation and impact on overall survival using immunohistochemistry, southern blot and in situ hybridization techniques. Immunoreactivity was evaluated semi quantitatively by determining the staining index of the studied proteins.
Results
There was a significant correlation between cyclin D1 gene amplification and protein overexpression (concordance = 63.6%) and between Ki-67 and the other studied proteins. The staining index for Ki-67, cyclin A and D1 was higher in large, poorly differentiated tumors. The staining index of cyclin D1 was significantly higher in cases with deeply invasive tumors and nodal metastasis. Overexpression of cyclin A and D1 and amplification of cyclin D1 were associated with reduced overall survival. Multivariate analysis shows that cyclin D1 and A are two independent prognostic factors in colorectal cancer patients.
Conclusions
Loss of cell cycle checkpoints control is common in colorectal cancer. Cyclin A and D1 are superior independent indicators of poor prognosis in colorectal cancer patients. Therefore, they may help in predicting the clinical outcome of those patients on an individual basis and could be considered important therapeutic targets.
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Background
Colorectal cancer (CRC) is the third most common cancer in Western countries [1]. In Egypt, CRC has unique characteristics that differ from that reported in other countries of the western society. It was estimated that 35.6% of the Egyptian CRC cases are below 40 years of age and patients usually present with advanced stage, high grade tumors that carry more mutations [2]. This uniquely high proportion of early-onset CRC, the early and continuous exposure to hazardous environmental agents, the different mutational spectrum and the prevalent consanguinity in Egypt justify further studies [3]. It was proved that most cancers result from accumulation of genetic alterations involving certain groups of genes, the majority of which are cell cycle regulators that either stimulate or inhibit cell cycle progression [1]. Cell proliferation allows orderly progression through the cell cycle, which is governed by a number of proteins including cyclins and cyclin dependent kinases [4,5]. The cyclins belong to a superfamily of genes whose products complex with various cyclin-dependent kinases (cdks) to regulate transitions through key checkpoints of the cell cycle [6]. Abnormalities of several cyclins have been reported in different tumor types, implicating, in particular, cyclin A, cyclin E and cyclin D [6,7].
Cyclin D1 is a G1 cyclin that regulates the transition from G1 to S phase since its peak level and maximum activity are reached during the G1 phase of the cell cycle. Whereas cyclin A is regarded a regulator of the transition to mitosis since it reaches its maximum level during the S and G2 phases [8]. The mechanisms likely to activate the oncogenic properties of the cyclins include chromosomal translocations, gene amplification and aberrant protein overexpression [7,9].
Several studies have shown that, histone H3 mRNA expression can be used to identify the S phase fraction (SPF) through the in situ hybridization (ISH) technique [10,11]. The level of histone H3 mRNA reaches its peak during the S phase and then drops rapidly at the G2 phase [12].
In face of the increasing incidence of CRC and its peculiar pattern in the Egyptian population, the present study was conducted to assess the role of Ki-67 (pan-cell cycle marker), cyclin D1 (G1 phase marker), histone H3 mRNA (S phase marker), cyclin A (S to G2 phase marker) in CRC. The expression level of these markers was correlated to the clinicopathologic features and the overall survival of patients.
Methods
Tissue samples
Paraffin-embedded tumor tissues were obtained from 60 CRC patients (47 colon and 13 rectal carcinomas) that were diagnosed and treated at the National Cancer Institute, Cairo, Egypt during the period from January, 1997 to June, 2002. Clinicopathological data of the studied cases are illustrated in table 1. None of the patients received any chemotherapy or irradiation prior to surgery. Histological diagnosis of all cases was done by 2 independent pathologists according to the WHO Histological Classification. Tumors were staged according to the TNM staging system [13]. The depth of tumor invasion was classified as invasion of the mucosa including muscularis mucosa (m), invasion of the submucosa (sm), or invasion beyond the submucosa [8]. Normal colonic tissues were obtained from autopsy specimens (n = 20) and were used as a control. The actual survival rate of the patients was calculated from the date of resection to the date of death.
Table 1 Clinicopathological features of patients in relation to the staining index (SI) of Ki-67, cyclin D1, cyclin A, histone H3
SI (mean + SD)
Variables No. of cases Ki-67 Cyclin DI Cyclin A Histone H3
Sex
Male 36 18.0 ± 6.4 6.7 ± 4.3 12.7 ± 5.7 10.7 ± 5.3
Female 24 20.1 ± 5.8 8.8 ± 8.4 10.0 ± 6.0 10.7 ± 5.4
Age (years)
≥50 41 11.7 ± 6.0* 5.6 ± 5.2 10.0 ± 5.3 6.0 ± 5.0*
<50 19 23.8 ± 5.6 7.7 ± 6.8 13.6 ± 5.7 22.0 ± 5.2
Tumor size (cm)
<5.0 33 12.2 ± 6.3* 5.3 ± 3.8* 11.5 ± 6.1* 10.3 ± 4.9*
≥5.0 27 30.1 ± 6.2 22.8 ± 7.2 28.6 ± 5.6 24.0 ± 5.6
Histology
Normal 20 3.5 ± 2.0* 0.6 ± 0.2* 2.3 ± 1.1* 2.2 ± 0.9
Carcinoma 60 30.3 ± 6.2 24.9 ± 6.3 27.2 ± 5.8 10.7 ± 5.3
GI 15 11.7 ± 6.2 6.6 ± 4.0 10.0 ± 5.4 11.4 ± 4.9
GII 21 11.8 ± 5.6 8.9 ± 3.6 12.3 ± 6.5 7.8 ± 5.4
GIII 24 30.0 ± 4.3 22.0 ± 8.1 27.0 ± 4.9 11.5 ± 5.4
Lymph node
Negative 33 19.5 ± 7.0 5.4 ± 5.3* 11.9 ± 6.5 12.3 ± 5.5
Positive 27 21.3 ± 4.9 20.6 ± 6.9 12.5 ± 5.0 14.2 ± 5.0
Depth of invasion
m, sm 17 20.7 ± 6.7 3.1 ± 3.1* 11.9 ± 7.2 10.4 ± 5.1
beyond sm 43 21.9 ± 6.2 12.4 ± 6.5 12.2 ± 5.6 10.7 ± 5.4
Stage
I 6 20.6 ± 6.7 5.7 ± 6.9 24.2 ± 6.9 11.1 ± 5.3
II 27 20.8 ± 6.9 5.3 ± 4.3 24.6 ± 6.0 10.4 ± 5.7
III 12 22.0 ± 5.4 7.7 ± 6.0 27.1 ± 5.2 10.4 ± 4.9
IV 15 24.7 ± 6.1 11.3 ± 9.6 27.5 ± 5.5 12.3 ± 6.2
* p. value < 0.05 (significant)
Immunohistochemistry
Four micron sections of each normal and tumor specimen were cut onto positive-charged slides; air dried overnight, de-paraffinized in xylene, hydrated through a series of graded alcohol and washed in distilled water and 0.01 PBS (pH 7.4). Slides were then processed for IHC as described by Handa et al. [8]. using the following antibodies: Ki-67 (MIB-1, Dako), cyclin A (6E6; Novocastra, Newcastle-Upon-Tyne, UK) and cyclin D1 (DCS-6, Dako). A case of invasive breast cancer was used as a positive control for Ki-67 and cyclin A whereas a case of mantle cell lymphoma was used as a control for cyclin D1. Negative controls were obtained by replacing the primary antibody by non-immunized rabbit or mouse serum.
Brown nuclear staining was regarded as a positive result for all studied markers. The proportion of positively-stained cells and the intensity of staining were scored in tumor and normal colorectal mucosal sections at medium power (×200). The degree of positive tumor staining (percentage of positive tumor cells in the examined section) was scored from 1–6 and the staining intensity was scored from 0–6 according to the pattern of staining in the examined section. Staining index (SI) was calculated by multiplying the cellularity and staining scores as described by King et al. [14].
In situ hybridization
All tumor samples and 5 normal controls were assessed for histone H3 mRNA by ISH using the commercially available 550 base fluorescein-labeled DNA probe (Dako, Carpinteria, CA) as described by Nagao et al., 1996. This probe hybridizes to the whole mRNA transcript of the human histoneH3 gene including the5' and 3' un-translated regions. Scoring of histone H3 mRNA was performed as for immunohistochemistry, however, hybridization signals were detected in the cytoplasm.
Molecular detection of cyclin D1 gene amplification
High molecular weight DNA was extracted from paraffin-embedded tissues of the tumor and normal colorectal mucosal samples as previously described [15]. The proportion of neoplastic and normal cells was determined in each tumor sample by examining hematoxylin and eosin-stained slides obtained from the edge of the specimen used for DNA extraction. Tumor samples were evaluated for amplification of cyclin D1 if more than 75% of the examined sections were formed of neoplastic cells. Accordingly, 50 cases were eligible for the analysis. Ten micrograms of the extracted DNA was digested with EcoR1. DNA from selected cases was also digested with BglII and HindIII. Samples were separated on 0.8% agarose gels and transferred to Hybond-N membranes (Amersham Int., Amersham, UK). The membranes were hybridized with 50% formamide, 5 × SSC, 5 × Denhardt's, 500 μg/ml denatured salmon sperm DNA, 10% dextran sulphate and 106 cpm/ml of 32P-labeled PRAD-1 probe for 24 h. Membranes were washed with 2 × SSC, 0.1% SDS at room temperature for 30 min followed by 2 × SSC, 0.1% SDS at 60°C for 30 min and 0.1 × SSC, 0.1% SDS at 60°C for 1 h. Filters were autoradiographed using an intensifying screen at -70°C for 24–72 h. After being stripped free of the PRAD-1 probe, the same blots were hybridized with 32P-labeled B-actin probe to normalize against possible variations in the loading or transfer of DNA. The autoradiograms were analyzed using a densitometer. Intensities of PRAD-1/cyclin D1 were normalized to the β-actin control bands. The degree of amplification was calculated from these normalized values. Amplification was considered when the signal of the tumor band was ≥2-fold the value of the matched normal mucosa [16].
Statistical analysis
The Mann-Whitney non-parametric test was used to compare the SIs of pairs of subjects whereas the Kruskal-wallis was used for categorial data. Correlation between indices was performed using a simple linear regression test. The Kaplan-Meier method was used to create survival curves which were analyzed by the log-rank test. The impact of different variables on survival was determined using the Cox proportional hazards model. p. values less than 0.05 were considered significant.
Results
The results of IHC are illustrated in figures 1 and 2. In general, the staining index (SIs) of all studied markers was higher in carcinomas than in normal colonic mucosal samples (p = 0.0001). Normal colorectal mucosa revealed positive imunostaining for Ki-67 in the lower half of the crypts only. A heterogeneous staining pattern was detected in the neoplastic cells of well and moderately-differentiated adenocarcinomas whereas a diffuse homogeneous staining pattern was detected in poorly-differentiated carcinomas. The SI ranged from 10–40.2 (mean: 24.6 ± 6.5).
Figure 1 Normal colonic mucosa showing positive nuclear immunostaining for: (a) cyclin D1, (b) ISH of histone H3 mRNA, (c) Ki-67 and (d) cyclin A
Figure 2 A case of well differentiated adenocarcinoma with positive immunostaining for: (a) cyclin D1, (b) histone H3 mRNA, (c) Ki-67, and (d) cyclin A. Another case of moderately differentiated denocarcinoma with positive immunostaining for: (e) cyclin D1, (f) histone H3 mRNA, (g) Ki-67, and (h) cyclin A. A case of poorly differentiated adenocarcinoma with diffuse staining for: (i) cyclin D1, (j) ISH of histone H3 mRNA, (k) Ki-67 and (l) cyclin A.
Immunostaining for cyclin D1 was predominantly nuclear but cytoplasmic staining was detected in some cases. However, unless a nuclear staining was also detected, cases with cytoplasmic staining were considered negative. Normal colorectal mucosal samples were almost negative for cyclin D1 whereas 41 out of the 60 (68.3%) CRC cases were positive. Marked heterogeneity was observed in well- and moderately-differentiated adenocarcinomas even within the same tumor. Poorly-differentiated carcinomas revealed a diffuse staining pattern with more darkly-stained nuclei. The SI ranged from 0.5–28.6 (mean: 9.3 ± 4.2).
Positive nuclear staining for cyclin A was detected in 80% (48/60) of CRC cases and in all non-neoplastic control samples. Positively-stained nuclei were confined to the lower half of the crypts in normal colonic mucosa and diffusely-dispersed in carcinomas. The SI ranged from 3.3–30.2 (mean: 15.1 ± 6.6).
Histone H3 mRNA was intensely expressed in the cytoplasm of all examined samples either neoplastic or non-neoplastic. The distribution of histone H3 mRNA was similar to that of cyclin A and Ki-67 however, the proportion of histone H3 mRNA positive cells was less than that of Ki-67. The SI ranged from 1.8–24.2 (mean: 12.4 ± 5.3).
The PRAD-1 probe detected 3 EcoRI fragments of 4.0, 2.2 and 2.0 and 1 BglII fragment of 15 Kb. PRAD-1/cyclin D1 gene amplification was detected in 22/50 (44%) cases analyzed. The degree of amplification was heterogeneous with 2–10 fold increase when compared to normal mucosal samples (Figure 3). Amplification was confirmed by other restriction enzymes.
Figure 3 A: Southern blot analysis of normal mucosa (N) and their seven corresponding cases of colonic adenocarcinomas (T1–T7), cases No. 1, 2, 4, and 5 are poorly differentiated whereas cases No. 3, 6, and 7 are moderately differentiated. Genomic DNA was digested with BglII, fractionated by electrophoresis in agarose gel, transferred onto membranes and hybridized with PRAD1 and β-actin. Tumors number 1–6 (Lanes 1–6) show different degrees of PRAD1/cyclin D1 amplification, tumor number 7 (lane 7) was not amplified. B: Southern blot analysis of 3 cases of adenocarcinomas (T) and matched normal colonic mucosa (N). Genomic DNA was digested with EcoRI, fractionated by electrophoresis in agarose gel, transferred onto membranes and hybridized with PRAD1 and β-actin probes for loading control. The identification of the 3 tumors is the same as in Fig. 3A with amplification of PRAD1/cyclin D1 in tumors number 4, 5 (Lanes 1, 2) but not 7 (Lane 3).
Correlations
There was a significant correlation between cyclin D1 gene amplification and protein overexpression. Out of the 22 cases that showed amplification 14 showed protein overexpression (concordance = 63.6%).
Linear regression analysis of SIs revealed a significant correlation between Ki-67 and cyclin D1, cyclin A, histone H3 as well as between the SIs of cyclin A and histone H3 (p = 0.008, 0.0001, and 0.0001 respectively) (Figure 4). There was a significant relationship between the SI of both Ki-67 and cyclin A and the degree of differentiation of tumors as well as the size of the tumor (p < 0.001 and p < 0.01 respectively). In addition, SI of Ki-67 and histone H3 were higher in patients <50 years than in those ≥50 years (p < 0.05) (table 1).
Figure 4 Correlation between the staining intensity of (a) Ki-67 vs. cyclin D1, (b) Ki-67 vs. histone H3, (c) Ki-67 vs. cyclin A and (d) cyclin A vs. histone H3 mRNA expression.
In addition table 2 shows a significant relationship between high cyclin D1 SI and large, poorly-differentiated tumors, carcinomas with positive lymph node metastasis and deeply-invasive carcinomas (p < 0.05, p < 0.001, p < 0.05 and p < 0.05 respectively). Whereas cyclin D1 gene amplification was significantly associated with an advanced disease stage since amplification was detected in 10/15 (66.7%) of stage IV tumors compared to 12/45 (26.7%) of stage I-III tumors (p = 0.002). Similarly, DNA amplification was detected in 60.5% (26/43) of the carcinomas with extensive local invasion (beyond sm) but only in 23.5% (4/17) of the carcinomas with limited invasion (m, sm) (p = 0.001). A significant correlation was also present between cyclin D1 gene amplification and the presence of lymph node metastasis (p = 0.008) as well as between the SI of histone H3, the size of the tumor and the patient's age (p < 0.05, p < 0.001 respectively). The SI was higher in tumors >5 cm in diameter and in patients <50 years.
Table 2 The relation between cyclin D1 overexpression vs cyclin D1 amplification and clinicopathological prognostic markers.
Variables No. of cases Cyclin DI overexpression Cyclin D1 Amplification
Tumor size (cm)
<5.0 33 5.3 ± 3.8* 13/33
≥5.0 27 22.8 ± 7.2 p <0.05 9/27 p <0.236
Histology
GI 15 6.6 ± 4.0 7/15
GII 21 8.9 ± 3.6 8/21
GIII 24 22.0 ± 8.1 p <0.001 7/24 p <0.075
Lymph node
Negative 33 5.4 ± 5.3* 6/33 (18.2%)
Positive 27 20.6 ± 6.9 p <0.05 16/27 (59.3%) p <0.008
Depth of invasion
m, sm 17 3.1 ± 3.1* 4/17 (23.5%)
beyond sm 43 12.4 ± 6.5 p <0.05 26/43 (60.5%) p <0.001
Stage
early 45 5.5 ± 10.1 12/45 (26.7%)
late 15 11.3 ± 9.6 P = 0.175 10/15 (66.7%) p <0.002
Survival analysis
The mean follow-up period for all patients was 30 months (range: 1–66 months). Eighteen of 60 patients had already died by the time the study was completed. We defined the cutoff level for overexpression of each cell cycle marker at the point that showed the maximum difference of survival rate between the 2 groups separated by that point. Cox regression analysis revealed that cyclin A overexpression (our definition: SI ≥ 10.5), cyclin D1 overexpression (our definition: SI ≥ 6.1), poorly differentiated histology, lymph node metastasis, TNM stage, tumor size and depth of invasion were all significant prognostic variables for survival (Table 3). The Kaplan-Meier survival curves for the subgroups of patients who are subdivided according to each marker's status are shown in Figure 5. Patient with tumors that showed Ki-67 overexpression (our definition: SI ≥ 11.5) and histone H3 overexpression (our definition: SI ≥ 8.2) tended to have poor prognosis but this did not reach a statistically significant level, however the overall survival was significantly lower in patient with cyclin A and cyclin D1 overexpression. Cox multivariate regression analysis revealed that lymph node metastasis, cyclin A and cyclin D1 overexpression were independent negative prognostic factors after adjustment for the depth of tumor invasion, age and sex of the patient (Table 4).
Table 3 Uunivariate analysis of the relationship between survival and the tested markers
PredictiveVariables Median Survival HR CI P
Ki-67
<11.5 36
≥11.5 32 1.826 0.636 – 5.243 0.26
Cyclin D1
<6.1 35
≥6.1 18 7.246 1.007 – 45.150 0.03*
Histone H3
<8.2 35
≥8.2 29 4.639 0.854 – 25.196 0.07
Cyclin A
<10.5 35
≥10.5 15 7.820 1.017 – 60.122 0.02*
Histological grade
Low 38
High 10 7.331 2.696 – 19.940 0.0001*
Lymph node
Negative 38
Positive 15 6.826 1.973 – 23.621 0.002*
Stage
I, II, III 38
IV 12 6.378 1.842 – 22.083 0.001*
Tumor size (cm)
<5.0 35
≥5.0 13 4.835 1.386 – 16.868 0.01*
Depth of invasion
T1, T2 36
T3, T4 20 7.759 1.024 – 58.789 0.04*
Age (years)
<50 38
≥50 28 2.802 0.988 – 7.943 0.0526
Sex
Male 38
Female 36 0.696 00.274 – 1.766 0.4449
* p. value < 0.05 (significant)
HR: Hazard Ratio
CI: 95% confidence Interval
Figure 5 Kaplan-Meier survival curves for colorectal carcinoma. Overall survival is significantly lower in patients with (a) cyclin A and (b) cyclin D1 overexpression. Patients with high SI for histone H3 mRNA have poorer prognosis but this was not statistically significant (c). No significant difference was present between patients with high Ki-67 SI and those with low Ki-67 SI (d).
Table 4 Multivariate analysis ofthe relationship between survival and thetested markers
PredictiveVariables HR CI P
Cyclin D1 10.864 1.055 – 86.250 0.03*
(baseline < 6.1) - - -
Cyclin A 13.886 1.012 – 190.579 0.0490*
(baseline < 10.5) - - -
Positive Lymph node metastasis 3.921 1.057 – 14.472 0.0410*
Stage IV 3.411 1.048 – 12.083 0.03*
Depth of invasion
T3, T4 5.408 0.449 – 65.080 0.1836
Age (years)
≥50 1.996 0.678 – 5.878 0.2310
Sex 0.910 0.315 – 2.358 0.8453
p. value < 0.05 (significant)
HR: Hazard Ratio
CI: 95% confidence Interval
Discussion
The proliferative activity of CRC cells has been investigated in several studies either by immunohistochemical determination of cell proliferation index using antibodies to some types of cyclins or by flowcytometric determination of the SPF of the cell cycle [8]. Although Leach et al. [17] did not find cyclin D1 gene amplification in a panel of 47 CRC cell lines; its protein was overexpressed in about 30% of CRC cases that were included in the studies of Bartakova et al. [6] and Arber et al. [18]. In the former study [6]cyclin D1 was aberrantly accumulated in a significant subset of human CRC cases and the cell lines derived from these cases were dependent on cyclin in their cell cycle progression. In the second study [18], overexpression of cyclin D1 was detected in 30% of adenomatous polyps indicating that overexpression is a relatively early event in colon carcinogenesis which is possibly responsible for the pathological changes in the mucosa preceding neoplastic transformation. More recently, Holland et al. [19], Pasz-Walczak et al. [20] and Utsunomiya et al. [21] reported up-regulation of cyclin D1 in 58.7%, 100% and 43% of their studied cases respectively.
In the present study, up-regulation of cyclin D1 was detected in 68.3% of the cases. The SI was significantly higher in carcinomas than in normal colorectal mucosa and in poorly-differentiated adenocarcinomas it was approximately twice that of other histological types. Amplification and/or overexpression of cyclin D1 significantly correlated with deeply invasive tumors and positive lymph node metastasis. Our results in this regards are consistent with previous studies [8,22]. In 2001, Holland et al. [19]. demonstrated that deregulation of cyclin D1 and p21waf proteins are important in colorectal tumorigenesis and have implications for patient prognosis. Similarly McKay et al. [23] found that cyclin D1 was the only protein in their panel (cyclin D1, p53, p16, Rb-1, PCNA and p27) that correlated with improved outcome in CRC patients. However, few studies failed to detect any correlation between cyclin D1 overexpression and the clinicopathological factors in CRC [6,18]. This controversy in results could partially be explained by the difference in the sampling of studied cases. The present study included 24 cases of poorly differentiated adenocarcinoma, which is not common in other studies of CRC in western countries. This was possible because the majority of CRC cases diagnosed in Egypt are of high histological grade [3]. The correlation between cyclin D1 overexpression and the high histological grade was also reported in other tumor types including non-small cell lung carcinomas [24] and squamous cell carcinomas of the larynx [16]. Another possible explanation for the observed controversy in the results of different studies is the detection method used.
In the present work, overexpression of cyclin D1 was more common than gene amplification of the PRAD-1/cyclin D1 gene with a 63.6% concordance. This was similarly reported by Bartakova et al. [6] who mentioned that there is a subset of CRC cases in which cyclin D1 is overexpressed without PRAD-1/cyclin D1 gene amplification. Consistent with this hypothesis are reports of elevated cyclin D1 mRNA levels and immunohistochemically detectable accumulation of the protein in over one third of breast cancer cases at a frequency significantly higher than that deduced from DNA amplification studies [9,25]. These data imply that mechanisms other than gene amplification can also lead to deregulation and accumulation of cyclin D1 in solid tumors.
So far, several studies were done to reveal the prognostic significance of cyclin D1 overexpression in various carcinomas, including CRC [22]. However, these studies yielded conflicting results which could be attributed to organ heterogeneity. In our study, patients with tumors that exhibited cyclin D1 overexpression tended to have poor prognosis.
It was reported that, patients with cyclin A positive carcinomas had significantly shorter median survival times. Handa et al. [8] were able to detect cyclin A overexpression in 77% of their CRC cases. They also demonstrated that, cylcin A could be used as a prognostic factor of CRC. More recently, Habermann et al. [26] studied cases of ulcerative colitis with and without an associated adenocarcinoma for the presence of cyclin A overexpression. They found that, cyclin A overexpression was higher in cases of ulcerative colitis with adenocarcinomas than in those without adenocarcinomas. Consequently, they concluded that, cyclin A could be used for monitoring ulcerative colitis patients and for the early detection of an emerging carcinoma in this high risk group of patients.
In our study, cyclin A was detected in 80% of the patients and Cox regression analysis showed that it could be used as a prognostic marker in CRC in addition to cyclin D1.
It would have been useful if we assessed the expression level of cyclin A by another technique (DNA amplification). This would have added more information regarding the gene status on one hand and confirmed the results of IHC on the other hand. Unfortunately, this was not possible because in most of the cases included in the present work, the extracted DNA was not sufficient to study cyclin amplification after the assessment of cyclin D1.
In 1996, Nagao et al. [11] reported that histone H3 labeling index significantly correlated with ki-67 immunostaining and was high in poorly differentiated human hepatocellular carcinoma. This was similarly reported in the present work since we found a significant correlation between the SI of histone H3 and Ki-67. However, no statistically significant correlation was found between histone H3 SI and any of the studied clinicopathological factors.
Although Ki-67 immunostaining reflects the proliferative activity of CRC, it has not been recognized as a significant prognostic factor in this type of tumors [27,28]. However, Suzuki at al. [29] found a significant correlation between Ki-67 labeling index and local invasion of CRC. In the present study there was a significant relationship between the SI of Ki-67, tumor size and grade. However, Kaplan-Meier survival curves showed no significant difference in survival rates between patients with- and without overexpression of Ki-67.
Conclusions
Our results demonstrate that cyclin D1, cyclin A, histone H3 and Ki-67 are overexpressed in a subset of CRC, however only cyclin D1 and cyclin A overexpression correlates with poor differentiation and tumor progression. This indicates the superiority of cyclin A and cyclin D1 as indicators of poor prognosis compared to Ki-67 and histone H3 mRNA in CRC. Cyclin A and D1 could therefore be considered significant, independent prognostic factors in CRC patients. These findings are especially important in stage II patients since 25–30% of those patients have poor prognosis in spite of being node-negative. However, the standard clinicopathologic prognostic factors can not identify this subset accurately and therefore; there is a great demand for more accurate, individually-based, biological prognostic parameters that help in detecting this high risk group of patients who can benefit from an adjuvant therapy. If the findings of the present study are confirmed in a larger study, evaluation of cyclin A and D1 may be applicable to clinical management of CRC, allowing the identification of patients with poor prognosis.
Competing interests
The author(s) declare that they have no competing interests.
List of abbreviations
CRC – Colorectal cancer
OS – overall survival
SI – staining index
SPF – S phase fraction
ISH – in situ hybridization
m – muscularis mucosa
sm – invasion of the sub mucosa
Authors' contributions
BA and ZA-R carried out the molecular genetic studies, designed, coordinated the study and drafted the manuscript. BA and El-HS carried out all the histopathological and immunohistochemical studies. El-SA participated in molecular genetic studies and drafted the manuscript. MM coordinated the study. El-SM carried out all the patient clinical data. All authors read and approved the final manuscript
Pre-publication history
The pre-publication history for this paper can be accessed here:
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| 15385053 | PMC524166 | CC BY | 2021-01-04 16:29:54 | no | BMC Gastroenterol. 2004 Sep 23; 4:22 | utf-8 | BMC Gastroenterol | 2,004 | 10.1186/1471-230X-4-22 | oa_comm |
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BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-4-361538505510.1186/1471-2180-4-36Methodology ArticleMethod for inducing experimental pneumococcal meningitis in outbred mice Chiavolini Damiana 12damianac@bu.eduTripodi Sergio 3tripodis@unisi.itParigi Riccardo 1parigi3@unisi.itOggioni Marco R 1oggioni@unisi.itBlasi Elisabetta 4blasi.elisabetta@unimore.itCintorino Marcella 3cintorino@unisi.itPozzi Gianni 1pozzi@unisi.itRicci Susanna 1riccisus@unisi.it1 Dipartimento di Biologia Molecolare, Laboratorio di Microbiologia Molecolare e Biotecnologia (LA.M.M.B.), Policlinico "Le Scotte" (5° lotto), Università di Siena, Viale Bracci, 53100 Siena, Italy2 Current address: Evans Medical Research Center, 650 Albany Street, Boston University School of Medicine, Boston Medical Center, Boston, MA 02118, USA3 Istituto di Anatomia Patologica e Istologia, Policlinico "Le Scotte", Università di Siena, Viale Bracci, 53100 Siena, Italy4 Dipartimento di Scienze Igienistiche, Microbiologiche e Biostatistiche, Università di Modena e Reggio Emilia, Modena, Via Campi 287, 41100 Modena, Italy2004 22 9 2004 4 36 36 9 4 2004 22 9 2004 Copyright © 2004 Chiavolini 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
Streptococcus pneumoniae is the leading cause of bacterial meningitis. Pneumococcal meningitis is associated with the highest mortality among bacterial meningitis and it may also lead to neurological sequelae despite the use of antibiotic therapy. Experimental animal models of pneumococcal meningitis are important to study the pathogenesis of meningitis, the host immune response induced after infection, and the efficacy of novel drugs and vaccines.
Results
In the present work, we describe in detail a simple, reproducible and efficient method to induce pneumococcal meningitis in outbred mice by using the intracranial subarachnoidal route of infection. Bacteria were injected into the subarachnoid space through a soft point located 3.5 mm rostral from the bregma. The model was tested with several doses of pneumococci of three capsular serotypes (2, 3 and 4), and mice survival was recorded. Lethal doses killing 50 % of animals infected with type 2, 3 and 4 S. pneumoniae were 3.2 × 10, 2.9 × 10 and 1.9 × 102 colony forming units, respectively. Characterisation of the disease caused by the type 4 strain showed that in moribund mice systemic dissemination of pneumococci to blood and spleen occurred. Histological analysis of the brain of animals infected with type 4 S. pneumoniae proved the induction of meningitis closely resembling the disease in humans.
Conclusions
The proposed method for inducing pneumococcal meningitis in outbred mice is easy-to-perform, fast, cost-effective, and reproducible, irrespective of the serotype of pneumococci used.
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Background
Bacterial meningitis is an important infection of the central nervous system (CNS), and the three major responsible bacteria are Neisseria meningitidis, Haemophilus influenzae and Streptococcus pneumoniae [1]. Despite the use of antimicrobial therapy, pneumococcal meningitis (PM) has the highest case-fatality rate (up to 30 %) for bacterial meningitis, and in 27 % of cases, it leads to serious neurological sequelae, including cognitive impairment [2,3]. Development of PM generally starts from pneumococcal colonisation of the nasopharynx, which is the natural reservoir of S. pneumoniae in humans and especially in children [4]. The pathogenic steps leading to PM include invasion of the bloodstream from the nasopharyngeal mucosa, survival in the blood, and subsequent entry into the CNS by crossing the blood-brain-barrier (BBB) [1,2]. However, PM can also be caused by either contiguous spread of pneumococci infecting the sinuses or the middle ear, or accidental traumatic inoculation of bacteria into the CNS [2]. A recent paper showed that non-hematogenous invasion of the brain by S. pneumoniae in mice may also occur through retrograde axonal transport along olfactory neurons [5]. Once the pneumococcus starts replicating in the cerebrospinal fluid (CSF), severe inflammation occurs in cerebral vessels and subarachnoid space, and damage to the brain parenchyma is produced [1,2].
Animal models of PM have been developed in order to: (i) characterise the pathogenesis of meningitis, (ii) analyse the role of pneumococcal virulence factors in the disease, (iii) understand the host immune response to S. pneumoniae infection, and (iv) test the efficacy of novel antibiotics and vaccine candidates. Both infant and adult rats [6-9], and also adult rabbits [10-13] have largely been employed as animal models to characterise PM induced by intracisternal inoculation of bacteria. Infant rats have also been used to study haematogenous meningitis following intraperitoneal infection with S. pneumoniae [14]. However, models of PM have also been developed in the mouse by using the following routes of infection: (i) intraperitoneal (i.p.) [15-17], (ii) intranasal (i.n.) [18,19], or (iii) intracranial (i.c.) parenchymal [20,21] or cisternal [22,23]. Haematogenous murine meningitis models (both i.p. and i.n.) allow to study PM pathogenesis, and i.n. models are particularly useful as they mimic the natural infection route of S. pneumoniae in humans. However, those models present the disadvantage that PM is induced in about half of the animals, while the remaining mice may die of sepsis without developing meningitis. Models of meningitis induced by the i.p. route were employed to carry out therapeutic studies [16] and investigations on PM pathogenesis [15,17]. The i.n. model by Zwijnenburg et al. [19] was employed in interleukin (IL)-10, IL-18, and IL-1 receptor deficient mice to investigate the role of different cytokines in PM [24-26]. Direct induction (i.c. route) of PM mimics meningitis caused by contiguous spread from the sinuses or traumatic entrance of pneumococci into the CNS and allows to study the host-parasite interaction in the brain. Besides an early model of i.c.-induced meningitis in mice [20] employed in therapeutic studies [6,20], the model by Gerber et al. is an useful and reliable system for causing PM in the mouse [21]. Following infection of C57BL/6 inbred mice into the right lobe of the brain with type 3 pneumococci, bacterial enumeration in different organs, brain histology, behavioural tests, and clinical scores were performed [21]. A model of intracisternal infection was described by Koedel et al., who induced meningitis via inoculation of S. pneumoniae (type 3) into the cisterna magna of C57BL/6 mice and investigated the function of nitric oxide in the disease [23]. Both models, largely employed in studies on the roles of both pneumococcal [27] and host factors [28-32] in PM, rely on the use of inbred mouse strains and type 3 pneumococci.
In the present study, we describe an experimental model of PM in outbred mice based on the direct inoculation of bacteria into the subarachnoid space through a soft point located 3.5 mm rostral from the bregma. Both the technique employed for infection and the anatomical coordinates of the inoculation site are accurately described. The model was tested with pneumococcal strains of three different capsular serotypes and it was characterised in detail by using TIGR4 (type 4) as a model strain. The proposed method is precise, simple, cost-effective, fast and reproducible, and the disease induced closely resembles PM in humans.
Results
Inoculation site and technique
The bregma is the intersection of the coronal and sagittal sutures of the skull and can be recognised in mice by visual examination of the exposed skull (Fig. 1A). We inoculated mice by the i.c. route through a soft point located along the skull midline 3.5 mm rostral to the bregma (Fig. 1A). The stereotaxic coordinates of such inoculation point are 0 mm (× plane), 3.5 mm rostral (y plane) and 2 mm ventral (z plane) from the bregma [33]. A preliminary study was carried out to trace diffusion of the inoculation material from the point of injection into the brain. Three animals were injected with 30 μl of trypan blue and sacrificed 30 minutes after inoculation. Following decapitation, skulls were sectioned into coronal planes, and diffusion of trypan blue was observed (Fig. 1B). The dye rapidly spread from the injection site into the subarachnoid and ventricular spaces (Fig. 1B); hence, this infection route is referred to as i.c. subarachnoidal. Histological analysis of the brain sections confirmed that the inoculation needle crossed the mouse frontal lobes and reached the subarachnoid space (data not shown). In order to assess whether the inoculation technique was traumatic to animals, another experiment was performed by inoculating three control mice with saline. Animals recovered soon after injection and did not present any neurological problem (i.e. lethargy, paralysis) for several weeks after inoculation (data not shown).
These data allowed localisation of the anatomical coordinates of the inoculation site and proved the suitability of the i.c. subarachnoidal infection technique.
Meningitis induction by type 2, 3 and 4 S. pneumoniae
After characterisation of the inoculation site and technique, mice were infected with pneumococci, and the establishment of PM was evaluated and clearly evidenced by histological analysis (see below).
In order to test the model with different pneumococcal serotypes, dose-dependent survival studies were performed, and the lethal doses killing 50% of animals (LD50) were calculated. We chose three commonly used S. pneumoniae strains, such as D39, HB565, and TIGR4. The D39 strain (type 2) is the encapsulated parent of the rough type 2 R36A strain used by Avery [34-36]. The HB565 strain (type 3) is a streptomycin-resistant derivative of the A66 strain used by Avery [34,36,37]. The serotype 4 TIGR4 is the genome strain sequenced by the Institute for Genomic Research [38]. The survival patterns of mice inoculated with D39 and HB565 were almost identical, with LD50 of 3.2 × 10 and 2.9 × 10 colony forming units (CFU), respectively (data not shown). The TIGR4 strain was less virulent in the i.c. subarachnoidal infection model compared to D39 and HB565, as its LD50 was 1.9 × 102 CFU (data not shown).
Animal survival and bacterial titres after infection with the TIGR4 strain
To describe the features of PM in detail following i.c. subarachnoidal infection of mice, we chose to characterise PM induced by the TIGR4 genome strain. For this purpose, we performed time-dependent survival studies, bacterial counts in different organs/tissues, and histological analysis of brain and spleen (see below). In order to study animal survival, five groups of MF1 mice were infected with doses of TIGR4 increasing from 10 to 105 CFU per mouse. The percentage of animals surviving over time at each bacterial dose was analysed by a Kaplan-Meier curve (Fig. 2). After inoculating 10 CFU, only one mouse out of eight died 72 hours after infection (87.5 % survival). At the doses of 102 CFU and 103 CFU, 40 % of mice survived pneumococcal challenge, whereas the remaining 60 % died within 72 hours from infection. Survival further decreased from 20 % in mice infected with 104 CFU to 0 % following infection with 105 CFU, which induced severe symptoms and subsequent death of all mice within the first 48 hours after challenge (Fig. 2). The median time-to-death of the groups injected with 10, 102, 103, 104, and 105 CFU were 240, 70, 72, 72, and 40 hours, respectively. From these results, the median survival time of animals did not vary at intermediate doses (102, 103, 104 CFU), while it considerably decreased at the highest dose (105 CFU) leading to rapid death of all mice.
To determine the number of pneumococci in brain, spleen and blood at the final stages of the disease, moribund mice infected with 105 CFU of TIGR4 were sacrificed, samples collected and appropriately treated, and viable counts were carried out. Moribund animals showed comparable bacterial counts in the brain (3.1 × 106 ± 1.3 × 106 CFU/organ). Similarly, dissemination from the brain to vital organs occurred and was consistent in all animals, with bacterial counts of 3.8 × 106 ± 4.8 × 106 CFU and 2.1 × 108 ± 3.0 × 108 CFU in the spleen and blood, respectively (data not shown).
Histological characterisation of the PM model
In order to prove the establishment of PM and study the features of the disease, we performed histological analysis on the brain of moribund mice inoculated with several doses of the TIGR4 strain and sacrificed at various time-points after infection. Animals at the final stages of the disease showed typical signs of meningitis (i.e. hunchbacked, photophobic, lethargic), but they did not develop hemiparesis or plegia. Moribund mice that had received 102, 103, 104, and 105 CFU were humanely killed at 72, 72, 48, and 24 hours post-infection, respectively. Two animals for each pneumococcal dose and three additional control mice were sacrificed. Brains and spleens were excised and treated for both haematoxilin-eosin and Gram staining.
In infected mice, no cerebral abscesses were observed, but only granulocytic infiltrations involving the subarachnoid and ventricular spaces. Differently, control animals injected with saline showed no histological changes following inoculation. Brains of moribund mice following infection with the TIGR4 strain showed different degrees of inflammatory changes. Inflammation was regarded as mild in the presence of marked congestion of leptomeningeal blood vessels with margination of polymorphonuclear cells (PMNs), edema, and wisps of fibrin (Fig. 3A). Inflammation was considered severe when the subarachnoid space (Fig. 3B,3C) and/or the ventricular spaces (purulent ventriculitis) (Fig. 3D) contained cellular exudates composed of PMNs entrapped in a dense fibrin net. No large areas of cerebral necrosis were found; however, in some cases, brain damage represented by neuronal shrinkage was observed in the hippocampus (Fig. 3E). Gram staining of brain sections of infected mice revealed the presence of short chains (mainly diplococci) of Gram-positive dark blue bacteria in the subarachnoid space; pneumococci were located mainly extracellularly in a background of PMNs (Fig. 3F). Analysis of the spleen of animals infected with S. pneumoniae revealed histological changes in both the white and red pulp with a massive congestion of the red pulp (Fig. 3G), compared to the spleen of control mice (Fig. 3H). These data demonstrate that the i.c. subarachnoidal route of infection is an effective and reliable way for inducing PM in the mouse.
Discussion
S. pneumoniae is one of the causative agents of bacterial meningitis responsible for death and sequelae worldwide. The mouse has largely proved to be a reliable animal model for studying two major pneumococcal diseases such as pneumonia [39-44] and sepsis [45-47]. In the case of PM, the rat [6-9,14] and the rabbit [10-13] have often been preferred to the mouse. With the exception of an initial work describing an i.c. infection procedure for inducing PM in mice in outbred mice [20], only recently, models of PM based on i.c. inoculation were made available in inbred mice [21,23].
In the present work, starting from an experimental method used to study meningitis caused by Cryptococcus neoformans [48], we developed a model of PM based on the inoculation of bacteria into the subarachnoid space of outbred mice. This infection route (i.c. subarachnoidal) mimics bacterial entrance into the CNS from the sinuses or the middle ear, or following a trauma. We chose to inoculate mice into the subarachnoid space through a soft point located on the skull 0 mm lateral, 3.5 mm rostral, and 2 mm ventral from the bregma. Such point easily allows inoculation of bacteria from the skull through the frontal lobes into the subarachnoid space, as shown by a preliminary experiment in which trypan blue was used to localise the injection site and trace the inoculum within the brain (Fig. 1). The finding that the inoculation technique did not cause any trauma to animals can be explained by the fact that frontal lobectomy is tolerated in both humans [49] and rats [50], as frontal lobes are mainly committed to behavioural and cognitive functions. We decided to use MF1 outbred mice because this strain is well-known for its susceptibility to both intranasal [40,51,52] and intravenous [47] challenge with S. pneumoniae, and because the use of outbred strains is cost-effective. Another research group had previously used CD-1 outbred mice in a study on the efficacy of clinafloxacin against PM; however, the authors did not provide a detailed description of the model [22].
Our i.c. subarachnoidal infection model was tested by using a range of bacterial doses of three different S. pneumoniae strains. The strains chosen are the serotypes routinely employed by researchers in the pneumococcal field, and have proved to be highly pathogenic in different mouse infection models [27,40,47,52]. The use of several bacterial doses is also important, as it allows a more accurate evaluation of virulence for each strain, as well as establishing the most appropriate dose to be employed in different studies. The model proved to be suitable for use with pneumococci of different serotypes, as type 2 D39, type 3 HB565, and type 4 TIGR4 were all able to cause PM with LD50 ranging from 2.9 × 10 to 1.9 × 102 CFU. Then, PM was further characterised and standardised by using TIGR4 as a model strain. Kaplan-Meier survival analysis of animals inoculated with different doses of TIGR4 showed that 105 CFU was lethal for all mice within 48 hours from infection (Fig. 2), suggesting it as the appropriate dose inducing PM similar to hyperacute meningitis in humans. Moribund mice with acute meningitis after infection with 105 CFU were also septicaemic, as pneumococci could also be recovered from the blood and spleen. Bacterial titres were consistent in each organ/tissue of every mouse examined, underlining the reproducibility of data obtainable by using our model. Dissemination of pneumococci after infection with lethal doses is also in agreement with other i.c. murine models of PM [21,22].
The actual induction and subsequent characterisation of PM caused by the TIGR4 strain was then carried out by histological analysis of the brain tissue from moribund animals. We chose not to analyse PM by viable counting of pneumococci in the CSF, due to the difficulty of sample collection [53] and to the necessity of using pooled CSF samples [21]. Histological examination of the brain showed both cases of mild meningeal inflammation and cases of severe granulocytic effusion in the subarachnoid and ventricular spaces (purulent ventriculitis) (Fig. 3). Cerebral abscesses were not observed, further confirming that the our i.c. subarachnoidal model is indeed a meningitis and not an encephalitis model of infection. Neither inflammatory changes nor death were observed following injection of saline into control mice. Inflammation and PMNs distribution in the brain of moribund mice closely mimicked the histopathology of meningitis in humans [54]. Post-mortem examination of brains from patients who rapidly (less than 24 hours) died due to hyperacute meningitis generally reveals the presence of mild lesions consisting of a sparse leptomeningeal exudate with vessel congestion and PMN margination, in contrast to patients who survived for two or more days, who often exhibit a severe inflammation with fibrin and PMNs in subarachnoid and ventricular spaces [54]. A detailed analysis of PM largely resembling human meningitis was also reported by Gerber et al., who injected C57BL/6 inbred mice into the right lobe of the brain [21]. In that model, the inoculation site was characterised by a large purulent infiltrate present in both meninges and ventricula, and necrosis was observed in all investigated brain regions [21]. In another model, proposed by Koedel et al., pneumococci were given by transcutaneous injection directly into the cisterna magna [23]. In that study, brain lesions occurred in all mice 24 hours after infection, and histopathological examination revealed intense granulocytic infiltrations in the subarachnoid and ventricular spaces, and absence of cortical necrosis [23]. This finding differs from the model by Gerber et al., who instead reported the presence of extensive cerebral necrotic processes [21]. In our model, we could not observe large areas of necrosis, but we found some signs of neuronal damage (i.e. neuronal shrinkage with picnotic nuclei) in the hippocampus of a few animals.
Conclusions
The present work proposes a method to induce experimental PM in outbred mice by using an i.c. subarachnoidal route of infection. The stereotaxic coordinates of the injection site are provided to allow easy recognition of the inoculation point in the mouse. The model is simple and fast, and the technique assures the development of meningitis, as demonstrated by histological analysis, survival data, and microbiological parameters. No significant differences were observed in the ability of the three pneumococcal strains used to cause disease, emphasising the value of the model. It is worth noting that the use of outbred mice still results in data reproducibility, as replicates in this model closely paralleled each other in terms of survival, CFU counts per organ, and histopathological features. In addition, experiments in outbred mice are cost-effective and can be performed in larger animal groups thereby improving statistical significance. This experimental PM model may be particularly useful for all researchers involved in studies that will investigate the host-pathogen interaction at the cerebral level, with emphasis on both pathogen-associated virulence factors and host-specific brain defences.
Methods
Pneumococcal strains, media and growth conditions
Survival studies were performed with the D39, HB565 and TIGR4 strains. TIGR4 was chosen as a model strain for histological characterisation of PM and CFU counts in organs. S. pneumoniae was cultured in Tryptic Soy Broth (TSB, Difco, Detroit, MI) at 37°C with 5 % CO2. Solid media were obtained by addition of 1.5 % agar and 3 % defibrinated horse blood (Biotec s.n.c., Grosseto, Italy) to TSB. When necessary, streptomycin was used at the final concentration of 500 μg/ml.
Mice
Outbred 9-weeks-old female MF1 mice weighing 25–30 grams were obtained from Harlan Nossan (Correzzana, Italy). Animals were allowed to settle in the new environment for one week before performing the experiments, they were caged and given food and water ad libitum. All animal experiments were approved by the Local Ethical Committee (document no. 754/03, 12.9.03, see Additional file 1) and were conducted according to institutional guidelines.
Preparation of the challenge dose
Mouse-passaged S. pneumoniae strains were prepared by using a modified version of a previously described method [40]. Briefly, bacteria were injected i.p. into mice and recovered 16 hours later from homogenising the spleens with a screen mesh in 2 ml of ice-cold sterile H2O. Passaged bacteria were grown to mid-exponential phase, centrifuged for 20 minutes at 1500 × g, resuspended in fresh TSB containing 10 % glycerol, and stored in aliquots at -70°C. Numbers of bacteria were determined by viable counting of serial dilutions in sterile phosphate-buffered saline, pH = 7.4 (PBS), and plating onto blood-agar plates. Before inoculation, bacteria were thawed at room temperature, harvested by centrifugation, and resuspended in sterile PBS at the appropriate dilutions.
Mouse model of meningitis
PM was induced in lightly anaesthetised mice (50 mg/kg ketamine and 3 mg/kg xylazine) by modifying a method previously used to establish meningitis by C. neoformans in mice [48,55]. Animals were immobilised by hand and inoculated i.c. at a depth of about 2 mm through a soft point located 3.5 mm rostral from the bregma. A preliminary experiment was carried out by injecting 30 μl of trypan blue i.c. into three MF1 mice. After 30 minutes, animals were sacrificed and decapitated. Their skulls were fixed in 10 % buffered formalin for 24 hours and treated with Decal (Decal Corporation, Tallman, NY) for 24 hours. Coronal sections of about 3 mm were made, and diffusion of trypan blue was observed. Then, to localise the injection site within the brain, the above sections were embedded in paraffin and treated for histological analysis. Standard experiments were performed by injecting the bacterial inoculum in a total volume of 30 μl. Injections were performed by using glass micro-syringes (Hamilton, Bonaduz, Switzerland) with 26 gauge needles.
Survival studies
Different bacterial doses ranging from 10 to 104 CFU per mouse were used to infect mice (n= 4) with strains D39 and HB565. In the case of TIGR4, groups of 6 to 10 animals each were inoculated with doses ranging from 10 to 105 CFU per animal. Control mice were inoculated with PBS (30 μl). Mice were closely monitored twice a day for clinical symptoms (starry fur, hunched appearance, photophobia, lethargy, moribund). Mice were humanely killed before reaching the moribund state. Survival was recorded for 10 days (240 hours).
Microbiology and histology
Infected mice were sacrificed either for microbiological or histological analysis. Animals were humanely killed before being moribund, and various samples were collected. For CFU counts, blood was withdrawn by cardiac puncture before sacrifice and added to a tube containing 3.8 % of sodium citrate. Brains and spleens were excised and homogenised in 2 ml of sterile PBS. Bacterial counts in blood, brain and spleen were performed by plating 10-fold dilutions onto blood-agar plates. For histopathological analysis of tissues after infection with TIGR4, brains and spleens were immediately fixed in formalin for 24 hours and then embedded in paraffin according to standard procedures. The brains were entirely sectioned along a coronal plane. Sections were stained with both haematoxilin-eosin and Gram according to standard techniques. Morphological changes were assessed by using routine light microscopy. The presence and degree of inflammation were carefully evaluated.
Statistical analysis
Calculations of LD50 values were performed by using both the method by Reed and Muench [56] and Probit analysis with 95 % confidence interval [57]. Survival over time was analysed by the Kaplan-Meier curve.
Authors' contributions
DC, animal experiments, microbiological analysis, writing of manuscript. ST, histological analysis, writing of manuscript. RP, animal experiments, microbiological analysis. MRO, experimental design. EB, development of methodology for induction of meningitis. MC, co-ordination of histological analysis. GP, co-ordination and design of the study, data evaluation. SR, co-ordination and design of the study, data evaluation, direct supervision of experimental work, writing of manuscript.
All authors read and approved the manuscript.
Supplementary Material
Additional File 1
Document stating the ethical approval for animal experimentation conceded to the Laboratory of Molecular Microbiology and Biotechnology (LA.M.M.B.) from the University Hospital of Siena, the Medical Faculty and the Local Ethical Committee (document no. 754/03, 12.9.03).
Click here for file
Acknowledgements
The work was supported by the Commission of the European Union (contract QLK2-2000-01536) and MIUR (COFIN 2002). We would like to acknowledge Velia Braione for excellent technical assistance with experimental work.
Figures and Tables
Figure 1 Site of injection in mice inoculated via the i.c. subarachnoidal route. Three MF1 mice were injected with 30 μl of trypan blue via the i.c. subarachnoidal route through a soft point located 0 mm lateral, 3.5 mm rostral and 2 mm ventral from the bregma. After 30 minutes, animals were sacrificed and decapitated. Their skulls were fixed in formalin, decalcified and then sectioned. Results from one mouse are shown. A. The exact location of the inoculation site with respect to the bregma is indicated by an arrow. Location of the bregma is also shown. B. Mouse brains were cut in correspondence of the site of injection and then sectioned into coronal planes. Diffusion of trypan blue from the inoculation site into the subarachnoid and ventricular spaces is visible.
Figure 2 Kaplan-Meyer survival curve of mice infected with type 4 S. pneumoniae. Five groups of MF1 mice (n = 6–10) were infected by the i.c. subarachnoidal route with different doses of type 4 S. pneumoniae ranging from 10 to 105 CFU per mouse. Mice were monitored for 10 days and survival was recorded. Results are expressed as percentage of survival over time.
Figure 3 Histological analysis of the brain and spleen of mice infected with type 4 S. pneumoniae. MF1 outbred mice were infected by the i.c. subarachnoidal route with the TIGR4 strain and humanely killed before reaching the moribund state. Brains (A-F) and spleens (G-H) were excised, fixed in formalin, embedded in paraffin, and stained with either haematoxilin-eosin or Gram. A. Mild inflammatory changes with congested leptomeningeal blood vessels and PMNs margination. B-C. Severe inflammation characterised by cellular exudates composed of PMNs entrapped in fibrin in the subarachnoid space. In panel C, the fibrin web is clearly visible. D. Acute inflammation in the ventricular spaces. E. Brain damage in the hippocampus: neuronal shrinkage in the CA3 hippocampal region is shown in the inset. The location of CA1, CA2 and CA3 areas is represented. F. Gram staining of pneumococci in the subarachnoid space of the brain of moribund mice. Short chains (mainly diplococci) of Gram positive bacteria surrounded by granulocytes. G-H. Haematoxilin-eosin stained spleen sections. A distinct congestion of the red pulp together with considerable modifications of the white pulp are present in the spleen of animals infected with S. pneumoniae (G) compared to controls (H).
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| 15385055 | PMC524167 | CC BY | 2021-01-04 16:03:38 | no | BMC Microbiol. 2004 Sep 22; 4:36 | utf-8 | BMC Microbiol | 2,004 | 10.1186/1471-2180-4-36 | oa_comm |
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BMC Dev BiolBMC Developmental Biology1471-213XBioMed Central London 1471-213X-4-111538003010.1186/1471-213X-4-11Research ArticleRegulation of signaling genes by TGFβ during entry into dauer diapause in C. elegans Liu Tao 1tliu@nel-exchange.rutgers.eduZimmerman Karen K 1kzim@satx.rr.comPatterson Garth I 12patterson@biology.rutgers.edu1 Department of Molecular Biology and Biochemistry, Rutgers, the State University of New Jersey, Piscataway, NJ 08854, USA2 Cancer Institute of New Jersey, New Brunswick, NJ 08901, USA2004 20 9 2004 4 11 11 19 5 2004 20 9 2004 Copyright © 2004 Liu et al; licensee BioMed Central Ltd.2004Liu 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
When resources are scant, C. elegans larvae arrest as long-lived dauers under the control of insulin/IGF- and TGFβ-related signaling pathways. However, critical questions remain regarding the regulation of this developmental event. How do three dozen insulin-like proteins regulate one tyrosine kinase receptor to control complex events in dauer, metabolism and aging? How are signals from the TGFβ and insulin/IGF pathways integrated? What gene expression programs do these pathways regulate, and how do they control complex downstream events?
Results
We have identified genes that show different levels of expression in a comparison of wild-type L2 or L3 larvae (non-dauer) to TGFβ mutants at similar developmental stages undergoing dauer formation. Many insulin/IGF pathway and other known dauer regulatory genes have changes in expression that suggest strong positive feedback by the TGFβ pathway. In addition, many insulin-like ligand and novel genes with similarity to the extracellular domain of insulin/IGF receptors have altered expression. We have identified a large group of regulated genes with putative binding sites for the FOXO transcription factor, DAF-16. Genes with DAF-16 sites upstream of the transcription start site tend to be upregulated, whereas genes with DAF-16 sites downstream of the coding region tend to be downregulated. Finally, we also see strong regulation of many novel hedgehog- and patched-related genes, hormone biosynthetic genes, cell cycle genes, and other regulatory genes.
Conclusions
The feedback regulation of insulin/IGF pathway and other dauer genes that we observe would be predicted to amplify signals from the TGFβ pathway; this amplification may serve to ensure a decisive choice between "dauer" and "non-dauer", even if environmental cues are ambiguous. Up and down regulation of insulin-like ligands and novel genes with similarity to the extracellular domain of insulin/IGF receptors suggests opposing roles for several members of these large gene families. Unlike in adults, most genes with putative DAF-16 binding sites are upregulated during dauer entry, suggesting that DAF-16 has different activity in dauer versus adult metabolism and aging. However, our observation that the position of putative DAF-16 binding sites is correlated with the direction of regulation suggests a novel method of achieving gene-specific regulation from a single pathway. We see evidence of TGFβ-mediated regulation of several other classes of regulatory genes, and we discuss possible functions of these genes in dauer formation.
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Background
Changes in environmental conditions alter the physiology of all organisms. Evolution and experience create a signaling architecture that assesses current conditions and makes changes in physiology to attain the most appropriate state for a predicted future condition. The dauer larva of C. elegans forms when sensory inputs suggest that food resources will be inadequate for successful reproduction [1]. Food availability, competition for available food resources (population density, as measured by the concentration of a constitutively secreted pheromone), and temperature are assessed by identified chemosensory and thermosensory neurons, and signals are transduced from these neurons to affect the physiology and structure of most cell types in the body. Development is arrested after the second larval molt, and the third-stage larva that is formed is structurally and behaviorally specialized for dispersal and long-term survival.
Figure 1 shows two pathways, related to TGFβ and insulin/IGF pathways in vertebrates, which repress dauer formation under non-inducing conditions [1-4]. Studies of these signaling pathways have led to some understanding of the basic role of these pathways in regulating dauer formation. Environmental cues received by chemosensory neurons regulate the transcription of genes that encode ligands in each of these pathways:daf-7 in the TGFβ pathway and daf-28 and perhaps other insulin-like ligands in the insulin/IGF pathway [5-7]. daf-7 and daf-28 are expressed in chemosensory neurons in the amphid sensillae, which senses environmental cues that regulate dauer formation. Experiments in which components of the TGFβ and insulin/IGF pathways were expressed from tissue-specific promoters suggest that these pathways function predominantly or entirely in the nervous system to control dauer formation [8-10]. Little is known about how transcription factors regulated by these pathways control dauer entry, except that these signaling pathways probably influence a hormonal signal, because most of the cells altered in dauer are not innervated. Two components downstream of these pathways are DAF-12, a nuclear hormone receptor [11], and DAF-9, a cytochrome p450 that is a putative hormone biosynthetic enzyme [12,13]; these two genes suggest that the secondary signal may be a ligand derived from a lipid.
Figure 1 Signal transduction pathways that regulate dauer. Relationships between genes are based on mutant phenotypes and genetic interactions, gene expression in mutants, and homology to pathways in other organisms.
Dauers are long-lived [1], and mutations in many genes, particularly insulin/IGF pathway genes, affect C. elegans lifespan [14]. The role of the insulin/IGF pathway in aging appears to be shared by related pathways in Drosophila and mice [15]. Unlike mutations in insulin/IGF pathway genes, mutations in TGFβ pathway genes do not extend adult lifespan.
Many genes have been shown to be regulated by dauer formation and by the insulin/IGF pathway. However, no previous studies have focused on regulation of the decision to enter dauer. In the present study, we have used microarray-based analysis of gene regulation in C. elegans TGFβ mutants to identify genes that are directly and indirectly regulated by TGFβ signaling during the dauer formation process. Using a stringent definition for significance, we identified over 1200 genes that are upregulated and downregulated in dauer entry. In this study, we focus on the expression and regulation of genes that encode proteins involved in signal transduction and gene regulation. Analysis of these genes has helped suggest mechanisms by which TGFβ signaling might regulate a secondary hormonal cue and how signaling from TGFβ, insulin/IGF, and other dauer regulators is integrated.
We have identified genes that show different levels of expression in a comparison between wild type L2 or L3 larvae (non dauer), and several TGFβ mutants undergoing dauer larva formation (L2d-early dauer). We identify a large number of genes encoding regulatory proteins that are regulated by TGFβ signaling; of special interest are a large group of putative hormone biosynthetic enzymes and hormone receptors. We see strong regulation of many genes related to Hedgehog and its receptor, Patched; our analysis of genes coregulated with these signaling molecules suggests that the dauer-regulated members of this family function in cuticle synthesis or other hypodermal functions. Genetic evidence shows that inactivation of either the TGFβ pathway or the insulin/IGF pathway is sufficient to induce dauer formation. These results can be explained in on of two ways. First, inactivation of either pathway, even with continued activity of the parallel pathway, causes dauer formation. Second, inactivation of one pathway may lead to an inactivation of the other. We show that, when the TGFβ pathway is inactive, expression of several genes is regulated in such a way as to decrease signaling in the insulin/IGF pathway. Also, expression of the daf-12 nuclear hormone receptor gene is strongly upregulated and expression of the daf-9 cytochrome p450 gene is downregulated. These results suggest that feedback inactivation of the insulin/IGF pathway and feedback regulation of other genes may be required in order for TGFβ pathway mutants to cause dauer formation. We suggest that this feedback promotes a clear on/off decision for dauer, even under moderate dauer-inducing conditions, and discuss the relevance of feedback for control of aging. We find altered expression of more than 70 genes with putative DAF-16 regulatory sites, and find that whether these genes are upregulated or downregulated depends on the location of the putative DAF-16 site. Finally, we see regulation of many insulin-related genes as well as genes that encode proteins similar to the extracellular domain of insulin/IGF receptors; this variety of signaling molecules may allow insulin/IGF signaling to have a dramatically different outcome in dauers and adults.
Results
Array-based hybridization experiments and analysis of expression profiles
We compared gene expression in C. elegans wild type to that of animals mutant for the TGFβ pathway genes daf-7 (ligand; [5,6]), daf-8 and daf-14 (Smad transcription factors; [8,16]). At 25°, these daf-c mutants form an L2d instead of the L2 larva, and begin dauer morphogenesis after the L2d to dauer molt. Completion of morphogenesis takes about 12 hours from the molt [1]. For all experiments, we examined RNA from animals close to the molt between the L2 (or L2d) and L3 (or dauer). We compared wild-type animals that had just completed the lethargus associated with the L2/L3 molt to daf-7 animals that had just completed the lethargus associated with the L2d/dauer molt (four independent experiments). For comparisons of daf-8 or daf-14 to wild type, we used a slightly earlier stage, and compared wild type animals near the beginning of the L2/L3 lethargus to animals near the beginning of the L2d/dauer lethargus (three independent experiments each).
We found that many genes showed significant regulation in at least one genotype (t-test p < 0.05; Table 1; full data in additional file 1: Table S1). More than 90% of the genes showed consistent regulation; if a gene had significantly altered expression in one mutANT, the gene was regulated in the same direction in the other two mutants (Fig. 2). This consistency is not surprising, because all three daf-c genes are in the same signal transduction pathway and have similar phenotypes. Because the results from the three daf-c genotypes were broadly similar, we analyzed combined data from all three genotypes. By repeating our statistical analysis on the combined data set, we identified 3248 (out of genes that were significantly up- or down-regulated (P < 0.01). We identified over 1200 genes that were strongly regulated (>2.1 fold, p < 0.01; see additional file 2: Table S2).
Table 1 Significantly regulated early dauer genes in three TGFβ pathway mutants.
Genotype Harvest stage Number of experiments # genes up-regulated p < 0.05a # genes down-regulated p < 0.05
daf-7 vs. wild type early dauer/L3 4 351 1069
daf-8 vs. wild type late L2d/L2 3 180 679
daf-14 vs. wild type late L2d/L2 3 552 1276
daf-c vs. wild typeb 10 2540 3076
a Upregulated genes are expressed at a higher level in daf-c mutants than in wild type, and downregulated are the reverse.
b This row is not a summary of the rows above, rather, it is a reanalysis of the data with all ten experiments considered together.
Figure 2 Cluster diagram of gene expression responses. Each row represents an average of 3–4 independent experiments. Each gene on the array is represented as a line in each column. The color of the line represents the log2 of the expression ratio, as indicated by the scale bar.
We compared our results to published analysis of gene expression in dauers. Many studies have reported the identification of "dauer-regulated" genes, but this term covers a vast range of very different experiments, and we carefully selected data for validation (see Methods). We found that our data was in good agreement with published data from experiments of similar design (see Methods and Table 2); 7 of 8 genes examined were similarly regulated in our data and published experiments.
Table 2 Comparison of microarray data to published experiments.
Gene Method Published difference Fold change, this study P value
C27H5.5/col-36 RT-PCR L2d/dauer >> L2/L3a [64] 6.8 <0.008
C47G2.1/cut-1 Northern L2d/dauer >> L2/L3a [65] 5.7 <0.003
C08A9.1/sod-3 Northern present in dauer, absent in non-dauer [66] 7.8 <0.00001
T01B7.7/rol-6 Northern and slotblot L2/L3 >> L2d/dauera [61] -7.4 <0.00002
B0491.2/sqt-1 Northern and slotblot L2/L3 >> L2d/dauera [61] -7.0 <0.0002
T23G5.1/rnr-1 GFP fusion not seen at L2d/dauer molt, seen in cells in S phase at L2/L3 molt [67] -1.8 <0.05a
W01B6.7/col-2 Northern and slotblot L2d/dauer >> L2/L3a [61] 2.2 <0.02
T13B5.4/col-40 RT-PCR L2d/dauer >> L2/L3a [64] 1.1 <0.8
a L2d/dauer refers to animals near the molt between these two larval stages; L2/L3 also refers to animals near the molt.
b The P value for rnr-1 was calculated using only the local standard deviation because the global standard deviation was not available.
Many strongly regulated early dauer genes have DAF-16 regulatory sites
We examined the regulated genes in our data set to see if we could identify possible cis-acting regulatory sites. Three Smads (DAF-8, DAF-14, and DAF-3) act downstream of the receptors. Two of the Smads do not have an identifiable DNA binding domain [4,5,16], and may serve to negatively regulate the DAF-3 Smad [4,17]. Unfortunately, the optimal binding site for DAF-3 is only 5 bp [18]. Most genes (>80%) have a DAF-3 binding site within 2000 bp upstream of the ATG (data not shown).
Therefore, we focused on the insulin/IGF pathway that regulates DAF-16, which has an eight bp optimal binding site in experiments performed in vitro, TTGTTTAC [19]. We expect that regulated genes in our data set include targets of DAF-16 for three reasons. First, signaling from the insulin/IGF pathway is decreased in the TGFβ pathway mutants (see below). DAF-16 is negatively regulated by DAF-2 signaling, so we would expect that DAF-16 would be more active in our mutant worms. Second, DAF-16 relocalizes to the nucleus when it is active, and daf-7 mutants accumulate DAF-16 in the nucleus during dauer entry [20]. Third, DAF-16 and DAF-3 both promote dauer formation, so might have targets in common.
We see strong evidence that genes with DAF-16 sites upstream of transcription are likely to be upregulated. 2.7% of genes without DAF-16 sites are strongly upregulated, but genes with DAF-16 sites in all intervals from -1 to -1500 have significantly more upregulated genes (Fig. 3A, additional file 3: Table S3). 82 genes with a DAF-16 site within 1500 bp upstream of the translation start are strongly upregulated against a random expectation of 40. We also examined genes that did not meet our most stringent criteria for regulation: these genes were at least two-fold upregulated, but not included in the analysis in Fig. 3A. We found 50 genes with a DAF-16 binding site within 700 bp upstream of the translation start against a random expectation of 24 (Fig. 3B; additional file 3: Table S3). We examined 734 strongly downregulated genes, and see no increased likelihood of upstream DAF-16 sites (58 genes expected, 58 observed). When we examined genes with DAF-16 sites within 200 bp downstream of the stop codon, we see no correlation with upregulation (Fig. 3C). However, we see 15 downregulated genes with DAF-16 binding sites against a random expectation of 6 (Fig. 3D, additional file 3: Table S3).
Figure 3 Regulation of genes with DAF-16 binding sites. In all panels, the bars show groups defined by the location of DAF-16 sites, as shown on the X-axis. We used overlapping intervals to allow robust statistical analysis. Negative numbers are bp upstream of the initiation codon, and positive numbers are bp downstream of the stop codon. Asterisks indicate statistical significance (exact hypergeometric probability) of the proportion of strongly regulated genes in the group compared to all genes:*** is p < 0.001, ** is p < 0.01, * is p < 0.05. A. Strongly upregulated (>2.1 fold, p < 0.01) genes. B. Two fold upregulated genes, excluding those genes in panel A. C. Strongly upregulated genes with downstream DAF-16 sites. D. Strongly downregulated (<2.1 fold, p < 0.01) genes.
Insulin/IGF pathway signaling is regulated by feedback from TGFβ signaling
Insulin/IGF receptor kinase and other downstream signaling molecules
Because we found significant regulation of genes with DAF-16 binding sites, we examined regulation of genes in the insulin/IGF pathway, which acts to antagonize DAF-16 signaling. Several genes in the insulin/IGF-like pathway that regulates dauer formation (see Fig. 1) are strongly regulated. The most critical of these is daf-2, which encodes the insulin/IGF receptor, because, downstream of the receptor, the pathway bifurcates, and mutants in downstream genes have weaker phenotypes [21-23]. Downregulation of daf-2 in TGFβ pathway mutants suggests that signaling from the TGFβ pathway positively regulates signaling from the insulin/IGF pathway. Published genetic analysis shows that a nuclear hormone receptor, DAF-12, is antagonized by signaling from the TGFβ receptors [3]. One means of antagonism may be to regulate a hormone that controls DAF-12 activity. A cytochrome p450 gene, daf-9, has a partial dauer constitutive mutant phenotype, and acts upstream of daf-12 and downstream of the TGFβ pathway to repress dauer formation [12,13]. In dauers, a daf-9::GFP reporter is downregulated in hypodermis and upregulated in a pair of cells in the head [12]. We see strong downregulation of daf-9 in our data; these results are consistent, given that the hypodermis is at least two orders of magnitude larger than the head cells. We also find that daf-12 itself is strongly upregulated in our data; this is a form of regulation that had been previously unidentified. Upregulation of daf-12 and downregulation of daf-2 and daf-9 would all be predicted to induce dauer formation.
Other genes in the insulin/IGF pathway are regulated, but the regulation is complex, with both induction and repression. AKT-1, ATK-2 and PDK-1 are kinases that negatively regulate DAF-16, a FOXO transcription factor. A loss of function mutation in pdk-1 causes a dauer constitutive phenotype that is much weaker than null mutations in daf-2 [23]. Simultaneous knockdown of akt-1 and akt-2 by RNAi also gives a dauer constitutive phenotype that also is weaker than a daf-2 null. Single knockdown of akt-1 or akt-2 by RNAi does not produce a dauer constitutive phenotype [24]. The weaker phenotype of akt-1, akt-2 and pdk-1 is at least partly due to redundancy in the pathway; a second output from DAF-2 is transduced by IST-1 [21]. The phenotypes may also be weaker because the genes were not completely knocked out by RNAi. We see upregulation of pdk-1 and one isoform of akt-1, and downregulation of akt-2, one isoform of akt-1, and some, but not all, isoforms of daf-16. The overall effect of this mix of regulation is hard to predict, but suggests variable function for different genes and isoforms. For example, akt-1a, akt-1b and akt-2 may be differently regulated in different tissues, with the result that the output of signal transduction is subtly different.
Regulation of insulin/IGF and novel genes with similarity to the extracellular domain of insulin/IGF
C. elegans has one insulin/IGF receptor kinase, but dozens of insulin-related genes [24]. The reason for the abundance of ligands is unclear, but perhaps multiple insulin-like ligandss allow for different temporal and spatial patterns of receptor activation, or produce receptor-ligand complexes with different activities. The structure of the insulin-like genes is quite diverse, with three major groups defined by the pattern of disulfide bonds, and subgroups defined by differences in gene structure [24]. Diversity in function of insulin like genes has been demonstrated; INS-4, INS-6, INS-7 and DAF-28 have been shown by genetic or biochemical analysis to be receptor agonists [7,25,26], and INS-1 and INS-18 act as antagonists [24].
We see strong upregulation and downregulation of a subset of these insulin-like genes. Insulin-like genes in C. elegans have been divided into three types on the basis of disulphide bonding patterns [24]. These three groups can be further subdivided on the basis of other sequence features. One subgroup has 9 genes, ins-2 through ins-9, and daf-28. Six of these are present on the array, and four (ins-4, ins-5, ins-6 and ins-7) show significant downregulation (Table 3). The other two insulin-like genes in this family that are present on the array (ins-2 and ins-3) are not significantly changed. INS-6 has been shown to be a receptor agonist in vitro [25]. Overexpression of ins-4 and ins-6 can partially or completely rescue a daf-28 mutant [7], and ins-7 RNAi enhances a weak daf-2 mutant [26], suggesting that these insulin-like ligands act as DAF-2 agonists. Three insulin-like genes are upregulated (Table 3); only one of the three, ins-18, has an identified function, and it acts as a receptor antagonist [24]. Increased expression of this ligand, like reduction in expression of daf-2, ins-6, etc., would be expected to promote dauer formation.
Table 3 Dauer and aging genes regulated by TGFβ signaling.
Gene Induces or represses dauer?a Fold regulationb p value
insulin pathway
daf-2 (receptor) strongly represses -3.1 <0.0001
akt-2 represses -3.0 <0.0001
akt-1 allc represses 1.0 ns
akt-1ac unknown -1.8 <0.003
akt-1bc unknown 1.4 <0.03
pdk-1 represses 1.8 <0.0001
daf-16ad unknown 1.0 ns
daf-16 alld promotes -1.7 <0.0004
Insulin-like ligands
ins-4 repressese -2.1 <0.002
ins-5 unknown -2.6 <0.02
ins-6 repressese -2.6 <0.02
ins-7 represses -2.1 <0.005
ins-18 promotese 1.8 <0.002
ins-33 unknown 3.9 <0.0003
ins-35 unknown 6.5 <0.0001
insulin receptor-like
F56A4.C unknown -3.5 <0.0001
Y19D10A.7 unknown -2.8 <0.0003
F14D2.6 unknown 1.8 <0.006
F15E11.11 unknown 1.8 <0.008
other dauer and aging regulators
daf-12 strongly induces 2.2 <0.0007
daf-5 induces -2.0 <0.0003
daf-9 represses -4.2 <0.02
scl-1 unknown 5.2 <0.006
ns, not significant This
table shows all insulin-like ligands, insulin-receptor-like genes, TGFβ, and insulin/IGF pathway genes with greater than 1.8-fold regulation and a p value less than 0.05. Genes checked for regulation that showed <1.8 fold regulation or p > 0.05 or both: clk-1, clk-2, sir-2.1, daf-11, daf-7, daf-1, daf-4, daf-14, daf-8, daf-3, daf-19, tax-4, npc-1, daf-18, age-1, old-1, mev-1, hsf-1, daf-21, gpa-2, gpa-3, kin-29, kin-8, unc-3 and tph-1, as well as all genes annotated as insulins present on the microarray (ins-2, ins-3, ins-11, ins-17, ins-22, ins-23, ins-24, ins-26, ins-30, ins-32, ins-34, ins-37) and nearly all genes identified as putative insulin receptors in Dlakic [27].
aInduction or repression of dauer is defined by mutant or RNAi loss-of-function phenotypes unless otherwise noted. daf-9 mutants have characteristics similar to both types, and are thus marked "mixed".
cThe fold change between mutant dauers and wild-type. A positive number indicates higher expression in dauers, a negative number indicates higher expression in N2.
cThe table entry "akt-1 all" is for a probe that recognizes both isoforms. The other two akt-1 entries each cover an exon unique to the indicated isoform.
dThe entry "daf-16a isoform" is for a probe that recognizes:R13H8.1c (daf-16a1), R13H8.1b (daf-16a2), and R13H8.1d, but not R13H8.1a (daf-16b) or R13H8.1e. The entry "daf-16 all" is for a probe that recognizes all five isoforms of daf-16.
eOverexpression of ins-4 or ins-6 represses dauer in a daf-28 mutant [7]. ins-6 has also been shown biochemically to act as a receptor agonist [25]. Overexpression of ins-18 promotes dauer [24].
A family of genes with modest but significant similarity to the ligand binding domain of insulin/IGF receptor has been identified [27], and these may contribute to insulin/IGF signaling and signaling diversity; however, because of weak similarity to insulin/IGF receptor and similarity to other receptor tyrosine kinase ligand binding domains, a function in insulin/IGF signaling is speculative. As with the insulin-like genes, we see both upregulation and downregulation of insulin-receptor like molecules.
Regulation of regulatory genes
Genetic and molecular analysis has allowed us to gain a basic understanding of the key regulatory pathways that affect dauer formation by acting in the nervous system, but we know little about regulatory events downstream of these pathways, i.e. the regulators that actually control dauer morphogenesis and physiology. Below, we discuss a selected set of regulated genes; a complete list of regulatory genes can be found in additional file 4: Table S4.
Regulators of aging
Because dauers are long lived, and because many genes that control lifespan also control dauer entry, we examined the expression of genes with mutant phenotypes of long or short lifespan. Other than the insulin/IGF pathway genes mentioned above, scl-1 was the only aging regulatory gene we identified as strongly regulated (Table 3). SCL-1 has an SCP domain, which defines a family of putative signaling molecules with unknown biochemical function [28,29]. The scl-1 gene is required for extension of lifespan in a daf-2 mutant, and scl-1 expression is upregulated in long-lived genotypes [28]. scl-1 is strongly upregulated in our data as well, and we suggest scl-1 is part of the mechanism of lifespan extension in dauers. Several other genes in the scl-1 family are upregulated in old animals and in mature dauers, but not in our data [29,30,52].
Cytochrome p450s
Cytochrome p450s are versatile enzymes that oxygenate a wide variety of compounds [31]. These reactions are involved in protection from toxins, hormone biosynthesis and other functions. Cytochrome p450s are very prominent among our regulated genes (additional file 4: Table S4); 43 of 75 are regulated >1.8 fold (p < 0.05). One putative hormone biosynthetic cytochrome p450, daf-9, is known to function in dauer formation, and these others may also participate in hormone metabolism in dauer.
Hedgehog/Patched
In Drosophila and vertebrates, Patched and Smoothened form a receptor complex that binds Hedgehog ligands. C. elegans has two functional Patched orthologs and a family of proteins similar to Patched, called Patched-related. One, ptc-1, has an RNAi phenotype of defective cytokinesis in the germ line [32]. However, none of the patched/hedgehog family genes shown in Table 4 has an RNAi phenotype similar to ptc-1 [51,33]. A group of 10 C. elegans proteins have a carboxyl terminus that is related to the carboxyl terminus of Hedgehog; however, no protein with substantial similarity to the N-terminal signaling domain of Hedgehog has been found in C. elegans. Instead the C. elegans proteins have two novel families of N terminal sequences, called Wart and Ground domains [34]. Genes that encode both the N-terminal domain and the Hedgehog-related C terminal domain are called warthog and groundhog. Some proteins have only Wart or Ground domains. Finally, a large family of proteins has a domain that is similar to the Ground domain, and these are called Ground-like. Careful examination of the sequence indicates that Wart, Ground, and Ground-like domains and the N terminal domain of Hedgehog, despite low sequence identity, share motifs that indicate descent from a common ancestor [34].
Table 4 Regulatory genes regulated by TGFβ signaling.
Hedgehog and Patched
Gene Type of gene Fold regulation p value Mountain
grd-2 groundhog -2.4 0.0005 14
grd-7 ground domain only 3.8 0.0003 13
grd-6 ground domain only -3.1 0.0002 16
grd-14 ground domain only -8.9 0.0002 16
wrt-7 warthog 6.7 0.01 17
wrt-1 warthog -6.8 0.0001 14
wrt-4 warthog -2.9 0.0003 14
wrt-6 warthog -2.7 0.0005 14
wrt-8 warthog -3.8 0.0005 14
wrt-2 wart domain only -1.8 0.008 14
C56A3.1 ground-like 4.8 0.0001 17
K03B8.7 ground-like 18.9 0.0003 17
ZC487.4 ground-like 3.4 0.009 17
C24G6.7 ground-like -3.6 0.0006 14
F42C5.7 ground-like -2.4 0.0007 1
T02E9.2 ground-like -7.7 0.0001 14
Y75B8A.20 ground-like -13.3 0.0001 14
ZC168.5 ground-like -4.6 0.0001 16
ptc-3 patched -2.1 0.0001 1
ptr-6 patched related -2.3 0.0008 14
ptr-11 patched related -2.6 0.0002 1
ptr-16 patched related -2.7 0.01 14
ptr-18 patched related -3.3 0.0002 16
ptr-23 patched related -2.5 0.0003 6
npc-2 patched family -2.5 0.0004 16
Dauer growth arrest
Gene Type of gene Fold regulation p value
dbl-1 TGFβ ligand, regulates growth and body size -2.4 0.001
cdk-4 cyclin dependent kinase -1.9 0.006
nhr-73 member of a family of NHR genes expressed exclusively in lateral hypodermis (seam cells) -4.4 0.00002
nhr-74 member of a family of NHR genes expressed exclusively in lateral hypodermis (seam cells) -5.5 0.00005
nhr-25 similar to NHR in Drosophila ecdysone regulatory cascade, required for embryogenesis and molting -2.4 0.001
G-protein-coupled receptors and olfaction
gene type of gene fold regulation p value
srh-75 chemoreceptor 2.6 0.007
srh-195 chemoreceptor 2.6 0.0009
srj-32 chemoreceptor 5.8 0.002
sru-21 chemoreceptor 6.3 0.0007
32 genes chemoreceptor 1.8 to 6.3 0.05 or less
15 genes GPCR, not chemoreceptor type 1.8 to 3.6 0.05 or less
C30F12.6 thyrotropin-releasing hormone receptor ortholog 1.8 0.002
npp-10 GPCR, nucleoporin -1.8 0.001
6 genes chemoreceptors -1.8 to -3.8 0.05 or less
gpa-10 G protein alpha subunit 2.0 0.003
Y71H2B.7 G protein alpha subunit -1.8 0.0001
F45B8.2 regulator of G-protein signaling domain 2.4 0.03
gcy-22 receptor guanylate cyclase 2.7 0.03
gcy-31 soluble guanylate cyclase 1.8 0.01
gcy-34 soluble guanylate cyclase 1.8 0.03
tax-2 cyclic nucleotide gated channel beta subunit 3.0 0.02
lim-6 homeobox protein, functions to allow chemosensory neurons to sense different molecules 2.0 0.003
Notch pathway
gene type of gene fold regulation p value
W02C12.1 notch family 3.9 0.0007
F47C12.1 notch family 7.4 0.0003
apx-1 ligand for GLP-1, notch receptor 1.8 0.02
R03D7.5 shaggy/GSK3 kinase 2.2 0.002
lag-1 ortholog of CBF1 and Suppressor of Hairless 1.6 0.0003
Transcriptional regulators
gene type of gene fold regulation p value
lin-28 cold-shock domain 1.8 0.0001
lin-29 zinc finger transcription factor -1.9 0.0002
A complete list of significantly regulated regulatory genes can be found in additional file 4: Table S4.
We see abundant regulation of these gene families in our data (Table 4). Both upregulated and downregulated genes are observed, but downregulated genes are much more abundant.
Olfaction and other G-protein-coupled receptor signaling
Two of the three well-characterized cues for dauer entry are food and pheromone, which are sensed by chemosensory neurons. Chemosensation in C. elegans is mediated by G protein coupled receptors (GPCRs), which regulate cyclic GMP levels [35]. We see many upregulated G protein coupled receptors, accessory proteins, and other proteins related to olfaction, but few downregulated genes of these types (Table 4).
Cell cycle and growth arrest
Many cell types undergo cell cycle arrest in dauers. We see downregulation of cdk-4 (homologous to human Cdk-4/Cdk-6), which is well suited to control cell cycle arrest in dauers. The cyd-1 (cyclin D) and cdk-4 genes function in larval development to promote exit from the G1 stage of the cell cycle [36]. Animals with loss of function of either gene fail to carry out postembryonic divisions. We see a significant reduction in expression of cdk-4 (Table 4), which would be predicted to cause cells that would normally divide in reproductive L3 to arrest in dauers. However, loss of cdk-4 would not be expected to lead to an arrest of all growth in dauers. Some cells in C. elegans have endoreduplication without cell division, producing large hyperploid cells. DBL-1 is a ligand in a TGFβ pathway that controls larval growth [4,37]. dbl-1 mutants grow less than wild type, and have lesser DNA content in hyperploid hypodermal cells [38]. We see downregulation of dbl-1 in dauers (Table 4), which may block endoreduplication, and thereby arrest growth, in cell types such as intestine and hypodermis. Thus the microarray analysis suggests a model for the arrest of both cell division and endoreduplication.
Notch
Notch pathways have not been previously implicated in dauer formation, but we see strong evidence for altered activity of these pathways in dauer entry. Two of nine genes annotated as Notch receptors in C. elegans show strong upregulation in our data, as does one ligand, apx-1. We also see regulation of two genes that act downstream of the receptors: a shaggy/GSK3 kinase and lag-1, a transcription factor [20]. The regulation of these various Notch pathway components suggests that Notch signaling has an important unidentified function in dauer formation.
lin-28 and lin-29
These two genes are part of a signal transduction cascade that regulates timing of developmental events during larval development [39]. During larval growth, abundance of the cold shock domain containing LIN-28 protein is post transcriptionally downregulated. This downregulation allows the zinc-finger transcription factor LIN-29 to accumulate and promote events appropriate to the third larval stage. In our data, lin-28 is upregulated, and lin-29 downregulated (as expected, since lin-28 negatively regulates lin-29). This regulation is consistent with some old observations of the role of these genes in dauer formation [40]. lin-28 loss-of-function mutants enter dauer, but have defects in dauer morphogenesis. These defects are suppressed by lin-29 mutations. The regulation we see is consistent with the prediction that downregulation of lin-29 by lin-28 is required for normal dauer morphogenesis [40].
Discussion
Feedback model for crosstalk between TGFβ pathway and other dauer regulatory genes
We find that mutations in TGFβ signaling genes affects the expression of numerous genes that are known regulators of dauer formation. For example, loss of TGFβ signaling causes reduction of expression of daf-2, would be expected to reduce signaling through the insulin/IGF pathway. In addition, the TGFβ pathway mutants have increased expression of daf-12 and reduced expression of daf-9, a cytochrome p450 that is predicted to be involved in the biosynthesis of a daf-12 antagonist. All of these changes in gene expression would be predicted to promote dauer formation, and suggest that one way that the wild-type TGFβ pathway promotes reproductive growth is by feedback regulation of other dauer pathway genes.
We propose that this regulation is part of a feedback mechanism that operates at many levels to insure a "clean" dauer/non-dauer decision. Under conditions that induce dauer formation to different extents, different percentages of the population form dauers, but individual animals either undergo morphologically complete dauer, or have no dauer morphogenesis; therefore, a mechanism must exist to convert ambiguous signals into a clear decision. If reduced TGFβ signaling causes a reduction in insulin/IGF signaling and vice versa, then weak signals can be strengthened to make a clear, organism-wide decision. Negative regulation of daf-12 and upregulation of daf-9 by TGFβ and insulin/IGF signaling would likewise amplify signals. Interestingly, daf-2 and daf-12 both function as "nodes" for signal transduction in dauer entry. Many genes function in TGFβ and insulin/IGF pathways in dauer formation, but all of them except daf-2 show genetic redundancy [1,3,8,21-23,41]. Regulation of genes other than daf-2 would produce a weaker effect on dauer formation. Similarly, daf-12 is the gene that TGFβ and insulin/IGF signaling converge on, and regulation of daf-12 would be expected to have a uniquely powerful effect on dauer formation.
The feedback regulation to the insulin/IGF pathway explains published observations that link the TGFβ pathway to the insulin/IGF pathway. First, daf-16 mutants partially suppress daf-7 and other mutants in the TGFβ pathway [3]. We suggest that feedback from the TGFβ pathway to the insulin/IGF pathway is essential for complete dauer formation. In this model, loss of daf-16 function does not have a direct effect on TGFβ signaling, rather, daf-16 mutants suppress the inactivation of insulin/IGF signaling that occurs in the TGFβ mutants. Second, DAF-16 is localized to the nucleus when insulin/IGF signaling is weak, for example in daf-2 mutants of all ages. DAF-16 is localized to the nucleus in daf-7 mutants that are entering dauer, but not at other stages [20]. We suggest that this localization is a consequence of feedback regulation from the TGFβ pathway to the insulin/IGF pathway. Third, insulin/IGF pathway mutant adults have a variety of stress-resistance phenotypes, including slowed aging, which are shared with dauers, but not with TGFβ pathway mutant adults. We suggest that the stress resistance seen in daf-7 dauers is mostly or entirely caused by feedback regulation of the insulin/IGF pathway, and that this feedback occurs in daf-7 mutant dauers, but not at other stages.
Regulation of insulin-like ligands and novel genes with similarity to insulin/IGF receptors suggests functions for these genes in dauer formation
We find several insulin-related genes and genes with similarity to insulin receptor that are regulated by TGFβ signaling. Four insulin-like genes are downregulated; these are members of a subfamily in C. elegans that encodes several agonists of insulin/IGF signaling. Published data suggest that three of the downregulated insulin-like ligands act as DAF-2 (receptor kinase) agonists [7,25,26]. Thus, downregulation of these genes and perhaps the closely related gene ins-5 would be predicted to promote dauer entry, and may be part of the feedback mechanism proposed above. Published data suggest that ins-18, which is upregulated in our data, acts as a DAF-2 antagonist; [24] upregulation of this gene would be predicted to promote dauer entry, and this gene is another candidate for participating in the feedback mechanism proposed above. Upregulation of ins-33 and ins-35 suggests that these genes, like ins-18, encode receptor antagonists.
The ins-7 and ins-18 genes, but not the other insulin-like genes in Table 3, are regulated by insulin/IGF signaling in adults. Conversely, several insulin-like genes that are not regulated in dauer entry are regulated by insulin/IGF signaling in adults [26,42]. The gene programs induced by in dauers have similarities to those induced in long-lived adults; for example, stress resistance genes are common to both. However, many gene regulatory programs are unique to dauer, for example growth arrest. The different spectrum of insulin-like genes expressed in dauer entry versus adults may explain at least part of the difference in events regulated by insulin/IGF signaling. As with the insulin-like genes, we see both upregulation and downregulation of insulin-receptor like molecules; this regulation identifies these genes as good targets for studies to determine if this gene family is involved in insulin/IGF pathway signal transduction. These results suggest that diversity in insulin-related ligands, and perhaps in receptors, contributes the ability of insulin/IGF signaling to produce dramatically different phenotypes in dauers and adults
Many strongly regulated early dauer genes have DAF-16 regulatory sites
We observed that genes with putative daf-16 binding sites show a tendency to be upregulated in our data, with the exception of a small number of genes with daf-16 sites downstream of the transcription start. These results are important in several ways. Most significantly, our data identify genes that may be directly regulated by DAF-16 to control dauer formation or to provide dauer-specific functions such as protection from environmental insults. Second, genetics predicts that DAF-16 might upregulate genes that promote dauer entry or downregulate genes that promote reproductive growth. Our results suggest that DAF-16 can do both, but upregulated genes are much more prominent in our data set. Third, we see that the direction of regulation is correlated with the position of the DAF-16 site.
Our results show interesting similarities and differences with recent reports about DAF-16 target genes [53,54,42,43]. A significant number of genes that are upregulated in our data are also upregulated in these other experiments, but some genes are differently regulated. These papers all examined gene expression in adults, and in insulin/IGF pathway mutants, whereas our experiments have perturbed but not mutated insulin/IGF signaling (see below), so we would expect that only a subset of genes would be in common. The most dramatic difference between our data and these published reports is that we see evidence for upregulation of genes by DAF-16 sites upstream of the transcription start, but not downregulation, whereas the other reports see as many upregulated genes as downregulated genes. These differences suggest that the activity of DAF-16 is fundamentally different in dauers and adults, presumably because of availability of different cofactors.
Other regulatory genes
Cytochrome p450s
A very large number of cytochrome p450s show strong regulation in our data. One putative hormone biosynthetic cytochrome p450, daf-9, is described above, and these others may also participate in hormone metabolism. Other microarray experiments have identified cytochrome p450s as regulated genes in dauer or under the control of insulin/IGF signaling in C. elegans [25,42,52]. Because of the diversity of functions of cytochrome p450s, and especially because of the prominent roles of cytochrome p450 in stress resistance, sorting out the function of these genes in defense and hormone biosynthesis will require detailed functional analysis.
Hedgehog/Patched
The function of these genes is uncertain, as most have not been studied. Based on the expression pattern of several Ground and Wart domain proteins, Aspock et al.[34] suggested a function for these genes in hypodermis. A comparison of regulated Hog and Patched genes to groups ("mountains") of putatively coregulated genes in C. elegans [44] shows that three mountains are highly enriched for these genes. Mount 14 and Mount 16, are enriched for downregulated genes, and Mount 17 is enriched for upregulated genes (Table 4). These mountains are even more highly enriched for hog/patched genes that are strongly regulated in our experiments. These three mountains have less than 5% of the genes in C. elegans, but 48% of hog/patched genes and 80% of hog/patched genes that are strongly regulated in our data. All three mountains are also enriched for cuticular collagens; thus, we suggest that the hog and patched genes function in the production of the cuticle by the hypodermis. The fact that we see substantial numbers of both upregulated and downregulated genes supports this hypothesis. Dauers and non-dauers each form a cuticle, but with dramatically different structures [1]; therefore, we would expect to see the same types of genes in each program, just as we do when examining expression of cuticle structural genes such as collagens and cuticlins (Table 2 and data not shown).
Olfaction and other G-protein-coupled receptor signaling
We see regulation of many genes that are candidate olfactory and gustatory signal transduction molecules. This regulation may be involved in changes in response to odor and taste cues in dauers. We see many more upregulated genes in this class than downregulated genes. However, both dauer and non-dauer larvae are responsive to chemical cues, and published results of GPCRs with dauer-regulated changes in expression of reporters are not noticeably biased toward upregulation [45,46]. Perhaps anatomical changes can explain the bias toward upregulation. The key sensillum for regulation of dauer formation is the amphid. In dauers, the amphid pore is filled with an unknown material. In addition, ASI and ASG, which are members of the subset of amphid neurons with a known role in dauer formation, have shortened nerve endings that are more distant from the pore [1]. These changes insulate the neurons from the environment, to an extent. For example, lipophilic dyes such as DiI are taken up by amphid neurons in all stages of C. elegans development, except in dauers [45,46]. However, dauers respond readily to chemical cues that regulate dauer formation, which are thought to be sensed by amphid neurons. Perhaps genes that are required for chemosensation are more strongly induced in dauers in order to compensate for reduced signals due to the reduced exposure of the sensory endings.
Conclusions
In summary, perhaps the most striking conclusions from study are that, in TGFβ pathway mutants, we see altered expression of many genes that are known regulators of dauer formation, and that regulation of DAF-16 target genes depends on the location of the DAF-16 binding site. We see that loss of TGFβ signaling causes changes in gene expression that would be expected to reduce signaling through the insulin pathway. In addition, in TGFβ mutants, we see increased expression of daf-12 and reduced expression of daf-9, a cytochrome p450 that is predicted to be involved in the biosynthesis of a daf-12 antagonist. We also see changes in expression of several insulin-related genes and putative non-kinase insulin receptors. This result suggests that diversity in insulin-related ligands, and perhaps in receptors, contributes the ability of insulin signaling to produce dramatically different phenotypes in dauers and adults. We see evidence that DAF-16 binding sites upstream of the coding region can promote upregulation, but not downregulation of gene expression.
We identify many other regulatory genes that have altered expression in TGFβ mutants. We see several genes likely to function in Notch pathway signaling; this is the first implication of Notch signaling in dauer formation. We find that many divergent C. elegans homologs of hunchback and patched are regulated by TGFβ. Because these genes are coregulated with genes that encode structural components of the cuticle, we suggest that these genes regulate the production of the dramatically different cuticles of dauer and reproductive L3. We see coordinate regulation of genes that are predicted to arrest cell division and endoreduplication, which together would be expected to promote growth arrest. We identify many genes that are candidate hormone biosynthetic enzymes that might help transduce signals from the nervous system to other tissues. Figure 4 is a graphic summary of the main conclusions of this work, with new regulatory relationships suggested by our data shown in red.
Figure 4 Model for gene regulatory events under the control of TGFβ signaling. Transcriptional regulatory events suggested by expression data in this paper are indicated in red. The TGFβ pathway is shown in green; DAF-3 and DAF-5 form a transcription factor complex that function in neurons to control dauer entry [9]. DAF-3 and DAF-5 are shown regulating DAF-9 and DAF-12 indirectly because these genes are likely to be regulated in non-neuronal tissues. Insulin genes are shown as directly regulated by DAF-3 and DAF-5, but it is equally likely that these genes are regulated by feedback from the insulin pathway or by DAF-12.
Methods
RNA Isolation, cDNA synthesis, and microarray hybridization
Wild type is C. elegans variety Bristol, Strain N2; Daf-c genotypes are daf-7(e1372), daf-8(e1393), and daf-14(m77). Temperature-sensitive strains were maintained at 15°. Eggs were collected by hypochlorite treatment and incubated overnight at 15°. L1 larvae were grown on plates at 25°. During C. elegans larval development, each molt is accompanied by a brief period of lethargus when the animal stops pharyngeal pumping, and sheds its old cuticle. Cessation of pumping was scored according to [47] and used to judge the stage of worms for harvesting. For comparing daf-7 to N2, worms were harvested at early L3 stage for N2, when >95% of the worm had entered the L3 stage and daf-7 at early dauer stage when > 85% of the worm had passed the L2d to dauer molt. Synchronization of development in C. elegans populations is imperfect. For daf-8/N2 and daf-14/N2 experiments, a small sample plate was started 2 hours ahead of the harvest plates. The worms were harvested at late L2 stages for N2 when the worm on sample plate showed maximal cessation of pumping and the very first animals on the harvesting plates entered lethargus. daf-8 and daf-14 animals were harvested at late L2d stage when 50% worm on the sample plates stopped pumping and the very first animals on the harvesting plates entered lethargus. These animals were not perfectly synchronous, but our monitoring of pumping suggests that the vast majority of worms fall within a four-hour developmental window. Worms were harvested quickly to avoid changes in mRNA levels caused by the collection procedure; no more than 15 minutes elapsed between the start of harvest and addition of Trizol. Each experiment compared RNA samples from the wild-type N2 to Daf-c genotype worms. For each Daf-c genotype, we did three or four independent experiments. RNA was prepared as described previously [48]. Labeled cDNA probe for DNA microarray hybridization was made from 5 μg of poly (A)+ as described [49]. The two cDNA probes were simultaneously hybridized to a single DNA microarray.
Imaging and data analysis
Arrays were scanned using Axon scanner as described previously [49], collecting measurements for Cy5 and Cy3 separately. The average level of regulation for each gene for each genotype was calculated as the mean of the Cy5/Cy3 ratios. Genes with significant regulation were identified by using the standard deviation from the ten experiments presented in this paper ("local standard deviation") and the standard deviation derived from a several hundred microarray experiments of various types ("global standard deviation"), as described [50]. In most cases, genes were considered significantly regulated only if they were significant in a Student's t test using both measurements of standard deviation. However, for a few hundred genes, global standard deviation was unavailable, and significance was measured using the local standard deviation. Our processed, annotated data are available in additional file 1: Table S1. Raw data compliant with the "Minimum information about a microarray experiment" (MIAME) standard is available at: .
Analysis of duplicated and reannotated spots
All spots on the array were generated by PCR of genomic DNA, as described [49]. Some PCR reactions were spotted in two separate locations on the array. In this case, both data points were used to calculate the average regulation. The PCR primers were designed a few years ago, and in some cases, EST data or other information has revealed that predictions upon which the primers were based were in error [51]. Three types of error account for the vast majority: 1) PCR products that are no longer believed to amplify sequence from a gene. These spots are excluded from the analysis. 2) Cases in which two PCR products that were thought to represent two different genes actually represent different parts of a single gene. In these cases, each spot was initially analyzed independently, but, when we count the number of genes with a particular property, the genes are not double counted. 3) Cases in which a single PCR product is now believed to overlap two genes. Data from these spots were excluded from the analysis. Fortunately, this type of error was uncommon.
Cross hybridization
Many genes in C. elegans have enough mRNA sequence similarity that our labeled cDNA probes might hybridize to homologous genes, obscuring true patterns of gene regulation. We examined our data and published data to evaluate how widespread this problem is. As a crude measure, we compared pairs of homologous genes and asked whether the genes ever show opposite regulation. Our expectation is that, if cross-hybridization is strong, the two genes will show similar regulation. That is, if one member of a pair shows upregulation in dauers and the other member shows down-regulation, then cross-hybridization is not at a high enough level to obscure true regulation. Of course, the converse is not necessarily true: if two homologous genes show similar regulation, that does not imply that cross hybridization is occurring.
We examined 8 groups of genes using blast to identify the most similar genes. In this way, each of the eight genes was matched with a small group of similar genes (6 were collagens, one was cuticlin, and one was superoxide dismutase). In seven groups, the match was approximately 80% identity over 200–700 bp, and several groups had short stretches (<100 bp) of 90% identical sequence. In each group, significantly different regulation was seen in the data collected for this paper. The last group had matches of >90% over 500 bases or more, and this group showed strong correlation in our experiments.
This analysis defines the limits of specificity. For genes with identities of <80%, and genes with short stretches of 90% identity, cross hybridization is not strong enough to obscure differences between genes. When similarity goes above 90% for more than 100 bp, genes show strongly correlated expression, and these results should be interpreted with caution. Our examination of the collagen, cytochrome p450, glutathione S-transferase, heat shock, and peroxidase, insulin ligand, and insulin receptor families of C. elegans indicates that no more than 10% of genes in families have similarity great enough to be an issue. Of course, this number applies to genes in families, and the bulk of C. elegans genes will have less similarity.
Validation of the DNA microarray results
We examined our data to see if it was consistent with published data on dauer gene regulation obtained by Northern blot and reporter gene constructs. The term "dauer-regulated" has been used in many published studies to describe results from experiments that are only superficially similar. It would be inappropriate and misleading to compare our data to most published data on "dauer-regulated" genes. For example, Wang, et al. [52] identified dauer-regulated genes, but they were examining wild-type animals over time (rather than comparing mutants to wild type) and studying the process of exiting dauer (these animals were several days older than the animals we were studying. If we were to use this data to validate our data, we would be making the assumption that the set of genes that are regulated during dauer entry are similar to the set of genes that are regulated in dauer exit. There is no data to support this assumption. Comparison of our data set to the Wang et al. [52] would be appropriate to identify interesting similarities and differences between dauer entry and exit, but to use one data set to validate the other would be an error.
Most experiments that we consider inappropriate for use in validation have one or both of the following characteristics:
1) In our experiments and published experiments summarized in Table 2, animals from which RNA is collected are of similar age, either dauers near the L2d/dauer molt or non-dauers near the L2/L3 molt. Many experiments compare dauer RNA to that of mixed stage worms or adult worms [53-55]. which is not useful for our goal of comparing the L3 to the dauer alternative. For example, using mixed stage RNA, a gene that is expressed at a high level in adults but is otherwise off, would be expected to show expression in a mixed-stage RNA prep, but not in dauer RNA. Yet a gene of this sort does not have a meaningful relationship to the dauer/non-dauer decision or dauer morphogenesis. Similarly, a gene that is expressed equally in dauers and in non-dauer L3 animals would be diluted by RNA from other stages, and therefore, less abundant, in the mixed stage RNA than in the dauer RNA, but the gene is not in fact more abundant in dauers than the non-dauer alternative.
2) Many studies use dauers ranging from about 15 hours to 7 days past the L2d/dauer molt [52,54-59]. Some of these studies also compare starvation-induced dauers to well-fed animals. These studies are often aimed toward understanding issues related to survival of dauers and aging. We would not expect that these studies would necessarily find the same genes to be regulated, because of differences in timing and differences in physiology due to starvation. In particular, we are looking at the very beginning of dauer morphogenesis, so would expect to see genes that are necessary for dauer formation, while the other studies are looking after the completion of dauer morphogenesis, so would expect to see genes necessary for dauer maintenance and survival.
We identified the small subset of experiments that are appropriate for validation of our data set, by identifying experiments that: compare animals close to the L2/L3 and L2d/dauer molts. Table 2 shows that our data agrees very well with published experiments of similar design. The first five genes show strong regulation in the published experiments, and 7–8-fold regulation in our experiments. The next two genes, rnr-1, and col-2, are also regulated similarly in our experiment and published data, although the magnitude and statistical significance are not as great as for the first 5 genes. The final gene, col-40, shows strong upregulation at the L2d-dauer molt in published experiments, but in our data does not show regulation. One possible explanation for this discrepancy is that this gene has been shown to have very rapid induction and repression near the time of molting [60,61]. Thus, seeing regulation of col-40 may depend on precisely when the RNA is collected. This gene showed very high variation in mutant/wildtype ratio from experiment to experiment, higher than 99% of the genes on the array. This unusual variation is consistent with the idea that timing is critical for measuring regulation of this gene. A second possible explanation is that the regulation of these genes is obscured by cross-hybridization to other collagen genes; however, the similarity of col-2 and col-40 to other genes at the level of coding DNA is low enough that we do not expect cross-hybridization to be a serious problem (see previous section of Methods). Overall, seven of eight genes show strong correlation with published data.
Identification of DAF-3 and DAF-16 binding sites
Binding sites for transcription factors were identified using RSA tools [62,63].
Authors's contributions
TL participated in the design of the study, performed wet lab experiments, analyzed data, and co-wrote the manuscript. KKZ participated in the growth and collection of samples for RNA. GIP conceived of the study, participated in the design and data analysis, and co-wrote the manuscript. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Full data set. Table S1 may be found online as an Excel file at: Please feel free to use any annotation in these tables, provided that the original source of the data is cited, and this collection of annotations is cited. Table S1 has the data for all of the genes on the microarray. Raw data in unprocessed, MIAME compliant format is available at: . Column A, "SMD gene name" is the name given to the probe on the microarray. The probe is a PCR product from a pair of primers made to amplify the ORF named in this column (Reinke, V., Smith, H. E., Nance, J., Wang, J., Van Doren, C., Begley, R., Jones, S. J. M., Davis, E., Scherer, S., Ward, S., & Kim, S. K. (2000). Mol. Cell 6, 605–616). Many of these ORF predictions have changed, and the current match is in column B. Column B, "wormbase gene name" gives the current gene prediction that is complementary to the probe on the array. Columns C-K are annotations downloaded from Wormbase in 2003, from April to June. The column headings are defined in Wormbase. Columns L and M are optimal DAF-16 binding sites, which are the sequence TTGTTTAC. Negative numbers are sites upstream of the start of translation, and positive numbers are downstream of the stop codon. These sites were predicted in Fall 2002 using data and software from (van Helden, J., André, B., & Collado-Vides, J. (2000). Yeast 16,177–187.). All sites within 2000 bp upstream and 300 bp downstream are shown, except for a few (<2%) that we were not able to match because of different annotation in our database and the rsat database. Columns N-O are our annotation of function based on sequence similarity, annotation from wormbase, and published reports. For the following groups, we have annotated all genes in the group, to the best of our knowledge: G protein coupled receptors, glutathione S transferases, cytochrome p450s, heat shock proteins, peroxidases, UGTs, epoxide hydrolases, collagens, cuticlins, NRF6 related, scl-1 familly (aka CRISP family), signaling proteins, and transcription factors. For the following groups, we have annotated only a subset of genes in the group: amine oxidases, ribosomal proteins, amino acid catabolism, and lipid metabolism. Column P, "mountains", lists groups of putatively co-regulated genes from Kim, S. K., Lund, J., Kiraly, M., Duke, K., Jiang, M., Stuart, J. M., Eizinger, A., Wylie, B. N., & Davidson, G. S. (2001). Science 293, 2087–2092. Column Q and R list the average ratio of signal from daf-c genotypes to wild-type, using all experiments. Column Q is the average expressed as a base 2 logarithm (>0 means the expression was higher in daf-c, <0 is higher in N2, and Column R is the average expressed as a fold change (for both columns, a positive number means the expression was higher in daf-c, a negative number means the expression was higher in N2). Column S is the p value for the values in column Q and R, using a t test, asking the question, given the standard deviation for the data, is the value significantly different from a ratio of 1 (or 0 for the base 2 log). For these calculations we used the local standard deviation and the global standard deviation as described in Jiang, M., Ryu, J., Kiraly, M., Duke, K., Reinke, V., & Kim, S. K. (2001). Proc. Natl. Acad. Sci. 98, 218–223. Column T is the number of successful experiments for each spot on the array. The numbers vary because the data for a particular spot may or may not be of acceptable quality for a given experiment. Some genes have a number greater than 10 (the total number of independent experiments) because the same PCR product was put on the array in two different locations. Columns U thru BH are the data for each spot for each experiment. The column labeled "CH1D_MEAN" is the data for wild-type sample, the column labeled CH2D_MEAN is the data for the daf-c mutant sample, the column labeled CORR is the correlation coefficient for the average ratio of channel 1 to channel 2 calculated pixel by pixel, and the column labeled Flag indicates the data quality. Any value other than 0 indicates that the data had problems and was not used for analysis. Columns BL to CG give the data broken down by genotype (for each of the three daf-c genotypes used in this study). For each genotype, the first three or four columns give the base 2 log of the ratio of channel 2 (from daf-c genotype) to channel 1 (from wild type) for each experiment. Blank cells indicate bad data, not used in the analysis. The five digit number in the headings of these colums refer to the experiment ID used to catalog data at the Stanford Microarray Database. The next column gives the average ratio, the next column the standard deviation and the next gives the number of successful experiments, and the next the p value, asking the question, given the standard deviation for the data, is the value significantly different from a ratio of 1 (or 0 for the base 2 log).
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Additional File 2
Strongly regulated genes. Table S2 may be found online at: Table S2 has data identical to table 1, except that only genes for which the regulation was greater than 2.145 fold, with a p value less than 0.01 are shown.
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Additional File 3
Regulated genes with putative DAF-16 binding sites. Table S3 can be found online at: All data in this table are taken from Table S1. The first 15 rows have data for downregulated genes that have a daf-16 binding site downstream of the stop codon. The next 134 rows have data for genes that are upregulated and have a daf-16 binding site upstream of the start codon. Column A, "SMD gene name" is the name given to the probe on the microarray in the Stanford Microarray Database. The probe is a PCR product from a pair of primers made to amplify the ORF named in this column (Reinke, V., Smith, H. E., Nance, J., Wang, J., Van Doren, C., Begley, R., Jones, S. J. M., Davis, E., Scherer, S., Ward, S., & Kim, S. K. (2000). Mol. Cell 6, 605–616). Many of these ORF predictions have changed, and the current match is in column B. Column B, "wormbase gene name" gives the current gene prediction that is complementary to the probe on the array. Columns C-G are annotations downloaded from Wormbase in 2003, from April to June. The column headings are defined in Wormbase. Columns H-J are optimal DAF-16 binding sites, which are the sequence TTGTTTAC. Negative numbers are sites upstream of the start of translation, and positive numbers are downstream of the stop codon. These sites were predicted in Fall 2002 using data and software from (van Helden, J., André, B., & Collado-Vides, J. (2000). Yeast 16,177–187.). All sites within 2000 bp upstream and 300 bp downstream are shown, except for a few (<2%) that we were not able to match because of different annotation in our database and the rsat database. Column K is our annotation of function based on sequence similarity, annotation from wormbase, and published reports. Our annotation of the following gene types is complete, to the best of our knowledge: G protein coupled receptors, glutathione S transferases, cytochrome p450s, heat shock proteins, peroxidases, UGTs, epoxide hydrolases, collagens, cuticlins, NRF6 related, scl-1 familly (aka CRISP family), signaling proteins, and transcription factors. The following groups are incompletely annotated: amine oxidases, ribosomal proteins, amino acid catabolism, and lipid metabolism. Column L, "mountains", lists groups of putatively co-regulated genes from Kim, S. K., Lund, J., Kiraly, M., Duke, K., Jiang, M., Stuart, J. M., Eizinger, A., Wylie, B. N., & Davidson, G. S. (2001). Science 293, 2087–2092. Column M lists the average ratio of signal from daf-c genotypes to wild-type, using all experiments. expressed as a fold change (a positive number means the expression was higher in daf-c, a negative number means the expression was higher in N2). Column N is the p value for the values in column M, using a t test, asking the question, given the standard deviation for the data, is the value significantly different from a ratio of 1 (or 0 for the base 2 log). For these calculations we used the local standard deviation and the global standard deviation as described in Jiang, M., Ryu, J., Kiraly, M., Duke, K., Reinke, V., & Kim, S. K. (2001). Proc. Natl. Acad. Sci. 98, 218–223.
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Additional File 4
Regulated regulatory genes. This table lists all transcription factors, signaling molecules, possible hormone biosynthetic enzymes, and other regulatory genes that are significantly regulated in our data.
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Acknowledgements
We thank S. Kim and J. Wang for their generosity in performing the microarray hybridizations for this work, and H. Robertson for sharing unpublished categorization of chemoreceptor genes. We thank Kamila Sekiewicz for assistance with annotation and Monica Driscoll and Ken Irvine for comments on the manuscript. This work was supported by a grant from the National Institute of General Medical Science.
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| 15380030 | PMC524168 | CC BY | 2021-01-04 16:30:29 | no | BMC Dev Biol. 2004 Sep 20; 4:11 | utf-8 | BMC Dev Biol | 2,004 | 10.1186/1471-213X-4-11 | oa_comm |
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BMC Evol BiolBMC Evolutionary Biology1471-2148BioMed Central London 1471-2148-4-361545652210.1186/1471-2148-4-36Research ArticleIs autoinducer-2 a universal signal for interspecies communication: a comparative genomic and phylogenetic analysis of the synthesis and signal transduction pathways Sun Jibin 1jsu@gbf.deDaniel Rolf 2rdaniel@gwdg.deWagner-Döbler Irene 3iwd@gbf.deZeng An-Ping 1aze@gbf.de1 Department of Genome Analysis, GBF – German Research Center for Biotechnology, Braunschweig, Germany2 Institute for Microbiology and Genetics, University of Göttingen, Göttingen, Germany3 Research Group Microbial Communication, GBF – German Research Center for Biotechnology, Braunschweig, Germany2004 29 9 2004 4 36 36 12 9 2004 29 9 2004 Copyright © 2004 Sun et al; licensee BioMed Central Ltd.2004Sun 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
Quorum sensing is a process of bacterial cell-to-cell communication involving the production and detection of extracellular signaling molecules called autoinducers. Recently, it has been proposed that autoinducer-2 (AI-2), a furanosyl borate diester derived from the recycling of S-adenosyl-homocysteine (SAH) to homocysteine, serves as a universal signal for interspecies communication.
Results
In this study, 138 completed genomes were examined for the genes involved in the synthesis and detection of AI-2. Except for some symbionts and parasites, all organisms have a pathway to recycle SAH, either using a two-step enzymatic conversion by the Pfs and LuxS enzymes or a one-step conversion using SAH-hydrolase (SahH). 51 organisms including most Gamma-, Beta-, and Epsilonproteobacteria, and Firmicutes possess the Pfs-LuxS pathway, while Archaea, Eukarya, Alphaproteobacteria, Actinobacteria and Cyanobacteria prefer the SahH pathway. In all 138 organisms, only the three Vibrio strains had strong, bidirectional matches to the periplasmic AI-2 binding protein LuxP and the central signal relay protein LuxU. The initial two-component sensor kinase protein LuxQ, and the terminal response regulator luxO are found in most Proteobacteria, as well as in some Firmicutes, often in several copies.
Conclusions
The genomic analysis indicates that the LuxS enzyme required for AI-2 synthesis is widespread in bacteria, while the periplasmic binding protein LuxP is only present in Vibrio strains. Thus, other organisms may either use components different from the AI-2 signal transduction system of Vibrio strains to sense the signal of AI-2, or they do not have such a quorum sensing system at all.
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Background
Quorum sensing through small signal molecules called autoinducers is an important process for the regulation of population density dependent cellular processes in bacteria, including the production of antibiotics and virulence factors, conjugation, transformation, swarming behaviour and biofilm formation [1,2]. Recently it was discovered that two different density dependent signal transduction cascades are present in Vibrio which converge to trigger luminescence in V. harveyi [3] and expression of virulence factors in V. cholerae [4,5]. Two chemically different autoinducers are involved in this regulation. While autoinducer-1 is an acylated homoserine lactone (AHL) (N-butanoyl-homoserine lactone) in V. harveyi, the structure of autoinducer-2 (AI-2) has been determined in a complex with the sensor protein LuxP [6] and shown to be a furanosyl-borate-diester. It is synthesized in two enzymatic steps (by the Pfs enzyme and the LuxS enzyme) from S-adenosyl-homocysteine (SAH), resulting in 4,5-dihydroxy 2,3 pentanedione (DPD) which undergoes spontaneous cyclization and is then complexed with borate to form AI-2 (Fig. 1).
Figure 1 Enzymes involved in the detoxification of SAH and synthesis of AI-2 and AI-3. Abbreviations: SAM, S-adenosyl-methionine; SAH, S-adenosyl-homocysteine; SRH, S-ribosyl-homocysteine; DPD, 4,5-dihydroxyl-2,3-pentanedione; Pro-AI-2, Ai-2 precursor; AI-2, autoinducer 2; AI-3, autoinducer 3. The numbers in brackets show the numbers of analyzed organisms that have that enzyme (reciprocal best hit).
The LuxS enzyme responsible for the last enzymatic step of AI-2 synthesis is present in a wide phylogenetic range of bacterial genera and AI-2 produced by heterologous organisms triggers luminescence in the V. harveyi reporter strains [7,8]. Thus it was hypothesized that AI-2 might be a universal signal molecule. In addition, a large fraction of E. coli genes is transcribed differently with culture supernatants containing AI-2 compared to culture supernatants from luxS- mutants [9,10]. Recently it could be shown that the expression of important genes of the virulence islands in E. coli serotype O157:H7 (EHEC) is controlled by a LuxS dependent molecule, which was later shown to be not AI-2 but AI-3 whose structure is not known yet and which does not activate the V. harveyi bioreporter strain [11]. It is also produced by the gut microflora. Moreover, the host hormone epinephrine activates virulence gene transcription through the same signalling pathway as AI-3, resulting in cross-talk between host and bacterium [11].
Knock-out mutants for luxS have been investigated for modifications of infectious phenotypes in some of the currently sequenced pathogens. In V. cholerae [4,5], Streptococcus pyogenes [12,13], Streptococcus pneumoniae [14], Neisseeria meningitidis [15] and Clostridiuim perfringens [16] luxS- mutants showed severe defects in the expression of virulence factors. In some other pathogens luxS- mutants showed none or very subtle changes in virulence related traits (e.g. Borrelia burgdorferi, [17]; Porphyromonas gingivalis, [18]; Shigella flexneri, [19]). In Salmonella typhimurium AI-2 controls the expression of an ABC transporter which is responsible for the back transport of AI-2 into the cell, presumably to conserve metabolic energy or to interfere with quorum sensing mechanisms of the gut microflora [20].
The signal detection system for AI-2 from Vibrio strains is well experimentally proven [4] (Fig. 2). In V. harveyi it is composed of a soluble periplasmic AI-2 binding protein LuxP, and a phosphorelay cascade resulting in density dependent activation of the lux operon (Fig. 2). The first step in this cascade is formed by the hybrid sensor kinase LuxQ, which contains both a N-terminal periplasmic membrane bound sensory domain and a C-terminal intracellular response regulator domain [21]. The signal is then transferred to the phosphorelay protein LuxU [22]. This phosphotransferase receives phosphorylation signals both from LuxQ and from LuxN, the parallel, homoserine lactone based quorum sensing circuit of Vibrio strains. It phosporylates the final response regulator, LuxO, which belongs to a large, highly conserved family of sigma54 dependent transcriptional regulators. LuxO has three conserved domains, e.g. the response regulator domain, the sigma54 activation domain, and a HTH (helix turn helix) motif for direct DNA binding [23]. At low cell density and in the absence of autoinducers, LuxQ autophosphorylates. The signal is transferred from its conserved aspartate residue to the histidine residue of LuxU, which phorphorylates the aspartate residue of the response regulator LuxO. In its phosphorylated (activated) form, and together with sigma54, LuxO activates the expression of small regulatory RNAs (sRNAs). The complexes of these sRNAs and the sRNA chaperone protein Hfq destabilize the mRNA of the quorum-sensing master regulator LuxR, resulting in the indirect repression of the lux operon transcription [24]. At high cell density, AI-2 present in the periplasmic space binds to the protein LuxP, which converts LuxQ from kinase to phosphatase. This reverses the flow of phosphate through the pathway, from LuxO to LuxU and then to LuxQ. In this case, sRNAs are not expressed. Without destabilization of the sRNA-Hfq complex, LuxR is translated and consequentially the transcription of the Lux operon is switched on.
Figure 2 Genes involved in the signalling cascade for detection of AI-2 in Vibrio. Abbreviations: OM outer membrane; IM inner membrane; H histidine; D aspartate; HTH helix turn helix motif; sRNA small regulatory RNAs; Hfq chaperone protein. Numbers indicate analyzed organisms that have an orthologous gene for that protein using a reciprocal best hit search strategy, numbers in brackets indicate the number of analysed organisms having a similar gene based on standard blast search.
The LuxS enzyme responsible for the last enzymatic step of AI-2 synthesis has at the same time an important function in the activated methyl cycle of the cell, since it is necessary for recycling of the toxic intermediate SAH [25]. Two pathways are known to be able to degrade and recycle SAH (Fig. 1). One pathway is composed of two successive enzymatic reactions catalysed by LuxS and Pfs. This pathway produces adenine, homocysteine and DPD which can be complexed with borate and converted to AI-2 by two non-enzymatic spontaneous reactions. The other pathway contains only one enzymatic step catalysed by SAH hydrolase (SahH) and produces adenosine and homocysteine. There is no AI-2 production through this pathway. Homocysteine can be further recycled to methionine by MetE or MetH and then activated to SAM by SAM synthetase.
Despite intensive research on AI-2 in the last years the available data do in many cases not allow to clearly separate the metabolic function of the LuxS gene product from its possible signalling activity in interspecies communication. Winzer and his colleagues [25,26] analysed the available genomes (by April 2003) for the presence of LuxS and related genes and critically reviewed the available experimental data with respect to the potential signalling function of AI-2. The emphases of these studies were on the genes pfs, luxS and sahH. A large-scale and more detailed comparative genomic analysis of other genes involved in the AI-2 related metabolic and signal transduction pathways is missing. Therefore, we present here a comprehensive investigation of the phylogenetic distribution of all the genes involved in the synthesis of AI-2, the detoxification of SAH, as well as the signalling cascade necessary for the detection of AI-2 by analysing 138 completely sequenced genomes from the KEGG database [42] and the EMBL database [43]. While LuxS is the enzyme necessary for AI-2 production, it is not required for AI-2 signal transduction. Theoretically, an organism may not be able to produce AI-2 but have the ability to detect the presence of coexisting or competing bacterial species by sensing the environmental concentration of AI-2. This is the case in Pseudomonas aeruginosa [27]. Therefore, not only the LuxS-containing organisms but also all other sequenced genomes have been analysed for the existence of the AI-2 signal transduction cascade.
Results
Metabolic pathways involved in SAH degradation and recycling
SahH and Pfs/LuxS are alternative pathways for recycling of SAH
The distribution of the orthologs of the proteins involved in AI-2 production, SAH degradation and recycling, and AI-2 signalling is listed in Supplementary Table s1 and s2 [additional file 1 and 2]. As shown in Supplementary Table s1 [additional file 1], 80% of the 138 completely sequenced genomes have at least one pathway to degrade SAH. 51 organisms have only the two-step pathway using Pfs and LuxS, while 60 have only the one-step pathway using SahH (Fig. 1). The remaining one-fifth having neither pathway mainly belong to symbionts, intracellular parasites, Mollicutes or Chlamydiates. They probably rely on their host to recycle the toxic intermediate. With the exception of Bifidobacterium longum NCCC2705 and Escherichia blattae, no organism has both the sahH and luxS gene. Interestingly, each organism has only a single copy of the highly conserved luxS gene. These results are consistent with the studies of Winzer and his colleagues [26].
Phylogenetic distribution of SAH detoxification pathways
The presence of either a one-step or a two-step detoxification pathway for SAH follows a phylogenetic pattern. Eukarya and Archaea use exclusively the one-step pathway to degrade SAH, while Bacteria use either the one-step or the two-step pathway depending on their phylogenetic position (Fig. 3). The two-step Pfs/LuxS pathway is consistenly present in all Firmicutes and absent in Actinobacteria (with the exception of Bifidobacterium longum). Within the Proteobacteria, Alphaproteobacteria clearly use the one-step detoxification pathway, while there is a dividing line going across the Betaproteobacteria and the Gammaproteobacteria. For the Betaproteobacteria, the pathogen Neisseria meningitidis uses the two step pathway, while Ralstonia solanacearum and Nitrosomonas europaea use the one-step pathway. With the exception of the Xanthomonadales and Pseudomonadales, all Gammaproteobacteria presently sequenced use the Pfs/LuxS pathway.
Figure 3 Distribution of one-step (red) and two-step (green) detoxification pathways of SAH within the three domains of life. All sequences shown in the tree could be found in the ARB database (ssujun02.arb), hence were already aligned, and for the desired presentation were all transferred to the rudimentary tree (tree_demo) by the ARB function "quick add by parsimony". After marking all species (sequences) of interest only these were kept by removing all unmarked species with an integrated ARB function. This leaves the original topology of the tree intact while eliminating all species and branches which are unnecessary for the demonstration of the phylogenetic distribution of sequences of prime interest. Phyla are numbered from 1 to 13. 1 Gammaproteobacteria; 2 Betaproteobacteria; 3 Alphaproteobacteria; 4 Epsilonproteobacteria; 5 Spirochaetes; 6 Chlorobia; 7 Bacteroidetes; 8 Cyanobacteria; 9 Actinobacteria; 10 Firmicutes; 11 Deinococcus-Thermus; 12 Thermotogae; 13 Aquificae. Numbers in brackets indicate sequenced genomes analysed. Shaded phyla are mixed, having organisms with the SahH pathway and organisms with the Pfs/LuxS pathway. Boxed strains have both LuxS and SahH.
Only one or two representatives have been sequenced from other microbial phyla, so it is premature to generalize these findings. However, presently the Pfs/LuxS pathway has been found in Borrelia burgdorferi (Spirochaetes) and Deinococcus radiodurans R1 (Deinococcus-Thermus), while the organisms from other sequenced phyla (Chlorobia, Bacteroidetes, Aquificae, Thermotogae) use the SahH pathway. The second sequenced strain from the phylum Spirochates, Leptospira interrogans, uses the SahH pathway. These results are also consistent with the analysis of Winzer et al. [26].
Exploring the ERGO database [44] containing approximately 400 genomes, of which appr. 200 are microbial genomes, resulted in a consistent conclusion on the distribution pattern of SAH hydrolase or Pfs/LuxS degradation pathways (data not shown).
Phylogeny of LuxS
The sequences of LuxS orthologs were aligned and a phylogenetic tree was built from the alignment. There are clearly three bigger branches in the phylogenetic tree (Fig. 4). The first contains most Gram negatives, i.e. Gamma- and Betaproteobacteria. The second brach is comprised mainly of Lactobacillales, but contains some other groups as well. Interestingly, the LuxS ortholog from Bifidobacterium longum, which is the only species of Actinobacteria having LuxS, and which at the same time has the SahH pathway for recycling of SAH, is most closely related to that of the phylogenetically only distantly related Lactobacillus plantarum. Both bacteria share the same habitat, being commensals of the healthy human gut. There would have been ample opportunities for B. longum to acquire luxS by horizontal gene transfer from Lactobacillus. The Lactobacillus branch also contains a small subcluster with luxS from Borrelia burgdorferi, a Spirochete, which is most similar to luxS from Clostridium acetobutylicum. The third branch is dominated by Bacillales. Interestingly, it also includes two of three sequenced Epsilonproteobacteria, namely two strains of Helicobacter pylori. However, the closely related Campylobacter jejuni forms a separate, deeply branching lineage. These data confirm those of Lerat & Moran [28]. Small differences can be attributed to the treeing methods used, e.g. the position of Campylobacter jejuni luxS and the fact that γ-Proteobacterial LuxS genes were monophyletic in our analysis, but comprised two different branches in their tree. In addition, we included luxS sequences from Enterococcus faecalis and Deinococcus radiodurans. The robustness of the tree topology is caused by the high degree of conservation of luxS and strongly supports the resulting conclusions regarding gene transfer for some species.
Figure 4 Phylogenetic tree of LuxS proteins from the completely sequenced genomes (138; July 2003) in the KEGG genome database. The tree was constructed using the neighbour-joining (NJ) method after alignment of orthologous genes by means of Vector NTI Advance (InforMax, United States).
Transformation of homocysteine to methionine
To complete the metabolic cycle of SAH, the common product homocysteine of the two degradative pathways is converted to methionine by a homocysteine methyltransferase (MetE, 5-methyltetrahydropteroyltriglutamate–homocysteine methyltransferase or MetH, 5-methyltetrahydrofolate–homocysteine methyltransferase), then to SAM by SAM synthetase (MetK). SAH is one of the products of SAM-dependent transmethylases. The distribution of MetE, MetH and MetK was analysed in a similar way to LuxS (Supplementary Table s1 [additional file 1]). As a general rule, bacteria that have one of the two pathways to degrade SAH are also able to recycle homocysteine to methionine and to synthesize SAM. This conclusion again supports the importance of the degradation and recycling of SAH. As the only few exceptions, the strains Helicobacter pylori, Streptococcus pyogenes and Enterococcus faecalis lack MetE/MetH but have MetK. The overview of such enzymes in Eukarya and Archaea is more complicated probably because of their incomplete identification by searching homologues to proteins with known functions or because of the existence of other unknown pathways or enzymes in these organisms.
Signal transduction pathway of AI-2
Reciprocal best hit strategy
The reciprocal best-hit orthologs of the signal transduction cascade (LuxP, LuxQ, LuxU and LuxO) from Vibrio for the sequenced genomes are listed in Supplementary Table s1 and s2 [additional file 1 and 2]. Unlike the broad distribution of LuxS, the orthologs of the AI-2 binding protein LuxP and the regulator LuxU were found exclusively in Vibrio strains. And only Vibrio strains have both the orthologs for the hybrid sensor kinase LuxQ and the two component response regulator LuxO. In addition, five other orthologs of LuxQ were found using the reciprocal best hit strategy, namely in Brucella melitensis, Brucella suis, Streptococcus agalactiae (two different strains), and in Methanosarcina mazei. For the two component response regulator LuxO, four additional orthologs were found in Bradyrhizobium japonicum, Listeria monocytogenes, Lactobacillus plantarum and Thermotoga maritima. Given the complexity of the proteins involved and the limited number of sequences presently available, it is not possible to draw consistent conclusions from this finding at this point.
Unidirectional best hit search
However, if not the reciprocal best-hit strategy but the uni-directional best-hit search was applied, 28 organisms were found to have homologues to LuxP. The LuxP homologues of 25 of these organisms were more similar to D-ribose binding proteins of Vibrio strains than to the AI-2 binding protein LuxP. We reconstructed the 3D models of LuxP proteins from different Vibrio strains by applying the method of SwissModel. All these LuxP proteins have similar 3D structures as expected from the high similarity of their sequences (data not shown). The three-dimensional structure of LuxP is very similar to that of D-ribose-binding proteins [6]. Because of the structural similarity between the ligands (AI-2 and D-ribose), and the structural similarity between the binding proteins, the question has to remain open whether the detected LuxP-homologues in the non-Vibrio organisms are actually functional AI-2 binding proteins.
104 organisms were found to have homologues both for the hybrid sensor kinase LuxQ, and the two-component response regulator LuxO. Most organisms had several homologous genes for these two-component systems, so that altogether 315 genes were found for LuxQ and 340 for LuxO. This was caused by the fact that several domains of the sensor and regulator components of signal transduction systems are highly conserved. We were not able to identify the unique binding domain from the sensor protein LuxQ specific for the detection of the AI-2 signal.
Discussion
Reciprocal or unidirectional best hit
The reciprocal best hit strategy of sequence similarity comparisons was used here to distinguish orthologous from paralogous genes. Orthologs are genes in different species that evolved from a common ancestral gene by speciation. Paralogs are genes originating from duplication events within a genome. Orthologs tend to retain the same function in the course of evolution, whereas paralogs often evolve new functions [29]. The reciprocal best hit strategy is known to be a better method than the unidirectional best hit method to distinguish orthologs from paralogs [29]. Here, this was especially significant for the identification of components of the AI-2 signal transduction system. The number of identified orthologs for LuxO and LuxQ decreases from over 300 down to 7 and 8 by applying the reciprocal best hit strategy. The resulting orthologs for LuxO and LuxQ are close to the number of identified LuxP and LuxU, confirming that the reciprocal best hit strategy significantly filtered out the potential paralogs.
However, it should be noted that in most cases the functions of these paralogs are not experimentally characterized and cannot be deduced by bioinformatics methods. Because of the high conservation among these regulatory components, it is hard to exclude the possibility that some of them may serve as alternative sensors for detecting the AI-2. On the other hand, the unidirectional best hits for the studied metabolic enzymes were basically the same as the reciprocal best hits, suggesting that the metabolic enzymes for the activated methyl cycle were seldom duplicated during the course of evolution.
Distribution of LuxS
The presence of either of two possible SAH degradation pathways in most living cells indicates their importance in the central cell metabolism. Both Archaea and Eukarya use exclusively a one-step detoxification pathway for SAH, indicating that this may be the ancient type of metabolism. The distribution of the two-step Pfs/LuxS pathway for detoxification of SAH within the domain Bacteria appears to be phylogenetically conserved. Since the currently sequenced genomes are biased towards pathogens, it remains to be seen if a similar phylogenetic pattern will also be found in non pathogenic bacteria from soils, sediments and marine environments. Previous studies [25,26] came to similar conclusions with respect to the presence of luxS. Our data strengthen the phylogenetic aspect of this distribution.
Interestingly, a unique species from the genomes in the KEGG database, namely Bifidobacterium longum NCC2705, possesses both pathways. This species is a key commensal of the healthy human gastrointestinal tract and vagina. The double pathways may be helpful to recycle and use methionine more economically or to accomplish its dependence on H2S or methanethiol for methionine biosynthesis [30]. Another non-pathogenic species, Escherichia blattae, was also identified to have both pathways (Göttingen Genomics Laboratory, unpublished). However, their physiological roles in this species have still to be clarified.
The phylogenetic tree of LuxS does not in all cases correspond to the 16S rRNA based microbial phylogeny. Thus, horizontal gene transfer might have resulted in the acquisition of LuxS genes e.g. in Bifidobacterium longum, Helicobacter pylori, Clostridium acetobutylicum and Borrelia burgdorferi, with the insect or mammalian gut serving as a melting pot of species.
Production of AI-2
In most of the microbial genera other than Vibrio spp. having a LuxS enzyme the production of AI-2 has been demonstrated using the Vibrio harveyi reporter strain BB170 (reviewed by Winzer et al. [26]; otherwise citation is given); e.g. for Actinobacillus actinomycetemcomitans, Bacillus anthracis [31]; Borrelia burgdorferi, Campylobacter jejuni, Clostridium perfringens, Escherichia coli, Helicobacter pylori, Lactobacillus [32], Neisseria meningitides, Porphyromonas gingivalis, Proteus mirabilis, Salmonella typhimurium, Shigella flexneri, Staphylococcus [27], Streptococcus, Pasteurellaceae, periodontal pathogens [33] and rumen bacteria [34]. However, only in V. harveyi BB170 it was clearly shown that the active compound was a furanosyl-borate-diester. In E. coli serotype O157, Sperandino et al. [11,35-38], showed that the transcription of essential virulence factors coded on the LEE genomic island was triggered by an as yet unknown compound termed autoinducer-3 (AI-3) which depends on the presence of the luxS gene and did not elicit luminescence in V. harveyi BB170. Thus, purification of culture supernatants used for detecting AI-2 activity would be required to show that the active fraction is indeed a furanosyl-borate-diester. Conversely, the "real" universal signal might be a different, presently unknown compound produced by a different cyclization product of DPD or by an enzymatic step downstream of LuxS.
Detection of AI-2
Our data clearly show that the signal transduction cascade for AI-2 is restricted to Vibrio species. This is consistent with the results of experimental studies published so far. No alternative signal transduction cascade for AI-2 has been experimentally identified in any of the strains studied, with the exception of Salmonella typhimurium [20,39]. Thus, there is no proof that these organisms actually respond to AI-2 in a quorum sensing related manner. However, the large diversity of two-component systems present in these organisms, for which in many cases the specific signals are not known, makes it quite possible that one of them might be devoted to the detection of AI-2 or another LuxS dependent compound. In Salmonella typhimurium, an ABC transporter with high homology to ribose transporters, which is however not homologous to LuxP, has been identified whose expression requires the presence of AI-2 and whose function is to transport it back into the cell [20,39]. No AI-2 induced genes other than this transporter have been found, indicating that in this organism AI-2 may not serve as a quorum sensing signal or the appropriate cultivation conditions for the expression of its activity were not met. Orthologs of the S. typhimurium lsr genes were found in most Enterobacteriales, as well as in Sinorhizobium meliloti and some Bacillus sp. (see Supplementary Table s3 [additional file 3]).
However, if AI-2 is indeed a universal signal molecule, it may be useful for bacteria to detect it even if they do not produce it themselves. This was shown to be actually the case in Pseudomonas aeruginosa, which does not contain the luxS gene [27]. Here, the promoters of 21 well characterized virulence associated genes were cloned into promoterless luxCDABE reporter plasmids and light induction was tested in the presence of AI-2 synthesized enzymatically from SAH or by co-culture with a luxS containing clinical isolate of Streptotoccus sp. (strain CF004). The fact that six of these virulence gene promoters were upregulated both by AI-2 and coculture with CF004 suggests a specific effect of AI-2 on the transcription of virulence associated genes in Pseudomonas aeruginosa, although the signalling cascade within the cell is presently unknown.
Conclusions
The presence of luxS in many phylogenetic groups within the domain Bacteria indicates that these bacteria, while recycling SAH in a two-step enzymatic process, at the same time produce a compound able to stimulate luminescence in a V. harveyi reporter strain which is most probably a furanosyl-borate-diester. The detection cascade, if any, for this compound in the producing organisms must be different from that in Vibrio strains and is presently not known. The diversity of physiological effects observed in luxS- mutants can either be interpreted as the result of a defect in a global quorum sensing regulatory mechanism, which may also be caused by a LuxS dependend compound other than AI-2, or as the result of a defect in the central methyl cycle of the cell. Thus, although there are intriguing indications for a LuxS dependent universal signal molecule in Bacteria, direct proof regarding the chemical nature of the compound and its signalling mechanism in non Vibrio organisms is presently missing.
Methods
Databases
The protein sequences of 138 sequenced genomes were downloaded from KEGG (Status June 2003) and reformatted as local blast databases. The non-redundant protein database of NCBI (nr) [45] and the KEGG Sequence Similarity Database (SSDB) [46] were explored through their online services.
Preparation of the queries
To achieve a more complete finding of the proteins functionally similar to the proteins related to either the metabolic pathway (LuxS, Pfs, SahH) or the signal transduction pathway (LuxP, LuxO, LuxQ, LuxU) of autoinducter-2, the NCBI protein database was at first searched with the relevant functional terms such as "AI-2 production" or "LuxS". A phylogenic tree was constructed based on the alignment of the relevant matches by using the component AlignX of the bioinformatic software suite "Vector NTI Advance" (InforMax, United States). From each branch of the tree, one protein (mainly the protein of which the function was manually curated, for example, by SWISSPROT) was selected. All of them were put together into a file as a blast query to represent a function. It is not necessary for the members of this function to be similar to each other in sequence level. This facilitates the finding of evolutionarily far-related proteins by blast search. The protein sequences of MetK, MetE and MetH from E. coli K12 and LsrR, -A, -B, -C, -D, -E, -F and G from Salmonella typhimurium [39] were used alone as query.
Blast search
The queries were used to search for their respective orthologs from the local KEGG genome databases by applying the reciprocal best hit strategy [40] with a blastp cutoff E-value 1E-4. In the reciprocal best hit strategy, protein i from genome A is orthologous to protein j from genome B only under the conditions that j is the best hit when i is queried in database B and reciprocally i is also the best hit when j is queried in database A [40]. A Visual Basic script was programmed to realize this strategy automatically. All identified orthologs were submitted for further analysis. The NCBI non-redundant protein database nr was searched using the normal one-direction blastp with a cutoff E-value 1E-4. The hits were manually checked to confirm that they had the same functional annotation as the query.
Phylogenetic tree construction
The phylogenetic tree for the orthologs was built with the neighbour-joining (NJ) method [41] using Vector NTI Advance (InforMax, United States) after the sequences had been aligned.
Authors' contributions
JS conducted the data mining work and contributed to writing the manuscript. RD cooperated with the access to the ERGO database. IWD initiated the study, contributed to the concept and drafted the manuscript. APZ supervised the study and contributed to writing the manuscript. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Supplementary Table s1. Presence of AI-2 synthesis and detection genes in 138 completed genomes of the KEGG database (July 2003). Abbreviations: luxS, AI-2 synthetase/SRH cleavage enzyme; pfs, SAH-nucleosidase enzyme; sahH, SAH hydrolase; metH and metH, methionine synthetase; metK SAM synthetase; luxP, AI-2 binding protein; luxQ, membrane bound hybrid sensor kinase; luxU, histidine phosphorelay protein ; luxO response regulator. See Fig. 1 for further information on the synthesis pathway and Fig. 2 for the phosporelay detection cascade. Organisms shaded violet contain neither luxS nor sahH.
Click here for file
Additional File 2
Supplementary Table s2. The accession numbers of the genes in Supplementary Table s1. Abbreviations as in Supplementary Table s1.
Click here for file
Additional File 3
Supplementary Table s3. Presence of the Salmonella lsr gene homologs in the completed genomes of the KEGG database (July 2003). Abbreviations as in Supplementary Table s1. X denotes bi-directional hits, ? denotes unidirectional hits.
Click here for file
Acknowledgements
Roland Weller is gratefully acknowledged for making Fig. 3.
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The KEGG database
The EMBL database
The ERGO database
The non-redundant protein database of NCBI (nr)
The KEGG Sequence Similarity Database (SSDB)
| 15456522 | PMC524169 | CC BY | 2021-01-04 16:29:00 | no | BMC Evol Biol. 2004 Sep 29; 4:36 | utf-8 | BMC Evol Biol | 2,004 | 10.1186/1471-2148-4-36 | oa_comm |
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BMC GenetBMC Genetics1471-2156BioMed Central London 1471-2156-5-301546267410.1186/1471-2156-5-30Methodology ArticleDiagnostic polymorphisms in the mitochondrial cytochrome b gene allow discrimination between cattle, sheep, goat, roe buck and deer by PCR-RFLP Pfeiffer Ina 1ipfeiff@gwdg.deBurger Joachim 2jburger@mail.uni-mainz.deBrenig Bertram 1bbrenig@gwdg.de1 Institute of Veterinary Medicine, Georg-August-University of Göttingen, Groner Landstrasse 2, D-37073 Göttingen, Germany2 Institute of Anthropology, Johannes Gutenberg-University of Mainz, Colonel Kleinmann Weg 2, D-55099 Mainz, Germany2004 5 10 2004 5 30 30 13 3 2004 5 10 2004 Copyright © 2004 Pfeiffer et al; licensee BioMed Central Ltd.2004Pfeiffer 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
As an alternative to direct DNA sequencing of PCR products, random PCR-RFLP is an efficient technique to discriminate between species. The PCR-RFLP-method is an inexpensive tool in forensic science, even if the template is degraded or contains only traces of DNA from various species.
Results
Interspecies-specific DNA sequence polymorphisms in the mitochondrial cytochrome b gene were analyzed using PCR-RFLP technology to determine the source (i.e., species) of blood traces obtained from a leaf.
Conclusions
The method presented can be used for the discrimination of cattle (Bos taurus), sheep (Ovis aries), goat (Capra hircus), roe buck (Capreolus capreolus) and red deer (Cervus elaphus).
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Background
Determination of the species from which traces of source material, such as blood stains on a leaf, originate can sometimes be a difficult task in forensic DNA analysis. For instance, insurance claims that involve car accidents with animals require authentication. Species identification is also essential in food quality control-procedures or for the detection and identification of animal material in food samples. Numerous analytical methods that rely on protein analysis have been developed for species identification, such as electrophoresis techniques [1,2], immunoassays [3] and liquid chromatography [4]. However, proteins are heat labile and lose their biological activity. Furthermore, their presence and characteristics depend on special cell types. Thus, for species identification, DNA analysis would be preferred over protein analysis. The first genetic approach for determination of species identity was the dot-blot technique [5]. At present, polymerase chain reaction (PCR) is the technique of choice for species identification [6]. Some PCR approaches are RAPD-PCR (random amplified polymorphic DNA fingerprints) [7] and others are focused on RFLP analysis [8]. In this work we present a more sensitive method to detect DNA from degraded samples. Usually, the required specimen (hair, a part of skin or a piece of meat) contains degraded DNA and the PCR products must be cloned before sequencing [9]. Existing techniques consist of laborious and costly DNA sequencing procedures. We therefore used a less time-consuming PCR method to amplify a short mitochondrial (mt) DNA fragment. The PCR-RFLP allowed discrimination between different species even in cases in which the source material contained only degraded DNA. The mitochondrial cytochrome b gene has been used in phylogenetic as well as in forensic investigations [10-12] and has been shown in a variety of studies to be a very useful DNA-region for species determination [13-18]
However, before applicable for routine analysis, species-specific diagnostic polymorphisms or mutations must be determined.
If these mutations affect restriction enzyme sites, a simple PCR-RFLP can be used as a "sceening tool" for detection.
One area in which the PCR-RFLP screening tool would be useful is in training hunting hounds. Before hounds are accepted and approved for hunting, they have to be evaluated by different tests. These tests include an examination of the dog's ability for winding and trailing. To examine these abilities normally a track is prepared consisting of minute amounts of blood from game animals, e. g., wild boar, spotted on a few leaves that are distributed in the forest or field. A trained hound should be capable of winding and trailing without any problems. However, in a case that came to our attention, hounds were unable to wind and it was assumed by the owners that the examiner had used blood from domestic animals. Hence, the question as to the source of the track (i.e., blood from domestic or game animals) was open.
To solve this problem we established genetic test (PCR-RFLP) that focused on the use of diagnostic polymorphisms in the mitochondrial cytochrome b gene: Our method can be used for the discrimination between the following mammal species: cattle (Bos taurus), sheep (Ovis aries), goat (Capra hircus), roe buck (Capreolus capreolus) and red deer (Cervus elaphus).
Results and discussion
For the analysis, DNA was prepared from blood remains on different leaves. The DNA was amplified as described in Methods. Figure 1 shows RFLP results of five different species (Bos taurus, Ovis aries, Capra hircus, Capreolus capreolus and Cervus elaphus) and the pattern of bands from the blood sample of one of the dry leaves. As controls, DNA-samples from known species were used. Specific RFLP patterns that distinguish between 5 species are analyzed here. To estimate the exact size of fragments, DNA sequence information was used. C. hircus shows a single fragment of 182 bp, whereas with C. capreolus a fragment of 162 bp was obtained. The RFLP pattern of C. elaphus consisted of 2 fragments of 108 bp and 54 bp respectively. The blood sample on the leaf shows four fragments: 114 bp and 68 bp-fragments, which are characteristic for B. taurus, and a 105 bp and 75 bp fragment which can be assigned to O. aries. This result indicates that the blood sample on the leaf represents a mixture from two species (B. taurus and O. aries). The results were obtained from two independent DNA extractions and confirmed several times by independent PCRs, as well as by DNA sequencing. Amplifications were repeated and species identification was verified by diagnostic Dloop sequencing [19]. The Dloop DNA sequence of the PCR amplified fragment of the blood track was aligned with the mtDNA sequence of B. taurus and three nucleotide differences were observed.
Figure 1 Restriction cleavage patterns of DNA mixtures with varying amounts of target DNA.
In addition to species determination using PCR-RFLP analysis, we tested for different DNA ratios of mixed samples, by which an assignment to a species is still possible. A valid assignment of a mixture of B. taurus and O. aries is still possible for a ratio of 59:1(Fig. 1).
The data clearly illustrate that it is possible to identify the species from unknown material using PCR-RFLP, provided that comparison to a known species is performed on the same gel.
Furthermore, the PCR-RFLP enables the observation of frequent contaminants such as cattle DNA in routine diagnostic labs. While direct sequencing of coamplified endogenous DNA would lead to multiple sequences, the PCR-RFLP is able to separate two signals. Sometimes, possible contaminants (such as human DNA) can lead to false results, but with the designed primer pair this problem was circumvented. For this reason we designed maximally discriminatory primers and the mismatches in each primer are sufficient to exclude human DNA under stringent PCR conditions. The primers were tested with different amounts of added DNA. This method can be used for analysis of mixed samples, since up to three species in different proportions can be determined. The RFLP test using other tissues, e.g., muscle, hair with roots, bones, and saliva, yielded reproducible results. Faeces have not been tested so far.
However, when minimizing target DNA, the bands tend to fade away on the agarose gel. The presence of a specific PCR-RFLP for the species analysed, a fragment length of less than 200 bp and the exclusion of contaminating sequences improved methods for existing species determination. The principle of RFLP is often used in food analysis [20,21]. However, the new PCR-RFLP method is capable of analysing degraded DNA, especially in forensic cases. Furthermore, the PCR-RFLP utilizes only a small fraction of apomorphic sites.
The speed and the efficiency of current nucleotide technology, such as automatic sequencing, will permit the identification of additional taxa. However, the establishment of a PCR-RFLP test would likely need further extensive experimentation.
Conclusions
In summary, we were able to show that a simple PCR-RFLP is efficient in differentiating between B. taurus, O. aries, C. hircus, C. capreolus and C. elaphus. However, after further development, the tested mitochondrial nucleotide sequences may allow the forensic identification of other animal species.
Methods
DNA extraction
DNA extraction (Normal samples)
DNA was extracted from blood and tissue samples using QIAamp® Tissue Kit (QIAGEN GmbH, Hilden, Germany) according to the manufacturers' handbook. Isolated DNA was diluted in 50 μL HPLC-H2O and used for further analyses.
DNA extraction (Trace material e.g. bones)
Bone samples were roughly ground with a pestle and mortar, then finely powdered in a Retsch mill. Bone powder (0.3 g) was incubated in 1.5 mL of 0.5 M EDTA (pH 8.3) for 20 h while rotating. The suspension was centrifuged for 4 min at 4000 rpm. The supernatant was transferred to a fresh tube or to an automated nucleic acids extraction system (Nucleic Acid Extractor 341A, Applied Biosystems) and 1.6 mL sterile distilled water (Ampuwa, Fresenius) was added. As the extraction procedure was automated the volumes of reagents dispensed may have varied between runs. Five hundred microliters of Proteinase K was added and the mixture incubated for 1 h at 58°C with shaking. Three milliliters of phenol/chloroform/isoamyl alcohol (25:24:1, pH 7.5–8.0) were added and the mixture was further incubated at room temperature for 6 min while shaking. The phases were allowed to separate by incubating at room temperature for 8 min without shaking and the organic phase and interphase, if present, were discarded. Chloroform (4.5 mL, 100%) was added to the aqueous phase and the mixture incubated for 6 min at room temperature while shaking. The phases were again allowed to separate by incubating at room temperature for 8 min without shaking and the organic phase and interphase, if present, were discarded. Ninety microliters of sodium acetate (pH 4.5) and 3.2 mL of 100% isopropanol were added followed by incubation for 2 min with shaking. Five microliters of Glasmilk (Dianova) were added and the suspension was shaken for another 10 min. To obtain a pellet, the solution was filtered through Precipitette filters (Applied Biosystems) or centrifuged for 3 min at 5000 rpm. The pellet was washed with 80% ethanol and eluted into 50 μL sterile distilled water (Ampuwa, Fresenius). Five to ten microliters of extract were used for PCR amplification or the extract was stored at -20°C. Glasmilk was not removed prior to amplification.
PCR-RFLP
For RFLP analysis, a 195 bp long PCR fragment was amplified from mitochondrial cytochrome b region. The following primer pair was used for amplification, CB7u (5'-GCGTACGCAATCTTACGATCAA-3') and CB7l (5'-CTGGCCTCCAATTCATGTGAG-3').
The PCR was carried out in a total volume of 50 μL consisting of 10 ng DNA, 60 mM KCl; 12 mM Tris-HCl; 2.5 mM MgCl2; 150 μM dNTPs; 0,18 μM of each Primer and 2 U AmpliTaq Gold (PE Applied Biosystems). Cycling conditions included a denaturation step at 95°C for 3 minutes, followed by 32 cycles of 95°C for 1 minute, primer annealing at 54°C for 1 minute and elongation at 72°C for 1 minute in a thermocycler (Hybaid).
The 195 bp fragment was digested with TSP509 (New England Biolabs) for two hours at 65°C. The resulting fragments were separated by gelelectrophoresis in a 2.5 % agarose gel.
MtDNA Dloop PCR sequencing reaction
A single fragment of the mitochondrial DNA Dloop region was amplified using primers Dloopu (5'-AAATGTAAAACGACGACGGCCAGTAATCCCAATAACTCAACAC-3') and Dloopll (5'-AAACAGGAAACAGCTATGACCACTCATCTAGGCATTTTC-3').
Amplifications were performed in a final volume of 20 μL in 10 × PCR buffer (15 mM MgCl2, pH 8.3) and Q-solution, 100 μM for each dNTP, with 1 M Taq Polymerase and 10 pmol of each primer. Four microlitres of the DNA-extract were added to the PCR mix. The amplification was carried out with initial denaturation at 95°C for 10 min, followed by 35 cycles of one denaturation step at 94°C for 40 sec, primer annealing at 52°C for 40 sec and primer extension at 72°C for 45 sec in a Hybaid thermocycler. PCR-products were purified using the QIAEX II Gel Extraction Kit (QIAGEN GmbH, Hilden, Germany) according to the manufacturers' instructions. Sequencing was performed using ABI-Prism™ Dye Kit V3 (Applied Biosystems) in a 10 μL volume containing 2 μL purified PCR-product and 5 pmol of primer. Sequencing reactions underwent 27 cycles of 30 sec at 94°C, 30 sec at 50°C and 3 min at 60°C in a Techne thermocycler. The dye terminators were removed by sephadex-G45 column purification (Millipore). Sequencing reactions were electrophoresed for 2 h on an ABI Prism® 3100 genetic analyzer (Applied Biosystems) according to the manufacturers' instructions.
Sample selection
In order to test the specifity of the technique the following numbers of specimens were tested:
7 unrelated samples from cattle: Holstein Frisian, Charolais, Limousin, Angus
7 unrelated samples from sheep
7 unrelated samples from goat
7 unrelated samples from deer collected from Lower Saxony and North Hesse
7 unrelated samples from roe deer collected from Lower Saxony
Regarding closely related species, we analyzed mouflon DNA (Ovis aries musimon) and observed approximately 100% sequence identity compared with Ovis aries. Furthermore, we investigated different cattle breeds and we could not find any sequence differences within the tested cytochrome b DNA-fragment.
Authors' contributions
IP performed the DNA extractions, PCR-RFLP analysis and mtDNA Dloop DNA sequencing.
JB developed and provided the PCR-RFLP protocol for species identification.
BB was responsible for funding, supervision of the research project, manuscript writing and editing as well as scientific correspondence.
Figure 2 Restriction profiles of the 195 bp cytochrome b PCR fragments showing interspecies-specific polymorphism between B. taurus, O. aries, C. hircus, C. capreolus and C. elaphus. The unknown blood sample shows the fragment length of B. taurus and O. aries. Nr. 1 and Nr.11 controls (Bos taurus, undigested PCR product), Nr. 2: C. hircus., Nr. 3: O. aries, Nr. 4: B. taurus, Nr. 5, 6 and 7 blood sample on a leaf, Nr. 8: DNA mixture B. taurus and O. aries, Nr. 9: C. elaphus, Nr. 10: C. capreolus.
Acknowledgements
This work was supported by a grant of the Erxleben Research & Innovation Council to B. Brenig (ERIC-BR1959-2000-06).
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| 15462674 | PMC524170 | CC BY | 2021-01-04 16:30:34 | no | BMC Genet. 2004 Oct 5; 5:30 | utf-8 | BMC Genet | 2,004 | 10.1186/1471-2156-5-30 | oa_comm |
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BMC ImmunolBMC Immunology1471-2172BioMed Central London 1471-2172-5-211538315310.1186/1471-2172-5-21Research ArticleCharacterization and phylogenetic epitope mapping of CD38 ADPR cyclase in the cynomolgus macaque Ferrero Enza 1enza.ferrero@unito.itOrciani Monia 2m.orciani@univpm.itVacca Paola 1paola78paola@yahoo.itOrtolan Erika 1erika.ortolan@unito.itCrovella Sergio 3crovella@burlo.trieste.itTitti Fausto 4titti@iss.itSaccucci Franca 2f.saccucci@univpm.itMalavasi Fabio 1fabio.malavasi@unito.it1 Department of Genetics, Biology & Biochemistry, University of Torino, Via Santena 19 and the CeRMS Research Center for Experimental Medicine, 10126 Torino, Italy2 Institute of Biology and Genetics, Marche Polytechnic University, Via Ranieri 69, 60131 Ancona, Italy3 Department of Reproductive and Developmental Sciences, University of Trieste, Via dell'Istria 65/1, 34137 Trieste, Italy4 Department of Parasitic, Infectious and Immune-mediated Diseases, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, Italy2004 21 9 2004 5 21 21 10 6 2004 21 9 2004 Copyright © 2004 Ferrero et al; licensee BioMed Central Ltd.2004Ferrero 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 CD38 transmembrane glycoprotein is an ADP-ribosyl cyclase that moonlights as a receptor in cells of the immune system. Both functions are independently implicated in numerous areas related to human health. This study originated from an inherent interest in studying CD38 in the cynomolgus monkey (Macaca fascicularis), a species closely related to humans that also represents a cogent animal model for the biomedical analysis of CD38.
Results
A cDNA was isolated from cynomolgus macaque peripheral blood leukocytes and is predicted to encode a type II membrane protein of 301 amino acids with 92% identity to human CD38. Both RT-PCR-mediated cDNA cloning and genomic DNA PCR surveying were possible with heterologous human CD38 primers, demonstrating the striking conservation of CD38 in these primates. Transfection of the cDNA coincided with: (i) surface expression of cynomolgus macaque CD38 by immunofluorescence; (ii) detection of ~42 and 84 kDa proteins by Western blot and (iii) the appearance of ecto-enzymatic activity. Monoclonal antibodies were raised against the cynomolgus CD38 ectodomain and were either species-specific or cross-reactive with human CD38, in which case they were directed against a common disulfide-requiring conformational epitope that was mapped to the C-terminal disulfide loop.
Conclusion
This multi-faceted characterization of CD38 from cynomolgus macaque demonstrates its high genetic and biochemical similarities with human CD38 while the immunological comparison adds new insights into the dominant epitopes of the primate CD38 ectodomain. These results open new prospects for the biomedical and pharmacological investigations of this receptor-enzyme.
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Background
Just over a decade after being identified as a leukocyte surface antigen with receptorial activity [1,2], CD38 was re-classified among the ADP-ribosyl (ADPR) cyclases [3,4]. These are a group of related membrane-bound or soluble enzymes, comprising CD157 and Aplysia ADPR cyclase [5,6], which have the unique capacity to convert NAD to cyclic ADP ribose (cADPR) or nicotinic acid-adenine dinucleotide phosphate (NAADP), part of a new generation of endogenous activators of intracellular Ca2+ release [6].
Human CD38 is a broadly expressed type II transmembrane glycoprotein of ~45 kDa in its monomeric form [7]. This consists of a short intracytoplasmic (IC) tail, a transmembrane domain and a major extracellular domain (ECD) formed by 256 of the 300 constituent amino acids of the CD38 polypeptide [7]. Homodimeric and homotetrameric forms have also been described [8,9] and a 3-D dimer structure obtained by homology modeling to Aplysia cyclase [10]. The CD38 ECD, where both receptor and enzymatic activities reside, harbours a 12 cysteine/6 disulfide signature common to the members of this family. According to a growing body of experimental evidence, the disulfides mediate control of the ECD conformation and function since reduction modifies CD38 enzymatic activity and homodimerization [11,12], and sensitivity to proteolysis and monoclonal antibody (mAb) binding [13].
The mobilization of intracellular Ca2+ caused by the CD38/cADPR/NAADP axis has been implicated in a variety of physiological and pathological processes including insulin secretion and diabetes [14], myometrial contractility and pregnancy [15], airway smooth muscle contractility and hyperreactivity [16], vascular smooth muscle contraction [17], osteoclast activity [18], and the functions of the immune [19], renal [20] and exocrine gland [21] systems. The assortment of effects caused by CD38 ligation and transmembrane signalling is also broad though mostly described in hematopoietic cells, and ranges from lymphocyte proliferation and cytokine release [2,22-24], regulation of B and myeloid cell development and survival [25-28], inhibition of human immunodeficiency virus (HIV) entry [29], to induction of dendritic cell maturation [30]. In addition, ligation of human pancreatic islet cells by anti-CD38 autoantibodies induces insulin release [31]. CD38 is also a clinically useful marker of HIV infection progression [32] and therapy-requiring B-CLL [33].
In this study, we describe the molecular cloning and functional expression of CD38 from the cynomolgus macaque. In addition, with a panel of newly-raised mAbs, we comparatively analyse the macaque and human CD38 ECDs and identify new structural-functional characteristics of CD38 epitopes.
Results
Cloning CD38 cDNA from cynomolgus macaque
Activation of human peripheral blood mononuclear cells (PBMC) with phytohemagglutinin (PHA) strongly upregulates expression of CD38 in human T lymphocytes [34]. Therefore, to isolate a CD38 cDNA, PHA-activated cynomolgus PBMC were chosen as the source of RNA for amplification by RT-PCR using primers derived from the human CD38 5' and 3' untranslated regions. The 1113 base-pair (bp) insert contained an open reading frame of 906 bp (Figure 1A) that was 95% identical to the human CD38 sequence. The cDNA encodes a 301 amino acid (aa) polypeptide with the typical CD38 type II membrane protein structure, i.e., a short cytosolic tail (residues 1–21), a transmembrane region (residues 22–44), and an ECD (residues 45–301) containing the signature 12-cysteine array. Alignment of the macaque and human CD38 polypeptides showed 92% identity and 94% similarity. There is complete conservation of the IC region while there are five conservative changes in the transmembrane region where macaque CD38 has one more residue than human CD38. Macaque CD38 has four potential N-linked glycosylation sites, as in human CD38; three are co-linear. Furthermore, macaque CD38 shows conservation of the 4 acidic residues (Glu148, Asp149, Asp157, Glu228) and 2 tryptophans (Trp127 and Trp191) that play a critical role in the ADP-ribosyl cyclase/cADPR hydrolase activities of human CD38 [35]. Lys130 is also maintained suggesting that, like human CD38, binding of ATP to this residue may lead to inhibition of the hydrolase activity [36]. Likewise, macaque CD38 conserves Arg271 which is ADP-ribosylated in human CD38, causing inactivation [37].
Figure 1 Cynomologus macaque CD38 cDNA, promoter and 5' end of intron 1. A. Primers used to clone the cDNA are wavy-underlined. Members of the 12-cysteine array of the ectodomain are color-boxed; cysteines that pair in disulfide formation are boxed in the same color. Differences in the human CD38 amino acid sequence are indicated under the macaque sequence. The transmembrane domain is underlined and glycosylation sites indicated. The sequence accession number is AY555148. B. Nucleotide sequence of the CD38 promoter from Macaca fascicularis (MFA) (Acc. No. AY622999), Homo sapiens (HSA) (Acc. No. AF001985) and Pan troglodytes (PTA) (Acc. No. AY623001). The nucleotide sequences begin at -1 immediately upstream of the ATG initiation codon. Potential transcription regulatory motifs common to the 3 species, identified with TRANSFAC® [62], are boxed and the relevant transcription factor indicated above. C. 5' end of intron 1 of macaque and human CD38, Acc. No. AY623000 and AF088883, respectively.
Common genomic organization and regulatory features of macaque and human CD38 genes
Human CD38 has been characterized as a single-copy, 8-exon gene that spans ~70 kb [5,38] and not only CD38 but ADPR cyclase genes in general are highly conserved from mollusks to humans [39,40]. In addition, the Southern blot hybridization patterns of macaque and human genomic DNAs digested with EcoRI, BamHI and HindIII and probed with their homologous CD38 cDNA are similar (data not shown), indicating that the structural organization of macaque and human CD38 is highly conserved. This was further demonstrated by the finding that the same primers previously used to amplify the 8 human CD38 exons [41] also amplified 8 CD38 exons from macaque genomic DNA. The putative macaque exons could be perfectly aligned with their human counterparts [5] in number, size and splice site of their exons (Table 1). All intron-exon boundaries conformed to the GT-AG rule, most 5' splice donor and 3' splice acceptor sequences of the 7 introns were identical.
Table 1 Exons and introns of cynomolgus macaque CD38
Exon 5' splice donor Intron 3' splice acceptor Exon
1 ATGAGgtggg I cacagACATG 2
MetAr79 gHisV
2 ACAGGgtaat II cttagACTCT 3
snLys122 ThrLe
3 TTTCGgtgag III tttagAAATA 4
rPheG168 luIle
4 GCAGGgtaag IV ttaagTTTGC 5
rgArg196 PheAl
5 AACAGgtaac V tttagCACTT 6
AsnSe221 rThrP
6 TCCAGgtata VI cccagAGACT 7
SerAr251 gAspL
7 TACAGgtaat VII cacagACCTG 8
TyrAr280 gProA
Transcription of TATA-boxless human CD38 initiates at multiple start sites [5,38] while induction of gene expression by retinoids is controlled by a retinoic acid responsive element (RARE) at the beginning of intron 1 [42]. To identify conserved cis-regulatory sequences, ~500 bp upstream of the initiation codon ATG were amplified by PCR from genomic DNA of cynomolgus macaque but also from chimpanzee (Pan troglodytes), to strengthen the alignment with the human CD38 promoter sequence, and numerous conserved general and immune-related potential binding sites were found (Figure 1B). The alignment of the 5' end of intron 1 from macaque and human CD38 shows the presence of the RARE (Figure 1C), suggesting that this and perhaps other molecular mechanisms involved in regulating CD38 are conserved between these primates.
Expression of macaque CD38 reveals an active cyclase of ~42 kDa
To analyse surface expression and function of macaque CD38, the cDNA insert was subcloned into the pcDNA3.1 expression vector and a similar construct was prepared containing the human CD38 cDNA (see Materials & Methods). DNAs were transfected for heterologous expression in the NIH/3T3 cell line which does not express CD38 [43]. Given that cross-reactivity of OKT10 anti-human CD38 mAb has been exploited to detect CD38 in rhesus macaque hematopoietic cells [44,45], clones expressing cynomolgus CD38 were identified by indirect immunofluorescence (IF) with OKT10 (see below). The stable cell line expressing macaque CD38 was designated NIH/mac38, while NIH/hum38 is the human CD38-expressing cell line.
The ecto-cyclase activity of macaque CD38 was evaluated by incubating the NIH/mac38 clone with nicotinamide guanine dinucleotide (NGD), an NAD analog which is converted by ADP-ribosyl cyclases such as CD38 to cyclic GDP ribose (cGDPR). Unlike cADPR, cGDPR is a stable, fluorescent end-product which can be detected in cell supernatants [46]. Increased fluorescence following incubation with NGD was detected in supernatants of macaque and human CD38 transfectants, demonstrating that macaque CD38 is enzymatically active (Figure 2A).
Figure 2 Enzymatic activity and western blot analysis of cynomolgus CD38. A. Ecto-cyclase activity was evaluated by measuring conversion of NGD to fluorescent cGDPR by NIH/mac38 (1), NIH/hum38 (2), NIH/3T3 (3), or cynomolgus macaque RBCs (4) and human RBCs (5). Each bar represents mean ± SD; (*) means significantly higher than controls (P < 0.05, t-test, n = 3 experiments). Y axis = fluorescence emission 410 nm. B. Western blot of lysates from parental NIH/3T3 cells (NIH), NIH/hum38 (hum38) and NIH/mac38 cells (mac38) analysed by 10% SDS-PAGE under non-reducing (NR) conditions. Blots were probed with AT1 anti-human CD38 mAb. C. Western blot of parental NIH/3T3 and NIH/mac38 cell lysates analysed by 8% SDS-PAGE in non-reducing (NR) or reducing (R) conditions and probed with the indicated anti-cynomolgus CD38 mAbs. In B and C, molecular weight markers (in kDa) are indicated on the right.
In human red blood cells (RBCs), CD38 is the only source of ecto-cyclase activity [47] which was also found on the surface of cynomolgus macaque RBCs (Figure 2A), suggesting a further parallel with human CD38.
To establish the approximate molecular weight of macaque CD38, SDS-PAGE and Western blot analysis were performed with lysates prepared from NIH/mac38 and NIH/hum38 cells. Blots were probed with the AT1 anti-human CD38 mAb which detected a band of ~42 kDa in both transfectants (Figure 2B).
Production of anti-macaque CD38 mAbs
To raise mouse mAbs against macaque CD38, live NIH/mac38 cells were used for immunization. Four mAbs, KK1B5 (IgG1), KK4E5 (IgG2a), KK6A11 (IgG2a) and KK9H4 (IgG1) were selected for further analyses. All four anti-macaque CD38 mAbs reacted by IF with NIH/mac38 but were negative with the parental cell line (Figure 3). Only two mAbs (KK1B5 and KK9H4) reacted with NIH/hum38.
Figure 3 Reactivity of anti-cynomolgus CD38 mAbs. Top row: Flow cytometric profiles obtained by IF of parental NIH/3T3 (grey profile) and NIH/mac38 expressing cynomolgus CD38 (white profile) with OKT10 anti-human CD38 mAb and anti-cynomolgus CD38 mAb panel. Profiles obtained by staining both cell lines with CBT3G IgG control mAb completely overlap with the grey profile. Bottom row: Flow cytometric profiles obtained with NIH/hum38 and the indicated mAbs (white profile). Grey profile is the reactivity of CBT3G.
The anti-macaque CD38 mAbs were further assessed by IF for binding to cynomolgus PBMC and to SL-691 and SL-999, two cynomolgus macaque B lymphoblastoid cell lines. All four mAbs reacted with PBMC from cynomolgus macaques, indicating they recognize native cynomolgus CD38, and they strongly stained cells of the two B cell lines (Table 2).
Table 2 Reactivity of anti-macaque CD38 mAbs
Monoclonal antibodies
Cell lines KK1B5 KK4E5 KK6A11 KK9H4 Control
Macaque CD38+
NIH/mac38 +++a +++ ++ +++ -
SL-691 ++ ++ ++ ++ -
SL-999 ++ ++ ++ ++ -
PBMC
++ ++ ++ ++ -
Human CD38+
NIH/hum38 ++ - - ++ -
RAJI ++ - - ++ -
Jurkat ++ - - ++ -
PBMC ++ - - + -
Control
NIH/3T3 - - - - -
a+++, very strong reactivity; ++, strong reactivity; +, weak reactivity; -, no reactivity.
Additional Western blot analyses were carried out with the anti-macaque CD38 mAbs. MAbs KK1B5 and KK9H4 confirmed detection of a ~42 kDa band in NIH/mac38 cell lysates but also recognized a second band of ~84 kDa. (Figure 2C). The doublet was also identified in SL-999 cynomolgus B cells (data not shown). Instead mAbs KK4E5 and KK6A11 only recognized a band of ~84 kDa, even in reducing conditions. No bands were detected by these mAbs in parental NIH/3T3 cells.
Anti-macaque CD38 mAbs recognize either species-specific/DTT-resistant epitopes or a human cross-reactive/DTT-sensitive epitope
The observation that mAbs KK4E5 and KK6A11 recognize only cynomolgus CD38 while mAbs KK1B5 and KK9H4 also recognize human CD38 indicates that the two mAb subsets are directed towards different epitopes. To evaluate the contribution of disulfides to these epitopes, mAb reactivity was assessed after treating NIH/mac38 with dithiothreitol (DTT). Reduction had no effect on binding of the species-specific mAbs (KK4E5 and KK6A11) but significantly reduced binding of mAbs KK1B5 and KK9H4 (Figure 4A), indicating that the latter recognize a disulfide-requiring conformational epitope of the cynomolgus CD38 ECD, and predicting they should recognize a similar epitope in human CD38. The results (Figure 4B) confirm that treatment of NIH/hum38 with DTT decreased binding of mAbs KK1B5 and KK9H4, indicating that cynomolgus macaque and human CD38 have a conformational epitope in common.
Figure 4 Reactivity of anti-macaque CD38 mAbs with native and DTT-treated NIH/macCD38 and NIH/humCD38. A. Flow cytometric profile of NIH/mac38 cells treated for 45 min at 37°C with 10 mM DTT (red profile) or without DTT (black profile) and then tested for binding of anti-cynomolgus CD38 mAbs by IF. Grey profile shows reactivity of CBT3G mAb (isotype control). B. Results of IF/DTT experiments illustrated by confocal microscopy. Transfectants are indicated at the top of the panel. Left vertical triplet of images (from top to bottom): (1) reactivity of mAb KK1B5 with native cynomolgus CD38 cells stained with FITC; (2) reactivity with DTT-treated cells stained by FITC; (3) cells in plate 2 viewed by differential interference contrast (DIC). (4–6): idem mAb KK1B5 with NIH/humCD38; (7–9): idem mAb KK4E5 mAb with NIH/macCD38. C. IF/confocal microscopy of NIH/humCD38, with/without DTT. Left vertical triplet of images (from top to bottom) shows staining with mAb IB4 and FITC of control (1), DTT-treated visualized by FITC (2) and DIC (3). Right trio: results with mAb AT1 (4–6). D. Flow cytometric profiles of control (black profile) and DTT-treated (red profile) NIH/macCD38 binding by anti-human CD38 mAbs and FITC. Grey profile shows reactivity of CBT3G mAb (isotype control).
Anti-human CD38 mAbs are also species-specific/DTT-resistant or cross-reactive/DTT-sensitive
Reciprocal experiments were performed to see if the correlation between cross-reactivity and epitope sensitivity to DTT was also valid for a panel of 6 well-known mAbs raised against human CD38. MAbs IB4, IB6, OKT10, SUN-4B7, AT1 and HB7 were assessed for binding to native and DTT-treated NIH/hum38, and for cross-reactivity with cynomolgus CD38. Binding of mAbs IB4, IB6 and HB7 to human CD38 was unaffected by DTT and none bound cynomolgus CD38 (Figure 4C and 4D). On the contrary, binding of mAbs OKT10, SUN-4B7 and AT1 to human CD38 was significantly reduced by DTT and all three mAbs bound cynomolgus CD38 (Figure 4D) in a DTT-sensitive manner.
The epitope recognized by cross-reactive cynomolgus anti-CD38 mAbs maps to the C-terminal disulfide loop
The observation that mAbs KK1B5 and KK9H4 (raised against cynomolgus CD38) and mAbs OKT10, AT1 and SUN-4B7 (raised against human CD38) all bind native but not reduced cynomolgus and human CD38 is compatible with their binding the same epitope. A priori knowledge of the human CD38 epitope map previously established that OKT10 binding is abrogated by deletion of one or both of the C-terminal Cys residues (Cys287 and Cys296) predicted to pair in disulfide bond formation [48] and that mAbs OKT10, AT1 and SUN-4B7 mutually compete for binding to the human CD38 ECD [49]. This would position the common epitope of cynomolgus and human CD38 in the C-terminal disulfide loop formed by Cys288 and Cys297 in cynomolgus CD38 (Cys287/Cys296 in human CD38).
To test this possibility, we analysed reactivity of these mAbs with the CD38-negative MT2 human T cell line stably transfected with CD38Δ285, a human CD38 deletion mutant which lacks the 15 C-terminal amino acids and loses OKT10 binding [29]. IF analysis demonstrates that the 15 C-terminal amino acids of human CD38 are required for binding of mAbs KK1B5, KK9H4 and OKT10 (Figure 5). In contrast, mAbs SUN-4B7 and AT1 maintained binding to MT2/CD38Δ285 (data not shown). These data are consistent with the presence of two close conformational epitopes in human and cynomolgus CD38: one identified by mAbs KK1B5, KK9H4 and OKT10 located in the last (6th) disulfide loop, the other by mAbs SUN-4B7 and AT1 mapping to the penultimate (5th) C-terminal disulfide loop involving Cys254-Cys275 (Figure 6). Note that human-cynomolgus CD38 amino acid sequence identity in the 5th loop is 20/22 amino acids, and 10/10 amino acids in the 6th loop.
Figure 5 Reactivity of macaque/human CD38 cross-reactive mAbs with MT2Δ285 cells expressing truncated human CD38. Flow cytometric profiles obtained by IF with the indicated mAbs and MT2 T lymphoid cells stably expressing human CD38 deleted of the 15 C-terminal residues (heavy black line profile). Isotype control (light black line profile).
Figure 6 Molecular model of human CD38 epitope map. A. Homology model of human CD38 derived from Aplysia ADPR cyclase 3-D model made with RasWin Molecular Graphics showing footprints of the relevant anti-macaque and anti-human CD38 mAbs. Close-up of two C-terminal disulfide loops delimited by Cys254-Cys275, and Cys285-Cys296. Position of cysteine residues and disulfide bonds are indicated in yellow. Sequence is represented by secondary structure (red, alpha helix; blue, beta strand; white, turn). B. Same model illustrating the two beta strands implicated in binding of human species-specific mAbs and the residue changes in macaque CD38 that may account for their lack of cross-reactivity. C. Model of the dimeric form of the human CD38 ECD showing where epitopes are located.
Discussion
In this study, we describe the molecular cloning and functional expression of the CD38 receptor/enzyme from the cynomolgus macaque. The cDNA described here presents the expected homology to human CD38 considering that the macaque-human lineages diverged some 25 million years ago [50] and their genomes are 93–95% identical. This homology was exploited in RT-PCR cloning and in our genomic PCR survey of cynomolgus CD38. Indeed, human CD38 primers proved to be equally agile with CD38 in other members of the Primate order such as the chimpanzee, the gibbon (Hylobates concolor) and the rhesus monkey (Macaca mulatta) (MO, FS and SC, unpublished observations).
The conceptual translation of the cynomolgus macaque CD38 cDNA yielded a polypeptide with the characteristic type II structure, size, catalytic core residues and 12-cysteine ECD array common to CD38 orthologs. With respect to human CD38, cynomolgus CD38 has an extra residue in the transmembrane domain but no difference was found in the IC tail, where human CD38 is reported to interact with the SH2 domain of Lck [51] in lipid rafts [52].
Cross-reactivity of anti-human CD38 mAbs was exploited in the initial part of the protein analyses although these give discrepant results in binding to leukocytes from other primates. For example, OKT10, but not Leu17 or T16, binds bone marrow from rhesus macaques [44] whereas HIT2 stains horse lymphocytes but not leukocytes from baboon, cynomolgus macaque, rhesus macaque, pig, sheep, cow, dog, cat or rabbit [53]. In addition, the behaviour of cross-reactive mAbs may not be reproducible in another species as illustrated by anti-human CD34 mAbs: 6 out of 13 mAbs cross-reacted with cynomolgus bone marrow but only 3 of these correctly identified the functional cynomolgus equivalent of the human progenitor cell in clonogenic assays [54]. To avoid similar pitfalls, we raised mAbs to macaque CD38.
The apparent molecular weight of macaque and human CD38 were indistinguishable by SDS-PAGE. The macaque polypeptide weighs 34.4 kDa and has four N-linked glycosylation motifs, suggesting it is probably glycosylated, like human CD38 [55], to give rise to the 42 kDa band. We wanted to confirm this result with anti-cynomolgus CD38 mAbs but when lysates were probed with mAbs KK1B5 and KK9H4, the 42 kDa band was always accompanied by an 84 kDa band, and the doublet was also observed with lysates obtained from SL-999 macaque B cells expressing CD38 in its native milieu. The KK4E5 and KK6A11 mAbs instead detected only the 84 kDa band in transfectants, and the band was unaffected by addition of DTT. CD38 dimers and tetramers have been abundantly reported and postulated to be formed by diverse mechanisms such as intermolecular disulfides [12,51], non-covalent association [56] and transglutamination [9]. Therefore, our interpretation of the upper band is that it represents a CD38 dimer, possibly a non-covalently associated form compatible with lysate preparation in NP-40 detergent which stabilizes such dimers [56], or a transglutaminase-linked form. Although the data are consistent with KK4E5 and KK6A11 recognizing a unique epitope in macaque CD38 dimers, it is also possible that these mAbs have another unknown specificity and that further experiments are needed to fully characterize their specificity.
The availability of the macaque CD38 amino acid sequence and its alignment with the human homolog gave a new dimension to the analysis of mAb cross-reactivity and ultimately led to a better understanding of CD38 epitopes. Macaque and human CD38 are strikingly conserved yet only two of the four anti-macaque CD38 mAbs cross-reacted, as did only three of the six anti-human CD38 mAbs in reciprocal experiments. The key finding was that a mAb's capacity to cross-react always correlated with the sensitivity of its target to reduction which, added to the prior knowledge of the human CD38 epitope map, crystal structure and active site [57], allowed us to footprint the binding sites of cross-reactive anti-CD38 mAbs.
The classification of anti-primate CD38 mAbs as species-specific/DTT-resistant (type I) or cross-reactive/DTT-sensitive (type II) and directed against a conformational epitope may be of practical importance. Firstly, our results demonstrate the necessity for careful antibody selection when performing biological assays involving detection of CD38 expression in circumstances of cell membrane redox perturbation, e.g., detection of membrane CD38 in apoptotic cells might be positive according to type I mAbs and negative by type II (Alla Egorova, personal communication). Secondly, simultaneous use of the two types of mAbs can provide information about CD38 expression (type I) while the type II mAb can give indications on its conformation. Thirdly, it is possible that potent Ca2+-mobilizing agonistic mAbs are more likely to be type I mAbs since this subgroup includes IB4, which is the only anti-human CD38 mAb to mobilize Ca2+, and NIM-R5, a rat anti-murine CD38 mAb [58] which also mobilizes Ca2+ and whose binding to murine CD38 transfectants was not affected by DTT (EF, personal communication). Finally, autoantibodies to CD38 have been detected in diabetes and thyroiditis and it would be interesting to identify the epitopic culprits.
Conclusions
Some of the essential biological features of CD38 in Macaca fascicularis have been elucidated and new insights obtained about the epitopic structure of the CD38 ECD. We hope that, by providing the reagents for analysis of CD38 in the cynomolgus macaque, this study may expedite our understanding of the role of CD38 in human disease.
Methods
Cynomolgus CD38 cDNA cloning
PBMC were isolated by Ficoll-Paque PLUS (Amersham Biosciences) centrifugation from whole blood obtained from a female cynomolgus macaque housed according to state regulations at the RBM (Ivrea, Italy). Cells were cultured in medium with 5 μg/ml PHA (Sigma-Aldrich) for 72 h, harvested and resuspended in TRIzol RNA extraction solution (Invitrogen). RT-PCR was carried out using the Titan One Tube RT-PCR system (Roche Diagnostics) with 150 ng total RNA and the gene-specific primers derived from the human CD38 sequence (GenBank accession no. D84278): forward 5'-AGT TTC AGA ACC CAG CCA-3' (corresponding to nt -84 to -66 upstream of the ATG initiation codon); reverse 5'-ATT GAC CTT ATT GTG GAG G-3' (corresponding to nt 102–121 downstream of the TGA stop codon). After RT for 50°C for 30 min, the cDNA was amplified by two rounds of PCR: 5 min at 94°C, followed by 30 (first round) or 35 (second round) cycles at 94°C for 30 s, 54°C for 30 s and 2 min at 72°C. The product was gel purified and cloned into the pGEM-T Easy vector (Promega). The inserts of three recombinant clones were analyzed by automated sequencing (Applied Biosystems).
Analysis of simian genomic DNAs
Cynomolgus macaque (15 samples) and chimpanzee (5 samples) genomic DNAs were obtained as described [59]. The eight exons of the cynomolgus CD38 gene were amplified by PCR (45 cycles, annealing temp 52°C) using primers known to amplify human CD38 exons [41] while the CD38 promoter of cynomolgus macaque was amplified (15 cycles annealing at 52°C, followed by 35 cycles with 0.3°C touchdown) with a forward primer from the human CD38 promoter (5'-GAA GAG GCA AGA AAA GCC-3') and reverse primer chosen from macaque CD38 exon 1 (5'-AACTCG CAG TTG GCC ATA-3'). The chimpanzee CD38 promoter was amplified with the human CD38 sequences. The 5' end of cynomolgus CD38 intron 1 was amplified (same conditions used for exon amplification but 57°C annealing and 1.5 M MgCl2) with forward primer 5'-CCG TCC TGG CAC GAT GCG TCA AG-3' from macaque exon 1, and reverse primer 5'-ACA CCC TCC TCC CCT ACC ACA GG-3' taken from human CD38 intron 1. Amplicons were gel purified and analysed by automated sequencing. Alignments were performed with CLUSTALW (ExPASy, Swiss Institute of Bioinformatics).
Cell lines and antibodies
NIH/3T3 murine fibroblast and COS-7 monkey kidney cell lines were from the ATCC. Production of SL-691 and SL-999 cynomolgus B lymphoblastoid cell lines was previously described [60]. The mutant human CD38Δ285 plasmid [48] was kindly provided by Dr. Toshiaki Katada (University of Tokyo, Japan) while the MT2Δ285 transfectant was kindly provided by Dr. Umberto Dianzani (A. Avogadro University of Eastern Piedmont, Novara, Italy) [29]. Cells were maintained in RPMI 1640 medium with 10% heat-inactivated FCS, penicillin/streptomycin. The murine anti-human CD38 mAbs AT1 (hybridoma kindly provided by Dr. Jo Hilgers, BioProbe AV, Amstelveen, The Netherlands), SUN-4B7, OKT10, IB4, IB6 and HB7 were produced in-house from hybridoma culture supernatants. CBT3G, a murine anti-human CD3 mAb, was used as IgG control. F(ab')2 goat anti-mouse Ig-FITC was used as secondary antibody (Jackson ImmunoResearch Laboratories).
Expression of macaque and human CD38
cDNAs were cloned into pcDNA3.1/V5-His-TOPO expression vector (Invitrogen). Stable transfected cell lines were produced in NIH/3T3 by electroporation (250 V, 960 μF at 20°C), selected for 3–4 weeks in G418 after which isolated clones were picked and transferred to 96-well plates.
Ecto-GDPR cyclase activity
Ecto-GDPR cyclase activity of intact cells was determined as previously described [29,30,61]. Briefly, parental and transfected NIH/3T3 were used at 2.5 or 5 × 105 cells/ml in PBS. For RBCs, 420 μl packed volume were brought to 1 ml by addition of NGT buffer (0.15 M NaCl, 5 mM glucose, 10 mM Tris. Cl, pH 7.4). To 1 ml cell suspensions 10 μl 10 mM NGD (Sigma) in 20 mM Tris, pH 7.4 or 10 μl buffer (control) were added. After 30 min at 37°C, supernatants were collected after brief centrifugation. Supernatants were analysed by fluorescence spectrometer set at excitation wavelength 300 nm and emission wavelength 410 nm. Cell lines were measured in triplicate in three independent experiments; RBCs from two different animals were tested once; RBCs from humans were tested in duplicate in two independent experiments.
Western blotting
Cells were lysed in NP-40 buffer (150 mM NaCl, 1.0% NP-40, 50 mM Tris pH 8.0) containing protease inhibitors. Samples (20 μg protein/lane) were analysed by 8 or 10% SDS-PAGE and transferred to PVDF membranes (Bio-Rad Laboratories, Hercules, CA). Membranes were blocked in 5% milk/TBST, incubated for 2–3 h at RT with mAb supernatant with 1% milk, and incubated with horseradish peroxidase-labeled anti-mouse IgG (PerkinElmer) followed by ECL visualization.
Production of anti-cynomolgus macaque CD38 mAbs
BALB/c mice (Charles River Laboratories) were anaesthetized with Avertin i.p. injection and immunized by intrasplenic injection with 300 μl containing 5 × 105 live NIH/mac38 cells in PBS. Eight days later, mice received an i.p. boost of NIH/mac38 cells, and mouse sera tested 8 days later. The spleen of one mouse that responded to immunization was selected for fusion to P3.X63.Ag8.653 murine myeloma cell line. Hybridoma supernatants were screened for reactivity with the immunizing cells and lack of reactivity with the parental cell line. Positive hybridomas were cloned by limiting dilution. MAbs were used in the form of supernatants containing NaN3.
Analysis of surface CD38 expression
Surface expression of cynomolgus and human CD38 was determined by IF. Briefly, 2 × 105 cells/sample were incubated with 100 μl mAb supernatant/NaN3 for 1 h at 4°C, and 30 min at 4°C with FITC-labeled secondary Ab. Background fluorescence was established with control IgG antibody. Cells were analysed immediately either by fluorescence microscope, FACSCalibur flow cytometer (10,000 events acquired) with CellQuest software (Becton Dickinson) or Olympus FV3000 confocal microscope with Nomarski optics for differential interference contrast (DIC) and FluoView 300 software.
Modulation of surface CD38 by treatment with DTT
Cells were detached with 1 mM EDTA/PBS, washed and resuspended in complete medium at a concentration of 2 × 106 cells/ml. One hundred μl 100 mM DTT stock was added per ml cell suspension, kept for 45 min in a 37°C incubator and washed twice with PBS/BSA/NaN3 before analysis.
Authors' contributions
EF carried out cellular, biochemical and enzymatic analyses, devised the comparative epitope mapping and wrote the manuscript; MO cloned the cDNA and participated in the genomic DNA analyses; PV carried out mAb production and confocal microscopy, and participated in cellular and biochemical assays; EO carried out FACS analyses; SC participated in the genomic DNA analyses and contributed primate DNA samples; FS designed and participated in the cDNA and genomic DNA analyses; FT carried out expression analyses in macaques; FM designed and supervised mAb generation, and edited the manuscript. All authors read and approved the final manuscript.
Table 3 Inter-species cross-reactivity of anti-CD38 mAbs
Macaque CD38 Human CD38
MAbs native DTT native DTT
Anti-macaque CD38
KK1B5 + - + -
KK4E5 + + - -
KK6A11 + + - -
KK9H4 + - + -
Anti-human CD38
IB4 - - + +
IB6 - - + +
HB7 - - + +
AT1 + - + -
OKT10 + - + -
SUN-4B7 + - + -
Acknowledgements
This work was supported by the AIRC-Italian Association for Cancer Research; by a FIRB grant from the Italian Ministry for Universities, Instruction and Research; by the Special Project in Oncology funded by The Compagnia SanPaolo of Torino, Italy; by the Compagnia SanPaolo, by the Piedmontese Regional Government and by the FIRMS-International Foundation for Research in Experimental Medicine (Torino, Italy). We are very grateful to Dr. Emilio Parisini (Harvard Medical School) for the homology model of human CD38.
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| 15383153 | PMC524171 | CC BY | 2021-01-04 16:28:17 | no | BMC Immunol. 2004 Sep 21; 5:21 | utf-8 | BMC Immunol | 2,004 | 10.1186/1471-2172-5-21 | oa_comm |
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BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-4-381544779310.1186/1471-2180-4-38Research ArticlePrediction of DtxR regulon: Identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae Yellaboina Sailu 1sailu@cdfd.org.inRanjan Sarita 1sarita@cdfd.org.inChakhaiyar Prachee 2prachee@cdfd.org.inHasnain Seyed Ehtesham 2ehtesham@cdfd.org.inRanjan Akash 1akash@cdfd.org.in1 Computational and Functional Genomics Group, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500076, INDIA2 Laboratory of Cellular and Molecular Biology, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500076, INDIA2004 24 9 2004 4 38 38 8 4 2004 24 9 2004 Copyright © 2004 Yellaboina 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 diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae.
Result
Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG), an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps) which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin.
Conclusions
We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae. Our analysis shows that DtxR could provide a molecular link between Fe+2-induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe+2 and H2O2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase, a potential vaccine candidate and proteins of secretory system.
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Background
Iron is an important inorganic component of a cell. Iron is required as co-factor for various essential enzymes and proteins some of which are involved in electron transport (Cytochromes), redox reactions (oxidoreductases) and regulation of gene expression (fumarate-nitrate reduction regulatory protein, iron-binding protein) [1]. However a higher level of intracellular iron can catalyze formation of hydroxyl radicals and reactive oxygen species through Fenton's reaction which could be lethal to the cell [2]. Hence, a careful regulation of iron-requiring enzymes/proteins and iron uptake proteins/enzymes is required for the survival of bacteria.
Inorganic iron is also known to influence virulence in many pathogenic bacteria such as Corynebacterium diphtheriae, Escherichia coli, and Bordetella bronchiseptica [3-5]. The diphtheria toxin repressor DtxR is known as an iron-activated global transcription regulator that represses the transcription of various iron-dependent genes in C. diphtheriae [6,7]. Eight DtxR-binding sites in upstream sequences of operons/genes named as tox, hmuO, irp1, irp2, irp3, irp4, irp5 and irp6 have been identified by DNA footprinting methods [6]. The product of tox gene is diphtheria toxin which catalyzes the NAD-dependent ADP ribosylation of eukaryotic aminoacyl-transferase-II, thereby causing inhibition of protein synthesis and subsequent death of the host. The hmuO gene, which encodes a haem oxygenase, oxidizes the haem to release free iron. The operons irp1 and irp6 encode the products with homology to ABC-type ferric-siderophore transport systems. The gene irp3 encodes a homologue of AraC-type transcriptional activators. The products of irp2, irp4 and irp5 do not show any homology to the other known proteins. In addition, C. diphtheriae with inactive DtxR has been shown to be sensitive to killing by exposure to high iron conditions or hydrogen peroxide than the wild type [8].
This work uses an in silico method to identify additional DtxR-binding sites and target genes to understand the role of DtxR in virulence and patho-physiology of C. diphtheriae.
Results
In silico identification of putative DtxR-binding sites
Experimentally characterized DtxR-binding motifs were collected from the literature (Table 1). These binding sites were used to identify additional putative DtxR-binding sites along with associated operons in C. diphtheriae NCTC13129 genome (see materials and methods). Table 2 shows the predicted DtxR-binding sites with score 3.7438 or more. We could identify five (tox, irp4, irp5, irp6 and hmuO) of the eight known DtxR-binding sites, in sequenced C. diphtheriae NCTC13129 genome. We could not find irp1 and irp2 motifs as the corresponding genes (irp1, irp2) are not present in the sequenced strain NCTC13129 [9]. The regulator binding sites of irp3, irp4 and irp6 genes in the strain NCTC13129 shows one base change from the binding sites reported in strain C7 [6]. Binding site of irp3 gene (TTAGGTGAGACGCACCCAT) although exists in strain NCTC13129, but not there in the predicted sites, because it is located within the coding region of irp3 ORF. The predicted ORF of irp3 in the sequenced strain NCTC13129 has different start position and is larger than what was previously reported in strain C7 [9,10].
In addition, we have identified binding sites in upstream sequences of eight genes recently reported to be regulated by DtxR [7]. However, our prediction differs from the previous report for five (secY, deoR, chtA, frgA, sidA) of the seven sites which were identified by BLAST search (Table 2). Our prediction agreed with the previous report that the genes such as recA (DIP1450) and ywjA (DIP1735) are not under a direct DtxR regulation as we could not detect any motif upstream to these gene with scores above the cutoff value [7].
Experimental validation of predicted binding sites
Since our approach to identify DtxR-regulated genes is purely computational in nature, we decided to test the validity of our predictions. A sample of predicted regulator binding motifs (Table 2) (upstream to ORFs: DIP2161, DIP0699, DIP0586, DIP2304, DIP2272) were experimentally verified by EMSA using IdeR, an orthologue of DtxR from M. tuberculosis. DtxR and IdeR are iron-dependent regulators. A pair wise sequence comparison of the two proteins shows a high (58%) overall sequence identity (similarity 72%) which increases further to 92% identity and 100% similarity in DNA recognition domain. In addition, the structural comparison of two regulators also shows a very similar 3D organization, suggesting that the IdeR regulator would be able to recognize the DtxR motif [11].
Synthetic double stranded oligonucleotides corresponding to DNA-binding sites were labeled with 32P and mixed with purified IdeR in presence of manganese ions and was assayed for the formation of DNA-protein complex using EMSA. Manganese was used as the divalent metal in the binding reactions on account of its redox stability compared with ferrous ion. Electrophoretic mobility of all five double stranded oligonucleotides tested was retarded by IdeR (Figure 1). However a synthetic motif (TTTTCATGACGTCTTCTAA) used as a negative control did not show any complex formation. These results indicate that the predicted DtxR-binding sites can indeed bind to DtxR.
Identification and annotation of DtxR-regulated genes C. diphtheriae genome
In addition to the binding site prediction, we have also identified co-regulated genes (operons) downstream to the predicted DtxR-binding site (Table 3). Function of the proteins encoded by the putative genes in Table 2 and Table 3 was predicted by RPS-BLAST search against conserved domain database [12].
Discussion
Our analysis identified putative DtxR motifs upstream to various operons/genes which could be involved in siderophore biosynthesis, ABC-type transport systems, iron storage, oxidative stress defense and iron-sulfur cluster biosynthesis. In addition, we have also identified the motifs upstream of operons that could be involved in anchoring of host-interacting proteins to the cell wall and secretion of various virulence factors. Important functions of some of these DtxR-regulated genes and their role in C. diphtheriae physiology are discussed here.
Regulation of siderophore biosynthesis and ABC-type transport systems
Predicted member of the DtxR regulon, the gene DIP0586, codes for the IucA/IucC family of enzymes that catalyze discrete step in the biosynthesis of the aerobactin [13]. In addition to known DtxR-regulated siderophore transport genes (irp1, irp6), DtxR could also regulate other ABC-type transport systems similar to Manganese/Zinc, peptide/Nickel and multidrug subfamilies of ABC transporters. The peptide/nickel transport system (DIP2162-DIP2165) has been suggested to be recently acquired by pathogenic C. diphtheriae [9].
Regulation of iron storage and oxidative stress defense
We predict that DtxR could regulate divergently transcribed genes DIP2303 and DIP2304 whose products are similar to starvation inducible DNA-binding protein (Dps) and Formamidopyrimidine-DNA glycosylase (Fpg), respectively. Dps in Escherichia coli is induced in response to oxidative or nutritional stress and protects DNA from oxidative stress damage by nonspecific binding [14]. Dps also catalyzes oxidation of ferrous iron to ferric iron by hydrogen peroxide (2Fe2+ + H2O2 + 2H2O → 2Fe+3OOH(core) + 4H+) which in turn prevents hydroxyl radical formation by Fenton's reaction (Fe2+ + H2O2 → Fe+3 + HO- + HO.) and thereby prevents subsequent DNA damage [15]. The enzyme, formamidopyrimidine-DNA glycosylase is a primary participant in the repair of 8-oxoguanine, an abundant oxidative DNA lesion [16]. The gene DIP1510 which codes for the site-specific recombinase XerD could also be regulated by DtxR. The xerD gene in E. coli belongs to the oxidative stress regulon [17].
Regulation of proteins involved in iron-sulfur cluster biosynthesis and iron-sulfur cluster containing proteins
We predict that the operon DIP1288-DIP1296, which is similar to the suf operon of E. coli, could be regulated by DtxR. The suf operon in bacteria encodes the genes for Fe-S cluster assembly machinery [18]. In addition, genes encoding the iron-sulfur containing proteins such as succinate dehydrogenase (Sdh), cytochrome oxidase (CtaD) and Ribonucleotide reductase (NrdF1) in C. diphtheriae also show DtxR motif in their upstream sequences.
Regulation of sortases
We predict that DtxR could regulate the recently acquired pathogenic island DIP2271-DIP2272, encoding the sortase srtA and hypothetical protein, respectively [9]. Sortases are membrane-bound trans-peptidases that catalyze the anchoring of surface proteins to the cell wall peptidoglycan [9]. Such systems are often used by gram-positive pathogens to anchor host-interacting proteins to the bacterial surface [19].
Regulation of protein translation and translocation system
DtxR could regulate two operons that contain genes DIP0699 (secA) and DIP0540 (secY) that code for the protein translocation system. The secY-containing operon, which is similar to the streptomycine operon spc from B. subtilis and other bacteria, involves the genes required for protein translation and translocation [20]. The operon contains additional sialidase gene (DIP0543) in comparison to non pathogenic Corynebacterium species. Activity of sialidase has been linked to virulence in several other microbial pathogens and may enhance fimbriae mediated adhesion in Corynebacterium diphtheriae by unmasking receptors on mammalian cells [9].
The Sec system can both translocate proteins across the cytoplasmic membrane and insert integral membrane proteins into it. The former proteins but not the latter possess N-terminal, cleavable, targeting signal sequences that are required to direct the proteins to the Sec system. Some of the DtxR-regulated genes including diphtheria toxin (Table 4) show predicted signal sequences by SignalP 3.0 [21] and hence they may play an important role in host interaction and virulence of Corynebacterium diphtheriae [9].
Conclusions
The bioinformatics method used to predict the targets of DtxR in C. diphtheriae NCTC13129 genome is promising, as some of the predicted targets were experimentally verified. The approach identified novel DtxR-regulated genes, which could play an important role in physiology of C. diphtheriae NCTC13129. DtxR, generally known as a repressor of diphtheriae toxin and iron siderophore/transport genes, can also regulate other metal ion transport genes, iron storage, oxidative stress, DNA-repair, biosynthesis of iron-sulfur cluster, Fe-S-cluster containing proteins, and even protein sortase and translocation systems.
Methods
Source of genome sequence
The complete genome sequence of C. diphtheriae was downloaded from NCBI ftp site [22], and the DtxR-binding sites identified by experimental methods were collected from literature [6,10,25-27].
Prediction of DtxR-binding sites
DtxR-binding site recognition profile was calculated by positional Shannon relative entropy method [23,24]. The positional relative entropy Qi at position i in a binding site is defined as
where b refers to each of the possible base (A, T, G, C), fb,i is observed frequency of each base at position i and qb is the frequency of base b in the genome sequence. The contribution of each base to the positional Shannon's relative entropy is calculated by multiplying positional frequency of each base with positional relative entropy. The binding site profile thus generated was used to scan upstream sequences of all the genes of the Corynebacterium diphtheriae genome. The score of each site is calculated as the sum of the respective positional Shannon relative entropy of each of the four possible bases. A maximally scoring site is selected from the upstream sequence of each gene. The lowest score among the input binding sites is considered as cut-off score. The sites scoring higher than the cut-off value are reported as potential binding sites conforming to the consensus sequence.
Prediction of operons
Co-directionally transcribed genes, downstream to the predicted binding site were selected as potential co-regulated genes (operons) according to one of the following criteria (a) Co-directionally transcribed orthologous gene pairs, conserved in at least 4 genomes; (b) genes belong to the same cluster of orthologous gene function category and the intergenic distance is less than 200 base pairs; (c) the first three letters in gene names are identical (gene names for putative genes were assigned from COG database); (d) intergenic distance is less than 90 base pairs [24].
Functional assignment of genes
The function of predicted genes was inferred using the RPS-BLAST search against conserved domain database [12]. These genes were further classified according to their function.
Expression and purification of IdeR
The iron-dependent regulator IdeR from M. tuberculosis was expressed from a recombinant pRSET vector containing the IdeR gene fused to a six His affinity tag (P. Chakhiyar unpublished). The expressed protein was first purified using Ni-NTA Metal Chelate Affinity chromatography; later it was desalted and concentrated using Centricon Ultra filtration device. The concentration of the recombinant protein was estimated using Bradford method.
Electrophoretic mobility shift assay
Double-stranded oligonucleotides containing the predicted binding motif (19 bp long) were end labeled with T4 polynucleotide kinase and [γ32P]-ATP and were incubated with the recombinant purified IdeR protein in a binding reaction mixture. The binding reaction mixture (20-μl total volume) contain the DNA-binding buffer (20 mM Tris-HCl [pH 8.0], 2 mM DTT, 50 mM NaCl, 5 mM MgCl2, 50% glycerol, 5 μg of bovine serum albumin per ml), 10 μg of poly(dI-dC) per ml (for nonspecific binding) and 200 μM MnCl2. The reaction mixture was incubated at room temperature for 30 min. Approximately 2 μl of the tracking dye (50% sucrose, 0.6% bromophenol blue) was added to the reaction mixture at the end of incubation and was loaded onto 7% polyacrylamide gel containing 150 μM MnCl2 in 1 × Tris-borate-EDTA buffer. The gel was electrophoresed at 200 V for 2 hours. Subsequently the gel was dried and exposed to Fuji Storage Phosphor Image Plates for 16 hours. The image plates were subsequently scanned in Fuji Storage Phosphor Imaging workstation.
List of abbreviations
DtxR – Diphtheria toxin repressor; IdeR – Iron-dependent regulator; Dps – DNA-binding protein from starved cells; RPS-BLAST – Reversed Position Specific – Basic Local Alignment Search Tool; EMSA – Electrophoretic Mobility Shift Assay
Authors' contributions
SY: carried out the computation, data analysis, and manuscript preparation. SR: Carried out the EMSA and drafted the manuscript. PC: provided the cloned IdeR construct, drafted the manuscript. SH: Manuscript preparation and coordination. AR: Design of the study and coordination. All authors read and approved the final manuscript.
Acknowledgements
This work is partially supported by CSIR NMITLI Grant to AR. SR is supported by CSIR NMITLI Grant. YS and PC is supported by CSIR Research Fellowships.
Figures and Tables
Figure 1 IdeR binds the predicted DtxR-binding DNA fragments. 30 pmoles of IdeR was added to 32P-labelled DNA probes in the presence of 200 μM Mn2+, and complexes were resolved on a 7% Tris-borate polyacrylamide gel containing 150 μM Mn2+. Lane 1: Control gel retardation using Radiolabeled DNA motif without DtxR-binding site. Lane 2: Radiolabeled DIP2161 motif without IdeR. Lane 3: Radiolabeled DIP2161 motif with IdeR. Lane 4: Radiolabeled DIP0699 motif with IdeR. Lane 5: Radiolabeled DIP0586 motif with IdeR. Lane 6: Radiolabeled DIP2304 motif with IdeR. Lane 7: Radiolabeled DIP2272 motif with IdeR.
Table 1 Known DtxR-binding sites from C. diptheriae
Binding site Gene Product Reference
TTAGGATAGCTTTACCTAA tox Diphtheria toxin [25]
TTAGGTTAGCCAAACCTTT Irp1 Periplasmic protein of siderophore transport system [26]
GCAGGGTAGCCTAACCTAA Irp2 Hypothetical protein [26]
TTAGGTGAGACGCACCCAT Irp3 AraC-type transcription regulator [10]
ATTACTAACGCTAACCTAA Irp4 Hypothetical protein [10]
CTAGGATTGCCTACACTTA Irp5 Hypothetical protein [10]
TTTCCTTTGCCTAGCCTAA Irp6 Periplasmic protein of siderophore transport system [6]
TGAGGGGAACCTAACCTAA hmuO Haem oxygenase [27]
Table 2 Predicted DtxR-binding sites in C. diphtheriae
Score Position Site Gene Synonym Product
4.45904 -80 TGAGGGGAACCTAACCTAA hmuO DIP1669** heme oxygenase
4.39003 -52 TTAGGATAGCTTTACCTAA Tox DIP0222** Diphtheria toxin precursor
4.25877 -60 ATAGGCTACACTTACCTAA - DIP0624 Putative membrane protein
4.21068 -168 TTGGATTAGCCTACCCTAA - DIP2162** ABC-type peptide transport system periplasmic component
4.2033 -21 TTAGGGTAGCTTCGCCTAA iucA DIP0586 Putative siderophore biosynthesis related protein
4.17632 -78 ATAGGCATGCCTAACCTCA - DIP2330 Putative membrane protein
4.07921 -130 TTAGGTCAGGGTACCCTAA - DIP0370 Putative succinate dehydrogenease cytochrome B subunit
4.03559 -30 TTAGCTTAACCTTGCCTAT arsR DIP0415 Putative ArsR family regulatory protein
4.01967 -239 TTAGGGTAGGCTAATCCAA sidA* DIP2161 nonribosomal peptide synthase
3.99985 -74 TTTTCTTTGCCTAGCCTAA irp6A DIP0108** Ferrisiderophore receptor Irp6A
3.99195 -241 TTAGGCACCCCTAACCTAG - DIP0539 Putative sugar ABC transport syste ATP-binding protein
3.98554 -72 TTAGCTTAGCCCTAGCTAA - DIP0169 Putative secreted protein
3.9296 -26 CTAGGATTGCCTACACTTA Irp5 DIP0894** Conserved hypothetical protein
3.9073 -93 GTTGGGTTGCCCAACCTAC - DIP2106 Putative ABC transport system, ATP-binding subunit
3.89763 -86 ATAGGTTAGGTTAACCTTG chtA* DIP1520 Putative membrane protein
3.89676 -130 TTGTGTTAGCCTAGGCTAA secA DIP0699 Translocase protein
3.89169 -26 TTGGGGTGGCCTATCCTTA - DIP2304 Putative DNA-repair glycosylase
3.88042 -172 TTAGGTAAGTGTAGCCTAT htaA* DIP0625 Putative membrane protein
3.86534 -69 ATTACTAATGCTAACCTAA Irp4 DIP2356** Putative conserved membrane protein
3.85539 -173 TTAGGGTGGGCTAACCTGC deoR* DIP1296 Putative DNA-binding protein
3.84889 -75 TTAGGGAACTCTTGCCTTA piuB* DIP0124 Putative membrane protein
3.83816 -121 TTAGCTAGGGCTAAGCTAA - DIP0168 Putative glycosyl transferase
3.83576 -219 GTAACAAAGGCAAGCCTAA xerD DIP1510 Putative integrase/recombinase
3.8224 -216 ATAGGCAAGGTTAAGCTAA - DIP0417 Putative membrane protein
3.81905 -47 GTTGGACAGGTTACCCTAA frgA* DIP1061 Putative iron-siderophore uptake system permease
3.8148 -37 TGTGGGCACACCAACCTAA - DIP2272 possible sortase-like protein
3.76235 -136 TTGGGGTTGCCCTTCCTAA - DIP0142 Hypothetical protein
3.76233 -268 CTAGGTTAGGGGTGCCTAA secY* DIP0540 preprotein translocase SecY subunit
3.74673 -110 TAAACATAGCCAAACCAAA nrdF1 DIP1865 ribonucleotide reductase beta-chain 1
3.7438 -81 TAAGGATAGGCCACCCCAA Dps DIP2303 Starvation inducible DNA-binding protein
Note: **Indicate the gene synonym with experimentally identified binding site in C. diphtheriae [6]. * Indicates the genes known to be regulated by DtxR [7]. The binding sites in Italics were verified by EMSA. The gene pairs, DIP0624-DIP0625, DIP2161-DIP2162, DIP0168-DIP0169, DIP0539-DIP0540 and DIP2303-DIP2304 are divergently transcribed and contain common regulatory regions.
Table 3 Predicted DtxR-regulated operons in C. diphtheriae
Synonym Gene Orthologue Product
DIP2158 COG1131 ABC-type transport system permease and ATPase component
DIP2159 COG1131 ABC-type transport system permease and ATPase component
DIP2160 - COG3321 Polyketide synthase modules and related proteins
DIP2161* - COG1020 Non-ribosomal peptide synthetase modules and related proteins
DIP0586 iucA Pfam04183 Catalyse discrete steps in biosynthesis of the siderophore aerobactin
DIP0587 - - Putative membrane protein
DIP0588 - - Putative membrane protein
DIP1059 fepC COG1120 ABC-type cobalamin/Fe3+-siderophores transport systems
DIP1060 fepG COG4779 ABC-type enterobactin transport system
DIP1061* fepD COG0609 ABC-type Fe3+-siderophore transport system
DIP2162 ddpA COG0747 ABC-type peptide transport system periplasmic component
DIP2163 ddpB COG0601 ABC-type peptide/nickel transport systems permease components
DIP2164 ddpC COG1173 ABC-type peptide/nickel transport systems permease components
DIP2165 dpdD COG0444 ABC-type peptide/nickel transport systems ATPase component
DIP0169 lraI COG0803 ABC-type metal ion transport system, periplasmic component
DIP0170 znuC COG1121 ABC-type Mn/Zn transport systems, ATPase component
DIP0171 znuB COG1108 ABC-type Mn2+/Zn2+ transport systems, permease components
DIP0172 znuB COG1108 ABC-type Mn2+/Zn2+ transport systems, permease components
DIP0173 lraI COG0803 ABC-type metal ion transport system, periplasmic component
DIP2106 mdlB COG1131 ABC-type multidrug transport system, ATPase and permease component
DIP2107 mdlB COG1131 ABC-type multidrug transport system, ATPase and permease component
DIP0625 htaa Pfam04213 Haemin transporter associated protein
DIP0626 hmuT COG4558 ABC-type haemin transport system
DIP0627 hmuU COG0609 ABC-type Fe3+-siderophore transport system
DIP0628 hmuV COG4559 ABC-type haemin transport system
DIP0629* htaa Pfam04213 Haemin transporter associated protein
DIP1519* htaa pfam04213 Haemin transporter associated protein
DIP1520* htaa pfam04213 Haemin transporter associated protein
DIP2303 dps COG0783 Starvation inducible DNA-binding protein
DIP2304 - COG0266 Formamidopyrimidine-DNA glycosylase
DIP2305 - COG0063 Predicted sugar kinase
DIP1510 xerD COG4974 Site-specific recombinase
DIP1288 - - Conserved hypothetical protein
DIP1289 uup COG0488 ATPase components of ABC transporters with duplicated ATPase domains
DIP1290 - COG2151 Predicted metal-sulfur cluster biosynthetic enzyme
DIP1291 iscU COG0822 NifU homolog involved in Fe-S cluster formation
DIP1292 csd COG0520 Selenocysteine lyase
DIP1293 sufC COG0396 ABC-type transport system involved in Fe-S cluster assembly
DIP1294 - COG0719 ABC-type transport system involved in Fe-S cluster assembly
DIP1295 sufB COG0719 ABC-type transport system involved in Fe-S cluster assembly
DIP1296* deoR COG2345 DeoR family transcriptional regulator
DIP0370 - - Putative succinate dehydrogenease (cytochrome b)
DIP0371 - COG1053 Succinate dehydrogenase/fumarate reductase
DIP0372 - COG0479 Succinate dehydrogenase/fumarate reductase
DIP0373 - - Putative membrane protein
DIP0374 - - Putative membrane protein
DIP0375 - - Putative membrane protein
DIP0376 - - Putative membrane protein
DIP0377 - - Putative membrane protein
DIP1864 ctaD COG0843 Heme/copper-type cytochrome/quinol oxidases
DIP1865 nrdF1 COG0208 Ribonucleotide reductase
DIP2330 - - Putative membrane protein
DIP2331 - COG1012 NAD-dependent aldehyde dehydrogenases
DIP0124* - Pfam03929 Uncharacterized iron-regulated membrane protein (DUF337)
DIP0622 - - Putative membrane protein
DIP0623 metA COG2021 Homoserine acetyltransferase
DIP0624 - - Putative membrane protein
DIP0415 - Pfam01022 Bacterial regulatory protein
DIP0539 - COG3839 ABC-type sugar transport systems
DIP0168 - - Putative glycosyl transferase
DIP0417 - - Putative membrane protein
DIP0142 - - Hypothetical protein
DIP0143 - - -
DIP0144 tra8 COG2826 Transposase and inactivated derivatives
DIP2271 - - Putative membrane protein
DIP2272 - COG3764 Sortase (surface protein transpeptidase)
DIP0699 secA COG0653 Preprotein translocase subunit SecA (ATPase
DIP0700 - - Hypothetical protein
DIP0540* secY Pfam00344 Eubacterial secY protein
DIP0541 Adk COG0563 Adenylate kinase and related kinases
DIP0542 mapA Methionine aminopeptidase
DIP0543 - - Sialidases or neuraminidases;
DIP0544 erfK Pfam03734 This family of proteins contains a conserved histidine and cysteine
DIP0545 infA COG0361 Translation initiation factor 1 (IF-1)
DIP0546 rpsM COG0099 Ribosomal protein S13
DIP0547 rpsK COG0100 Ribosomal protein S11
DIP0548 rpsD COG0522 Ribosomal protein S4 and related proteins
DIP0549 rpoA COG0202 DNA-directed RNA polymerase
DIP0550 rplQ COG0203 Ribosomal protein L17
DIP0551 truA COG0101 Pseudouridylate synthase
Note: * Indicate the genes reported be regulated by DtxR. Genes listed together belongs to same operon.
Table 4 DtxR-regulated genes containing the potential signal sequence
Gene Product
DIP0222 Diphtheria toxin
DIP0109 IRP6B
DIP2356 IRP4
DIP2162 ABC-type peptide transport system periplasmic component
DIP0172 Putative membrane protein
DIP2107 Putative integral membrane transport protein
DIP0625 Haemin transporter associated protein
DIP0626 ABC-type haemin transport system
DIP0627 ABC-type haemin transport system
DIP1519 Haemin transporter associated protein
DIP0629 Haemin transporter associated protein
DIP1520 Haemin transporter associated protein
DIP2330 Putative membrane protein
DIP0543 Sialidases or neuraminidases
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| 15447793 | PMC524172 | CC BY | 2021-01-04 16:03:38 | no | BMC Microbiol. 2004 Sep 24; 4:38 | utf-8 | BMC Microbiol | 2,004 | 10.1186/1471-2180-4-38 | oa_comm |
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BMC NeurosciBMC Neuroscience1471-2202BioMed Central London 1471-2202-5-381545857310.1186/1471-2202-5-38Research ArticleEnhancement of blood-tumor barrier permeability by Sar-[D-Phe8]des-Arg9BK, a metabolically resistant bradykinin B1 agonist, in a rat C6 glioma model Cardoso Ronie Cleverson 1roniecardoso@hotmail.comLobão-Soares Bruno 23brunolobao@rnp.fmrp.usp.brBianchin Marino Muxfeldt 3mmbianchin@rnp.fmrp.usp.brCarlotti Carlos Gilberto Jr4carlotti@fmrp.usp.brWalz Roger 256rogerwalz@hotmail.comAlvarez-Silva Márcio 2malvarez@ccb.ufsc.brTrentin Andréa Gonçalves 3atrentin@ccb.ufsc.brNicolau Mauro 1mnicolau@mbox1.ufsc.br1 Departamento de Fisiologia, Universidade Federal de Santa Catarina, Brazil2 Departamento de Biologia Celular, Embriologia e Genética, Universidade Federal de Santa Catarina, Brazil3 Departamento de Neurologia, Psiquiatria e Psicologia Médica, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, São Paulo, Brazil4 Departamento de Cirurgia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, São Paulo, Brazil5 Centro de Cirurgia de Epilepsia, Hospital Governador Celso Ramos, Florianópolis, Santa Catarina, Brazil6 Centro de Ciências da Saúde, Faculdade de Medicina da Universidade do Vale do Itajaí, UNIVALI, Itajaí, Santa Catarina, Brazil2004 30 9 2004 5 38 38 11 6 2004 30 9 2004 Copyright © 2004 Cardoso 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 it is well known that bradykinin B2 agonists increase plasma protein extravasation (PPE) in brain tumors, the bradykinin B1 agonists tested thus far are unable to produce this effect. Here we examine the effect of the selective B1 agonist bradykinin (BK) Sar-[D-Phe8]des-Arg9BK (SAR), a compound resistant to enzymatic degradation with prolonged activity on PPE in the blood circulation in the C6 rat glioma model.
Results
SAR administration significantly enhanced PPE in C6 rat brain glioma compared to saline or BK (p < 0.01). Pre-administration of the bradykinin B1 antagonist [Leu8]-des-Arg (100 nmol/Kg) blocked the SAR-induced PPE in the tumor area.
Conclusions
Our data suggest that the B1 receptor modulates PPE in the blood tumor barrier of C6 glioma. A possible role for the use of SAR in the chemotherapy of gliomas deserves further study.
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Background
Bradykinin (BK) is a vasoactive peptide released from its high molecular weight precursors, the kininogens, through the action of serine proteases, the kallikreins, playing a crucial role in pathologic processes like inflammation, infectious diseases, and cancer [1,2]. The brain and spinal cord contain all of the components necessary for kinin formation and action. In addition, central nervous system traumas lead to kinin formation [3]. BK type-1 (B1) receptors are mostly expressed in pathological or stressful situations related to tissue damage [1,2] including tumors [2]. The BK type-2 (B2) receptor is defined as a constitutive one, being normally encountered in many tissues, including the brain [2,4]. It is well known that the blood-brain barrier (BBB) in brain tumor regions (also called blood tumor barrier, or BTB) shows different plasma protein extravasation (PPE) characteristics when compared with the BBB of normal brain tissue and this effect is particularly related to the increase of B2 receptors [5-7]. In animal models, B2 receptor agonists like Cereport® (RMP-7) have been used by the intracarotid route to enhance the delivery of chemotherapeutic agents to the brain tumor area [7-9]. B1 receptor agonists with low metabolic resistance (MR) have already been unsuccessfully tested on PPE extravasation through the BTB in brain tumors [8,9]. The B1 receptor agonist, Sar-[D-Phe8]des-Arg9BK (SAR), shows some resistance to enzymatic degradation that is due to the addition of amino acids to the amino-terminal portion of the molecule [10]. Thus, it is possible that SAR could be successful in promoting PPE through the BTB, having potential uses in enhancing the delivery of chemotherapeutic agents to brain tumors. In order to test this hypothesis, we investigated the effect of SAR on PPE using the rat C6 glioma model [11].
Results
Eighty percent of C6-inoculated animals developed brain tumors after a period of 30 days (data not shown). We determined PPE in experimental groups of animals treated with bradykinin (BK), the BK receptor B1 agonist (SAR) or the BK receptor B1 antagonist (LEU) (Fig. 1). PPE in the tumor area of C6-inoculated animals was 22.8 ± 6.4 μg EB/g dry tissue, a value that did not differ from those observed in tumor-free animals inoculated with vehicle only (26.3 ± 16.7 μg EB/g dry tissue), or inoculated with cell vehicle plus SAR (23.2 ± 9.8 μg EB/g dry tissue). Injection of BK into C6-inoculated animals also did not change the tumor PPE (30.6 ± 10.9 μg EB/g dry tissue). It is important to note that in all groups the left (non-inoculated) hemispheres presented PPE values similar to those of the right (inoculated) hemisphere in the control animals. However, SAR significantly increased PPE in the tumor area of C6-inoculated animals (91.9 μg EB/g dry tissue ± 7.9) (p < 0.01). This effect was abolished, with a return to basal levels, by pre-treatment of the animals with the BK receptor B1 antagonist LEU (35.8 ± 8.6 μg EB/g dry tissue). The effect of SAR in increasing PPE in C6-inoculated right hemispheres (91.9 μg EB/g dry tissue ± 7.9) was also observed (t = 24.9, p < 0.001) when compared to the contralateral non-tumoral hemisphere (21.7 μg EB/g dry tissue ± 3.0, n = 6) (Fig. 2).
Discussion
We demonstrate here that the selective B1 receptor agonist SAR [16] enhances PPE in C6 glioma without affecting the normal brain parenchyma. It has been previously shown that SAR at 100 nmol/Kg also does not alter the systemic blood pressure of rats [17]. The effect of SAR was blocked by pre-treatment with the selective B1 receptor antagonist LEU, suggesting that PPE can be modulated by B1 receptors in the glioma model of C6-inoculated rats.
It was recently described that gliomas may express both B1 and B2 BK receptors, with B2 being located closer to the periphery of the tumor cells while B1 was observed throughout the cell [18]. In view of their effects on vascular dilatation and blood flow, bradykinin receptor agonists have been tested in the chemotherapy of brain tumors [18,19], whereas bradykinin itself was less used for this purpose [6,7] due to its lower efficacy and shorter blood half-life. In contrast to other authors [6,9] we did not observe an effect of BK by itself in enhancing BBB or BTB permeability. Fast BK degradation could account for this difference since we used a femoral vein, whereas other authors used more proximal accesses like the carotid artery [6,9]. The B2 receptor agonist RMP-7 (Cereport®) has been successfully employed to enhance BTB permeability to chemotherapeutic agents [7,20], but in the animal models already tested only local or regional routes like the carotid artery were used [20,21].
In general, B1 receptors are non-constitutive [3] and restricted to pathologic processes including tumors or degeneration [2]. Systemically administered metabolically resistant B1 receptor agonists may be useful to increase chemotherapy levels at the target site, with higher specificity and lower toxicity than B2 receptor agonists. Thus, we believe that SAR injected together with chemotherapeutic agents may be useful to increase drug delivery specifically to the brain tumor with less toxicity to non-affected areas. Additionally, because EB circulates bound to albumin, it is reasonable to think that SAR could increase the delivery of several chemotherapeutic agents of molecular weight similar to, or lower than that of albumin [22,23]. Although the Evans Blue method is less sensitive than other labeling methods like quantitative autoradiography, for example, we used it because it was the only method available to us at the time of this experiment. However, the Evans-Blue method is of low cost, can be easily reproduced by other laboratories, and was sensitive enough to detect differences provoked by SAR in these experiments.
BK or BK agonists have been previously used to increase BTB permeability but, due to their faster enzymatic degradation [6,8], they were injected into the carotid artery. However, our findings suggest, that SAR administered intravenously remains stable and thus could be an attractive agent for the treatment of brain or even other tumors [24,25] that express BK B1 receptors.
Conclusions
Our data suggest that the B1 receptor modulates PPE in the blood tumor barrier of C6 glioma. A possible role for the systemic use of SAR in the chemotherapy of gliomas or other CNS neoplasms deserves further study.
Methods
C6 glioma cell culture
The C6 rat glioma cell line was cultured as previously described [12]. Briefly, cells were grown in Dulbecco's modified Eagle medium (DMEM, Sigma, Saint Louis, MO, USA) supplemented with 5% fetal calf serum (FCS, Cultilab, Brazil), 100 mg/ ml streptomycin and 100 U/ ml penicillin (all from Sigma) under standard culture conditions. Cells were harvested with 0.125% trypsin/0.78 mM EDTA when they reached confluence.
Animals and tumor inoculation
Male Wistar rats (aged 3 months and weighing 250–300 g upon arrival from the UFSC Central Animal House) were used. The rats were maintained in a temperature- and light-controlled vivarium (22°C; 12:12-h light:dark cycle; lights on at 07:00 h), with food and water available ad libitum. Animals were treated according to the Guidelines for the Use of Animals of Universidade Federal de Santa Catarina. Before the procedures, the rats were anesthetized with sodium pentobarbital (50 mg/Kg body weight, i.p.) and then injected with 1 × 106 C6 cells prepared in 5 ml DMEM/FCS (vehicle) into the right cerebral hemisphere using the following coordinates: 4 mm lateral from right bregma and 4.5 mm deep from the dural surface, as previously described [14].
Pharmacological treatment and protein plasma extravasation (PPE) studies
Seventeen days after C6 inoculation, BBB or BTB extravasations were assessed by the Evans blue (EB, Sigma) method [14]. EB (20 mg/Kg; 25 mg/ml in 0.9% NaCl) was administered intravenously via a femoral vein with saline (n = 10, C6-inoculated; n = 6, control) or in combination with 100 nmol/Kg bradykinin (RBI, USA) (n = 6, C6-inoculated) or with 100 nmol/kg of selective bradykynin B1 agonist Sar-[D-Phe8]des-Arg9BK (n = 9, C6 inoculated; n = 6, control) (SAR, a gift from Dr Domenico Regoli, Université de Sherbrooke, Sherbrooke, Québec, Canada). An additional group of C6-inoculated animals (n = 6) were treated intravenously with SAR (100 nm/Kg) 5 min after pre-treatment with 100 nmol/Kg of the B1 receptor antagonist [Leu8]-des-Arg9BK (LEU, Sigma). Previous pilot studies conduced in our laboratory (data not presented) showed that SAR had a maximum effect at the equivalent dose of 100 nmol/Kg. These assays also showed that LEU at the dose used was effective in blocking the effect of SAR effect on isolated brain parenchyma and dura-mater. Fifteen minutes after the treatments, rats were perfused with 4 ml/Kg 0.9% NaCl for 3 min [14] and the brains were removed. Two cubic centimeters of tissue were removed around the inoculation site (right hemisphere) and from the contralateral homologous region (left hemisphere). EB was extracted with formamide (4 ml/g of wet weight tissue at room temperature for 24 h) and quantified at 620 nm with a Titerk Multiscan Microplate reader by comparison with a standard curve of EB (0.5 to 25 μg/ml of formamide). Extravasation was expressed as microgram of EB per gram of dry tissue.
Statistical analysis
Differences between treatments were evaluated by one-way ANOVA followed by the Bonferroni post-hoc test (plasma extravasations studies) or by the Student t-test for paired samples (for comparisons between right and left cerebral hemispheres). Values were considered statistically significant when p < 0.05.
List of abbreviations used
BBB-Blood brain barrier
BK-Bradykinin
BTB-Blood tumor barrier
B1-Bradykinin receptor B1
B2-Bradykinin receptor B2
EB-Evans Blue
LEU-[Leu8]-des-Arg9BK
MR-Metabolic resistance
PPE-Plasma protein extravasation
SAR-Sar-[D-Phe8]des-Arg9BK metabolically resistant bradykinin B1 agonist
Authors' contributions
BLS and RCC contributed equally to this work. BLS and RCC carried out the surgical procedures and cell culture. MMB, RW, and CGCJr participated in the preparation of the manuscript. MAS carried out the absorbance assays. AGT and MN conceived the study and participated in its design and coordination. All authors participated in the analysis of the data and discussion of the results. All authors read and approved the final manuscript.
Acknowledgements
We would like to thank Dr. Vivaldo Moura Neto, Departamento de Anatomia e Histologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brazil,, for kindly providing C6 cells from his personal cell bank, and Dr. Domenico Regoli, Université de Sherbrooke, Sherbrooke, Québec, Canada, for providing Sar-[D-Phe8]des-Arg9. This work was funded by Capes, CNPq and Funpesquisa-UFSC. Dr Bianchin was supported by FAPESP (02/03743-0). The authors are indebted to Elettra Greene for revising the English text.
Figures and Tables
Figure 1 Protein plasma extravasation (PPE) in the right (inoculated) hemisphere of 6 different groups of animals. There was a significant increase in PPE when the 17-day-C6-injected animals were concomitantly injected with SAR 100 nm/Kg (C6 + SAR) compared to the control group (C6-inoculated). Vehicle-inoculated and vehicle-inoculated + SAR (100 nm/Kg) animals did not differ from each other or from the control. Bradykinin (100 nm/Kg) injected through the femoral vein did not enhance BTB permeability (C6 inoculated + BK). However, the specific bradykinin B1 antagonist, LEU (100 nm/Kg), improved SAR-induced PPE in the tumor mass (C6-inoculated + LEU + SAR). *p < 0.01 compared to PPE in the C6-inoculated, vehicle-inoculated, vehicle-inoculated + SAR, and C6 inoculated + BK groups and in the C6-inoculated+LEU+SAR group.
Figure 2 Protein plasma extravasation (PPE) in the right (C6-inoculated) and left (non-tumoral) hemisphere of rats. The analysis was performed 17 days after the inoculations. PPE was significantly increased in the tumor hemisphere compared to the non-tumoral one. *p < 0.001 compared to PPE in the control (left) hemispheres.
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| 15458573 | PMC524173 | CC BY | 2021-01-04 16:03:46 | no | BMC Neurosci. 2004 Sep 30; 5:38 | utf-8 | BMC Neurosci | 2,004 | 10.1186/1471-2202-5-38 | oa_comm |
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BMC Plant BiolBMC Plant Biology1471-2229BioMed Central London 1471-2229-4-171537738810.1186/1471-2229-4-17Research ArticleRegulation of membrane fatty acid composition by temperature in mutants of Arabidopsis with alterations in membrane lipid composition Falcone Deane L 14deane_falcone@uml.eduOgas Joseph P 2ogas@purdue.eduSomerville Chris R 3crs@andrew2.stanford.edu1 Department of Agronomy and the Kentucky Tobacco Research & Development Center, University of Kentucky, Lexington, KY 40546 USA2 Department of Biochemistry, Purdue University, W. Lafayette, IN 47907 USA3 Carnegie Institution, Department of Plant Biology, 260 Panama Street, Stanford, CA 94305 USA4 Current Address:Department of Biological Sciences, University of Massachusetts Lowells One University Avenue, Lowell, MA/01854 USA2004 17 9 2004 4 17 17 7 1 2004 17 9 2004 Copyright © 2004 Falcone 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
A wide range of cellular responses occur when plants are exposed to elevated temperature, including adjustments in the unsaturation level of membrane fatty acids. Although membrane bound desaturase enzymes mediate these adjustments, it is unknown how they are regulated to achieve these specific membrane compositions. Furthermore, the precise roles that different membrane fatty acid compositions play in photosynthesis are only beginning to be understood. To explore the regulation of the membrane composition and photosynthetic function in response to temperature, we examined the effect of temperature in a collection of mutants with altered membrane lipid fatty acid composition.
Results
In agreement with previous studies in other species, the level of unsaturation of membrane fatty acids in Arabidopsis was inversely correlated with growth temperature. The time required for the membrane fatty acids to attain the composition observed at elevated temperature was consistent with the timing required for the synthesis of new fatty acids. Comparisons of temperature-induced fatty acid alterations in membranes were made among several Arabidopsis lines including wild-type Columbia, and the compositional mutants, fad5, fad6, act1 and double mutants, fad7 fad8 and act1 fad6. The results revealed key changes that occur in response to elevated temperature regardless of the specific mutations in the glycerolipid pathway, including marked decreases in trienoic fatty acids and consistent increases in unsaturated 16:0 and in dienoic 18:2 levels. Fluorescence measurements of various mutants indicated that photosynthetic stability as well as whole plant growth at elevated temperature is influenced by certain membrane fatty acid compositions.
Conclusions
The results of this study support the premise that defined proportions of saturated and unsaturated fatty acids in membrane lipids are required for photosynthetic thermostability and acclimation to elevated temperature. The results also suggest that changes in the membrane fatty acid composition brought about in response to temperature are regulated in such a way so as to achieve highly similar unsaturation levels despite mutations that alter the membrane composition prior to a high-temperature exposure. The results from examination of the mutant lines also suggest that interorganellar transfer of fatty acids are involved in mediating temperature-induced membrane alterations, and reveal steps in the fatty acid unsaturation pathway that appear to have key roles in the acclimatization of membranes to high temperature.
Membrane ipidsthermotolerancefatty acid desaturaseglycerolipid pathwayPS II fluorescence
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Background
One of the most prevalent environmental challenges encountered by plants is the exposure to a broad range of temperatures. Plants use a variety of anatomical, metabolic and cellular strategies to deal with changing environmental temperatures. Acclimation to elevated temperatures is mediated at the cellular level in part by the induction of general stress responses, which include the increased expression and activity of heat shock proteins [1-6]. These proteins enable organisms to withstand elevated temperatures by functioning as molecular chaperones to offset damage from misfolded proteins that would otherwise accrue during exposure to high temperature. Changes in the properties of cellular membranes, on the other hand, occur to ensure the proper function of processes that take place within them. The chloroplast thylakoids house the photosynthetic electron transport machinery, and are the most abundant membranes of leaf tissue. They are responsible for all light harvesting and photosynthetic energy conversion in the cell. Some alterations within thylakoid membranes occur rapidly to diminish stress triggered by immediate changes in the environment. For example, short-lived alterations in membranes can take place to counter excess absorbed energy in response to sudden exposures to high light [7,8]. Thermal dissipation of such excess light energy is mediated by the function of the carotenoid zeaxanthin, which is converted from violaxanthin by a de-epoxidase that is rapidly activated in response to high light [9]. In general, however, temperature-induced compositional changes of membranes follow time scales that reflect the acclimatization of plants at different temperatures [10].
Early studies of the ability of plants to acclimate to higher temperatures were conducted on plants adapted to high temperature growth [10-12]. For example, the desert shrub Atriplex lentiformis, changes its membrane fatty acid composition by decreasing the level of unsaturated fatty acids such as hexadecatrienoic acid (16:3) and increasing the level of saturated lipids at higher growth temperatures [13]. Membrane fatty acids of plants from temperate environments show similar trends in response to temperature, an observation that suggests that alterations in membrane lipids generally contribute to the ability of plants to acclimate to different temperatures [14,15].
Of the numerous cellular processes likely to be affected by the membrane composition, photosynthesis is probably the most critical. Adjustments in the level of unsaturation of thylakoid membranes may therefore affect the capacity of plants to adapt to elevated temperature conditions in order to avoid a reduction in photosynthetic efficiency. In this regard, the reaction center of PSII is considered to be the most sensitive component of the thylakoid membrane to thermal breakdown, and the function of the water-splitting D1 protein within PSII has been implicated as the most readily damaged by high temperature [10] as well as the being the primary target for photoinhibition [16,17]. High-temperature induced changes in the membrane composition may therefore play a role in the stability of such proteins leading to positive effects on whole plant growth at elevated temperature.
Studies on cyanobacteria have indicated that the mechanism by which temperature mediates compositional alterations in membranes is at the level of transcription. The level of desaturase transcripts in cyanobacterial cells increases in response to growth at low temperature [18]. It is likely that the transcription of cyanobacterial desaturase genes is dependent on the physical properties of the membranes themselves [19]. The idea that changes in the degree of fluidity of cyanobacterial thylakoid membranes might be a means of sensing thermal stress is supported by the finding that heat shock proteins were induced when the membrane fluidity was chemically altered [20]. However, most investigations conducted with plants suggest that transcription is not the primary means of controlling membrane fatty acid unsaturation. Studies examining the level of expression of desaturase genes in Arabidopsis have shown that the majority of them do not respond to either decreases or increases in temperature via changes in transcription [21-23], or to alterations in the membrane fatty acid composition due to mutations in the desaturase pathway [24,25]. Only the relatively unusual case of the desaturation step catalyzed by the Arabidopsis fad8 gene [25], and other highly specific examples for particular plant species [26], have been shown to be regulated at the level of transcription by temperature.
In this study we examined the leaf membrane fatty acid composition of Arabidopsis in response to temperature. After establishing the changes that occur at different elevated temperatures, we examined a number of mutant lines of Arabidopsis that possess well-characterized alterations in their membrane fatty acid content. The lines studied differ primarily in the degree of unsaturation of various lipids in chloroplast membranes. Examination of the fatty acid profiles of these lines grown at high temperature reveals a regulatory system that mediates membrane compositional changes even in the absence of specific desaturase steps. The results also suggest some general control points that might be important in the mechanism by which the membrane fatty acid unsaturation level is adjusted in response to temperature. In the course of carrying out these studies, we also examined the relationship between membrane fatty acid composition and growth at elevated temperatures.
Results
Elevated temperatures alter the membrane fatty acids of Arabidopsis
Arabidopsis lines were germinated and grown at 17°C for seven days before being shifted to designated temperatures. Total leaf fatty acids were extracted from lines grown at various temperatures for 30 to 35 d, converted to methylesters and analyzed by gas chromatography. Changes in the relative abundance of the major fatty acid species from the Columbia wild-type line grown at 17°C, 20°C, 29°C and 36°C were plotted and are shown in Fig. 1. The tendency of polyunsaturated species to decrease in abundance upon increasing growth temperature is evident within both 16 and 18 carbon-length fatty acids. The level of 18:3 in leaves decreased from 54 to 21 mol% of the total fatty acids from plants grown at 17°C and 36°C, respectively, and 16:3 species decreased from approximately 16 to 2.3 mol% for the same growth temperatures. In contrast, the proportion of diunsaturated linoleic acid (18:2) and monounsaturated oleic acid (18:1) showed an opposite response to elevated growth temperatures, with incremental increases of these species detected in plants grown at progressively higher temperatures. Specifically, the level of 18:2 increased from 10.1 mol% to 31.5 mol% of total fatty acids at 17°C and 36°C growth temperatures, respectively. These changes did not occur linearly over the temperatures measured but showed larger changes between 17°C and 20°C. At temperatures above 20°C, the relative abundance of the fatty acids generally changed in a more linear fashion. However, 16:0, unlike most other fatty acids, changed more abruptly between the two uppermost growth temperatures of 29°C and 36°C. To provide an additional estimation of the total membrane unsaturation level, the double bond index was calculated from the mol% fatty acid data (Table 2). The double bond index showed a corresponding decrease as the growth temperature was increased. Likewise, the levels of saturated palmitic acid, 16:0, accumulated to higher proportions in plants grown at elevated temperature, from 12.9 to 31 mol%. The relative abundance of other fatty acids (16:1, 16:2, and 18:0) showed alterations that were less pronounced in response to growth at elevated temperatures.
Temporal evaluation of membrane alterations induced by high temperature
Based on the substantial changes detected after the shift to elevated temperature, we wished to determine whether these changes occurred on time scales similar to the timing known for new synthesis of fatty acids. To estimate the time required for a temperature increase to induce measurable changes in the membrane fatty acid composition, Arabidopsis seedlings were germinated and grown at 22°C for seven days and then shifted to 29°C. The fatty acid composition was then evaluated in rosette leaves sampled at various times after the shift to elevated temperature by gas chromatographic analysis (Fig. 2). The leaf fatty acid profile of plants grown at 22°C (0 h) was comparable to previous determinations made on plants grown at similar temperatures (Fig. 1). No significant changes were detected in the fatty acid profile 60 h after the shift to 29°C. The earliest time point reflecting an alteration in response to elevated temperature occurred at 108 h, with 16:0 and 16:3 exhibiting the largest and most abrupt shifts, and 18:2 and 18:3 showing detectable, but more gradual changes at this time. At the 204-h time point, 18:2 and 18:3 species exhibited alterations in their accumulation to a degree similar to those observed to change markedly in plants grown at different temperatures. Specifically, 18:2 increased in a relatively linear manner from approximately 16 to 19.5 mol% of the total while 18:3 decreased from about 39 to 34 mol% and these proportions remained relatively constant at the final time point measured, 240 h after the shift to high temperature.
The time course observed for the fatty acid composition to change in response to elevated temperatures correlates with the time determined for the incorporation of precursors to attain steady state levels in radiolabel feeding experiments [27]. The same general pattern of fatty acid changes was observed after the shift to high temperature. For example, 16-C fatty acids, 16:0 and 16:3, exhibited an abrupt shift from 18.9 to 24.8 mol% and 13.6 to 8.2 mol%, respectively, at the 108-hr time point, and remained relatively constant, until the final time point, except that 16:0 tended to decrease somewhat, after the increase observed at 108 h. On the other hand, major changes in the relative proportions of 18-C fatty acids, a large percentage of which are derived through the eukaryotic pathway, were not evident until the 204-h time point. This distinction between the onset of changes of 18:2 and 18:3 and of 16:0 and 16:3 is also reflected in the more linear response of 18:2 and 18:3 compared to the more abrupt transition and then fairly linear response of 16:0 and 16:3. Control experiments in which wild-type Arabidopsis lines were maintained at 22°C and sampled for membrane fatty acids over the same time intervals as shown in Figure 2, did not show equivalent alterations at 108 h but maintained similar profiles throughout (data not shown). Thus, detection of the first alterations in the fatty acid composition in response to increased growth temperature is consistent with the time required for new synthesis of fatty acids. These results also suggest that changes in membrane fatty acids in response to temperature require turnover and resynthesis of new lipid to achieve the temperature-adapted composition.
Temperature-induced changes in membrane fatty acid composition of mutant lines to probe membrane regulation
A number of Arabidopsis lines possessing well-characterized alterations in their membrane fatty acid profiles (Table 1) were used to examine how a specific block in the glycerolipid pathway affects the membrane composition in response to high temperature. For this analysis, we examined the membrane fatty acid content of plants grown at 17°C and 36°C. As in the previous determinations (Fig. 1), all plants were germinated and grown in an environmental chamber at 17°C for seven days before shifting to one set to 36°C. The fatty acid profile was then determined after 25–30 d of growth. The lower growth temperature of 17°C was chosen based on the response of the membrane fatty acid composition of leaves to this temperature determined previously, as well as the overall growth performance of the plants. The upper temperature of 36°C was selected based on the pronounced alterations observed in the fatty acid composition of wild-type plants grown at this temperature and the fact that this temperature represents the physiological upper limit for vegetative growth in soil. Indeed, growth at this temperature led to sterile plants (data not shown). This loss of seed production was apparently due to insufficient pollen formation and was consistent with notable decreases in seed yield (approximately 50%) from lines grown at 29°C (data not shown). Incubation at 36°C was also used to provide conditions by which the leaf fatty acid profiles would be most clearly delineated among the various Arabidopsis mutant lines as well as to establish the magnitude of the alterations in the fatty acid composition in response to elevated temperature.
Each line used in this analysis possessed a mutation that primarily impacts the composition of the photosynthetic membranes of the chloroplasts (Table 1). Several of these mutants have been shown previously to display variable degrees of thermal tolerance [28-31]. Examination of the fatty acid profiles from these lines reflect the same general trends seen for wild-type plants grown at temperatures above 17°C (Fig. 1). As observed previously, the level of polyunsaturated fatty acids generally decreased with a concomitant increase in diunsaturated and saturated fatty acids when compared to plants grown at 17°C (Fig. 3). Specifically, trienoic fatty acids (16:3 and 18:3) decreased sharply and the level of dienoic 18:2 (but not 16:2) increased at the elevated temperature. Saturated 16:0 and, in some lines, monounsaturated 18:1, also accumulated to higher levels in plants grown at 36°C. A general estimation of the membrane unsaturation level was also provided by the double bond indices derived from this data (Table 2). Mutant lines fad5, fad6, fad7 fad8, and act1 fad6 showed a lower double bond index from plants grown at 17°C compared to wild type, with fad6 displaying the most pronounced decrease in overall unsaturation. In contrast, the double bond indices obtained from membranes of the mutant lines grown at 36°C were similar to each other and the wild type with an average value of 1.5. Thus the total membrane unsaturation level is relatively equivalent among the different lines grown at the higher temperature.
Two principal changes were apparent among the individual lines in response to high temperature: an increase in the abundance of 16:0 and 18:2 fatty acids and a pronounced decrease of both trienoic polyunsaturated species, 16:3 and 18:3 (Fig. 3). In the case of the fad5 mutant line, which is deficient in the desaturation of 16:0 to 16:1 at the sn-2 position only on chloroplastic monogalactosyldiacylglycerol [32], the 16-C fatty acids from plants grown at 17°C resembles those of the wild type grown at high temperature (Fig. 3B). This includes the proportion of 16:3, which is essentially absent due to the block in the prokaryotic pathway at the level of 16:0. At 36°C, the composition of fad5 membranes is most similar among all of the mutants examined to that of the wild type grown at high temperature. The high degree of similarity of the fad5 and wild-type compositions may implicate the step catalyzed by the FAD5 desaturase to be an important control point in the acclimatization of the membrane composition in response to temperature.
Examination of the membrane fatty acid composition of the fad6 mutant line in response to high temperature similarly reveals the general trends seen in the wild-type line grown at elevated temperature (Fig. 3C). Because fad6 is deficient in the desaturation of 16:1 and 18:1 to 16:2 and 18:2, respectively, on all chloroplastic lipids [33], the accumulation of both 16:1 and 18:1 in this line are evident. The proportions of these two monounsaturated fatty acids remain virtually unchanged in fad6 plants grown at low and high temperature, showing that the overaccumulated levels of these species, due to the mutation in the FAD6 desaturase, is not subject to alterations in response to temperature.
The mutation in the act1 line blocks entry of fatty acids into the prokaryotic pathway by a deficiency in chloroplast GPAT [34]. This is reflected in the fatty acid composition of act1 plants grown at both low and high temperature, with a decrease in all 16-C fatty acid species (Fig. 3D). Temperature-induced changes in the fatty acid composition of the act1 line shows a profile highly similar overall in 18-C fatty acids compared to the wild type, suggesting that the desaturases controlling the conversion of 18:2 to 18:3 is a major control point capable of adjusting unsaturation levels of leaf membranes. The slightly elevated level of 18:2 at both temperatures in act1 compared to the wild type likely reflects the previously demonstrated increase of fatty acid flux into the chloroplast membranes via transfer of primarily this fatty acid [27,34].
The deficiency in the fad7 fad8 line is due to mutations at two loci, each encoding desaturase isozymes that convert 16:2 and 18:2 to 16:3 and 18:3, respectively, in the chloroplast [35]. In this line, the dienoic fatty acids, 16:2 and 18:2, are elevated and the effect of high temperature resulted in a reduction of this elevated 16:2 from 9.8 to 5.4 mol% (Fig. 3E). The proportion of 18:2, on the other hand, increased in response to high temperature from 36.8 to 55.7 mol%. The trienoic fatty acid, 18:3, which due to the fad7 fad8 mutations was lower than the level in the wild type at 17°C (28 vs 54.8 mol% in the wild type), decreased to 6 mol% of total fatty acids at 36°C, the lowest leaf 18:3 levels of all the lines tested. Thus, the general trend of increasing 18:2 and decreasing 18:3 in response to high temperature growth was retained in the absence of most FAD7 and FAD8 desaturase activities, which catalyze the formation of the majority of trienoic fatty acids in the leaf membranes.
A line derived from a cross between act1 and fad6 was produced during this study and used to evaluate the performance and temperature response of plants containing a membrane fatty acid composition which is distinguished by an elevated level of 18:1 (due to the deficiency in the FAD6 desaturase) but no increase in the relative amounts of 16:1 (because of the block into the prokaryotic pathway, due to diminished GPAT activity). The resulting composition in the act1 fad6 double mutant line grown at 17°C indicates the profile expected for mutations at each of these steps. The fatty acid profile altered in response to elevated temperature is similar to each parental mutant line grown at high temperature (Fig. 3F). The act1 fad6 line thus provides a membrane fatty acid profile dissimilar to other lines in this study in that it contains elevated 18:1 but no increases in the proportion of 16:1 or 16:3. Such a profile can be used to address the functional significance of having only increased 18:1 but relatively similar proportions of all other fatty acids (see below).
Fluorescence yield enhancement
Six Arabidopsis lines possessing distinct membrane fatty acid compositions were evaluated by measuring chlorophyll fluorescence parameters to determine the thermal stability of PSII. The use of chlorophyll fluorescence has been used extensively to investigate photosynthesis and previous studies have examined photosynthetic stability using similar methods on isolated chloroplasts or detached leaves from the fad5 and act1 lines [29,36]. However, the analysis conducted here is the first to use in planta measurements in side-by-side comparisons to examine differences in thermal tolerance. In addition, prior to the fluorescence stability measurements, the fatty acid compositions of all lines used in this analysis were determined and all were found to be within the standard error of those values determined for the fatty acid profiles of the lines grown at 17°C (Fig. 3, data not shown). Table 3 shows the results of the fluorescence analysis. Plants were grown at 17°C and evaluated at approximately four weeks of age. In all plants grown at this temperature, it is apparent that mutant lines fad6, fad5 and act1 show a statistically significant increase in the fluorescence transition point (TP) temperature while fad7 fad8 shows a slight but insignificant increase. These results are likely to be due to differences stemming predominantly from the distinct membrane fatty acid compositions in leaves from the lines grown at this temperature. The TP values obtained for these intact leaf measurements here, are very similar to various determinations previously conducted on some of the lines using isolated chloroplast preparations or detached whole leaves [29,36,37]. Thus, only some lines display enhanced stability of photosynthetic quantum yield as the leaf temperature is increased and this seems to be positively correlated with a decrease in trienoic fatty acids, particularly 16:3, derived from the prokaryotic pathway. However, the relative proportion of 16:3 does not appear to be the only determinant for increased thermal stability.
The double mutant act1 fad6 provided a line with a fatty acid profile that is distinct from that of other lines analyzed in this study (i.e., an increase in the percentage of 18:1 but no increased level of 16:1 at 17°C) (Fig. 3F). To determine if this composition resulted in differences in the photosynthetic thermostability, we subjected the act1 fad6 line to fluorescence measurements. The act1 fad6 double mutant did not show a significant difference in the TP temperature from that of the wild type, even though each of the parental lines that possess only the single respective mutation exhibited a measurable enhancement of thermal stability (Table 3).
The act1++ line is a transgenic line that over expresses GPAT (i.e., the act1 gene product). It was included as an additional line here to test whether its fatty acid composition would impact the thermal stability measurements as determined by chlorophyll fluorescence. However, the leaf fatty acid composition of act1++ plants grown at 17°C is similar to the wild-type composition except that the percentage of 16:0 and 16:3 fatty acids is increased to 2.0 and 1.5 mol%, respectively, over the proportions determined in the wild type. No differences in thermostability as indicated by chlorophyll fluorescence measurements were apparent for this line compared to the wild type.
Although the most equivalent comparisons for stability measurements among the different lines would be obtained from those grown at temperatures considered moderate for Arabidopsis, such as 17°C used here, we also determined the TP temperatures for those lines that exhibited enhanced thermal stability at 17°C after growth at high temperature. Since this study revealed clear differences in the membrane fatty acid composition at various elevated temperatures, an indication of high-temperature acclimation based on fluorescence measurements may be evident. Four plants including wild type were grown at 29°C for three weeks before conducting the fluorescence stability tests. The results indicated an increase in the TP temperature from 42.7°C for wild type grown at 17°C to about 44.8°C in plants grown at 29°C (Table 3). However, the fad5, fad6 and act1 lines, which showed reproducible increases in thermal stability compared to wild type when grown at 17°C, showed essentially the same TP temperatures as the wild type when grown at the elevated temperature. The lack of a detectable increase in thermal stability in mutant plants above the temperature found for the wild-type line grown at high temperature may be a consequence of the altered composition of the membrane fatty acids after growth at high temperature. The similar TP temperatures are also consistent with the overall similar unsaturation levels as indicated by the double bond index calculated for these lines. These results may also reflect the upper tolerance limit attainable that arises from fatty acid adjustments in response to elevated growth temperature, at least with the different compositions in the lines studied here.
Growth at elevated temperature
Most of the mutant lines used in this study were chosen on the basis of their altered fatty acid profiles in chloroplast membranes. As shown here, reductions in the total level of triunsaturated fatty acids in many lines grown at 17°C reflects the composition of the wild-type line grown at elevated temperature. To establish whether the observed changes translates into improved performance at the whole plant level, growth rates were determined for the lines at various temperatures. Growth rates were determined only during the first six days after the shift to elevated temperatures in order to maintain equivalent membrane fatty acid compositions of the lines before changes occurred in membranes during acclimation to high temperature (Fig. 2). As shown in Table 4, the relative growth rates of fad5, fad6, act1 and fad7 fad8 seedlings are at least the same or slightly higher than wild type within several days after the shift to high temperature. In agreement with findings by Murakami et al. [31], the fad7 fad8 mutant line exhibited the most pronounced tolerance to high temperature based on growth rate. These results indicate that a less polyunsaturated membrane fatty acid composition than normally found in wild type favors seedling growth at elevated temperatures.
Discussion
Several clear alterations are evident in the membrane fatty acid composition in response to high temperature growth. A decrease in trienoic fatty acids, including strongly diminished 16:3, produced exclusively within the prokaryotic pathway in the chloroplast, is consistent with the general decrease of polyunsaturated fatty acids in response to high temperature. Concurrent with the reduced accumulation of trienoic fatty acids at high temperature is an increase in linoleic acid, 18:2, and an increase in 16:0 (Figs. 1 and 3). The observation that 16-C fatty acids show a pattern distinct from that of 18-C fatty acids suggests that individual fatty acid classes may have specific roles in maintaining optimal membrane function as well as different mechanisms governing their synthesis. This idea of distinct roles for particular fatty acids in the membrane is also supported by the relatively similar degree of membrane unsaturation in most of the lines examined (Table 2), despite the differences found in growth or photosynthetic stability.
It is remarkable that these general alterations are observed even in mutant lines that are deficient in steps early or late in the desaturation pathways. For example, the profile of fad5, which is deficient in 16:0 desaturation in the chloroplast compared to fad7 fad8, which is deficient in the final desaturase step forming trienoic fatty acids, show similar overall trends in response to high temperature. These temperature responses must take into account the two glycerolipid pathways that operate in parallel in Arabidopsis, one in the chloroplastic envelope membranes and one in the endoplasmic reticulum [38,39].
Previous characterizations of all of the individual mutant background lines used in this study have clearly indicated the primary lipid species acted upon by the specific desaturase (or acyltransferase) activity missing in each mutant (Table 1). The temperature-induced alterations in the membrane composition can be considered in the context of the particular mutant background with its corresponding deficiency in a given step of the glycerolipid pathway. In this case, the mutations examined primarily affect chloroplastic lipids. In addition, the polyunsaturated 16-C fatty acids can be used as reliable markers for the major chloroplastic lipids monogalactosyldiacylglycerol and digalactosyldiacylglycerol, since they are the only lipids that contain these fatty acids. In regard to lipid compositions following growth at elevated temperature, examination of the proportions of individual lipids from the related species, Brassica napus, has shown that significant changes do not occur in leaf membranes from plants grown at 20°C and 30°C [15]. This finding suggests that it is the degree of fatty acid unsaturation that varies most appreciably at these temperatures and not the levels of the major leaf lipids themselves [15].
Temporal basis for temperature-induced membrane alterations
The time required for the fatty acid composition to adjust to high-temperature growth conditions demonstrated that major alterations in leaf membranes do not occur rapidly in response to elevated temperature. The ~60-h period before changes become evident in the fatty acid profile corresponds with the occurrence of new lipid synthesis and turnover and therefore does not suggest a mechanism by which temperature induces modifications of existing membrane fatty acids. These results are also consistent with labeling studies that show fatty acids produced by the prokaryotic pathway accumulate prior to those synthesized via the eukaryotic pathway. The abrupt changes in 16-C fatty acids beginning 60 h after the shift to high temperature compared to the gradual and more continuous alterations observed for 18-C fatty acids (Fig. 2) also fits with these labeling patterns. It is well established by a number of time-course radiotracer labeling studies, including several conducted on most of the mutant lines used here, that earlier stages in the glycerolipid pathway show alterations prior to those formed through the eukaryotic pathway [27,33-35,40]. These include the formation of saturated fatty acids prior to the accumulation of unsaturated species and the earlier production of palmitate-containing species in the prokaryotic pathway. Overall, these time-course observations suggest that the modulation of membrane unsaturation levels plays a role in longer-term acclimation of the plant. Transient fluxes in environmental temperature are therefore not likely to result in pronounced alterations in the composition of leaf membranes.
Membrane composition in response to temperature in mutant lines
The fatty acid composition resulting from high-temperature growth in the different genetic backgrounds reveals a complex regulatory system. Thus, despite deficiencies in several enzymatic steps in the different mutants, the membrane fatty acid composition undergoes adjustments similar to those observed in the wild type in response to elevated temperature. The similar increase in 18:2 levels after high temperature growth in the fad5, fad6, act1, act1 fad6 and wild-type lines suggests that the percentage of 18:2 may be important in membrane acclimatization. These results also suggest that desaturase activities as well as flux from extrachloroplastic membranes might also be controlled to mediate the response to temperature (see below). The accumulation of 18:2 (as opposed to 18:1) in the lines tested implicates it as a preferred species in membranes adapted to high-temperature growth. Although unknown, one speculation for 18:2 for this may be due to the "intermediate" level of disorder represented by diunsaturated acyl chains in the membrane. Fatty acids with one double bond, such as 18:1, impart a greater relative degree of disorder to the membrane than acyl groups containing two double bonds which, in turn, confer only slightly less disorder to the membrane relative to triunsaturated 18:3. The composition of the fad7 fad8 mutant line supports this contention, in which the mol% of 18:2 is almost 2-fold higher than that of wild-type membranes and this line exhibited the best growth at elevated temperature. However, biological membranes are complex, dynamic structures and it is likely that other, unknown factors will be important to maintain optimally functioning membranes.
The fatty acid profiles of several mutants grown at high temperature suggests that the control of flux of fatty acids from the eukaryotic pathway is partly responsible for the changes observed in 18:2 and 18:3 due to temperature. In the fad6 mutant grown at high temperature, the proportions of 18:2 and 18:3 are highly similar to the proportions observed in the wild type, despite that essentially all of the 18:2 must be derived from the eukaryotic pathway. Labeling studies have shown previously that the fad6 line exhibits a decrease in lipid synthesis via the prokaryotic pathway [33], and this same mechanism, which presumably operates to maintain specific physical properties of the chloroplast membranes, may also be involved in mediating compositional adjustments of the membranes in response to increased temperature. In this case, a possible mechanism might be a reduction in the amount of 18:2 fatty acids transferred to the chloroplast for desaturation by the FAD7 and FAD8 desaturases. The fad6 profile also reveals that activity of the FAD2 enzyme, operating in the endoplasmic reticulum, might also be subject to temperature regulation.
Similarly, in the act1 mutant line, in which entry of fatty acids into the prokaryotic pathway is blocked by the step catalyzed by GPAT, the primary difference is a decrease in the level of 16:0 when grown at elevated temperatures. This presumably reflects an increase into the eukaryotic pathway but with a similar temperature-responsive regulation. Flux of 18:2 from the eukaryotic pathway back into the chloroplast also appears to be modulated, as the proportions of 18:1 and 18:2 are slightly elevated in act1 at both temperatures, while the 18:3 level is highly similar to wild type.
The fatty acid composition of the fad7 fad8 mutant reveals alterations that occur in response to elevated temperature in the absence of all trienoic fatty acid-forming desaturase activity in the chloroplast (Fig. 3E). This profile also suggests that transfer of fatty acids from the eukaryotic pathway may be an important component in temperature regulation of the membrane composition. Such a mechanism is possible considering that the major proportion of 18:3 produced in this line must be synthesized through the eukaryotic pathway via the FAD3 desaturase [27]. The resulting low level of 18:3 detected in plants grown at high temperature is evidence that the FAD3 enzyme in the endoplasmic reticulum also is subject to temperature regulation. Thus it appears that desaturase enzyme activity is inversely regulated by increased temperature, in agreement with previous proposals as a likely mechanism [41]. Analysis of the data presented here suggests that the desaturases that catalyze trienoic fatty acid formation (FAD7, FAD8 and FAD3) and the FAD5 desaturase are the enzymes likely to have the greatest impact if regulated in this way.
Membrane fatty acid composition has a role in enhancing photosynthesis to tolerate high temperature
Studies conducted on the ability of plants to acclimate to elevated temperature have mainly focused on components most likely to affect the stability of photosynthetic electron transport, particularly PSII. In this respect, the composition of the chloroplast thylakoids is expected to be important in the thermal tolerance of photosynthetic electron transport [10]. Moon et al., [42] have implicated the unsaturation level of PG as being important in the removal and replacement of damaged D1 proteins in plants. However, the direct relationship pointing to protein-lipid associations being involved in stabilizing the D1 protein at high temperature has only recently been suggested [43]. The results presented here imply a regulatory mechanism that confers a similar overall composition in response to temperature regardless of the initial fatty acid alteration in the membranes due to mutation. A possible reason for such apparently stringent control might be that compositions that are deleterious for membrane function are curtailed, utilizing desaturase pathways that are present in both chloroplastic and extrachloroplastic locations.
Measurement of PS II activity during leaf heating was used here as a sensitive indicator of the thermostability that might be conferred by the different membrane compositions. In this case, the temperature at which the quantum yield of PS II electron transport collapses (TP) was determined in intact leaves. The fluorescence measurements were conducted on plants grown at 17°C, to minimize variation and other potential responses, such as increases in the synthesis of heat shock proteins that might be induced at higher temperatures. In addition, only at the 17°C growth temperature were differences observed in the total membrane unsaturation level among the different lines tested as estimated by the double bond index, which might suggest that the largest influence of the fatty acid composition occurs at lower and more moderate temperatures.
The fad6 mutant exhibited the maximum fluorescence yield enhancement of the lines grown at 17°C. This maximum TP is essentially the same as that obtained from several plants grown at 29°C, including the wild-type line (Table 3B). The 2°C difference apparent in the mutant lines grown at 17°C may be an accurate indication of the magnitude of PSII thermal stability that can be conferred by adjustments in the membrane fatty acid composition and therefore may reflect the extent to which these adjustments can contribute to high-temperature acclimation in Arabidopsis. While it is unknown how specific fatty acids influence thermal stability, analysis of the act1 fad6 mutant described in this study demonstrates that alterations in the relative abundance of 16:1 and 18:1 have an effect. Both act1 and fad6 mutant plants display enhanced stability compared to wild type as determined by fluorescence measurements whereas the act1 fad6 line, which does not exhibit elevated 16:1 but slightly higher levels of 18:1, shows no statistical difference in the TP temperature compared to wild type (Table 3). This difference in fluorescence TP temperatures among these three mutants, as well as a lack of a correlation between the TP values and the double bond index, illustrates that the relative level of a specific lipid class can influence thermal stability. Measurements of diffusion rates of light-harvesting complexes in desaturase mutants of cyanobacteria also point to distinct roles that lipids may have in photosystem stability. In a recent study, the interaction of phycobilisomes with reaction centers was proposed to be stabilized by lipids as opposed to being affected by the level of membrane unsaturation directly [44]. Studies using spectroscopic methods have also suggested that overall lipid acyl chain disorder in cyanobacterial membranes is similar despite differences in growth temperature or unsaturation levels [45] and that protein-to-lipid interactions in membranes seem to be a key parameter in membrane dynamics [45,46].
Measurements of a single physical parameter attributable to alterations in the membrane composition have often not correlated with results apparent in whole plant performance tests. Similar to the results presented here, Murakami, et al., [31] have shown that chlorophyll fluorescence measurements might not be the ideal indicator to assess whole-plant performance. For example, although the fad7 fad8 line showed the fastest growth rate at high temperature, it did not show a significant difference in thermal stability based on fluorescence yield. The use of other functional measurements, such as CO2 uptake rates or O2 evolution, may provide indicators that more reliably assess potential high-temperature tolerance, although these measurements can also lead to unpredictable results regarding whole-plant physiology. In an Arabidopsis mutant devoid of virtually all digalactosyldiacylglycerol in chloroplast membranes, O2 evolution was found to be unaffected despite large changes in thylakoid membrane organization and in fluorescence energy transfer characteristics [47]. Thus it is likely that additional differences stemming from the relative levels of distinct fatty acids in the membrane affect thermal tolerance and that membrane unsaturation levels will not be the exclusive factor. Other induced changes that impact membrane structure and function can be important. For example, alterations in the length and positions of double bonds within the acyl chain of a lipid molecule can confer widely differing properties and suggest that specific proportions of distinct fatty acid classes may be necessary for optimum membrane function [48].
A number of processes are called into play in response to stresses such as high temperature. Induction of heat shock proteins serves as one countermeasure to respond to elevated temperatures [5] and their specific roles in thermal tolerance are becoming clearer [2-4,49,50]. Correlations between the antioxidant status of plants and thermotolerance have also been noted recently [51-53]. Additional, perhaps more species-specific, responses are likely to be important in protecting against harmful effects of high temperature growth, including the accumulation of small molecules such as glycinebetaine and through the regulation of carbon fixation via rubisco activase [6,54].
Although decreases in the amounts of trienoic fatty acids may be an important determinant for plant thermal tolerance, lines possessing elevations in other, distinct fatty acid species, exhibit different characteristics. A triple desaturase mutant of Arabidopsis demonstrated that all trienoic fatty acids in leaf membranes are not essential for growth at low temperature [55]. This fad7 fad8 fad3 mutant also displayed thermostability but actually died after prolonged exposure to 33°C, suggesting that some trienoic fatty acids are indeed essential for high temperature growth [56]. The upper limit of chronic high temperature exposure for all lines tested here was about 34°C, where plants continue to grow and flower but exhibit reduced seed yield (data not shown), consistent with the idea that some trienoic fatty acids are essential. Although not addressed in the present study, it would be of interest to determine if this decreased seed yield from high-temperature-grown plants was related to insufficient levels of linolenic acid, a precursor required for the synthesis of jasmonic acid, a signaling molecule necessary for pollen development [57].
The results relating to growth performance at high temperature in this study are noteworthy in view of the fact that Arabidopsis is not considered a high temperature tolerant plant [58]. In more heat tolerant species, adjustment of the membrane fatty acid composition may well have greater significance in providing a rational means to control plant high-temperature tolerance. For example, suppression of a FAD7 homolog to concomitantly raise 18:2 and decrease 18:3 in tobacco enabled enhanced growth at elevated temperature [31]. Thus elimination of trienoic fatty acids might be the most critical aspect of altering the membrane composition to favor such enhanced growth. It is unclear, however, if the corresponding increases in monounsaturated and diunsaturated fatty acids that occur in such lines also contribute to the improved tolerance. Several of the mutant lines examined in this study also possessed very low levels of trienoic fatty acids but were accompanied by distinct alterations in other fatty acids. Most of the mutant lines exhibited elevations in the fatty acid species that serves as a precursor to the mutated step. The fad5 line grown at 17°C displayed 16-C fatty acids that were most similar to that of the wild-type line grown at 36°C, and had a membrane fatty acid profile almost identical to the wild type when each was grown at 36°C (Fig. 3A,3B). While such a composition has no deleterious effects at moderate or elevated temperatures, this line, as well as the fad6 line, shows impaired growth and chloroplast development at low temperature [28]. Based on the similar composition to high temperature-grown wild-type plants, the reaction catalyzed by the FAD5 desaturase, which has been identified as an expressed sequence tag [59], may be an additional target to further manipulate tolerance to high temperature.
Conclusions
This study has shown that temperature precisely modulates the membrane fatty acid composition and these changes occur via mechanisms that are not profoundly affected by a number of mutations in the fatty acid desaturation pathway. These observations support the idea that the unsaturation level of plant membranes plays some role in enabling the plant to tolerate elevated temperatures but other characteristics of membrane lipids will likely also be important. Examination of a number of fatty acid desaturase mutants also suggests that alterations in the unsaturation level of membrane fatty acids in response to growth temperature apparently occurs by controlling the level of desaturase activity at several steps within the lipid biosynthetic pathway as well as by modulating inter-compartmental flux between the chloroplastic and cytosolic pathways.
Methods
Plant material and growth conditions
Arabidopsis lines were grown in environmentally controlled chambers (Conviron, Inc.) adjusted to a given temperature under continuous light at 120–150 μmol m-2 s-1. Seeds were sown on pots containing vermiculite-perlite mix (1:1:1) potting soil irrigated with a commercial fertilizer at every third watering. For growth in pots at elevated temperatures, seeds were germinated and grown at 17°C for seven days and then shifted to growth chambers adjusted to the respective temperatures and set to maintain humidity levels to at least 80% or higher, which was found to be essential to maintain growth at temperatures above 32°C. These chamber-grown plants were utilized for determining leaf membrane fatty acid compositions and for analyzing fluorescence yield characteristics. Growth rates of seedlings were determined on lines germinated and grown in Murashige and Skoog salts media (Sigma) containing 1% sucrose and 0.7% agar. Surface-sterilized seeds were plated, treated at 4°C for 2 to 3 days to synchronize germination, and grown for 16 d at 16°C in a growth chamber before shifting to elevated temperatures. Light intensity remained constant at 60 μmol m-2 s-1. Four seedlings were sampled at days 0, 2, 4 and 6 d after the shift to elevated temperatures and were dried for 2 d at 70°C before weighing. The relative growth rates (ω-1) were calculated as the slope of the natural log of the seedling dry weight plotted over time in days. Growth rate determinations for seedlings grown at 22.5°C and 30°C were conducted 3 separate times to obtain SE and growth rates determined for 28 and 34°C were conducted once.
The Arabidopsis mutant lines used in this study are listed in Table 1. All of these are descendents of the Columbia ecotype. The act1 fad6 double mutant line was derived by first crossing act1 to the fad6 line and then crossing progeny from the resulting heterozygotes back to fad6 before selecting for lines possessing a fatty acid composition indicative of both homozygous mutations. The act1++ line, is a transgenic line containing the gene encoding glycerol-3-phosphate acyltransferase (GPAT) (Schneider and Somerville, unpublished, [60]) under the control of a dual 35S cauliflower mosaic virus promoter. It was included as an additional control for the chlorophyll fluorescence studies and possesses a membrane fatty acid composition virtually identical to the wild-type profile, except for a very slight elevation in the amount of 16:3 (~1.5 mol%, over the percentage in wild type at 17°C).
Fatty acid analysis
For each determination, at least two plants were used as a source of leaf material for extraction and analysis. Three mid-to-fully expanded (2 to 5-cm long) rosette leaves were harvested from each plant by removing approximately one-third of the leaf and immediately storing at -80°C in Teflon-capped tubes until needed. Preparation of methyl esters from these leaves and gas chromatographic analysis of the resulting extracts was performed using established procedures [61] with a Hewlett-Packard 5800 series gas chromatograph equipped with Supelco SP2330 glass capillary column (0.75-mm × 20-m). An estimation of the membrane total unsaturation level (double-bond index) was calculated from the mol% values derived from the gas chromatographic data, according to the equation: [Σ(mol% fatty acid content × no. of double bonds)]/100 as described by Skoczowski, et al. [62].
Fluorescence measurements
Chlorophyll fluorescence was measured using an Opti-Sciences OS500-FL pulse modulated fluorometer (Opti-Sciences, Inc. Tyingsboro, MA). A custom designed aluminum heating block was constructed to hold an Arabidopsis rosette leaf, the associated optical cables and the temperature probes to conduct the leaf chlorophyll excitation and fluorescence measurements. An Arabidopsis leaf (~2.4 cm long) was fitted into a recessed (~0.5-mm) portion of the heating block to prevent damage to the leaf section. An ethylene glycol solution was circulated within the block to control temperature. The block and clamp module also provided an adjustable fixture to stably hold the leaf of a potted plant during the measurements.
The photosynthetic thermostability of the different lines was evaluated by determining the transition point temperature of fluorescence quantum yield (TP). An attached rosette leaf was fitted into the thermally controlled heating block and fluorescence was monitored with a saturating light pulse (0.8 s duration) every 90 s. After stabilization at 29°C (4–5 pulses), the temperature of the heating block was increased at a rate of 0.75°C min-1 to a final temperature of 48.5°C using a digital temperature control unit (Omega Technologies Co. Stamford, CT). Leaf temperatures indicated were measured with a thermocouple in contact with the leaf surface. Quantum yield was calculated by the equation F'ms-Fs/F'ms according to Genty [63], where Fs is the steady state fluorescence under environmental conditions, and F'ms is the maximal fluorescence yield obtained after a saturating light pulse. Fm-Fo/Fm, which is a measure of the photochemical efficiency of photosystem II, is based on the variable fluorescence (Fm-Fo), which is the minimum (Fo) and maximum (Fm) fluorescence of a dark adapted leaf before and after, respectively, of a saturating light pulse. All determinations were made on leaf samples that gave an initial Fm-Fo/Fm ratio of at least 0.80, prior to initiating the temperature increase. This measure was taken to ensure that the integrity of the leaf section introduced into the clamp module was sound and to verify that the leaf was properly fitted into the measurement module. The mean value ratio of 0.83 is indicative of a well functioning photosynthetic apparatus in an unstressed leaf as has been shown in a variety of other plant species [64].
Authors' contributions
DF executed the fatty acid analysis, photosynthetic measurements, data analysis and drafted the manuscript. JO undertook the production of the act1 overexpressing lines and assisted in the construction of the double mutant line. CS conceived of the study. All authors read and approved the final manuscript.
Acknowledgements
We are grateful to Olle Björkman for his assistance and advice on setting up and conducting the temperature-dependent fluorometer measurements. We also thank Bonnie Kinney and Peggy Rice for assistance in determining growth rates, the Kentucky Tobacco Research Board for resources and an anonymous reviewer for useful suggestions on the manuscript.
Figures and Tables
Figure 1 Temperature modulates the leaf membrane fatty acid composition in Arabidopsis. Wild-type Columbia plants were grown at various temperatures and total fatty acids were extracted from fully expanded rosette leaves. Line colors indicate the specific fatty acid as indicated in the legend. c+t indicates the combined amounts of cis and trans isomers of 16:1 fatty acids which co-elute under the gas chromatographic temperature profile used.
Figure 2 Time-course analysis of the leaf membrane fatty acid composition in response to elevated growth temperature. Plants were germinated and grown for 7 d at 22°C before being shifted to high temperature (29°C). Fatty acid profiles of wild-type Arabidopsis were determined by gas chromatographic analysis at the designated times over ten days after the shift to elevated temperature as described in materials and methods.
Figure 3 Leaf fatty acid profiles obtained from Arabidopsis lines grown at 17°C (black bars) and 36°C (white bars). (A), wild-type Columbia. Mutant lines: (B) fad5; (C) fad6; (D) act1; (E) fad7 fad8; (F) act1 fad6.
Table 1 Arabidopsis lines used in this study. All lines contain mutations that primarily affect the composition of chloroplast membranes involved in photosynthesis.
Line Biochemical defect Primary affect on membrane composition Reference
fad5 16:0 to 16:1 desaturation on sn-2 of all chloroplast galactolipids Elevated 16:0; no 16:3 in chloroplast membranes [32]
fad6 16:1 to 16:2 and 18:1 to 18:2 desaturation on sn-1 and sn-2 of all chloroplast lipids Elevated 16:1 and 18:1; no 16:3, diminished 18:2, 18:3 [33]
fad7 fad8 16:2 to 16:3 and 18:2 to 18:3 desaturation on sn-1 and sn-2 of all chloroplast lipids Elevated 16:2 and 18:2; diminished 16:3 and 18:3 [35]
act1 Plastid glycerol-3-phosphate acyltransferase (GPAT) activity; first step in the prokaryotic pathway Slightly elevated 18:1; diminished levels of 16-C fatty acids (prokaryotic pathway) [34]
act1 fad6 Double mutant containing both the act1 and fad6 mutations Slightly elevated levels of 18:1 (than act1 alone); no elevation of 16:1 (as in fad6); prokaryotic pathway blocked This work
act1++ Plastid GPAT overexpressor Similar to wild type. Slightly elevated levels of 16:3, reflecting slightly enhanced flux through prokaryotic pathway This work
Table 2 Double bond indices of lines grown at 17°C and 36°C. The double bond index was calculated for each line from the mol % fatty acid values indicated in Figure 3.
Line Growth temperature
17°C 36°C
WT 2.39 1.46
act1 2.33 1.62
fad5 2.13 1.46
fad6 1.78 1.53
fad7 fad8 2.00 1.49
act1 fad6 2.01 1.53
Table 3 Temperature (TP, °C) at which fluorescence yield enhancement occurs in several Arabidopsis lines. Plants were grown at 17°C or 29°C and fluorescence was analyzed continuously using an OSI systems fluorometer during heating at 0.75 °C min-1, as described in methods. TP is the transition point temperature corresponding to 50% of the maximal quantum yield due to leaf heating. Values are the means ± SE on six determinations conducted on two different plants for 17°C-grown plants and four determinations for 29°C-grown plants. Asterisks indicate significant differences from the value obtained for wild-type plants, * P < 0.05; ** P < 0.01. ND, not determined.
17°C-grown 29°C-grown
Line TP (°C) °C above WT TP (°C)
WT 42.7 ± 0.21 --- 44.8 ± 0.9
fad6 45.0 ± 0.42 ** 2.2 44.9 ± 0.5
act1 44.2 ± 0.32 ** 1.5 44.2 ± 0.7
fad5 44.0 ± 0.26 * 1.2 44.2 ± 0.7
fad7 fad8 43.8 ± 0.64 1.0 ND
act1 fad6 43.0 ± 0.18 0.2 ND
act1++ 43.0 ± 0.53 0.2 ND
Table 4 Relative growth rates of Arabidopsis lines at different temperatures. All lines were grown on MS + 1% sucrose media. Growth rate is calculated as the difference of the natural log of seedling dry weight measured over a six d period.
Rate (ω-1)
22.5°C 28°C 30°C 34°C
WT 0.52 ± 0.13 0.18 0.22 ± 0.10 0.14
fad5 0.34 ± 0.01 0.21 0.24 ± 0.09 0.15
fad6 0.37 ± 0.05 0.17 0.24 ± 0.11 0.15
act1 0.60 ± 0.24 0.26 0.23 ± 0.02 0.13
act1 fad6 0.43 ± 0.15 0.17 0.15 ± 0.04 0.11
fad7 fad8 0.51 ± 0.10 0.22 0.26 ± 0.04 0.19
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| 15377388 | PMC524174 | CC BY | 2021-01-04 16:03:51 | no | BMC Plant Biol. 2004 Sep 17; 4:17 | utf-8 | BMC Plant Biol | 2,004 | 10.1186/1471-2229-4-17 | oa_comm |
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BMC Cardiovasc DisordBMC Cardiovascular Disorders1471-2261BioMed Central London 1471-2261-4-161545391310.1186/1471-2261-4-16Research ArticleSingle nucleotide polymorphisms in the apolipoprotein B and low density lipoprotein receptor genes affect response to antihypertensive treatment Liljedahl Ulrika 1Ulrika.Liljedahl@medsci.uu.seLind Lars 14Lars.Lind@medsci.uu.seKurland Lisa 1Lisa.Kurland@medsci.uu.seBerglund Lars 2Lars.Berglund@ucr.uu.seKahan Thomas 3Thomas.Kahan@med.ds.sll.seSyvänen Ann-Christine 1Ann-Christine.Syvanen@medsci.uu.se1 Department of Medical Sciences, Uppsala University, Uppsala University Hospital, Entrance 70, 3rd floor, 751 85 Uppsala, Sweden2 Uppsala Clinical Research Center (UCR), Uppsala University, 751 85 Uppsala, Sweden3 Division of Internal Medicine, Karolinska Institute, Danderyd Hospital, 182 88 Stockholm, Sweden4 Astra Zeneca Research & Development Mölndal, 431 83 Mölndal, Sweden2004 28 9 2004 4 16 16 2 6 2004 28 9 2004 Copyright © 2004 Liljedahl et al; licensee BioMed Central Ltd.2004Liljedahl 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
Dyslipidemia has been associated with hypertension. The present study explored if polymorphisms in genes encoding proteins in lipid metabolism could be used as predictors for the individual response to antihypertensive treatment.
Methods
Ten single nucleotide polymorphisms (SNP) in genes related to lipid metabolism were analysed by a microarray based minisequencing system in DNA samples from ninety-seven hypertensive subjects randomised to treatment with either 150 mg of the angiotensin II type 1 receptor blocker irbesartan or 50 mg of the β1-adrenergic receptor blocker atenolol for twelve weeks.
Results
The reduction in blood pressure was similar in both treatment groups. The SNP C711T in the apolipoprotein B gene was associated with the blood pressure response to irbesartan with an average reduction of 19 mmHg in the individuals carrying the C-allele, but not to atenolol. The C16730T polymorphism in the low density lipoprotein receptor gene predicted the change in systolic blood pressure in the atenolol group with an average reduction of 14 mmHg in the individuals carrying the C-allele.
Conclusions
Polymorphisms in genes encoding proteins in the lipid metabolism are associated with the response to antihypertensive treatment in a drug specific pattern. These results highlight the potential use of pharmacogenetics as a guide for individualised antihypertensive treatment, and also the role of lipids in blood pressure control.
Antihypertensive treatmentpharmacogeneticslipidsminisequencinggenotyping
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Background
Hypertension is a complex trait caused by multiple environmental and genetic factors interacting through the cardiac, vascular and endothelial systems. Several drug classes with different mechanisms of action, including inhibitors of the renin-angiotensin-aldosterone system (RAAS), calcium channel blockers, adrenergic receptor blockers and diuretics, are available for treatment of hypertension. However, the response to antihypertensive treatment is highly variable between individuals, which makes it difficult to predict the efficacy of a specific drug in the individual patient [1-3]. Currently, there are no clinically useful biochemical or metabolic markers for predicting the individual responses to antihypertensive treatment [4-6].
Twin studies have estimated that as much as half of the variability in blood pressure levels between individuals is due to genetic factors [7,8]. Based on the abundance of single nucleotide polymorphisms (SNPs) in the human genome [9], it can be expected that one or more SNPs occur in each of the genes encoding components of the blood pressure regulating systems, and that they are the genetic factors influencing individual blood pressure levels. Coding SNPs affecting the function of enzymes and receptors in pathways of blood pressure regulation, or regulatory SNPs, affecting the expression levels of genes, are likely to explain part of the variability of the response to antihypertensive treatment. Hence, these functional SNPs, or other SNPs inherited in linkage disequilibrium with them, could be potential pharmacogenetic markers for predicting the response to a certain drug, and thus guide the selection of the optimal drug for each individual patient [10-12].
The RAAS and the sympathetic nervous system play key roles in blood pressure regulation. We have earlier shown that polymorphisms in the angiotensin converting enzyme gene [13] and a SNP in the aldosterone synthase gene [14] are related to changes in blood pressure during treatment with the angiotensin II receptor blocker irbesartan, whereas two SNPs in the angiotensinogen gene were associated to the reduction in blood pressure by the β1-adrenergic receptor blocker atenolol [15]. Dyslipidemia with high levels of serum triglycerides and free fatty acids, and elevated serum cholesterol levels and low levels of high-density lipoprotein cholesterol are common in hypertensive patients. Association has been found between disturbance in lipid metabolism and hypertension, but so far no attempts have been made to relate variables reflecting lipids, or the genes involved in lipid metabolism, to the individual response to antihypertensive treatment.
We have recently developed a microarray based minisequencing system for parallel genotyping of multiple SNPs in blood pressure regulating candidate genes [16]. Here we analysed the relationships between the genotypes of SNPs in the apolipoprotein A-IV, apolipoprotein A-V, apolipoprotein B-100, low density lipoprotein receptor, hepatic lipase and lipoprotein genes and reductions in blood pressure in hypertensive patients randomised to monotherapy with either irbesartan or atenolol. We found that SNP alleles in the apolipoprotein B gene and the low density lipoprotein receptor gene were associated to the antihypertensive response after twelve weeks of treatment.
Methods
Study population
DNA extracted from blood samples from 97 hypertensive patients from the double blind parallel group "Swedish Irbesartan Left Ventricular Hypertrophy Investigation versus Atenolol" (SILVHIA) trial [17] were analysed. Men and women above the age of 18, having primary mild to moderate hypertension and left ventricular hypertrophy were enrolled in the trial and randomised to receive either 150 mg of the angiotensin II type 1 receptor blocker irbesartan or 50 mg of the β1-adrenergic receptor blocker atenolol once daily as monotherapy. The dose was doubled after six weeks if the diastolic blood pressure was ≥ 90 mmHg. Blood pressure was measured by trained nurses using a mercury sphygmomanometer, after the patients had rested for at least 10 min in the seated position. Left ventricular hypertrophy was defined as left ventricular mass index of > 131 g/m2 for men and > 100 g/m2 for women, assessed by echocardiography. The data presented relates to the change in blood pressure after 12 weeks of treatment. For details on the SILVHIA trial, see Malmqvist etal [17]. Baseline characteristics for the patients are presented in Table 1. The study was approved by the ethics committees of all participating centres of the SILVHIA trial and that of the Medical Faculty of Uppsala University.
Table 1 Characteristics of the hypertensive patients in the two treatment groups.
Irbesartan group2 Atenolol group2
Number of patients 48 49
Age (years) 54 ± 8 54 ± 8
Gender (proportion females) 37% 31%
Height (m) 1.74 ± 0.09 1.73 ± 0.09
Weight (kg) 83 ± 15 82 ± 14
Smokers trial start (%) 29 18
Baseline fs-cholesterol (mM) 6.1 ± 1.0 5.8 ± 1.1
Baseline fb-glucose (mM) 5.7 ± 3.1 5.2 ± 2.5
Pre-treatment SBP1 (mmHg) 164 ± 18 160 ± 20
Pre-treatment DBP1 (mmHg) 104 ± 7 103 ± 8
Change in SBP at 12 weeks (mmHg) -16 ± 20 -11 ± 16
Change in DBP at 12 weeks (mmHg) -9.0 ± 11 -12 ± 7.7
1 Systolic blood pressure (SBP) and diastolic blood pressure (DBP)
2 Data are mean ± SD
SNP markers and genotyping procedure
In our previous study [16], 98 SNPs were selected from the NCBI (dbSNP, ) and the SNP Consortium (TSC, ) databases and validated in a pooled DNA sample representing the Swedish population. A subset of these SNPs located in genes involved in lipid metabolism and that were polymorphic in the Swedish population were included in the study presented here, together with one additional SNP in the apolipoprotein A-V gene. See Table 2 for information on the SNPs.
Table 2 Investigated polymorphisms given as gene names, acronym and GenBank accession number.
Gene name and acronym1 dbSNP ID2 Amino acid alteration SNP name3
Apolipoprotein A-IV rs5092 Thr/Thr A1449G
APOA-IV; J02758
Apolipoprotein A-V rs662799 Promoter C31455T
APOA-V; AC074203
Apolipoprotein B-100 rs1801701 Arg/Gln G10108A†
APOB; M19828†; M19810§ rs1367117 Thr/Ile C711T§
Low density lipoprotein receptor rs688 Asn/Asn C16730T
LDLR; AF217403 rs5925 Val/Val C2000IT
Lipase, hepatic rs6083 Asn/Ser A110G
LIPC; M35429
Lipoprotein rs328 Ser/Term C9040G
LPL; AF050163 rs312 Intron G7315C
rs314 Intron A7360G
1 Gene name and acronym, GenBank accession number for the sequence used in the design of primers for the PCR and minisequencing reactions.
2 SNP identification number in the NCBI SNP database dbSNP, .
3 Corresponding to the nucleotide position in the gene sequence referenced in the first column and the nucleotide variation in the coding strand.
Fragments comprising the SNPs were amplified in multiplex PCR described previously [16]. A microarray based minisequencing single nucleotide primer extension assay, in which one or two of four ddNTPs labelled with the fluorophore Tamra (Perkin Elmer Life Sciences, Boston, MA, USA) were incorporated by the Thermo Sequenase™ DNA-polymerase at each SNP site. The incorporated ddNTPs were detected using a fluorescence scanner, and the fluorescence signals were extracted. A signal intensity fraction, obtained by dividing the fluorescence signal intensity for allele 1 with the sum of the fluorescence signal intensities for allele 1 and allele2, was used to assign the individual genotypes. The SNP APOA-V C31455T was genotyped using a microtiter plate minisequencing assay with tritium detection [18].
Statistical analyses
Analysis of covariance (ANCOVA) with each SNP as factor, baseline blood pressure as covariate and the change in blood pressure as response, was performed. The analyses were performed by treatment group and blood pressure measurement (systolic and diastolic blood pressures). Correction for multiple testing was performed by calculation of critical p-values corresponding to a nominal type I error of 5% using a permutation test [19]. Two tailed significance levels were used.
Results and discussion
We explored possible associations between individual genotypes of ten SNPs and reduction in systolic and diastolic blood pressure as response to treatment with atenolol or irbesartan (Figure 1) in samples from the SILVHIA trial [17]. In the irbesartan group, a change in systolic blood pressure appeared to be related to genotype for the SNPs ApoA-IV A1449G, ApoA-V C31455T and ApoB C711T. In the atenolol treatment group, presence of the C-allele of the SNP LDLR C16730T was associated to the reduction in systolic blood pressure.
Figure 1 Effect of SNP genotype on the change in blood pressure after 12 weeks of treatment for the ten SNPs. For each of the SNPs, the pattern of change in blood pressure related to genotype is illustrated for the systolic blood pressure (SBP) and diastolic blood pressure (DBP) in separate panels. In each panel, the mean change in blood pressure is shown for the SNP genotypes in the atenolol treatment group on the left, and the corresponding results in the irbesartan treatment group are given on the right. The error bars corresponds to the standard error of the mean. The p-values indicating significance for the APOA-IV A1449G, APOA-V C31455T, APOB C711T and LDLR C16730T SNPs are given in the corresponding panels. The number of individuals of each genotype is shown above the bars in each panel.
Correction for multiple testing using a permutation test [19] yielded critical p-values of 0.004 and 0.007 for systolic blood pressure after atenolol and irbesartan treatment, respectively, and 0.006 and 0.007 for the diastolic blood pressure, corresponding to the significance level of p = 0.05. After the permutation test, carriership of the C-allele of the C711T SNP in the apolipoprotein B gene remained significantly associated to the reduction in systolic blood pressure (p = 0.004) in the irbesartan treatment group (Figure 1) while the individuals homozygous for the T-allele showed no reduction in systolic blood pressure. The same pattern of response related to genotype was seen for diastolic blood pressure, although it did not reach statistical significance. In the atenolol treatment group, the SNP C16730T in the low density lipoprotein receptor gene showed a trend of association to the reduction in systolic blood pressure. Presence of the C-allele was related to blood pressure reduction (p = 0.006), while the individuals homozygous for the T-allele (n = 9) actually showed an increase in systolic blood pressure (Figure 1). A similar response pattern was not seen for the diastolic blood pressure during atenolol treatment (p = 0.44) (Figure 1). There were 39 carriers of the favourable C-allele of the APOB C711T SNP in the irbesartan treatment group. The average reduction in systolic blood pressure for these individuals was 19 mmHg, compared to 0 mmHg for the individuals lacking this allele. In the atenolol treatment group, the individuals carrying the favourable C-allele of the SNP LDLR C16730T showed an average reduction of 14 mmHg in systolic blood pressure compared to an increase of 7.5 mmHg for the individuals homozygous for the T-allele.
The SNP C711T in the apolipoprotein B gene is located in the coding region of the gene, and alters a threonine residue to an isoleucine residue in the protein. This SNP is located in the amino-terminal part of the enzyme and has been suggested to affect the dimerisation of apolipoprotein B and low density lipoprotein during cholesterol transport [20]. The C16730T SNP in the LDLR gene results in a synonymous amino acid change, however this SNP could be in linkage disequilibrium with another functional SNP potentially influencing the response to drug treatment. Irrespectively if the tested SNPs are actually functional, our findings imply a potential connection between lipid metabolism and response to antihypertensive treatment.
We have recently found circulating apolipoprotein B to be the most powerful predictor of endothelium-dependent vasodilation of the commonly used markers of cholesterol metabolism [21]. It is not evident, however, why apolipoproteins predict the response to irbesartan, and not to atenolol treatment, as these drugs appear to improve endothelium-dependent vasodilation to a similar extent [22]. Lipid abnormalities, commonly seen in hypertension, have been considered to be connected to the blood pressure level by the common denominators obesity and insulin resistance. Other studies have suggested a more direct effect of lipids in blood pressure control, as infusion of the fat emulsion Intralipid together with heparin increases blood pressure in healthy subjects [23-25]. This effect is more pronounced in the normotensive subjects with a family history of hypertension [26]. It has also been shown that an acute elevation of free fatty acids alters heart rate variability, an index of cardiac autonomic nervous system balance [27], suggesting that lipid metabolism may be involved in the regulation of cardiovascular autonomic tone. Thus our results that indicate involvement of components of lipid metabolism in the response to antihypertensive treatment are supported by cross-sectional epidemiological studies.
In our earlier exploratory study, 74 SNPs with a minor allele frequency over 5%, including nine of the SNPs analysed here were tested as predictors of blood pressure regulation in the SILVHIA study samples using a multiple regression model [16]. The main aim of this study was to establish the microarray-based genotyping system. Analysis of twenty-eight SNPs from this panel that are located in genes from the renin-angiotensin aldosterone system identified a SNP in the aldosterone synthase gene (CYP11B2 T267C) and two SNPs in the angiotensinogen gene (AGT G1218A and T1198C) that appeared to be associated to blood pressure reduction [14,15]. A limitation in these previous studies was that correction for multiple testing was not applied, whereas in the current study we used a permutation test.
A remaining weakness in our study is the small number of samples available for analysis, which does not allow detection of small to medium size gene effects, and results in uncertain estimation of the the magnitude of the effects detected. Moreover, in a small study there is the risk of a non-representative group of patients with respect to gender, age, and genotype distribution. Despite these limitations, we detected a significant effect of the SNP C711T in the apolipoprotein B gene and the SNP C16730T in the low density lipoprotein receptor after correction for multiple testing. The pharmacogenetically interesting results from our study need to be replicated in other studies.
As the C711T SNP in the apolipoprotein B gene predicted response to treatment with irbesartan, and the C16730T SNP in the low density lipoprotein receptor gene appeared to predict response to atenolol treatment, our results point at possible use of SNPs in genes encoding components of lipid metabolism in pharmacogenetic panels for selecting the optimal drug for each patient. To our knowledge our study is the first one to investigate the relationship between polymorphisms in genes involved in lipid metabolism and the response to antihypertensive treatment.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
UL performed the development of genotyping technology, genotyping lab work, interpretation of data and had a substantial role in writing the manuscript. LL provided clinical expertise, participated in selection of candidate genes and contributed to writing. LK provided clinical expertise, established a database of the SILVHIA phenotypes, and in writing. LB performed the statistical analysis. TK provided the SILVHIA samples and contributed to writing the manuscript. A-CS contributed by planning and supervision of the project, and to writing the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Financial support for this study was provided by the Swedish Research Council and the K&A Wallenberg foundation (WCN) (A-C S) and the Karolinska Institute, Stockholm (T K).
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| 15453913 | PMC524175 | CC BY | 2021-01-04 16:30:02 | no | BMC Cardiovasc Disord. 2004 Sep 28; 4:16 | utf-8 | BMC Cardiovasc Disord | 2,004 | 10.1186/1471-2261-4-16 | oa_comm |
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BMC Med Res MethodolBMC Medical Research Methodology1471-2288BioMed Central London 1471-2288-4-231545857110.1186/1471-2288-4-23Research ArticleParticipant characteristics associated with withdrawal from a large randomized trial of spermicide effectiveness Raymond Elizabeth G 1eraymond@fhi.orgChen Pai Lien 1pchen@fhi.orgPierre-Louis Bosny 1bpierre-louis@fhi.orgLuoto Joanne 2luotoj@hd01.nichd.nih.govBarnhart Kurt T 3kbarnhart@mail.obgyn.upenn.eduBradley Lynn 4lbradle@jhmi.eduCreinin Mitchell D 5mcreinin@mail.magee.eduPoindexter Alfred 6alfredp@bcm.tmc.eduWan Livia 7livia.wan@med.nyu.eduMartens Mark 8mark-martens@ouhsc.eduSchenken Robert 9schenken@uthscsa.eduNicholas Cate F 1011cate.nicholas@uvm.eduBlackwell Richard 12rblackwe@uabmc.edu1 Family Health International, Research Triangle Park, NC, USA2 National Institute of Child Health and Human Development, Rockville, MD, USA3 Department of Obstetrics and Gynecology and Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Medical Center, Philadelphia, PA, USA4 Department of Reproductive Medicine, Johns Hopkins Community Physicians, Baltimore, MD, USA5 University of Pittsburgh and the Magee-Womens Research Institute, Pittsburgh, PA, USA6 Department of, Baylor College of Medicine, Houston, TX, USA7 Department of Obstetrics and Gynecology, New York University School of Medicine, New York, NY, USA8 Minneapolis Medical Research Foundation, Hennepin County Medical Center, Minneapolis, MN, USA (Current affiliation: Department of Obstetrics and Gynecology, University of Oklahoma College of Medicine, Tulsa, OK, USA)9 Department of Obstetrics and Gynecology, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA10 Vermont Women's Choice Program of Planned Parenthood, Burlington, VT, USA11 Current affiliation: University of Vermont College of Medicine, Burlington, VT, USA12 Department of Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, AL, USA2004 1 10 2004 4 23 23 6 7 2004 1 10 2004 Copyright © 2004 Raymond et al; licensee BioMed Central Ltd.2004Raymond 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 most recent large efficacy trials of barrier contraceptive methods, a high proportion of participants withdrew before the intended end of follow-up. The objective of this analysis was to explore characteristics of participants who failed to complete seven months of planned participation in a trial of spermicide efficacy.
Methods
Trial participants were expected to use the assigned spermicide for contraception for 7 months or until pregnancy occurred. In bivariable and multivariable analyses, we assessed the associations between failure to complete the trial and 17 pre-specified baseline characteristics. In addition, among women who participated for at least 6 weeks, we evaluated the relationships between failure to complete, various features of their first 6 weeks of experience with the spermicide, and characteristics of the study centers and population.
Results
Of the 1514 participants in this analysis, 635 (42%) failed to complete the study for reasons other than pregnancy. Women were significantly less likely to complete if they were younger or unmarried, had intercourse at least 8 times per month, or were enrolled at a university center or at a center that enrolled fewer than 4 participants per month. Noncompliance with study procedures in the first 6 weeks was also associated with subsequent early withdrawal, but dissatisfaction with the spermicide was not. However, many participants without these risk factors withdrew early.
Conclusions
Failure to complete is a major problem in barrier method trials that seriously compromises the interpretation of results. Targeting retention efforts at women at high risk for early withdrawal is not likely to address the problem sufficiently.
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Background
Retention of participants has been a consistent problem in clinical studies of barrier contraceptive methods. For example, in six large studies of condoms, diaphragms, and spermicides conducted in the past decade, more than 30% of the participants failed for reasons other than pregnancy to complete the intended six months or six menstrual cycles of follow-up [1-6] Such high dropout rates seriously compromise the interpretation of trial results.
Issues regarding the design of barrier method studies have become increasingly important to researchers and public health scientists since the onset of the HIV epidemic because of the urgent need for methods to prevent this disease and other sexually transmitted infections. Numerous new barrier contraceptive methods and microbicides are currently in various stages of development and testing. Devising effective approaches to maximize retention in these studies will be critical.
In this analysis, we used data from a large, recently completed randomized trial of the efficacy and safety of five spermicide products to determine whether we could identify specific subgroups of participants who were at particular risk for failure to complete the trial. Our goal was to provide information that might assist in the development of targeted approaches to improve follow-up in future trials.
Methods
The primary purpose of this randomized trial was to estimate and compare the probability of pregnancy during six months of typical use of five nonoxynol-9 spermicide products. Safety, acceptability, and product use were additional specified outcomes. The trial was conducted at 14 sites in the United States between June 1998 and August 2002. The study was approved by the institutional review boards at each site and at Family Health International. All participants signed written informed consent forms before enrollment.
A full description of the trial procedures has been published previously [7]. In brief, the study enrolled 1536 healthy, sexually active women aged 18–40 years who had no history suggestive of subfecundity, who were at low risk for sexually transmitted infections, and who stated that they were willing to rely on a spermicide as their only contraceptive method for 7 months and to accept a moderate risk of pregnancy. At the enrollment visit, each volunteer had an interview, pelvic examination, Pap smear, wet prep, and urine pregnancy test. After eligibility was established, she completed a self administered questionnaire that included a question about strength of desire to avoid pregnancy. Each eligible participant was randomly assigned to one of the five study spermicide groups. She was given a supply of her assigned spermicide and a diary on which to record relevant information daily throughout the study. Some participants at two centers were enrolled into a substudy to evaluate colposcopic effects of the spermicides. Participants were encouraged but not required to inform their partners about the study except at one center, where the Institutional Review Board required signed consent of the partner.
Follow-up visits were scheduled at 4, 17, and 30 weeks after admission. Each participant was also asked to return to the study site if she wished to discontinue use of the spermicide. At each visit, the participant was interviewed, and a urine pregnancy test was done. At the 4-week and final visits, she completed a seven-page acceptability questionnaire. A pelvic examination was performed at the final visit and at other visits as indicated. Colposcopy substudy participants had a vaginal colposcopy at each follow-up visit. Each participant was asked to do a pregnancy test at home 2, 10, and 23 weeks after admission and to telephone the site with the result. If a participant missed a scheduled contact, study procedures required that staff make at least four attempts to contact her by at least two different modalities (telephone, mail, etc.) If they could not contact her directly, staff were to try to reach her through an alternate contact person identified by the participant at admission. Compensation for completion of all scheduled visits in the primary study ranged from $120 to $400 at the 14 study sites; at most sites, the amount was divided evenly among the separate visits.
In this analysis, we included all randomized participants except for 22 who were discovered to have been pregnant at admission and who therefore contributed no data to the primary analysis. We classified each of the remaining 1514 participants as having completed the study if she considered the spermicide to be her primary contraceptive method for at least 183 days after randomization, or she became pregnant before she stopped relying on it. Otherwise, she was classified as having failed to complete the study. We assigned each participant's last day in the analysis as the earliest of the following dates: the estimated date of fertilization of a pregnancy; the date she was last known to have been relying primarily on the assigned spermicide for contraception; the latest date her pregnancy status could be reliably determined; and 183 days after randomization. These rules were the same as those used in the prior primary pregnancy analyses [7].
We assessed the associations between failure to complete and 17 baseline factors of interest, which were prespecified before the analysis. Among the subset of participants who were in the analysis for at least 6 weeks, we examined the associations between final status category and various factors that characterized their experience during the first 6 weeks in the study. Factors were categorized in part to ensure substantial numbers of participants in each level. Hypotheses about the effects of factors on completion status were tested using chi square tests, Fisher's exact tests, Mantel Haenszel tests. Parameters estimated by multivariable logistic regressions were tested using Wald tests. We included factors in regression models if they were associated with the outcome (alpha<0.10) in bivariable analyses. None of the included factors were highly correlated. In both bivariable and multivariable analyses, a p-value of <0.05 was considered to indicate a significant association.
Results
Of the 1514 participants in this analysis, 635 (42%) failed to complete the study for reasons other than pregnancy. The proportion who withdrew early at each of the 14 study sites ranged from 17% to 83%. Only 3 centers had completion rates ≥65%. Forty nine participants (8% of those who withdrew) were discontinued by the site investigator because of a concern about their safety (such as increased risk of sexually transmitted infection that would indicate need for condom use, or use of a drug contraindicated in pregnancy that would indicate need for a more effective contraceptive than spermicide alone), staff error, or closure of the trial at the study site (Table 1). Of the 586 who withdrew on their own accord, 382 (65%) did not provide a reason, in most cases because they did not return for a discontinuation visit. The other 204 women reported a variety of reasons; 99 cited complaints that might have been related in some way to the spermicide. Of the other 105 participants, only 31 said that they would like to continue using the spermicide after leaving the study.
Table 1 Reasons for early withdrawal
Reason Participants N = 635
n %
Discontinued by site
Safety concerns 38 6%
Site closure/staff error 11 2%
Participant decision, reason provided* 204 32%
Unwillingness to continue study visits 60 9%
Objections from partner† 48 8%
Desire to change contraceptive method† 42 7%
Separation from partner 40 6%
Side effects or other medical events† 37 6%
Cessation of sexual activity 18 3%
Dissatisfaction with spermicide† 8 1%
Distrusted contraceptive efficacy† 8 1%
Desire for pregnancy 7 1%
Mistaken suspicion of pregnancy 4 1%
Participant decision, reason unknown 382 60%
*Participants may have provided more than one reason
†Considered "related to spermicide" in text
During their time in the analysis, women who failed to complete the study were less compliant with follow-up visits and diary records than women who completed (Table 2). Twenty-one percent of the population (135 participants) contributed no data at all to the analysis after admission.
Table 2 Protocol compliance by final status category
Final status category p-value†
Completed study Did not complete study
Number of participants 879 (58%) 635 (42%)
Median days in analysis per participant 183 32
Mean % of expected follow-up visits completed* 85% 64% <.0001
Mean % of expected diary days recorded* 97% 72% <.0001
Mean % of expected pregnancy tests completed* 95% 97% 0.0001
*The number of expected visits was prorated for each participant considering the total duration of her participation in the analysis
†p-value from independent sample t-test.
Of the 17 baseline factors examined separately, nine were associated with significantly increased (p < 0.05) relative risk of failure to complete the trial (Table 3). Factors that did not significantly increase risk included spermicide group, race, educational level, prior spermicide use, strength of desire to avoid pregnancy as reported on the self-administered admission questionnaire, desire for additional children, reason for choosing spermicide as a contraceptive method, and enrollment date relative to notification in 1999 of new data suggesting concern about the possibility that nonoxynol-9 might affect the risk of HIV acquisition. In multivariable analyses including the nine high risk factors and one additional factor (level of schooling, which was marginally associated with withdrawal, p = 0.09), only the associations with young age, unmarried status, frequent intercourse, enrollment at a university center, and enrollment at a center with a lower recruitment rate remained significant.
Table 3 Association between baseline factors and failure to complete study
Total Did not complete study Relative Risk (95% confidence interval)
N n %
Age
≤25 years 660 317 48.0 1.29 (1.15 – 1.45)
> 25 years 854 318 37.2 1
Relationship
single not living with partner 522 247 47.3 1.21 (1.07 – 1.36)
married or living with partner 992 388 39.1 1
Living children
None 639 288 45.1 1.14 (1.0 1 – 1.28)
Any 875 347 39.7 1
Baseline coital frequency
≥8 acts per month 862 389 45.1 1.21 (1.07 – 1.37)
≤7 acts per month 640 239 37.3 1
Geographic region of US
West 424 215 50.7 1.28 (1.12 – 1.46)
South 460 170 37.0 0.93 (0.80 – 1.09)
Northeast 630 250 39.7 1
Center type
university* 1069 476 44.5 1.25 (1.08 – 1.44)
other 445 159 35.7 1
Recruitment rate at study site
≤4 per month 640 301 47.0 1.23 (1.09 – 1.38)
> 4 per month 874 334 38.2 1
Reimbursement rate
≤$200 462 232 50.2 1.31 (1.16 – 1.47)
>$200 1052 403 38.3 1
Participation in colposcopy study
No 1381 590 42.7 1.26 (0.99, 1.61)†
Yes 133 45 33.8 1
*University centers were defined as those at which participants were seen in a primary university clinic setting. These included: University of Alabama at Birmingham, Birmingham, AL; University of Tennessee at Memphis, Memphis, TN; The University of Texas Health Science Center at San Antonio, San Antonio, TX; Baylor College of Medicine, Houston, TX; Medical University of South Carolina, Charleston, SC; University of Pittsburgh and the Magee-Womens Research Institute, Pittsburgh, PA; University of Pennsylvania Medical Center, Philadelphia, PA; University of Arizona Health Sciences Center, Tucson, AZ; NYU School of Medicine, New York, NY. Other centers included: Johns Hopkins Medical Services Corporation, Baltimore, MD; Vermont Women's Choice Program of Planned Parenthood, Burlington, VT; Eastern Virginia Medical School, Norfolk, VA; Minneapolis Medical Research Foundation, Minneapolis, MN; Planned Parenthood of Central and Northern Arizona, Phoenix, AZ
†Although this confidence limit includes 1, the p-value for the association between this factor and early withdrawal was 0.047.
Of the 1095 participants who contributed more than 6 weeks to the analysis, those who in their first 6 weeks were not compliant with follow-up visits, coital diary completion, or use of the spermicide during sex were significantly less likely than others to complete the study (Table 4). However, among the 925 participants who completed a contact during the initial 6 weeks, neither reported complaints nor any measure of satisfaction with the spermicide during the first 6 weeks was associated with increased risk of early withdrawal. We created a single variable to indicate whether or not each subject was "happy" with the spermicide in the first 6 weeks after admission (i.e., she found it acceptable, had no side effect or adverse event, and had a satisfied partner). Women who were "happy" were not significantly less likely than other women to withdraw early.
Table 4 Association between early study experience and failure to complete study*
Experience during first 6 weeks Total Did not complete study Relative Risk (95% confidence interval)
N n %
Completed at least one follow-up visit
yes 925 203 21.9 0.68 (0.53 – 0.87)
no 170 55 32.4 1
Completed at least one pregnancy test within first 4 weeks
yes 1070 250 23.4 0.73 (0.41 – 1.31)
no 25 8 32.0 1
Provided diary information for each day
yes 958 215 22.4 0.71 (0.54 – 0.94)
no 137 43 31.4 1
Used spermicide at every coital act
yes 739 153 20.7 0.70 (0.57 – 0.87)
no 356 105 29.5 1
Of those who completed follow-up visit
Reported medical complaints
yes 437 104 23.8 1.17 (0.92 – 1.50)
no 488 99 20.3 1
Disliked spermicide somewhat or a lot
yes 52 12 23.1 1.05 (0.63 – 1.76)
no 873 191 21.9 1
Distrusted contraceptive efficacy
yes 209 51 24.4 1.15 (0.87 – 1.52)
no 716 152 21.2 1
Disliked timing of application
yes 435 96 22.1 1.01 (0.79 – 1.29)
no 490 107 21.8 1
Complained about messiness
yes 375 76 20.3 0.88 (0.68 – 1.13)
no 550 127 23.1 1
Had problems with insertion
yes 465 105 22.6 1.06 (0.83 – 1.35)
no 460 98 21.3 1
Reported that partner disliked spermicide
yes 208 52 25.0 1.18 (0.90 – 1.56)
no 717 151 21.1 1
Happy with spermicide†
yes 408 80 19.6 0.82 (0.64 – 1.05)
no 517 123 23.8 1
*Includes only participants in the analysis for at least 6 weeks
†Did not dislike spermicide, had no side effect/AE, and had a satisfied partner
Discussion and conclusions
In analyzing data from longitudinal studies, researchers commonly assume that the experience of participants who withdraw early, had they stayed in the study, would have been similar to the experience of those who completed. However, this assumption is generally impossible to confirm and is often implausible. If the assumption is false, the study findings may substantially misrepresent the likelihood of the outcome in the study population. If the degree of misrepresentation is not consistent across study groups, comparisons could be seriously biased. Indeed, some expert epidemiologists have suggested that a trial with losses of greater than 20% of the participants "would be unlikely to successfully withstand challenges to its validity" [8,9].
Our study, like other recent barrier contraceptive method studies, did not even approach this standard: 42% of our enrolled participants did not complete the trial. Furthermore, the participants who failed to complete were different in key ways from those who did – they reported significantly more frequent coitus at baseline, and they also were more likely to be younger, unmarried, and poorly compliant with study procedures and method use in the first few weeks after admission. All of these characteristics were associated to some extent with elevated risk of pregnancy in our population [7], which suggests that our high withdrawal rate indeed may have distorted our findings: the pregnancy probabilities that we reported may be underestimates.
Clearly, increased attention to preventing this problem in future studies is imperative. In performing this analysis, our intention was to explore the potential impact of focusing retention efforts on participants with characteristics that are associated with failure to complete. However, although we did find some factors that were significantly associated with early withdrawal, none was highly predictive; that is, many participants without these factors failed to complete the study, and many with these factors did complete. Therefore, applying special efforts only to the high-risk participants would not likely have been sufficient to raise completion rates to desirable levels. In future trials, aggressive follow-up measures should be instituted universally. Such efforts might include assigning individual "case-workers" to participants, using novel means for communicating with the participants, such as pagers, conducting visits at participants' homes or at other locations convenient for them, providing specific reimbursement for expenses such as travel, parking, and child care, or providing extra incentives for completing follow-up. Researchers should be mindful, however, that one downside to some of these approaches is that they might influence participants' use of the study product or other behaviors related to the study outcome, which is detrimental if the goal of the trial is to estimate effectiveness during "typical use" of the product.
In our study, participants who enrolled at study centers where enrollment was slow were at increased risk of failure to complete the study. The reason for this association is unclear. Factors at these centers that hindered enrollment also may have adversely affected participants' interest in remaining in the study. Alternatively, in responding to pressure to hasten recruitment, these centers may have enrolled women who were not good candidates for study completion. This latter possibility emphasizes the need to maintain a careful balance between recruitment and retention goals: rapid recruitment of participants who then drop out of the study is not beneficial to the study as a whole.
The amount of reimbursement promised to our participants was strongly associated with final completion status in the bivariable analysis, but this effect was not significant when adjusted for other factors in our multivariable model. Numerous prior studies have shown that modest monetary incentives (e.g., $20 or less) increase response rates to surveys or short follow-up studies [10,11] Some data also suggest that the value of the incentive matters, although possibly with diminishing returns as the value increases [12,13]. However, the effect of higher levels of compensation in longer trials such as ours has not been rigorously studied. The possibilities that large financial incentives could be coercive, weaken generalizability, or encourage bogus participation are important concerns [14].
We were surprised that several of the factors that we expected would be associated with early withdrawal did not show significant associations in this analysis. When we began this analysis, we presumed that one reason for both slow enrollment and poor follow-up rates in barrier method trials is the relatively poor efficacy of these products: women may consider them to be temporary or backup methods and thus may be unwilling to use them as their sole or primary contraceptive for the 6–12 month duration of these studies. However, in our study, participants who strongly wished to avoid pregnancy or who had completed their desired family size were not more likely than others to drop out, nor were participants who expressed concerns about contraceptive efficacy early in the trial. Furthermore, neither early medical problems nor other complaints about the spermicides were predictive of withdrawal. These findings differ from that of a previous randomized trial of spermicides conducted mostly in developing countries. In that trial, participants who initially liked the assigned product very much were more likely than others subsequently to complete the study and to use the product for a longer period of time after admission [15].
In one respect, the poor retention rate in our study and in other barrier method trials is a result of the design of these studies, which typically call for censoring data (and in most barrier method trials, terminating active follow-up) when participants stop relying on the assigned contraceptive method. This design prohibits a true intent-to-treat analysis and is consequently a potential source of bias. Clearly, retention would be higher if the trials were designed at the outset to follow all subjects for the full intended duration of follow-up, even if they switched contraceptive methods. However, data from participants who are not using the method under study are not necessarily relevant to the efficacy and safety of the method. For the results of these trials to be meaningful, as many subjects as possible must not only complete follow-up but also continue to use the method during the full follow-up period. In our study, almost all the women who gave a reason for withdrawing early either cited problems with the spermicide or indicated that they wished to switch to another method after leaving the study. Our results are consistent with the findings of the 1995 National Survey of Family Growth, which showed that more than 47% of US spermicide users stopped relying on the method within the first 6 months of use [16]. These findings are discouraging: they suggest that even if the retention in the study could be improved by aggressive follow-up techniques, the likelihood of significant extension of method use is low.
Our results suggest that to reduce bias potentially introduced by a large proportion of participants failing to complete the study, future barrier contraceptive method researchers should consider approaches in addition to those directly aimed at tracking and retaining individual participants. For example, both to reduce the burden on participants and to help the study staff maintain focus on follow-up, limiting data collection to critical variables may be appropriate. Complete collection of key data is clearly preferable to inadequate collection of less important data. Reducing the planned duration of follow-up would also certainly reduce withdrawals; although a larger sample size would be needed to provide the desired levels of precision and power, this disadvantage might be overcome if the shorter study were more attractive to potential participants. Given the large proportion of women who stop using the method earlier than 6 months, it is not clear that 6-month pregnancy probabilities are clinically needed anyway. Adding a run-in period to the trial before randomization might be helpful in excluding participants likely to drop out very early after admission, although such an addition might deter enrollment of other women as well, which is also a problem in these trials. Finally, innovative study designs to measure product efficacy should be evaluated. The design proposed by Steiner et al., which compares the one-month pregnancy probability in a relatively small number of women using a contraceptive method to the probability in women using a placebo, offers an alternative to the traditional 6–12 month trial [17]. It showed some promise in a pilot study and is currently being further tested in a study of a new candidate spermicide.
Competing interests
No authors have any declared interests except the following:
Elizabeth Raymond owns stock in Johnson and Johnson.
Mitchell Creinin serves as a speaker for Ortho.
Alfred Poindexter has had research grants from Columbia Laboratories and serves as speaker for Ortho.
Authors' contributions
EGR helped design the trial, managed the trial, planned this analysis, and drafted the manuscript.
PLC and BPL helped design the trial and/or this analysis, performed the analysis, and contributed to the manuscript.
JL designed the trial and contributed to the manuscript.
Other authors participated in the design of the trial, conducted the trial, and contributed to the manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Support for this study was provided by Family Health International (FHI) with funds from the National Institute of Child Health and Human Development (NICHD) contract number N01-HD-7-3271. The views expressed in this article do not necessarily reflect those of FHI or NICHD.
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| 15458571 | PMC524176 | CC BY | 2021-01-04 16:32:50 | no | BMC Med Res Methodol. 2004 Oct 1; 4:23 | utf-8 | BMC Med Res Methodol | 2,004 | 10.1186/1471-2288-4-23 | oa_comm |
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BMC Med ImagingBMC Medical Imaging1471-2342BioMed Central London 1471-2342-4-41546961410.1186/1471-2342-4-4Research ArticleIdentification of hip fracture patients from radiographs using Fourier analysis of the trabecular structure: a cross-sectional study Gregory Jennifer S 1j.gregory@abdn.ac.ukStewart Alison 2a.stewart@abdn.ac.ukUndrill Peter E 3p.undrill@abdn.ac.ukReid David M 2d.m.reid@abdn.ac.ukAspden Richard M 1r.aspden@abdn.ac.uk1 Department of Orthopaedics, University of Aberdeen, Aberdeen, United Kingdom2 Department of Medicine and Therapeutics, University of Aberdeen, Aberdeen, United Kingdom3 Department of Biomedical Physics and Bioengineering, University of Aberdeen, Aberdeen, United Kingdom2004 6 10 2004 4 4 4 30 4 2004 6 10 2004 Copyright © 2004 Gregory et al; licensee BioMed Central Ltd.2004Gregory 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 study presents an analysis of trabecular bone structure in standard radiographs using Fourier transforms and principal components analysis (PCA) to identify contributions to hip fracture risk.
Methods
Radiographs were obtained from 26 hip fracture patients and 24 controls. They were digitised and five regions of interest (ROI) were identified from the femoral head and neck for analysis. The power spectrum was obtained from the Fourier transform of each region and three profiles were produced; a circular profile and profiles parallel and perpendicular to the preferred orientation of the trabeculae. PCA was used to generate a score from each profile, which we hypothesised could be used to discriminate between the fracture and control groups. The fractal dimension was also calculated for comparison. The area under the receiver operating characteristic curve (Az) discriminating the hip fracture cases from controls was calculated for each analysis.
Results
Texture analysis of standard radiographs using the fast Fourier transform yielded variables that were significantly associated with fracture and not significantly correlated with age, body mass index or femoral neck bone mineral density. The anisotropy of the trabecular structure was important; both the perpendicular and circular profiles were significantly better than the parallel-profile (P < 0.05). No significant differences resulted from using the various ROI within the proximal femur. For the best three groupings of profile (circular, parallel or perpendicular), method (PCA or fractal) and ROI (Az = 0.84 – 0.93), there were no significant correlations with femoral neck bone mineral density, age, or body mass index. PCA analysis was found to perform better than fractal analysis (P = 0.019).
Conclusions
Both PCA and fractal analysis of the FFT data could discriminate successfully between the fracture and control groups, although PCA was significantly stronger than fractal dimension. This method appears to provide a powerful tool for the assessment of bone structure in vivo with advantages over standard fractal methods.
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Background
The NIH Consensus Statement defines Osteoporosis as "a skeletal disorder characterised by compromised bone strength predisposing to an increased risk of fracture" [1]. Bone strength was defined as "the integration of two main features: bone density and bone quality". Currently, clinical diagnosis is based solely on bone mineral density (BMD) in accordance with the World Health Organisation guidelines [2]. Previous studies, however, have found that trabecular bone structure also plays a significant role in determining bone strength [3-5] with BMD explaining only 60 to 80 % of the variability in mechanical resistance [6].
Trabecular bone structure is visible on standard pelvic radiographs and many attempts have been made to quantify the quality of the structure and assess its relationship to osteoporosis and BMD. These range from visual scoring systems, such as the Singh index [7], through to sophisticated computerised methods based on fractals [8-10] and other image processing methods [11-13]. A review of the literature suggests that fractal analysis has been a method of choice in recent years for the analysis of trabecular bone structure in CT scans [14,15], MRI [16], histology [17] and radiographs [18-21], although it has not been established categorically that it is preferable to other methods of texture analysis [22,23]. By reducing all the information in the image to one descriptor, the fractal dimension [24], a large part of the information is lost. The Fourier transform of an image expresses the information in the image in terms of spatial frequencies rather than distances. Various methods can be applied to extract information from the Fourier transform [25], including the fractal dimension [24]. However such methods have not been fully exploited for analysing bone structure [8,26-30].
In this study we investigate the use of Fourier transforms and Principal Components Analysis to generate a mathematical model of the data which can be used to help classify individuals according to the presence or absence of a hip fracture. Principal component analysis (PCA) [31] is a data reduction technique that has been applied in many fields of study, including investigation of gene expression [32], development of an electronic nose [33] and tracing of the evolutionary changes in fish morphometry [34]. It describes data in terms of a small number of orthogonal, linearly independent components which contain the majority of the information. PCA has no preconditions, such as relying on the data to fit a normal or fractal distribution, but builds a mathematical model based on the correlations present in the data. An eigenanalysis of the correlation or covariance matrix is used to perform PCA. The resulting components are then selected in order of the amount of variance they account for, enabling an efficient mapping of the data. As the first few components account for the vast majority of the variance in the original data, they can be selected for analysis whilst the remainder are discarded as 'noise'. In this way, the number of variables can be greatly reduced whilst maintaining the information present in the original data. In this pilot study we used these methods to investigate the similarities and differences between trabecular bone structure in fracture and control groups using standard radiographs of the proximal femur.
Methods
Study data
A set of digitised standard pelvic radiographs was available from a previous investigation into the morphology of the proximal femur [35]. These radiographs were taken from an earlier study [36], that had examined three groups (osteoporotic, osteoarthritic and control) of age matched, postmenopausal women (30 subjects per group). Subjects with osteoarthritis were excluded from the present study. All patients had undergone a scan of the unfractured hip by dual-energy x-ray absorptiometry (DXA) using a Norland XR-26 scanner (CooperSurgical Inc, Trumbull, CT). The controls had had their left hip scanned. All patients and controls had had a pelvic antero-posterior radiograph recorded within a year of the DXA scan. We used those radiographs and the femoral neck BMD (Neck-BMD) data in the current study. A data set of 50 digitised radiographs was available comprising 26 hip fracture patients (HIP) and 24 controls (CNT). The radiographs were digitised, using a Howtek MultiRAD 850 scanner (Howtek, Hudson, New Hampshire) at a resolution of 584 dpi (44 μm per pixel) and a depth of 12 bits. The age, height and weight of each subject were also recorded.
Region selection
Five regions of interest (ROIs) were selected relative to the principal trabecular systems in locations known to be related to hip fracture via the Singh index [7] and BMD analysis [37]. To ensure reproducibility, their locations were determined in relation to the centre and angle of the narrowest part of the femoral neck and the centre and radius of the femoral head on each image, as shown in Figure 1.
Figure 1 Regions of interest. Displays the five regions of interest, upper femoral head (UH), central femoral head (CH), upper femoral neck (UN), Ward's triangle area (WA) and the lower femoral neck (LN) used for analysis. Points A to G are determined by the femoral head and neck and used to locate the ROIs. Points A and E mark the femoral neck width. Points B, C and D lie at 1/4, 1/2 and 3/4 along this line. Point F is the centre point of the femoral head, point G at 1/2 the radius of the femoral head at an angle of 45 degrees to the neck width, 135 degrees to the neck shaft, shown as a dashed line through point C.
Each ROI was 256 × 256 pixels (11.3 mm square), to enable use of the fast Fourier transform, and were selected as follows. The upper region of the head (UH) lies on the upper part of the principal compressive trabeculae, the central region of the head (CH) is at the intersection of the principal compressive and tensile trabeculae, the upper region of the neck (UN) lies on the principal tensile trabeculae, the lower region of the neck (LN) is at the base of the principal compressive trabeculae and finally Ward's triangle (WA) which lies between these structures. The points and regions were identified using a macro written for Image Pro Plus software (version 4.1.0.0, Media Cybernetics, Silver Spring, Maryland). The femoral head was described by a best-fit circle, calculated from a series of manually marked points around the outline of the femoral head. Between 15 and 20 evenly spaced points were used to describe the outline, depending on the size of the head. The radius and centre (marked as F in Figure 1) of the femoral head were then taken from this circle. The narrowest part of the neck (neck-width) was determined using two automatic edge traces, marking the upper and lower outlines of the femoral neck. The first point and the direction for each trace were marked manually; the edge of the neck could then be identified automatically by the software. The neck width (A – E in Figure 1) was calculated by finding the smallest Euclidean distance between the traces. The centre of the neck was located at the mid-point of this line (point C) and the axis of the femoral neck was taken to be a line perpendicular to this through the centre of the neck (dashed line). The top right corner of the WA region was located at the midpoint of the neck width (point C). Points B and D were placed 25% and 75% of the way along the neck width and used as the midpoints of the UN and LN regions respectively. Point F, the centre of the femoral head marked the centre of the CH region and point G, the centre of the base of the UH region. Point G was placed one half of the femoral head radius above point F, at a 45-degree angle to the neck width (A-E).
Region analysis
Analysis was performed using Matlab software (version 6.1.0, MathWorks Inc, Natick, Massachusetts). A fast Fourier transform was generated for each ROI and three profiles were generated using data from the power spectrum. Firstly a global or circular profile (CircP) was generated, composed of the magnitude at each spatial frequency averaged across all angles, resulting in a profile with 128 data points. To create this profile, each pixel in the Fourier transform was assigned to the integer spatial frequency that most closely matched its' distance from the zero'th component.
The angle of preferred orientation was calculated by finding the angle of the maximum value in the power spectrum for the first 25 spatial frequencies [38]. The maximum value over this range relates to the dominant texture orientation within the image, the trabecular structure. As data in the frequency domain relate to features in the spatial domain rotated by 90°, the median of the values plus 90° was taken as the angle of preferred orientation for each image. Due to the symmetry of the Fourier power spectrum, angles were only calculated between 0° and 180°, rather than 0° and 360°. Two more profiles were then generated, parallel with (ParP) and perpendicular to (PerP) the angle of preferred orientation. In this case the average value was calculated at each spatial frequency from all points lying within ± 5° of the desired angle (Fig. 2).
Figure 2 Profile generation. (A) Shows a typical region of interest (contrast enhanced for visualisation) showing the trabecular bone structure, in this case aligned approximately 22° to the vertical. (B) The central section of the FFT (128 × 128 pixels). The horizontal and vertical axes have been marked with a mid-grey tone to indicate that they have been excluded from the angle calculation. The bright strip at the centre (running from top left to bottom right) shows the preferred orientation of the trabeculae. Angles calculated from the Fourier power spectrum correspond to the same angles in the spatial domain, rotated by 90°. (C) The pixels with the maximum values are marked using white squares for the first 25 spatial frequency values of the Fourier power spectrum. The median angle, lying 21.8° from the horizontal is shown by a dashed white line. (D)_The regions used to generate the parallel (shaded black) and perpendicular (shaded white) profiles, based on the orientation of the trabecular structure.
Principal component analysis
Principal component analysis [31] was used to model statistically the shape of each set of profiles (parallel, perpendicular and circular). This was performed using an eigenanalysis of the correlation matrix. The eigenvectors then become the principal components and are selected in order, depending on their eigenvalue. The eigenvalues are associated with the components in decreasing order, the largest eigenvalue is associated with the first component and the smallest with the last. In order to choose the number of components for analysis, a scree plot [31,39] was generated by plotting the eigenvalues (representing the proportion of variance described by each component) against the component number (Figure 3). In each case, the first few principal components were selected for analysis using the scree test [39] to find an 'elbow' in the slope of the plot. This is used as a threshold between the components that contained useful information, which were then used as input variables for further analysis, and those that could be attributed to noise.
Figure 3 Scree plot. Example of a scree plot from the perpendicular profile. The first component typically accounts for the largest amount of variance. The components are chosen to the left of an 'elbow' in the plot. Here components 1 to 5 are included in the analysis as they lie before the 'elbow' at point6 (eigenvalue = 1.63).
Fractal analysis
Fractal analysis was performed on each profile using a method similar to the Fourier transform technique described by Majumdar et al [40]. The average power spectrum of the circular profile was plotted on a log-log scale, three approximately linear regions were defined and the gradient (slope) of a straight line fitted to each region was found; slopeA, a 'coarse' slope, where the log of the spatial frequency is less than or equal to 1.0, slopeB a 'medium' slope, where the log of the spatial frequency lies between 1.0 and 1.75 and slopeC, a 'fine' slope where the log of the spatial frequency is above 1.75. The fractal dimension was calculated for each slope using the formula suggested by Majumdar et al [40]
Statistical analysis
Stepwise discriminant analysis was used to select principal components that could be combined to build a linear classifier. If the stepwise procedure failed to select any components, the most accurate of the individual components was chosen. The same procedure was used to discriminate between the groups using the fractal dimension. Measurement of the area under the ROC curve was used to compare the classifiers built using the discriminant analysis [41]. A three way ANOVA was applied in order to determine whether there were significant differences between the performance of classifiers depending on the type of analysis, the profile used or the region analysed. Pearson product moment correlation was applied to examine the relationship with age, BMI and Neck BMD for the strongest classifiers. A one-way ANOVA was used to test for significant differences in the performance of the slopes from each spatial frequency band used in the fractal analysis. T-tests, correlation and ANOVA were performed using SigmaStat (version 2.03, SPSS Science, Chicago). Principal component analysis, discriminant analysis, and measurement of the area under the ROC curve were calculated using SPSS (version 10 SPSS Science, Chicago).
Results
There were no significant differences between the age, height, weight or body mass index (BMI) of the fracture and control groups (Table 1). As expected femoral neck-BMD was significantly lower in the fracture group in comparison to the control group (P = 0.001).
Table 1 Summary of anthropometric variables for the fracture and controls groups. Mean and standard deviation (SD) of the age, height, weight, BMI and BMD of the fracture and control groups. P values were obtained from a two-tailed t-test.
Variable Control Group (n = 24) Fracture Group (n = 26)
Mean SD Mean SD P
Age, years 69.1 6.5 69.2 6.3 0.97
Height, cm 158.6 7.1 157.1 0.4 0.38
Weight, kg 63.4 9.5 61.0 9.0 0.38
Body Mass Index, kg/m2 25.2 3.2 24.8 4.1 0.72
Femoral neck BMD (g cm-2) 0.70 0.11 0.604 0.066 0.001
The Receiver Operating Characteristic (ROC) curve is a plot of True Positive Fraction v False Positive Fraction (or Sensitivity v 1 – Specificity). The area underneath the curve (Az) represents the performance of the classifier ranging from a value of 0.5 if it is no better than chance to 1.0 for a perfect discriminator. Table 2 shows Az for PCA analysis by region for the circular, perpendicular and parallel profiles respectively, discriminating fracture and control cases. A wide range of values was observed (overall mean 0.70, standard deviation 0.11). Some were little better than chance (Az = 0.5) (mostly derived from the parallel profile) and the strongest ones were from the perpendicular profiles. The 5 largest areas under the ROC curve were obtained by PCA of the perpendicular profile of the lower neck, upper and central head regions (Table 3) (Az = 0.93, 0.84 and 0.84 respectively), followed by PCA analysis of the circular profile in the upper head region (Az = 0.76) and, finally, fractal analysis of the parallel profile in the upper neck region (Az = 0.75). Femoral neck BMD lay between the third and fourth best texture measures (Az = 0.79 95% CI = 0.66 – 0.91). Plots of the ROC curves for the strongest combinations of image analysis classifier are shown in Figure 4.
Table 2 Classification accuracy for each region-profile combination. Area under the ROC curve for principal component analysis of each profile by region of the femoral neck. Analysis using three-way ANOVA found that the area under the ROC curve was significantly higher in the perpendicular profile than in the parallel profile. (P < 0.05)
Region Circular (95% CI) Parallel (95% CI) Perpendicular (95% CI)
Upper head 0.76 (0.63 – 0.89) 0.57 (0.41 – 0.73) 0.84 (0.73 – 0.95)
Central head 0.59 (0.43 – 0.75) 0.56 (0.40 – 0.73) 0.84 (0.72 – 0.95)
Upper neck 0.72 (0.58 – 0.86) 0.72 (0.57 – 0.86) 0.67 (0.52 – 0.82)
Wards triangle 0.74 (0.61 – 0.88) 0.61 (0.45 – 0.76) 0.71 (0.56 – 0.86)
Lower neck 0.71 (0.56 – 0.85) 0.55 (0.39 – 0.71) 0.93 (0.87 – 1.00)
Table 3 The best five classifiers: Area under the curve and correlation with BMD, age and BMI. Area under the ROC curve (Az) for each of the best 5 classifiers and the correlation with age Rage, femoral neck BMD (RBMD) and body mass index (RBMI) and associated significance values (P).
Analysis Profile ROI Az(95% CI) RBMD(P) Rage(P) RBMI(P)
PCA PerP LN 0.93 (0.87 – 1.00) 0.09 (0.55) 0.14 (0.34) -0.08 (0.58)
PCA PerP UH 0.84 (0.73 – 0.95) 0.09 (0.52) -0.17 (0.24) -0.03 (0.86)
PCA PerP CH 0.84 (0.72 – 0.95) 0.06 (0.70) 0.27 (0.055) -0.11 (0.46)
PCA CircP UH 0.76 (0.63 – 0.89) -0.16 (0.28) -0.15 (0.29) 0.07 (0.62)
Fractal ParP UN 0.75 (0.61 – 0.89) -0.30 (0.034) 0.25 (0.081) -0.04 (0.78)
Figure 4 Comparison of ROC curves. Comparison of the ROC curves for the strongest classifier from the combination of (A) PCA analysis of the perpendicular profile (Lower neck region), (B) PCA analysis of the circular profile (Upper head region) and (C) Fractal analysis of any profile (Upper neck region).
Table 3 also shows the correlations between the top five classifiers with age, BMI and Neck-BMD. No significant correlations were found between any of these classifiers and either age or BMI and, for the top three, there was also no significant correlation with Neck-BMD (P > 0.05). The fifth placed classifier, fractal analysis of the parallel profile in the upper neck region, was the only one significantly associated with Neck-BMD (P = 0.034).
A three-way analysis of variance was used to examine differences in performance due to the region, profile or type of analysis used. It showed that overall PCA analysis performed significantly better than fractal analysis (P = 0.019) and that analysis of both the perpendicular and circular profiles performed significantly better than the parallel profile (P = 0.003 and 0.011 respectively). No significant differences were found between the different regions of the femoral neck (P = 0.241) (despite the apparently large differences in Az). The power of this test was 0.69, 0.97 and 0.15 for the investigation of differences due to the method of analysis, type of profile used and the region analysed respectively.
Table 4 presents the mean Az for the slope from each of the spatial frequency bands for all regions of interest. This was assessed for each profile individually and also for all the profiles together. A one-way ANOVA was used to test for significant differences in Az between slopes A, B and C. In the individual profiles, slopeA performed significantly better than slopeC for the circular profile (P = 0.008), however when all the profiles were considered, no significant differences were apparent (P = 0.26).
Table 4 Comparing slopeA, slopeB and slopeC. The average and standard deviation of the area under the ROC curve (Az) are presented for each of the slopes used in the fractal analysis for all regions of interest. A significant difference was found between slopeA and slopeC in the circular profile, however when all the profiles were compared, no significant differences were found.
SlopeA SlopeB SlopeC P
All profiles 0.601 (0.074) 0.598 (0.055) 0.565 (0.067) 0.260
Circular 0.670 (0.072) 0.611 (0.022) 0.531 (0.026) 0.008
Parallel 0.544 (0.042) 0.620 (0.083) 0.563 (0.037) 0.140
Perpendicular 0.589 (0.047) 0.563 (0.032) 0.600 (0.104) 0.678
Discussion and conclusions
In these short series, this study found that texture analysis of standard radiographs using the fast Fourier transform can yield variables that are significantly associated with fracture but not significantly correlated with age, body mass index or Neck-BMD. Both PCA and fractal analysis of the FFT data could be used to discriminate successfully between the groups, although overall PCA was significantly stronger than fractal dimension. The best results from this study were not significantly correlated with femoral neck-BMD, age or BMI, indicating their potential for use as an independent predictor of fracture. The radiographic appearance of bone is known to be affected by factors including the size of the patient. As there was no significant difference in the BMI of the fracture and control groups, it is unlikely that this has influenced the results, however it is an issue that will need addressing in future studies.
The PCA method extends a method previously developed for analysis of histological sections [26]. The use of oriented profiles improved the performance of the analysis by selecting directions in which there was the most information about bone structure i.e. perpendicular to the preferred orientation of the trabeculae. PCA considerably reduces the number of variables required to characterise the image via its power spectrum. For example, in this study, we start with a 256 × 256 pixel ROI (65,536 pixels), the Fourier transform is performed and a profile of 128 spatial frequency values is generated. For each profile, PCA was able to describe over 70 % of the variance present in the data using only 5 components or fewer. Overall, the performance of principal components analysis was significantly stronger than that of fractal analysis (P < 0.01). One advantage of PCA that may contribute to this finding is the ability to summarise the information present in the dataset with a small number of components via an economical mapping of the variance present in the data. In addition, the property of orthogonality between these components ensures that the variables generated are linearly independent (Fig. 5). Benefits can also be found by the use of a model built on the mathematical distributions present in the data, rather than expecting the data to meet a given mathematical property, such as fitting a fractal distribution.
Figure 5 Plot of two principal components. Example of a scatterplot of two principal components. For FFT/PCA analysis of the upper head region, principal components 4 and 5 were selected by stepwise analysis and are shown here. They are plotted against each other with fracture and control subjects identified using separate markers. The lack of correlation between the components can be seen (r = 0.040, P = 0.997).
Previous studies using non-fractal analysis of the Fourier power spectrum have focussed on images of the spine or wrist, where the alignment of trabeculae is generally orthogonal [28-30]. In such images, analysis of trabecular orientation can be performed by examining the vertical and horizontal sectors as the trabeculae lie predominantly in these directions. The trabecular structure of the femur is more complicated as the trabeculae are aligned in arcs, so the preferred orientation changes throughout the proximal femur. Analysis parallel to the preferred orientation of the trabeculae was significantly poorer than analysis using either the perpendicular or circular profiles (P < 0.05). Analysis in the perpendicular direction was strongest overall, although it was not significantly better than the circular profile. This accords with the increasingly anisotropic nature of trabecular bone with aging; bone loss is not evenly distributed but is lost primarily at angles perpendicular and oblique to the preferred orientation of the trabeculae [30]. This loss heightens the risk of fracture, especially if the impact is from the side, as expected from a typical fall from standing height, as there are fewer trabeculae orientated in this direction to absorb the force of impact.
In summary, this paper presents a new method for analysing the structure of trabecular bone from standard radiographs. It demonstrates that the Fourier transform can be used to describe structural information in images which may be related to fracture, independently of BMD. This study is limited by the small size of the data set and further analysis is needed to validate these findings. This should be performed on a similar series of radiographs, consisting of fracture and control subjects scanned at the same resolution. The methods from this study could then be applied directly to this group (without recalculating the PCA) to evaluate whether they were generally applicable. However the success of both this and our previous study, using similar techniques to analyse histological sections, indicates that this may be an effective method with clinical utility for describing bone quality statistically in terms of structural parameters.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
Author JG helped design the study, performed the image and data analysis and drafted the manuscript
Author AS collected the data/images used within this study and helped with writing of the paper.
Author PU assisted with some of the practical approaches, and the writing of the paper
Author DMR designed the initial case control study and assisted with interpretation of the results and writing the paper
Author RMA helped with the design of the study, the interpretation of the results and the writing of the paper.
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 PPP Foundation and the Arthritis Research Campaign for funding this study and the MRC for a Senior Fellowship for RMA. We are grateful to Mr G. Turner for expert technical assistance. AS is an Arthritis Research Campaign Postdoctoral Research Fellow.
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| 15469614 | PMC524177 | CC BY | 2021-01-04 16:30:01 | no | BMC Med Imaging. 2004 Oct 6; 4:4 | utf-8 | BMC Med Imaging | 2,004 | 10.1186/1471-2342-4-4 | oa_comm |
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BMC Pregnancy ChildbirthBMC Pregnancy and Childbirth1471-2393BioMed Central London 1471-2393-4-201545012310.1186/1471-2393-4-20Research ArticleA comprehensive evaluation of food fortification with folic acid for the primary prevention of neural tube defects Liu Shiliang 1shiliang_liu@hc-sc.gc.caWest Roy 2roywest@mun.caRandell Edward 3erandell@mun.caLongerich Linda 2lindal@mun.caO'Connor Kathleen Steel 4koconnor@healthunit.on.caScott Helen 5helen_scott55@hotmail.comCrowley Marian 6hcc.cromar@hccsj.nf.caLam Angeline 37abddoell@primus.caPrabhakaran Victor 8victor.prabhakaran@lhsc.on.caMcCourt Catherine 1Catherine_McCourt@hc-sc.gc.ca1 Health Surveillance and Epidemiology Division, Centre for Healthy Human Development, PPHB, Health Canada, Ottawa, Ontario, Canada2 Division of Community Health, Faculty of Medicine, Memorial University, St. John's, Newfoundland and Labrador, Canada3 Health Sciences Centre and Division of Laboratory Medicine; Faculty of Medicine, Memorial University, St. John's, Newfoundland and Labrador, Canada4 Public Health Research, Education and Development Program, Kingston, Frontenac and Lennox & Addington Health Unit, Kingston, Ontario, Canada5 Department of Public Health Sciences, University of Toronto, Toronto, Ontario, Canada6 Provincial Medical Genetics Program, Health Care Corporation of St. John's, St. John's, Newfoundland and Labrador, Canada7 Department of Earth Sciences, University of Waterloo, Waterloo, Ontario, Canada8 London Health Sciences Centre & Department of Clinical Biochemistry, University of Western Ontario, London, Ontario, Canada2004 27 9 2004 4 20 20 13 5 2004 27 9 2004 Copyright © 2004 Liu et al; licensee BioMed Central Ltd.2004Liu 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
Periconceptional use of vitamin supplements containing folic acid reduces the risk of a neural tube defect (NTD). In November 1998, food fortification with folic acid was mandated in Canada, as a public health strategy to increase the folic acid intake of all women of childbearing age. We undertook a comprehensive population based study in Newfoundland to assess the benefits and possible adverse effects of this intervention.
Methods
This study was carried out in women aged 19–44 years and in seniors from November 1997 to March 1998, and from November 2000 to March 2001. The evaluation was comprised of four components: I) Determination of rates of NTDs; II) Dietary assessment; III) Blood analysis; IV) Assessment of knowledge and use of folic acid supplements.
Results
The annual rates of NTDs in Newfoundland varied greatly between 1976 and 1997, with a mean rate of 3.40 per 1,000 births. There was no significant change in the average rates between 1991–93 and 1994–97 (relative risk [RR] 1.01, 95% confidence interval [CI] 0.76–1.34). The rates of NTDs fell by 78% (95% CI 65%–86%) after the implementation of folic acid fortification, from an average of 4.36 per 1,000 births during 1991–1997 to 0.96 per 1,000 births during 1998–2001 (RR 0.22, 95% CI 0.14–0.35). The average dietary intake of folic acid due to fortification was 70 μg/day in women aged 19–44 years and 74 μg/day in seniors. There were significant increases in serum and RBC folate levels for women and seniors after mandatory fortification. Among seniors, there were no significant changes in indices typical of vitamin B12 deficiencies, and no evidence of improved folate status masking haematological manifestations of vitamin B12 deficiency. The proportion of women aged 19–44 years taking a vitamin supplement containing folic acid increased from 17% to 28%.
Conclusions
Based on these findings, mandatory food fortification in Canada should continue at the current levels. Public education regarding folic acid supplement use by women of childbearing age should also continue.
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Background
Neural tube defects (NTDs) are birth defects resulting from the failure of neural tube closure during early development of the human embryo. The 1997 Canadian national NTD birth prevalence was 0.75 per 1,000 births (live births and stillbirths), down from 1.16 per 1,000 in 1989 [1]. The rates tend to be higher in the eastern provinces than in the west [2-4]. Historically, Newfoundland has had one of the highest rates in North America with a reported average yearly rate for 1976–1997 of 3.4 per 1,000 births (including live births, stillbirths and fetuses from pregnancies terminated after a prenatal diagnosis of an NTD) [4].
Evidence from a number of studies has demonstrated that periconceptional use of vitamin supplements containing folic acid reduces the risk of NTDs [5-8]. Although the mechanism of action of this nutrient in influencing the risk of NTDs is poorly understood, the evidence of the benefit of folic acid has led many health organizations since late 1992 to recommend periconceptional folic acid supplementation, at a level of 400 μg /day for low risk women [9-11].
Because of concern that public education campaigns alone would not be effective in achieving optimal periconceptional folic acid intake for the majority of women, food fortification with folic acid was proposed as a strategy to ensure that all women of childbearing age increase their dietary intake of this vitamin. In November 1998, Health Canada mandated fortification of white flour and enriched pasta and cornmeal with folic acid [12]. Since diets vary, it was known that it would be virtually impossible to fortify food with folic acid at a level that ensures that the target population receives an additional 400 μg /day, while protecting the non-targeted population from an undesirably high amount. As a result, conservative levels of fortification were introduced. White flour is fortified with folic acid at a level of 0.15 mg per 100 g of flour. This intervention was expected to increase the average daily folic acid intake of women of childbearing age by about 100 μg [13].
The question of whether folic acid fortification of grain products poses any serious health risk has been controversial. The main concern has been the potential masking of vitamin B12 deficiency, a condition that affects 10–15% of the population over age 60 years [14,15]. Increased folic acid intake may correct the haematologic signs of vitamin B12 deficiency, thus delaying diagnosis and treatment of the condition while its attendant neurologic manifestations progress. Seniors may be at particular risk since the incidence of vitamin B12 deficiency increases with age.
We therefore undertook a comprehensive population based study to evaluate the effectiveness of the public health strategy of food fortification with folic acid and to determine possible adverse effects resulting from fortification.
Methods
Study design
This evaluative study was designed as a population based study and included four components as follows: I) Determination of rates of NTDs; II) Dietary assessment; III) Blood analysis; IV) Assessment of knowledge and use of folic acid supplements. The latter three components of the study were carried out in two phases; the first phase took place prior to the introduction of mandatory fortification, from November 1997 to March 1998 and the second phase occurred from November 2000 to March 2001, after two years of implementation of mandatory fortification.
This study was undertaken in Newfoundland because of the historically high rates of NTDs in the province, and because of strong interest in the health community in this initiative. Newfoundland and Labrador, with a population of approximately 500,000, has about 5,000 births annually. An urban (St. John's) and rural (Clarenville, Port Blandford, Random Island area) location in the province were chosen as the sites for this study. Data collected from these sites were compared between Phase I (November 1997 to March 1998) and Phase II (November 2000 to March 2001). Table 1 shows schematically the framework including objectives and sampling of subjects for this study. As part of this project, dietary assessment, blood analysis and assessment of knowledge and use of supplements were also carried out in a 2-phase population based study of women of reproductive age in Kingston, Ontario and environs. The results of this study will be reported elsewhere.
Table 1 Framework for a two phase, multi site study to examine the effects of food fortification with folic acid
Content Study objective Sample ** Location
I. Rates of NTDs Determine rate of NTD-affected pregnancies, pre and post fortification Newfoundland population Newfoundland
II. Dietary assessment* Determine dietary intake of folate, pre and post Fortification A) Non-pregnant women of childbearing age (19–44 years), not taking supplements containing folic acid; St. John's, Rural Newfoundland
III. Blood analysis* Determine blood folate and vitamin B12 status, pre and post fortification B) Seniors (65 years or older) not taking supplements containing folic acid or B12 supplement and not diagnosed with anaemia. St. John's, Rural Newfoundland
IV. Knowledge and intake of folic acid supplements Determine knowledge and consumption of folic acid supplements, pre and post fortification Non-pregnant women of childbearing age (19–44 years) St. John's, Rural Newfoundland
* The same sample of women and seniors are analyzed in Components II and III.
** Sampling was done separately for Phases I and II.
Data collection
In order to examine temporal changes in the rates of NTDs in Newfoundland, data were compiled from the Newfoundland and Labrador Medical Genetics Program from 1976 to 2001. This Program ascertains cases of NTDs annually and maintains an NTD database. The database has recorded cases of NTD since 1976. Cases are identified in the following ways: provincial live birth and stillbirth notification forms, maternal-fetal medicine referrals (only one tertiary care unit in the province), and letters sent to all medical records departments of all provincial hospitals requesting data on cases assigned ICD-9/10 codes associated with NTDs or terminations for NTDs. These multiple sources are utilized to ensure complete ascertainment. NTD cases include anencephaly, spina bifida and encephalocele diagnosed in live births, stillbirths (a gestational age of 20 weeks and above or birthweight of 500 g and above) and fetuses from pregnancies terminated (at any gestational age) after a prenatal diagnosis of an NTD.
For the knowledge assessment component of the study, women between the ages of 19 and 44 years were recruited through a random telephone survey. In the initial telephone survey, women were asked about their use of vitamin supplements and knowledge of the importance of folic acid for reducing the risk of NTDs or for fetal development. Women who completed the initial telephone survey were subsequently screened for their eligibility for dietary and blood assessments. Women who were not taking supplements containing folic acid and not pregnant were eligible to participate. This sampling procedure for Phase I and Phase II resulted in a response rate of 59.7% and 65.4%, respectively, with no difference between urban and rural response rates. A total of 233 women were recruited into Phase I and 204 women were recruited in Phase II, who completed components II, III and IV of the study.
Seniors were recruited in the same manner as the samples of women, but were drawn only from St. John's, Newfoundland. Seniors aged 65 years or over, not diagnosed with vitamin B12 deficiency or anaemia and not taking vitamin B12 or supplements containing folic acid, were eligible for dietary and blood sample assessments. A total of 202 seniors were recruited in Phase I and 186 were recruited in Phase II (response rate 45.1% and 44.9%, respectively).
In order to determine intakes of naturally occurring folate (the form of the vitamin found naturally in foods) pre and post fortification, and dietary intakes of folic acid (the synthetic form of the vitamin) post fortification, a Willett food frequency dietary questionnaire [16] was administered to subjects during an in-person interview. There were some modifications to the questionnaire to include common Newfoundland foods and to ensure that all foods high in folate were included. The dietary questionnaire was used to estimate an average frequency of consumption of 124 food items over the previous period of one year.
The women and senior participants were also asked to provide a sample of blood in order to determine blood folate and vitamin B12 status in Phase I and Phase II. Laboratory tests for complete blood count (CBC), red blood cell (RBC) folate, serum folate, creatinine, vitamin B12, plasma homocysteine (HCY) and methylmalonic acid (MMA) were conducted at the laboratories of the Health Care Corporation of St. John's.
Data analysis
Rate of NTDs was defined as the number of above described NTD cases, divided by the total number of live births, stillbirths, and pregnancy terminations for an NTD (termed as "births" hereafter). First we examined the temporal trend in annual rates of NTDs from 1976 to 2001 using 3-year moving average rates, then we focused on comparison of the NTD data for the most recent 11 years, identified as pre-supplementation (1991–1993), pre-fortification (1994–1997) and post-fortification (1998–2001). We regard the year 1997 as a transition period, or partial fortification period, since fortification of white flour and enriched pasta and cornmeal was permitted in Canada as of December 1996 [17]. Thus we also analysed the NTD data using 1994–1996 as a pre-fortification period.
Mean daily intakes of naturally occurring folate were calculated for women aged 19–44 years and for seniors in Phase I and Phase II. Also, for Phase II, average daily intakes of folic acid from fortified foods were calculated.
Data from the blood analyses were tested for normality with the Komogorov-Smirnov test, and differences between groups were tested using the non-parametric Mann-Whitney U test. The distributions of plasma MMA, plasma HCY, serum folate, RBC folate and serum vitamin B12were skewed. Values were therefore log transformed to give an approximate normal distribution for estimation of geometric mean and confidence intervals. Unless otherwise stated, all laboratory values presented in this paper are geometric means and 95% confidence intervals (CI). Differences in the frequency of high or low results based on reference values were tested by Pearson chi-square statistics.
All data for this study were entered into SPSS (the Statistical Package for Social Sciences) Rel. 10.0 after the end of each phase. Data from the dietary interviews were analyzed using Epi-Info (Version 6.04d), while the laboratory data and the data about knowledge and use of supplements were analyzed using SPSS.
Results
1. Rate of NTDs
There were 617 ascertained cases of NTD among live births, stillbirths and pregnancies terminated for an NTD in Newfoundland over the 26 year period. The annual rates of NTDs in the province varied greatly over time, with the lowest rate of 2.18 per 1,000 births in 1989, and the highest rate of 5.92 per 1,000 births in 1995. The average rate of NTDs between 1976 and 1997 was 3.40 per 1,000 births. A dramatic drop is seen in 1997, in which the rate of NTDs was 2.20 per 1,000 births, down from 5.49 per 1,000 births in the previous year. The decreasing trend continued after 1998 (Figure 1 shows 3-year moving average rates).
Figure 1 Rates of NTDs in Newfoundland and Labrador, 1976 to 2001 (3-year moving average rates) *The rate for 1976 is a 2-yr average based on data for 1976 and 1977 and the rate for 2001 is a 2-yr average based on data for 2000 and 2001.
The NTD data for the years 1991–2001 are presented in three periods in Table 2. The mean annual rates were 4.35 per 1,000 births during 1991–1993 and 5.02 per 1,000 births during 1994–1996 (1994–96 vs 1991–93, relative risk [RR] 1.15, 95% CI 0.86–1.54, p = 0.95), and 4.37 per 1,000 births during 1994–1997 (1994–97 vs 1991–93, RR 1.01, 95% CI 0.76–1.34, p = 0.54).
Table 2 Annual rates of neural tube defects (NTDs) in Newfoundland and Labrador before folic acid supplementation (1991–1993), prior to folic acid fortification (1994–1997) and after fortification (1998–2001)
Period No. of cases of NTDs Total no. of births* Rate per 1,000 births
In live births and stillbirths In terminated pregnancies Total
Pre-supplementation
1991–1993 50 40 90 20,711 4.35
Pre-fortification
1994–1997 53 50 103 23,592 4.37
Post-fortification
1998–2001 8 11 19 19,816 0.96
* The total number of births includes live births, stillbirths and terminations for an NTD.
The total annual rate of NTDs fell by 78% after the implementation of folic acid fortification, from an average of 4.36 per 1,000 births during 1991–1997 to 0.96 per 1,000 births during 1998–2001 (RR 0.22, 95% CI 0.14–0.35, p < 0.0001). It is worthwhile to note that there has been no significant increase in the proportion of NTDs from terminated pregnancies since 1994.
II. Dietary Assessment
There was no statistically significant change in the average daily intake of naturally occurring folate among either women aged 19–44 years or seniors between Phase I and Phase II (p = 0.19 and p = 0.18, respectively). Seniors generally had dietary folate intake slightly higher than women of childbearing age. In Phase I, the average daily intake of naturally occurring folate was 306 μg/day for seniors and 262 μg/day for women aged 19–44 years, while in Phase II, the average daily intake of naturally occurring folate was 290 μg/day for seniors and 248 μg/day for women aged 19–44 years.
The implementation of mandatory fortification resulted in an average additional dietary intake of 70 μg/day of folic acid in women aged 19–44, and 74 μg/day of folic acid among seniors. It is noteworthy that for the women the average daily folic acid intake due to food fortification was less than the approximately 100 μg that was previously predicted for women of childbearing age. The maximum dietary intake of folic acid due to fortification for an individual woman was 235 μg/day, and for an individual senior was 219 μg/day.
III. Blood Analysis
Serum folate and RBC folate increased significantly from Phase I to Phase II in both women aged 19–44 years and seniors (p < 0.001). For both age groups, there was a corresponding decrease in mean plasma HCY levels (Tables 3 and 4). The prevalence of low serum folate (≤6.8 nmol/L) was eliminated from the sample of seniors and the proportion of elderly participants with low stores as indicated by RBC folate levels (< 373 nmol/L) was reduced from 2.5% to 1.6%. The proportion of women aged 19–44 years with high HCY(>13.2 μmol/L) also decreased from 15.9% to 7.6% (p = 0.002) (data not shown).
Table 3 Laboratory data (geometric mean and 95% confidence interval) for young women participants (age 19–44 years) in Phase I and Phase II
Characteristic Phase I Phase II p value †
Total participants (n) 233 204
Serum folate (nmol/L) 13.5 (12.9 – 14.1) 18.1 (17.3 – 18.9) <0.001
RBC folate (mol/L) 625 (601 – 649) 818 (784 – 854) <0.001
Plasma HCY (μmol/L) 10.2 (9.8 – 10.7) 9.2 (8.8 – 9.6) 0.001
Serum vitamin B12 (pmol/L) 177 (169 – 186) 200 (190 – 211) 0.02
Plasma MMA (μmol/L) 0.18 (0.17 – 0.19) 0.21 (0.19 – 0.22) 0.008
† P value for the difference between Phase I and Phase II is based on a non-parametric Mann-Whitney U test.
RBC denotes red blood cell, HCY denotes homocysteine, and MMA refers to methylmalonic acid.
Table 4 Laboratory data (geometric mean and 95% confidence interval) for senior participants (age 65 years or over) between Phase I and Phase II
Characteristic Phase I Phase II P value ‡
Total participants (n) 202 186
Serum folate (nmol/L) 14.8 (14.0 – 15.6) 23.0 (22.0 – 24.1) <0.001
RBC folate (mol/L) 745 (713 – 779) 916 (873 – 961)† <0.001
Plasma HCY (μmol/L) 13.6 (13.0 – 14.2)† 12.3 (11.7 – 12.9)† 0.001
Serum vitamin B12 (pmol/L) 183 (173 – 194) 216 (202 – 231) <0.001
Plasma MMA (μmol/L) 0.24 (0.22 – 0.27)† 0.26 (0.24 – 0.28) 0.229
† The Komogorov-Smirnov test showed that the log transformed data were non-normal (p < 0.05).
‡ P value for the difference between Phase I and Phase II is based on a non-parametric Mann-Whitney U test.
RBC denotes red blood cell, HCY denotes homocysteine and MMA refers to methylmalonic acid.
There was a significant increase in mean vitamin B12 levels in women aged 19–44 and seniors (p = 0.020 and p < 0.001, respectively, Tables 3 and 4). The proportion of seniors with low vitamin B12 (<133 pmol/L) was 18.8% prior to fortification and following fortification this proportion declined to 11.8% (p = 0.032) (data not shown). A statistically significant increase in mean plasma MMA levels was observed in women subjects (p = 0.008) but not in seniors (p = 0.229) (Tables 3 and 4). There was also an increase in the proportion of women aged 19–44 years with MMA values above the upper reference value of 0.37 μmol/L from 3.6% in Phase I to 14.9% in Phase II (p < 0.001). There was no significant change in the proportion of abnormal MMA values in seniors. Moreover, among seniors, blood analysis showed no significant difference in mean haemoglobin concentrations, mean corpuscular volume (MCV), or proportion with abnormally high MCV (>99 fL) or low haemoglobin (<120 g/L) concentrations.
IV. Knowledge and use of folic acid supplements
There was a significant increase from Phase I to Phase II in the proportion of women aged 19–44 years who knew the importance of folic acid (from 33% to 46%, p < 0.001). The proportion of women taking a vitamin supplement containing folic acid increased substantially between the two time periods (from 17% to 28%, p < 0.003). Information about folic acid dosage was not collected.
Discussion
The results of a number of studies have led to the conclusion that periconceptional folic acid supplementation reduces the risk of NTDs [5-8]. Among the responses to this research evidence were calls in the early 1990s for mandatory fortification of food with folic acid. It was argued that this public health intervention would address concerns about achieving population level compliance with recommendations to women to take vitamin supplements containing folic acid before becoming pregnant and in the first weeks of pregnancy. These concerns were borne out in several Canadian studies suggesting that many caregivers [18,19] and women [20,21] remained unaware of the relationship between folic acid and NTDs. More recent studies have shown an increase in knowledge about folic acid, but supplementation rates remain low [22-25].
In March 1996 the US Food and Drug Administration (FDA) announced that it would permit addition of folic acid to enriched flour and other enriched cereal grain products, and that this addition would be mandatory as of January 1998. The level of fortification was set at 0.14 mg folic acid per 100 g of cereal grain product. It was determined that at this level of fortification, the intake of folate (from all sources) for the target and the general population would be kept below 1,000 μg/day, which was deemed to be the safe upper limit. This level of fortification was estimated to increase the average daily intake of folic acid in women of childbearing age by about 100 μg [26]. Subsequent to the US decision, Canada followed suit, permitting folic acid fortification at an equivalent level in December 1996 (addition of folic acid to white flour and enriched pasta and cornmeal at 0.15 mg folic acid per 100 g of flour and 0.20 mg folic acid per 100 g of pasta). In Canada, fortification became mandatory in November 1998.
Rate of NTDs
Our results show a highly significant drop in the rate of NTDs in Newfoundland, taking into account all identified affected pregnancies (live births, stillbirths and pregnancies terminated after a prenatal diagnosis of an NTD). The 78% (95% CI 65%–86%) reduction in the NTD rate after implementation of fortification is greater than the 18%–22% reduction predicted at current levels of fortification [27,28], and greater than the 19% reduction in birth prevalence of NTDs reported in the US after mandatory fortification [29]. The results in Newfoundland are closer to the 54% reduction (95% CI 34%–68%) in rate of NTDs reported in Nova Scotia after fortification [2]. De Wals et al. observed a 32% reduction (95% CI 23%–41%) in NTDs in Quebec between 1992–97 and 1998–2000 [30]. Ray et al. [31] analyzed maternal serum screening data for Ontario and observed a decline in NTD prevalence from 1.13 per 1,000 pregnancies before fortification to 0.58 per 1,000 pregnancies thereafter (prevalence ratio 0.52, 95% CI 0.40–0.67).
The large reduction in the rate of NTDs in Newfoundland may be due, at least in part, to the fact that Newfoundland had higher background rates of NTDs. This population may be more sensitive to the influence of folic acid. In a large-scale public health campaign in northern and southern China, periconceptional use of 400 μg/day folic acid supplements was associated with a reduction in NTD risk of 79% for women in northern China, where the baseline NTD rate was high and similar to that observed in Newfoundland. A lower risk reduction of 41% was observed in the southern region where the pre-campaign NTD rate was much lower [32].
The 65% increase in the proportion of women taking vitamin supplements containing folic acid, from 17% in Phase I to 28% in Phase II, suggests that an increasing trend in folic acid supplementation may have played a role in the declining NTD rate in Newfoundland. In this study it was not possible to determine the individual contribution of supplementation and fortification to the trend in NTDs.
The annual rate of NTDs in the pre-fortification period (1994–97) did not differ significantly from that of the pre-supplementation period (1991–93); this is true whether 1997 is excluded or included in the pre-fortification period. The increase in the rates of NTDs in 1995 and 1996 appears random and largely unexplainable. The changes in the NTD rates between 1994–1996 and 1991–1993 and between 1995–1997 and 1991–1993 were not statistically significant. In addition, our data do not show an obvious increase in the proportion of NTDs in terminated pregnancies during 1994 and 1996 (data available upon request).
Dietary intakes and blood folate levels
The questionnaire used in this dietary assessment was a modified Willett questionnaire [16], administered in a face-to-face interview with trained personnel. The Willett food frequency dietary questionnaire has been well validated [33] and proved easy to administer for this sample population.
The daily intake of naturally occurring folate among women aged 19–44 years in this study (average 248 μg/day in the Phase II sample) was similar to values found in other studies of women's diet [34,35]. For seniors in Phase II, naturally occurring folate in the diet averaged 290 μg/day which was comparable to values found for persons age 49 and older in an Australian study [36]. The dietary folic acid intake due to fortification did not exceed the Tolerable Upper Intake Level (UL) of 1,000 μg folic acid/day [14] for any of the participants (this UL for folic acid does not include naturally occurring folate). It is important to note that this part of the study excluded persons taking vitamin supplements containing folic acid. While it was not possible to estimate the proportion of people in the general Newfoundland population who may be consuming more than 1,000 μg/day of folic acid from fortification and supplementation combined, it is likely that this proportion is small. The average dietary intake and maximum intake of folic acid due to fortification were 70 μg/day and 235 μg/day, respectively, for women aged 19–44 years, and 74 μg/day and 219 μg/day, respectively, for seniors. The average folic acid dose in folic acid containing over-the-counter supplements marketed in Canada is about 350 μg/day (Health Canada unpublished information).
The results of this study provide strong evidence of improved blood folate status in women aged 19–44 years following mandatory fortification with folic acid. Women showed evidence of increased levels of serum and RBC folate and decreased levels of plasma HCY. These results are consistent with an earlier study examining the effect of fortification in the Framingham offspring study cohort [37].
Mandatory food fortification with folic acid has resulted in improvements in folate indices in seniors. Both mean serum folate and mean RBC folate increased following folic acid fortification (55% and 23%, respectively, Table 4). Consistent with this was a moderate decrease in mean plasma HCY levels among seniors by 1.3 μmol/L. Fortification of food with folic acid and an upward shift in blood folate levels is of benefit to the elderly population especially with regard to risk of cardiovascular disease. High levels of homocysteine are associated with both cerebrovascular and coronary heart disease [38-40].
Vitamin B12 status
There was a decline in the proportion of seniors with low vitamin B12 levels, and there was actually a slight increase in mean vitamin B12 levels. In vitamin B12 deficiency, plasma MMA is usually elevated. Plasma MMA is believed to be a better indicator of vitamin B12 status at the tissue level than serum vitamin B12 levels are. Our study showed no change in mean MMA levels nor increased proportion of elderly with high levels. In addition, there was no change in the indicators of anaemia (i.e., haemoglobin and MCV) in seniors post fortification in our study. Thus, these results show no evidence of a deterioration in vitamin B12 status among seniors. Furthermore, there is no evidence of improved folate status resulting in masking of the haematological manifestations of vitamin B12 deficiency among seniors as a group. There was no evidence of deteriorating vitamin B12 status among young women participants based on vitamin B12 measurements. The upward trend in plasma MMA levels and higher proportion of abnormal values among young women is being further evaluated. It is unlikely that this is a direct effect of folic acid fortification and this observation is not consistent with any known effects of folic acid on vitamin B12 status.
Limitations
We have documented the rate of NTDs among live births, stillbirths and terminated pregnancies known to have an NTD. It was not possible to include NTDs that may have occurred in pregnancies that resulted in a spontaneous abortion or a termination that occurred for reasons other than a congenital anomaly.
This study, and other studies of fortification in Canada, are limited by the fact that there was no precise date when exposure to food fortified with folic acid began. The addition of folic acid to white flour and enriched pasta and cornmeal was permitted as of December 1996. Industry was switching to folic acid-containing enrichment premixes, especially towards the end of 1997, in anticipation of both US requirements for fortification as of January 1, 1998, and Canadian plans to implement mandatory fortification. Although this requirement did not come into force in Canada until late 1998, the Phase I (November 1997 to March 1998) subjects of our study may have consumed at least some food fortified with folic acid. This would result in an underestimate of improvements in blood folate status due to fortification, and might lead us to miss adverse effects on vitamin B12 status. On the other hand, the fact that we observed such marked improvements in blood folate status leads us to conclude that there was a real increase in exposure to folic acid through fortification, over the study period.
Another limitation of this study is the possible underestimation of folic acid intake due to fortification. Our calculations were based on the assumption that manufacturers are fortifying flour at the required level. It has been suggested that allowance for "overages" is resulting in higher amounts in the affected products [41]. Also, for enriched pasta, the required level of fortification is from a minimum of 0.20 mg/100 g pasta to a maximum of 0.27 mg/100 g. In our calculations we assumed the minimum level of fortification.
We initially selected a random sample of subjects through random digit dialling, and asked eligible respondents for voluntary participation in the study. The reasonable level of response for the dietary questionnaire and blood sampling among rural and urban women aged 19–44 years suggests that with caution, we can generalize the results to all Newfoundland women of childbearing age. However, these findings may not be representative of the rest of Canada because of population differences in factors such as genetic background and dietary behaviour. These differences may also affect the generalizability of the NTD trend.
The sample response rate for the dietary questionnaire and blood sampling in seniors was approximately 45% both in Phase I and in Phase II. Many of the refusals to participate were due to illness of the eligible person. Furthermore, seniors residing in long term care settings were not included. Thus our sample population of seniors may be healthier than the general population age 65 and over in the province.
Conclusions
The implementation of food fortification with folic acid has been accompanied by a marked decrease (78%) in the rate of NTDs in Newfoundland. The blood folate status of women aged 19–44 years improved following mandatory fortification. There is no evidence of adverse effects of the current levels of fortification on individuals aged 65 years and older. Specifically, there is no evidence to suggest an adverse effect of folic acid fortification on detection of abnormalities in vitamin B12 status based on biochemical and haematological indices.
Based on these findings, mandatory food fortification with folic acid should continue in Canada at the current levels. Over the time period of this study, the proportion of women aged 19–44 years taking a vitamin supplement containing folic acid increased. It was not possible to determine the magnitude of the separate contributions of fortification and supplementation to the decline in NTDs. Therefore, we recommend that public health efforts to promote awareness of the importance of folic acid supplementation among women of childbearing age continue. Ongoing surveillance of NTDs in Newfoundland and other parts of Canada is necessary to determine if the decline in NTD rate is maintained, and to enable further evaluation of prevention strategies. National surveillance of congenital anomalies including NTDs is a critical public health function that should be strengthened where necessary.
We look forward to the results of a current epidemiologic study, funded by the Canadian Institutes of Health Research (CIHR), of NTDs in 7 Canadian provinces between 1993 and 2002. There is also research into the relationship between increased folic acid consumption and reduced risk of other congenital anomalies, cardiovascular disease and cancer [42-45]. As this body of knowledge grows, public health practitioners and regulators in Canada and internationally will have more evidence with which to refine existing disease prevention policies and develop new ones.
Competing interests
The authors declare that they have no competing interests.
List of abbreviations
CBC, complete blood count
CI, confidence interval
CIHR, Canadian Institutes of Health Research
FDA, Food and Drug Administration
HCY, homocysteine
MCV, mean corpuscular volume
MMA, methylmalonic acid
NTD, neural tube defect
RBC, red blood cell
SPSS, Statistical Package for Social Sciences
Authors' contributions
SL and CM oversaw the whole study and drafted the manuscript. SL carried out the analysis of NTD rate and statistical analysis. RW, LL, KSO and HS designed the study and carried out the data collection and the dietary assessment. ER, AL and VP participated in the design and carried out the blood analysis. MC carried out the collection of NTD data. All authors read, revised and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
This study was funded by Health Canada's Health Surveillance and Epidemiology Division. This study was granted full ethics approval by Research Ethics Boards at Memorial University of Newfoundland and at Queen's University. All study subjects gave written informed consent prior to participation in this study.
We particularly thank Linda Turner for her earlier work on this study. We gratefully acknowledge the support and assistance of many individuals for their participation in this study, including the interviewers, laboratory and clinical support staff, and data entry and analysis staff. Particular thanks to Vicki Gill, project coordinator in Newfoundland, Millie Trask, for help with data entry and word processing in the laboratory component of the study, and Ernesto Delgado, for his logistical support within Health Canada.
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BMC Public HealthBMC Public Health1471-2458BioMed Central London 1471-2458-4-431545856710.1186/1471-2458-4-43Research ArticleTargeting smoking cessation to high prevalence communities: outcomes from a pilot intervention for gay men Harding Richard 1richard.harding@kcl.ac.ukBensley James 2James.Bensley@gmfa.org.ukCorrigan Nick 2Nick.corrigan@gmfa.org.uk1 Department of Palliative Care & Policy, Guy's King's & St Thomas' School of Medicine, King's College London, Weston Education Centre, Cutcombe Road, London, SE5 9PJ, UK2 GMFA, Unit 42 Eurolink Centre, 49 Effra Road, London, SW2 1BZ, UK2004 30 9 2004 4 43 43 1 7 2004 30 9 2004 Copyright © 2004 Harding et al; licensee BioMed Central Ltd.2004Harding 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
Cigarette smoking prevalence among gay men is twice that of population levels. A pilot community-level intervention was developed and evaluated aiming to meet UK Government cessation and cancer prevention targets.
Methods
Four 7-week withdrawal-oriented treatment groups combined nicotine replacement therapy with peer support. Self-report and carbon monoxide register data were collected at baseline and 7 weeks. N = 98 gay men were recruited through community newspapers and organisations in London UK.
Results
At 7 weeks, n = 44 (76%) were confirmed as quit using standard UK Government National Health Service monitoring forms. In multivariate analysis the single significant baseline variable associated with cessation was previous number of attempts at quitting (OR 1.48, p = 0.04).
Conclusions
This tailored community-level intervention successfully recruited a high-prevalence group, and the outcome data compares very favourably to national monitoring data (which reports an average of 53% success). Implications for national targeted services are considered.
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Background
Analysis of tobacco marketing has demonstrated lesbian and gay youth as an emerging target community [1], thereby reinforcing behaviour patterns that contribute to the adult gay smoking prevalence (39.7–47.8%) being up to twice that of adult heterosexuals [2].
Gay men have been disproportionately affected by HIV/AIDS disease in developed countries. HIV risk-taking behaviour is associated with cigarette smoking among HIV-negative gay men [3], and among gay men infected with HIV, studies of co-morbidity and survival have identified cigarette smoking as a significant risk factor for opportunistic infections [4] and rapid disease progression [5]. A review of the evidence on sexuality and cigarette smoking found the elevated rates of tobacco use to be consistent across international studies, and concluded with a strengthened call for targeted cessation interventions to lesbians, gays and bisexuals [6]. None have been published to date.
The National Health Service (NHS) Cancer Plan, a UK Government health strategy, recommends that Primary Care Trusts (PCTs) take a commissioning lead in forming local alliances involving community groups, harnessing community efforts, and dissemination of effective interventions. [7]. In order to meet smoking cessation targets, PCTs are recommended to develop specialist smoking cessation services and develop links with local community groups [8].
This innovative pilot study aimed to design, recruit to, and deliver a series of pilot smoking cessation group interventions and to evaluate outcomes using standard UK Government assessment criteria.
Methods
Intervention design
The intervention was developed and delivered by a community-based volunteer-led charity in London UK, with a remit to promote the health of gay men. Potential acceptability and effectiveness were maximised by providing an NHS-approved programme adapted for an appropriate service wholly facilitated and attended by gay men. Seven volunteers experienced in delivering group interventions within the organisation were trained in the 3 day course "Setting up and running specialist Smoking Cessation Clinics", part of the Smoking Cessation Training and Research Programme (SCTRP) at St Bartholomew's and Royal London School of Medicine and St George's Hospital Medical School. The programme of withdrawal-oriented treatment combines groupwork, nicotine replacement therapy (obtained on prescription from general practitioners) and ongoing peer support throughout. An initial information session is followed by 6 closed group sessions, setting a quit data for week 3. This pilot consisted of 4 delivered groups, and each group consisted of 7 closed weekly meetings each of 2 hours.
The service principle was for a non-judgemental environment where gay men could address socialising and gay social spaces, recreational drug use, sexuality and HIV and the impact of these on their motivations, and ability, to quit smoking. Several specific modifications were made to the taught model. Our intervention modified the SCTRP program's use of "Quit buddies" which promoted partnered support, instead creating "Quit cells" of 3 or 4 participants. This design modification was made in the light of other group interventions delivered by this community organisation in which reliance of a participant on more than one person for support has found to be more reliable. The information on Zyban was expanded to address contraindications with HIV antiretroviral combination therapies. Exercises from assertiveness training courses were imported to assist participants in clearly communicating the intention to remain a non-smoker. In general, group discussion and processes were focussed on culturally-specific contexts to gay men. A detailed intervention programme was written in order to promote consistency across the cycles of intervention delivery.
Week 1: information on the course content as well as expectations of quit date are given along with information regarding potential side effects and how to deal with them. Week 2: what to expect when you quit and how to deal with reactions, information on the effects of carbon monoxide, preparation for quit date, personal action plan and the how to use a smoking diary. Week 3: information on how to use nicotine replacements, role play of assertive refusal of cigarettes, selection and formation of quit support cells, and personal statements of cessation. Week 4: group review of challenges of the first week of not smoking with reference to smoking diary and personal action plan, exploration of potential "alternative" support such as meditation and exercise, discussion of the challenges of drug use with respect to smoking cessation. Week 5: group review of previous week's experience, information on health benefits achieved to date and weight gain issues. Week 6: review of previous week's experience, identification of future sources of support. Week 7: review of previous week's experience, information of health benefits to date, elaboration on support sources, small celebration of the group's achievement.
Recruitment
Twenty-four recruitment advertisements were placed in free London-wide and national gay press, and accompanying editorial and articles were secured to support the recruitment process.
Data collection and analysis
Prior to the initial session, participants were sent the required UK Department of Health self-completion Smoking Cessation Service NHS Client Assessment Form. Carbon monoxide readings were taken at each session from week 2, using the "Smokealyser" calibrated carbon monoxide register, and readings were used in addition to self-report data to confirm smoking cessation at week 7. All intervention attendees were asked to give written permission for data collection purposes and were given guarantees of confidentiality.
All data were entered into SPSS for windows V11. In line with NHS monitoring data requirements, the percentage of successful quitters was calculated as those who gave carbon monoxide readings and confirmed they had quit at week 7 as a percentage of those who set a quit date for week 3. Variables were entered individually into univariate binary logistic regressions, with cessation outcome as the dependent variable and participant baseline characteristics, attitudes and behaviour, and nicotine replacement methods as independent variables. Variables with p values below 0.25 were then entered stepwise into a multivariate logistic regression, with 95% confidence intervals (95% CI) reported.
Results
Participant characteristics
Ninety-eight men registered to attend the intervention, and of these 76 attended at least the first session. Sixty-nine of men returned the assessment sheet, and the outcome analysis is of those 69 men.
The mean age of participants was 37.1 years (range 23–63, SD = 7.2 years), and n = 63 (90%) reported their ethnicity as White. Forty-four men (64%) had been educated to degree level or higher, and n = 52 (75%) were in full time employment with a further 9 (13%) men medically retired, n = 5 (7%) unemployed, n = 2 (3%) in full time education and n = 1 (1%) retired. Seventeen men (25%) were entitled to free prescriptions (i.e. the welfare state pays for their prescribed medications). Sixty-five men (94%) reported that they drink alcohol, consuming a mean of 22.8 units per week (median = 20, SD = 19, range 1–120).
Smoking behaviours at baseline
The daily number of cigarettes smoked was as follows: 1–5 (n = 3, 4%); 5–10 (n = 5, 7%); 11–20 (n = 27, 39%); 21–30 (n = 21, 30%); 31–40 (n = 8, 12%); 41+ (n = 5, 7%). The first cigarette after waking was smoked during the following number of minutes after waking: 5 minutes (n = 19, 28%); 6–30 minutes (n = 31, 45%); 31–60 minutes (n = 7, 10%); 61+ minutes (n = 11, 16%). Smoking motivations are summarised in Table 1.
Table 1 Smoking behaviour at baseline
(Strongly) agree Neither (Strongly) Disagree
I enjoy smoking 44 (64) 11 (16) 13 (18)
Smoking helps me cope with stress 38 (55) 15 (22) 15 (21)
Smoking helps me to socialise 39 (57) 16 (23) 13 (19)
Smoking helps me to cope with boredom 31 (45) 22 (32) 15 (21)
I smoke to keep my weight down 5 (7) 7 (10) 55 (80)
Health status and consultations
Participants reported a mean 2.6 of consultations with their primary care General Practitioner (GP) in the previous year (median = 2, SD 3.5). Secondary/hospital consultations in the previous year were reported by n = 35 (52%) men, with a mean of 2.26 consultations for these men (median = 1, SD = 3.9). Thirty-four men (51%) had been recommended by their GP to give up cigarette smoking, and n = 26 (38%) men were currently on prescribed medication. Fourteen men (20%) were diagnosed HIV-positive, n = 25 (51%) HIV-negative, n = 16 (23%) untested and n = 4 (6%) refused to answer. The participants rated their health as follows: excellent n = 10 (14.5%); good n = 36 (52%); moderate n = 20 (29%); poor n = 2 (3%); very poor n = 1 (1%).
Quitting motivations and history
Sixty-one men (90%) had made a previous attempt to quit, and of those who had made an attempt the mean was 2.85 attempts (median 3, SD = 1.4). Previously employed nicotine replacement methods were gum n = 30 (49%), patches n = 30 (49%), nasal spray n = 3 (5%), inhalor n = 12 (20%), microtabs n = 3 (5%), nicotine lozenges n = 4 (7%), and Bupropion (Zyban) n = 12 (20%).
Participants described the importance of this current attempt to quit as extremely important (n = 33, 48%); very important (n = 27, 39%); quite important (n = 9, 13%); not at all important (n = 0). Participants rated their chances of quitting for good on this attempt as extremely high (n = 10, 15%); very high (n = 27, 39%); quite high (n = 24, 35%); not very high (n = 7, 10%); very low (n = 1, 1%).
Intervention attendance and outcomes
Attendance at sessions was consistently high, of 532 person-sessions 13 sessions were missed. Non-attendance did not apparently cluster around a particular session.
At week 3, of the 69 men who gave data, n = 58 men (84%) set a quit date. At week 7 (4 weeks after the quit date) n = 44 men (64%) were confirmed as having quit using the CO monitor, representing 58% of those who attended the first session, 76% of those who set a quit date and 64% of those who gave data at baseline and week 7.
A further 3 men reported by telephone that they had quit smoking but did not attend the final session to give clinical data to verify. Nine men (13%) reported not having stopped smoking, n = 6 men (9%) set a quit date at week 3 and did not return to group, n = 7 men (10%) attended the first session only. For the purposes of this analysis, these 25 men were coded as not having quit in the following modelling.
Variables associated with cessation outcomes in multivariate logistic regression
This analysis considers those 44 men confirmed as having ceased compared to those 25 categorised as not having quit. Following univariate analysis (see Table 2), the 4 variables entered into the multivariate model were smoking for enjoyment, number of cigarettes per day, smoking to keep weight down, and number of previous attempts. Only the latter (continuous) variable was significantly associated with successful quitting at week 7 (OR = 1.48, 95% CI = 1.02, 2.14, p = 0.04). Data from the multivariate model are presented in Table 3.
Table 2 Univariate binary regression analysis of demographic and behavioural baseline data with respect to cessation outcomes
Variable p Odds Ratio 95% CI
Age 0.36 1.03 0.96, 1.11
"I enjoy smoking" 0.22* 1.38 0.82, 2.32
"Smoke helps me cope with stress" 0.39 0.82 0.53, 1.29
"Smoking helps me to socialise" 0.58 0.89 0.58, 1.36
"Smoking helps me to cope with boredom" 0.97 0.99 0.63, 1.55
"I Smoke to keep down weight" 0.18* 1.41 0.85, 2.33
No. of cigarettes per day 0.08* 0.67 0.42, 1.05
Time to 1st daily cigarette 0.52 1.18 0.71, 1.96
No. of previous attempts 0.04* 1.44 1.02, 2.01
Importance of this attempt 0.80 0.91 0.45, 1.84
No. of GP visits 0.33 1.09 0.92, 1.29
No. of secondary care visits 0.43 1.06 0.92, 1.22
Expected chance of quitting success on this attempt 0.91 0.97 0.58, 1.62
Perceived health status 0.96 1.02 0.55, 1.90
* Included in multivariate analysis (see Table 3)
Table 3 Multivariate analysis of variables identified as associated with cessation at week 7 (i.e. p < 0.25 in univariate analysis, Table 2).
Variable p Odds Ratio 95% CI
No of cigarettes per day 0.15 0.68 0.41, 1.14
Smoking to keep down weight 0.20 1.43 0.83, 2.45
No of previous attempts to give up 0.04* 1.48 1.02, 2.14
I enjoy smoking 0.38 1.30 0.73, 2.30
Discussion
This pilot intervention has targeted a hitherto overlooked high smoking prevalence group, and has adapted a Government-approved intervention to meet the specific needs of gay men in an appropriate and acceptable setting. The success rate of 76% of men who had set a quit date being confirmed as having quit at week 7 compares extremely favourably to national monitoring data, which reports a success rate nationally 2001–2002 for smoking cessation services as 53% [9].
Public health targets must consider the needs of high prevalence communities, and this may be achieved through innovative development of existing effective services. However, this study has highlighted the lack of targeted interventions for gay men, and the evidence demonstrates further elevated health needs compared to the general population in the fields of alcohol and drug use [10] mental health [11] and cancer [12,13].
Further research may identify the factors which contributed to the effectiveness of this pilot complex participative intervention, including offering recruitment and delivery outside of community settings, measuring success rates for gay men in non-gay specific or tailored groups, and the usefulness of "quit cells". Longer-term follow-up data and increasing dosage to include a follow-up session would also provide further useful data. In order to refine the intervention for trial testing, qualitative data regarding the utility, acceptability and preferences for the content of specific sessions would be illuminating. Further, the non-randomised design without comparison group limits presents a limitation to the generalisability of findings, yet still offers cessation outcomes much better than standard national cessation data quoted above which were collected without quasi-experimental design using the same follow-up period. Data were not available on the 29 men who registered for the course but did not attend or complete baseline data, and so it is not possible to compare their demographics or smoking behaviours to those who took up the intervention. Certainly, replication of this first pilot would be necessary in other settings, e.g. non-metropolitan communities, where issues of feasibility and uptake should be addressed. Commissioners may consider the purchase of existing facilitators from cities to deliver in non-metropolitan areas where demand is likely to be lower, as smoking cessation service recommendations state that group leaders need to keep up to date with their skills and to use them on a regular basis [14].
Conclusions
In order to meet the smoking cessation needs of this hitherto overlooked population, and to meet public health policy targets, a rigorous research agenda must be established. While the use of required standard outcome monitoring must be continued, rigorous experimental trials using longer term follow up and commonly reported measures are required. Complex participative interventions must be developed, as in this pilot, from evidence-based interventions with full programme description to ensure replication. The development of appropriate interventions must first pilot services to ensure that they are appropriately adapted to maximise acceptability and uptake among target communities.
Lastly, provision of the service by skilled volunteer facilitators has ensured an acceptable, low-cost intervention with a rate of effectiveness in these four pilot groups that compares favourably to national non-targeted interventions outcomes calculated using standard assessment formula. Acceptability of the model appears high with respect to the low number of missed sessions. Voluntary sector provision and delivery should be considered as a low-cost and highly acceptable point of delivery for effective community-level smoking cessation interventions.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
JB and NH managed the pilot study. RH was responsible for data management and analysis 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
The authors wish to thank Russell Fleet, Geoff Benham, Nic Collins, Robert Thompson, Simon Bryant, and Ken Drakou who implemented the intervention, and to Den Copps and Barrie Dwyer who designed the recruitment. We are grateful to Richard Boxford, Mirielle Herbert and Dinah Thompson and the Health Development Team at Enfield & Haringey NHS Trust who provided the funding to develop this project. We thank, and acknowledge the work of, Professor Peter Hajek and Dr Haydn McRobbie of St Bartholomew's Hospital and Royal London Hospital School of Medicine and Dentistry for their training in the original intervention, and to Sam Andrews and Jackie Wilderspin of Oxfordshire Smoking Advice Service for additional resources and materials.
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| 15458567 | PMC524179 | CC BY | 2021-01-04 16:28:47 | no | BMC Public Health. 2004 Sep 30; 4:43 | utf-8 | BMC Public Health | 2,004 | 10.1186/1471-2458-4-43 | oa_comm |
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BMC Med EducBMC Medical Education1472-6920BioMed Central London 1472-6920-4-181546178610.1186/1472-6920-4-18Research ArticleMapping medical careers: Questionnaire assessment of career preferences in medical school applicants and final-year students Petrides KV 1k.petrides@ioe.ac.ukMcManus IC 2i.mcmanus@ucl.ac.uk1 School of Psychology and Human Development Institute of Education University of London London WC1H 0AA, UK2 Department of Psychology University College London Gower Street London WC1E 6BT, UK2004 1 10 2004 4 18 18 4 5 2004 1 10 2004 Copyright © 2004 Petrides and McManus; licensee BioMed Central Ltd.2004Petrides and McManus; 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 medical specialities chosen by doctors for their careers play an important part in the workforce planning of health-care services. However, there is little theoretical understanding of how different medical specialities are perceived or how choices are made, despite there being much work in general on this topic in occupational psychology, which is influenced by Holland's RIASEC (Realistic-Investigative-Artistic-Social-Enterprising-Conventional) typology of careers, and Gottfredson's model of circumscription and compromise. In this study, we use three large-scale cohorts of medical students to produce maps of medical careers.
Methods
Information on between 24 and 28 specialities was collected in three UK cohorts of medical students (1981, 1986 and 1991 entry), in applicants (1981 and 1986 cohorts, N = 1135 and 2032) or entrants (1991 cohort, N = 2973) and in final-year students (N = 330, 376, and 1437). Mapping used Individual Differences Scaling (INDSCAL) on sub-groups broken down by age and sex. The method was validated in a population sample using a full range of careers, and demonstrating that the RIASEC structure could be extracted.
Results
Medical specialities in each cohort, at application and in the final-year, were well represented by a two-dimensional space. The representations showed a close similarity to Holland's RIASEC typology, with the main orthogonal dimensions appearing similar to Prediger's derived orthogonal dimensions of 'Things-People' and 'Data-Ideas'.
Conclusions
There are close parallels between Holland's general typology of careers, and the structure we have found in medical careers. Medical specialities typical of Holland's six RIASEC categories are Surgery (Realistic), Hospital Medicine (Investigative), Psychiatry (Artistic), Public Health (Social), Administrative Medicine (Enterprising), and Laboratory Medicine (Conventional). The homology between medical careers and RIASEC may mean that the map can be used as the basis for understanding career choice, and for providing career counselling.
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Background
Medical careers begin as undifferentiated, and postgraduate training ends with most doctors specialised for a specific area of practice. Relatively little is known about the transition from the medical student, who can be seen as a relatively undifferentiated, totipotent 'stem doctor' [1,2], potentially capable of entering any speciality, through to the final, fully-differentiated specialist who is almost entirely restricted to one specialised area of medical work. Although medical career specialisation has been subject to a moderate amount of research (for reviews see e.g. [3,4]), some of it going back over half a century (e.g. [5]), much of that research has concentrated on the personal characteristics of individuals choosing particular careers (e.g. [6-8], on background factors in childhood influencing career choice (e.g. [8-10]), on associations with particular personality types (e.g. [11]), on the careers of specific groups, such as women doctors (e.g. [12]), on attitudes towards specific specialities, such as psychiatry (e.g. [13,14]) or anaesthetics (e.g. [15,16]), or has concentrated on the basic statistics necessary for workforce planning (e.g. [17,18]). There is, however, a lack of any broad theoretical framework in which to place career choice and specialisation.
UK medical education requires undergraduates to study a wide range of medical specialities, and most students will have sampled many of the broad areas of practice by the time they qualify. As a result, it is often assumed that students do not make their career choices until after they have finished at medical school, remaining agnostic about their final speciality choice until that time. However, not only medical school entrants (e.g. [19]), but even medical school applicants, a year or so earlier, at the typical age of about seventeen, often have surprisingly strong preferences for, and particularly, against, some medical careers (e.g. [20]). There is strong evidence, therefore, that career choice can be determined during or even before medical school ([21,22])). Thus, it makes sense to try and understand those preferences, which probably underpin eventual career choice.
Much research into medical careers does not take into account the broader research literature on non-medical careers (see [23-25]), or on socio-psychological models of the theoretical underpinnings of career choice (e.g. [26], [27], [28,29]). Consequently, medical careers research often fails to provide any broader theoretical framework or conceptualisation within which the empirical findings may be explained or which allow generalisations beyond the immediate data collected in the study (although there are exceptions, e.g. [30,31]).
The present study takes its origins in three separate sets of theoretical approaches, each of which examines different aspects of careers. None of these approaches, however, concerns medical careers specifically. Neither are they restricted to career choice in adulthood. Furthermore, at least one of them is specifically developmental, emphasising the processes by which career choice occurs and changes. The best place to begin this brief theoretical review is with the work of Gottfredson [27], who identifies the distinct processes of circumscription and compromise in career choice.
Careers differ in their demands, requiring different amounts of intellectual ability, manual skill, long-term commitment, or willingness to work in particular environments, and can be better suited to particular personalities, aptitudes, and physical dispositions. Individuals also differ, having different aptitudes, interests and abilities. Career choice therefore involves people considering the entire range of careers and then circumscribing those which they regard as broadly acceptable, making their eventual choices within that subset.
An important practical point highlighted by studies such as Gottfredson's is that choices tend to be negative, meaning that careers are rejected because they do not have attributes which are consonant with the person making the choice, rather than positively chosen for their special suitability.
Once circumscription has taken place, a number of possible careers still remain. The second stage of choice is compromise. Because of various practical constraints, certain careers are restricted in the number of people they can accommodate or they are unsuitable in other terms, such as their geographical location or the remuneration they can provide. The eventual career chosen is one that 'satisfices,' [32] being realistically good, though not optimal. The applications of this theory to medical careers are self-evident and describe many of the problems facing medical students and junior doctors.
Implicit in Gottfredson's conceptualisation is the concept of a map of careers. In her 1981 paper she provides an example a two-dimensional representation of 129 occupations which have been scored in terms of 'Prestige level' (high vs low) and 'sextype rating' (masculine vs feminine). When careers are mapped into this space, the process of circumscription involves drawing an area within which careers are acceptable to a person, being neither too masculine nor too feminine, nor being too high in terms of their prestige and hence effort required, nor too low, and hence insufficiently rewarding. A primary concern of the present study is the nature of the map underlying medical careers, and on which circumscription eventually takes place.
Perhaps the most influential study of the structure of career preferences is that of Holland [26], an overview and critical analysis of which can be found in the special issue of the Journal of Vocational Behavior published in 2000 (e.g. [25]; see also [33] and [34]). Holland's theory suggests that careers can be organised into six broad types, which can be represented around a hexagon (see figure 1), and which are often known by the acronym RIASEC, standing for Realistic, Investigative, Artistic, Social, Enterprising and Conventional. In Holland's original conceptualisation the specific orientation of the hexagon is arbitrary to rotation, but subsequent analyses have suggested that the hexagonal structure can be reduced to two dimensions [35,36]. One dimension runs from Realistic to Social, involving careers that are primarily Things-oriented rather than People-oriented. The second orthogonal dimension runs from midway between Enterprising and Conventional to midway between Artistic and Investigative, and involves careers varying from those that are primarily Data-oriented to those that are primarily Ideas-oriented. Holland's RIASEC model provides an appropriate two-dimensional space in which Gottfredson's circumscription model can apply [37].
Figure 1 The hexagon of Holland's RIASEC typology, along with the Things-People and Ideas-Data dimensions proposed by Prediger (1982).
Although Holland's work suggests how careers might be mapped, and Gottfredson's work suggests how career choices might take place within the space underlying those careers, a missing link in the overall picture concerns how individuals choose within the space. This is a significant question because individuals are expected to circumscribe in different ways according to their particular personalities and abilities. Ackerman [28,29] has described how intellectual ability and personality relate to Holland's RIASEC model. Measures of intellectual ability primarily correlate with interest in the Realistic, Investigative and Artistic careers, people with higher verbal abilities preferring careers in Artistic and Investigative careers, and people with higher spatial and mathematical abilities preferring Realistic and Investigative careers. In contrast, measures of personality mainly correlate with the SEC components of RIASEC. Ackerman uses the Big Five typology of personality (see [38], [39]), and shows that Extraversion primarily correlates with an interest in Social and Enterprising careers, whereas Conscientiousness correlates with an interest in Conventional and Enterprising careers. The personality dimension of Openness to Experience is to some extent a hybrid between intellectual ability and personality, and tends to correlate positively with Artistic, Investigative and Realistic careers, and negatively with Conventional careers. This pattern is similar to that which Zhang has reported in which the RIA cluster of careers relates to a deep approach to learning [40,41], whereas the SEC cluster relates to a strategic approach to learning [42].
Between them, the models of Holland, Ackerman and Gottfredson provide, respectively, a good conceptualisation of i) the structure of careers and career preferences, ii) the correlations of careers with ability and personality, and iii) the developmental processes by which career choices are made. The question for medical education is the extent to which these approaches are appropriate for understanding medical career choice. If they are valid, then that will allow the much broader research literature from career choice in general to inform the more specific area of medical career choice. Underpinning the models of both Ackerman and Gottfredson is Holland's picture of a relatively simple, two-dimensional career map, onto which ability and personality can project, and on the basis of which career choices can develop. We therefore have two main objectives in this paper; firstly, to use data on career preferences from three separate cohorts of medical students, both at the time of application and in their final year at medical school, in order to derive a map of medical careers. And second, to assess the extent to which this specific map of medical careers is homologous to Holland's more general map of a broad range of careers.
The data collected in our studies consist of ratings of attractiveness of different medical careers on a five-point scale, ranging from 'Definite intention to go into this' through to 'Definite intention not to go into this'. However, our primary interest for the purpose of deriving a map of careers is not in career preference, but rather in career similarity. If a student has a preference for career A and career B, but has no interest in career C and D, it follows that career A is probably relatively close to career B on the map, and career C is relatively close to career D, whereas careers A and B are likely to be more distant from careers C and D. A matrix of similarities between all possible pairs of a large number of careers from a large number of students then allows one to construct the underlying map (just as, in a classic example, a knowledge of the geographical closeness, or the drive-time, between many pairs of towns in a country allows one to reconstruct a map of the country [43,44]). The statistical technique is known as multi-dimensional scaling (MDS).
Although conventional MDS can reconstruct the underlying map showing the relations between a number of objects, the map itself is arbitrary to rotation. Turning the map through any angle does not change any of the distances between pairs of objects, and therefore the axes of the map cannot be known – in the case of a geographical map, there is no indication of the north-south and east-west axes. The problem of the arbitrariness of dimensions can be circumvented by means of a variant of MDS known as INDSCAL (Individual Differences Scaling) [44,45]. This method analyses the similarity matrices either of individual subjects or of groups of subjects who are likely to differ, so that, for instance, one might have groups based on sex and age, the presumption being that older students may have different career preferences from their younger peers, and female students may have different preferences from their male peers. INDSCAL then allows the assignment of axes, it being likely that the grouping variables will mainly affect one rather than all of the dimensions on which the map is represented. An example in the case of geographical distance might be to examine the time of travel between pairs of towns in winter and summer. Inclement winter weather will increase the time of travel in the more northerly towns, but the dimension of east-west will have little impact on the measures. In this paper, we use INDSCAL to construct our maps of medical careers, so that the axes are identified and not arbitrary to rotation.
Methods
Two different types of data have been used in the present study. The bulk of the analysis looks at data collected during studies of medical student selection and training, and can be used to map medical careers. A subsidiary, but important, analysis looks at a large convenience sample of people of different ages who were taking part in a survey about careers in general, and were asked about their interest in a range of careers, of which only a few were medical. These latter data allowed us both to calibrate specific medical careers in the context of the general Holland typology, and to validate the INDSCAL methodology for deriving a map of careers.
Medical student data
The data were collected during three longitudinal studies of medical student selection, the first of which began in the autumn of 1980, looking at students who had applied for entry to medical school in 1981 [46,47], the second began in the autumn of 1985, studying applicants for entry to medical school in 1986 [48,49], and the third began in 1990, studying applicants for entry to medical school in 1991 [50,51]. The 1981 and 1986 cohort studies were restricted to students applying for entry to St. Mary's Hospital Medical School in London, although since applicants had each applied to five or six medical schools, many students entered schools other than St. Mary's. The 1991 cohort study looked at applicants to five different English medical schools, and because each applicant applied to several schools, these applicants represented 70% of all applicants and entrants to UK medical schools in that year. In each survey, applicants were sent questionnaires as soon as possible after UCCA, the central universities admission system, had received their application and entered their names had been onto the computer database. In general this was many weeks or even months before applicants were asked to come for interview, or were sent decisions on whether they had been accepted or rejected. The data are therefore to a great extent properly prospective.
For the present paper, the analysis of the 1981 and 1986 cohort data considers data on all applicants who replied to our questionnaires, whereas the 1991 cohort, which was very much larger, considers only those questionnaire respondents who entered medical school (although we will generally refer to this group as 'applicants' since that reflects the time at which the questionnaire was completed). In additional file 1 we present separate information for the entire 1991 cohort which shows that there are unlikely to be response biasses, either due to differences between accepted and rejected applicants, or due to not all entrants responding to the final-year questionnaire. Response rates in the 1981, 1986 and 1991 applicants surveys were 85%, 93% and 93% [46,48,50].
Students who entered medical schools in 1981, 1986 or 1991 (or in a few cases due to deferred or repeated entry, in 1982, 1987 or 1992) were followed up as final-year students in 1986 (or 1987), in 1991 (or 1992) and 1996 (or 1997). Students still in medical school were identified through their medical schools, and questionnaires sent to those medical schools. Response rates were 65%, 50%, and 56% in the follow-up of the 1981, 1986 and 1996 cohorts of students in their final year [49,51].
The questionnaires used in the study, both at application and in the final year, were detailed, typically covering 16 sides of A4, and the results reported here concern only one of the questions asked. Career preferences were assessed by a question which used the rubric,
"Below is a detailed list of specialities in which a medical career can be pursued. Please indicate your attitude towards each speciality as a possible career. If you either know nothing about a speciality, or have no opinions about it at all, simply leave that answer blank".
A list of specialities followed, each of which was rated on a five-point scale, for which the categories were, "Definite intention to go into this", "Very attractive", "Moderately attractive", "Not very attractive", and "Definite intention not to go into this".
The list of specialities varied a little over the different surveys, becoming slightly more extensive as the years passed. The original list was based on the questionnaire distributed as part of the Royal Commission on Medical Education of 1968 [52] (The Todd Report). The questionnaire for 1981 applicants had 24 questions. The final-year questionnaire for the 1981 applicants had 26 questions, the two new categories being "Pre-clinical teaching" and "Geriatric Medicine". The questionnaire for the 1986 applicants was the same as that for the 1981 applicants except that it had 25 specialities, "Geriatric medicine" having been added. The final-year questionnaire for the 1986 cohort had 27 questions, the 25 used for applicants, with the addition of "Genito-Urinary Medicine" and "Infectious Diseases". The applicant questionnaire for the 1991 cohort had the same 27 questions as did the final-year questionnaire for the 1986 cohort. The final-year questionnaire for the 1991 cohort was similar to that for the applicants except that it had 28 questions, "Radiology/Radiotherapy" having been split into two separate specialities. In the present study all of the questionnaires have been used in the form in which they were originally administered, the only omission being the speciality "Pre-clinical teaching", which was used in one survey only and is of little interest.
The general population sample
This questionnaire was completed by a sample of 1026 subjects, stratified by age using a median split (≥ 42; <42) and by sex. It asked about the suitability of twenty-four different careers for the person. Twenty careers were derived, as far as possible, from Holland's RIASEC classification, with at least three in each of the six categories. In addition there were four categories which were medical (Anaesthetist, Hospital Doctor, Psychiatrist and Surgeon). The rubric was,
"Below is a list of careers. Please indicate for each one how much you think it might have been suitable for you as a career".
Each career was rated on a five-point scale, ranging from 'Extremely suitable', through 'Very suitable' and 'Quite suitable', to 'Not very suitable' and 'Completely unsuitable'. The subjects were a convenience sample obtained from amongst friends and relations by a first year lab class at University College London, each student being responsible for obtaining a group of twelve subjects, stratified by age and sex.
Statistical analysis
INDSCAL analysis was carried out using the ALSCAL program within SPSS 10.1. Data in each subset were broken down into four groups by age and sex, age referring to mature vs non-mature students in the medical student samples (≤ 21; >21) and to subjects aged <42 or ≥ 42 in the general population sample.
The raw data, which were collected on a 5 point Likert scale, were transformed into Euclideanbased dissimilarities for all combinations of career pairs, using the PROXIMITIES program in SPSS. Four different dissimilarity matrices were produced (nonmature males, nonmature females, mature males, and mature females), and these matrices provided the basis for the INDSCAL analysis that involved minimisation, in Euclidean space, of the discrepancies between the career dissimilarities and the corresponding interpoint distances on the map. The loadings of each career on the two extracted dimensions were then plotted onto the figures to provide the maps.
The dimensionality of MDS/INDSCAL analyses can be assessed, in a manner analogous to that used in factor analysis in which eigenvalues are plotted against components. In MDS one plots a measure of 'stress' (in effect, the opposite of goodness-of-fit) against the number of dimensions which have been extracted. If too few dimensions have been extracted then the stress is high, the model not accounting adequately for the richness of the data. The optimal number of dimensions is typically indicated by a sudden 'dog-leg' in the stress plot.
Results
We consider firstly the general population sample since it both validates the method which we will subsequently use for the medical student samples, and also helps calibrate the axes.
The general population sample
The questionnaire was completed by 1044 subjects, 49.2% of whom were male, and 46% aged over 42. Multidimensional scaling used the INDSCAL method, with the four groups comprising older and younger males and older and younger females. The stress plot indicated that there were two major underlying dimensions in the data, as Holland's typology would suggest (see also Prediger [53,35]). The locations of the different careers are shown in figure 2. There is good evidence for Holland's RIASEC typology, and the letters R, I, A, S, E and C have been placed on the graph to clarify interpretation. Pilot and Engineer are typical of Realistic careers, Biologist of Investigative careers, Artist and Museum Curator of Artistic careers, Social Worker, Counsellor and Teacher of Social careers, Personnel Director and Lawyer of Enterprising careers, and Accountant and Computer Programmer of Conventional careers. For this non-medical group of subjects, the four medical careers are all placed in the top half of the figure, with surgeon and anaesthetist closest to Investigative, and Psychiatrist closest to Social.
Figure 2 INDSCAL group space of the career preferences expressed by the general population sample. The locations of the labels R, I, A, S, E and C are approximate and are only for guidance and orientation. The four medical specialities are shown in blue so that they are more visible.
Of some importance, given the arbitrariness of the Holland hexagon to rotation in conventional MDS, is that the INDSCAL analysis clearly sets one axis as running from R to S, with the other axis orthogonal to that, running from I and A to C and E. These are similar to the Things-People and Ideas-Data dimensions shown in figure 1.
The medical student samples
Sample sizes for the medical student studies were 1135, 2032 and 2973 for the students in the 1981, 1986 and 1991 cohorts (and these samples consisted of all applicants in the 1981 and 1986 cohorts, and all entrants in the 1991 cohort), and were 330, 376 and 1437 for the final-year students in the 1981, 1986 and 1991 cohort studies. The INDSCAL analyses were restricted to those subjects for whom complete career information was available; this consisted of 538 applicants and 312 final-year students in the 1981 cohort, 1118 applicants and 301 final-year students in the 1986 cohort, and 1638 entrants and 1437 final-year students in the 1991 cohort. See additional file 1 for details of the breakdown of samples by sex and maturity.
The dimensionality of the medical student samples was assessed by carrying out a standard multi-dimensional scaling analysis (i.e. MDS, not INDSCAL), separately for the combined applicant data and the combined final-year data from the three cohorts. The stress formula attempts to quantify the discrepancies between the fitted distances in the model and the observed dissimilarities among the career ratings, with larger values indicating poorer fit. It is obviously the case that the more dimensions are extracted, the better the fit of the model and, hence, the lower the stress value. However, it is also the case that a greater number of dimensions complicates interpretation and may lead to overfitted and unstable solutions. The stress levels with 1,2,3,4,5, and 6 dimensions were .352, .174, .112, .077, .059 and .048 for applicants, and .390, .174, .112, .082, .064 and .052 for final-year students. For the final-year students, it is clear that two dimensions are necessary, and that there is little advantage of adding extra dimensions. The applicant data are slightly less clear and although there is still no doubt that at least two dimensions are necessary there is a suggestion that a third dimension may be of value. Subsequent scrutiny of models with three dimensions suggested that the third dimension was contributed almost entirely by one or two specialities such as forensic medicine, which have a high public and media profile, but which form only a small proportion of medical personnel. It was, therefore, felt to be safe to extract two dimensions, particularly since Holland's typology provided an a priori expectation that there would be two dimensions.
INDSCAL analyses
Separate analyses were carried out for the applicant and final-year data in each of the three cohorts. In each case, data were broken down into sub-groups according to sex (male-female) and age (mature at entry to medical school, i.e. >21 yrs old; or typical post-school entry, at ≤ 21 years old). INDSCAL analyses can clarify the underlying dimensions within data as long as the sub-groups are likely to vary along those dimensions. It should be noted that many studies have found sex differences in medical career interest (e.g. [54]), and younger students are also likely to have different attitudes towards careers than their non-mature counter-parts [55].
Figures 3,4 and 5 show the group plots of the different specialities in applicants to medical school, and figures 6, 7 and 8 show the group plots for the specialities in final-year medical students. In order to help interpret these plots, and for reasons which will become clearer later, we have joined together the data points for Surgery, Hospital Medicine, Psychiatry, Public Health, Administrative Medicine and Laboratory Medicine. For the applicants, it is now clear that these specialities are arranged approximately in the form of a hexagon, with Surgery at the extreme left and Administrative Medicine at the bottom right-hand corner. The pattern shown in the final-year students is similar, Surgery still being at the left-hand side, and Administrative Medicine at the bottom right. Although there are some minor differences between the three cohorts, the broad picture is of overall similarity in the structure of the maps.
Figure 3 The INDSCAL group space for the medical specialities for the applicants in the 1981 cohort. For abbreviations see the Abbreviations section.
Figure 4 The INDSCAL group space for the medical specialities for the applicants in the 1986 cohort. For abbreviations see the Abbreviations section.
Figure 5 The INDSCAL group space for the medical specialities for the entrants in the 1991 cohort. For abbreviations see the Abbreviations section.
Figure 6 The INDSCAL group space for the medical specialities for the final-year medical students in the 1981 cohort. For abbreviations see the Abbreviations section.
Figure 7 The INDSCAL group space for the medical specialities for the final-year medical students in the 1986 cohort. For abbreviations see the Abbreviations section.
Figure 8 The INDSCAL group space for the medical specialities for the final-year medical students in the 1991 cohort. For abbreviations see the Abbreviations section.
The maps shown in figures 3 to 8 are, in INDSCAL terminology, group spaces [44,45]. They are, however, composed of several different sources, broken down by age and sex. Maps can also be produced of 'source space' which shows how the groups differ in their relative weighting of the two extracted dimensions. Figure 9 shows the source spaces for the applicant and final-year student data in the three cohorts. The vertical axis represents the relative importance of the Things-People dimension, whereas the horizontal dimension shows the importance of the Data-Ideas dimension. It should be noted that these axes do not mean that, say, People are more important than Things, but that the Things-People dimension is more differentiated than the Data-Ideas dimension (just as, say, in a map of Italy or Chile, there is far more north-south differentiation than east-west, as they are long-thin countries). In each of the six analyses, the male subjects put more emphasis on the Things-People dimension whereas the female subjects put more emphasis upon the Data-Ideas dimension (and hence the male subjects tend to be in the top left corner and the female subjects in the bottom-right). In the 1981 cohort there is also a suggestion that younger subjects put more emphasis on the Things-People dimension, and older subjects on the Data-Ideas dimension for differentiating careers, but the effect is smaller in the 1986 cohort, and barely visible in the 1991 cohort, suggesting a possible change in the way these groups perceive medical careers. In interpreting these analyses it should be noted that although the absolute size of the various groups was more than adequate for the INDSCAL analyses, the group weights for the mature candidates (male and female) in the 1981 and 1986 finalyear data were based on very small samples, ranging between 5 and 17 participants, and may, therefore, be somewhat unstable.
Figure 9 INDSCAL source spaces for the applicants/entrants and final-year medical students in the 1981, 1986 and 1991 cohorts. Square symbols are for male subjects and circles for female subjects. Solid symbols are for younger students, whereas hatched symbols are for mature students. To help visualisation, the solid arrows connect from younger males to younger females, whereas dashed arrows connect from mature males to mature females. See text for further details of interpretation.
Discussion
The primary objectives of this study were to use the empirical method of individual differences scaling to derive maps of the underlying perceived structure of medical career specialities, and to assess the extent to which those maps are similar to those described by Holland in his hexagonal representation of the RIASEC groups of careers. That this method is a valid way of deriving Holland's structure in general is seen in figure 2, in which a broad range of non-medical careers is assessed by non-medical individuals, and the RIASEC structure is readily derived. Of particular importance is that because the analysis used INDSCAL, the dimensions are not arbitrary to rotation, and that the R-S dimension (corresponding to the Things-People dimension) and the IA-EC dimension (corresponding to the Ideas-Data dimension) are the basic underlying structure, as shown by Prediger [35,53]. The "Things-People" dimension also bears a strong similarity to the Technique orientation and People orientation which has also been described in relation to medical specialities [56].
The general population sample also rated four medical specialities, with Surgery and Anaesthetics at one extreme, and Psychiatry at the other, and these medical specialities differed principally along the R-S dimension. That Surgery and Anaesthetics are more concerned with Things, and Psychiatry is more concerned with People fits well with the reduction of Holland's hexagon to the two dimensions of Things-People and Ideas-Data. It is also worth noting that all of the four medical specialities are seen by the general public as being primarily concerned with Ideas rather than with Data, as surely befits medical careers.
The MDS analyses demonstrate that the representation of the various medical specialities by the medical student samples can be captured within a two-dimensional space, as Holland had suggested. The maps shown in figures 3 to 8 indicate that the structures are broadly similar across the three cohorts, and that although there are some minor differences between the applicants and the final-year students, it is the case that overall the similarities are more impressive than the differences. The crucial question therefore concerns whether the medical student maps are homologous to those of Holland's RIASEC typology. If there is a homology, then one may ask what are the Realistic, Investigative, Artistic, Social, Enterprising and Conventional specialities of medicine.
From scrutinising figures 3 to 8 we suggest that the RIASEC structure of medicine is typified by the six prototypical specialities of Surgery, Hospital Medicine, Psychiatry, Public Health, Administrative Medicine and Laboratory Medicine. It should be emphasised that in suggesting this we are not implying a direct comparability in the posts, rather a formal similarity within the limits imposed by being within the domain of medicine, as opposed to that of careers in general.
Surgery – Realistic
Surgeons can be seen as the engineers of medicine, solving problems at high levels of mechanical and technical proficiency, with an emphasis upon practical skills, craftsmanship, and immediate and effective results.
Hospital Medicine – Investigative
The core of Hospital Medicine (Internal Medicine) is diagnosis, achieved by carrying out appropriate investigations. Physicians typify the model of the 'scientist-practitioner', investigating symptoms and signs and relating them to the underlying pathophysiology of the patient.
Psychiatry – Artistic
Psychiatrists, and also General Practitioners, have a more artistic approach to medicine, seeing, interpreting and responding imaginatively to a range of medical, social, ethical and other problems. The emphasis in many ways is on the uniqueness of the patient, the ideas that they are expressing, and the psycho-social theories and concepts which are necessary for interpreting the individual.
Public Health – Social
Although most medicine is concerned with individual patients, the remit of Public Health is primarily social in the sense of applying medicine to society as a whole, treating the 'body politic'. It is noteworthy that in the maps, Public Health is not only at the Social end, but also closer to Data than to Ideas. Public Health manages social and community health by the appropriate analysis of data.
Administrative medicine – Enterprising
The management of hospitals and health-care requires the creative skills of the business executive, the lawyer and the personnel director to achieve a smoothly running system. People, both patients and carers, are at the heart of any health-care system, and therefore administrative medicine is at the People end of the dimension.
Laboratory Medicine – Conventional
The running of efficient systems in haematology, histopathology or chemical pathology requires many of the attributes shared with the accountant or the banker, including the willingness to develop, implement and follow standard procedures within a complex system. The emphasis is inevitably upon the things that do the measurements, and upon the data collected, rather than the ideas or people behind the data and the technology.
The analyses in this paper suggest that in our groups of students there is a broad similarity between preferences for medical careers and the typology found by Holland in careers in general, suggesting that the structures are homologous. Although our study has been restricted to medical students in the UK, our findings are likely to be generalisable, given that the patterns are found in three separate cohorts studied over a decade, and across medical school applicants and final-year students. Just as Holland's typology is found in most studies of careers, over a period of three decades and in many countries, despite a wide range of changes in society, in education, and in the nature of jobs and careers themselves, so we would predict that our typology of medical careers will be robust to such changes. To put it more strongly, we would predict that despite enormous changes in every aspect of medicine over two and a half millennia, just as Hippocrates recognised that surgery is different in many ways from other branches of medicine, and that not every doctor wishes or is able to be a surgeon, so the same applies today and will probably continue to apply as long as medicine is practised. That is likely to be so primarily, as Ackerman has suggested, because Holland's typology is underpinned by wide-ranging, broadly defined individual differences in aptitude and personality [36] which are also likely to be stable across time and cultures [57].
It may at first be felt that our approach to mapping careers is fundamentally different to that of Gale and Grant [58,59], who describe a questionnaire, the Sci-45, which has twelve sub-scales and allows discrimination between 45 different medical specialities as possible careers. However, the purposes of that instrument and our analyses are very different. Gale and Grant aimed at developing a practical instrument for counselling individuals, which would allow a detailed differentiation between careers. In contrast, we aimed at investigating and mapping the broad picture underlying careers. To use an analogy with geography, our map is primarily a large-scale representation of a region such as Britain, which lays out the main north-south and east-west axes and defines the broad regions of that map (Scotland, Wales, South of England, East Anglia), as well as placing the main cities, which are analogous to the specific careers. Gale and Grant in contrast are developing a method of differentiating between the various cities, particularly when, as say in the West Midlands conurbation, some cluster closely together within the map. We therefore expect that underlying the Gale and Grant questionnaire will be two broad dimensions equivalent to those which we have described.
Abbreviations
INDSCAL Individual differences scaling
MDS Multidimensional scaling
RIASEC Realistic-Investigative-Artistic-Social-Enterprising-Conventional
Speciality abbreviations in figures 3 to 8.
ADM Administrative Medicine
ANS Anaesthetics
ARM Armed Forces
BMS Basic Medical Sciences
DRM Dermatology
ENT Ear, Nose & Throat
FRN Forensic
GER Geriatrics
GPlrg GP Large Group practice
GPsml GP Small practice
GPsng GP Single handed
GUM Genito-urinary medicine
IND Industrial Medicine
INF Infectious diseases
LAB Laboratory (Haematology, Clinical Chemistry, etc.)
MED Internal Medicine
O&G Obstetrics & Gynaecology
O&T Orthopaedics & Trauma
OPH Ophthalmology
PED Paediatrics
PHM Pharmaceutical Medicine
PSY Psychiatry
PTH Pathology
PUB Public Health
RAD Radiology/ Radiotherapy
RDL Radiology
RDT Radiotherapy
RES Research
SRG Surgery
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
ICM had collected the data in the various surveys over a number of years. ICM and KVP jointly decided how to do the statistical analysis, and KVP was responsible for the programming and data analysis. ICM wrote the first draft of the paper, which was revised by KVP, with both authors being responsible for the final draft.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Supplementary Material
Additional File 1
Additional analyses of data
Click here for file
Acknowledgments
We thank the many medical students and doctors who, over many years, have enabled ICM to carry out these longitudinal studies of medical student selection and training. K V Petrides was supported by a Postdoctoral Research Fellowship awarded by the Economic and Social Research Council (ESRC) and mentored by I C McManus.
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| 15461786 | PMC524180 | CC BY | 2021-01-04 16:30:53 | no | BMC Med Educ. 2004 Oct 1; 4:18 | utf-8 | BMC Med Educ | 2,004 | 10.1186/1472-6920-4-18 | oa_comm |
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Biomed Eng OnlineBioMedical Engineering OnLine1475-925XBioMed Central London 1475-925X-3-311546178710.1186/1475-925X-3-31ResearchImageParser: a tool for finite element generation from three-dimensional medical images Yin HM 13huiming@uiuc.eduSun LZ 1lizhi-sun@uiowa.eduWang G 2ge-wang@uiowa.eduYamada T 24yamataka@rad.med.tohoku.ac.jpWang J 25hstjen@yahoo.com.twVannier MW 26mvannier@radiology.bsd.uchicago.edu1 Center for Computer-Aided Design, The University of Iowa, Iowa City, IA 52242, USA2 Department of Radiology, The University of Iowa, Iowa City, IA 52242, USA3 Department of Civil Engineering, University of Illinois, Urbana, IL 61801, USA4 Department of Diagnostic Radiology, Tohoku University, Sendai 9808574, JAPAN5 Department of Radiology, National Taiwan University, Taipei, TAIWAN ROC6 Department of Radiology, The University of Chicago, Chicago, IL 60637, USA2004 1 10 2004 3 31 31 7 7 2004 1 10 2004 Copyright © 2004 Yin et al; licensee BioMed Central Ltd.2004Yin 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 finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures) of interest (ROIs) may be irregular and fuzzy.
Methods
A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements.
Results
The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues.
Conclusion
The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information.
Breast imagingimage segmentationbiomechanical analysismeshingfinite element method (FEM)
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Background
Diagnostic imaging devices such as CT, MRI and PET scanners are able to produce three-dimensional (3-D) descriptions of various features such as tissues and organs. In a computer, these images are some data to describe the intensity at each spatial point of a volume. The interpretation of the dataset requires special training and depends on the experience. Researchers have introduced a variety of algorithms to visualize 3-D medical images, and to extract the geometric information of objects from volumetric image data [1-3].
In recent years, the finite element method (FEM) has widely been used to simulate the mechanical deformation of tissues and organs during examinations or interventions [4-6]. To build up an FEM mesh from a medical image, the contour information of segmented regions of interest (ROIs) need to be first extracted from a volume of data [7,8]. Then, the volume is meshed into nodes and elements, and material properties are endowed to each element in accordance with the segmentation information [9]. By further applying the boundary conditions and mechanical loadings on the corresponding nodes or elements, commercial FEM software packages such as ANSYS and ABAQUS may calculate the mechanical stress and strain, and predict the deformation and motion in the field of view.
The purpose of this work is to establish an FEM model to simulate the deformation of a woman breast based on mammography compression. A patient's breast may include three kinds of tissues: fatty, parenchyma, and cancerous tissues [6]. During the examination, the breast is squeezed by two flat paddles to obtain an image with a good contrast. The dependence of the relative deformation carries information on the mechanical properties of the tumors and masses. Thus, the FEM is a powerful tool to simulate this kind of deformation. The breast need first be separated from the context of a biomedical image which includes some other organs and the different tissues of the breast are then segmented. As seen in Figure 1, parenchyma has a cloud-like shape and three tissues are fully mixed in some regions. While existing modeling techniques [e.g., [1,2]] may be applied, a significant amount of 3-D elements have to be introduced because the geometric shapes of the constituent tissues are fairly irregular with fuzzy boundaries. It is not optimal to apply those techniques to our research and clinical studies due to the requirements on the computational efficiency.
Figure 1 The Interface of ImageParser When Loading a 3D Image. The image is automatically shown slice by slice with the slice number shown in the text box, and the interval between two slices can be changed. Clicking the slide bar or text box, we can focus on the current slice; double clicking the window area, we can navigate the image slice by slice again; and dragging the slide bar or inputting the slice number in the text box, we can jump to the desired slice.
In this paper, a software package called the ImageParser is developed to generate an FEM model from 3-D medical images. While aiming at the imaging segmentation, mesh generation, and deformation simulation of heterogeneous breast tissues, the method is applicable to the many biomedical imaging and biomechanical analysis of soft/hard tissues such as mammography and cardiovascular imaging. This software uses a semi-automatic method to detect the objective constituents from the context of an image including neighboring tissues and organs. It segments an image based on customer-defined grayscale ranges, and meshes tissues into elements with a customer-defined size. Inputting the generated FEM mesh into an FEM program, we can calculate the mechanical deformation under specific boundary conditions and mechanical loadings. The ImageParser is written in Microsoft Visual C# .NET (Microsoft Development Environment 2003 Version 7.1), and can be integrated into a high-level image analysis environment with a good extendibility and scalability.
Description
Overview
The ImageParser provides a window style GUI as shown in Figure 1. A 3-D image is loaded and shown slice by slice. We can focus on any slice and edit it. While the image can be displayed in the color mode, in graphics analysis, we use 8-bit grayscale to describe a voxel. The RGB color can always be transformed into grayscale according to a desirable equation [10]. The size of voxel can be user-defined. The image can then be segmented into the real organs. Here we use Figure 1 as an example to show the procedure for generating an FEM mesh using the ImageParser. In Figure 1, the breast is the selected ROI within the axial CT image including the breast, ribs, and organs in the thorax. To obtain its geometric information, we first isolate it from other unwanted regions by selecting a rectangular region as shown in Figure 2. It is noted that this selection also works for all other slices so that when we select the ROI, we need work on the most representative slice and reserve enough space not to truncate the wanted region in other slices. Because the shape of the breast is irregular, we can still see the rib and part of the thorax in the ROI as well as some regions with the background color. We need further detect the borderline of the breast in each slice.
Figure 2 The Region of Interest in a Slice. Under the function of selecting ROI, press the left button of the mouse and drag the mouse. When the dashed line rectangle covers ROI, release the button. All the slices will be shown as this selection.
This software provides a semi-automatic interface to detect the borderline of the breast as shown in Figure 3. We use the computer mouse to select some key points on the borderline, and then the software will automatically detect the borderline between the key points. Because the borderline changes from one slice to another, the software is designed to automatically detect the borderline of the neighboring slice using the known borderline as a seed. Repeating this procedure, the software can detect the borderlines for all slices. The algorithmic details will be provided in the next section. Based on these borderlines, we can reconstruct the surface of the breast. It is noted that for some special cases that the borderlines are fuzzy or irregular, the software cannot effectively detect the borderlines. However, we can manually select more key points in the first slice, and process other slices similarly. Then, based on our experience we can always manage to obtain the borderlines with a high precision.
Figure 3 Selecting and Detecting the Borderline of the Breast in ROI. Under the function of selecting Outline, click the left button of the mouse on a point close to the borderline. The software will detect the closest point of the borderline and mark it with a yellow cross. After click the next point close to the borderline, the software will automatically detect the closest borderline between the previous point and this one. Repeat this procedure. The borderline is finally detected.
Figure 3 shows three types of tissues in the breast: the black area representing fatty tissue, the gray area representing parenchyma, and the light area representing the tumor. Because these tissues have different mechanical properties, we need segment them out of the breast as new ROIs. Here we use the grayscale to classify the voxels. From the grayscale histogram in Figure 4, we can find the grayscale ranges corresponding to the different tissue types. With the grayscale range for each tissue, the software can map the voxels onto corresponding categories. For example, in this figure we can use the grayscale from 0 to 64 to represent the fatty tissue, 64 to 144 the parenchyma tissue, and 144–256 the cancerous tissue.
Figure 4 The Grayscale Histogram of ROI. Horizontal axis denotes a grayscale (G), and vertical axis a number of voxels. G = 0 is the background color of black; G = 255 the color of white. From the grayscale distribution corresponding to the tissues in Figure 3, we can define the grayscale range for fat, parenchyma, and tumor tissues.
While we are able to directly output the segmentation information based on the voxels, it cannot be effectively used by any FEM software since the whole breast includes more than ten million voxels. We therefore mesh the breast into larger elements based on the specific requirements of precision and computation capability. Figure 5 shows the FEM mesh of one slice with three tissues marked by different colors. Extending this procedure to all slices and considering the slice thickness and element size, we can obtain the 3-D FEM mesh of the breast. While we take cuboidal elements as an example to generate the mesh at this stage, we can also mesh the breast into other elements such as tetrahedrons.
Figure 5 The FEM Mesh of the Breast. The selected region is meshed by cuboidal elements. The color of black denotes fat; gray parenchyma; and white tumor. The green lines are the boundary of elements. Though only one slice is shown here, elements are also generated for some other slices so that the 3D FEM mesh of the Breast is obtained.
After the mesh of the breast is generated, we can implement it into an FEM software package to simulate the mechanical deformation of the breast with given material constants of all the tissues and appropriate boundary conditions.
Borderline Detection
A medical image typically includes many kinds of organs and tissues. However, biomedical engineers may only be interested in a small number of regions in a complex medical image. While certain algorithms have been developed to automatically detect the surface of the 3-D image [1-3,11], the object surface may not be well defined because the ROI is in the context of the complex image, and the boundary is not clear especially for some soft tissues. We have to use our knowledge to isolate ROIs from the image. Therefore, we propose to develop a semi-automatic method as described in the following steps.
1. We first focus on one slice. When the first point (x0, y0) is selected close to the borderline, a function is then used to search the most possible border point in the square region with the left-top point (x0 - s, y0 - s) and the right-bottom point (x0 + s, y0 + s). Here s is a customer-defined parameter with a default value as 3 pixels. In this region, the gradient of each point Δ(x, y) is defined by a Laplace operator [12]
so that
where f(x, y) denotes the intensity at (x, y). The detected point is the one with the different color from the background and with the maximum value of Δ(x, y)/[(x - x0)2 + (y - y0)2 + ε] where ε is a customer-defined parameter with a default value as 0.1 to prevent the singularity on the point (x0, y0). The detected point is denoted as (x1, y1). It is noted that the Laplacian normalized by the distance of the point to the selected seed point is to make the neighboring points have a higher priority to be detected. At certain regions, the borderline may not be clear or two borderlines are close enough, in which cases the program will not get lost.
2. We start to select the next point of the borderline. After we manually select one point visually close to the borderline following the method of detecting (x1, y1), the software can adjust the location of the point and detect the second point (x2, y2) on the borderline. As seen in Figure 6, a function detects the borderline between (x1, y1) and (x2, y2). Two squares with edge length 2s are marked by the dark color in a big square having a diagonal line from (x1, y1) to (x2, y2). We find the most possible border point in the two dark squares by using the same method in the first step. If this new border point is in the right-top square, we replace (x2, y2) by this point. Otherwise, we replace (x1, y1) by the new border point. Once (x1, y1) or (x2, y2) is updated, we continue to find the next border point in the same way. Repeat this procedure until the distance between the two points is less than 2s. Connecting all points in such an orderly way, we obtain the borderline. It is noted that this method is convergent because the distance between two working points becomes smaller and smaller in this procedure.
Figure 6 Detecting Borderline between Two Points (x1, y1) and (x2, y2). First find the most possible border point in two dark regions. Then, treat the new point and the left old one as same as (x1, y1) and (x2, y2), and find the next border point. Repeat this procedure until the distance between two points is less than 2s. Connecting all points orderly, we obtain the borderline.
3. We repeat step 2 until the borderline is closed. We thus obtain the whole closed borderline in the slice.
4. For a 3-D medical image, due to the similarity of neighboring slices, the proposed software can map the selected key border points of the slice onto the neighboring slice and use the method in step 1 to find the corresponding border points in the new slice. After that we adopt step 2 to detect the borderline between the border points. In this way, we are able to detect the borderlines in all the slices. From these borderlines we can finally construct the surface of the selected ROI.
Because the borderlines of other slices are detected on the basis of the first slice, selection of this slice greatly affects the quality of results. We suggest that this slice need contain the most representative information. If the change of two neighboring slices is large, we can optionally reselect the border point in the new slice instead of detecting the borderline by the computer. It is further noted that because the borderlines detected by the computer may be very irregular, we can use a cubic Bezier curve fitting technique to smooth the borderlines.
FEM mesh Generation
Among several methods to automating mesh generation [9], the mesh with cuboidal elements is the fastest and most stable method to mesh an organ with irregular shape even though it may require more elements at the boundary. We therefore apply the cuboidal-element mesh to make this software applicable for complex cases. For instance, in Figure 3 the cloud-like parenchyma is dispersed in the fatty tissue. It is almost impossible to extract the exact geometry of parenchyma. In this case, most geometry-based methods are invalid. In the cuboidal mesh, elements are generated layer by layer and are automatically connected through the overlaid nodes. Given an element size, we can calculate how many slices each layer of elements spans. For simplicity, we assume the borderline of the central slice to be the borderline of that layer. Since the borderline consists of many points, we first build up a grid using the element size, move each border point to the closest cross-point of the grid, and remove the repeated points. We thus obtain the borderline denoted by the cross-points of the grid. It is noted the borderline may be entangled somewhere due to the numerical truncation. We need normalize the borderline so that it encloses a single-connected region and the distance between two neighboring point is equal to the size of the elements.
When we scan the single connected region, there exist two types of points on the borderline: jumping points and inertial points. If the left and right sides of a point are in the different states; i.e. one side is in the inside of the objective region and the other side is in the outside, then the point is called a jumping point. Otherwise, this point is called an inertial point. For instance, in an upstanding rectangle, all points on the left and right sides are jumping points, whereas the rest points on the top and bottom sides are inertial ones. On a closed borderline, each point is connected to two points. For a jumping point, the two neighboring points apparently have different values of y coordinate, whereas those for an inertial point do not. From this criterion we can identify the jumping points on the borderline. Once the points of the borderline are given, we can sort the points from top to bottom by y coordinate and from left to right by x coordinate. Then, for any y coordinate we can obtain a list of points with increasing x coordinates. During a horizontal scan for a fixed y coordinate, the number of jumping points in this list must be even, with which we obtain the pair-wise jumping points and find all the internal points between each pair of jumping points. Scanning the points from top to bottom, we can obtain all the internal points for the connected region. Then we can obtain the cuboidal-element mesh for this layer by mapping one point onto one element.
Because different elements may have different material properties, we need find the segmentation information for each element. From the grayscale histogram, we have defined the grayscale ranges corresponding to the tissues. Typically, an element may contain many voxels that belong to different tissues, whereas the FEM requires the element to be homogeneous. We count the number of voxels for each tissue in the element and assume the maximum one to be the material of the element. Thus, we can map the elements onto the different tissues as shown in Figure 5. We can thus mesh the object layer by layer and finally obtain the total FEM mesh, from which we can further calculate the volume of each tissue.
The surface information of the object is important for applying boundary conditions and mechanical loadings. This software uses the 2-D rectangular elements to describe the surface. Each 3-D cuboidal element has six rectangular faces. We collect the faces from all cuboidal elements. Thus, for an object containing N cuboidal elements, we can obtain 6N 2-D rectangular elements. Obviously not all the rectangular elements are on the surface of the object. If an element is not on the surface, from the connectivity, another 2-D element containing the same nodes must exist which belongs to the neighboring cuboidal element. Eliminating each pair of these inside elements, we are able to obtain surface elements. We further input the mesh with segmentation information into an FEM program based on the required data format, assign material properties to tissues, and apply boundary conditions on the surface nodes. We can eventually calculate the mechanical deformation, internal stress and strain by the FEM software.
Results and Discussion
3-D FEM Mesh and Material Properties
To illustrate the capability of this software, we construct an FEM model of a woman breast and simulate the mechanical deformation with applied compressive forces. A set of CT image of the prone breast was acquired consisting of 512 × 512 × 243 voxels. The voxel size is 0.46875 × 0.46875 × 0.6 mm3. As an example, the 148th slice is shown in Figure 1. The breast includes three kinds of tissues: fat, parenchyma, and tumor, which are represented by three grayscales as dark, gray, and light, respectively. Using the ImageParser package, we are able to mesh the breast by cuboidal elements with a size of 2.8125 × 2.8125 × 3 mm3. The breast is meshed into 14,902 elements with 18,486 nodes as shown in Figure 7. The tumor, parenchyma, and fatty tissue consist of 154, 5783, and 8965 elements, respectively. The surface of the breast includes 6,900 rectangular 2-D surface elements. The region of breast is defined as follows: 0 <x < 84.375 mm, 0 <y < 87.1875 mm and 0 <z < 135 mm. Here x is from left to right in a slice of the image, y is from the top to bottom, and z is from the first slice to the last slice. Corresponding to the human body, y represents the normal direction of the coronal plane, while z signifies the normal direction of the axial (transverse) plane (Figure 7).
Figure 7 3D FEM Mesh of the Breast. The breast is meshed by cuboidal elements with a size of 2.8125 × 2.8125 × 3 mm. 14,902 elements and 18,486 nodes are generated. The breast is in the region as: 0 <x < 84.375 mm, 0 <y < 87.1875 mm and 0 <z < 135 mm.
Based on Krouskop et al. [13], the initial elastic moduli of three tissues are taken as 20 KPa for fat, 35 KPa for parenchyma, and 100 KPa for tumor. Because these tissues may undergo large (finite) deformation, we apply the Mooney-Rivlin nonlinear elastic (hyperelastic) model to describe the constitutive law for the finite deformation. Using the initial elastic moduli we can calculate the Mooney-Rivlin material constants as: C01 = 1,333 Pa, C10 = 2,000 Pa for fat; C01 = 2333.3 Pa, C10 = 3500 Pa for parenchyma; and C01 = 6,667 Pa, C10 = 10,000 Pa for tumor. It is noted that, due to the nonlinear characteristics, the elastic modulus for each tissue change as a function of deformation.
FEM Modeling by ANSYS
ANSYS 7.0 [14] is the commercial nonlinear FEM software. We input the nodes and elements into ANSYS, and define the material models for three tissues. The applied compression with two flat-paddles is designed to simulate the clinical mammography examination. The ANSYS elastic contact model is adopted for the interaction between the breast tissue and the much more rigid paddle. The paddle's Young's modulus and Poisson's ratio are taken as 210 GPa and 0.3, respectively. During the compression process, the breast deforms. The contact area between the breast surface and the paddle increases automatically. The friction coefficient between the breast and the paddle is assumed to be 0.2. The boundary conditions are assumed that all nodes attached to thorax are constraint as Ux = Uy = 0, so that they can only move in the z direction for computational convenience. The two paddles move toward each other with a quasi-static strain rate. The maximum paddle movement is limited to be 13.5 mm (20% deformation) in the z direction.
FEM Results
To simulate the nonlinearly elastic deformation, we divide this compression process into 20 incremental steps. At each step the displacement, strain, and stress fields can be calculated. Figure 8 shows the von Mises strain and tangential Young's modulus distributions at the last step. The deformation-dependent tangential Young's modulus is defined as
Figure 8 The Strain and Tangent Young's Modulus Distribution. The von Mises strain (a) and Tangent Young's modulus (b) distribution in the layers at z = 69, 78, 87 mm are illustrated. Because the tumor is much harder than other tissues, the Tangent Young's modulus is obviously higher and the strain is lower than those at the neighoring region.
where σε and εe are the von Mises stress and strain, respectively. It is noted that, for linear elastic material, E is always a material constant. Because the material properties of skin, normal entity and tumor are all nonlinear, E should change during the process of compression. Figure 8(a) shows the von Mises strain for the sections at z = 69,78,87 mm. The strain around the thorax is quite significant due to the boundary constraint, whereas the strain close to skin is small because of the free boundary condition. In the region of tumor, it is shown that the strain is much smaller than that in the neighboring region because the tumor is much harder than other tissues. Figure 8(b) demonstrates that the tangential Young's modulus is no longer uniform even in the same tissue because its strain field is not uniform.
Conclusions
The ImageParser system has been developed to create FEM mesh models from 3-D medical images. A semi-automatic method has been proposed to detect the ROIs from the context of complex image structures. The ROIs can be meshed into cuboidal elements and segmented based on the grayscale of the voxels. It has been demonstrated that, through a 3-D CT image volume of the woman breast, the ImageParser can effectively mesh the breast into cuboidal elements, and simulate the realistic nonlinear deformation responses of the breast tissues upon compression.
Authors' contributions
LZS, GW, and MWV conceived and planned this research project. HMY and LZS designed and developed this software. TY prepared the CT image volume of the breast. TY, JW, and GW analyzed the CT images. HMY, LZS, and GW wrote the manuscript.
Acknowledgements
This work is sponsored by the University of Iowa's Iowa Informatics Initiative.
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| 15461787 | PMC524181 | CC BY | 2021-01-04 16:37:31 | no | Biomed Eng Online. 2004 Oct 1; 3:31 | utf-8 | Biomed Eng Online | 2,004 | 10.1186/1475-925X-3-31 | oa_comm |
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Ann Clin Microbiol AntimicrobAnnals of Clinical Microbiology and Antimicrobials1476-0711BioMed Central London 1476-0711-3-181545856510.1186/1476-0711-3-18ResearchUtilization of a ts-sacB selection system for the generation of a Mycobacterium avium serovar-8 specific glycopeptidolipid allelic exchange mutant Irani Vida R 1virani@mail.med.upenn.eduLee Sun-Hwa 2Sun-Hwa_Lee@hms.harvard.eduEckstein Torsten M 3torsten.eckstein@colostate.eduInamine Julia M 3julia.inamine@colostate.eduBelisle John T 3john.belisle@colostate.eduMaslow Joel N 14joel.maslow@med.va.gov1 School of Medicine, Division of Infectious Diseases, University of Pennsylvania, Philadelphia, PA 19104, USA2 Harvard Medical School, New England Regional Primate Center, Southborough, MA 01772, USA3 Mycobacterial Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins CO 80523, USA4 Section of Infectious Diseases, VA Medical Center, Philadelphia PA 19104, USA2004 30 9 2004 3 18 18 20 4 2004 30 9 2004 Copyright © 2004 Irani et al; licensee BioMed Central Ltd.2004Irani 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
Mycobacterium avium are ubiquitous environmental organisms and a cause of disseminated infection in patients with end-stage AIDS. The glycopeptidolipids (GPL) of M. avium are proposed to participate in the pathogenesis of this organism, however, establishment of a clear role for GPL in disease production has been limited by the inability to genetically manipulate M. avium.
Methods
To be able to study the role of the GPL in M. avium pathogenesis, a ts-sacB selection system, not previously used in M. avium, was employed as a means to achieve homologous recombination for the rhamnosyltransferase (rtfA) gene of a pathogenic serovar 8 strain of M. avium to prevent addition of serovar-specific sugars to rhamnose of the fatty acyl-peptide backbone of GPL. The genotype of the resultant rtfA mutant was confirmed by polymerase chain reaction and southern hybridization. Disruption in the proximal sugar of the haptenic oligosaccharide resulted in the loss of serovar specific GPL with no change in the pattern of non-serovar specific GPL moieties as shown by thin layer chromatography and gas chromatography/mass spectrometry. Complementation of wild type (wt) rtfA in trans through an integrative plasmid restored serovar-8 specific GPL expression identical to wt serovar 8 parent strain.
Results
In this study, we affirm our results that rtfA encodes an enzyme responsible for the transfer of Rha to 6d-Tal and provide evidence of a second allelic exchange mutagenesis system suitable for M. avium.
Conclusion
We report the second allelic exchange system for M. avium utilizing ts-sacB as double-negative and xylE as positive counter-selection markers, respectively. This system of allelic exchange would be especially useful for M. avium strains that demonstrate significant isoniazid (INH) resistance despite transformation with katG. Through the construction of mutants in GPL or other mycobacterial components, their roles in M. avium pathogenesis, biosynthesis, or drug resistance can be studied in a consistent manner.
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Background
Mycobacterium avium is a frequent cause of disseminated infection among patients with end-stage AIDS [9,11,19]. M. avium can also present with a similar spectrum of pulmonary and extra pulmonary syndromes as Mycobacterium tuberculosis [27] including the establishment of latent infection that can reactivate concomitant with immune suppression [13]. While significant advances have been made in deciphering the host responses against M. avium infection, there is only a rudimentary understanding of the bacterial factors involved in the pathogenesis of infection [14,22].
Numerous studies have implicated the cell wall lipids in mycobacterial pathogenesis. For M. avium, there is evidence that the glycopeptidolipids (GPL), as the dominant lipid for this species, may negatively affect host immunity [4,25]. Study of GPL in M. avium pathogenesis has been limited by a lack of suitable genetic techniques to be able to create site directed knockouts. Further, as reviewed below, there is controversy as to which portion of GPL predominates in disease production.
The GPLs are comprised of a lipopeptide (LP) core of D-phenylalanine-D-allo threonine-D-alanine-alaninol with a fatty acyl group N-linked to the phenylalanine residue and a methylated rhamnose modifying the terminal alaninol. The LP core is glycosylated at D-allo threonine with 6-deoxytalose (6dTal) to form non-specific GPL (nsGPL) and is further glycosylated at 6dTal with a haptenic oligosaccharide to yield serovar-specific GPL (ssGPL). All serovars maintain a common α-L-rhamnopyranosyl-(1→2)-6dTal [6].
Historically, the predominance of serovars 1, 4, and 8, among patients with disseminated infection [10,26] has been suggested as evidence to support a role for the oligosaccharide moiety of GPL in pathogenesis, but may conversely represent the fact that a restricted set of clones are disease producing. More direct evidence of a role of the GPL oligosaccharide in pathogenesis is provided by the study of Minami that demonstrated that heat-killed Staphylococcus aureus coated with M. avium GPL promote phagocytosis and inhibit phagolysosomal fusion in relation to serovar [17]. Other studies have, however, suggested a dominant role for the lipopeptide core in pathogenesis [5]. Significantly limiting the development of a consistent framework of the role of GPL in mycobacterial pathogenesis has been the inability to construct isogenic strains differing in GPL structure, necessitating the comparison of genetically distinct strains of differing serotypes.
To study the role of the serovar-specific oligosaccharide moiety of GPL in the pathogenesis of M. avium, an allelic exchange mutant in rtfA was created for a pathogenic serovar 8 strain to yield a strain deficient in ssGPL. Homologous recombination was performed using a novel allelic exchange vector that incorporated a temperature-sensitive mycobacterial origin of replication (ts-oriM) and sacB as counter selective markers [21] and xylE [7] as a positive selection marker. Complementation of rtfA in trans through an integrative plasmid restored serovar-8 specific GPL expression identical to wild type (wt) serovar 8 smooth opaque (SmO) parent strain. In addition to reaffirming our results for serovar 2 [15] that rtfA encodes an enzyme responsible only for the transfer of Rha to 6d-Tal to form the serovar-8 specific oligosaccharide, this study delineates a second system of allelic exchange mutagenesis for M. avium.
Methods
Bacterial strains and plasmids
Escherichia coli strain DH5α was used as the host strain for plasmid construction and propagation. Wild type and recombinant M. avium and Mycobacterium smegmatis strains were grown in Middlebrook 7H9 broth or 7H11 agar supplemented with 10% OADC (Difco Laboratories, Detroit, MI) at 37°C, except where indicated. M. smegmatis mc2155 [24] was employed as a test strain for mycobacterial shuttle vectors. M. avium 920A6 is a serovar 8 bloodstream isolate cultured from a patient with AIDS [1]. Transformation of E. coli and M. smegmatis was performed as described [23,24]. Transformation of M. avium was performed according to the protocol of Lee et al. [12]. For E. coli, selection was carried out using ampicillin at 50 μg ml-1 and kanamycin at 25 μg ml-1. For M. smegmatis and M. avium, selection was accomplished using hygromycin at 100 μg ml-1, gentamicin at 100 μg ml-1, and kanamycin at 50 μg ml-1.
Construction of allelic exchange vector pVAP39
The allelic exchange vector pVAP39 was created in a manner similar to allelic exchange vector pVAP41 [15] to include counter selection markers ts-oriM, sacB, and the hygromycin resistance gene (hyg); and positive selection marker xylE. Construction of allelic exchange vector pVAP39 is shown in Fig. 1. The 1.1 kb BamHI-XbaI fragment of pXYL4 containing the xylE gene [21] was ligated into the BamHI site of pPR27, containing a temperature-sensitive origin of replication of M. fortuitum plasmid pAL5000 and sacB [21] to create pVAP38 (10.8 kb). The 3.2 kb XbaI-XhoI fragment containing rtfA::hyg, isolated from pVAP37 [15], was blunt-ligated into pVAP38 to create pVAP39 (14.1 kb). The presence of rtfA::hyg in pVAP38 was confirmed by PCR and Southern blot analysis as described [15]. Expression of XylE was detected by applying one drop of filter-sterilized 1.1% catechol solution (1.1% catechol in 50 mM potassium phosphate buffer, pH 7.5) to individual colonies to detect a yellow color [20]. Plasmid pVAP42 was constructed by ligating the amplified wt rtfA gene with HindIII overhangs into the HindIII site of plasmid pMVGFP (kanamycin-resistant, GFP-positive, [12]). Plasmid pVAP52 was constructed by ligating the amplified wt rtfA gene with HindIII overhangs into the HindIII site of plasmid pIGFP2 (kanamycin-resistant, GFP-positive, [12]).
Figure 1 Construction of allelic exchange vector pVAP39. See Methods and Reference 15 for details.
Isolation and analysis of GPL
Colonies of wt, mutant, and complemented strains were collected from 7H10 plates. Procedures for purification of alkaline stable GPLs, and alditol acetate analyses of sugar moieties by gas chromatography/mass spectrometry (GC/MS) were performed as described by Eckstein et al [8].
Results
Selection of rtfA allelic exchange mutants of M. avium 920A6 strain
The expression of xylE was first examined for M. avium since there is minimal published data on the use of this marker in mycobacteria. After construction, pVAP38 was first electroporated into M. smegmatis strain mc2155 to assess expression in a test system. All (100%) of gentamicin-resistant colonies expressed XylE as determined by a yellow color change after application of catechol. M. avium 920A6 SmO was then transformed with pVAP39 and selected at 32°C on 7H11 medium containing 100 μg ml-1 hygromycin. Yellow colonies were easily detected, indicating that xylE represents a suitable marker for M. avium. However, only 25–40% of hygromycin-resistant colonies yielded a yellow color, indicating a high rate of spontaneous hygromycin resistance when M. avium is transformed at 32°C, with a final efficiency of transformation of 1–8 × 102 transformants per μg of DNA. These results contrasted with our earlier observations that transformation of M. avium with non-temperature sensitive plasmids yielded less than 5% of spontaneously resistant colonies and an efficiency of transformation 1.6-log higher (8 × 103 transformants per μg of DNA, [12]).
To derive an allelic exchange mutant, a representative hygromycin-resistant, XylE-positive colony of M. avium 920A6 SmO/pVAP39 was inoculated into 7H9 medium for 3 weeks at 32°C to late log phase. Growth in hygromycin-free medium allowed for spontaneous loss of plasmid DNA. Moreover, expansion in hygromycin-free medium limited the appearance of spontaneous hygromycin resistance (unpublished data). Selection for allelic exchange mutants was performed at 39°C on 7H11 medium containing 100 μg ml-1 hygromycin and 2% (w/v) sucrose to isolate single colonies. Incubation at 39°C precludes the replication of the temperature-sensitive origin of replication of pVAP39. Hygromycin-resistant, XylE-positive colonies that arose at this non-permissive temperature represented single crossover mutants or illegitimate recombinants, whereas XylE-negative colonies represented either double crossover mutants or colonies that had lost plasmid DNA and had developed spontaneous hygromycin resistance. Growth on sucrose was used as a means to eliminate strains that retained plasmid DNA.
Of >104 colonies screened, three XylE-negative colonies were identified of which only one (213R.4) colony with an SmO morphotype yielded a single 3.2 kb PCR product corresponding to the 1.9 kb rtfA gene interrupted with the 1.3 kb hyg cassette. Southern blot analysis confirmed that strain 213R.4 possessed only a chromosomal copy of rtfA::hyg (Fig 2a,2b). The remaining 2 XylE-negative colonies yielded a single 1.9 kb band corresponding to the native rtfA gene, indicating spontaneous hygromycin-resistant strains.
Figure 2 PCR and Southern hybridization of wild type 920A6 and ΔrtfA mutant, 213R.4. (A) PCR of wild type M. avium 920A-6 (lane 3) yielded a single 1.9 kb band corresponding rtfA whereas the rtfA mutant 213R.4 yielded a 3.2 kb band corresponding to rtfA with an inserted 1.3 kb hygromycin resistance gene cassette (rtfA::hyg, lane 2). Vector pVAP39 served as a positive control (lane 4). Lane 1 represents a molecular weight marker. (B) Southern blot analysis of genomic DNA from wt M. avium 920A6 and clone 213R.4 was digested with HindIII and probed for rtfA. M. avium 920A6 yielded a 11.13 kb band (lane 2) whereas clone 213R.4 (lane 1) yielded a 12.49 kb band, corresponding to the incorporation of the 1.3 kb hyg gene.
GPL analysis of serovar 8 M. avium strains by TLC and GC-MS
Total lipids were isolated from wild type and mutant strains. Alkaline stable lipids analyzed by TLC demonstrated that wt strains 920A6 SmO and 920A6 SmT expressed serovar 8 specific GPL (Fig. 3, lanes 1, 2). Strain 213R.4 was devoid of ssGPL but produced an identical pattern of nsGPL as the wt strains (Fig. 3, lane 3). To confirm that the loss of serovar 8 specific GPL resulted from the disruption of rtfA, clone 213R.4 was transformed with integrative (pVAP52) plasmid to complement rtfA in trans. Strain 233R.1 created by transformation of 213R.4 with pVAP52 and thus containing only a single copy of rtfA, demonstrated a pattern of ssGPL and nsGPL similar to wild-type, serovar 8 M. avium (Fig. 3, lane 5). Strain 277R.1 created by transformation of 213R.4 with rtfA on an episomal plasmid (pVAP42) expressed ssGPL but not nsGPL (Fig. 3. lane 4).
Figure 3 Thin layer chromatography (TLC) of alkaline-stable lipids from GPL mutants of 920A6. GPL were isolated from each strain and 100 μg of lipid was applied to each lane on a silica gel TLC plate, developed in CHCl3:CH3OH:H2O (65:35:4), and sprayed with H2SO4 in ethanol. Lane 1, 920A6 SmO; Lane 2, 920A6 SmT; Lane 3, ΔrtfA mutant 213R.4; Lane 4, 227R.1; Lane 5, 233R.1. Wild-type strains 920A6 SmT and 920A6 SmO both expressed ssGPL and nsGPL whereas 213R.4 did not express serovar-8 specific GPL (arrow). Complementation of rtfA with a single copy integrant restored ssGPL expression for 233R.1 to a pattern similar to wild-type M. avium. Strain 227R.1 complemented with rtfA on an episomal plasmid expressed ssGPL but did not express nsGPL.
Analysis of the glycosyl residues was performed by GC-MS of alditol acetate derivatives of GPL (Fig. 4). Relative to wt 920A6 SmO (Fig. 4, panel B), clone 213R.4 (Fig. 4, panel A) demonstrated loss of both the non-methylated rhamnose (Rha) of the haptenic oligosaccharide (peak 4) and the terminal glucose residue (peak 6). Clone 213R.4 however retained 3,4-O-diMe-Rha (peak 1), 3-O-Me-6dTal (peak 2), 3-O-Me-Rha (peak 3), and 6dTal (peak 5) associated with nsGPL. Individual nsGPL and ssGPL band(s) were isolated from a preparative TLC gel and each band resolved separately by TLC (Fig. 5) and analyzed by GC. Band α, absent from 213R.4, contained serovar 8 specific GPL. Bands β, γ2, γ3, and δ represented nsGPL bands demonstrating the sequential addition of methyl groups to Rha attached to the alaninol of the nsGPL, and 6dTal to generate serovar 8 specific GPL (band α). These data further confirm our previous results for serovar 2 [15] that rtfA encodes for the transfer of Rha to 6dTal as the proximal sugar in the oligosaccharide moiety of GPL and does not encode for the transfer of Rha to the alaninol of the GPL lipopeptide core.
Figure 4 Gas chromatography of alditol derivatives of GPL of 920A6 SmO and ΔrtfA mutant 213R.4. Panel A, 213R.4; Panel B, 920A6 SmO, Panel C rhamnose (Rha) standard. Peaks 1, 2, 3, 4, 5 and 6 represent 3,4-O-dimethylrhamnose (diMe-Rha), 3-O-methyl-6dtalose (3-O-Me-6dTal), 3-O-methylrhamnose (Me-Rha), rhamnose (Rha), 6dTal, and glucose, respectively. The peak at 18.5 min. in all the panels represents the Rha standard. Peaks with asterisks (*) do not represent pattern associated with alditol acetates of known sugars.
Figure 5 TLC and GC analyses of individual GPL bands (α, β, γ, γ2, γ3, δ) of wt M. avium 920A6, confirms the role of rtfA in ssGPL biosynthesis. GPL from 920A6 SmO was resolved by preparative TLC and individually resolved by analytical TLC. Each band was collected from the plate, and the lipids analyzed by GC/MS. Bands α represented serovar-8 specific GPL, bands β, γ (mix of γ2, γ3), and δ represented nsGPLs. GPL from the ΔrtfA mutant, 213R.4 was analyzed similarly and yielded identical nsGPL (data not shown).
Discussion
Here we report on the generation of allelic exchange mutants using a double negative-selection system utilizing a temperature sensitive origin of replication of plasmid pAL5000 and the Bacillus subtilis sacB gene. This vector (pPR27) has been used successfully to generate homologous recombinants of M. tuberculosis [21]. The inclusion of the reporter gene xylE [7], that encodes for catechol 2,3-dioxygenase and converts catechol into 2-hydroxymuconic semialdehyde [20], provided identification of true transformants and allowed for differentiation of putative double crossover mutants (XylE-negative) from single crossover mutants or illegitimate recombinants (XylE-positive).
We observed a high background of hygromycin-resistant, sucrose-resistant, XylE-positive colonies after selection at 39°C on sucrose-containing media suggesting a high frequency of a single crossover or illegitimate recombination. The high number of XylE-positive clones either represented a high degree of spontaneous mutation in sacB or the inability of this gene to provide efficient counter selection as a single copy. The latter was consistent with our observation that katG expressed as a single copy-integrant did not confer INH-susceptibility to M. avium sufficient to serve as a counter selection marker [15]. Additionally, we observed a high degree of spontaneous hygromycin resistance at 32°C. Although poorly efficient, this system of allelic exchange would be useful for strains that exhibit significant isoniazid resistance despite transformation with katG, as we have observed with the smooth transparent (SmT) morphotype of 920A6 (unpublished data). In this system, for INH-resistant strains, it may be prudent to perform selections as a two-step process, i.e., growth in broth at 39°C to eliminate plasmid replication followed by selection in solid medium containing hygromycin to increase the yield of double crossover mutants in relation to spontaneous hygromycin-resistant strains. Although sacB is a useful marker for M. tuberculosis, it appears to be minimally useful as a counter-selection marker for allelic exchange in M. avium. Also, this is the first reported instance of using xylE as a marker for allelic exchange in M. avium.
The glycopeptidolipids represent the most abundant cell wall component of M. avium. Studies have suggested a role for serovar-specific GPL in the pathogenesis of M. avium infection as highly antigenic molecules [16] affecting host immune function. However, these data have relied on comparisons of strains representing different serovars [18] or have used purified and/or chemically modified GPL and GPL components [2,3,5,25]. In this study, we disrupted the rtfA gene via homologous recombination to block the addition of rhamnose as the proximal sugar common to ssGPLs resulting in construction of isogenic mutants expressing only non-specific GPL. Complementation of the rtfA gene as a single copy integrant in trans restored ssGPL synthesis and maintained nsGPL synthesis. Complementation of the ssGPL-null mutant with rtfA on an episomal plasmid, however yielded only serovar-8 specific GPL. In the latter case, all nsGPL components (bands β, γ2, γ3, δ) were utilized as substrates for generation of ssGPL and thus were lost due to over-expression of rtfA. Also, since we do not observe any serovar-1 ssGPL (6dTal-Rha) on TLC or GC analyses, this would suggest that the serovar-8 specific GPL disaccharide Rha-Gluc was generated prior to its addition to 6dTal for the generation of ssGPL.
Conclusion
Insertion mutagenesis via the ts-sacB double negative and xylE counter-selection system was reported for M. avium and we were able to construct isogenic mutants devoid of serovar-8 GPL. Due to limitations of various genetic manipulation techniques, this is the second only reported allelic exchange system for M. avium. With a few experimental modifications, this system of allelic exchange would be especially useful for M. avium strains that demonstrate high levels of INH drug resistance. Finally, through the construction of mutants in GPL (or any other cellular component) synthesis, the role of M. avium GPLs (and other components) in host-pathogen interaction, immunogenesis, and other qualities such as drug resistance can be determined.
List of abbreviations used
GPL: glycopeptidolipid
6-d Tal: 6-deoxytalose
nsGPL: non-specific glyopeptidolipid
ssGPL: serovar-specific glycopeptidolipid
rtfA: rhamnosyltransferase
wt: wild type
LP: lipopeptide
SmO: smooth opaque
Rha: rhamnose
Hyg: hygromycin
GC/MS: gas chromatography/mass spectrometry
PCR: polymerase chain reaction
TLC: thin-layer chromatography
3,4-O-diMe-Rha: 3,4-O-dimethyl-Rhamnose
3-O-Me-6dTal: 3-O-Methyl-6-deoxytalose
3-O-Me-Rha: 3-O-Methyl-Rhamnose
SmT: smooth transparent
INH: isoniazid hydrazide
6dTal-Rha: 6-deoxytalose-rhamnose
Rha-Gluc: rhamnose-glucose
μg ml-1: microgram per milliliter
Authors' contributions
VRI: Writing and submission of this manuscript, molecular genetic analysis of the wt, rtfA mutant, and complemented strains, generation of pVAP52 and complemented rtfA mutant as well as selection techniques of the rtfA mutant.
SHL: Generation and initial characterization of plasmids and the serovar 8 rtfA mutant.
TME, JMI, and JTB: Isolation and analysis of GPL, critical reading of the manuscript, and assistance in experimental techniques and study design.
JNM: Principal Investigator in whose lab this research was conducted.
Acknowledgements
W. Jacobs, Jr., S. Bardarov, V. Vissa, and C. Guilhot are acknowledged for their gift of plasmids and strains. Thomas Glaze and Ansel Hsiao are gratefully acknowledged for technical assistance. Support for this study came from Merit Review and VISN 4 CPPF Grants from the Veterans Affairs to JNM, SHL and RO1 AI41925 (NIH/NIAID, M. avium), RO1 AI51283 (NIH/NIAID, M. paratuberculosis) to TME, JMI, and JTB.
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| 15458565 | PMC524182 | CC BY | 2021-01-04 16:38:17 | no | Ann Clin Microbiol Antimicrob. 2004 Sep 30; 3:18 | utf-8 | Ann Clin Microbiol Antimicrob | 2,004 | 10.1186/1476-0711-3-18 | oa_comm |
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Ann Clin Microbiol AntimicrobAnnals of Clinical Microbiology and Antimicrobials1476-0711BioMed Central London 1476-0711-3-181545856510.1186/1476-0711-3-18ResearchUtilization of a ts-sacB selection system for the generation of a Mycobacterium avium serovar-8 specific glycopeptidolipid allelic exchange mutant Irani Vida R 1virani@mail.med.upenn.eduLee Sun-Hwa 2Sun-Hwa_Lee@hms.harvard.eduEckstein Torsten M 3torsten.eckstein@colostate.eduInamine Julia M 3julia.inamine@colostate.eduBelisle John T 3john.belisle@colostate.eduMaslow Joel N 14joel.maslow@med.va.gov1 School of Medicine, Division of Infectious Diseases, University of Pennsylvania, Philadelphia, PA 19104, USA2 Harvard Medical School, New England Regional Primate Center, Southborough, MA 01772, USA3 Mycobacterial Research Laboratories, Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins CO 80523, USA4 Section of Infectious Diseases, VA Medical Center, Philadelphia PA 19104, USA2004 30 9 2004 3 18 18 20 4 2004 30 9 2004 Copyright © 2004 Irani et al; licensee BioMed Central Ltd.2004Irani 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
Mycobacterium avium are ubiquitous environmental organisms and a cause of disseminated infection in patients with end-stage AIDS. The glycopeptidolipids (GPL) of M. avium are proposed to participate in the pathogenesis of this organism, however, establishment of a clear role for GPL in disease production has been limited by the inability to genetically manipulate M. avium.
Methods
To be able to study the role of the GPL in M. avium pathogenesis, a ts-sacB selection system, not previously used in M. avium, was employed as a means to achieve homologous recombination for the rhamnosyltransferase (rtfA) gene of a pathogenic serovar 8 strain of M. avium to prevent addition of serovar-specific sugars to rhamnose of the fatty acyl-peptide backbone of GPL. The genotype of the resultant rtfA mutant was confirmed by polymerase chain reaction and southern hybridization. Disruption in the proximal sugar of the haptenic oligosaccharide resulted in the loss of serovar specific GPL with no change in the pattern of non-serovar specific GPL moieties as shown by thin layer chromatography and gas chromatography/mass spectrometry. Complementation of wild type (wt) rtfA in trans through an integrative plasmid restored serovar-8 specific GPL expression identical to wt serovar 8 parent strain.
Results
In this study, we affirm our results that rtfA encodes an enzyme responsible for the transfer of Rha to 6d-Tal and provide evidence of a second allelic exchange mutagenesis system suitable for M. avium.
Conclusion
We report the second allelic exchange system for M. avium utilizing ts-sacB as double-negative and xylE as positive counter-selection markers, respectively. This system of allelic exchange would be especially useful for M. avium strains that demonstrate significant isoniazid (INH) resistance despite transformation with katG. Through the construction of mutants in GPL or other mycobacterial components, their roles in M. avium pathogenesis, biosynthesis, or drug resistance can be studied in a consistent manner.
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Background
Mycobacterium avium is a frequent cause of disseminated infection among patients with end-stage AIDS [9,11,19]. M. avium can also present with a similar spectrum of pulmonary and extra pulmonary syndromes as Mycobacterium tuberculosis [27] including the establishment of latent infection that can reactivate concomitant with immune suppression [13]. While significant advances have been made in deciphering the host responses against M. avium infection, there is only a rudimentary understanding of the bacterial factors involved in the pathogenesis of infection [14,22].
Numerous studies have implicated the cell wall lipids in mycobacterial pathogenesis. For M. avium, there is evidence that the glycopeptidolipids (GPL), as the dominant lipid for this species, may negatively affect host immunity [4,25]. Study of GPL in M. avium pathogenesis has been limited by a lack of suitable genetic techniques to be able to create site directed knockouts. Further, as reviewed below, there is controversy as to which portion of GPL predominates in disease production.
The GPLs are comprised of a lipopeptide (LP) core of D-phenylalanine-D-allo threonine-D-alanine-alaninol with a fatty acyl group N-linked to the phenylalanine residue and a methylated rhamnose modifying the terminal alaninol. The LP core is glycosylated at D-allo threonine with 6-deoxytalose (6dTal) to form non-specific GPL (nsGPL) and is further glycosylated at 6dTal with a haptenic oligosaccharide to yield serovar-specific GPL (ssGPL). All serovars maintain a common α-L-rhamnopyranosyl-(1→2)-6dTal [6].
Historically, the predominance of serovars 1, 4, and 8, among patients with disseminated infection [10,26] has been suggested as evidence to support a role for the oligosaccharide moiety of GPL in pathogenesis, but may conversely represent the fact that a restricted set of clones are disease producing. More direct evidence of a role of the GPL oligosaccharide in pathogenesis is provided by the study of Minami that demonstrated that heat-killed Staphylococcus aureus coated with M. avium GPL promote phagocytosis and inhibit phagolysosomal fusion in relation to serovar [17]. Other studies have, however, suggested a dominant role for the lipopeptide core in pathogenesis [5]. Significantly limiting the development of a consistent framework of the role of GPL in mycobacterial pathogenesis has been the inability to construct isogenic strains differing in GPL structure, necessitating the comparison of genetically distinct strains of differing serotypes.
To study the role of the serovar-specific oligosaccharide moiety of GPL in the pathogenesis of M. avium, an allelic exchange mutant in rtfA was created for a pathogenic serovar 8 strain to yield a strain deficient in ssGPL. Homologous recombination was performed using a novel allelic exchange vector that incorporated a temperature-sensitive mycobacterial origin of replication (ts-oriM) and sacB as counter selective markers [21] and xylE [7] as a positive selection marker. Complementation of rtfA in trans through an integrative plasmid restored serovar-8 specific GPL expression identical to wild type (wt) serovar 8 smooth opaque (SmO) parent strain. In addition to reaffirming our results for serovar 2 [15] that rtfA encodes an enzyme responsible only for the transfer of Rha to 6d-Tal to form the serovar-8 specific oligosaccharide, this study delineates a second system of allelic exchange mutagenesis for M. avium.
Methods
Bacterial strains and plasmids
Escherichia coli strain DH5α was used as the host strain for plasmid construction and propagation. Wild type and recombinant M. avium and Mycobacterium smegmatis strains were grown in Middlebrook 7H9 broth or 7H11 agar supplemented with 10% OADC (Difco Laboratories, Detroit, MI) at 37°C, except where indicated. M. smegmatis mc2155 [24] was employed as a test strain for mycobacterial shuttle vectors. M. avium 920A6 is a serovar 8 bloodstream isolate cultured from a patient with AIDS [1]. Transformation of E. coli and M. smegmatis was performed as described [23,24]. Transformation of M. avium was performed according to the protocol of Lee et al. [12]. For E. coli, selection was carried out using ampicillin at 50 μg ml-1 and kanamycin at 25 μg ml-1. For M. smegmatis and M. avium, selection was accomplished using hygromycin at 100 μg ml-1, gentamicin at 100 μg ml-1, and kanamycin at 50 μg ml-1.
Construction of allelic exchange vector pVAP39
The allelic exchange vector pVAP39 was created in a manner similar to allelic exchange vector pVAP41 [15] to include counter selection markers ts-oriM, sacB, and the hygromycin resistance gene (hyg); and positive selection marker xylE. Construction of allelic exchange vector pVAP39 is shown in Fig. 1. The 1.1 kb BamHI-XbaI fragment of pXYL4 containing the xylE gene [21] was ligated into the BamHI site of pPR27, containing a temperature-sensitive origin of replication of M. fortuitum plasmid pAL5000 and sacB [21] to create pVAP38 (10.8 kb). The 3.2 kb XbaI-XhoI fragment containing rtfA::hyg, isolated from pVAP37 [15], was blunt-ligated into pVAP38 to create pVAP39 (14.1 kb). The presence of rtfA::hyg in pVAP38 was confirmed by PCR and Southern blot analysis as described [15]. Expression of XylE was detected by applying one drop of filter-sterilized 1.1% catechol solution (1.1% catechol in 50 mM potassium phosphate buffer, pH 7.5) to individual colonies to detect a yellow color [20]. Plasmid pVAP42 was constructed by ligating the amplified wt rtfA gene with HindIII overhangs into the HindIII site of plasmid pMVGFP (kanamycin-resistant, GFP-positive, [12]). Plasmid pVAP52 was constructed by ligating the amplified wt rtfA gene with HindIII overhangs into the HindIII site of plasmid pIGFP2 (kanamycin-resistant, GFP-positive, [12]).
Figure 1 Construction of allelic exchange vector pVAP39. See Methods and Reference 15 for details.
Isolation and analysis of GPL
Colonies of wt, mutant, and complemented strains were collected from 7H10 plates. Procedures for purification of alkaline stable GPLs, and alditol acetate analyses of sugar moieties by gas chromatography/mass spectrometry (GC/MS) were performed as described by Eckstein et al [8].
Results
Selection of rtfA allelic exchange mutants of M. avium 920A6 strain
The expression of xylE was first examined for M. avium since there is minimal published data on the use of this marker in mycobacteria. After construction, pVAP38 was first electroporated into M. smegmatis strain mc2155 to assess expression in a test system. All (100%) of gentamicin-resistant colonies expressed XylE as determined by a yellow color change after application of catechol. M. avium 920A6 SmO was then transformed with pVAP39 and selected at 32°C on 7H11 medium containing 100 μg ml-1 hygromycin. Yellow colonies were easily detected, indicating that xylE represents a suitable marker for M. avium. However, only 25–40% of hygromycin-resistant colonies yielded a yellow color, indicating a high rate of spontaneous hygromycin resistance when M. avium is transformed at 32°C, with a final efficiency of transformation of 1–8 × 102 transformants per μg of DNA. These results contrasted with our earlier observations that transformation of M. avium with non-temperature sensitive plasmids yielded less than 5% of spontaneously resistant colonies and an efficiency of transformation 1.6-log higher (8 × 103 transformants per μg of DNA, [12]).
To derive an allelic exchange mutant, a representative hygromycin-resistant, XylE-positive colony of M. avium 920A6 SmO/pVAP39 was inoculated into 7H9 medium for 3 weeks at 32°C to late log phase. Growth in hygromycin-free medium allowed for spontaneous loss of plasmid DNA. Moreover, expansion in hygromycin-free medium limited the appearance of spontaneous hygromycin resistance (unpublished data). Selection for allelic exchange mutants was performed at 39°C on 7H11 medium containing 100 μg ml-1 hygromycin and 2% (w/v) sucrose to isolate single colonies. Incubation at 39°C precludes the replication of the temperature-sensitive origin of replication of pVAP39. Hygromycin-resistant, XylE-positive colonies that arose at this non-permissive temperature represented single crossover mutants or illegitimate recombinants, whereas XylE-negative colonies represented either double crossover mutants or colonies that had lost plasmid DNA and had developed spontaneous hygromycin resistance. Growth on sucrose was used as a means to eliminate strains that retained plasmid DNA.
Of >104 colonies screened, three XylE-negative colonies were identified of which only one (213R.4) colony with an SmO morphotype yielded a single 3.2 kb PCR product corresponding to the 1.9 kb rtfA gene interrupted with the 1.3 kb hyg cassette. Southern blot analysis confirmed that strain 213R.4 possessed only a chromosomal copy of rtfA::hyg (Fig 2a,2b). The remaining 2 XylE-negative colonies yielded a single 1.9 kb band corresponding to the native rtfA gene, indicating spontaneous hygromycin-resistant strains.
Figure 2 PCR and Southern hybridization of wild type 920A6 and ΔrtfA mutant, 213R.4. (A) PCR of wild type M. avium 920A-6 (lane 3) yielded a single 1.9 kb band corresponding rtfA whereas the rtfA mutant 213R.4 yielded a 3.2 kb band corresponding to rtfA with an inserted 1.3 kb hygromycin resistance gene cassette (rtfA::hyg, lane 2). Vector pVAP39 served as a positive control (lane 4). Lane 1 represents a molecular weight marker. (B) Southern blot analysis of genomic DNA from wt M. avium 920A6 and clone 213R.4 was digested with HindIII and probed for rtfA. M. avium 920A6 yielded a 11.13 kb band (lane 2) whereas clone 213R.4 (lane 1) yielded a 12.49 kb band, corresponding to the incorporation of the 1.3 kb hyg gene.
GPL analysis of serovar 8 M. avium strains by TLC and GC-MS
Total lipids were isolated from wild type and mutant strains. Alkaline stable lipids analyzed by TLC demonstrated that wt strains 920A6 SmO and 920A6 SmT expressed serovar 8 specific GPL (Fig. 3, lanes 1, 2). Strain 213R.4 was devoid of ssGPL but produced an identical pattern of nsGPL as the wt strains (Fig. 3, lane 3). To confirm that the loss of serovar 8 specific GPL resulted from the disruption of rtfA, clone 213R.4 was transformed with integrative (pVAP52) plasmid to complement rtfA in trans. Strain 233R.1 created by transformation of 213R.4 with pVAP52 and thus containing only a single copy of rtfA, demonstrated a pattern of ssGPL and nsGPL similar to wild-type, serovar 8 M. avium (Fig. 3, lane 5). Strain 277R.1 created by transformation of 213R.4 with rtfA on an episomal plasmid (pVAP42) expressed ssGPL but not nsGPL (Fig. 3. lane 4).
Figure 3 Thin layer chromatography (TLC) of alkaline-stable lipids from GPL mutants of 920A6. GPL were isolated from each strain and 100 μg of lipid was applied to each lane on a silica gel TLC plate, developed in CHCl3:CH3OH:H2O (65:35:4), and sprayed with H2SO4 in ethanol. Lane 1, 920A6 SmO; Lane 2, 920A6 SmT; Lane 3, ΔrtfA mutant 213R.4; Lane 4, 227R.1; Lane 5, 233R.1. Wild-type strains 920A6 SmT and 920A6 SmO both expressed ssGPL and nsGPL whereas 213R.4 did not express serovar-8 specific GPL (arrow). Complementation of rtfA with a single copy integrant restored ssGPL expression for 233R.1 to a pattern similar to wild-type M. avium. Strain 227R.1 complemented with rtfA on an episomal plasmid expressed ssGPL but did not express nsGPL.
Analysis of the glycosyl residues was performed by GC-MS of alditol acetate derivatives of GPL (Fig. 4). Relative to wt 920A6 SmO (Fig. 4, panel B), clone 213R.4 (Fig. 4, panel A) demonstrated loss of both the non-methylated rhamnose (Rha) of the haptenic oligosaccharide (peak 4) and the terminal glucose residue (peak 6). Clone 213R.4 however retained 3,4-O-diMe-Rha (peak 1), 3-O-Me-6dTal (peak 2), 3-O-Me-Rha (peak 3), and 6dTal (peak 5) associated with nsGPL. Individual nsGPL and ssGPL band(s) were isolated from a preparative TLC gel and each band resolved separately by TLC (Fig. 5) and analyzed by GC. Band α, absent from 213R.4, contained serovar 8 specific GPL. Bands β, γ2, γ3, and δ represented nsGPL bands demonstrating the sequential addition of methyl groups to Rha attached to the alaninol of the nsGPL, and 6dTal to generate serovar 8 specific GPL (band α). These data further confirm our previous results for serovar 2 [15] that rtfA encodes for the transfer of Rha to 6dTal as the proximal sugar in the oligosaccharide moiety of GPL and does not encode for the transfer of Rha to the alaninol of the GPL lipopeptide core.
Figure 4 Gas chromatography of alditol derivatives of GPL of 920A6 SmO and ΔrtfA mutant 213R.4. Panel A, 213R.4; Panel B, 920A6 SmO, Panel C rhamnose (Rha) standard. Peaks 1, 2, 3, 4, 5 and 6 represent 3,4-O-dimethylrhamnose (diMe-Rha), 3-O-methyl-6dtalose (3-O-Me-6dTal), 3-O-methylrhamnose (Me-Rha), rhamnose (Rha), 6dTal, and glucose, respectively. The peak at 18.5 min. in all the panels represents the Rha standard. Peaks with asterisks (*) do not represent pattern associated with alditol acetates of known sugars.
Figure 5 TLC and GC analyses of individual GPL bands (α, β, γ, γ2, γ3, δ) of wt M. avium 920A6, confirms the role of rtfA in ssGPL biosynthesis. GPL from 920A6 SmO was resolved by preparative TLC and individually resolved by analytical TLC. Each band was collected from the plate, and the lipids analyzed by GC/MS. Bands α represented serovar-8 specific GPL, bands β, γ (mix of γ2, γ3), and δ represented nsGPLs. GPL from the ΔrtfA mutant, 213R.4 was analyzed similarly and yielded identical nsGPL (data not shown).
Discussion
Here we report on the generation of allelic exchange mutants using a double negative-selection system utilizing a temperature sensitive origin of replication of plasmid pAL5000 and the Bacillus subtilis sacB gene. This vector (pPR27) has been used successfully to generate homologous recombinants of M. tuberculosis [21]. The inclusion of the reporter gene xylE [7], that encodes for catechol 2,3-dioxygenase and converts catechol into 2-hydroxymuconic semialdehyde [20], provided identification of true transformants and allowed for differentiation of putative double crossover mutants (XylE-negative) from single crossover mutants or illegitimate recombinants (XylE-positive).
We observed a high background of hygromycin-resistant, sucrose-resistant, XylE-positive colonies after selection at 39°C on sucrose-containing media suggesting a high frequency of a single crossover or illegitimate recombination. The high number of XylE-positive clones either represented a high degree of spontaneous mutation in sacB or the inability of this gene to provide efficient counter selection as a single copy. The latter was consistent with our observation that katG expressed as a single copy-integrant did not confer INH-susceptibility to M. avium sufficient to serve as a counter selection marker [15]. Additionally, we observed a high degree of spontaneous hygromycin resistance at 32°C. Although poorly efficient, this system of allelic exchange would be useful for strains that exhibit significant isoniazid resistance despite transformation with katG, as we have observed with the smooth transparent (SmT) morphotype of 920A6 (unpublished data). In this system, for INH-resistant strains, it may be prudent to perform selections as a two-step process, i.e., growth in broth at 39°C to eliminate plasmid replication followed by selection in solid medium containing hygromycin to increase the yield of double crossover mutants in relation to spontaneous hygromycin-resistant strains. Although sacB is a useful marker for M. tuberculosis, it appears to be minimally useful as a counter-selection marker for allelic exchange in M. avium. Also, this is the first reported instance of using xylE as a marker for allelic exchange in M. avium.
The glycopeptidolipids represent the most abundant cell wall component of M. avium. Studies have suggested a role for serovar-specific GPL in the pathogenesis of M. avium infection as highly antigenic molecules [16] affecting host immune function. However, these data have relied on comparisons of strains representing different serovars [18] or have used purified and/or chemically modified GPL and GPL components [2,3,5,25]. In this study, we disrupted the rtfA gene via homologous recombination to block the addition of rhamnose as the proximal sugar common to ssGPLs resulting in construction of isogenic mutants expressing only non-specific GPL. Complementation of the rtfA gene as a single copy integrant in trans restored ssGPL synthesis and maintained nsGPL synthesis. Complementation of the ssGPL-null mutant with rtfA on an episomal plasmid, however yielded only serovar-8 specific GPL. In the latter case, all nsGPL components (bands β, γ2, γ3, δ) were utilized as substrates for generation of ssGPL and thus were lost due to over-expression of rtfA. Also, since we do not observe any serovar-1 ssGPL (6dTal-Rha) on TLC or GC analyses, this would suggest that the serovar-8 specific GPL disaccharide Rha-Gluc was generated prior to its addition to 6dTal for the generation of ssGPL.
Conclusion
Insertion mutagenesis via the ts-sacB double negative and xylE counter-selection system was reported for M. avium and we were able to construct isogenic mutants devoid of serovar-8 GPL. Due to limitations of various genetic manipulation techniques, this is the second only reported allelic exchange system for M. avium. With a few experimental modifications, this system of allelic exchange would be especially useful for M. avium strains that demonstrate high levels of INH drug resistance. Finally, through the construction of mutants in GPL (or any other cellular component) synthesis, the role of M. avium GPLs (and other components) in host-pathogen interaction, immunogenesis, and other qualities such as drug resistance can be determined.
List of abbreviations used
GPL: glycopeptidolipid
6-d Tal: 6-deoxytalose
nsGPL: non-specific glyopeptidolipid
ssGPL: serovar-specific glycopeptidolipid
rtfA: rhamnosyltransferase
wt: wild type
LP: lipopeptide
SmO: smooth opaque
Rha: rhamnose
Hyg: hygromycin
GC/MS: gas chromatography/mass spectrometry
PCR: polymerase chain reaction
TLC: thin-layer chromatography
3,4-O-diMe-Rha: 3,4-O-dimethyl-Rhamnose
3-O-Me-6dTal: 3-O-Methyl-6-deoxytalose
3-O-Me-Rha: 3-O-Methyl-Rhamnose
SmT: smooth transparent
INH: isoniazid hydrazide
6dTal-Rha: 6-deoxytalose-rhamnose
Rha-Gluc: rhamnose-glucose
μg ml-1: microgram per milliliter
Authors' contributions
VRI: Writing and submission of this manuscript, molecular genetic analysis of the wt, rtfA mutant, and complemented strains, generation of pVAP52 and complemented rtfA mutant as well as selection techniques of the rtfA mutant.
SHL: Generation and initial characterization of plasmids and the serovar 8 rtfA mutant.
TME, JMI, and JTB: Isolation and analysis of GPL, critical reading of the manuscript, and assistance in experimental techniques and study design.
JNM: Principal Investigator in whose lab this research was conducted.
Acknowledgements
W. Jacobs, Jr., S. Bardarov, V. Vissa, and C. Guilhot are acknowledged for their gift of plasmids and strains. Thomas Glaze and Ansel Hsiao are gratefully acknowledged for technical assistance. Support for this study came from Merit Review and VISN 4 CPPF Grants from the Veterans Affairs to JNM, SHL and RO1 AI41925 (NIH/NIAID, M. avium), RO1 AI51283 (NIH/NIAID, M. paratuberculosis) to TME, JMI, and JTB.
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| 15462675 | PMC524183 | CC BY | 2021-01-04 16:38:17 | no | Ann Clin Microbiol Antimicrob. 2004 Oct 5; 3:20 | latin-1 | Ann Clin Microbiol Antimicrob | 2,004 | 10.1186/1476-0711-3-20 | oa_comm |
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Int J Health GeogrInternational Journal of Health Geographics1476-072XBioMed Central London 1476-072X-3-211545651410.1186/1476-072X-3-21ResearchDistance, rurality and the need for care: access to health services in South West England Jordan Hannah 1h.c.jordan@soton.ac.ukRoderick Paul 1p.j.roderick@soton.ac.ukMartin David 2d.j.martin@soton.ac.ukBarnett Sarah 3s.barnett@ich.ucl.ac.uk1 Health Care Research Unit, CCS Division, School of Medicine, University of Southampton, UK2 School of Geography, University of Southampton, UK3 International Perinatal Care Unit, Institute of Child Health, London, UK2004 29 9 2004 3 21 21 31 8 2004 29 9 2004 Copyright © 2004 Jordan et al; licensee BioMed Central Ltd.2004Jordan 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 explores the geographical accessibility of health services in urban and rural areas of the South West of England, comparing two measures of geographical access and characterising the areas most remote from hospitals.
Straight-line distance and drive-time to the nearest general practice (GP) and acute hospital (DGH) were calculated for postcodes and aggregated to 1991 Census wards. The correlation between the two measures was used to identify wards where straight-line distance was not an accurate predictor of drive-time. Wards over 25 km from a DGH were classified as 'remote', and characterised in terms of rurality, deprivation, age structure and health status of the population.
Results
The access measures were highly correlated (r2>0.93). The greatest differences were found in coastal and rural wards of the far South West. Median straight-line distance to GPs was 1 km (IQR = 0.6–2 km) and to DGHs, 12 km (IQR = 5–19 km). Deprivation and rates of premature limiting long term illness were raised in areas most distant from hospitals, but there was no evidence of higher premature mortality rates. Half of the wards remote from a DGH were not classed as rural by the Office for National Statistics. Almost a quarter of households in the wards furthest from hospitals had no car, and the proportion of households with access to two or more cars fell in the most remote areas.
Conclusion
Drive-time is a more accurate measure of access for peripheral and rural areas. Geographical access to health services, especially GPs, is good, but remoteness affects both rural and urban areas: studies concentrating purely on rural areas may underestimate geographical barriers to accessing health care. A sizeable minority of households still had no car in 1991, and few had more than one car, particularly in areas very close to and very distant from hospitals. Better measures of geographical access, which integrate public and private transport availability with distance and travel time, are required if an accurate reflection of the experience those without their own transport is to be obtained.
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Background
The UK National Health Service has always aimed to provide health care for all. Although the importance of "fair access for all" (independent of the ability to pay, age, sex or area of residence) has been highlighted in recent policy documents [1], the meaning of 'fair access' is still debated [2]. Although there will always be variations in geographical access to health services, the extent of such variations and the relationship between distance to health services and the need for health care is unclear. If policy makers are to address inequities of access, more understanding is needed both of appropriate methods for measuring access and of the relationship between access to health services and health.
Although 'fair access' can be characterised simply as 'providing the right service at the right time in the right place'[3], it is a complex concept covering the provision of services, the knowledge and opportunity to use them, and the measurement of need [4]. In the UK mergers of hospital trusts have highlighted tensions between the perceived safety, effectiveness and efficiency of larger specialist centres and the demand for more geographically accessible local care [5,6], revealing the lack of evidence on which to base decisions [7]. Geographical access – the distance which must be travelled in order to use health services – is one aspect of access which is often overlooked [2], but which presents barriers of cost, time and inconvenience.
Although there is some evidence that increasing distance from health services inhibits the use of primary [8] and secondary care [9], and that it is associated with a range of poor health outcomes, from higher than expected numbers of deaths from asthma to lower than expected five year survival from cancer [10,11], few studies have attempted to quantify or set thresholds of poor access [12,13]. Furthermore, measures of geographical access can be difficult to compare. Rurality has often been used as a proxy for inaccessibility [14], as have dichotomous categorisations such as the presence or absence of a service provider in an area [15,8]. More complex measurements such as the straight line distance between populations (i.e demand points) and health service providers [16,17], or 'network distances' (which can include both road distance and travel time) [8] have added complexity, but the relationship between these measures is not clear.
One assumption which is commonly made is that geographical inaccessibility of health services is essentially a rural problem, but there is little evidence demonstrating the differences in accessibility between rural and other areas. In any area, the greatest disadvantage is likely to be experienced by individuals without access to a car (including members of one-car households without daytime access). With the declining availability of public transport, it is likely that a private car is the only convenient way to travel in rural Britain [18]. Although car ownership is relatively high in rural areas, rates for the poor, the elderly and for women are far lower than average: the 2001 Census reports that more than two thirds of single-pensioner households, many of which comprise single women, do not have access to a car. Distance may therefore be a further burden on groups with a particularly high need for health care, raising issues of inequity. Furthermore, if geographical access to health services is a problem for some groups outside of traditional rural areas, then rural policies alone will not tackle the problem.
In this paper, we aim to determine the geographical accessibility of health services, and the demographic and health related factors associated with it. We compare two measures of geographical access: straight-line distance and modelled drive-time along the road network to primary and secondary care throughout South West England. We investigate whether the most geographically inaccessible populations are in rural areas, describe the relationship between geographical access to hospital and population health, and investigate whether the populations furthest from health services have a greater need for health care due to age or deprivation.
The study area is the former South West Region, comprising the counties of Avon, Cornwall and the Isles of Scilly, Devon, Dorset, Gloucestershire, Hampshire, the Isle of Wight, Somerset and Wiltshire. As defined in 1991 this area has a population of about 6 million, with a low proportion from ethnic minorities, and a higher than average proportion living in rural areas.
Results
Correlation between the access measures
The straight-line and drive-time measures were highly correlated for both GP and hospital services (figure 1). Areas where residuals from the regression analysis of straight-line distance and drive-time to DGHs are more than two standard deviations from the norm were concentrated in coastal and rural wards of the far South West. Areas where residuals are negative indicate faster than expected drive times, wheras positive residuals indicate that drive time is slower than predicted by straight line distances (figure 2). The analysis was repeated, excluding wards along the boundary between the study area and neighbouring counties to check for edge-effects, but there was no difference in results.
Figure 1 Correlation between straight line and drive-time measures to GP and hospital services
Figure 2 Standardised residuals from the regression of drive time and straight-line distance to hospitals
Distances to health services
Distances to GPs were low, with a median distance of just 1 km to the closest practice (IQR 0.6 – 2.2). The calculation was repeated excluding branch surgeries (which tend to have limited opening hours), but this made little difference to the outcome, with a median distance to a main surgery of just 1.2 km. 95% of wards (98% of the population) were under 4.4 km, or 6.3 minutes, from their closest GP. The maximum distance to a GP was just 9.4 km (13.7 minutes). The median distance to a DGH was just less than 12 km (IQR 5.4 – 19.0), with a maximum of 50 km, corresponding to an estimated 13 and 48 minutes drive-time (table 1).
Table 1 Access to DGHs and GPs
25th centile Popn (%)* Median Popn (%) 75th centile Popn (%) 95th centile Popn (%) Maximum
Straight line (km) DGH 5.4 2.40 (39.3) 11.6 3.97 (65.1) 19.0 5.15 (84.3) 29.0 5.92 (97.1) 50.1
GP surgery 0.6 2.24 (36.8) 1.0 4.17 (68.3) 2.2 5.39 (88.4) 4.4 5.96 (97.7) 9.4
Drive time ('minutes') DGH 7.1 2.38 (38.9) 13.4 3.93 (64.4) 20.5 5.17 (84.7) 31.6 5.93 (97.2) 48.3
GP surgery 1.0 2.19 (35.9) 1.7 4.00 (65.5) 3.4 5.28 (86.5) 6.3 5.89 (96.5) 13.7
*Population in millions (percent of the total population) living in wards within this distance of their closest DGH and GP
Remoteness and rurality
For the purposes of this study, remoteness from health services was defined as over 5 km from a GP or over 25 km from a DGH. Access to primary care was good, with just 91 wards (6.3% of the total) remote from primary care. These areas have just 3% of the regional population. Of these the majority (63%) were ONS 'rural' areas. There were 162 wards which we classified as remote from hospitals (11% of the total, home to 6.5% of the region's population). All had drive-times to hospital of over 21 minutes; 81 (51%) were urban by the ONS classification, 69 (43%) were rural areas and the remaining eight (5%) were rural fringe. Four wards had no ONS urban / rural classification (table 2).
Table 2 ONS rurality and remoteness from hospital
N (%) Rural Rural fringe Not rural No classification Total*
Remote 69 (43%) 8 (5%) 81 (51%) 2 (1%) 162 (100%)
Not remote 184 (14%) 146 (11%) 950 (74%) 6 (0.5%) 1286 (100%)
Distance and the need for health care
Deprivation scores ranged from -6.2 to 9.9, with a mean of -1.0, indicating that the study area had a slightly more affluent profile than the England and Wales average. The most affluent wards were in the middle of the range of straight-line distances from secondary care. The median deprivation score was 1.0 in the decile of wards closest to hospitals, decreased to a low of -2.2 in the 5th decile, then rose steadily to -1.0 in the decile of wards furthest from hospitals, giving a slight 'U' shape to the relationship between deprivation and distance from health services (figure 3).
Figure 3 Townsend deprivation score for deciles of wards by straight-line distance from DGH
The proportion of over 65 year olds increased slightly with straight-line distance from hospitals: more remote wards had a slightly higher proportion of residents over the age of 65, but there was considerable variation within deciles of remoteness, and the observed difference was small. The proportion of the population under five years old in 1991 showed no clear trend with ward distance from hospital, but was slightly lower in more remote wards (figure 4).
Figure 4 Age structure of wards by straight-line distance from DGH. average proportion of young (under 5) and elderly (over 65) population for deciles of Wards by straight line distance from DGH
The age-standardised rate of LLTI was highest in the areas closest to hospitals. The LLTI rate decreased with increasing distance from hospital and then increased again in the most remote areas. Standardised rates of premature mortality showed no strong pattern with distance from a hospital, although median rates were high in areas close to hospitals and also slightly raised in the most remote areas. The proportion of households with no car was highest in the areas closest to hospital, but increased again in the decile of wards furthest from hospital. The same pattern was seen in the ownership of two or more cars – the lowest rates were found in areas either very close to or very far from hospitals (table 3).
Table 3 Median values for health outcomes and car ownership for deciles of ward by straight-line distance from DGH
Closest 2 3 4 5 6 7 8 9 Furthest
LLTI SMR (0–64) 1.08 1.02 0.92 0.84 0.85 0.89 0.85 0.87 0.89 1.02
All-cause SMR (0–64) 1.08 0.99 0.93 0.91 0.87 0.93 0.88 0.91 0.96 0.94
Proportion of households with No car 34.2 29.3 25.4 20.4 20.3 21.0 20.1 20.7 20.2 23.1
Two or more cars 20.0 23.2 27.8 32.1 33.2 32.0 32.8 32.5 31.2 27.0
Discussion
The impact of distance on the use of hospitals and other health care, and on health status, has not been well established. In the UK threshold distances of between 24 and 50 miles to specialist hospital services [19,20], 10 miles to screening services [21], 7 km (4 miles) to family planning clinics [22] and 2.5 miles to primary care [23] have all been used in reporting 'poor access', but there is little consensus and no strong theoretical or empirical basis for these choices. By international standards, distances to health services for our study population are low, averaging just 12 km to the closest hospital, but drive-times to hospital of up to 50 minutes are predicted by our model and there are groups who could be considerably disadvantaged by the travel distances we have reported.
A variety of measures of geographic access of varying complexity and specificity exist and selecting an appropriate measure is not simple. Straight-line distances are widely used, easy to calculate and to compare and, in this study, they are closely correlated with the more complex drive-times. However, there is some evidence that areas of low correlation are concentrated in peripheral areas of the rural South West. In these areas straight-line distances underestimate true travel distance, reflecting sparse road networks and geographical barriers such as hills, rivers and coastline. Access to health services in these areas could be misrepresented by the use of the simpler measure, masking problems faced by these populations. Furthermore, neither measure used here reflects the experience of those without access to a private car. Travel to hospital and GP appointments is already known to be a problem for some groups in rural areas of the UK. Although informal systems of 'lift-giving' and more formal 'voluntary taxi' schemes often exist [24] these are not available everywhere [25,26], and it could be argued that a measure of travel by public transport is vital in determining accessibility for the most disadvantaged populations. Few studies have attempted this [27-29]., and composite measures, which include both public and private transport, are even less common [30]. Better measures of access, which integrate private and public transport, are required to reflect the experience of those on low incomes, and without their own transport.
A surprising finding of this study was the relatively low proportion of wards remote from health care which are defined as 'rural'. Fewer than half of the wards remote from hospital and under two-thirds of those remote from primary care are classified as rural by the ONS. Analysis which concentrates on rural areas under the ONS definition, or even stretches this to include 'rural fringe' areas, will still miss over half of the wards which are remote from hospitals. There has been concern over the targeting of resources in concentrations of deprivation: the majority of deprived people live outside of these areas and are not reached by narrowly focused initiatives. Although the ward-level definition of rurality used here may class as 'urban' some small towns which many would consider essentially 'rural' when viewed at a larger scale (such as the Local Authority level), we conclude that caution should be exercised when evaluating and responding to poor access to health services, a high proportion of which occurs outside areas traditionally considered to be remote.
In this study, we found no clear threshold at which need becomes greater or health status sharply declines. If anything, the converse is true with worse health status and greatest need in areas close to health services. Distance to health care was not associated with a high proportion of elderly or very young residents, but was related to deprivation. We found high deprivation in areas close to hospitals, relative affluence in more distant areas and an increase in deprivation in the most remote wards. Deprivation indices have been criticised for failing to represent deprivation in rural areas [31] and the relatively high proportion of rural areas in the most remote wards may hide even higher need in these areas. Further research using different measures of need and deprivation is indicated.
Although the highest rates of morbidity and mortality were found in the areas closest to hospitals, there was some evidence of increasing rates in more remote areas. Rates of LLTI, particularly for those under 64, show an upwards trend in more remote areas. This supports previous findings that LLTI is higher in rural wards with the most dispersed populations [31], but it is not clear whether this reflects a true increase in morbidity or a perception of handicap of those living in such areas. The relationship between distance and all-cause premature mortality is less clear. The high levels of mobility which are often reported in populations living far from services were upheld by our study (expressed through high car ownership), but the areas most remote from hospitals begin to show a decrease in levels of car ownership. It is unlikely that this indicates less need for private transport, and may indicate a less wealthy population for whom travel is a potential problem.
There are a number of important limitations to our study. We have explored only one region of England, a relatively affluent area with a very small ethnic minority population and an unusual 'peninsular' geography. Our findings need to be reproduced in other areas. We have limited our definition of access to simple geographical measures. Other aspects of accessibility include the quantity and quality of health services, and financial and cultural barriers to their use, and have not been explored here. The choice of SMRs and LLTI rates as health outcome indicators may have resulted in our inability to observe stronger relationships between geographical access and health: even over a six year period absolute numbers of deaths were low. More research is needed including the young and elderly and using a wider range of health status measures. Finally, the inter relationship between use of health care, need and access has been insufficiently explored.
Conclusions
This paper has provided a population-based estimate for access to both primary and secondary health care in South West England. We have shown that although geographical access to health services is generally good, remoteness from health services is an issue which affects both urban and rural areas. Studies concentrating purely on rural areas are therefore likely to underestimate the extent of geographical barriers to accessing health care. Areas which were furthest from hospitals did not have an especially old or young population, but there was some evidence of higher rates of LLTI and of deprivation in the most remote wards, indicating higher need for services in the areas furthest from them. Finally, the fact that almost a quarter of households in the decile of wards most remote from hospital services had no car in 1991 indicated a large number of people for whom travel is likely to be more difficult than implied by current measures of geographical access.
Our understanding of the effect of distance on the use of services and on health outcomes is far from complete. Both the measurement of access and the understanding of need and deprivation require further exploration. The development of web-based public transport information systems may supply the data needed to enhance currently available measures of access by adding public transport travel times, likely to be relevant to access for the poorest and most deprived populations and the introduction of the Indices of Multiple Deprivation 2000 in England may present a clearer picture of the need for health care than traditional census-based indices [32]. This index contains a measure of geographical access to services, which has been of particular interest to rural populations and may provide a missing dimension to the measurement of deprivation. Linking geographical access with a wider range of health status measures and health care use in different populations is also vital if a clear picture of the impact of accessibility of health care is to be fully understood.
Methods
Measuring geographical access to health services
A Geographical Information System (Arc/Info) and custom written programs were used to calculate two measures of access to health services. Access was calculated from all residential postcodes to primary care services (all main and branch General Practice (GP) surgeries) and secondary care services (acute hospitals (DGHs)) in the region. Data on main and branch GP surgeries (n = 1469) were obtained from all Family Health Services Authorities in 1998. Acute DGHs (n = 39) were defined as hospitals with general medicine and general surgery facilities and an Accident and Emergency department. DGHs were identified using the hospital year-books (1992–97) and hospitals were contacted to clarify their status in 1997 as necessary.
The first access measure calculated was a widely used measure: the shortest straight-line distance between every residential postcode, the closest GP (both main and branch) and the closest DGH. A more complex measure of access was the shortest drive-time from each residential postcode to the closest GP and the closest DGH. This was modelled using estimated road-network travel speeds along the Bartholomew digital road network and associating these with residential postcode locations by the use of a travel time (drive-time) surface model. While including provision for congestion and slow travel through urban areas, this measure does not include any estimates for parking times or transfers between car and surgery or hospital. The methods are described in detail elsewhere [33].
The need for health care
Proxy measures of the need for health care were calculated. The Townsend score, a widely used indicator of material deprivation, was calculated from 1991 census data. The variables used in the score are the percentage of economically active people over the age of 16 who are unemployed; the percentage of households which are overcrowded; the percentage of households with no car and the percentage of households not owning their own home. A log transformation is applied to the overcrowding and unemployment variables. The logged variables and the car ownership and owner occupation variables are standardised by creating z-scores for each value, and the four z-scores are summed to provide the final Townsend score. Scores are standardised to give a mean of zero for England and Wales: any scores greater than zero indicate relative deprivation, any less than zero represent relative affluence. The proportions of the population over 65 and under 5 years old – were taken from the 1991 Census Small Area Statistics (SAS). Health status was assessed using indirectly standardised rates of all-cause mortality and Limiting Long Term Illness (LLTI) for all those under 65 (premature mortality and morbidity). Data on LLTI were taken from the 1991 Census. The Office for National Statistics (ONS) provided data on all-cause mortality for the years 1991–1996. Data were aggregated over the six years, to minimise problems due to small numbers of cases in some wards.
Assigning data to geographical areas
Postcodes were allocated to 1991 Census wards using the 1991 and subsequent postcode to enumeration district directories. Travel times and distances were calculated for all residential postcodes and aggregated to ward level for analysis. The resident population of each ward was used to weight individual postcode times and distances to create a population-weighted average, as demonstrated in table 4. ONS ward classifications were used to select 'rural' wards [34]. The ONS classifications are listed in table 5. Only two categories: 'rural areas' and 'rural fringe', are unambiguously rural under this definition and we have defined than as rural here. All other wards were defined as urban.
Table 4 Aggregating household level access data to wards
Ward Postcode N Households from each postcode in Ward1 Time from PC to health services Households * time
Ward1 PC1 10 10 100
Ward1 PC2 7 13 91
Ward1 PC3 2 11 22
Ward1 PC4 6 21 126
Sum (Ward1) 25 339
Population weighted average time for Ward1 ((hhds*time)/hhs)
Table 5 The ONS ward classification
ONS group Rural / urban classification
Suburbia Urban
Rural areas Rural
Rural fringe Rural
Industrial areas Urban
Middling Britain Urban
Prosperous areas Urban
Inner city estates Urban
Established owner occupiers Urban
Transient populations Urban
Metropolitan professionals Urban
Deprived city areas Urban
Lower status owner occupiers Urban
Mature populations Urban
Deprived industrial areas Urban
Analyses
To investigate if straight-line distance was a valid proxy for the more complex drive-time measure, the two were compared using Pearson correlation coefficients and a regression analysis of drive-time against straight-line distance. Areas where straight-line distance appeared to underestimate the drive-time more than expected were identified and mapped to investigate the extent of geographical clustering. Access to primary and secondary health services was described using median distances and inter-quartile ranges for both measures.
To investigate the assumption that it is the residents of rural areas who are most disadvantaged by poor geographical access to health services, we first had to define poor access. Standard estimates of 'remoteness' from health services have not been established – there is no a priori definition of the distance regarded as 'remote from health services' and no consensus has been established in the literature on access to health services. The proportion of rural, rural fringe and urban wards which were 'remote' from health services under the definition of a straight-line distance of three, five or seven kilometres to a GP and 20, 25, 30 or 35 km to a hospital was therefore calculated (Table 6). We used an arbitrary cut-off point of a straight-line distance of 5 km to a GP and 25 km to a hospital, beyond which wards were classed as 'remote' from health services. These distances classified approximately 6% of the study population as remote from secondary care and 3% as remote from primary care.
Table 6 ONS rurality and remoteness from primary and secondary care
Rural Rural fringe Urban No classification Total wards
All wards 253 (18%) 154 (11%) 1031 (71%) 10 (1%) 1448 (100%)
GPs
Remote (3 km) 117 (53%) 14 (6%) 84 (38%) 6 (3%) 221 (100%)
Remote (5 km) 20 (53%) 4 (10%) 12 (32%) 2 (5%) 38 (100%)
Remote (7 km) 5 (71%) 1 (14%) 0 (0%) 1 (14%) 7 (100%)
Hospitals
Remote (20 km) 126 (39%) 36 (11%) 158 (49%) 4 (1%) 324 (100%)
Remote (25 km) 69 (43%) 8 (5%) 81 (51%) 2 (1%) 162 (100%)
Remote (30 km) 30 (49%) 1 (2%) 28 (46%) 2 (3%) 61 (100%)
Remote (35 km) 17 (59%) 0 (0%) 12 (41%) 0 (0%) 29 (100%)
We then identified the proportion of remote wards that were rural under the ONS classification. To investigate relationships between distance to health services and the need for health care, straight-line distance to hospital was used to group wards into deciles and the deprivation score and the age profile of the population in each decile was described. Standardised rates for premature all-cause mortality and LLTI were used to indicate health outcomes for each decile of wards, and car ownership (as reported in the 1991 census) was used to indicate how easy travel would be for the population in each group.
Authors' contributions
HJ carried out the analyses and drafted the manuscript. HJ, PR, and DM collaborated in the formation of the research questions, the management of the study and the development of the paper. HJ and SB collected the data and calculated measures of deprivation, health and accessibility. DM designed the drive-time access measure. All authors read and approved the final manuscript.
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| 15456514 | PMC524184 | CC BY | 2021-01-04 16:39:01 | no | Int J Health Geogr. 2004 Sep 29; 3:21 | utf-8 | Int J Health Geogr | 2,004 | 10.1186/1476-072X-3-21 | oa_comm |
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Int J Health GeogrInternational Journal of Health Geographics1476-072XBioMed Central London 1476-072X-3-211545651410.1186/1476-072X-3-21ResearchDistance, rurality and the need for care: access to health services in South West England Jordan Hannah 1h.c.jordan@soton.ac.ukRoderick Paul 1p.j.roderick@soton.ac.ukMartin David 2d.j.martin@soton.ac.ukBarnett Sarah 3s.barnett@ich.ucl.ac.uk1 Health Care Research Unit, CCS Division, School of Medicine, University of Southampton, UK2 School of Geography, University of Southampton, UK3 International Perinatal Care Unit, Institute of Child Health, London, UK2004 29 9 2004 3 21 21 31 8 2004 29 9 2004 Copyright © 2004 Jordan et al; licensee BioMed Central Ltd.2004Jordan 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 explores the geographical accessibility of health services in urban and rural areas of the South West of England, comparing two measures of geographical access and characterising the areas most remote from hospitals.
Straight-line distance and drive-time to the nearest general practice (GP) and acute hospital (DGH) were calculated for postcodes and aggregated to 1991 Census wards. The correlation between the two measures was used to identify wards where straight-line distance was not an accurate predictor of drive-time. Wards over 25 km from a DGH were classified as 'remote', and characterised in terms of rurality, deprivation, age structure and health status of the population.
Results
The access measures were highly correlated (r2>0.93). The greatest differences were found in coastal and rural wards of the far South West. Median straight-line distance to GPs was 1 km (IQR = 0.6–2 km) and to DGHs, 12 km (IQR = 5–19 km). Deprivation and rates of premature limiting long term illness were raised in areas most distant from hospitals, but there was no evidence of higher premature mortality rates. Half of the wards remote from a DGH were not classed as rural by the Office for National Statistics. Almost a quarter of households in the wards furthest from hospitals had no car, and the proportion of households with access to two or more cars fell in the most remote areas.
Conclusion
Drive-time is a more accurate measure of access for peripheral and rural areas. Geographical access to health services, especially GPs, is good, but remoteness affects both rural and urban areas: studies concentrating purely on rural areas may underestimate geographical barriers to accessing health care. A sizeable minority of households still had no car in 1991, and few had more than one car, particularly in areas very close to and very distant from hospitals. Better measures of geographical access, which integrate public and private transport availability with distance and travel time, are required if an accurate reflection of the experience those without their own transport is to be obtained.
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Background
The UK National Health Service has always aimed to provide health care for all. Although the importance of "fair access for all" (independent of the ability to pay, age, sex or area of residence) has been highlighted in recent policy documents [1], the meaning of 'fair access' is still debated [2]. Although there will always be variations in geographical access to health services, the extent of such variations and the relationship between distance to health services and the need for health care is unclear. If policy makers are to address inequities of access, more understanding is needed both of appropriate methods for measuring access and of the relationship between access to health services and health.
Although 'fair access' can be characterised simply as 'providing the right service at the right time in the right place'[3], it is a complex concept covering the provision of services, the knowledge and opportunity to use them, and the measurement of need [4]. In the UK mergers of hospital trusts have highlighted tensions between the perceived safety, effectiveness and efficiency of larger specialist centres and the demand for more geographically accessible local care [5,6], revealing the lack of evidence on which to base decisions [7]. Geographical access – the distance which must be travelled in order to use health services – is one aspect of access which is often overlooked [2], but which presents barriers of cost, time and inconvenience.
Although there is some evidence that increasing distance from health services inhibits the use of primary [8] and secondary care [9], and that it is associated with a range of poor health outcomes, from higher than expected numbers of deaths from asthma to lower than expected five year survival from cancer [10,11], few studies have attempted to quantify or set thresholds of poor access [12,13]. Furthermore, measures of geographical access can be difficult to compare. Rurality has often been used as a proxy for inaccessibility [14], as have dichotomous categorisations such as the presence or absence of a service provider in an area [15,8]. More complex measurements such as the straight line distance between populations (i.e demand points) and health service providers [16,17], or 'network distances' (which can include both road distance and travel time) [8] have added complexity, but the relationship between these measures is not clear.
One assumption which is commonly made is that geographical inaccessibility of health services is essentially a rural problem, but there is little evidence demonstrating the differences in accessibility between rural and other areas. In any area, the greatest disadvantage is likely to be experienced by individuals without access to a car (including members of one-car households without daytime access). With the declining availability of public transport, it is likely that a private car is the only convenient way to travel in rural Britain [18]. Although car ownership is relatively high in rural areas, rates for the poor, the elderly and for women are far lower than average: the 2001 Census reports that more than two thirds of single-pensioner households, many of which comprise single women, do not have access to a car. Distance may therefore be a further burden on groups with a particularly high need for health care, raising issues of inequity. Furthermore, if geographical access to health services is a problem for some groups outside of traditional rural areas, then rural policies alone will not tackle the problem.
In this paper, we aim to determine the geographical accessibility of health services, and the demographic and health related factors associated with it. We compare two measures of geographical access: straight-line distance and modelled drive-time along the road network to primary and secondary care throughout South West England. We investigate whether the most geographically inaccessible populations are in rural areas, describe the relationship between geographical access to hospital and population health, and investigate whether the populations furthest from health services have a greater need for health care due to age or deprivation.
The study area is the former South West Region, comprising the counties of Avon, Cornwall and the Isles of Scilly, Devon, Dorset, Gloucestershire, Hampshire, the Isle of Wight, Somerset and Wiltshire. As defined in 1991 this area has a population of about 6 million, with a low proportion from ethnic minorities, and a higher than average proportion living in rural areas.
Results
Correlation between the access measures
The straight-line and drive-time measures were highly correlated for both GP and hospital services (figure 1). Areas where residuals from the regression analysis of straight-line distance and drive-time to DGHs are more than two standard deviations from the norm were concentrated in coastal and rural wards of the far South West. Areas where residuals are negative indicate faster than expected drive times, wheras positive residuals indicate that drive time is slower than predicted by straight line distances (figure 2). The analysis was repeated, excluding wards along the boundary between the study area and neighbouring counties to check for edge-effects, but there was no difference in results.
Figure 1 Correlation between straight line and drive-time measures to GP and hospital services
Figure 2 Standardised residuals from the regression of drive time and straight-line distance to hospitals
Distances to health services
Distances to GPs were low, with a median distance of just 1 km to the closest practice (IQR 0.6 – 2.2). The calculation was repeated excluding branch surgeries (which tend to have limited opening hours), but this made little difference to the outcome, with a median distance to a main surgery of just 1.2 km. 95% of wards (98% of the population) were under 4.4 km, or 6.3 minutes, from their closest GP. The maximum distance to a GP was just 9.4 km (13.7 minutes). The median distance to a DGH was just less than 12 km (IQR 5.4 – 19.0), with a maximum of 50 km, corresponding to an estimated 13 and 48 minutes drive-time (table 1).
Table 1 Access to DGHs and GPs
25th centile Popn (%)* Median Popn (%) 75th centile Popn (%) 95th centile Popn (%) Maximum
Straight line (km) DGH 5.4 2.40 (39.3) 11.6 3.97 (65.1) 19.0 5.15 (84.3) 29.0 5.92 (97.1) 50.1
GP surgery 0.6 2.24 (36.8) 1.0 4.17 (68.3) 2.2 5.39 (88.4) 4.4 5.96 (97.7) 9.4
Drive time ('minutes') DGH 7.1 2.38 (38.9) 13.4 3.93 (64.4) 20.5 5.17 (84.7) 31.6 5.93 (97.2) 48.3
GP surgery 1.0 2.19 (35.9) 1.7 4.00 (65.5) 3.4 5.28 (86.5) 6.3 5.89 (96.5) 13.7
*Population in millions (percent of the total population) living in wards within this distance of their closest DGH and GP
Remoteness and rurality
For the purposes of this study, remoteness from health services was defined as over 5 km from a GP or over 25 km from a DGH. Access to primary care was good, with just 91 wards (6.3% of the total) remote from primary care. These areas have just 3% of the regional population. Of these the majority (63%) were ONS 'rural' areas. There were 162 wards which we classified as remote from hospitals (11% of the total, home to 6.5% of the region's population). All had drive-times to hospital of over 21 minutes; 81 (51%) were urban by the ONS classification, 69 (43%) were rural areas and the remaining eight (5%) were rural fringe. Four wards had no ONS urban / rural classification (table 2).
Table 2 ONS rurality and remoteness from hospital
N (%) Rural Rural fringe Not rural No classification Total*
Remote 69 (43%) 8 (5%) 81 (51%) 2 (1%) 162 (100%)
Not remote 184 (14%) 146 (11%) 950 (74%) 6 (0.5%) 1286 (100%)
Distance and the need for health care
Deprivation scores ranged from -6.2 to 9.9, with a mean of -1.0, indicating that the study area had a slightly more affluent profile than the England and Wales average. The most affluent wards were in the middle of the range of straight-line distances from secondary care. The median deprivation score was 1.0 in the decile of wards closest to hospitals, decreased to a low of -2.2 in the 5th decile, then rose steadily to -1.0 in the decile of wards furthest from hospitals, giving a slight 'U' shape to the relationship between deprivation and distance from health services (figure 3).
Figure 3 Townsend deprivation score for deciles of wards by straight-line distance from DGH
The proportion of over 65 year olds increased slightly with straight-line distance from hospitals: more remote wards had a slightly higher proportion of residents over the age of 65, but there was considerable variation within deciles of remoteness, and the observed difference was small. The proportion of the population under five years old in 1991 showed no clear trend with ward distance from hospital, but was slightly lower in more remote wards (figure 4).
Figure 4 Age structure of wards by straight-line distance from DGH. average proportion of young (under 5) and elderly (over 65) population for deciles of Wards by straight line distance from DGH
The age-standardised rate of LLTI was highest in the areas closest to hospitals. The LLTI rate decreased with increasing distance from hospital and then increased again in the most remote areas. Standardised rates of premature mortality showed no strong pattern with distance from a hospital, although median rates were high in areas close to hospitals and also slightly raised in the most remote areas. The proportion of households with no car was highest in the areas closest to hospital, but increased again in the decile of wards furthest from hospital. The same pattern was seen in the ownership of two or more cars – the lowest rates were found in areas either very close to or very far from hospitals (table 3).
Table 3 Median values for health outcomes and car ownership for deciles of ward by straight-line distance from DGH
Closest 2 3 4 5 6 7 8 9 Furthest
LLTI SMR (0–64) 1.08 1.02 0.92 0.84 0.85 0.89 0.85 0.87 0.89 1.02
All-cause SMR (0–64) 1.08 0.99 0.93 0.91 0.87 0.93 0.88 0.91 0.96 0.94
Proportion of households with No car 34.2 29.3 25.4 20.4 20.3 21.0 20.1 20.7 20.2 23.1
Two or more cars 20.0 23.2 27.8 32.1 33.2 32.0 32.8 32.5 31.2 27.0
Discussion
The impact of distance on the use of hospitals and other health care, and on health status, has not been well established. In the UK threshold distances of between 24 and 50 miles to specialist hospital services [19,20], 10 miles to screening services [21], 7 km (4 miles) to family planning clinics [22] and 2.5 miles to primary care [23] have all been used in reporting 'poor access', but there is little consensus and no strong theoretical or empirical basis for these choices. By international standards, distances to health services for our study population are low, averaging just 12 km to the closest hospital, but drive-times to hospital of up to 50 minutes are predicted by our model and there are groups who could be considerably disadvantaged by the travel distances we have reported.
A variety of measures of geographic access of varying complexity and specificity exist and selecting an appropriate measure is not simple. Straight-line distances are widely used, easy to calculate and to compare and, in this study, they are closely correlated with the more complex drive-times. However, there is some evidence that areas of low correlation are concentrated in peripheral areas of the rural South West. In these areas straight-line distances underestimate true travel distance, reflecting sparse road networks and geographical barriers such as hills, rivers and coastline. Access to health services in these areas could be misrepresented by the use of the simpler measure, masking problems faced by these populations. Furthermore, neither measure used here reflects the experience of those without access to a private car. Travel to hospital and GP appointments is already known to be a problem for some groups in rural areas of the UK. Although informal systems of 'lift-giving' and more formal 'voluntary taxi' schemes often exist [24] these are not available everywhere [25,26], and it could be argued that a measure of travel by public transport is vital in determining accessibility for the most disadvantaged populations. Few studies have attempted this [27-29]., and composite measures, which include both public and private transport, are even less common [30]. Better measures of access, which integrate private and public transport, are required to reflect the experience of those on low incomes, and without their own transport.
A surprising finding of this study was the relatively low proportion of wards remote from health care which are defined as 'rural'. Fewer than half of the wards remote from hospital and under two-thirds of those remote from primary care are classified as rural by the ONS. Analysis which concentrates on rural areas under the ONS definition, or even stretches this to include 'rural fringe' areas, will still miss over half of the wards which are remote from hospitals. There has been concern over the targeting of resources in concentrations of deprivation: the majority of deprived people live outside of these areas and are not reached by narrowly focused initiatives. Although the ward-level definition of rurality used here may class as 'urban' some small towns which many would consider essentially 'rural' when viewed at a larger scale (such as the Local Authority level), we conclude that caution should be exercised when evaluating and responding to poor access to health services, a high proportion of which occurs outside areas traditionally considered to be remote.
In this study, we found no clear threshold at which need becomes greater or health status sharply declines. If anything, the converse is true with worse health status and greatest need in areas close to health services. Distance to health care was not associated with a high proportion of elderly or very young residents, but was related to deprivation. We found high deprivation in areas close to hospitals, relative affluence in more distant areas and an increase in deprivation in the most remote wards. Deprivation indices have been criticised for failing to represent deprivation in rural areas [31] and the relatively high proportion of rural areas in the most remote wards may hide even higher need in these areas. Further research using different measures of need and deprivation is indicated.
Although the highest rates of morbidity and mortality were found in the areas closest to hospitals, there was some evidence of increasing rates in more remote areas. Rates of LLTI, particularly for those under 64, show an upwards trend in more remote areas. This supports previous findings that LLTI is higher in rural wards with the most dispersed populations [31], but it is not clear whether this reflects a true increase in morbidity or a perception of handicap of those living in such areas. The relationship between distance and all-cause premature mortality is less clear. The high levels of mobility which are often reported in populations living far from services were upheld by our study (expressed through high car ownership), but the areas most remote from hospitals begin to show a decrease in levels of car ownership. It is unlikely that this indicates less need for private transport, and may indicate a less wealthy population for whom travel is a potential problem.
There are a number of important limitations to our study. We have explored only one region of England, a relatively affluent area with a very small ethnic minority population and an unusual 'peninsular' geography. Our findings need to be reproduced in other areas. We have limited our definition of access to simple geographical measures. Other aspects of accessibility include the quantity and quality of health services, and financial and cultural barriers to their use, and have not been explored here. The choice of SMRs and LLTI rates as health outcome indicators may have resulted in our inability to observe stronger relationships between geographical access and health: even over a six year period absolute numbers of deaths were low. More research is needed including the young and elderly and using a wider range of health status measures. Finally, the inter relationship between use of health care, need and access has been insufficiently explored.
Conclusions
This paper has provided a population-based estimate for access to both primary and secondary health care in South West England. We have shown that although geographical access to health services is generally good, remoteness from health services is an issue which affects both urban and rural areas. Studies concentrating purely on rural areas are therefore likely to underestimate the extent of geographical barriers to accessing health care. Areas which were furthest from hospitals did not have an especially old or young population, but there was some evidence of higher rates of LLTI and of deprivation in the most remote wards, indicating higher need for services in the areas furthest from them. Finally, the fact that almost a quarter of households in the decile of wards most remote from hospital services had no car in 1991 indicated a large number of people for whom travel is likely to be more difficult than implied by current measures of geographical access.
Our understanding of the effect of distance on the use of services and on health outcomes is far from complete. Both the measurement of access and the understanding of need and deprivation require further exploration. The development of web-based public transport information systems may supply the data needed to enhance currently available measures of access by adding public transport travel times, likely to be relevant to access for the poorest and most deprived populations and the introduction of the Indices of Multiple Deprivation 2000 in England may present a clearer picture of the need for health care than traditional census-based indices [32]. This index contains a measure of geographical access to services, which has been of particular interest to rural populations and may provide a missing dimension to the measurement of deprivation. Linking geographical access with a wider range of health status measures and health care use in different populations is also vital if a clear picture of the impact of accessibility of health care is to be fully understood.
Methods
Measuring geographical access to health services
A Geographical Information System (Arc/Info) and custom written programs were used to calculate two measures of access to health services. Access was calculated from all residential postcodes to primary care services (all main and branch General Practice (GP) surgeries) and secondary care services (acute hospitals (DGHs)) in the region. Data on main and branch GP surgeries (n = 1469) were obtained from all Family Health Services Authorities in 1998. Acute DGHs (n = 39) were defined as hospitals with general medicine and general surgery facilities and an Accident and Emergency department. DGHs were identified using the hospital year-books (1992–97) and hospitals were contacted to clarify their status in 1997 as necessary.
The first access measure calculated was a widely used measure: the shortest straight-line distance between every residential postcode, the closest GP (both main and branch) and the closest DGH. A more complex measure of access was the shortest drive-time from each residential postcode to the closest GP and the closest DGH. This was modelled using estimated road-network travel speeds along the Bartholomew digital road network and associating these with residential postcode locations by the use of a travel time (drive-time) surface model. While including provision for congestion and slow travel through urban areas, this measure does not include any estimates for parking times or transfers between car and surgery or hospital. The methods are described in detail elsewhere [33].
The need for health care
Proxy measures of the need for health care were calculated. The Townsend score, a widely used indicator of material deprivation, was calculated from 1991 census data. The variables used in the score are the percentage of economically active people over the age of 16 who are unemployed; the percentage of households which are overcrowded; the percentage of households with no car and the percentage of households not owning their own home. A log transformation is applied to the overcrowding and unemployment variables. The logged variables and the car ownership and owner occupation variables are standardised by creating z-scores for each value, and the four z-scores are summed to provide the final Townsend score. Scores are standardised to give a mean of zero for England and Wales: any scores greater than zero indicate relative deprivation, any less than zero represent relative affluence. The proportions of the population over 65 and under 5 years old – were taken from the 1991 Census Small Area Statistics (SAS). Health status was assessed using indirectly standardised rates of all-cause mortality and Limiting Long Term Illness (LLTI) for all those under 65 (premature mortality and morbidity). Data on LLTI were taken from the 1991 Census. The Office for National Statistics (ONS) provided data on all-cause mortality for the years 1991–1996. Data were aggregated over the six years, to minimise problems due to small numbers of cases in some wards.
Assigning data to geographical areas
Postcodes were allocated to 1991 Census wards using the 1991 and subsequent postcode to enumeration district directories. Travel times and distances were calculated for all residential postcodes and aggregated to ward level for analysis. The resident population of each ward was used to weight individual postcode times and distances to create a population-weighted average, as demonstrated in table 4. ONS ward classifications were used to select 'rural' wards [34]. The ONS classifications are listed in table 5. Only two categories: 'rural areas' and 'rural fringe', are unambiguously rural under this definition and we have defined than as rural here. All other wards were defined as urban.
Table 4 Aggregating household level access data to wards
Ward Postcode N Households from each postcode in Ward1 Time from PC to health services Households * time
Ward1 PC1 10 10 100
Ward1 PC2 7 13 91
Ward1 PC3 2 11 22
Ward1 PC4 6 21 126
Sum (Ward1) 25 339
Population weighted average time for Ward1 ((hhds*time)/hhs)
Table 5 The ONS ward classification
ONS group Rural / urban classification
Suburbia Urban
Rural areas Rural
Rural fringe Rural
Industrial areas Urban
Middling Britain Urban
Prosperous areas Urban
Inner city estates Urban
Established owner occupiers Urban
Transient populations Urban
Metropolitan professionals Urban
Deprived city areas Urban
Lower status owner occupiers Urban
Mature populations Urban
Deprived industrial areas Urban
Analyses
To investigate if straight-line distance was a valid proxy for the more complex drive-time measure, the two were compared using Pearson correlation coefficients and a regression analysis of drive-time against straight-line distance. Areas where straight-line distance appeared to underestimate the drive-time more than expected were identified and mapped to investigate the extent of geographical clustering. Access to primary and secondary health services was described using median distances and inter-quartile ranges for both measures.
To investigate the assumption that it is the residents of rural areas who are most disadvantaged by poor geographical access to health services, we first had to define poor access. Standard estimates of 'remoteness' from health services have not been established – there is no a priori definition of the distance regarded as 'remote from health services' and no consensus has been established in the literature on access to health services. The proportion of rural, rural fringe and urban wards which were 'remote' from health services under the definition of a straight-line distance of three, five or seven kilometres to a GP and 20, 25, 30 or 35 km to a hospital was therefore calculated (Table 6). We used an arbitrary cut-off point of a straight-line distance of 5 km to a GP and 25 km to a hospital, beyond which wards were classed as 'remote' from health services. These distances classified approximately 6% of the study population as remote from secondary care and 3% as remote from primary care.
Table 6 ONS rurality and remoteness from primary and secondary care
Rural Rural fringe Urban No classification Total wards
All wards 253 (18%) 154 (11%) 1031 (71%) 10 (1%) 1448 (100%)
GPs
Remote (3 km) 117 (53%) 14 (6%) 84 (38%) 6 (3%) 221 (100%)
Remote (5 km) 20 (53%) 4 (10%) 12 (32%) 2 (5%) 38 (100%)
Remote (7 km) 5 (71%) 1 (14%) 0 (0%) 1 (14%) 7 (100%)
Hospitals
Remote (20 km) 126 (39%) 36 (11%) 158 (49%) 4 (1%) 324 (100%)
Remote (25 km) 69 (43%) 8 (5%) 81 (51%) 2 (1%) 162 (100%)
Remote (30 km) 30 (49%) 1 (2%) 28 (46%) 2 (3%) 61 (100%)
Remote (35 km) 17 (59%) 0 (0%) 12 (41%) 0 (0%) 29 (100%)
We then identified the proportion of remote wards that were rural under the ONS classification. To investigate relationships between distance to health services and the need for health care, straight-line distance to hospital was used to group wards into deciles and the deprivation score and the age profile of the population in each decile was described. Standardised rates for premature all-cause mortality and LLTI were used to indicate health outcomes for each decile of wards, and car ownership (as reported in the 1991 census) was used to indicate how easy travel would be for the population in each group.
Authors' contributions
HJ carried out the analyses and drafted the manuscript. HJ, PR, and DM collaborated in the formation of the research questions, the management of the study and the development of the paper. HJ and SB collected the data and calculated measures of deprivation, health and accessibility. DM designed the drive-time access measure. All authors read and approved the final manuscript.
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| 15461814 | PMC524185 | CC BY | 2021-01-04 16:38:29 | no | Cardiovasc Ultrasound. 2004 Oct 4; 2:18 | latin-1 | Cardiovasc Ultrasound | 2,004 | 10.1186/1476-7120-2-18 | oa_comm |
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Health Qual Life OutcomesHealth and Quality of Life Outcomes1477-7525BioMed Central London 1477-7525-2-531538314710.1186/1477-7525-2-53ResearchIdentification of rehabilitation needs after a stroke: an exploratory study Talbot Lise R 1Lise.Talbot@USherbrooke.caViscogliosi Chantal 2Chantal.viscogliosi@USherbrooke.caDesrosiers Johanne 2Johanne.desrosiers@USherbrooke.caVincent Claude 3Claude.Vincent@rea.ulaval.caRousseau Jacqueline 4Jacqueline.Rousseau@umontreal.caRobichaud Line 3Line.Robichaud@rea.ulaval.ca1 Nursing Department, Faculty of Medicine, Université de Sherbrooke, 3001, 12e Avenue Nord, J1H 5N4 Sherbrooke (Québec), Canada2 Research Centre on Aging, Faculty of Medicine, Université de Sherbrooke, Canada3 Occupational Therapy Department, Université Laval, Québec, G1K 7P4 Canada4 Occupational Therapy Department, Faculty of Medicine, Université de Montréal, H3C 3J7 Canada2004 21 9 2004 2 53 53 22 10 2003 21 9 2004 Copyright © 2004 Talbot et al; licensee BioMed Central Ltd.2004Talbot 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
Services to meet adequate rehabilitation needs of elderly stroke survivors are not always provided. Indeed, since 1995, in the wake of the Quebec shift to ambulatory care, home care services, mainly those related to rehabilitation of the elderly, are either unavailable or incomplete. The aim of this study was to examine the rehabilitation needs of this clientele from their hospitalization to their reintegration into the community.
Methods
The "Handicap Production Process" conceptual approach was chosen to help identify the rehabilitation needs of persons affected by physical or cognitive disabilities due to the interactions between personal and environmental factors, and (activities of daily living, social roles). This qualitative exploratory study was performed in 2003. Data were collected among four groups of experts: patients, caregivers, health care providers and administrators. Data triangulation was used to ensure a rigorous analysis and validity of the results.
Results
Unfulfilled needs could be found in the categories of pertaining to residence, community living, psychological and emotional needs. Indeed, it appears that a psychological follow-up to discuss acceptance and consequences of non-acceptance would facilitate mid-to long-term rehabilitation.
Conclusion
Improving accessibility to healthcare services, respecting priority parking spaces for the disabled as well as promoting public awareness would enable a better social reintegration and recovery of social roles, thus limiting the onset of handicap situations.
strokeneedsrehabilitationcommunity reintegrationimpairmentdisability
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Background
After a stroke, a good proportion of the elderly rapidly re-enter the community without having benefited from rehabilitation services to help reduce their impairments and disabilities. Indeed, in Canada, only about 10% of stroke sufferers have access to intensive rehabilitation services [1]. The others, being relatively independent in their activities of daily living (walking, dressing, eating), return home with or without support services. However, aside from physical problems, there often are less noticeable disorders of a perceptive-cognitive nature (hemineglect, attention or organizational problems, and impaired learning ability). These disorders could trigger handicap situations [2] and be a source of subsequent losses of autonomy, which in turn can increase use of health services, recurring hospitalizations and premature institutionalization, resulting in an expensive health system. Moreover, a person's disabilities almost always affect the lives of his/her/family.
The World Health Organization [3] defines rehabilitation as the combination and coordination of medical, social, educational and vocational resources aimed at optimizing a person's functional independence. Rehabilitation methods are essentially intended to reduce a person's disabilities and prevent the onset of disabling situations in order to support an optimal quality of life. Local community service centers (CLSC) are deeply concerned that they are unable to assume their role of providing, for their elderly users, front-line services that should cover various areas such as prevention, screening, general services and social reintegration [4]. The shift to ambulatory care initiated in Quebec in 1995 did not result in the development of outpatient rehabilitation services, even though these services, regarded as essential, can noticeably reduce hospitalization and improve quality of life. The outpatient clientele is more often left to fend for itself and sometimes has to turn to private clinics. For those with insurance coverage, the costs of these services are partly reimbursed; but 1.5 million Quebecois (23%) do not own private health insurance. Moreover, there is no comparable information on the waiting delays of private clinics that would allow to evaluate accessibility to their rehabilitation services [5]. Because of that lack of information, the Ministry of Health and the Regional Health and Social Services Boards can hardly provide cost-effective human resources in rehabilitation and equitably distribute financial resources, all the while keeping in perspective intra-regional as well as inter-regional needs. In order to delimit these issues from different perspectives, this study examines the rehabilitation needs of stroke patients in relation to their being cared for in their own home and according to their capabilities and their. This research was based on the "Handicap Production Process" conceptual approach (HPP) [6,7].
Handicap Production Process conceptual approach (HPP)
The HPP (handicap production process) ensues from the works of the International Network of the Handicap Production Process (Figure 1) – formerly known as the Quebec Committee for the International Classification of Impairment, Disability and Handicap (QC-ICIDH) [6,7] – which followed those of the World Health Organization [8]. This anthropologic model, used in research as well as in clinical situations, holds four components: risk factors (causes), personal factors (body systems and aptitudes), environmental factors (facilitator and obstacle) and (social participation and handicap situation).
Figure 1 Handicap production process conceptual approach [8,9]
Personal factors relate to the person's basic characteristics like age, sex, socio-cultural identity, body systems (integrity vs. impairment) and the aptitudes (capacities vs. disabilities). Body systems identify components of the whole body. Integrity of these systems is based on the human biological norms while an impairment relates to a degree of anatomical, or physiological damage. Aptitudes are associated with a person's capacity for physical or mental activity such as walking or understanding. The value of an aptitude is measured on a scale ranging from optimal capacity to total disability. In the HPP, ensure the survival and thriving of an individual within society, during his/her entire life. They are arranged in twelve categories, the first six referring to activities of daily living and the last six relating to social roles valued by the person or his/her socio-cultural context. These categories are: nutrition, body condition, personal care, speech, habitation, mobility, responsibilities, interpersonal relationships, community living, leisure activities as well as education and work. The environmental factors are the constituents of a person's surroundings than can affect the realization of a living habit. Interactions between personal and environmental factors create needs that impact a person in the execution of his/her activities of daily living, thus limiting his/her social participation. A positive interaction between personal and environmental factors supports social participation while a negative interaction produces the development of handicap situations.
Definition of needs
Needs are subjective, since they are felt by the person (Talbot L. Les besoins de santé des individus. Unpublished manuscript). It could be a need for a resource to provide adequate and ample services. Bradshaw's taxonomy [9], used by Pineault and Daveluy [10], distinguishes four types of needs: normative, perceived, expressed and comparative. Normative needs are those that agree with norms, as defined by health professionals. Perceived needs are those perceived by individuals, depending on health services available. They become expressed needs, once articulated. Generalization of evaluated needs in a population results in comparative needs. Finally, needs depend on factors related to the person and his/her environment, on organizational factors, on factors related to the service providers [11]. As observed by repeated measures done in the post-stroke period, needs evolve with time, as do their response, depending on which services were provided. Furthermore, existing definition of needs seem to justify resource constraints rather than to satisfy health care needs of the person. The gap between perceived needs and normative needs is an area of improvement in the quality of services [21].
According to the HPP, rehabilitation needs would result from a discrepancy between the capacities of the person and the different factors of his/her environment [12]. These rehabilitation needs are associated with the handicap situations of the person in doing his/her daily activities, as compared to the most desirable level. Needs can therefore be multilevel (personal or environmental factors).
Using four groups of people (patients, caregivers, health care providers and administrators), the aim of this research was to investigate the expressed and normative rehabilitation needs of post-stroke elderly living in the community.
Methods
Instruments
As proposed by Morgan and Krueger [13], an inductive qualitative research tool was selected. The method of focus group discussion [13] was used with four groups of key-informants: patients, caregivers, health care providers and administrators. Focus groups are an effective method of obtaining data in new or ill-defined research fields. The method is divided in four phases: 1) establishing the questions; 2) planning the focus groups (number and size of groups, time and place of meetings, selection and recruitment of participants, choice of moderator); 3) leading of the focus group; 4) analysis and report. Participants (n = 25) were explained the aim and procedures of the study and agreed by signing a consent form. This research was approved by an ethics committee.
Recruitment procedure
In order to achieve experimental diversification, participants were identified by purposive selection. The patients (n = 4) and the caregivers (n = 5) were recruited through social workers from the local community service centers, daycare centers and also chosen from a data bank of participants to previous studies. Health care providers (n = 9) were solicited through directors of professional services and coordinators of rehabilitation or home-based services. They worked in different fields of healthcare and services, in rural and urban areas. Administrators (n = 7) were recruited through hospital managers who would identify which one was more familiar with the study clientele and worked in various rural and urban areas. All participants were recruited because of their critical abilities and their experience with needs related to the stroke process from onset to reintegration into the community. The area were the research took place is known as rural and semi-rural with a population of 150,000.
Data collecting procedure
Each of the four meetings lasted approximately two hours and was recorded on audiotape. A interview guide (Appendix 1 [additional file]) was built according to the method suggested by Morgan and Krueger [13]. Each group included a moderator and her assistant, an observer and a co-investigator. To make sure the participants would convey their perceived and expressed needs, the first meeting was held with the patients' group. Then followed the meetings with the caregivers, the health care providers and finally the administrators. The summary of the first meeting (group of patients) was used as an introduction to discussion for the second group; the third group benefited from the summary of the two previous ones and so forth.
Data analysis process
In order to ensure the validity of results, data was triangulated as described hereafter. During the last minutes of the meetings, the assistant-moderator would ask the participants to clarify some statements she had jotted down during the encounter. She would then sum up the meeting to validate its content with the participants, at which time they could complement, rectify or add to the information already given. This information along with the notes of the observer would help summarize the focus after each of the meetings. Later, a member of the team listened to the audiotape, allowing further analysis of the data. In the following weeks, each participant was sent a brief report of his/her focus group meeting. One week later, each participant was contacted to corroborate the content of the report. During these interviews, the comments of the participants testified to their understanding and approval of each report and allowed to add some details. Verbal and written summarized reports on the four groups were presented to the research team.
Normative and expressed needs were grouped according to the twelve categories of the HPP model. After analysis of the focus groups, two categories were added in order to include psychological-emotional needs as well as psychological-cognitive needs and the education and work categories were abandoned. The participants from the four groups identified their needs as: a) needs already fulfilled or not mentioned, b) needs partially fulfilled c) unfilled needs.
Results
Characteristics of the participants of the four focus groups are presented in Table 1. Patients were aged between 71 and 85 years old and most of them had suffered a stroke less than three years before and were identified as having severe to moderate limitations requiring more than 5 hours of assistance per week. None received home-based care from public services and only one in four was assisted by a relative about two hours a week. Most of the caregivers were retired women – aged between 42 and 60 years old – who took care of their disabled husband. Notice that the participants from this group were not related to the participants from the patients' group. Generally, the number of weekly care-giving hours varied from 8 to more than 20 hours.
Table 1 Description of characteristics of patients and caregivers
Patients characteristics n = 4 Caregivers characteristics n = 5
Age: Age:
71–75 years old 3 41–59 years 3
81–85 years old 1 60–69 years 2
Time since stroke: Current occupation:
2–3 years 3 Work outside home 1
4–8 years 1 Retired 4
Homecare public services Relationship with the stroke victim:
Yes 0 Wife 4
No 4 Daughter 1
Help from relatives: Length of caregiver's role:
Yes 1 (2 hrs/wk.) 3–4 years 2
No 3 More that 4 years 3
Level of education: Hours of weekly help:
Primary 2 8–12 hours 1
High-school 2 12–16 hours 1
16–20 hours 1
More that 20 hours 2
Type of help provided:
A.D.L. 5
I.A.D.L. 5
Psychological support 3
Other (stimuli) 3
ADL: activities of daily living
IADL: instrumental activities of daily living
Eight out of nine health care providers had a fairly good knowledge of stroke and seven of them had more than nine years of experience with a stroke clientele. They were from different professional fields: special education (1), occupational therapy (1), social work (2), neuropsychology (1), speech therapy (1), physiotherapy or physical rehabilitation therapy (3). These professionals practiced in an active care hospital (2), a CLSC (4), a daycare center (2), a day hospital (1) and a community organization (1). The administrators came from the same kinds of facilities with the addition of an intensive functional rehabilitation unit and a rehabilitation center. Four of the administrators had a restricted knowledge of stroke and had other customers aside from stroke patients. Two out of seven took care only of persons over 65 years old or with neurological problems. Education fields of the administrators were either management or health related disciplines.
The most important expressed needs of the patients were acceptance of their health problem (stroke) and accessibility to physiotherapy and occupational therapy services on an outpatient basis. Then subsequently followed the needs relating to adapted means of transportation, medical follow-up, home visit from healthcare personnel, and stimulus and motivation provided by a caregiver. Domestic help and encouragement from the healthcare personnel were also important needs that have been expressed. Patients were more communicative about their needs relating to community, their psychological and emotional needs, and house alteration requirements. Unfulfilled needs mainly included the occasional home visit from a health professional, domestic help, coaching by the CLSC and medical follow-up.
The foremost rehabilitation need identified by the caregivers was that the patient be loved, surrounded, and that he felt secure. These were followed by the necessity to make home adaptations, the need to inform the stroke patient and to provide him with physical and mental stimuli. Finally, the needs relating to tactile sensation problems, supportive care and attention, and acceptance of the situation were also important. It is worth noting that participating caregivers looked after individuals much more severely impaired than our group of patients. These caregivers mentioned the same categories of needs but in a different order of priority. For them, the psychological needs were the top priority; then came the need to adapt the home followed by community living needs. Notice that the beneficiaries had not resumed many of their social roles in the community. According to the caregivers, the less fulfilled needs were mainly related to psychological needs and associated with community living. Specifically, they concerned medication and its side effects, adaptation to this new situation for the caregiver and acceptance by the beneficiary. Respite, emergency help, supportive care and attention, training of family members were also needs partially fulfilled in these categories.
For the health care providers, the needs that were less fulfilled mainly concerned related to community living, psychological needs and speech impairment. More precisely, they included: leisure activities, awareness, long-term family support, bond between spouses, respect of the person's pace, delivery of timely and simplified medical information to the patient and his/her spouse, adaptation of the home and respite, because in rural areas, for instance, there is no specialized transportation.
Re-education for basic activities like eating or getting dressed and psychological assistance for acceptance, self-esteem and dignity were the most important. Followed the capacity to communicate and the family's need to be supported in understanding the health problem. Finally, long-term follow-up, simplification of the information given and home alterations also constituted essential needs, again according to the health care providers. For the most part, the health care providers worked with severely disabled persons. In their view, the interventions having to do with personal care held a priority over those concerning psychological needs and communication needs. As also identified by the caregivers, needs related to community living and the home followed.
In the administrators' view, a psychological support intervention made by the case manager, for instance, was more necessary in rural areas. They mentioned more "partially fulfilled" needs in the areas of speech, mobility and community living. They underlined the necessity to become sensitive to this clientele with cognitive problems and their needs for spirituality, means of transportation, financial support, the need to maintain and improve speech re-education.
Administrators emphasized their wish to ensure the complete management of the patient. They were interested in the list of needs identified by the patients, since the needs of the affected individuals cannot be dissociated from those of their family. Needs identified as a priority by the administrators were a stabilized health condition, recovery of biological, psychological and social abilities, compensation mechanisms, integration into the community and support in finding a new sense to one's life. The chronology of those needs was unanimous because it set a continuum in the rehabilitation process. Priority needs identified by the administrators seemed closer to those listed by the patients. Administrators seemed to believe the patients had made a fairly good functional recovery and insisted on needs related to community living, personal care and psychological well-being. Finally, they were the only ones to clearly talk about spiritual needs.
On the whole, unfulfilled needs were identified in the four groups as from categories relating to housing, community living, psychological and emotional needs. Table 2 summarizes the response to rehabilitation needs according to the categories of from the HPP model.
Table 2 Participants' perception of the response to rehabilitation needs
Patients Caregivers Health care providers Administrators
F PF U F PF U F PF U F PF U
Nutrition x nm nm nm
Body condition x x x x
Personal care x nm x x
Communication nm x x x
Housing x x x x
Mobility x nm x x
Responsibilities nm nm nm nm
Interpersonal relationships including sexuality x x x x
Community living x x x x
Leisure activities nm x x x
Psychological x x x x
Cognitive x x x nm
F: Need fulfilled; PF: Need partially fulfilled; U: Need unfulfilled; nm: Need not mentioned by this group of participants Note: the «education» and «work» categories were removed.
Although some of the categories were partially fulfilled for the health care providers and administrators, the gradient of the providers' opinion on each of the needs specifically mentioned, stood between "partially fulfilled" and "unfulfilled". Conversely, the gradient of the administrators' answers stood between "fulfilled" and "partially fulfilled". Interestingly, only the patients' group acknowledged nutrition needs.
Discussion
In Lewinter et al. [14], results from individual interviews show that the cognitive needs are not very well fulfilled, if at all, by the available rehabilitation services. Results from the current study tend to draw the same conclusions. Indeed, the patients from the groups mentioned they had to perform their own intellectual activities, in order to stimulate and maintain cognitive functions during rehabilitation and after reintegrating their home. Furthermore, the patients from the current study point out the lack of continuity between resources when discharged from rehabilitation services. This also corroborates the results of Zwygart-et al [15], who collected their data through a mail questionnaire, and those of Brandriet, et al. [16].
The perceived needs of the caregivers really stood out during focus groups and would be inseparable from those of the patients. Caregivers considered rehabilitation in terms of recovery and excluded compensation mechanisms. For instance, they were unable to imagine any possible means to compensate for poor vision, a need expressed by the patients. While patients referred to the psychological need of accepting the situation, caregivers mentioned the psychological need to face one's own limitations and the probability of complete rehabilitation. These results agreed with the study of Gauthier [17] who collected his data six to nine months post-stroke, and who noticed some unfulfilled psychological needs.
From our results, it seems that supporting the caregiver at the time of the hospitalization would allow him to offer a better support to the stroke victim. That support would perhaps allow acceptance of the situation and an active implication in the rehabilitation. Long-term follow-up and respect of the person's pace were mentioned as being important. Caregivers felt useful and appreciated this phase of the rehabilitation where attendance, supportive care and attention as well as information were provided at the day hospital. All groups pointed out the need for a more aggressive early re-education and a continuing rehabilitation. None of the groups mentioned needs pertaining to responsibilities. Finally, needs associated with sexuality were acknowledged by all groups, but none offered any solution.
Health care providers felt powerless, even frustrated, with so many needs to be fulfilled and so little human resources available. Health care providers proposed many possible avenues worth exploring in relation with community and some ways of addressing psychological problems.
The health care providers identified most of the partially fulfilled needs, ranging the whole continuum of the rehabilitation process. They pointed out the necessity for health system administrators to acknowledge expressed and normative needs of stroke patients. Adding human resources would begin solving the problem. Patients who benefit from intensive rehabilitation (about 10% of the stroke clientele) are treated according to their impairments in order to diminish their disabilities and improve their functionality. Services to help the family and to modify to the physical environment are usually available. The only help rarely provided is that of fulfilling psychological or cognitive needs and supporting social integration. However for 90% of the stroke clientele who only benefits from rehabilitation services at the acute care hospital, little of their needs are fulfilled.
This data concurs with that of Lewinter et al. [14] on the inadequate length of rehabilitation services, as reported by patients and caregivers. As inferred by these focus group discussion, it would appear more important, in the current health system, to assess capabilities and impairments of the stroke patients than to offer proper services to fulfill their expressed needs. And yet, the same health care providers considered the assessment more important to their own normative needs than to those of the patients.
In general, the answers of the administrators were based on what the resources should offer instead of on the accessibility to services, which they were less aware of. It seems that most of the participating administrators were preoccupied by the needs of the patients throughout the whole process and not only when they were using their services. They proposed solutions focused on the needs of the patient and on the most adequate resource to fulfill those needs at this stage of the rehabilitation process. In fact, the need for specially trained personnel to help prevent contractures and dehydration, as well as spiritual needs, were reported by administrators from chronic care facilities. Spiritual needs had also been reported by McLean et al. [18] in their pilot study with individual interviews. Administrators were much more precise in their description of the patients' sexual needs than the health care providers. This need was also described in the Lewinter et al. [14] study, but solutions have yet to be proposed. Since they are often consulted on this topic, the administrators were surprised the health care providers had so little to say about it. Admitting that the providers may be uncomfortable about their patient's sexuality, administrators sometimes provide counselling themselves.
Regarding prevention and treatment of secondary impairments, which is the second stage of the rehabilitation process described by Duncan, et al. [19], administrators pointed out the importance of intense early rehabilitative interventions, no matter how old the stroke victim was. They noticed gaps in the early rehabilitation process that bear long-term repercussions. They identified a lack or resources or of specific knowledge as possible reasons of these impairments in those services where the priority is to have versatile care providers to work with a diversified clientele. They also mentioned the importance of integration to promote long-term rehabilitation. They seemed to trust existing services and the competence of health care providers regarding functional rehabilitation and compensation needs. Even though the administrators said that all services were available, they acknowledged the necessity of a resource person to help access these services. In a system where, it seems, the responsibility of answering the needs of stroke patients is being discarded, case managers and administrators will share this difficult task of making services available and guiding the patients towards them. It is interesting to note the discrepancy between the perception of fulfilled needs identified by the patients and the caregivers and those identified by the health care providers and administrators. This inconsistency shows that the two categories of needs in Bradshaw's taxonomy [9], namely the perceived and expressed needs (patients and caregivers) are different from the normative needs (health care providers and administrators).
Strengths and limits
Many strengths and limitations have to be mentioned. Methodologically speaking, holding the first meeting with the patients' focus group ensured a valid identification of their needs, as they were perceived. As for the other participants, recruitment was done in a rigorous manner in order to obtain a fairly equal number of representatives from rural and urban areas, from various professions, and from different types of rehabilitation resources, including representatives of community organizations. It should be mentioned that recruitment of the patients and caregivers was difficult; participants from these two groups were probably not typical of persons being dismissed to their home after a stroke. However, the fact that the severity of the stroke ranged from severe to mild in those two groups increases the external validity of the results.
Recall bias is significant in this study as patients and caregivers had to recall events that took place few years ago.
The implication of the four groups of participants ensures a better validity of the data as was suggested by Liu and Mackenzie [20]. The rigorous triangulation analysis also ensures a good validity of the results. Data collection having been done more than two years after the stroke allowed for identification of needs in the continuing process of rehabilitation, until social integration. The obvious needs concern the actual day-to-day living of the elderly, because the study was intended for stroke patients who were over 65 years old when they had their stroke. During the focus group discussions, patients who had suffered a stroke at least two years before conveyed their perception of unfulfilled needs all through the rehabilitation process. However, the "unfulfilled" perception may have been attributable to memory loss. Nevertheless, since the results from this group of participants agree with those from the caregivers' and health care providers' groups, and sometimes even with those of the administrators' group, it seems that the cause is to be attributed to the inaccessibility to services, their unavailability or a poor knowledge of their existence. To help clarify this question, a multi-center longitudinal study is ongoing to follow-up on the evolution of the needs in rehabilitation for post-stroke victims after being released to their home.
Conclusions
After a stay in an active care hospital (ACH), before the patient is discharged, a meeting between family members and a stroke specialist (social worker, nurse and volunteer worker having had similar experience) could allow discussions about a possible mental depression of the stroke patient and about upcoming difficulties. It would also be necessary at this time to give the caregivers information on their loved one's health status and to inform them of their future needs.
After hospital discharge, a specially trained healthcare worker could remain available by telephone to counsel the caregivers. Finally, a psychological follow-up of the caregiver would allow him to better support his/her relative in his/her rehabilitation process. After discharge from the hospital or from the rehabilitation center, a better communication between healthcare facilities and increased availability of services at the CLSC – like twice a year home visits by a health care provider – are suggested by the patients. As concluded by Lewinter et al [14], it seems that a professional psychological follow-up to discuss acceptance and consequences of non-acceptance would favour mid- to long-term rehabilitation.
Recommendations to health services
Improving accessibility to services, respecting priority parking spaces for the disabled and promoting public cooperation would allow for a better social integration and recovery of social roles. On the whole, a better distribution of financial resources between institutions having to deal with this clientele, would allow long-term support of the person and his/her family. Health care providers first suggest that full rehabilitation teams (from different professional fields) be created (for example stroke team). They also propose the appointment of a case administrator or pivotal health care provider, based on the total system concept in healthcare, which would simplify communication between partners (hospitals, local community service centers, rehabilitation centers, daycare centers...). Services would be more suited to the needs of the individual and available for the families. Intervention priorities would be centered on needs expressed by the person. Education programs on how to deal with different types of clienteles would be made available to the health care providers to help them adjust to the difficulties associated with all kinds of issues. For mid- to long-term needs, improving means of transportation, adding support groups in rural areas, improving long-term follow-up in urban areas, humanizing of care, making information accessible, educating the neighbours and demystifying stroke by informing the public, would help integration and recovery of social roles to counter handicap situations. Finally, it is imperative to consider the perceived and expressed needs of the patients and caregivers and to integrate those needs with the normative needs identified in planning rehabilitation programs.
Supplementary Material
Additional File 1
Appendix 1: Course of the group discussions for the patients, caregivers, health providers and administrators
Click here for file
Acknowledgments
We wish to express our recognition towards the Réseau de recherche en gérontologie for their financial support.
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| 15383147 | PMC524186 | CC BY | 2021-01-04 16:38:12 | no | Health Qual Life Outcomes. 2004 Sep 21; 2:53 | utf-8 | Health Qual Life Outcomes | 2,004 | 10.1186/1477-7525-2-53 | oa_comm |
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World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-2-321546178810.1186/1477-7819-2-32ReviewRole of primary surgery in advanced ovarian cancer Münstedt Karsten 1karsten.muenstedt@gyn.med.uni-giessen.deFranke Folker E 2folker.e.franke@patho.med.uni-giessen.de1 Department of Obstetrics and Gynecology, Justus-Liebig-University of Giessen, Klinikstrasse 32, D 35385 Giessen, Germany2 Institute of Pathology, Justus-Liebig-University Giessen, Langhansstrasse 10, D 35385 Giessen, Germany2004 2 10 2004 2 32 32 4 7 2004 2 10 2004 Copyright © 2004 Münstedt and Franke; licensee BioMed Central Ltd.2004Münstedt and Franke; 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
Major issues in surgery for advanced ovarian cancer remain unresolved. Existing treatment guidelines are supported by a few published reports and fewer prospective randomized clinical trials.
Methods
We reviewed published reports on primary surgical treatment, surgical expertise, inadequate primary surgery/quality assurance, neoadjuvant chemotherapy, interval debulking, and surgical prognostic factors in advanced ovarian cancer to help resolve outstanding issues.
Results
The aim of primary surgery is a well-planned and complete intervention with optimal staging and surgery. Surgical debulking is worthwhile as there are further effective treatments available to control unresectable residual disease. Patients of gynecologic oncology specialist surgeons have better survival rates. This may reflect a working 'culture' rather than better technical skills. One major problem though, is that despite pleas to restrict surgery to experienced surgeons, specialist centers are often left to cope with the results of inadequate primary surgical resections. Patients with primary chemotherapy or those who have had suboptimal debulking may benefit from interval debulking. A proposal for a better classification of residual tumor is given.
Conclusions
Optimal surgical interventions have definite role to play in advanced ovarian cancers. Improvements in surgical treatment in the general population will probably improve patients' survival when coupled with improvements in current chemotherapeutic approaches.
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Background
The Fédération Internationale de Gynécologie et d'Obstétrigue (FIGO) classifies ovarian carcinoma in stage I to IV [1,2]. Stage I has been defined as growth limited to the ovaries; stage II as growth involving one or both ovaries with pelvic extension; stage III as tumor involving one or both ovaries with peritoneal implants, and outside the pelvis and/or positive retroperitoneal or inguinal nodes and stage IV as having distant metastasis [1,2].
Tumors in stages I and II are generally considered to represent early disease, while stages III and IV evince late or advanced disease [3,4]. The strong prognostic value of the FIGO classification system has been proved in number of studies [5].
Unfortunately, most ovarian carcinomas are detected only when they are advanced. Results of studies evaluating screening by tumor markers (a raised CA125 value) and/or ultrasonography to detect early disease are not clear [6,7]. Ultrasonography may become an increasingly important tool as it has been associated with higher detection rates in early stage disease and in patients with a genetic predisposition to tumor [8-11]. However, use of proteomics will perhaps identify more ovarian carcinomas at early stages in the future [12].
Though controversial till 70s, surgery is now recognized an integral part of the treatment armamentarium in advanced ovarian carcinoma. Aure et al., [13] presented convincing evidence that extensive tumor removal resulted in better survival even in advanced stage disease and introduced the idea of primary tumor debulking surgery. The value of primary debulking surgery was confirmed and its theoretical background was elucidated by Griffith and Fuller [14]. Subsequent work showed that debulking surgery improves an adverse vegetative function and nutritional problems such as loss of appetite and nausea [15,16]. It was also suggested that primary debulking surgery removes therapy-resistant tumor cells and increases the number of proliferating tumor cells (the Gompertzian phenomenon), which makes these cells more susceptible to subsequent chemotherapy [17-19]. These early hypotheses have partly been confirmed by the finding of increased postoperative tumor proliferation rates in patients after surgery [20].
Ongoing discussions about quality assurance and guideline-based therapy had helped to foster the impression that the main issues in treating ovarian cancer have been resolved and that the value of each procedure involved has been supported by high levels of scientific evidence [21-23]. Closer inspection reveals that it is not true. Only a few treatment guidelines are supported by published reports, and even fewer by prospective randomized clinical trials. However, we strongly believe the value of retrospective studies is greatly underestimated. Recent analyses show that the treatment effects assessed by observational studies do not greatly differ in magnitude or quality from those published in randomized, controlled trials [24,25]. Furthermore, biases created by the selection criteria inherent in prospective randomized trials are frequently ignored.
Thus, in this article we will concentrate on looking more closely at several issues in surgical treatment, their effects and importance in relation to outcome in advance ovarian cancer.
Primary surgical treatment
The utility of primary surgery for advanced ovarian cancer is well established. Its aim should be a well-planned, extensive and complete intervention. Thus, no facility should offer surgery for patients with ovarian cancer if adequate standards of care cannot be met.
The optimal preparation of patients for surgery is very important. Patients must be in a position to give fully informed consent to any additional surgical procedures found necessary during the operation. They should also undergo colonic lavage, which will provide the surgeon with better access to the lymph nodes and reduce risks in cases where intestinal surgery is undertaken. Where cytological evaluation of peritoneal fluid aspired preoperatively, a raised concentration of serum CA125, or ultrasound results indicate advanced malignancy, the patient should be transferred to a specialist surgeon (see below).
Many cases where the staging is not clear, laparoscopy appears to be good tool for obtaining a definitive histological diagnosis in advanced ovarian cancer and helps in planning the best surgical approach. Laparoscopic staging, in particular, can give a clear view of the extent of surgery required and the difficulties that may be expected, and it may be helpful in selecting patients for primary (neoadjuvant) chemotherapy [26]. Video recording can document the findings during laparoscopy and can be used subsequently by the surgeon to plan optimal debulking surgery.
However, laparoscopic surgery of any suspicious adnexal mass is not encouraged unless the risk of capsular rupture and tumor spill is minimized by the use of endobags [27]. No cystic mass which is >10 cm in diameter and/or adherent to the lateral pelvic wall should be removed laparoscopically [28].
The fear due to some in-vitro and animal studies that showed carbon dioxide pneumoperitoneum has adverse effects on outcomes is probably unfounded, as a recent analysis from second-look laparoscopies showed no influence of pneumoperitoneum on overall survival [29]. Certainly, more data on this issue is required.
Since laparoscopy may increase tumor growth rates, delays between laparoscopy and definitive surgery should be avoided [30]. Although this view has not yet been supported by any other study, we believe that the time between the suspected diagnosis of advanced ovarian cancer and surgery should be kept as short as possible. Delays may result in a higher preoperative tumor mass which has been identified as an adverse prognostic factor [31].
Surgical staging
Tumor stage is one of the primary prognostic factors. Appropriate staging is vitally important for effective postoperative therapeutic decision-making. Patients who have been accurately staged as stage I may not require adjuvant chemotherapy [32,33].
Requirements for appropriate staging after total abdominal hysterectomy and bilateral salpingo-oophorectomy include multiple cytological washings, random biopsies from the peritoneum and the diaphragm, omentectomy and lymphadenectomy. The value of peritoneal cytology is supported by prospective studies [34]. There are several issues surrounding lymphadenectomy, and these are discussed later. In two studies, optimal staging resulted in 30% to 50% of the patients being reclassified to a higher stage – a fact which has implications for subsequent treatment [35,36]. A classification system for determining the quality of surgical staging was introduced recently and is shown in Table 1[33]. However, it may be only helpful for comparisons of older studies since optimal staging is a prerequisite of later therapeutic decisions.
Table 1 Surgical quality categories for staging of ovarian carcinomas (based on Trimbos et al. 2003)
Category of surgical quality Staging procedures included
Optimal - Inspection and palpation of all peritoneal surfaces; biopsies of any suspect lesion for metastasis; peritoneal washings; infra-colic omentectomy; blind biopsies of the right diaphragm and right and left para-colic gutter, pelvic side-walls of the ovarian fossa, of the bladder peritoneum and of the cul-de-sac and sampling of iliac and para-aortic lymph nodes
Modified - Everything between optimal and minimal staging
Minimal - Inspection and palpation of all peritoneal surfaces and the retroperitoneal area; biopsies of any suspect lesions for metastasis; peritoneal washing; infracolic omentectomy
Inadequate - Less than minimal staging but at least careful inspection and palpation of all peritoneal surfaces and the retroperitoneal area; biopsies of any suspect lesion for metastasis
Extent of surgery
In addition to the staging procedures mentioned earlier, optimal surgical treatment for ovarian cancer comprises tumor removal; removal of remaining ovaries, uterus, and fallopian tubes, omentectomy, and radical para aortic and pelvic lymphadenctomy [3,37]. The German national treatment guidelines recommend a simultaneous appendectomy and removal of the cul de sac over the peritoneum of the small pelvis [38]. Since removal of all grossly visible tumor is considered crucial for long-term survival, surgery should be extended to include hemicolectomy, splenectomy and stripping of the peritoneal reflection of the diaphragm when the tumor masses infiltrate the entire abdominal cavity, the colon, the diaphragm or other structures respectively.
Although the reasoning behind performing these measures seems convincing, only lymphadenectomy has been partly evaluated in a prospective, randomized trial. The previously held belief that mere palpation of lymph nodes is sufficient to gauge nodal status was refuted in this study [39].
Lymphadenectomy plays a triple role in the treatment of ovarian cancer. First, it is of diagnostic value since tumors of apparently early stage show nodal involvement in about 20% to 40% of the cases [40], If found positive, the tumor must be classified as stage IIIc. Secondly, lymphadenectomy is of immense prognostic value. Most importantly, lymphadenectomy may also have a therapeutic effect as retrospective studies comparing lymphadenectomy with no lymphadenectomy reported a survival benefits with this procedure [41-43]. The data on lymphadenectomy is however conflicting with one study showing that the patients with stage III disease (tumor residuals >2 cm) that has been debulked suboptimally do not benefit from lymphadenectomy [44]. Other workers report no benefit even if the residual tumor size is smaller (1 cm) [45]. Though not fully published, the only prospective, randomized trial shows that systematic lymphadenectomy did not result in better survival compared to selective lymphadenectomy [46]. Mainly based on the retrospective findings current views on treating stage III disease suggest: systematic lymphadenectomy in cases of residual tumors <1 cm, nodal debulking only where tumors are larger than intra-abdominal residuals, and nodal sampling in stage IV disease with pleural effusions only [47].
To the best of our knowledge, there has been no study testing the benefit of hysterectomy or omentectomy. However, the concurrent incidence of endometrial carcinoma in 10% to 25 % of patients, or its precursors in about 30% to 50% of all ovarian cancers justifies this procedure [48,49].
Optimal debulking
Ovarian cancer is one of the tumors where surgical debulking is considered worthwhile. This is due to availability of further effective treatments that are available to control the unresectable residual disease. As early as 1934, Meigs suggested that maximum cytoreductive surgery was beneficial [50]. Many years later, in 1968, Munnell followed this idea and proposed the idea of 'maximum surgical effort' [51]. He distinguished between definitive surgery, partial removal of the tumor and biopsy only. Since partial removal covers a wide range of interventions that requires varying amount of efforts, optimal debulking was distinguished from suboptimal debulking. Although there is no generally accepted definition, most early studies considered a residual tumor size of <2 cm as optimal [52]. In a more recent survey among gynecological oncologists from United States of America (USA), 12% of the responders defined optimal debulking surgery as no visible tumor residuals, while 14% described it as residual tumor masses less than 0.5 cm. However, 61% chose a 1 cm threshold and 13% considered a tumor of 1.5 cm to 2.0 cm as optimal [53]. Comparative analysis of diameters of various residual diseases has shown that there exists some sort of a threshold at 2 cm, above which no significant differences in survival can be found. In contrast, subset analyses of smaller diameters in residual disease show improved patient prognosis [54]. This variation in the interpretation of thresholds with prognostic impact calls for a commonly accepted definition (see concluding remarks) and more controlled trials, that need to be non-randomized as it will not be ethically possible to leave some tumor behind.
The results of an earlier meta analysis on cytoreductive surgery might have been flawed not only due to absence of clear definitions but also due to the combined effects of subsequent chemotherapy [52]. In this study, the then novel, platinum-containing chemotherapy had a stronger impact on survival than cytoreductive surgery. A recent and otherwise comparable meta analysis however, confirms the greater survival benefit of patients undergoing maximum cytoreduction [55]. Another interesting study stated that optimal cytoreduction means no visible residual tumor [31]. It has been further shown that the volume of the residual tumor and the success of subsequent chemotherapy are interdependent [56].
Expertise of gynecological oncology surgeons
Based on available evidence it is generally accepted that the experience and technical expertise of a surgeon are important prognostic factors. Comparisons of overall survival in patients treated by gynecological oncology, gynecologists and general surgeons have shown that patients treated by surgeons trained in gynecology (gynecological oncology) have a significantly better prognosis [57,58]. This finding may not reflect primarily on the technical skills of these surgeons but rather reflection the 'environment' in which they work – where views and thoughts on the biology of advanced tumors are freely shared and patients are often treated by a team rather then individuals. As for surgeons there are only select patients with uncommon neoplasms like gastrinomas, glucagonomas, stomatostatinomas, and VIPomas, who profit from debulking surgery with particular reference to prevent deleterious hormonal side-effects [59]. It is expected that new chemotherapy and immunotherapeutical approaches will probably lead to a re-evaluation of debulking surgery as a complementary approach [60-62]. Till such time where definite evidence is available, it is strongly recommended that all patients should be treated by a gynec-oncologist. There had been constant calls to regionalize specialist surgery, however, no studies have yet shown better survival in patients treated by 'high volume' operators or such specialists [63,64]. A recent study on quality control from Hesse, Germany, showed striking deficiencies even at central-referral hospitals [23]. Treatment by a multidisciplinary team of specialists, has been shown to increase patients' chances of survival without any disputes [65,66]. Patients probably benefit most from being treated in centers which promote excellent scientific exchange, and continuous education and self-evaluation among surgeons besides providing multidisciplinary approach to management.
Coping with inadequate primary surgery
Surgical treatment of advanced ovarian cancer is one of the most demanding procedures in gynecological surgery. Despite repeated requests to restrict surgery to experienced surgeons, considerable numbers of patients are still operated by others. A population based study from Germany showed that omentectomies were performed in about 50% of all cases of ovarian cancer and lymphadenectomy were carried out only in 30% [22]. Another study from USA showed that only about half of the patients receive 'standard' care [68]. In spite of the establishment of gynecological oncology as a specialty in the USA, fewer than half of the patients were originally seen by such a specialist [68]. More over the terminologies like "standard" are not defined well.
The situation with regard to specialism depends strongly on the medical infrastructure, and varies from country to country and region to region. However, the problem of inadequate primary surgery is real, and coping with it is a frequent task in specialist centers even in developed countries. The question is what should be done for the patient concerned? Interestingly, this is something that cannot be found in textbooks [3,69,70]. Some of the literature suggest re-laparotomy by experienced surgeons to achieve reductions in all possible tumor mass [71,72] however, there is no evidence to support this strategy.
In general, one of two situations occurs. First patients present with no evidence of macroscopic tumor residuals but staging procedures and/or operative measures were omitted. Computed tomography (CT) or Magnetic resonance imaging (MRI) to identify enlarged lymph nodes or possible residual tumors in these situations may help to decide on the need for second surgery. The belief that tumor cells in retroperitoneal lymph nodes are better able to survive chemotherapy is supported by low cytotoxic drug concentrations in these [73]. Therefore, it is reasonable to consider enlarged lymph nodes as a decisive factor favoring a direct surgical approach. It is interesting to note that in endometrial carcinomas, a clinically negative omentum was also found to be histologically negative in most cases (sensitivity 89%) [74].
Patients with residual tumor mass have to be evaluated to determine if it is possible to achieve no residual tumor or microscopic residual tumor by immediate secondary surgery. Although immediate laparotomy seems to be a good idea, the limited capacity for surgery at specialist departments and delays in having the surgery are to be considered. The peritoneum shows inflammation shortly after surgery reaching a high about 7 to 14 days afterwards [75]. Surgery at this time is considered far more complicated and may result in higher blood loss and greater risk of injury to neighboring abdominal organs [76]. However, waiting for the inflammatory processes to resolve will give the tumor further time to proliferate [20]. Therefore, interval debulking surgery after three courses of chemotherapy should be considered as an appropriate alternative.
Neoadjuvant chemotherapy
Disease spread >2 cm to the spleen, diaphragm, liver surface, mesentery, or gallbladder is generally believed to be inoperable. However, even these patients may often undergo effective debulking procedures [26,77]. As mentioned earlier, laparoscopy can be used to reach decisions on surgery. The only problem with laparoscopy in combination with neoadjuvant chemotherapy is a 30% rate of port site metastasis, which is believed to be a result of the pneumoperitoneum procedure created for laparoscopy [78]. These metastases should be excised at the time of any subsequent surgery [79].
An analysis of several retrospective studies on neoadjuvant chemotherapy showed that there are no good reasons to assume that this approach is associated with a poorer prognosis [26]. The European Organisation for Research and Treatment of Cancer (EORTC) protocol 55971 comparing upfront tumor debulking surgery with neoadjuvant chemotherapy in patients with stage IIIc or IV disease is accruing and its results will provide better insights on this issue.
Interval tumor debulking
Interval debulking, is another approach to reduce tumor burden between the cycles of chemotherapy. It has been evaluated in two prospective randomized trials [80,81]. The EORTC study showed a clear survival advantage for interval debulking (still noted in the 2001 update), the Gynecologic Oncology Group (GOG-152) study has, as yet, failed to show any benefit from interval debulking [80,81]. Patients with residual tumor >1 cm received three courses of cyclophosphamide/cisplatinum in the EORTC study [80] or three courses of paclitaxel/cisplatinum in the GOG-152 study. In both studies, patients who did not respond to chemotherapy were removed from the study. Those who responded were randomized to either secondary surgery or no surgery. Afterwards, all patients received three more courses of the earlier chemotherapeutic regimen.
Although there seem to be only minor differences in the design of both trials, a closer look shows that in the GOG-152 study, the number of stage IV patients was lower (6%) compared with the EORTC (21%) study, the performance status was better, and there was less residual tumor. This was due to the eligibility criteria for GOG 152 which stated that patients should have had surgery with maximal effort to resect the uterus, tubes, ovaries, omentum, and all gross residual ovarian cancer at the time of primary surgery.
The questions about the benefit of interval debulking surgery remain unresolved. However, it appears that patients who have had neoadjuvant chemotherapy or suboptimal debulking may profit from this treatment, while those who have undergone primary, maximum effort surgery by a gynecological oncologist are less likely to profit from it [82].
Surgical prognostic factors
Size of the residual tumor, volume of the residual disease and experience of the surgeon are important prognostic factors [56,77]. Among these, only few can be influenced by human intervention. Except for dose intensity of chemotherapy, recent literature indicates that the hemoglobin concentrations before chemotherapy are of prognostic value [83,84]. The latter may be influenced by the use of erythropoietin which has shown positive effects on survival in cervical cancer [86].
As mentioned above, the frequently used definition of <2 cm for optimal debulking is arbitrary since every further reduction in the size of residual tumor improves the prognosis [54]. Thus, each threshold between 0 and 2 cm will have its own prognostic relevance. While the criterion 'diameter of residual tumor' reflects tumor cell hypoxia and reduces the pool of proliferating tumor cells susceptible to chemotherapy, the criterion 'residual tumor volume' alludes to the removal of therapy-resistant tumor cells, which are believed to be responsible for early recurrences. A comparison of both criteria in relation to their prognostic impact has shown that residual tumor volume is of greater importance [56]. As shown in subgroup analyses of the intergroup trial confirming the results of the GOG-111 study, a possibly superior chemotherapeutic regimen containing taxanes cannot compensate for the tumor left behind after primary surgery [19].
Future trends
It is difficult to assess the future role of surgery in advanced ovarian cancer. Neoadjuvant chemotherapy may become more important. However, as the tumor debulking surgery works, except in stage IV patients with solid distant metastasis, it may be worth trying combined ultrasound-guided laser interstitial thermotherapy for non-resectable liver metastasis with conventional debulking surgery [87]. Apart from technical innovations, quality control, quality assurance and documentation of patient outcomes after surgery will probably play major parts in treatment improvements.
Conclusion
Numerous studies have analyzed the effects of various kind of chemotherapy in ovarian cancer. In contrast, only a few prospective randomized studies have focused on surgical issues in this type of tumor [46,80,81]. This lack of surgical trials has probably contributed to inhomogenous definitions regarding the terminology of surgical interventions and surgical stages (early compared with late) and the classification of operative success in general.
In future, we must aim to ensure that all patients are treated along the generally accepted guidelines and receive optimal debulking surgery which leaves only microscopically detectable residual tumor as shown in number of studies; it is certainly unethical at present to evaluate this procedure in randomized clinical trials (see Introduction). Other then this, there are many other relevant issues which need to be resolved or clarified with special reference to neoadjuvant chemotherapy, interval debulking, the surgeon's training, and inadequate primary treatment. It would certainly be very helpful to demonstrate clearly the consequences of what is supposed to be an inadequate treatment.
The simple dichotomization of FIGO stages to early or late does not correspond to any diagnostic, biological or therapeutic advantage. We believe that it is far more reasonable to consider stage I alone as early disease (perhaps even only stage Ia and b), stages II and III (perhaps even stage IV with pleural effusions) as intermediate disease, and stage IV with organ metastasis as advanced disease. Such a classification would follow current views on treatment, since early ovarian carcinomas are treated primarily by surgery (eventually fertility-sparing) and adjuvant chemotherapy in cases of increased risk, intermediate ones by surgery and routine chemotherapy, and advanced disease by chemotherapy only. Thus far, results of studies on stage IV patients with organ metastases are inconsistent regarding the benefit of surgery. This is another issue to be resolved [88]. In this respect, FIGO may find subdividing stage IV into stage IVa (pleural effusions) and IVb (organ metastasis) worthwhile.
Disappointingly, the Tumor-Nodes-Metastasis (TNM) classification follows the FIGO system and violates its own principles by not accepting distant peritoneal metastasis as a natural indicator of primary tumor size but also by summarizing a nodal-positive disease stage as T3c (corresponding to FIGO IIIC) regardless of intra-abdominal findings. This inconsistency has already created curious confusions in current research. Nodal involvement has been shown to impair prognosis, however, smaller intra-abdominal tumors with nodal involvement (presented as stage I to IIIb disease but, by definition, all stage IIIC) show a significantly better prognosis than extensive intra-abdominal tumor masses (again stage IIIC) [89].
Furthermore, residual disease should be properly defined. The most rational approach is to regard microscopic residuals as optimal. Case series claim that experienced gynecologic-oncologic surgeons can clear up to 85% of patients in the unfavorable subgroups (FIGO stage IIIc and IV) of all visible tumor, leading to an extraordinarily high five year survival rate of about 50% [77]. As discussed (see surgical prognostic factors), a good definition of residual tumor would include aspects of both residual tumor size and volume. A proposal is made in Table 2.
Table 2 Surgical documentation of residual tumor after debulking of ovarian carcinomas
Residual tumor status* Maximum diameter of residual tumor Maximum total volume of residual tumor
Optimal Microscopic No visible tumor
Minimal < 1 cm ≤ 10 cm3
Intermediate 1 – 2 cm > 10 cm3 but ≤ 100 cm3
Gross > 2 cm > 100 cm3
*To assign residual tumor to a certain status, both criteria, diameter and volume, have to be fulfilled. Otherwise the next lower category should be used.
In summary, more attention need be paid to surgery for advanced ovarian cancer. These include necessary improvements in treatment in the general population, uniform definitions and terminology, and increasing number of surgical clinical trials. Extrapolating from the results of truly optimal ovarian cancer surgery, we believe that improvements in surgery will lead to better patient survival than improvements in current chemotherapeutic approaches [55,90,91].
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
KM and FEF both participated equally in literature search, conceptualization and preparation of the manuscript. Both authors have read the manuscript and approve it for publication.
Acknowledgments
The author takes the opportunity to thank Professor Dr. Wolfgang Künzel, FRCOG, for his helpful comments on the manuscript.
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| 15461788 | PMC524187 | CC BY | 2021-01-04 16:38:38 | no | World J Surg Oncol. 2004 Oct 2; 2:32 | utf-8 | World J Surg Oncol | 2,004 | 10.1186/1477-7819-2-32 | oa_comm |
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World J Surg OncolWorld Journal of Surgical Oncology1477-7819BioMed Central London 1477-7819-2-321546178810.1186/1477-7819-2-32ReviewRole of primary surgery in advanced ovarian cancer Münstedt Karsten 1karsten.muenstedt@gyn.med.uni-giessen.deFranke Folker E 2folker.e.franke@patho.med.uni-giessen.de1 Department of Obstetrics and Gynecology, Justus-Liebig-University of Giessen, Klinikstrasse 32, D 35385 Giessen, Germany2 Institute of Pathology, Justus-Liebig-University Giessen, Langhansstrasse 10, D 35385 Giessen, Germany2004 2 10 2004 2 32 32 4 7 2004 2 10 2004 Copyright © 2004 Münstedt and Franke; licensee BioMed Central Ltd.2004Münstedt and Franke; 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
Major issues in surgery for advanced ovarian cancer remain unresolved. Existing treatment guidelines are supported by a few published reports and fewer prospective randomized clinical trials.
Methods
We reviewed published reports on primary surgical treatment, surgical expertise, inadequate primary surgery/quality assurance, neoadjuvant chemotherapy, interval debulking, and surgical prognostic factors in advanced ovarian cancer to help resolve outstanding issues.
Results
The aim of primary surgery is a well-planned and complete intervention with optimal staging and surgery. Surgical debulking is worthwhile as there are further effective treatments available to control unresectable residual disease. Patients of gynecologic oncology specialist surgeons have better survival rates. This may reflect a working 'culture' rather than better technical skills. One major problem though, is that despite pleas to restrict surgery to experienced surgeons, specialist centers are often left to cope with the results of inadequate primary surgical resections. Patients with primary chemotherapy or those who have had suboptimal debulking may benefit from interval debulking. A proposal for a better classification of residual tumor is given.
Conclusions
Optimal surgical interventions have definite role to play in advanced ovarian cancers. Improvements in surgical treatment in the general population will probably improve patients' survival when coupled with improvements in current chemotherapeutic approaches.
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Background
The Fédération Internationale de Gynécologie et d'Obstétrigue (FIGO) classifies ovarian carcinoma in stage I to IV [1,2]. Stage I has been defined as growth limited to the ovaries; stage II as growth involving one or both ovaries with pelvic extension; stage III as tumor involving one or both ovaries with peritoneal implants, and outside the pelvis and/or positive retroperitoneal or inguinal nodes and stage IV as having distant metastasis [1,2].
Tumors in stages I and II are generally considered to represent early disease, while stages III and IV evince late or advanced disease [3,4]. The strong prognostic value of the FIGO classification system has been proved in number of studies [5].
Unfortunately, most ovarian carcinomas are detected only when they are advanced. Results of studies evaluating screening by tumor markers (a raised CA125 value) and/or ultrasonography to detect early disease are not clear [6,7]. Ultrasonography may become an increasingly important tool as it has been associated with higher detection rates in early stage disease and in patients with a genetic predisposition to tumor [8-11]. However, use of proteomics will perhaps identify more ovarian carcinomas at early stages in the future [12].
Though controversial till 70s, surgery is now recognized an integral part of the treatment armamentarium in advanced ovarian carcinoma. Aure et al., [13] presented convincing evidence that extensive tumor removal resulted in better survival even in advanced stage disease and introduced the idea of primary tumor debulking surgery. The value of primary debulking surgery was confirmed and its theoretical background was elucidated by Griffith and Fuller [14]. Subsequent work showed that debulking surgery improves an adverse vegetative function and nutritional problems such as loss of appetite and nausea [15,16]. It was also suggested that primary debulking surgery removes therapy-resistant tumor cells and increases the number of proliferating tumor cells (the Gompertzian phenomenon), which makes these cells more susceptible to subsequent chemotherapy [17-19]. These early hypotheses have partly been confirmed by the finding of increased postoperative tumor proliferation rates in patients after surgery [20].
Ongoing discussions about quality assurance and guideline-based therapy had helped to foster the impression that the main issues in treating ovarian cancer have been resolved and that the value of each procedure involved has been supported by high levels of scientific evidence [21-23]. Closer inspection reveals that it is not true. Only a few treatment guidelines are supported by published reports, and even fewer by prospective randomized clinical trials. However, we strongly believe the value of retrospective studies is greatly underestimated. Recent analyses show that the treatment effects assessed by observational studies do not greatly differ in magnitude or quality from those published in randomized, controlled trials [24,25]. Furthermore, biases created by the selection criteria inherent in prospective randomized trials are frequently ignored.
Thus, in this article we will concentrate on looking more closely at several issues in surgical treatment, their effects and importance in relation to outcome in advance ovarian cancer.
Primary surgical treatment
The utility of primary surgery for advanced ovarian cancer is well established. Its aim should be a well-planned, extensive and complete intervention. Thus, no facility should offer surgery for patients with ovarian cancer if adequate standards of care cannot be met.
The optimal preparation of patients for surgery is very important. Patients must be in a position to give fully informed consent to any additional surgical procedures found necessary during the operation. They should also undergo colonic lavage, which will provide the surgeon with better access to the lymph nodes and reduce risks in cases where intestinal surgery is undertaken. Where cytological evaluation of peritoneal fluid aspired preoperatively, a raised concentration of serum CA125, or ultrasound results indicate advanced malignancy, the patient should be transferred to a specialist surgeon (see below).
Many cases where the staging is not clear, laparoscopy appears to be good tool for obtaining a definitive histological diagnosis in advanced ovarian cancer and helps in planning the best surgical approach. Laparoscopic staging, in particular, can give a clear view of the extent of surgery required and the difficulties that may be expected, and it may be helpful in selecting patients for primary (neoadjuvant) chemotherapy [26]. Video recording can document the findings during laparoscopy and can be used subsequently by the surgeon to plan optimal debulking surgery.
However, laparoscopic surgery of any suspicious adnexal mass is not encouraged unless the risk of capsular rupture and tumor spill is minimized by the use of endobags [27]. No cystic mass which is >10 cm in diameter and/or adherent to the lateral pelvic wall should be removed laparoscopically [28].
The fear due to some in-vitro and animal studies that showed carbon dioxide pneumoperitoneum has adverse effects on outcomes is probably unfounded, as a recent analysis from second-look laparoscopies showed no influence of pneumoperitoneum on overall survival [29]. Certainly, more data on this issue is required.
Since laparoscopy may increase tumor growth rates, delays between laparoscopy and definitive surgery should be avoided [30]. Although this view has not yet been supported by any other study, we believe that the time between the suspected diagnosis of advanced ovarian cancer and surgery should be kept as short as possible. Delays may result in a higher preoperative tumor mass which has been identified as an adverse prognostic factor [31].
Surgical staging
Tumor stage is one of the primary prognostic factors. Appropriate staging is vitally important for effective postoperative therapeutic decision-making. Patients who have been accurately staged as stage I may not require adjuvant chemotherapy [32,33].
Requirements for appropriate staging after total abdominal hysterectomy and bilateral salpingo-oophorectomy include multiple cytological washings, random biopsies from the peritoneum and the diaphragm, omentectomy and lymphadenectomy. The value of peritoneal cytology is supported by prospective studies [34]. There are several issues surrounding lymphadenectomy, and these are discussed later. In two studies, optimal staging resulted in 30% to 50% of the patients being reclassified to a higher stage – a fact which has implications for subsequent treatment [35,36]. A classification system for determining the quality of surgical staging was introduced recently and is shown in Table 1[33]. However, it may be only helpful for comparisons of older studies since optimal staging is a prerequisite of later therapeutic decisions.
Table 1 Surgical quality categories for staging of ovarian carcinomas (based on Trimbos et al. 2003)
Category of surgical quality Staging procedures included
Optimal - Inspection and palpation of all peritoneal surfaces; biopsies of any suspect lesion for metastasis; peritoneal washings; infra-colic omentectomy; blind biopsies of the right diaphragm and right and left para-colic gutter, pelvic side-walls of the ovarian fossa, of the bladder peritoneum and of the cul-de-sac and sampling of iliac and para-aortic lymph nodes
Modified - Everything between optimal and minimal staging
Minimal - Inspection and palpation of all peritoneal surfaces and the retroperitoneal area; biopsies of any suspect lesions for metastasis; peritoneal washing; infracolic omentectomy
Inadequate - Less than minimal staging but at least careful inspection and palpation of all peritoneal surfaces and the retroperitoneal area; biopsies of any suspect lesion for metastasis
Extent of surgery
In addition to the staging procedures mentioned earlier, optimal surgical treatment for ovarian cancer comprises tumor removal; removal of remaining ovaries, uterus, and fallopian tubes, omentectomy, and radical para aortic and pelvic lymphadenctomy [3,37]. The German national treatment guidelines recommend a simultaneous appendectomy and removal of the cul de sac over the peritoneum of the small pelvis [38]. Since removal of all grossly visible tumor is considered crucial for long-term survival, surgery should be extended to include hemicolectomy, splenectomy and stripping of the peritoneal reflection of the diaphragm when the tumor masses infiltrate the entire abdominal cavity, the colon, the diaphragm or other structures respectively.
Although the reasoning behind performing these measures seems convincing, only lymphadenectomy has been partly evaluated in a prospective, randomized trial. The previously held belief that mere palpation of lymph nodes is sufficient to gauge nodal status was refuted in this study [39].
Lymphadenectomy plays a triple role in the treatment of ovarian cancer. First, it is of diagnostic value since tumors of apparently early stage show nodal involvement in about 20% to 40% of the cases [40], If found positive, the tumor must be classified as stage IIIc. Secondly, lymphadenectomy is of immense prognostic value. Most importantly, lymphadenectomy may also have a therapeutic effect as retrospective studies comparing lymphadenectomy with no lymphadenectomy reported a survival benefits with this procedure [41-43]. The data on lymphadenectomy is however conflicting with one study showing that the patients with stage III disease (tumor residuals >2 cm) that has been debulked suboptimally do not benefit from lymphadenectomy [44]. Other workers report no benefit even if the residual tumor size is smaller (1 cm) [45]. Though not fully published, the only prospective, randomized trial shows that systematic lymphadenectomy did not result in better survival compared to selective lymphadenectomy [46]. Mainly based on the retrospective findings current views on treating stage III disease suggest: systematic lymphadenectomy in cases of residual tumors <1 cm, nodal debulking only where tumors are larger than intra-abdominal residuals, and nodal sampling in stage IV disease with pleural effusions only [47].
To the best of our knowledge, there has been no study testing the benefit of hysterectomy or omentectomy. However, the concurrent incidence of endometrial carcinoma in 10% to 25 % of patients, or its precursors in about 30% to 50% of all ovarian cancers justifies this procedure [48,49].
Optimal debulking
Ovarian cancer is one of the tumors where surgical debulking is considered worthwhile. This is due to availability of further effective treatments that are available to control the unresectable residual disease. As early as 1934, Meigs suggested that maximum cytoreductive surgery was beneficial [50]. Many years later, in 1968, Munnell followed this idea and proposed the idea of 'maximum surgical effort' [51]. He distinguished between definitive surgery, partial removal of the tumor and biopsy only. Since partial removal covers a wide range of interventions that requires varying amount of efforts, optimal debulking was distinguished from suboptimal debulking. Although there is no generally accepted definition, most early studies considered a residual tumor size of <2 cm as optimal [52]. In a more recent survey among gynecological oncologists from United States of America (USA), 12% of the responders defined optimal debulking surgery as no visible tumor residuals, while 14% described it as residual tumor masses less than 0.5 cm. However, 61% chose a 1 cm threshold and 13% considered a tumor of 1.5 cm to 2.0 cm as optimal [53]. Comparative analysis of diameters of various residual diseases has shown that there exists some sort of a threshold at 2 cm, above which no significant differences in survival can be found. In contrast, subset analyses of smaller diameters in residual disease show improved patient prognosis [54]. This variation in the interpretation of thresholds with prognostic impact calls for a commonly accepted definition (see concluding remarks) and more controlled trials, that need to be non-randomized as it will not be ethically possible to leave some tumor behind.
The results of an earlier meta analysis on cytoreductive surgery might have been flawed not only due to absence of clear definitions but also due to the combined effects of subsequent chemotherapy [52]. In this study, the then novel, platinum-containing chemotherapy had a stronger impact on survival than cytoreductive surgery. A recent and otherwise comparable meta analysis however, confirms the greater survival benefit of patients undergoing maximum cytoreduction [55]. Another interesting study stated that optimal cytoreduction means no visible residual tumor [31]. It has been further shown that the volume of the residual tumor and the success of subsequent chemotherapy are interdependent [56].
Expertise of gynecological oncology surgeons
Based on available evidence it is generally accepted that the experience and technical expertise of a surgeon are important prognostic factors. Comparisons of overall survival in patients treated by gynecological oncology, gynecologists and general surgeons have shown that patients treated by surgeons trained in gynecology (gynecological oncology) have a significantly better prognosis [57,58]. This finding may not reflect primarily on the technical skills of these surgeons but rather reflection the 'environment' in which they work – where views and thoughts on the biology of advanced tumors are freely shared and patients are often treated by a team rather then individuals. As for surgeons there are only select patients with uncommon neoplasms like gastrinomas, glucagonomas, stomatostatinomas, and VIPomas, who profit from debulking surgery with particular reference to prevent deleterious hormonal side-effects [59]. It is expected that new chemotherapy and immunotherapeutical approaches will probably lead to a re-evaluation of debulking surgery as a complementary approach [60-62]. Till such time where definite evidence is available, it is strongly recommended that all patients should be treated by a gynec-oncologist. There had been constant calls to regionalize specialist surgery, however, no studies have yet shown better survival in patients treated by 'high volume' operators or such specialists [63,64]. A recent study on quality control from Hesse, Germany, showed striking deficiencies even at central-referral hospitals [23]. Treatment by a multidisciplinary team of specialists, has been shown to increase patients' chances of survival without any disputes [65,66]. Patients probably benefit most from being treated in centers which promote excellent scientific exchange, and continuous education and self-evaluation among surgeons besides providing multidisciplinary approach to management.
Coping with inadequate primary surgery
Surgical treatment of advanced ovarian cancer is one of the most demanding procedures in gynecological surgery. Despite repeated requests to restrict surgery to experienced surgeons, considerable numbers of patients are still operated by others. A population based study from Germany showed that omentectomies were performed in about 50% of all cases of ovarian cancer and lymphadenectomy were carried out only in 30% [22]. Another study from USA showed that only about half of the patients receive 'standard' care [68]. In spite of the establishment of gynecological oncology as a specialty in the USA, fewer than half of the patients were originally seen by such a specialist [68]. More over the terminologies like "standard" are not defined well.
The situation with regard to specialism depends strongly on the medical infrastructure, and varies from country to country and region to region. However, the problem of inadequate primary surgery is real, and coping with it is a frequent task in specialist centers even in developed countries. The question is what should be done for the patient concerned? Interestingly, this is something that cannot be found in textbooks [3,69,70]. Some of the literature suggest re-laparotomy by experienced surgeons to achieve reductions in all possible tumor mass [71,72] however, there is no evidence to support this strategy.
In general, one of two situations occurs. First patients present with no evidence of macroscopic tumor residuals but staging procedures and/or operative measures were omitted. Computed tomography (CT) or Magnetic resonance imaging (MRI) to identify enlarged lymph nodes or possible residual tumors in these situations may help to decide on the need for second surgery. The belief that tumor cells in retroperitoneal lymph nodes are better able to survive chemotherapy is supported by low cytotoxic drug concentrations in these [73]. Therefore, it is reasonable to consider enlarged lymph nodes as a decisive factor favoring a direct surgical approach. It is interesting to note that in endometrial carcinomas, a clinically negative omentum was also found to be histologically negative in most cases (sensitivity 89%) [74].
Patients with residual tumor mass have to be evaluated to determine if it is possible to achieve no residual tumor or microscopic residual tumor by immediate secondary surgery. Although immediate laparotomy seems to be a good idea, the limited capacity for surgery at specialist departments and delays in having the surgery are to be considered. The peritoneum shows inflammation shortly after surgery reaching a high about 7 to 14 days afterwards [75]. Surgery at this time is considered far more complicated and may result in higher blood loss and greater risk of injury to neighboring abdominal organs [76]. However, waiting for the inflammatory processes to resolve will give the tumor further time to proliferate [20]. Therefore, interval debulking surgery after three courses of chemotherapy should be considered as an appropriate alternative.
Neoadjuvant chemotherapy
Disease spread >2 cm to the spleen, diaphragm, liver surface, mesentery, or gallbladder is generally believed to be inoperable. However, even these patients may often undergo effective debulking procedures [26,77]. As mentioned earlier, laparoscopy can be used to reach decisions on surgery. The only problem with laparoscopy in combination with neoadjuvant chemotherapy is a 30% rate of port site metastasis, which is believed to be a result of the pneumoperitoneum procedure created for laparoscopy [78]. These metastases should be excised at the time of any subsequent surgery [79].
An analysis of several retrospective studies on neoadjuvant chemotherapy showed that there are no good reasons to assume that this approach is associated with a poorer prognosis [26]. The European Organisation for Research and Treatment of Cancer (EORTC) protocol 55971 comparing upfront tumor debulking surgery with neoadjuvant chemotherapy in patients with stage IIIc or IV disease is accruing and its results will provide better insights on this issue.
Interval tumor debulking
Interval debulking, is another approach to reduce tumor burden between the cycles of chemotherapy. It has been evaluated in two prospective randomized trials [80,81]. The EORTC study showed a clear survival advantage for interval debulking (still noted in the 2001 update), the Gynecologic Oncology Group (GOG-152) study has, as yet, failed to show any benefit from interval debulking [80,81]. Patients with residual tumor >1 cm received three courses of cyclophosphamide/cisplatinum in the EORTC study [80] or three courses of paclitaxel/cisplatinum in the GOG-152 study. In both studies, patients who did not respond to chemotherapy were removed from the study. Those who responded were randomized to either secondary surgery or no surgery. Afterwards, all patients received three more courses of the earlier chemotherapeutic regimen.
Although there seem to be only minor differences in the design of both trials, a closer look shows that in the GOG-152 study, the number of stage IV patients was lower (6%) compared with the EORTC (21%) study, the performance status was better, and there was less residual tumor. This was due to the eligibility criteria for GOG 152 which stated that patients should have had surgery with maximal effort to resect the uterus, tubes, ovaries, omentum, and all gross residual ovarian cancer at the time of primary surgery.
The questions about the benefit of interval debulking surgery remain unresolved. However, it appears that patients who have had neoadjuvant chemotherapy or suboptimal debulking may profit from this treatment, while those who have undergone primary, maximum effort surgery by a gynecological oncologist are less likely to profit from it [82].
Surgical prognostic factors
Size of the residual tumor, volume of the residual disease and experience of the surgeon are important prognostic factors [56,77]. Among these, only few can be influenced by human intervention. Except for dose intensity of chemotherapy, recent literature indicates that the hemoglobin concentrations before chemotherapy are of prognostic value [83,84]. The latter may be influenced by the use of erythropoietin which has shown positive effects on survival in cervical cancer [86].
As mentioned above, the frequently used definition of <2 cm for optimal debulking is arbitrary since every further reduction in the size of residual tumor improves the prognosis [54]. Thus, each threshold between 0 and 2 cm will have its own prognostic relevance. While the criterion 'diameter of residual tumor' reflects tumor cell hypoxia and reduces the pool of proliferating tumor cells susceptible to chemotherapy, the criterion 'residual tumor volume' alludes to the removal of therapy-resistant tumor cells, which are believed to be responsible for early recurrences. A comparison of both criteria in relation to their prognostic impact has shown that residual tumor volume is of greater importance [56]. As shown in subgroup analyses of the intergroup trial confirming the results of the GOG-111 study, a possibly superior chemotherapeutic regimen containing taxanes cannot compensate for the tumor left behind after primary surgery [19].
Future trends
It is difficult to assess the future role of surgery in advanced ovarian cancer. Neoadjuvant chemotherapy may become more important. However, as the tumor debulking surgery works, except in stage IV patients with solid distant metastasis, it may be worth trying combined ultrasound-guided laser interstitial thermotherapy for non-resectable liver metastasis with conventional debulking surgery [87]. Apart from technical innovations, quality control, quality assurance and documentation of patient outcomes after surgery will probably play major parts in treatment improvements.
Conclusion
Numerous studies have analyzed the effects of various kind of chemotherapy in ovarian cancer. In contrast, only a few prospective randomized studies have focused on surgical issues in this type of tumor [46,80,81]. This lack of surgical trials has probably contributed to inhomogenous definitions regarding the terminology of surgical interventions and surgical stages (early compared with late) and the classification of operative success in general.
In future, we must aim to ensure that all patients are treated along the generally accepted guidelines and receive optimal debulking surgery which leaves only microscopically detectable residual tumor as shown in number of studies; it is certainly unethical at present to evaluate this procedure in randomized clinical trials (see Introduction). Other then this, there are many other relevant issues which need to be resolved or clarified with special reference to neoadjuvant chemotherapy, interval debulking, the surgeon's training, and inadequate primary treatment. It would certainly be very helpful to demonstrate clearly the consequences of what is supposed to be an inadequate treatment.
The simple dichotomization of FIGO stages to early or late does not correspond to any diagnostic, biological or therapeutic advantage. We believe that it is far more reasonable to consider stage I alone as early disease (perhaps even only stage Ia and b), stages II and III (perhaps even stage IV with pleural effusions) as intermediate disease, and stage IV with organ metastasis as advanced disease. Such a classification would follow current views on treatment, since early ovarian carcinomas are treated primarily by surgery (eventually fertility-sparing) and adjuvant chemotherapy in cases of increased risk, intermediate ones by surgery and routine chemotherapy, and advanced disease by chemotherapy only. Thus far, results of studies on stage IV patients with organ metastases are inconsistent regarding the benefit of surgery. This is another issue to be resolved [88]. In this respect, FIGO may find subdividing stage IV into stage IVa (pleural effusions) and IVb (organ metastasis) worthwhile.
Disappointingly, the Tumor-Nodes-Metastasis (TNM) classification follows the FIGO system and violates its own principles by not accepting distant peritoneal metastasis as a natural indicator of primary tumor size but also by summarizing a nodal-positive disease stage as T3c (corresponding to FIGO IIIC) regardless of intra-abdominal findings. This inconsistency has already created curious confusions in current research. Nodal involvement has been shown to impair prognosis, however, smaller intra-abdominal tumors with nodal involvement (presented as stage I to IIIb disease but, by definition, all stage IIIC) show a significantly better prognosis than extensive intra-abdominal tumor masses (again stage IIIC) [89].
Furthermore, residual disease should be properly defined. The most rational approach is to regard microscopic residuals as optimal. Case series claim that experienced gynecologic-oncologic surgeons can clear up to 85% of patients in the unfavorable subgroups (FIGO stage IIIc and IV) of all visible tumor, leading to an extraordinarily high five year survival rate of about 50% [77]. As discussed (see surgical prognostic factors), a good definition of residual tumor would include aspects of both residual tumor size and volume. A proposal is made in Table 2.
Table 2 Surgical documentation of residual tumor after debulking of ovarian carcinomas
Residual tumor status* Maximum diameter of residual tumor Maximum total volume of residual tumor
Optimal Microscopic No visible tumor
Minimal < 1 cm ≤ 10 cm3
Intermediate 1 – 2 cm > 10 cm3 but ≤ 100 cm3
Gross > 2 cm > 100 cm3
*To assign residual tumor to a certain status, both criteria, diameter and volume, have to be fulfilled. Otherwise the next lower category should be used.
In summary, more attention need be paid to surgery for advanced ovarian cancer. These include necessary improvements in treatment in the general population, uniform definitions and terminology, and increasing number of surgical clinical trials. Extrapolating from the results of truly optimal ovarian cancer surgery, we believe that improvements in surgery will lead to better patient survival than improvements in current chemotherapeutic approaches [55,90,91].
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
KM and FEF both participated equally in literature search, conceptualization and preparation of the manuscript. Both authors have read the manuscript and approve it for publication.
Acknowledgments
The author takes the opportunity to thank Professor Dr. Wolfgang Künzel, FRCOG, for his helpful comments on the manuscript.
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| 15461790 | PMC524188 | CC BY | 2021-01-04 16:38:38 | no | World J Surg Oncol. 2004 Oct 3; 2:33 | latin-1 | World J Surg Oncol | 2,004 | 10.1186/1477-7819-2-33 | oa_comm |
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Reprod Biol EndocrinolReproductive biology and endocrinology : RB&E1477-7827BioMed Central London 1477-7827-2-671538314610.1186/1477-7827-2-67ResearchAnalysis of Maxi-K alpha subunit splice variants in human myometrium Curley Michael 1michael_curley@hotmail.comMorrison John J 12john.morrison@nuigalway.ieSmith Terry J 1terry.smith@nuigalway.ie1 National Centre for Biomedical Engineering Science, National University of Ireland, Galway, Galway, Ireland2 Department of Obstetrics and Gynaecology, National University of Ireland, Galway, Clinical Science Institute, University College Hospital Galway, Newcastle Road, Galway, Ireland2004 21 9 2004 2 67 67 25 6 2004 21 9 2004 Copyright © 2004 Curley et al; licensee BioMed Central Ltd.2004Curley 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
Large-conductance, calcium-activated potassium (Maxi-K) channels are implicated in the modulation of human uterine contractions and myometrial Ca2+ homeostasis. However, the regulatory mechanism(s) governing the expression of Maxi-K channels with decreased calcium sensitivity at parturition are unclear. The objectives of this study were to investigate mRNA expression of the Maxi-K alpha subunit, and that of its splice variants, in human non-pregnant and pregnant myometrium, prior to and after labour onset, to determine whether altered expression of these splice variants is associated with decreased calcium sensitivity observed at labour onset.
Methods
Myometrial biopsies were obtained at hysterectomy (non-pregnant, NP), and at Caesarean section, at elective (pregnant not-in-labour, PNL) and intrapartum (pregnant in-labour, PL) procedures. RNA was extracted from all biopsies and quantitative real-time RT-PCR was used to investigate for possible differential expression of the Maxi-K alpha subunit, and that of its splice variants, between these functionally-distinct myometrial tissue sets.
Results
RT-PCR analysis identified the presence of a 132 bp and an 87 bp spliced exon of the Maxi-K alpha subunit in all three myometrial tissue sets. Quantitative real-time PCR indicated a decrease in the expression of the Maxi-K alpha subunit with labour onset. While there was no change in the proportion of Maxi-K alpha subunits expressing the 87 bp spliced exon, the proportion of alpha subunits expressing the 132 bp spliced exon was significantly increased with labour onset, compared to both non-pregnant and pregnant not-in-labour tissues. An increased proportion of 132 bp exon-containing alpha subunit variants with labour onset is of interest, as channels expressing this spliced exon have decreased calcium and voltage sensitivities.
Conclusions
Our findings suggest that decreased Maxi-K alpha subunit mRNA expression in human myometrium at labour onset, coupled to an increased proportion of Maxi-K channels expressing the 132 bp spliced exon, may be linked to decreased Maxi-K channel calcium and voltage sensitivity, thereby promoting enhanced uterine activity at the time of labour.
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Background
The regulatory mechanisms for uterine smooth muscle contractility during human pregnancy and labour are poorly understood. Such information is essential to understanding the clinical problems associated with human parturition and particularly preterm or premature labour. It is clear however that the myometrium is transformed from a state of relative quiescence during pregnancy, to one of maximal contractile activity at the time of labour. It is also established that the state of contractility of uterine smooth muscle is intrinsically linked to cell membrane ion channel activity [1,2].
Potassium (K+) channels are functionally important in the regulation of smooth muscle tone [3]. Among the diverse family of K+ channels, large-conductance, calcium-activated K+ (Maxi-K, also known as BKCa) channels are the predominant K+ channels in myometrium, and thus have been implicated in the control of cellular excitability [4]. While evidence for an important role of Maxi-K channels is not particularly strong, it is thought that they play a pivotal role in the modulation of uterine contractility and myometrial calcium homeostasis. Pharmacological inhibition of Maxi-K channels, by the specific channel blocker iberiotoxin, increases contractile activity in human uterine tissue [5], whereas compounds that promote Maxi-K channel opening, such as NS1619, have a potent relaxant effect on pregnant human myometrium [6]. Structurally, Maxi-K channels are tetramers of a pore-forming α subunit of the slo gene family, and a regulatory β subunit [7-10]. The α subunit comprises 7 transmembrane regions (S0-S6) and 4 intracellular hydrophobic domains (S7-S10) [11]. The β subunit is a structurally unique, membrane-spanning protein that contributes to channel gating and pharmacology [12]. The α subunit is encoded by a single gene. However, it achieves molecular diversity by extensive alternative splicing of its gene transcript at several sites [7,13-15], which generates Maxi-K channel variants. There is a substantial body of evidence indicating that alternate splicing of the maxi-K transcript plays a major role in regulating potassium channel conductance [7,15]. These data include evidence for splice variation effecting calcium and voltage sensitivity, surface expression, and sensitivity to protein phosphorylation of the maxi-K channel [16,17]; [18]. Alternative splicing of the maxi-K channel α subunit is considered to be a molecular mechanism by which the channel is able to adjust and tune its response to a variety of regulatory and conductance requirements. Further evidence of the role of alternate splicing of the maxi-K transcript in altering maxi-K protein function in myometrium is provided by the finding of up-regulation of maxi-K splice variants known to alter channel current through alterations in calcium and voltage sensitivity in pregnant mouse myometrium [19]. What initiates alternative splicing of the α subunit transcript is incompletely understood, however there is evidence that expression of different alternatively spliced transcripts can be hormonally induced [20,21].
It appears that expression of different pore-forming α subunit isoforms, with associated regulatory β subunits, occurs in a tissue-specific manner, thereby providing functional specificity [22]. Maxi-K channels have been identified both in human non-pregnant [23] and pregnant [24] myometrium. For animal myometrial tissues, the data outlining Maxi-K α subunit mRNA expression in relation to labour are conflicting [19,25,26]. For human myometrium, it has more recently been reported that protein expression of both α and β subunits is down-regulated with labour onset [27].
Although multiple alternatively spliced exons of the Maxi-K α subunit have been identified [10,19,21,28], there is no information available to date pertaining to expression of α subunit splice variant mRNA transcripts in human myometrium during pregnancy or at the time of labour. Because phosphorylation sites can be introduced into the channel protein via alternatively spliced exons [19], alternative splicing may represent an important control mechanism regulating Maxi-K channel function during pregnancy and at labour. The aim of this study was to investigate the expression of alternatively spliced exons of the Maxi-K α subunit transcript in non-pregnant myometrium and in pregnant myometrium, prior to and after labour onset using quantitative real-time PCR.
Methods
Patient recruitment and tissue collection
Patient recruitment took place in the Department of Obstetrics and Gynaecology, University College Hospital Galway (UCHG), Ireland, between October 2001 and August 2002. The study was approved by the Research Ethics Committee, UCHG, and recruitment was carried out by provision of information sheets and obtaining written informed consent.
Biopsies of myometrium were excised from the midline of the upper lip of the uterine incision made at caesarean section, at elective (pregnant not-in-labour, PNL; n = 8) and intrapartum (pregnant in-labour, PL; n = 7) procedures. The mean age of the women was 33.3 years (range 26–42) of whom four were primagravida and eleven were multigravida. All women were delivered between 37 and 41 weeks gestation. There was no significant difference between those undergoing elective or emergency caesarean section in terms of age, parity or gestation. Women who had received prostaglandins or oxytocin were excluded from the study. Reasons for emergency section included breech presentation, previous caesarean section and abnormal foetal position. The criteria for inclusion in the intrapartum group were regular spontaneous uterine contractions, effacement of the cervix, and cervical dilatation >3 cm prior to caesarean section.
Samples of non-pregnant myometrium (NP; n = 7) were excised from the body of the uterus of hysterectomy specimens from pre-menopausal women. The mean age of women undergoing hysterectomy was 42.5 years (range 34–48). Women with malignant conditions, and those receiving exogenous hormone therapy (e.g. progestagens), were excluded from the study. Immediately upon removal, tissue samples were rinsed in sterile saline, snap frozen in liquid nitrogen and stored at -80°C until RNA extraction.
RNA preparation/Reverse Transcriptase-Polymerase Chain Reaction
RNA was isolated from frozen tissue by homogenisation in TRIzol® Reagent (Life Technologies, Paisley, UK) [29]. RNA concentration was determined by absorbance at A260. To eliminate any residual contaminating genomic DNA, all RNA samples were DNase-treated with the DNA-free™ DNA removal kit (Ambion, Huntingdon, Cambridgeshire, UK), as previously described [30]. RNA concentration was measured again by absorbance at A260, after removal of DNA, and adjusted to a final concentration of 500 ng/μL.
Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) was performed to check for mRNA expression of all potential spliced exons of the Maxi-K α subunit in non-pregnant and pregnant myometrium, prior to and after labour onset. Purified RNA samples were reverse transcribed using oligo (dT)15 primer and 200 IU M-MLV reverse transcriptase (Promega, Madison, WI, USA), as previously described [30]. PCR amplification was performed with 20 pmol of each specific oligonucleotide primer pair (Table 1), and 1.25 IU Taq DNA Polymerase (Promega, Madison, WI, USA) as previously described [30]. Primer pairs were designed to flank predicted splice sites, allowing spliced exon expression in these different regions to be assessed. PCR products were separated by electrophoresis on a 1.5% agarose gel and visualised after ethidium bromide staining by UV illumination. Bands identified were purified by gel extraction using Qiagen Gel Extraction kit (Qiagen, West Sussex, UK), and sent for sequencing (MWG-Biotech Ltd., Milton-Keynes, UK).
Table 1 Primer Pairs
Primer name Primer sequence (5' – 3') Primer Tm (°C)
Maxi 0F CGGAGGCAGCAGTCTTAG 58.2
Maxi 0R AAGAAAGTCACCATGGAGGAG 57.9
Maxi 1F CTCCTCCATGGTGACTTTCTT 57.9
Maxi 1R TTACAAGTGCACCGATGCTG 57.3
Maxi 2F GGAAACCGCAAGAAATAC 53.1
Maxi 2R ACCTCATGGAGAAGAGGTTG 57.3
Maxi 3F GGTCTGTCCTTCCCTACTGT 59.4
Maxi 3R CAAAGATGCAGACCACGACA 57.3
Maxi 4F GTGCCAGCAACTTTCATTAC 55.3
Maxi 4R TCAGGGTCATCATCATCGTC 57.3
Maxi 5F ACAGCATTTGCCGTCAGTG 56.7
Maxi 5R GGTCCGTCTGCTTATTTGCT 57.3
β-actin F CAACTCCATCATGAAGTGTGAC 55.8
β-actin R GCCATGCCAATCTCATCTTG 59.3
Splice variant-specific cDNA synthesis
Splice variant-specific cDNAs were prepared for each RNA sample using reverse primers as shown in Table 2. 3 μg of purified RNA (1 μg for β-actin) was reverse transcribed to cDNA for each amplicon of interest using 500 nmol/L specific reverse primer and 200 IU M-MLV reverse transcriptase (Promega, Madison, WI, USA), as previously described [30]. These cDNAs were stored at -20°C until required for real-time PCR. New forward primers were designed upstream of the spliced exon sequences, to ensure that product size was approximately 200 bp, the optimum product length for use with hydrolysis TaqMan probes.
Table 2 Amplicon-specific primer and probe sequences
Primer name Primer/Probe sequence (5' – 3') Primer/Probe Tm (°C)
Conserved F TGCACAAAGAGGTATGTCATCAC 58.9
Conserved R GTTTGCTGTGGATGGGATGGA 59.8
Conserved Probe 6F * -CCCACTCGTCGCAGTCCTCCAGCAAGAAGA XT♣ 68.9
132 bp splice F ACGCTCAAGTACCTGTGGACCGT 64.2
132 bp splice R TGTGGTTCCAGTTGAGTCACCA 60.3
132 bp Probe 6F-CTCCAGGGTGGAGTGATTGGCTGTATGTT XTCAC 71.5
87 bp splice F CATCGCAAGTGATGCCAAAGAA 58.4
87 bp splice R TCAACTGGCTCGGTCACAAGC 61.8
87 bp Probe 6F-TTGCAGCTAGATCACGCTATTCCAAAGATCCA XT 68.9
β-actin F CAACTCCATCATGAAGTGTGAC 55.8
β-actin nested R GTCAAGAAAGGGTGTAACGCA 55.4
β-actin Probe 6F-TGGCACCCAGCACAATGAAGATCAAATCA XT 70.3
* 6F = FAM reporter dye; ♣ XT = TAMRA quencher dye
Synthesis of cDNA standards
Standards (1 × 109 to 1 × 104 cDNA copies, in 10-fold increments) were created for each spliced exon and conserved region amplicons, and for β-actin, to enable accurate quantitation of product-specific cDNA copy numbers. Amplicon-specific PCR products were generated by RT-PCR (as described above) using primers shown in Table 2. Products were purified using Qiagen PCR purification kit (Qiagen, West Sussex, UK), quantified by absorbance at A260, and ligated into TA cloning vector pCR® 2.1 (TA cloning® kit, Invitrogen Ltd, Paisley, UK), according to manufacturers' instructions. Vector-ligated PCR products were transformed into One Shot® TOP10 cells, which were plated on Luria-Bertani (LB) agar plates containing 50 μg/mL kanamycin antibiotic, and incubated overnight at 37°C. Plasmid templates containing inserts in the desired orientation to transcribe sense RNA, as determined by colony PCR, were linearized by HindIII digestion. 2 μL of digestion products were electrophoresed on 1% agarose gels and visualised to ensure complete plasmid linearisation.
Sense cRNA transcripts were generated by in vitro transcription using the MAXIscript™ In vitro Transcription Kit (Ambion, Huntingdon, Cambridgeshire, UK). 1 μg of linearized plasmid DNA was in vitro transcribed in a final volume of 20 μL containing 0.5 mmol/L each of ATP, CTP, GTP, and UTP, 2 μL 10X Transcription buffer, and 2 μL T7 Enzyme mix for 1 hr at 37°C. After transcription, samples were treated with DNA-free™ DNA removal kit (Ambion, Huntingdon, Cambridgeshire, UK) to remove plasmid DNA. The supernatant, containing purified cRNA, was pipetted onto pre-hydrated NucAway™ spin columns (Ambion, Huntingdon, Cambridgeshire, UK) to remove free nucleotides from the transcription reaction and further purify the cRNA samples. These columns were centrifuged at 1200 g for 2 min. Eluted cRNA concentration was determined by absorbance at A260. Copy number/μL of cRNA was calculated according to the following formula, available from the Roche Lightcycler™ website:
Once the total amount of cRNA copies/μL had been calculated, serial dilutions of cRNA standards were produced (from 1 × 109 cRNA copies/μL to 1 × 104 cRNA copies/μL, in 10-fold increments) for each product-specific cRNA molecule generated. Serially-diluted cRNA standards were reverse transcribed in a 20 μL final volume as described above, using transcript-specific reverse primers (Table 2), thereby generating product-specific cDNA standards. These cDNA standards were stored at -20°C until required for real-time PCR.
Quantitative expression analysis using real-time PCR
Real-time PCR amplification was performed on the Lightcycler™ instrument using the Lightcycler™ FastStart DNA Master Hybridization Probes kit (Roche Diagnostics, Mannheim, Germany). Hydrolysis TaqMan probes were synthesized for each amplicon to be quantified (TIB MolBiol Syntheselabour, Berlin, Germany), and are shown in Table 2. Probes were designed with consideration taken for the design parameters outlined by Bustin [31]. Probes were resuspended in PCR-grade water to a working stock concentration of 4 μmol/L, and stored in the dark at 4°C. Prior to quantitative analysis, several titration experiments for cDNA, probe, primer, and MgCl2 concentration were performed to determine optimum reaction conditions for amplification. The following master mix of the reaction components was prepared to the indicated end-concentration: 10.6 μL water, 2.4 μL MgCl2 (3 mmol/L), 1.0 μL forward primer (0.5 μmol/L), 1.0 μL reverse primer (0.5 μmol/L), 1.0 μL specific probe (200 nmol/L) (see Table 2) and 2 μL Hybridization Master Mix. The master mix (18 μL) was aliquoted into Lightcycler™ glass capillaries (Roche Diagnostics) and 2 μL cDNA (samples and standards) was added to respective capillaries. Capillaries were centrifuged at 3000 rpm for 5 s, and loaded into the Lightcycler™ instrument.
The experimental protocol used for TaqMan probe quantitative analysis consisted of two stages: initial denaturation (95°C for 10 mins), followed by 45 cycles of denaturation (95°C for 0 s) and annealing/extension (59–61°C for 50 s). The annealing temperature used in each experiment was dependent on the melting temperature of both the primers and probe involved. Fluorescence data were acquired at the end of each annealing/extension cycle.
Data analysis was performed using Lightcycler™ Second Derivatives Method software. This method automatically determines the threshold cycle (CT) values for each individual sample using a software algorithm, which allows initial mRNA concentration in each sample to be accurately quantified based on the standards used. Using this method removes user influence, as well as any influence of background fluorescence on the data. The fluorescence display mode used was F1/F2, which is the optimal setting for use with hydrolysis TaqMan probes. PCR products were isolated from capillaries after each program had finished and were visualised by electrophoresis on 1.5% agarose gels.
Statistical analysis
The SPSS computer software package was used for all statistical analyses (Statistical Package for the Social Sciences, v.10, SPSS Inc., Chicago, IL, USA). Multiple group comparisons were made using analysis of variance (ANOVA), which were followed by individual group comparisons using the Tukey HSD test, where appropriate.
Results
Analysis of expression of alternatively spliced exons of the Maxi-K α subunit in human myometrium
RT-PCR analysis of the Maxi-K α subunit gene, using primers designed to flank predicted splice sites, produced a variety of bands in samples of non-pregnant (NP), pregnant not-in-labour (PNL) and pregnant in-labour (PL) myometrium (data not shown). From this analysis, only two potential alternatively spliced exon-containing PCR products were identified in the three tissue sets assayed (Figure 1). Sequence analysis of these bands confirmed the presence of two alternatively spliced exons, both of which had previously been identified in human myometrium. The first was a 132 bp spliced exon located in the S0-S1 linker region identified by Korovkina et al. [26], and the second was an 87 bp spliced exon located in the S8-S9 linker region identified by Wallner et al. [10]. PCR of reverse transcriptase negative controls (RT-) and a water control (no cDNA template) did not generate any products, confirming the absence of genomic DNA contamination (data not shown).
Figure 1 Detection of alternatively spliced exon-containing RT-PCR products. Ethidium bromide stained agarose gels (2%) showing (A) 132 bp spliced exon-containing (437 bp) and exon-less (305 bp) PCR products and (B) 87 bp spliced exon-containing (622 bp) and exon-less (535 bp) PCR products, in non-pregnant (NP), pregnant not-in-labour (PNL), and pregnant in-labour (PL) myometrial tissues. M = 100 bp marker (Promega, US); M2 = 2-log ladder (New England Biolabs Inc., UK).
Quantitative analysis of alternatively spliced exon expression using real-time PCR
Quantitative analysis of alternatively spliced exon expression was performed using sequence-specific hydrolysis TaqMan probes to analyse mRNA expression of these exons in non-pregnant myometrium and pregnant myometrium, prior to and after labour onset, as outlined. In order to correct for random errors from sources such as pipetting inaccuracies, separate real-time PCR reactions were performed in triplicate for each amplicon involved. Agarose gel electrophoresis, as well as sequencing analysis, confirmed the specificity of PCR products formed, yielding single product bands of the expected size (data not shown).
Quantitative results for each amplicon were obtained by determination of the threshold cycle (CT) values for each sample, as determined mathematically by the "Second Derivatives" method. Mean absolute cDNA copy number values for each probed amplicon involved, in each myometrial sample, were calculated and grouped per tissue set (i.e. NP, PNL, PL), as shown in Figure 2. All data were normally distributed, as determined by Normality plots for each group (P > 0.05). Analysis of the expression of the housekeeping gene, β-actin, showed no significant differences between the three tissue sets assayed (P > 0.05). The 3' conserved region of the Maxi-K α subunit was analysed as a measure of overall α subunit expression. The results of this analysis indicated a decrease in expression of the α subunit transcript with labour onset (Figure 2A). Although this did not reach statistical significance (P = 0.052), the observed decrease in α subunit mRNA expression at labour is in agreement with the decrease seen in α subunit protein levels at labour, reported recently [27]. Quantitative analysis of the expression of the 132 bp and 87 bp spliced exon transcripts indicated no significant differences in expression, in absolute terms, between NP, PNL, and PL tissues (P > 0.05)(Figure 2B).
Figure 2 Maxi-K α subunit mRNA expression analysed by quantitative real-time PCR. Results shown represent mean (± standard error of the mean, SEM) copy number values for (A) total Maxi-K α subunit (represented by the 3' conserved region), and β-actin, and (B) the 132 bp and 87 bp alternatively spliced exons of the Maxi-K α subunit. Copy number values were obtained based on product-specific serially-diluted cDNA standards, generated individually for each amplicon of interest. Tissue sets are indicated by striped columns (non-pregnant, NP), black columns (pregnant not-in-labour, PNL) and open columns (pregnant in-labour, PL).
The results of expression analyses for the 87 bp and 132 bp spliced exons as a proportion of the total Maxi-K α subunit (i.e. the 87 bp and 132 bp variants) are demonstrated in Figure 3. Analysis of mRNA expression of the 87 bp variant indicated no significant differences between the three tissue sets assayed (Figure 3A). Expression of this variant mRNA accounted for only 1% of total Maxi-K α subunit expressed. However, the proportion of Maxi-K channels expressing the 132 bp spliced exon was significantly increased with labour onset (PL), compared to both non-pregnant (NP)(P < 0.05) and pregnant not-in-labour myometrial tissues (PNL) (P < 0.01)(Figure 3B). Duplicate RT and quantitative PCR analysis confirmed these data. The increase in proportion of this 132 bp variant could be equated to approximately 1.7 fold, from 9% to 15% of total α subunit mRNA expressed.
Figure 3 Expression of 132 bp and 87 bp variant mRNAs of the Maxi-K α subunit. The histograms show the mean (± standard error of the mean, SEM) of the ratios of spliced exon to total maxi-K α subunit mRNA for both (A) the 87 bp and (B) the 132 bp variants in NP, PNL and PL tissues. Results indicate significantly higher expression of the 132 bp exon as a proportion of the total α subunit with labour onset, compared to non-pregnant and pregnant not-in-labour samples. There is no change in expression of the 87 bp variant between the three tissue sets. Tissue sets are indicated by striped columns (non-pregnant, NP), black columns (pregnant not-in-labour, PNL) and open columns (pregnant in-labour, PL). *P < 0.05 versus PL; +P < 0.01 versus PL.
Discussion
In this study RT-PCR analyses were performed to identify mRNA expression of the Maxi-K α subunit, and alternatively spliced exons of this subunit, in human myometrium in its non-pregnant state, and at term pregnancy, prior to and after labour onset. This was followed by quantitative real-time PCR, which was performed to determine the overall pattern of expression of the Maxi-K α subunit as well as expression of alternatively spliced exons of this subunit identified in these tissue sets.
Our findings indicate a trend towards a decrease in α subunit mRNA levels with human labour onset. In order to maintain the uterus in a quiescent state during pregnancy, K+ channels provide a potent repolarizing current through the efflux of K+ ions, thereby dampening cell excitability and promoting cell relaxation [32]. Previous studies on murine and rodent myometrium have reported conflicting results for Maxi-K α subunit mRNA and protein expression during pregnancy and with labour onset. Song et al. [26] identified a decrease in Maxi-K α subunit protein levels in rats at term pregnancy, whereas Benkusky et al. [19] indicated an increase in protein levels of this subunit in mouse term myometrium. However, a recent report has outlined significant down-regulation in the protein levels of both α- and β-subunits of the Maxi-K channel in human myometrium at labour onset, suggesting that the loss of Ca2+ and voltage sensitivity is at least partly due to decreased levels of the Maxi-K channel [27]. Our findings are in agreement with this report, with the highest levels of mRNA expression in the PNL group, and decreased mRNA expression of the Maxi-K α subunit with labour onset (Figure 2). Although the decrease in mRNA expression between PNL and PL tissues was ~50%, it was found not to be statistically significant (P = 0.052). A reduction in expression of the Maxi-K α subunit could allow for enhanced myometrial contractility, as reduced α subunit expression would permit an increase in intracellular Ca2+ levels without the activation of an opposing K+ conductance [32].
Maxi-K channels derive their molecular diversity by alternative splicing of their α subunit transcript at several key sites, which generate channel variants with distinct phenotypes [7,15,16]. Previous studies provide evidence that alternate splicing effects calcium and voltage sensitivity of the maxi-K channel and thus channel function in myometrium [16], surface expression [17], and sensitivity to protein phosphorylation of the maxi-K channel [18]. Further direct evidence for the role of alternate splicing of the maxi-K transcript in altering maxi-K protein function in myometrium is provided by the finding of up-regulation of maxi-K splice variants known to alter channel current through alterations in calcium and voltage sensitivity in pregnant mouse myometrium [19]. Our results from RT-PCR analysis indicate the presence of only two spliced exons, both of which had been identified previously, in human myometrium. The 132 bp exon, previously identified by Korovkina et al. [28], encodes a 44 amino acid peptide that is inserted into the first intracellular loop of the Maxi-K α subunit, and contains four potential consensus sites for post-translational modification. The 87 bp exon, isolated by Wallner et al. [10], encodes a 29 amino acid peptide that is introduced into the loop region between hydrophobic regions S8 and S9 of the α subunit protein. Protein sequence analysis of this exon using PROSITE revealed a potential cAMP-/cGMP-protein kinase phosphorylation site (KKeT).
Quantitative real-time PCR was used to determine whether identified spliced exons displayed altered expression in pregnancy and/or with labour onset. The use of hydrolysis TaqMan probes provided high reaction specificity and sensitivity, and allowed for highly accurate quantification of target sequences. Our results indicate that there was no significant change in expression of the 87 bp spliced exon, in absolute terms, in non-pregnant (NP), pregnant not-in-labour (PNL) and pregnant in-labour (PL) myometrium. Furthermore, analysis of the expression of this spliced exon as a proportion of the total α subunit expressed (i.e. the 87 bp exon-containing α subunit splice variant) also showed no differences between the three tissue sets assayed. The proportion of Maxi-K α subunits expressing this variant was very low, accounting for only ~1% of Maxi-K channels expressed in the three tissues sets. Little is currently known about the physiological effects of expression of this variant of the Maxi-K channel. However, as described above, it contains a consensus sequence for protein kinase phosphorylation; therefore, it may have important consequences for post-translational modification of channel function. Also, the region into which this exon is inserted, between hydrophobic regions S8 and S9 of the α subunit protein, is thought to be involved in determining the Ca2+ sensitivity of the Maxi-K channel [16].
In contrast, while there was no significant change in the mRNA levels of the 132 bp spliced exon in absolute terms between the three tissue sets, there was a significant increase (~1.7 fold) in the proportion of Maxi-K α subunits expressing this exon with labour onset, compared to both non-pregnant and pregnant not-in-labour tissues. Messenger RNA for this 132 bp variant was expressed at much higher levels in comparison to the 87 bp variant, accounting for 9% of total Maxi-K channels in NP and PNL tissues, increasing to 15% at labour onset. An increased proportion of myometrial Maxi-K α subunits expressing the 132 bp spliced exon with labour onset in the human is of interest, as the presence of this exon has been shown to decrease both the Ca2+ and voltage sensitivities of the Maxi-K channel [28]. Thus, our findings may provide an additional explanation for the observation of decreased Ca2+ and voltage sensitivities of Maxi-K channels after labour onset [24] to reduced expression levels of the α- and β-subunits reported recently [27]. The exact mechanism by which the presence of this exon causes decreased sensitivity of the Maxi-K channel is unknown. It is possible that post-translational modifications at the four consensus sites present in the exon, perhaps in combination with conformational changes in the intracellular loop due to its increased length, may bring about the observed changes. Determination of the precise mechanism by which the 132 bp exon causes decreased channel sensitivity is an interesting question and is the subject of ongoing investigations in our laboratory.
Conclusions
Following the onset of labour, the putative disabling of the link between Ca2+ and Maxi-K channel activation would permit Ca2+ levels in the cell to rise without the activation of an opposing K+ conductance, hence increasing the availability of Ca2+ for myometrial contraction [30]. Our findings here suggest that, in human myometrium at labour onset, in addition to decreased Maxi-K α subunit mRNA expression, the increased proportion of Maxi-K α subunits containing the 132 bp spliced exon that are insensitive to Ca2+ and voltage levels, is responsible for enhanced uterine activity at the time of labour. Whether these variants are assembled as homo- or hetero-tetramers at the plasma membrane remains to be determined. Further investigations are required to assess factors such as the role of β-subunit attachment and modulation of the calcium bowl, and their input to regulation of Maxi-K channels during human pregnancy and labour. This study provides the first quantitative analysis of Maxi-K α subunit mRNA expression in human myometrium, and also highlights alternative exon splicing as a potentially important control mechanism by which myometrial Maxi-K channels may be modulated to suit their functional requirements during these physiological processes.
Authors' Contributions
MC designed the quantitative RT-PCR techniques and carried out all experimental work. JJM recruited patients, organised the collection of tissues, and conceived of the study. TJS conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
Acknowledgements
We gratefully acknowledge the support and assistance of the staff of the labour ward at University College Hospital Galway, the National Diagnostics Centre (BioResearch Ireland), Prof. John Hinde, Department of Mathematics, NUI Galway, and Dr. John Kelly, Department of Pharmacology, NUI, Galway. This research was funded by the Higher Education Authority of Ireland, Programme for Research in Third Level Institutions
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| 15383146 | PMC524189 | CC BY | 2021-01-04 16:36:43 | no | Reprod Biol Endocrinol. 2004 Sep 21; 2:67 | utf-8 | Reprod Biol Endocrinol | 2,004 | 10.1186/1477-7827-2-67 | oa_comm |
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Reprod Biol EndocrinolReproductive biology and endocrinology : RB&E1477-7827BioMed Central London 1477-7827-2-681538504810.1186/1477-7827-2-68ReviewMethods to find out the expression of activated genes Cekan Sten Z 1Sten.Cekan@kbh.ki.se1 Karolinska Institute, Department of Woman and Child Health, Division of Reproductive Endocrinology, Karolinska University Hospital, Building L5, 17176 Stockholm, Sweden2004 23 9 2004 2 68 68 8 7 2004 23 9 2004 Copyright © 2004 Cekan; licensee BioMed Central Ltd.2004Cekan; 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.
This review deals with the methods of identifying genes that have been activated by inner or outer impulses. The activation and subsequent expression of a gene can be detected by its transcription into a corresponding messenger ribonucleic acid (mRNA). Principles of the methods for identification of individual activated genes, as well as groups of activated genes are described, the former methods being mostly based on subtractive hybridization and serial analysis of gene expression (SAGE), the latter on microarrays. Examples of gene activation by the hormone 17beta-estradiol (E2) are given.
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Introduction
In previous reviews, methods for the measurement of receptors and their interactions with other transcription factors and genes were described [1-3]. In this review, gene activation is discussed with a particular emphasis on the methods enabling detection of the activated, turned-on, genes. The action of the hormone 17beta-estradiol (E2) is taken as an example of the function of many other small-molecule compounds in gene activation and in the expression of the activated gene.
The life of humans and animals is influenced by the activity of a series of genes that are kept in a silent state, or are activated, depending on the temporary needs of the body. This switching on and off of each gene is executed by an assembly of transcription factors forming a transcription initiation complex (TIC).
Examples of such transcription factors are estrogen receptors (ER-alpha, ER-beta, and possibly other isomers) that, before being incorporated into a TIC, have to be activated by E2. This hormone itself is synthesized, when an initial signal is given, by virtue of an activation of a series of appropriate genes. Via ER, E2 has manifold biological effects. Biological targets of E2 are, inter alia, blood vessel walls [4-8], blood platelets [9], bone [7,10-12], breast cancer cells [13], central nervous system [7,14,15], retinal pigment epithelium [16], synthesis of clotting factors [17].
It is evident that E2 is associated with many biological effects and that many genes must be involved. Consequently, ER must be able to bind to DNA segments, called response elements, in the neighborhood of various genes. The response elements participate, together with other transcription factors, in the formation of TICs that are specific for each gene.
An important problem, currently studied in many laboratories, is to find out which genes are activated in various circumstances. The methods that solve this problem are based on a comparative (differential) approach. A test (target) sample, containing active genes is compared with a control sample in which the genes have not been activated. Using this approach, the active genes are singled out among the multitude of inactive genes. However, the comparisons may reveal the opposite of activation, i.e., downregulation of genes.
Generally, the activity of a gene is characterized by its transcription into mRNAs as the first step leading to the synthesis of specific proteins. Non-activated genes in the control tissue do not produce any corresponding mRNAs. In most methods, the mRNAs prepared from the test and control tissue are each reverse transcribed into the corresponding complementary deoxyribonucleic acid (cDNA), in order to enable a substantial increase of the material for analysis by polymerase chain reaction (PCR) [2]. As most methods do not operate with full mRNA transcripts, but with shorter sequences, the allocation of such sequences to known (or unknown) genes has to be found by advanced computer programs and gene databases.
The methods used for the identification of active genes are sketched below. Included are even methods that have not yet been used for the identification of E2-activated genes. It has to be mentioned that only principles, not technical details are dealt with in this review. Neither the techniques of cloning or of identification of genes by sequencing are described here. The readers who are not familiar with these techniques are advised to consult appropriate textbooks [e.g., [18]]. The dedicated computer programs and databases that are needed for the identification of sequences or genes will not be described here either. These can be found in the references quoted below. It will only be mentioned here that the large databases are GenBank and Celera .
Activated (expressed) genes can be found by comparison of gene contents in the test and control tissues. There are essentially two approaches for finding activated genes: (i) an individual identification, or (ii) an identification of expression profiles after hybridization to a set of known gene fragments (probes) attached to chips in microarrays.
Individual identification
This approach means that genes are identified individually, even if several genes can eventually be picked up after cloning. There are several methods that can be used.
Differential display
Differential display seems to be the technically simplest method. Its name stems from the end-point that is a comparison of a side-by-side display of the test and control preparations by electrophoresis. In its basic form, total RNA of the test and control samples is separately subjected to reverse transcription into cDNA that, in turn, is PCR-amplified using arbitrarily chosen primers. The products are applied to a gel electrophoresis and the band(s) that are specific for one of the preparations are cut from the gel, further amplified by PCR (using the same primers) and eventually sequenced [19].
In a more advanced version, mRNAs of the test and control cells are separately reverse transcribed to cDNA (Fig. 1). Each transcription is carried out in the presence of a oligo(dT) primers, directed to the poly(A) tail at the 3' terminus of the mRNA and constructed as 5'(NMT11)3' where N can be guanine (G), adenine (A), thymine (T), or cytosine (C), and M is G, A, or C [20-22]. The primers with G residues are superior to those having one C residue. Those ending in A or T are the least efficient. With use of an arbitrary decamer as the second primer, a PCR is carried out to amplify the transcript in order to obtain a sufficient working material. This is usually done in the presence of a radioactive nucleotide. Other methods are commonly used, such as silver staining. Amplified DNA fragments are separated on a denaturing polyacrylamide gel, the test preparation side by side with the control. Each band differing from those seen in the control electrophoresis is then used for sequencing, subcloning, or as a probe for cDNA library screening. Large amount of results can be obtained depending on the variation in N and M nucleotides. In spite of the basic simplicity of the procedure, the time and workload can be considerable, depending on the number of NM combinations tried.
Figure 1 Principle of a differential display. Test and control mRNA are separately reverse transcribed in the presence of anchored oligo(dT) primers containing nucleotides N and M in various combinations (see the text). The same primer and an arbitrary decamer are then used as primers in a PCR. The products are subjected to electrophoresis (PAGE). An additional band (see arrow) in the test sample represents a gene that had not been activated in the control sample. A11 and T11 denote eleven A and T molecules, respectively.
Subtractive hybridization with hydroxylapatite separation
The test mRNA is reverse transcribed into cDNA [23]. This is hybridized with the mRNA of the control sample (Fig. 2). A portion of the test cDNA (corresponding to the activated gene) does not find any complementary part in the mRNA of the control sample and remains non-hybridized as a single-stranded cDNA (ss-cDNA). This can be isolated by chromatography on a hydroxylapatite column. The hybridization of the isolated ss-cDNA with control mRNA followed by another chromatography can be repeated to increase the purity of the isolated product [23]. A cDNA library is produced and the subtracted sequence eventually identified. Alternatively, a second hybridization of the isolated ss-cDNA is carried out with the original test mRNA giving rise to a cDNA-mRNA hybrid which, after conversion to double stranded cDNA, is inserted into a vector, a cDNA library is constructed and several specific cDNA clones are isolated, leading to the identification of several genes [24].
Figure 2 Flow-sheet of subtractive hybridisation with hydroxylapatite separation. Test mRNA is reverse transcribed into a cDNA. This is hybridized with control mRNA. The non-hybridized portion of the single-stranded sequence of test cDNA is separated by chromatography on hydroxylapatite (HAP) and further processed.
In another variant [25], the test and control mRNAs are both reverse transcribed into cDNA. cDNA of the test sample is hybridized with cDNA of the control sample. The non-hybridized part of the test cDNA is a single-stranded DNA that is separated by hydroxylapatite. The single-stranded DNA is cloned into a vector to produce a subtracted library. Clones with a strong hybridization signal to the subtracted probe are selected and sequenced.
Subtractive suppression hybridization with PCR
Isolation of a single-stranded test cDNA is not needed in this method. mRNAs of the test and control samples are prepared and each is reverse transcribed into cDNA. Each transcript is digested with the enzyme RsaI to obtain shorter, blunt-ended fragments. The test cDNA is divided into two portions (see Fig. 3). One of them is ligated with Adapter A, the second with adapter B. Each portion is hybridized with an excess of control cDNA. A mixture of hybridization products is formed (Fig. 3). A tiny fraction of cDNA remains unhybridized, single-stranded. This is a fragment that may be called specific, or differentially expressed, or subtracted. It originates from the gene that had been activated. It is absent in the control sample. This specific fragment is bound either to Adapter A or B in the two portions. In the second hybridization, the portions are mixed. After annealing, a small amount of the specific fragment is obtained double-stranded. It contains Adapter A on the one end and Adapter B on the other. After adding primers specific for the Adapters, the ends are filled and the specific fragment is amplified by PCR to make sure that sufficient amounts are available for a further processing. Cloning, sequencing and comparing with a gene database establish the identity of the gene(s) [26,27] [ – "PCR-Select Subtraction kit"]. In contrast to the above methods, the primers for PCR amplification are clearly defined, avoiding thus problems with random primers. This method was used in a number of studies, such as the identification of genes upregulated in rats by E2 and progesterone treatment [28]. A predecessor of this technique is the "representational difference analysis" [29,30].
Figure 3 Outline of subtractive suppression hybridisation with PCR. Test cDNA and control cDNA are digested with RsaI. The test cDNA sequences are divided into two halves, one of them being ligated with Adapter A (empty squares), the second one with Adapter B (filled squares). Each half is hybridized with control cDNA. The single-stranded (non-hybridized) sequences of both halves (denoted by asterisks) are annealed in a second hybridization step, primers to the Adapters are added and, after PCR, cloning and gene identification are carried out.
Expressed sequence tags (EST)
To describe the EST method, the following example is given. cDNA libraries were prepared by reverse transcription from mRNAs of the tissues to be examined [31]. The libraries were converted to plasmids, transfected into Escherichia coli and plated. Hundreds of clones were picked at random. These were subjected to sequencing, followed by computer matching to known genes listed in the GenBank database. The average length of a sequence was 397 bases; ESTs longer than 150 bases were found to be most useful for similarity searches and mapping.
Subtractive hybridization (see above) was used to isolate the ESTs specific for one of the libraries. For example, a fibroblast cell line cDNA library was hybridized with a hippocampus library; the common sequences were removed and the specific hippocampus sequences remained. Using the EST method, more than 2000 human brain genes were identified [32].
Serial Analysis of Gene Expression (SAGE)
The SAGE allows serial analysis of gene expression, an analysis of thousands of transcripts. It is based on the assumption that a short nucleotide sequence 10 base pairs (bp) – a tag – contains sufficient information to uniquely identify a transcript. In this respect SAGE differs from the EST approach.
The principle of SAGE is as follows: mRNA is reverse transcribed into cDNA with use of a biotinylated primer, the cDNA is cleaved with a restriction endonuclease and the 3' portions are then isolated by binding to streptavidin beads [33]. In another version() (Fig. 4), mRNAs are captured prior to reverse transcription on oligo(dT) magnetic beads. Double stranded cDNAs are synthesized and digested with the restriction endonuclease NlaIII that cleaves most transcripts at least once. The part attached to the magnetic bead is further processed. The reaction mixture is divided into two portions. The portions are ligated via a restriction site R to an adapter A and B, respectively, each consisting of 40 bp. Taking advantage of the restriction sites R, both portions are cleaved with the restriction enzyme BsmFI in the distance of 14 bp. In this way "tags" are formed. Out of these 14 bp, 4 bp are a non-specific segment GTAC. These tags are blunt-ended with the Klenow fragment of DNA polymerase I. The two separate pools of tags are ligated together via a blunt-end ligation to produce "ditags". The ditags, flanked by the adapters A and B, are amplified by PCR with use of primers for A and B. The adapters are removed by the enzyme NlaIII and the ditags are concatenated. The resulting concatemers (a series of linked ditags) are cloned into a plasmid vector to create a SAGE library. Individual clones are then sequenced. SAGE is carried out for each sample to be compared.
Figure 4 Flow-sheet of SAGE. mRNAs are captured on oligo(dT) magnetic beads (open ovals). Double stranded cDNAs are synthesized. They are digested with Nla III. The product is divided into two halves. These are ligated to 40 bp adapters AR and BR, respectively. Both adapters contain a sequence R that is a recognition site for the restriction enzyme BsmFI. This cuts a 14 bp sequence 3' of the site, forming a 10 bp tag. After cleavage with BsmFI, the tags are ligated to form a product containing a ditag (the points of ligation are denoted by filled circles). This is amplified using primers complementary to A and B. The AR and BR adapters are cut away with Nla III to release a ditag. These are ligated to form concatemers containing multiple ditags. The concatemers are cloned and sequenced.
Thanks to the concatenation, many tags can be detected in a single clone [33]. As each tag is supposed to uniquely identify a transcript, SAGE can generate a comprehensive profile of gene expression. Indeed, many unique transcripts were identified with use of SAGE tags [34]. The method is particularly useful for detecting genes of low level of expression or in rare tissues (e.g., early embryo) [35,36]. In addition, the amount of individual tags provides quantitative estimates of gene expression [37].
Still, the specificity of detection of genes with use of the short tags is not absolute. There are two main problems [38]. The first one is that many SAGE tags have no match to known sequences in databases. These tags may represent so far unidentified genes, but their shortness makes it difficult to characterize the genes. The second problem is that the SAGE tags may find multiple matches in the databases [39,40]. Therefore, attempts have been made to increase the specificity by prolongation of the tags by various methods.
One such method is called GLGI (Generation of Longer cDNA fragments from SAGE tags for Gene Identification) [34,38,40]. The main feature of this method is the use of a SAGE tag as the sense primer for the PCR of a segment of cDNA. An anchored oligo(dT) serves as an antisense primer. In this manner a cDNA "tag" of up to several hundred bases is created. However, this method does not seem to improve the specificity of SAGE because even "non-specific" tags are co-amplified.
Better of seems to be another variant of SAGE, the LongSAGE [41]. This is based on the use of tags 21 bp (out of which 4 represent a restriction site), tags longer than those in SAGE. The prolongation of tags is achieved by the use of the restriction endonuclease MmeI. The longer tags increase the power of identification of genes, while not diminishing the sensitivity of SAGE given by the use of PCR and concatenation. Theoretical calculations showed that >99.8% of the 21 bp tags were expected to occur only once in a genome.
SAGE was used for the investigation of differences in gene expression in various health conditions. In the studies of breast tumors [37], global gene expression profiles in breast carcinoma cells were compared with those in normal mammary epithelial cells. The patterns of gene clusters in normal tissue were distinctly different from those of tumors of different stage and histological grade. The most dramatic change occurred at the normal-to-in situ carcinoma transition. This change can be an important marker for an early diagnosis. In another study, several genes regulated by estrogen or tamoxifen were identified in an estrogen-dependent breast cancer cell line. One of them was studied closer. It appeared to play a significant role in estrogen-promoted cell growth [42].
Gene profiles – microarrays
The DNA microarray analysis is used to identify profiles of expressed genes in a given tissue and time. Thousands of known cDNA sequences or oligonucleotides are imprinted on a solid support, sometimes called a chip (e.g., a microscope slide or a nylon membrane), using application robots. Typically, individual spots are 100–300 micrometers in size and are spaced about the same distance apart [43]. More than 30,000 sequences can be fitted on the surface of a chip. These sequences serve as probes. Alternatively, the probes are synthesized in situ (60-mers) [44]. By hybridization, test (target) sequences (cDNAs or cRNAs) are bound to the cognate probes. The basic approach is the comparison of degree of hybridization in the control and test preparation. There are two basic techniques for the detection of hybridization. The control and test preparations are placed on a single chip, or, separately, on two chips.
In the single chip technique [18], mRNAs from the control and test cells/tissues are separately reverse transcribed. During the transcription processes two different fluorescent dyes (e.g., Cy3 – green, Cy5 – red) are incorporated into the control and test cDNAs, respectively. The labeled molecules are mixed and hybridized to the cDNA array. There is a competition for each probe on the chip between the control and test mRNAs. The test cDNAs are selectively bound to some probes, the control cDNAs may be bound to other probes. With use of fluorescence scanning it is possible to distinguish the hybrids with control sequences (exhibiting, e.g., green fluorescence) from the hybrids with test sequences (e. g., red) [45]. Alternatively, the dyes may be reversed, and the control and test cDNAs may be labeled with the red and green dye, respectively. The hybrids that arise when the control and test cDNA occur in equal amounts may show a yellow fluorescence. The black spots indicate no hybridization (Fig. 5). One of the commercial companies utilizing this approach is Agilent .
Figure 5 Model of a microarray. In a single-chip technique reverse transcription from mRNAs to cDNAs is separately carried out for the test and control cell preparations. During the transcription one of the fluorescent dyes (e.g., Cy3 – green and Cy5 – red) are incorporated into the cDNAs of each preparation. A mixture of these two preparations is then hybridised to the corresponding gene-representing sequences on a chip. The activated genes of the control sample exhibit green color, those of the test sample provide red spots, equally bound cDNAs can be visualized by yellow spots, no hybridization remains black.
Using a variant of the method [46,47], certain groups of activated genes could be defined as predictors of the clinical outcome of breast cancer. Up to 5000 genes were tested for up-regulation (red) or down-regulation (green) in up to 100 patients with various degrees of disease progression. Correlations of disease grades with gene expression profiles were established, and a strategy was provided to select patients who would benefit from adjuvant therapy.
In the two-chip technique, mRNAs of the test and control tissues/cells is reverse transcribed into a double-stranded cDNA from which a cRNA is prepared. In the course of the cRNA synthesis biotin molecules are incorporated [48]. The control and test cRNAs are separately hybridized to two identical chips. The binding is detected by staining with a fluorescent dye coupled to streptavidin. Signal intensities are used to calculate the relative cRNA abundance for the genes represented on the array. For comparisons of the intensities on both chips advanced computer programs have to be used. A combination of single-chip and two-chip techniques was applied in a study [51] where two chips and two fluorescent dyes were used.
Commercial systems are available from several sources. For example, Affymetrix (GeneChip) [] produce chips by a photolithographic method in which thousands of different oligonucleide probes are synthesized in situ on the chip [49]. A compact technique has been introduced by the Febit company [50]. In a single benchtop instrument called Geniom a light-activated oligonucleotide microarray synthesis takes place, as well as addition of biotin-labeled cRNA sample, hybridization and fluorescence detection after incubation with streptavidin-phycoerythrin [50]. Other systems for microarray production, target preparation, hybridization and result evaluation are offered by Amersham Biosciences and Clondiag Chip Technologies .
As a rule, more than one gene is activated, and a spectrum of genes is discovered either occurring sporadically or in clusters [49]. For example, when a diseased tissue was compared with a healthy one, an expression profile, a disease fingerprint, was identified [49]. In the case of breast tumors, a molecular portrait of each tumor was obtained [52], or, molecular profiling (a set of gene clusters) provided predictions of responses to adjuvant treatment [46,53]. Gene activation in breast cancer cells in the presence of E2 included, apart from the known estrogen-responsive genes, a series of novel genes expressing growth factors and components of the cell cycle, adhesion molecules, enzymes, signaling molecules and transcription factors [48]. Gene expression patterns of breast carcinomas allowed to distinguish tumor subclasses [54]. E2 caused up-regulation of 250 genes in vascular endothelial cells that could be prevented by an inhibitor [55]. In an experimental encephalomyelitis a markedly enhanced gene activation by E2 was noted [56].
Sometimes a technically easier macroarray is used, e.g., on a 96-well plate [57]. Obviously, the choice of gene sequences to be used as probes must be very selective in this case. This approach has been adopted by the SuperArray Bioscience Corporation offering selected profiles of genes in the macroarray format for various areas (e.g., cancer, cell cycle, cytokine and inflammatory response, etc.).
Quite often the gene identification obtained by an array is confirmed by other methods such as Northern blot analysis [58], or real-time PCR [43,58][]. A negative identification can be achieved by the use of siRNA (small interfering RNA – SuperArray Corp.). siRNAs are short RNA duplexes between 15 to 21 nucleotides in length. Once transfected into cells, a siRNA targets the mRNA containing an identical sequence and degrades it in a catalytic manner. The degraded message is no longer functional in translation (the biosynthesis of protein) and thus in the expression of the corresponding gene. SuperArray Corp. provides a line of validated populations of siRNAs in the form of SureSilencing siRNA kits.
Conclusions
The methods described above can suit two purposes. The single-gene methods can detect and identify new, previously unknown, genes, whereas microarrays can handle a great number of known genes to establish profiles of their expression.
SAGE seems to have advantages over hybridization-based methods for the studies of gene expression, such as differential display and subtractive hybridization. SAGE is superior to the EST approach in providing high efficiency in identifying the genes that are expressed at low levels and that represent a majority of genes in the human genome [36].
Microarray techniques usually detect activation of a multitude of genes – a gene profile – that differs from the profile in control tissues/cells and thus – in medicine – may have a diagnostic and/or prognostic value. However, the microarray techniques usually require commercially produced chips as well as specialized equipment and advanced, powerful, computing facilities. Thus they are hardly affordable for small or medium-size laboratories unless they have substantial financial resources.
A big question at another level remains so far unanswered: which is the biological "chain of commands" in a given tissue and time resulting in the activation of genes enabling the biosynthesis of cornerstones for gene activation, such as ligands (e.g., E2), receptors (e.g., ER) and other transcription factors, the entire machinery leading to gene activation and expression.
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| 15385048 | PMC524190 | CC BY | 2021-01-04 16:36:43 | no | Reprod Biol Endocrinol. 2004 Sep 23; 2:68 | utf-8 | Reprod Biol Endocrinol | 2,004 | 10.1186/1477-7827-2-68 | oa_comm |
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Theor Biol Med ModelTheoretical Biology & Medical Modelling1742-4682BioMed Central London 1742-4682-1-91544778710.1186/1742-4682-1-9ResearchA mathematical model for LH release in response to continuous and pulsatile exposure of gonadotrophs to GnRH Washington Talitha M 1twashington@cnr.eduBlum J Joseph 2jblum@cellbio.mc.duke.eduReed Michael C 3reed@math.duke.eduConn P Michael 4connm@OHSU.edu1 Department of Mathematics, College of New Rochelle, USA2 Department of Cell Biology, Duke University, Durham, USA3 Department of Mathematics, Duke University, Durham, USA4 Oregon National Primate Research Center, Oregon Health & Science University, Beaver-ton, USA2004 24 9 2004 1 9 9 14 6 2004 24 9 2004 Copyright © 2004 Washington et al; licensee BioMed Central Ltd.2004Washington 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 a previous study, a model was developed to investigate the release of luteinizing hormone (LH) from pituitary cells in response to a short pulse of gonadotropin-releasing hormone (GnRH). The model included: binding of GnRH to its receptor (R), dimerization and internalization of the hormone receptor complex, interaction with a G protein, production of inositol 1,4,5-trisphosphate (IP3), release of calcium from the endoplasmic reticulum (ER), entrance of calcium into the cytosol via voltage gated membrane channels, pumping of calcium out of the cytosol via membrane and ER pumps, and release of LH. The extended model, presented in this paper, also includes the following physiologically important phenomena: desensitization of calcium channels; internalization of the dimerized receptors and recycling of some of the internalized receptors; an increase in Gq concentration near the plasma membrane in response to receptor dimerization; and basal rates of synthesis and degradation of the receptors. With suitable choices of the parameters, good agreement with a variety of experimental data of the LH release pattern in response to pulses of various durations, repetition rates, and concentrations of GnRH were obtained. The mathematical model allows us to assess the effects of internalization and desensitization on the shapes and time courses of LH response curves.
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Background
Gonadotropin-releasing hormone (GnRH) is released by the hypothalamus in a pulsatile fashion and stimulates luteinizing hormone (LH) and follicle stimulating hormone (FSH) release by pituitary cells by a complex series of signaling processes. Although there is substantial information about various individual steps in the signaling system, there is less understanding of how these components interact to give rise to the overall behavior of the system. The frequency of pulses varies throughout the menstrual cycle increasing markedly just prior to ovulation. And, it has been observed in in vitro experiments on perifused pituitary cells that pulse frequency and concentration have marked (nonlinear) influences on the release of LH and FSH. The purpose of our work is to use mathematics and machine computation to understand the dynamics of this important and interesting physiological system.
In a prior study, [1], a mathematical model was developed to investigate the rate of release of luteinizing hormone from pituitary gonadotrophs in response to short pulses of gonadotropin-releasing hormone. The model included binding of the hormone to its receptor, dimerization, interaction with a G-protein, production of inositoltrisphosphate (IP3), release of calcium from the endoplasmic reticulum (ER), entrance of calcium into the cytosol via voltage gated membrane channels, pumping of calcium out of the cytosol via membrane and ER pumps, and the release of luteinizing hormone (LH). Cytosolic calcium dynamics were simplified and it was assumed that there is only one pool of releasable LH. Despite these and other simplifications, the model results matched experimental curves and enabled us to understand the reasons for the qualitative features of the LH release curves in response to GnRH pulses of short durations and different concentrations both in the presence and absence of external calcium. We note that Heinze et al, [2], created a mathematical model for LH release that reproduces some data for pulsatile administration of GnRH. Their model, however, does not include most of the important intracellular mechanisms known to play important roles; thus, they match data but do not study mechanisms. We also note that mathematical models for other aspects of the reproductive hormone system have been created: Keenan et al, [3], developed a stochastic systems model for the interactions between GnRH, LH, and testosterone; Gordan et al, [4] modelled the pulsatile release of GnRH by hypothalamic neurons.
There are four important medium-term effects that were not included in the previous study. Desensitization of the response to GnRH occurs because after GnRH binds to its receptors, some of the bound complexes are internalized and partially degraded [5]. Secondly, prolonged exposure to GnRH desensitizes the outer membrane calcium ion channels, as described in detail by Stojilkovic et al [6]. Thirdly, there exist basal rates of receptor synthesis and degradation. Finally, in response to GnRH, there also occurs an increase in the number of Gq/11 proteins closely associated with the plasma membrane [7]. Incorporation of these four phenomena into the previous model allows us to analyze the contrasting effects of desensitization and signal amplification during medium-term continuous and pulsatile exposures to GnRH. We then show that the LH response curves of the enlarged model capture most of the essential features of a large number of experimental studies.
It should be noted that in the present model we ignore the long-term effects that result in changes in DNA, messenger RNA, and protein concentrations (e.g., receptor number) that are known to occur several hours after exposure to GnRH [8-11]. Thus, in the present study, we limit the time of exposure to three hours. We also ignore the long term effects of diacylglycerol which is known to cause an increase in the synthesis of LHα, the α subunit of the LH dimer [12].
Model Development
Let H(t) represent the GnRH concentration (nM) in the surrounding medium t minutes after the initiation of the experiment. Initially, the hormone is bound by the receptor, R.
The bound complex HR reacts with itself to form dimers [13], denoted by HRRH.
A Gq/11 protein, denoted GQ, reacts with the dimer to produce an effector, E (e.g., phospholipase C, [13]).
The values of the rate constants, k1, k2, k3, k-1, k-2, k-3, are the same as in our earlier model [1]. The abbreviations for the physiological components of the model are listed in Table 1 and all the rate constants for the current model are listed in Table 2.
Table 1 Glossary of Variables
H GnRH concentration (nM)
R Free GnRH receptor concentration (nM)
HR Hormone-receptor complex concentration (nM)
HRRH Hormone-receptor dimer concentration (nM)
GQ Gq/11 protein concentration (nM)
E Effector concentration (nM)
IP3 Inositol 1,4,5-trisphosphate concentration (nM)
CAC Cytosolic Ca2+ concentration (μM)
CAER ER Ca2+ concentration (μM)
CHO Fraction of open ER Ca2+ channels
LH LH concentration (ng)
Table 2 Constants
R0 Total receptor concentration (nM)
GQ0 Total Gq/11 protein concentration (nM)
ERUL Resting Ca2+ concentration in ER (normally 40 μM)
CAE External Ca2+ concentration (normally 1000 μM)
α = 2 nM-1, see equation (17)
β = 4 min-1, see equation (17)
v1 = 0.02 min-1, see equation (12)
v2 = 0.002 min-1, see equation (12)
r0 = 0.6, fraction internalized receptors returned
P0 = 8.3 × 10-6 nM·min-1, basal rate of receptor synthesis
γ = 8.3 × 10-4 min-1, basal rate of receptor degradation
k1 = 2.5 nM-1·min-1
k-1 = 5 min-1
k2 = 2500 nM-1·min-1
k-2 = 5 min-1
k3 = 4000 nM-1·min-1
k-3 = 200 min-1
k5 = 2 × 107 min-1
k-5 = 10 min-1
k6 = 1 nM-1·min-1
k66 = 10 nM-1·min-1
k666 = 0
k-6 = 5 min-1
k7 = 2.2 μM·min-1
k8 = 0.4 nM-1·min-1
k88 = 0
k888 = 0
k9 = 0.0002 min-1
k10 = 5 ng·min-1
k11 = 0.0008 nM-1·min-1
k33 = 2.7 min-1
The monomers, HR, can also interact with each other to form larger aggregates [14]. Macroaggregation and internalization occur at least 20 minutes after exposure to GnRH [14]. All of the internalized hormone and some of the receptors are then degraded, and the receptors that are not degraded are returned to the membrane [15,16]. We assume that a fraction of receptors, r0, can be returned intact to the membrane after a time delay of 20 minutes. Consistent with the data of [14], we assume that r0 = 0.6. Since we are not concerned with the details of the internalization or return processes, we adopt simple first order reactions for these processes. We assume that n monomers, HR, are internalized at a rate k11 and that r0n monomers that have been internalized are available to be returned to the membrane at rate k11.
There is evidence that the macroaggregates consist of an average of n = 100 monomers [14]. In our model, we will choose k11 = 0.08/n = 0.0008 nM-1·min-1. With this choice, 7% of the receptors are internalized after a 5 minute pulse of 1 nM GnRH, and 60 minutes after the initial exposure, approximately half of the internalized receptors have returned. It should be noted that it is only the combination k11n that occurs in the equations.
We make the following simple assumption about the recyling of receptors (consistent with the data of Maya-Nunez et al. [17] and Table 2 of Conn et al. [18]). i.e. that the formation of macroaggregates begins 20 minutes after exposure to GnRH and that the internalization and recycling process takes 20 minutes after the formation of the macroaggregates. Let χ(t) be the function that equals 1 for t ≥ 0 and equals 0 for t < 0. Then, at time t, the rate of internalization of receptors is k11n[HR](t) and the rate of return of receptors to the membrane is k11n[HR](t - 40)χ(t - 40). To simplify notation, we write [HR]40 = [HR](t - 40)χ(t - 40).
Since only 60% percent of the internalized receptors are returned to the membrane after exposure to GnRH, there would not be a full recovery of receptors in the membrane. In the model we therefore include a low basal rate of receptor synthesis, P0 = 8.3 × 10-6 nM·min-1, and degradation, γ = 8.3 × 10-4 min-1. The ratio is chosen so that the resting (in the absence of hormone) receptor concentration is R0 = 10-2 nM, and the magnitude of P0 is chosen so that approximately of the resting amount of receptor is produced per hour, thus ensuring a slow recovery to the steady state receptor concentration in the absence of GnRH.
The number of membrane associated GQ proteins increases in response to a GnRH agonist as described by Cornea et al [7]. For simplicity we assume that the increase of GQ proteins near the membrane depends on the concentration of HRRH in the membrane. The kinetic coefficient k33 is the parameter that determines the rate of increased concentration of GQ at the membrane in response to the formation of HRRH. We are assuming a finite pool of GQ that can be transported from the cytoplasm to the immediate vicinity of the plasma membrane. This pool is assumed to be regulated by the amount of HRRH for only the first 20 minutes, and after this time the rate of increase is negligible [7]. To fit the experimental data, we choose k33 = 2.7 min-1 and multiply the kinetic coefficient k33 by e-t/20. With these parameters, 60 minutes after a constant exposure to 1 nM GnRH, there is a 40% increase of GQ concentration near the membrane and 120 minutes after exposure to the hormone, there is only a 43% increase. The following differential equations reflect the physiological assumptions that we have so far discussed.
We further assume that the production of IP3 is proportional to the concentration of E and that it is converted to inactive metabolites at a rate proportional to its concentration.
As in [1], the fraction of open channels in the ER, denoted by CHO, depends on IP3 concentration. CHO reaches its maximum 0.25 min after exposure to GnRH and the maximum value of CHO is 0.6. To incorporate multiple pulses, we modify the function CHO from the previous model so that it reaches its maximum 0.25 min after the start of each pulse. Thus we have
where tp is the time after the start of each individual pulse and, as in [1],, α = 2 nM-1 and β = 4 min-1.
In response to GnRH, calcium is released from the ER into the cytoplasm with a rate constant ERR and is pumped back into the ER. As discussed in the previous model, the rate constant ERR increases proportionally to cytosolic calcium concentration, CAC, with a rate constant k66 and is inhibited at high CAC at a rate that is proportional to the square of CAC, with a rate constant k666. Just as in, [1], k6 = 1, k66 = 10, and k666 = 0, i.e., we ignore the inhibitory effects of calcium on reuptake of calcium into the ER.
ERR = k6 + k66[CAC] - k666[CAC]2 (8)
The change in cytosolic calcium concentration, CAER, is then determined by the rate constant ERR, which is the rate of extrusion, multiplied by the fraction of open channels, CHO, and the difference in concentration between the calcium concentration in the cytoplasm and the endoplasmic reticulum. As in Blum et al. [1], calcium is actively transported back into the ER by pumps with the rate constant k-6 = 5 min-1.
As in the previous model, the volume of the ER is assumed to be 1/20 of the volume of the cytosol. CAC is determined by the rate of calcium efflux through ion channels in the ER membrane minus the rate at which calcium is being pumped back into the ER, plus the rate of calcium entry from the plasma membrane. The function VSR denotes the rate of calcium influx from extracellular calcium into the cytosol and depends on E with rate constant k8 [19] and on CAC with rate constants k88 for the influx at low CAC and k888 for the inhibitory effects at high CAC. There is considerable evidence that desensitization occurs, i.e., the fraction of open calcium channels in the cell membrane decreases soon after exposure to GnRH [18]. Since the precise mechanism of desensitization in unknown, we assume that VSR depends on E and CAC, and that channels slowly become inactive in response to exposure to GnRH, consistent with the experimental data [18]. We further assume that the fraction of open calcium channels in the outer membrane, denoted by VSRO(t), decreases at a linear rate of v1 = 0.02 min-1 when the hormone is applied and has a minimum value of 0. In the absence of hormone, the fraction of open channels increases at a linear rate of v2 = 0.002 min-1 and has a maximum value of 1. Thus, immediately a five minute pulse of 5 nM GnRH, 10% of the channels are in the refractory state and 50 minutes after the removal of the GnRH, all of the channels have recovered, consistent with experimental data; see [18] for more details. Incorporating calcium influx, pumps and leakage into the cytoplasm from the medium (the term k9 [CAE], we have
where
VSR(t) = (k8E(t) + k88[CAC](t) - k888([CAC])(t))2) × VSRO(t) (11)
and VSRO satisfies the following.
0 ≤ VSRO(t) ≤ 1 (13)
Finally, the rate of release of LH depends on cytosolic calcium concentration (see Blum et al. [1] for details). Although there is evidence that there are three pools of LH in gonadotrophs, one pool, comprising of only 2% of the total LH, is released within one minute after exposure to GnRH, and the third pool is not released during continuous exposure to GnRH (Naor et al.,[20]). Therefore, as in the previous model [1], we treat LH as being released from a single pool.
The mathematical model consists of equations (1) – (14). These non-linear equations cannot be solved analytically but solutions can be obtained by machine computation. To do this, we used the solver ODE45 in Matlab.
The values of the rate constants are given in Table 2. The values for many of them are discussed in detail, with references, in our original paper, [1]. The values of the rate constants for the signalling mechanisms introduced in this paper were discussed (above) as the mechanisms were introduced. In some cases the rate constants were taken from experimental data (references given) and in other cases, where direct experimental data does not yet exist, we explained the rationale for our choices. Since the resulting model captures and explains many experimental studies (see below), these choices provide useful predictions for future experimental studies.
Results
In Figure 1, we compare the amounts of LH released in 5 minute intervals in the original model and the present model in response to continuous administration of 5 nM GnRH. In both models there is an initial large pulse of LH released. However, in the original model (open circles in Panel A) the long-term release plateaus at a high level, while in the present model (solid circles) the long term release declines to a low level. Panel A in Figure 4 contains experimental results of Hawes et al. [21], that clearly show show a decline in LH release to a low level after approximately 1.5 to 2 hours. Similar experimental results were obtained by Baird et al, [[22], Figure 4] and by Janovick and Conn, [[5], Figure 1, Panel A].
Figure 1 Amount of LH released in five minute intervals in response to constant exposure to 5 nM GnRH. The solid circles show the results of the present model while the open circles show the results of the original model [1]. The decay of LH release to zero is in accord with experimental results (see discussion in text); thus, new mechanisms included in the present model allow one to match this data (and other data, see other figures) from several laboratories for medium-term GnRH exposure experiments.
Figure 4 Experimental data of Hawes et al.[21]. Gonadotrophs were treated continuously with lO nM GnRH (Panel A), with 5 minute pulses every 30 minutes (Panel B), or every 15 minutes (Panel C).
Figures 2 and 3 show in detail the changes that occur in all components of the system during the model experiments described above. Fig. 2A shows the total amount of the LH released as a function of time while Fig. 2B shows the LH release rate (LHRR), which peaks within one minute after exposure to GnRH and then declines slowly for the next 50 minutes to a very low value in the present model. Note that LHRR is the instantaneous rate of LH release (in ng/min) while LH release in Figure 1A is in ng released in each five minute interval. In the previous model(dashed lines), LHRR plateaus at a high level (Figure 2B), so the total LH released increases linearly (Figure 2A). In the present model (solid lines), LHRR declines to a low level. In both the previous and present models, there is a rapid extrusion of calcium from the ER (Fig. 2D) and an initial rapid increase in CAC (Fig. 2C), which correlate well with the time course of the rate of change of LHRR (Figure 2B). However, the long-term behavior is different in the two models because in the present model CAC declines to a low plateau. This explains the similar drop in LH release since the rate of LH release depends on CAC (see equation (14)). The drop in CAC is caused by the desensitization of the outer membrane channels; Figure 2E shows that the fraction of open channels declines linearly to zero in 50 minutes. In the ER membrane, there is an almost instantaneous increase of open calcium channels followed by a rapid decrease and then a slight further decline (Fig. 2F).
Figure 2 Panel A shows the total amount of LH released as a function of time during continuous exposure to 5 nM GnRH, while Panel B shows the instantaneous rate of LH release at each moment of time. Panels C and D show the calcium concentration in the cytosol and the endoplasmic reticulum, respectively. Panels E and F show the fraction of open calcium channels in the outer membrane and the endoplasmic reticulum, respectively. The solid lines show the results of the present model while the dashed lines show the results of the earlier model [1].
Figure 3 Panels A, C, and D show the concentrations of free, bound, and dimerized receptors, respectively, while Panel B shows the total amount of receptors in the membrane. Panel E shows the concentration of IP3. Panel F shows the GQ concentration at the membrane as a function of time during the continuous exposure to 5 nM GnRH. The solid lines show the results of the current model and the dashed lines show the results of the earlier model in [1].
Figures 3A and 3C show the concentrations of free receptors and receptors bound to the hormone. It can be seen that, initially in both the present and previous models, there is a very rapid decline in free receptors, R, and a very rapid increase of receptors to which GnRH has bound (HR) but have not yet dimerized. This is immediately followed, as shown in Figure 3D, by the formation of the dimers (HRRH). After this initial reaction, the concentrations of HR and HRRH remain constant in the previous model, but decline in the present model due to internalization and degradation. The recycling of receptors was assumed to start at 40 minutes (see equation (1)), which is why the rates of decrease of HR and HRRH decline at that time. Because of degradation, only a fraction (r0 = 0.6) of the internalized receptors are returned to the membrane. Thus, in the presence of continuous exposure to GnRH, the total number of receptors in the membrane continues to decline as shown in Figure 3B. The rate of change of IP3 (Fig. 3E) is closely related to the rate of change of HRRH as shown in Fig. 3D. Finally, Fig. 3F shows that there is a slow increase of approximately 43% of the concentration GQ associated with the membrane during the exposure.
Figures 6, 7, and 8 show model results for gonadotrophs exposed to 5 minute pulses of 5 nM GnRH administered every 15 minutes for a total duration of 3 hours. In the previous model (Figure 6A, open circles), there was a drop in LH release between the first and second pulse, but the same amount of LH was released in response to all subsequent pulses, contrary to experimental observations. The initial drop occurs because there is insufficient time for the calcium in the ER to refill completely (data not shown). In the present model, in response to the first pulse there is a large release of LH. In response to the second pulse considerably less LH is released, and in subsequent pulses there is a steady decline in the amount of LH released. This continual decline in LH release has been observed in a large number of experiments. Panels B and C of Figure 4 show the results of Hawes et al [21] obtained from female weanling rats. Figure 5 shows the results of experiments by Baird et al. [22] in which LH release was measured in response to similar GnRH pulse patterns in pubertal female rats (Panel A) and hamsters (Panel B). See also Janovick & Conn, [[5], Figure 1B]. This decline in the amount of LH release results both from desensitization of the calcium channels in the outer membrane and internalization of the receptors into the lysosomes, as we will see below.
Figure 5 Experimental data of Baird et al.[22]. Panels A and B show the response of pubertal rat and hamster anterior pituitary cells, respectively, to six minute pulses of 10 nM GnRH.
Figure 6 Amount of LH released as a function of time during a series of 5 minute pulses of 5 nM GnRH every 15 minutes. Open circles are the original model results and solid circles are the current model results.
Figure 7 Model responses to a series of 5 minute pulses of 5 nM GnRH every 15 minutes.
Figure 8 Model responses to a series of 5 minute pulses of 5 nM GnRH every 15 minutes.
The previous model (Blum et al, [1]) was intended to explain the short term response of gonadotrophs to GnRH. The success of the previous model in the first few minutes is not visible in Figures 1, 2, 3, and 6 because the long time scale compresses the first five minutes. The present model, which includes the four important medium-term processes discussed in the Introduction, now enables us to study the effects of these intracellular processes on medium-term responses, including the responses to pulses of GnRH. From now on, when we refer to the "model", we mean the present expanded model.
As shown in Figure 7B, the LH release rate decreases appreciably after the first pulse, and then continues to decrease slowly with each subsequent pulse. This arises (see equation (14)) because of the decline in the size of the cytosolic calcium pulse after each GnRH pulse as shown in Figure 7C. The ER is able to refill its calcium store to almost the same level as the preceding pulse, although the amount remaining in the ER after each pulse decreases appreciably (Figure 7D). Notice that the fraction of open channels in the outer membrane (Figure 7F) declines dramatically, while the fraction of open ER channels declines only slightly with each pulse (Figure 7E). This suggests that the primary cause of decline in the amount LH release with each GnRH pulse is the desensitization of the outer membrane. We examine this hypothesis further below.
To understand why the number of open ER channels does not decrease markedly from pulse to pulse, we refer to Figure 8. Note that the total number of receptors (Figure 8B) declines steadily by approximately 1/3 in the course of the experiment as does the number of free receptors (Figure 8A). The decline in the HRRH peaks is much greater (approximtely 40%, Figure 8D) because the formation of these dimers depends on the square of [HR]. However, the decline in the effector, E, which leads to the formation of IP3 (see equation (6)) is only 25% (data not shown) because of the substantial, rapid rise in GQ (Figure 8F) in response to the first pulse of GnRH. Thus, the IP3 peaks decline only about 25% (Figure 8E). Because of the Michaelis-Menten kinetics of the interaction between IP3 and the ER channels, there is an even smaller change in the fraction of open ER channels (CHO) in response to each GnRH pulse. This explains why the internalization and degradation of receptors does not have a more profound effect.
We now investigate how the desensitization depends on pulse frequency and GnRH concentration. In Figure 4, we examined the response of the cells to pulsatile administration of a intermediate concentration of GnRH. We now examine the LH release pattern in response to pulsatile exposure to lower (0.1 nM) and higher (10 nM) concentrations of GnRH. Panels A, B, and C of Figure 9 show the model results for five minute pulses of GnRH administered every 15, 30, and 60 minutes, respectively. On each panel, the three curves correspond to pulse concentrations of 10(stars), 1 (crosses), and 0.1 (open circles) nM of GnRH, respectively. At the lowest concentration in each case there is little or no desensitization throughtout the three hour time period. At the high concentration, there is a large release of LH in response to the first pulse. For pulse period of 15 minutes, there is a large decline in the amount of LH released with each subsequent pulse (Panel A).
Figure 9 Dependence of desensitization on GnRH concentration and pulse frequency. Panels A, B, and C show model LH outputs in response to 5 minutes pulses of GnRH at pulse periods of 15 (Panel A), 30 (Panel B), and 60(Panel C) minutes. Each panel shows responses to 10 nM(*), 1 nM(+), and O.1 nM(○) GnRH.
The decline is much smaller for pulse period of 30 minutes (Panel B). For a pulse period of 1 hour, the same amount of LH is released in response to each pulse for each GnRH concentration (Panel C). In vivo, one would not expect desensitization, so this result is consistent with experimental observations that LH pulses of the same magnitude occur approximately once an hour except just prior to ovulation (Kaiser et al,[23]). Note also that at the medium concentration of 1nM there is less desensitization at both period 15 and period 30 minutes than at the high concentration. These results are consistent with the experimental results seen by Hawes et al, [21] (our Figure 4) and Baird et al., [22] (our Figure 5), and Janovick & Conn, [[5], see their Figures 1,2,3,4].
Experiments have been performed to examine LH release in response to different concentrations of GnRH. King et. al. [24] performed an experiment in which they exposed pituitary cells to increasing concentrations of GnRH for 2 minutes at 30 minute intervals for a total time of three hours. Fig. 10 shows the model results for such an experiment. The pattern of LH release by the model closely coincides with the experimental results except that at 150 minutes the model predicts a somewhat larger LH release than observed experimentally. In Figure 11 we show the total amount of LH released in the model during a one hour and a two hour exposure to increasing concentrations of GnRH. The saturating shape of each curve is sigmoidal at medium and high GnRH concentrations, as observed experimentally (see: Keri et al. [[25], Figure 1]; King et al., [[24], Figure 4]; Conn et al, [[18], Figure 6]; and Stoljikovic et al. [[26], Figure 7]). Note that, because of desensitization, the amount of LH released in 2 hours is much less than twice the amount released in one hour.
Figure 10 LH released during 2 minute pulses of GnRH administered every 30 minutes at the indicated increasing concentrations of GnRH.
Figure 11 Total LH released after a 1 hour (open circles) and 2 hour (closed circles) continuous exposure to the concentrations of GnRH shown on the abscissa.
King et al. [24] also performed an experiment in which the cells were exposed to 20-minute pulses of 100 nM GnRH at 1-hour intervals. The model results (Figure 12) show a peak followed by a rapid decline to approximately half of the peak value and then a slower decrease to a lower level of LH release. The pattern is repeated at a reduced peak level with subsequent pulses. This pattern resembles Fig. 9 in King et al. [24] except that the experimental results show a flattening of the LH release curve late in the pulse, while the model results show a continual slow decline. Notice that both the model and experimental results show that even at one hour intervals pulses can cause desensitization if the pulse length is long enough or the frequency is high enough.
Figure 12 LH released in the model in response to 20 minute pulses of 100 nM GnRH administered every hour.
To investigate which of the two desensitization mechanisms, receptor interalization or outer membrane calcium channel desensitization, plays the major role in LH release densensitization, we set either the receptor internalization to zero (i.e k11 = 0) or calcium channel densensitization to zero (v0 = 0 = v1) and compared the results to the full model for continuous and pulsatile exposures. In the full model, in response to continuous exposure there is initial rapid increase in LH release followed by a decrease to basal levels at about 40 minutes (Figure 13, Panel A, open squares), comparable to the results observed by Janovick & Conn [5]. An almost identical response occurs if k11 = 0, except that the rate of decline after the initial spike is somewhat slower(Figure 13, Panel A, solid circles). If, however, v0 = 0 and v1 = 0, while k11 retains its normal value, then the amount of LH released declines much more slowly and does not reach basal levels (Figure 13, Panel A, open circles). In response to 5 minute pulses every 15 minutes (Figure 13, Panel B), again there is a relatively small effect of setting the internalization of the receptors to zero and a much larger effect of ignoring the desensitization of the calcium channels. Thus, for continuous and pulsatile exposures up to 3 hours, internalization of the receptors plays a relatively small role in the desensitization of gonadotrophs, whereas calcium channel desensitization has a much larger effect.
Figure 13 LH released during constant exposure (Panel A) and to 5 minute pulses every 15 minutes (Panel B) to 5 nM GnRH. Open circles indicate the model with no desensiti-zation of calcium channels in outer membrane (v1 = 0 and v2 = 0); solid circles indicate the model with calcium channel desensitization but with no internalization of receptors (k11 = 0); open squares indicate the full model.
In all of our previous simulations, except those in Figure 13 where we compared the two mechanisms for desensitization of LH release, the parameters in the model were never varied. We now discuss two situations where the modification of parameters gives good fits to the data and possibly new insights.
Stojilkovic et al. [6] exposed gonadotrophs from two week old ovariectomized female rats to two 30 minute pulses of 100 nM GnRH at one hour intervals or to two 30 minute pulses of 100 nM endothelin (ET), a hormone with LH releasing activity comparable to GnRH. In response to GnRH, the peak of the response to the second pulse was actually slightly larger than the response of the first pulse (Figure 14, Panel A). However, the response to the second pulse using the present model without any change in parameters was appreciably smaller than the response to the first pulse (Figure 14, Panel B). A closer approximation to the experimental results from ovariectomized rats was obtained simply by increasing the rate of recovery of the outer membrane calcium channels from v2 = 0.002 min-1 to v2 = 0.02 min-1 (data not shown). If, in addition, the rate of internalization of receptors is decreased from k11 = 0.08/n nM-1·min-1 to k11 = 0.04/n nM-1·min-1, the response to the second pulse of GnRH was very similar to that observed experimentally, as shown in Figure 14, Panel C.
Figure 14 Panel A shows the results of an experiment of Stojilkovic et al.[19] in which rat pituitary cells were exposed to two 30 minute pulses of 100 nM GnRH at one hour intervals. Panel B shows the response of the present model to the same pulses. If, how-ever, the rate of recovery of the calcium channels in the outer membrane is increased from v2 = 0.002 min-1 to v2 = 0.02 min-1 and the rate internalization of receptors is decreased from k11 = 0.08/n nM-1·min-1 to k11 = 0.04/n nM-1·min-1, then the present model gives responses (Panel C) similar to the exerperimental results in Panel A. The ordinate units for Panels B and C are ng.
In the experiments of Stojilkovic et al. [6], the first 30 minute pulse of ET provokes a high peak in LH release, as for GnRH. This peak, however, is followed by a rapid decline to basal levels. Furthermore, only a very small amount of LH was released in response to the second pulse of ET (see our Figure 15, Panel A). They attributed this rapid desensitization in part to rapid internalization of the ET receptors (see also Stojilkovic et al. [27]). To test this hypothesis, we increased the rate of internalization of these receptors from k11 = 0.08/n to k11 = 0.8/n. Although this decreased the amount LH released appreciably on the second pulse, the amount of LH released was not reduced to a comparably low level as observed experimentally. We therefore also decreased the amount of return of internalized ET receptors to the membrane, r0, from 60% to 10%. As shown in Fig. 15, Panel B, the model now produces a good match to the experimental data. We also note that as in the experimental data, the LH released in response to ET with the receptor internalization modification returns to basal level much faster than in the case of GnRH.
Figure 15 Panel A shows the results of an experiment of Stojilkovic et al. [6] in which rat pituitary cells were exposed to two 30 minute pulses of 100 nM endothelin at one hour intervals. Note that the response to Endothelin is markedly different than the response to GnRH in Panel A of Figure 14. If we change the present model by increasing in internalization of receptors (k11 = 0.8/n nM-1·min-1) and a decreasing the return of internalized receptors (from 60% to 10%), then the model (Panel B) closely approximates the experimental results. The ordinate units for Panels B are ng.
A similar result can be acheived by introducing desensitization of both the outer membrane and ER calcium channels instead of changing the internalization and recycling of the receptors. The parameters for the desensitization of the calcium channels in the outer membrane were increased from 0.02 min-1 to 0.4 min-1. This resulted in approximately 70% decrease in the magnitude of response to the second pulse of ET, but further increase in v1 did not cause any further reduction in magnitude. Since there is evidence suggesting that the calcium channels in the ER desensitize in response to GnRH (Conn et al [18]), we introduced this desensitization into the model to see if ER desensitization might also be occuring in response to ET. For simplicity, the rates of desensitization and of recovery of the ER calcium channels were chosen to be identical to that of the desensitization of the outer calcium channels. By including desensitization of both the outer membrane and ER calcium channels, the amount of LH released in response to the second pulse of ET was as small as was observed experimentally (data not shown). Thus, our current model, with few parameter changes, appears capable of explaining the responses to endothelin. However, in the absence of more detailed experimental data (for example responses to pulses of different durations and frequencies, etc.) we cannot at present distinguish between the two above proposed mechanisms.
Discussion
We have extended our previous model to include receptor internalization and partial degradation, outer membrane calcium channel desensitization, basal levels of receptor synthesis and destruction, and an increase in the number of Gq/11 proteins closely associated with the plasma membrane. With these additions we are now able to examine the behavior of the model system over medium term (up to three hours) exposures to GnRH and to a variety of pulsatile exposures. We have compared the model behavior to many such different experiments and found that it shows the essential response properties of the gonadotrophs. Furthermore, since the model includes many of the intracellualar physiological processes, we have used the model to investigate and understand the mechanisms that give rise to the various experimental results.
We note that the response of gonadotrophs to GnRH depends on the method of cell preparation, the stage of the estrous cycle, and the particular animals and species used. Thus, the real physiological parameters will vary in these different situations. Therefore, one would not expect that our model with the fixed set of "standard" parameters (used for the simulations in Figures 1,2,3 and 6,7,8,9,10,11,12) would match perfectly any particular set of experimental data. Of course, one can tune the model by adjusting parameters. For example, notice that the degree of desensitization to six minute pulses of 10 nM GnRH is differs markedly for the pubertal female rats and hamsters in the experiments of Baird et al. [22] as shown in Figure 5. The model behavior with standard parameters gives less desensitization than the hamster and more than the rat (see open circles in Figure 16). By changing the model parameter v1 (the rate of desensitization of the outer membrane calcium channels) from 0.02/min to 0.005/min we obtain a good match to the rat data (closed circles in Figure 16), and by changing v1 from 0.02/min to 0.05/min we obtain a good match to the hamster data (stars in Figure 16). This does not prove, of course, that it is only physiological variation in this parameter that gives the different experimental results, but it does suggest the specific experiments that could be performed to test this hypothesis.
Figure 16 Model responses to six minutes pulses of 10 nM GnRH every 30 minutes with the standard parameters (crosses), with v1 changed from 0.02/min to 0.005/min (stars) or to 0.05/min (open circles). The weak desensitization (stars) is similar to that of the rat in the experiments of Baird et al.[22](our Figure 5A) and the strong desensitization (open circles) is similar to that seen in the hamster (our Figure 5B).
We used parameter variation to investigate whether receptor internalization or outer membrane calcium channel desensitization plays the major role in LH release desensitization and concluded that outer membrane calcium channel desensitization is more important, at least in the experiments of Janovick and Conn [5]. We also used parameter variation to show that changing two parameters (the rate of recovery of the outer membrane channels and the rate of receptor internalization) the model gives good matches to the data of Stoljilkovic et al [19], on LH responses to pulses of endothelin. This strongly suggests that the same intracellular mechanisms are primarily responsible for the LH responses to GnRH and endothelin.
It is important to note that the model ignores a number of processes that play a role in the long-term response to GnRH. In gonadotrophs, depending on the frequency and duration of exposure to pulses of GnRH, there may be an increase or decrease in the number of receptors in the cell membrane due to changes in gene expression and/or mRNA translation [28,9,8,30]. These long-term effects are not important for the current study but will be included in future work. It is also known that there is activation of protein kinase C in gonadotrophs exposed to GnRH [20], but while PKC may not be involved in GnRH-mediated LH release [31], PKC may have other roles in the pituitary, such as to modulate gonadotroph responsiveness to GnRH [32]. Another aspect that our model ignores is the rapid calcium concentration oscillations in the cytosol. As shown by Stojilkovic and Tomic [33], the frequency of the oscillations affect the LH release. In the present model, as in the previous model [1], for simplicity we have assumed that the average cytosolic calcium concentration is an adequate approximation to the rapid oscillatory responses. Finally, we note (Stanislaus et al, [34]) that there is evidence that the GnRH receptor interacts with more than one G protein and Stanislaus et al,[13], have proposed that this underlies the differential regulation of the release of luteinizing hormone and follicle stimulating hormone. We plan to address these questions in future work.
Authors' Contributions
Washington and Reed contributed mostly to the mathematical development, Conn contributed to the physiological analysis, and Blum contributed to both.
Competing Interests
The authors declare that they have no competing interests.
Acknowledgements
This research was supported by National Science Foundation grant DMS-0109872 and National Institues of Health grant HD19899. We are grateful to Dr. Paula Budu for helping us prepare some of the figues.
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| 15447787 | PMC524191 | CC BY | 2021-01-04 16:39:22 | no | Theor Biol Med Model. 2004 Sep 24; 1:9 | utf-8 | Theor Biol Med Model | 2,004 | 10.1186/1742-4682-1-9 | oa_comm |
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Theor Biol Med ModelTheoretical Biology & Medical Modelling1742-4682BioMed Central London 1742-4682-1-91544778710.1186/1742-4682-1-9ResearchA mathematical model for LH release in response to continuous and pulsatile exposure of gonadotrophs to GnRH Washington Talitha M 1twashington@cnr.eduBlum J Joseph 2jblum@cellbio.mc.duke.eduReed Michael C 3reed@math.duke.eduConn P Michael 4connm@OHSU.edu1 Department of Mathematics, College of New Rochelle, USA2 Department of Cell Biology, Duke University, Durham, USA3 Department of Mathematics, Duke University, Durham, USA4 Oregon National Primate Research Center, Oregon Health & Science University, Beaver-ton, USA2004 24 9 2004 1 9 9 14 6 2004 24 9 2004 Copyright © 2004 Washington et al; licensee BioMed Central Ltd.2004Washington 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 a previous study, a model was developed to investigate the release of luteinizing hormone (LH) from pituitary cells in response to a short pulse of gonadotropin-releasing hormone (GnRH). The model included: binding of GnRH to its receptor (R), dimerization and internalization of the hormone receptor complex, interaction with a G protein, production of inositol 1,4,5-trisphosphate (IP3), release of calcium from the endoplasmic reticulum (ER), entrance of calcium into the cytosol via voltage gated membrane channels, pumping of calcium out of the cytosol via membrane and ER pumps, and release of LH. The extended model, presented in this paper, also includes the following physiologically important phenomena: desensitization of calcium channels; internalization of the dimerized receptors and recycling of some of the internalized receptors; an increase in Gq concentration near the plasma membrane in response to receptor dimerization; and basal rates of synthesis and degradation of the receptors. With suitable choices of the parameters, good agreement with a variety of experimental data of the LH release pattern in response to pulses of various durations, repetition rates, and concentrations of GnRH were obtained. The mathematical model allows us to assess the effects of internalization and desensitization on the shapes and time courses of LH response curves.
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Background
Gonadotropin-releasing hormone (GnRH) is released by the hypothalamus in a pulsatile fashion and stimulates luteinizing hormone (LH) and follicle stimulating hormone (FSH) release by pituitary cells by a complex series of signaling processes. Although there is substantial information about various individual steps in the signaling system, there is less understanding of how these components interact to give rise to the overall behavior of the system. The frequency of pulses varies throughout the menstrual cycle increasing markedly just prior to ovulation. And, it has been observed in in vitro experiments on perifused pituitary cells that pulse frequency and concentration have marked (nonlinear) influences on the release of LH and FSH. The purpose of our work is to use mathematics and machine computation to understand the dynamics of this important and interesting physiological system.
In a prior study, [1], a mathematical model was developed to investigate the rate of release of luteinizing hormone from pituitary gonadotrophs in response to short pulses of gonadotropin-releasing hormone. The model included binding of the hormone to its receptor, dimerization, interaction with a G-protein, production of inositoltrisphosphate (IP3), release of calcium from the endoplasmic reticulum (ER), entrance of calcium into the cytosol via voltage gated membrane channels, pumping of calcium out of the cytosol via membrane and ER pumps, and the release of luteinizing hormone (LH). Cytosolic calcium dynamics were simplified and it was assumed that there is only one pool of releasable LH. Despite these and other simplifications, the model results matched experimental curves and enabled us to understand the reasons for the qualitative features of the LH release curves in response to GnRH pulses of short durations and different concentrations both in the presence and absence of external calcium. We note that Heinze et al, [2], created a mathematical model for LH release that reproduces some data for pulsatile administration of GnRH. Their model, however, does not include most of the important intracellular mechanisms known to play important roles; thus, they match data but do not study mechanisms. We also note that mathematical models for other aspects of the reproductive hormone system have been created: Keenan et al, [3], developed a stochastic systems model for the interactions between GnRH, LH, and testosterone; Gordan et al, [4] modelled the pulsatile release of GnRH by hypothalamic neurons.
There are four important medium-term effects that were not included in the previous study. Desensitization of the response to GnRH occurs because after GnRH binds to its receptors, some of the bound complexes are internalized and partially degraded [5]. Secondly, prolonged exposure to GnRH desensitizes the outer membrane calcium ion channels, as described in detail by Stojilkovic et al [6]. Thirdly, there exist basal rates of receptor synthesis and degradation. Finally, in response to GnRH, there also occurs an increase in the number of Gq/11 proteins closely associated with the plasma membrane [7]. Incorporation of these four phenomena into the previous model allows us to analyze the contrasting effects of desensitization and signal amplification during medium-term continuous and pulsatile exposures to GnRH. We then show that the LH response curves of the enlarged model capture most of the essential features of a large number of experimental studies.
It should be noted that in the present model we ignore the long-term effects that result in changes in DNA, messenger RNA, and protein concentrations (e.g., receptor number) that are known to occur several hours after exposure to GnRH [8-11]. Thus, in the present study, we limit the time of exposure to three hours. We also ignore the long term effects of diacylglycerol which is known to cause an increase in the synthesis of LHα, the α subunit of the LH dimer [12].
Model Development
Let H(t) represent the GnRH concentration (nM) in the surrounding medium t minutes after the initiation of the experiment. Initially, the hormone is bound by the receptor, R.
The bound complex HR reacts with itself to form dimers [13], denoted by HRRH.
A Gq/11 protein, denoted GQ, reacts with the dimer to produce an effector, E (e.g., phospholipase C, [13]).
The values of the rate constants, k1, k2, k3, k-1, k-2, k-3, are the same as in our earlier model [1]. The abbreviations for the physiological components of the model are listed in Table 1 and all the rate constants for the current model are listed in Table 2.
Table 1 Glossary of Variables
H GnRH concentration (nM)
R Free GnRH receptor concentration (nM)
HR Hormone-receptor complex concentration (nM)
HRRH Hormone-receptor dimer concentration (nM)
GQ Gq/11 protein concentration (nM)
E Effector concentration (nM)
IP3 Inositol 1,4,5-trisphosphate concentration (nM)
CAC Cytosolic Ca2+ concentration (μM)
CAER ER Ca2+ concentration (μM)
CHO Fraction of open ER Ca2+ channels
LH LH concentration (ng)
Table 2 Constants
R0 Total receptor concentration (nM)
GQ0 Total Gq/11 protein concentration (nM)
ERUL Resting Ca2+ concentration in ER (normally 40 μM)
CAE External Ca2+ concentration (normally 1000 μM)
α = 2 nM-1, see equation (17)
β = 4 min-1, see equation (17)
v1 = 0.02 min-1, see equation (12)
v2 = 0.002 min-1, see equation (12)
r0 = 0.6, fraction internalized receptors returned
P0 = 8.3 × 10-6 nM·min-1, basal rate of receptor synthesis
γ = 8.3 × 10-4 min-1, basal rate of receptor degradation
k1 = 2.5 nM-1·min-1
k-1 = 5 min-1
k2 = 2500 nM-1·min-1
k-2 = 5 min-1
k3 = 4000 nM-1·min-1
k-3 = 200 min-1
k5 = 2 × 107 min-1
k-5 = 10 min-1
k6 = 1 nM-1·min-1
k66 = 10 nM-1·min-1
k666 = 0
k-6 = 5 min-1
k7 = 2.2 μM·min-1
k8 = 0.4 nM-1·min-1
k88 = 0
k888 = 0
k9 = 0.0002 min-1
k10 = 5 ng·min-1
k11 = 0.0008 nM-1·min-1
k33 = 2.7 min-1
The monomers, HR, can also interact with each other to form larger aggregates [14]. Macroaggregation and internalization occur at least 20 minutes after exposure to GnRH [14]. All of the internalized hormone and some of the receptors are then degraded, and the receptors that are not degraded are returned to the membrane [15,16]. We assume that a fraction of receptors, r0, can be returned intact to the membrane after a time delay of 20 minutes. Consistent with the data of [14], we assume that r0 = 0.6. Since we are not concerned with the details of the internalization or return processes, we adopt simple first order reactions for these processes. We assume that n monomers, HR, are internalized at a rate k11 and that r0n monomers that have been internalized are available to be returned to the membrane at rate k11.
There is evidence that the macroaggregates consist of an average of n = 100 monomers [14]. In our model, we will choose k11 = 0.08/n = 0.0008 nM-1·min-1. With this choice, 7% of the receptors are internalized after a 5 minute pulse of 1 nM GnRH, and 60 minutes after the initial exposure, approximately half of the internalized receptors have returned. It should be noted that it is only the combination k11n that occurs in the equations.
We make the following simple assumption about the recyling of receptors (consistent with the data of Maya-Nunez et al. [17] and Table 2 of Conn et al. [18]). i.e. that the formation of macroaggregates begins 20 minutes after exposure to GnRH and that the internalization and recycling process takes 20 minutes after the formation of the macroaggregates. Let χ(t) be the function that equals 1 for t ≥ 0 and equals 0 for t < 0. Then, at time t, the rate of internalization of receptors is k11n[HR](t) and the rate of return of receptors to the membrane is k11n[HR](t - 40)χ(t - 40). To simplify notation, we write [HR]40 = [HR](t - 40)χ(t - 40).
Since only 60% percent of the internalized receptors are returned to the membrane after exposure to GnRH, there would not be a full recovery of receptors in the membrane. In the model we therefore include a low basal rate of receptor synthesis, P0 = 8.3 × 10-6 nM·min-1, and degradation, γ = 8.3 × 10-4 min-1. The ratio is chosen so that the resting (in the absence of hormone) receptor concentration is R0 = 10-2 nM, and the magnitude of P0 is chosen so that approximately of the resting amount of receptor is produced per hour, thus ensuring a slow recovery to the steady state receptor concentration in the absence of GnRH.
The number of membrane associated GQ proteins increases in response to a GnRH agonist as described by Cornea et al [7]. For simplicity we assume that the increase of GQ proteins near the membrane depends on the concentration of HRRH in the membrane. The kinetic coefficient k33 is the parameter that determines the rate of increased concentration of GQ at the membrane in response to the formation of HRRH. We are assuming a finite pool of GQ that can be transported from the cytoplasm to the immediate vicinity of the plasma membrane. This pool is assumed to be regulated by the amount of HRRH for only the first 20 minutes, and after this time the rate of increase is negligible [7]. To fit the experimental data, we choose k33 = 2.7 min-1 and multiply the kinetic coefficient k33 by e-t/20. With these parameters, 60 minutes after a constant exposure to 1 nM GnRH, there is a 40% increase of GQ concentration near the membrane and 120 minutes after exposure to the hormone, there is only a 43% increase. The following differential equations reflect the physiological assumptions that we have so far discussed.
We further assume that the production of IP3 is proportional to the concentration of E and that it is converted to inactive metabolites at a rate proportional to its concentration.
As in [1], the fraction of open channels in the ER, denoted by CHO, depends on IP3 concentration. CHO reaches its maximum 0.25 min after exposure to GnRH and the maximum value of CHO is 0.6. To incorporate multiple pulses, we modify the function CHO from the previous model so that it reaches its maximum 0.25 min after the start of each pulse. Thus we have
where tp is the time after the start of each individual pulse and, as in [1],, α = 2 nM-1 and β = 4 min-1.
In response to GnRH, calcium is released from the ER into the cytoplasm with a rate constant ERR and is pumped back into the ER. As discussed in the previous model, the rate constant ERR increases proportionally to cytosolic calcium concentration, CAC, with a rate constant k66 and is inhibited at high CAC at a rate that is proportional to the square of CAC, with a rate constant k666. Just as in, [1], k6 = 1, k66 = 10, and k666 = 0, i.e., we ignore the inhibitory effects of calcium on reuptake of calcium into the ER.
ERR = k6 + k66[CAC] - k666[CAC]2 (8)
The change in cytosolic calcium concentration, CAER, is then determined by the rate constant ERR, which is the rate of extrusion, multiplied by the fraction of open channels, CHO, and the difference in concentration between the calcium concentration in the cytoplasm and the endoplasmic reticulum. As in Blum et al. [1], calcium is actively transported back into the ER by pumps with the rate constant k-6 = 5 min-1.
As in the previous model, the volume of the ER is assumed to be 1/20 of the volume of the cytosol. CAC is determined by the rate of calcium efflux through ion channels in the ER membrane minus the rate at which calcium is being pumped back into the ER, plus the rate of calcium entry from the plasma membrane. The function VSR denotes the rate of calcium influx from extracellular calcium into the cytosol and depends on E with rate constant k8 [19] and on CAC with rate constants k88 for the influx at low CAC and k888 for the inhibitory effects at high CAC. There is considerable evidence that desensitization occurs, i.e., the fraction of open calcium channels in the cell membrane decreases soon after exposure to GnRH [18]. Since the precise mechanism of desensitization in unknown, we assume that VSR depends on E and CAC, and that channels slowly become inactive in response to exposure to GnRH, consistent with the experimental data [18]. We further assume that the fraction of open calcium channels in the outer membrane, denoted by VSRO(t), decreases at a linear rate of v1 = 0.02 min-1 when the hormone is applied and has a minimum value of 0. In the absence of hormone, the fraction of open channels increases at a linear rate of v2 = 0.002 min-1 and has a maximum value of 1. Thus, immediately a five minute pulse of 5 nM GnRH, 10% of the channels are in the refractory state and 50 minutes after the removal of the GnRH, all of the channels have recovered, consistent with experimental data; see [18] for more details. Incorporating calcium influx, pumps and leakage into the cytoplasm from the medium (the term k9 [CAE], we have
where
VSR(t) = (k8E(t) + k88[CAC](t) - k888([CAC])(t))2) × VSRO(t) (11)
and VSRO satisfies the following.
0 ≤ VSRO(t) ≤ 1 (13)
Finally, the rate of release of LH depends on cytosolic calcium concentration (see Blum et al. [1] for details). Although there is evidence that there are three pools of LH in gonadotrophs, one pool, comprising of only 2% of the total LH, is released within one minute after exposure to GnRH, and the third pool is not released during continuous exposure to GnRH (Naor et al.,[20]). Therefore, as in the previous model [1], we treat LH as being released from a single pool.
The mathematical model consists of equations (1) – (14). These non-linear equations cannot be solved analytically but solutions can be obtained by machine computation. To do this, we used the solver ODE45 in Matlab.
The values of the rate constants are given in Table 2. The values for many of them are discussed in detail, with references, in our original paper, [1]. The values of the rate constants for the signalling mechanisms introduced in this paper were discussed (above) as the mechanisms were introduced. In some cases the rate constants were taken from experimental data (references given) and in other cases, where direct experimental data does not yet exist, we explained the rationale for our choices. Since the resulting model captures and explains many experimental studies (see below), these choices provide useful predictions for future experimental studies.
Results
In Figure 1, we compare the amounts of LH released in 5 minute intervals in the original model and the present model in response to continuous administration of 5 nM GnRH. In both models there is an initial large pulse of LH released. However, in the original model (open circles in Panel A) the long-term release plateaus at a high level, while in the present model (solid circles) the long term release declines to a low level. Panel A in Figure 4 contains experimental results of Hawes et al. [21], that clearly show show a decline in LH release to a low level after approximately 1.5 to 2 hours. Similar experimental results were obtained by Baird et al, [[22], Figure 4] and by Janovick and Conn, [[5], Figure 1, Panel A].
Figure 1 Amount of LH released in five minute intervals in response to constant exposure to 5 nM GnRH. The solid circles show the results of the present model while the open circles show the results of the original model [1]. The decay of LH release to zero is in accord with experimental results (see discussion in text); thus, new mechanisms included in the present model allow one to match this data (and other data, see other figures) from several laboratories for medium-term GnRH exposure experiments.
Figure 4 Experimental data of Hawes et al.[21]. Gonadotrophs were treated continuously with lO nM GnRH (Panel A), with 5 minute pulses every 30 minutes (Panel B), or every 15 minutes (Panel C).
Figures 2 and 3 show in detail the changes that occur in all components of the system during the model experiments described above. Fig. 2A shows the total amount of the LH released as a function of time while Fig. 2B shows the LH release rate (LHRR), which peaks within one minute after exposure to GnRH and then declines slowly for the next 50 minutes to a very low value in the present model. Note that LHRR is the instantaneous rate of LH release (in ng/min) while LH release in Figure 1A is in ng released in each five minute interval. In the previous model(dashed lines), LHRR plateaus at a high level (Figure 2B), so the total LH released increases linearly (Figure 2A). In the present model (solid lines), LHRR declines to a low level. In both the previous and present models, there is a rapid extrusion of calcium from the ER (Fig. 2D) and an initial rapid increase in CAC (Fig. 2C), which correlate well with the time course of the rate of change of LHRR (Figure 2B). However, the long-term behavior is different in the two models because in the present model CAC declines to a low plateau. This explains the similar drop in LH release since the rate of LH release depends on CAC (see equation (14)). The drop in CAC is caused by the desensitization of the outer membrane channels; Figure 2E shows that the fraction of open channels declines linearly to zero in 50 minutes. In the ER membrane, there is an almost instantaneous increase of open calcium channels followed by a rapid decrease and then a slight further decline (Fig. 2F).
Figure 2 Panel A shows the total amount of LH released as a function of time during continuous exposure to 5 nM GnRH, while Panel B shows the instantaneous rate of LH release at each moment of time. Panels C and D show the calcium concentration in the cytosol and the endoplasmic reticulum, respectively. Panels E and F show the fraction of open calcium channels in the outer membrane and the endoplasmic reticulum, respectively. The solid lines show the results of the present model while the dashed lines show the results of the earlier model [1].
Figure 3 Panels A, C, and D show the concentrations of free, bound, and dimerized receptors, respectively, while Panel B shows the total amount of receptors in the membrane. Panel E shows the concentration of IP3. Panel F shows the GQ concentration at the membrane as a function of time during the continuous exposure to 5 nM GnRH. The solid lines show the results of the current model and the dashed lines show the results of the earlier model in [1].
Figures 3A and 3C show the concentrations of free receptors and receptors bound to the hormone. It can be seen that, initially in both the present and previous models, there is a very rapid decline in free receptors, R, and a very rapid increase of receptors to which GnRH has bound (HR) but have not yet dimerized. This is immediately followed, as shown in Figure 3D, by the formation of the dimers (HRRH). After this initial reaction, the concentrations of HR and HRRH remain constant in the previous model, but decline in the present model due to internalization and degradation. The recycling of receptors was assumed to start at 40 minutes (see equation (1)), which is why the rates of decrease of HR and HRRH decline at that time. Because of degradation, only a fraction (r0 = 0.6) of the internalized receptors are returned to the membrane. Thus, in the presence of continuous exposure to GnRH, the total number of receptors in the membrane continues to decline as shown in Figure 3B. The rate of change of IP3 (Fig. 3E) is closely related to the rate of change of HRRH as shown in Fig. 3D. Finally, Fig. 3F shows that there is a slow increase of approximately 43% of the concentration GQ associated with the membrane during the exposure.
Figures 6, 7, and 8 show model results for gonadotrophs exposed to 5 minute pulses of 5 nM GnRH administered every 15 minutes for a total duration of 3 hours. In the previous model (Figure 6A, open circles), there was a drop in LH release between the first and second pulse, but the same amount of LH was released in response to all subsequent pulses, contrary to experimental observations. The initial drop occurs because there is insufficient time for the calcium in the ER to refill completely (data not shown). In the present model, in response to the first pulse there is a large release of LH. In response to the second pulse considerably less LH is released, and in subsequent pulses there is a steady decline in the amount of LH released. This continual decline in LH release has been observed in a large number of experiments. Panels B and C of Figure 4 show the results of Hawes et al [21] obtained from female weanling rats. Figure 5 shows the results of experiments by Baird et al. [22] in which LH release was measured in response to similar GnRH pulse patterns in pubertal female rats (Panel A) and hamsters (Panel B). See also Janovick & Conn, [[5], Figure 1B]. This decline in the amount of LH release results both from desensitization of the calcium channels in the outer membrane and internalization of the receptors into the lysosomes, as we will see below.
Figure 5 Experimental data of Baird et al.[22]. Panels A and B show the response of pubertal rat and hamster anterior pituitary cells, respectively, to six minute pulses of 10 nM GnRH.
Figure 6 Amount of LH released as a function of time during a series of 5 minute pulses of 5 nM GnRH every 15 minutes. Open circles are the original model results and solid circles are the current model results.
Figure 7 Model responses to a series of 5 minute pulses of 5 nM GnRH every 15 minutes.
Figure 8 Model responses to a series of 5 minute pulses of 5 nM GnRH every 15 minutes.
The previous model (Blum et al, [1]) was intended to explain the short term response of gonadotrophs to GnRH. The success of the previous model in the first few minutes is not visible in Figures 1, 2, 3, and 6 because the long time scale compresses the first five minutes. The present model, which includes the four important medium-term processes discussed in the Introduction, now enables us to study the effects of these intracellular processes on medium-term responses, including the responses to pulses of GnRH. From now on, when we refer to the "model", we mean the present expanded model.
As shown in Figure 7B, the LH release rate decreases appreciably after the first pulse, and then continues to decrease slowly with each subsequent pulse. This arises (see equation (14)) because of the decline in the size of the cytosolic calcium pulse after each GnRH pulse as shown in Figure 7C. The ER is able to refill its calcium store to almost the same level as the preceding pulse, although the amount remaining in the ER after each pulse decreases appreciably (Figure 7D). Notice that the fraction of open channels in the outer membrane (Figure 7F) declines dramatically, while the fraction of open ER channels declines only slightly with each pulse (Figure 7E). This suggests that the primary cause of decline in the amount LH release with each GnRH pulse is the desensitization of the outer membrane. We examine this hypothesis further below.
To understand why the number of open ER channels does not decrease markedly from pulse to pulse, we refer to Figure 8. Note that the total number of receptors (Figure 8B) declines steadily by approximately 1/3 in the course of the experiment as does the number of free receptors (Figure 8A). The decline in the HRRH peaks is much greater (approximtely 40%, Figure 8D) because the formation of these dimers depends on the square of [HR]. However, the decline in the effector, E, which leads to the formation of IP3 (see equation (6)) is only 25% (data not shown) because of the substantial, rapid rise in GQ (Figure 8F) in response to the first pulse of GnRH. Thus, the IP3 peaks decline only about 25% (Figure 8E). Because of the Michaelis-Menten kinetics of the interaction between IP3 and the ER channels, there is an even smaller change in the fraction of open ER channels (CHO) in response to each GnRH pulse. This explains why the internalization and degradation of receptors does not have a more profound effect.
We now investigate how the desensitization depends on pulse frequency and GnRH concentration. In Figure 4, we examined the response of the cells to pulsatile administration of a intermediate concentration of GnRH. We now examine the LH release pattern in response to pulsatile exposure to lower (0.1 nM) and higher (10 nM) concentrations of GnRH. Panels A, B, and C of Figure 9 show the model results for five minute pulses of GnRH administered every 15, 30, and 60 minutes, respectively. On each panel, the three curves correspond to pulse concentrations of 10(stars), 1 (crosses), and 0.1 (open circles) nM of GnRH, respectively. At the lowest concentration in each case there is little or no desensitization throughtout the three hour time period. At the high concentration, there is a large release of LH in response to the first pulse. For pulse period of 15 minutes, there is a large decline in the amount of LH released with each subsequent pulse (Panel A).
Figure 9 Dependence of desensitization on GnRH concentration and pulse frequency. Panels A, B, and C show model LH outputs in response to 5 minutes pulses of GnRH at pulse periods of 15 (Panel A), 30 (Panel B), and 60(Panel C) minutes. Each panel shows responses to 10 nM(*), 1 nM(+), and O.1 nM(○) GnRH.
The decline is much smaller for pulse period of 30 minutes (Panel B). For a pulse period of 1 hour, the same amount of LH is released in response to each pulse for each GnRH concentration (Panel C). In vivo, one would not expect desensitization, so this result is consistent with experimental observations that LH pulses of the same magnitude occur approximately once an hour except just prior to ovulation (Kaiser et al,[23]). Note also that at the medium concentration of 1nM there is less desensitization at both period 15 and period 30 minutes than at the high concentration. These results are consistent with the experimental results seen by Hawes et al, [21] (our Figure 4) and Baird et al., [22] (our Figure 5), and Janovick & Conn, [[5], see their Figures 1,2,3,4].
Experiments have been performed to examine LH release in response to different concentrations of GnRH. King et. al. [24] performed an experiment in which they exposed pituitary cells to increasing concentrations of GnRH for 2 minutes at 30 minute intervals for a total time of three hours. Fig. 10 shows the model results for such an experiment. The pattern of LH release by the model closely coincides with the experimental results except that at 150 minutes the model predicts a somewhat larger LH release than observed experimentally. In Figure 11 we show the total amount of LH released in the model during a one hour and a two hour exposure to increasing concentrations of GnRH. The saturating shape of each curve is sigmoidal at medium and high GnRH concentrations, as observed experimentally (see: Keri et al. [[25], Figure 1]; King et al., [[24], Figure 4]; Conn et al, [[18], Figure 6]; and Stoljikovic et al. [[26], Figure 7]). Note that, because of desensitization, the amount of LH released in 2 hours is much less than twice the amount released in one hour.
Figure 10 LH released during 2 minute pulses of GnRH administered every 30 minutes at the indicated increasing concentrations of GnRH.
Figure 11 Total LH released after a 1 hour (open circles) and 2 hour (closed circles) continuous exposure to the concentrations of GnRH shown on the abscissa.
King et al. [24] also performed an experiment in which the cells were exposed to 20-minute pulses of 100 nM GnRH at 1-hour intervals. The model results (Figure 12) show a peak followed by a rapid decline to approximately half of the peak value and then a slower decrease to a lower level of LH release. The pattern is repeated at a reduced peak level with subsequent pulses. This pattern resembles Fig. 9 in King et al. [24] except that the experimental results show a flattening of the LH release curve late in the pulse, while the model results show a continual slow decline. Notice that both the model and experimental results show that even at one hour intervals pulses can cause desensitization if the pulse length is long enough or the frequency is high enough.
Figure 12 LH released in the model in response to 20 minute pulses of 100 nM GnRH administered every hour.
To investigate which of the two desensitization mechanisms, receptor interalization or outer membrane calcium channel desensitization, plays the major role in LH release densensitization, we set either the receptor internalization to zero (i.e k11 = 0) or calcium channel densensitization to zero (v0 = 0 = v1) and compared the results to the full model for continuous and pulsatile exposures. In the full model, in response to continuous exposure there is initial rapid increase in LH release followed by a decrease to basal levels at about 40 minutes (Figure 13, Panel A, open squares), comparable to the results observed by Janovick & Conn [5]. An almost identical response occurs if k11 = 0, except that the rate of decline after the initial spike is somewhat slower(Figure 13, Panel A, solid circles). If, however, v0 = 0 and v1 = 0, while k11 retains its normal value, then the amount of LH released declines much more slowly and does not reach basal levels (Figure 13, Panel A, open circles). In response to 5 minute pulses every 15 minutes (Figure 13, Panel B), again there is a relatively small effect of setting the internalization of the receptors to zero and a much larger effect of ignoring the desensitization of the calcium channels. Thus, for continuous and pulsatile exposures up to 3 hours, internalization of the receptors plays a relatively small role in the desensitization of gonadotrophs, whereas calcium channel desensitization has a much larger effect.
Figure 13 LH released during constant exposure (Panel A) and to 5 minute pulses every 15 minutes (Panel B) to 5 nM GnRH. Open circles indicate the model with no desensiti-zation of calcium channels in outer membrane (v1 = 0 and v2 = 0); solid circles indicate the model with calcium channel desensitization but with no internalization of receptors (k11 = 0); open squares indicate the full model.
In all of our previous simulations, except those in Figure 13 where we compared the two mechanisms for desensitization of LH release, the parameters in the model were never varied. We now discuss two situations where the modification of parameters gives good fits to the data and possibly new insights.
Stojilkovic et al. [6] exposed gonadotrophs from two week old ovariectomized female rats to two 30 minute pulses of 100 nM GnRH at one hour intervals or to two 30 minute pulses of 100 nM endothelin (ET), a hormone with LH releasing activity comparable to GnRH. In response to GnRH, the peak of the response to the second pulse was actually slightly larger than the response of the first pulse (Figure 14, Panel A). However, the response to the second pulse using the present model without any change in parameters was appreciably smaller than the response to the first pulse (Figure 14, Panel B). A closer approximation to the experimental results from ovariectomized rats was obtained simply by increasing the rate of recovery of the outer membrane calcium channels from v2 = 0.002 min-1 to v2 = 0.02 min-1 (data not shown). If, in addition, the rate of internalization of receptors is decreased from k11 = 0.08/n nM-1·min-1 to k11 = 0.04/n nM-1·min-1, the response to the second pulse of GnRH was very similar to that observed experimentally, as shown in Figure 14, Panel C.
Figure 14 Panel A shows the results of an experiment of Stojilkovic et al.[19] in which rat pituitary cells were exposed to two 30 minute pulses of 100 nM GnRH at one hour intervals. Panel B shows the response of the present model to the same pulses. If, how-ever, the rate of recovery of the calcium channels in the outer membrane is increased from v2 = 0.002 min-1 to v2 = 0.02 min-1 and the rate internalization of receptors is decreased from k11 = 0.08/n nM-1·min-1 to k11 = 0.04/n nM-1·min-1, then the present model gives responses (Panel C) similar to the exerperimental results in Panel A. The ordinate units for Panels B and C are ng.
In the experiments of Stojilkovic et al. [6], the first 30 minute pulse of ET provokes a high peak in LH release, as for GnRH. This peak, however, is followed by a rapid decline to basal levels. Furthermore, only a very small amount of LH was released in response to the second pulse of ET (see our Figure 15, Panel A). They attributed this rapid desensitization in part to rapid internalization of the ET receptors (see also Stojilkovic et al. [27]). To test this hypothesis, we increased the rate of internalization of these receptors from k11 = 0.08/n to k11 = 0.8/n. Although this decreased the amount LH released appreciably on the second pulse, the amount of LH released was not reduced to a comparably low level as observed experimentally. We therefore also decreased the amount of return of internalized ET receptors to the membrane, r0, from 60% to 10%. As shown in Fig. 15, Panel B, the model now produces a good match to the experimental data. We also note that as in the experimental data, the LH released in response to ET with the receptor internalization modification returns to basal level much faster than in the case of GnRH.
Figure 15 Panel A shows the results of an experiment of Stojilkovic et al. [6] in which rat pituitary cells were exposed to two 30 minute pulses of 100 nM endothelin at one hour intervals. Note that the response to Endothelin is markedly different than the response to GnRH in Panel A of Figure 14. If we change the present model by increasing in internalization of receptors (k11 = 0.8/n nM-1·min-1) and a decreasing the return of internalized receptors (from 60% to 10%), then the model (Panel B) closely approximates the experimental results. The ordinate units for Panels B are ng.
A similar result can be acheived by introducing desensitization of both the outer membrane and ER calcium channels instead of changing the internalization and recycling of the receptors. The parameters for the desensitization of the calcium channels in the outer membrane were increased from 0.02 min-1 to 0.4 min-1. This resulted in approximately 70% decrease in the magnitude of response to the second pulse of ET, but further increase in v1 did not cause any further reduction in magnitude. Since there is evidence suggesting that the calcium channels in the ER desensitize in response to GnRH (Conn et al [18]), we introduced this desensitization into the model to see if ER desensitization might also be occuring in response to ET. For simplicity, the rates of desensitization and of recovery of the ER calcium channels were chosen to be identical to that of the desensitization of the outer calcium channels. By including desensitization of both the outer membrane and ER calcium channels, the amount of LH released in response to the second pulse of ET was as small as was observed experimentally (data not shown). Thus, our current model, with few parameter changes, appears capable of explaining the responses to endothelin. However, in the absence of more detailed experimental data (for example responses to pulses of different durations and frequencies, etc.) we cannot at present distinguish between the two above proposed mechanisms.
Discussion
We have extended our previous model to include receptor internalization and partial degradation, outer membrane calcium channel desensitization, basal levels of receptor synthesis and destruction, and an increase in the number of Gq/11 proteins closely associated with the plasma membrane. With these additions we are now able to examine the behavior of the model system over medium term (up to three hours) exposures to GnRH and to a variety of pulsatile exposures. We have compared the model behavior to many such different experiments and found that it shows the essential response properties of the gonadotrophs. Furthermore, since the model includes many of the intracellualar physiological processes, we have used the model to investigate and understand the mechanisms that give rise to the various experimental results.
We note that the response of gonadotrophs to GnRH depends on the method of cell preparation, the stage of the estrous cycle, and the particular animals and species used. Thus, the real physiological parameters will vary in these different situations. Therefore, one would not expect that our model with the fixed set of "standard" parameters (used for the simulations in Figures 1,2,3 and 6,7,8,9,10,11,12) would match perfectly any particular set of experimental data. Of course, one can tune the model by adjusting parameters. For example, notice that the degree of desensitization to six minute pulses of 10 nM GnRH is differs markedly for the pubertal female rats and hamsters in the experiments of Baird et al. [22] as shown in Figure 5. The model behavior with standard parameters gives less desensitization than the hamster and more than the rat (see open circles in Figure 16). By changing the model parameter v1 (the rate of desensitization of the outer membrane calcium channels) from 0.02/min to 0.005/min we obtain a good match to the rat data (closed circles in Figure 16), and by changing v1 from 0.02/min to 0.05/min we obtain a good match to the hamster data (stars in Figure 16). This does not prove, of course, that it is only physiological variation in this parameter that gives the different experimental results, but it does suggest the specific experiments that could be performed to test this hypothesis.
Figure 16 Model responses to six minutes pulses of 10 nM GnRH every 30 minutes with the standard parameters (crosses), with v1 changed from 0.02/min to 0.005/min (stars) or to 0.05/min (open circles). The weak desensitization (stars) is similar to that of the rat in the experiments of Baird et al.[22](our Figure 5A) and the strong desensitization (open circles) is similar to that seen in the hamster (our Figure 5B).
We used parameter variation to investigate whether receptor internalization or outer membrane calcium channel desensitization plays the major role in LH release desensitization and concluded that outer membrane calcium channel desensitization is more important, at least in the experiments of Janovick and Conn [5]. We also used parameter variation to show that changing two parameters (the rate of recovery of the outer membrane channels and the rate of receptor internalization) the model gives good matches to the data of Stoljilkovic et al [19], on LH responses to pulses of endothelin. This strongly suggests that the same intracellular mechanisms are primarily responsible for the LH responses to GnRH and endothelin.
It is important to note that the model ignores a number of processes that play a role in the long-term response to GnRH. In gonadotrophs, depending on the frequency and duration of exposure to pulses of GnRH, there may be an increase or decrease in the number of receptors in the cell membrane due to changes in gene expression and/or mRNA translation [28,9,8,30]. These long-term effects are not important for the current study but will be included in future work. It is also known that there is activation of protein kinase C in gonadotrophs exposed to GnRH [20], but while PKC may not be involved in GnRH-mediated LH release [31], PKC may have other roles in the pituitary, such as to modulate gonadotroph responsiveness to GnRH [32]. Another aspect that our model ignores is the rapid calcium concentration oscillations in the cytosol. As shown by Stojilkovic and Tomic [33], the frequency of the oscillations affect the LH release. In the present model, as in the previous model [1], for simplicity we have assumed that the average cytosolic calcium concentration is an adequate approximation to the rapid oscillatory responses. Finally, we note (Stanislaus et al, [34]) that there is evidence that the GnRH receptor interacts with more than one G protein and Stanislaus et al,[13], have proposed that this underlies the differential regulation of the release of luteinizing hormone and follicle stimulating hormone. We plan to address these questions in future work.
Authors' Contributions
Washington and Reed contributed mostly to the mathematical development, Conn contributed to the physiological analysis, and Blum contributed to both.
Competing Interests
The authors declare that they have no competing interests.
Acknowledgements
This research was supported by National Science Foundation grant DMS-0109872 and National Institues of Health grant HD19899. We are grateful to Dr. Paula Budu for helping us prepare some of the figues.
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| 15500703 | PMC524214 | CC BY | 2021-01-04 16:36:21 | no | Cytojournal. 2004 Sep 24; 1:3 | latin-1 | Cytojournal | 2,004 | 10.1186/1742-6413-1-3 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1551022410.1371/journal.pbio.0020364Research ArticleNeurosciencePsychologyHomo (Human)Perception, Action, and Roelofs Effect: A Mere Illusion of Dissociation Perception, Action, and Roelofs EffectDassonville Paul prd@darkwing.uoregon.edu
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Bala Jagdeep Kaur
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1Department of Psychology and Institute of Neuroscience, University of OregonEugene, OregonUnited States of America11 2004 26 10 2004 26 10 2004 2 11 e36420 2 2004 23 8 2004 Copyright: © 2004 Dassonville and Bala.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.
One Brain, One Vision
A prominent and influential hypothesis of vision suggests the existence of two separate visual systems within the brain, one creating our perception of the world and another guiding our actions within it. The induced Roelofs effect has been described as providing strong evidence for this perception/action dissociation: When a small visual target is surrounded by a large frame positioned so that the frame's center is offset from the observer's midline, the perceived location of the target is shifted in the direction opposite the frame's offset. In spite of this perceptual mislocalization, however, the observer can accurately guide movements to the target location. Thus, perception is prone to the illusion while actions seem immune. Here we demonstrate that the Roelofs illusion is caused by a frame-induced transient distortion of the observer's apparent midline. We further demonstrate that actions guided to targets within this same distorted egocentric reference frame are fully expected to be accurate, since the errors of target localization will exactly cancel the errors of motor guidance. These findings provide a mechanistic explanation for the various perceptual and motor effects of the induced Roelofs illusion without requiring the existence of separate neural systems for perception and action. Given this, the behavioral dissociation that accompanies the Roelofs effect cannot be considered evidence of a dissociation of perception and action. This indicates a general need to re-evaluate the broad class of evidence purported to support this hypothesized dissociation.
Paul Dassonville and Jagdeep Bala challenge a prominent hypothesis that proposes the existence of two separate visual systems within the brain, one creating perception and the other guiding action
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Introduction
Several anatomical, neurophysiological, clinical, and behavioral investigations of human subjects and nonhuman primates have provided evidence for two separate and dissociable cortical systems for visual processing. One of these systems—the ventral stream—resides in a swath of cortex that extends in an anteroventral direction from primary visual cortex to the temporal lobe. The second system resides in a dorsal stream that roughly extends from primary visual cortex to the parietal lobe. These ventral and dorsal systems were originally thought to be dedicated to the visual processing required to determine an object's identity and location, respectively (Ungerleider and Mishkin 1982). However, a more recent hypothesis suggests that both streams process information concerning object properties and locations, but that they do so for different purposes. In this revised model of the visual system (Milner and Goodale 1995), the ventral stream is presumably responsible for the formation of perceptual/cognitive representations of objects and events in the world, whereas the dorsal stream is responsible for guiding sensorimotor actions in response to those objects and events.
Much of the evidence for separate perception and action systems has come from behavioral studies of normal subjects. The general logic of these behavioral paradigms (e.g., Bridgeman et al. 1981, 1997; Aglioti et al. 1995; Daprati and Gentilucci 1997; Goodale and Murphy 1997; Haffenden and Goodale 1998) is as follows: An illusory stimulus is presented to the subject, who is required to report some characteristic of the stimulus (location, size, orientation, etc.) using perceptual (e.g., verbally compare the test object to some reference object) or sensorimotor means (e.g., make a movement to reach toward or grasp the test object). As a general finding, it seems that perceptual reports are more prone to illusions than are sensorimotor responses, suggesting that the systems are dissociable not only in terms of their cortical pathways, but also in terms of their processing capabilities.
As a specific example of this type of evidence, Bridgeman et al. (1997) tested the ability of subjects to indicate the location of a small visual target presented within an illuminated frame that was offset left or right from the subject's midline plane (Figure 1A). When asked to perceptually compare the location of the target with respect to an array of possible locations learned earlier, subjects reported the target to be in a location that was shifted in a direction opposite that of the frame—a perceptual phenomenon known as the induced Roelofs effect (Bridgeman et al. 1997; see also Roelofs 1935). In contrast, subjects could accurately guide the hand to the target's location, indicating that sensorimotor localization was immune to the illusion. These findings were cited as strong evidence for the existence of two distinct, differently abled visual systems for perception and action. However, Bridgeman et al. (1997) further demonstrated that not all actions were immune to the illusion; in particular, sensorimotor responses were prone to the induced Roelofs effect when subjects were required to point to the remembered location of the target after a delay of 4 s. As suggested by Bridgeman et al. (1997), this delayed sensorimotor effect could possibly be explained by a sensorimotor system that lacks a memory of its own and therefore must rely on the memory of the illusion-prone perceptual system to determine the goal of a movement directed toward a remembered target.
Figure 1 Schematic of the Induced Roelofs Effect
(A) Example visual display (not drawn to scale) comprising a target (red circle) and a frame offset to the subject's left. Gray circles (unseen by subjects) represent the remembered positions of the items within the comparison array, centered on the subject's midline.
(B) One possible mechanism for the inaccurate perceptual report of the target location, based on an illusory rightward shift of the perceived target location (green circle).
(C) An alternative mechanism for the inaccurate perceptual report, based on a leftward shift of the memorized location of the comparison array (blue circles). Either mechanism (B or C) would result in the subject reporting the target to occupy the remembered location of item 4 in the comparison array.
Although these findings are compatible with the hypothesis of two separate visual systems that are differentially affected by Roelofs illusion, it is important to consider the possibility of an alternative explanation. While it is true that both perceptual and sensorimotor measures within the task of Bridgeman et al. (1997) assayed the subjects' abilities to determine the location of the target, the two measures did so in markedly different ways. For the sensorimotor task, subjects could complete the task knowing only the location of the target within a body-centered or egocentric reference frame. In contrast, the perceptual task required the subjects to compare the location of the target relative to the locations of the items within the remembered comparison array. Given this, errors in the perceptual report could be due to either a misrepresentation of the target's position (Figure 1B) or a misrepresentation of the position of the remembered comparison array (Figure 1C). Whereas Bridgeman et al. (1997) concluded that the target is perceptually mislocalized in a direction opposite the frame offset, an inaccurate perceptual report could equally be due to a memory of the comparison array that is shifted in the same direction as the frame. The studies presented here were designed to test this alternative hypothesis for the mechanism underlying the induced Roelofs effect, and to critically examine the apparent dissociation of perception and action related to the illusion. We first replicate the findings of Bridgeman et al. (1997), using saccadic eye movements rather than a pointing task. We then test subjects' memory for the comparison array and show that it is biased by the offset frame in a way that can completely account for the perceptual illusion. A subsequent experiment demonstrates that this distortion of remembered visual space occurs when the brain, faced with an impoverished visual environment, incorrectly uses the location of the frame as a cue to establish an egocentric reference map whose origin (the apparent midline) is transiently biased toward the direction of the frame. Furthermore, movements guided within this same distorted reference map are shown to be accurate, given that the errors of target localization will be cancelled by subsequent errors of motor guidance. Thus, the perceptual and sensorimotor effects of the Roelofs illusion can be mechanistically explained without requiring the existence of separate neural processing streams for perception and action.
Results/Discussion
Perceptual and Sensorimotor Effects of the Illusion
We first sought to replicate the findings of Bridgeman et al. (1997) by testing subjects' abilities to indicate the locations of targets presented within the context of a centered frame or one displaced 5° left or right of the midline. Subjects provided a perceptual report of each target location by comparing it to an array of five possible target locations (−4°, −2°, 0°, 2°, and 4° from the subject's midline, at eye level) learned during an earlier training session. As had been demonstrated previously (Bridgeman et al. 1997), the displaced frame did cause a mislocalization of the target, whether the subject responded immediately after the offset of the target and frame (Figure 2A, solid line; Table 1) or after a 4-s delay period during which the subject was in complete darkness (Figure 2A, dashed line; Table 1). The size of this illusion was quantified by subtracting the magnitude of the localization bias caused by a right-shifted frame from that caused by a left-shifted frame, resulting in an effect size of 1.47° ± 0.32° (mean ± SEM) across all subjects for immediate responses and 1.37° ± 0.30° for delayed responses.
Figure 2 Perceptual and Sensorimotor Roelofs Effects
(A) Effect of frame location on immediate (solid line) and delayed (dashed line) perceptual judgments of target location, with a significant main effect of frame offset but no frame × delay interaction (Table 1); error bars represent the standard error of the mean localization errors for each subject. (See also Figure S1A for a time line of the task events, Figure S1B for a plot of the Roelofs effect for each of the individual target locations, and Figure S1C for plots of the Roelofs effect within individual subjects.)
(B) Effect of frame offset on immediate (solid line) and delayed (dashed line) saccadic eye movements, with a significant main effect of frame offset and a significant frame × delay interaction. When tested separately, the main effect of frame offset was not significant for immediate responses, but was significant for delayed responses (Table 1; see also Figure S2).
Table 1 Significance of Effects
a Main effect: Frame duration
b Interaction: Frame offset × Frame duration
NA, not applicable
n.s., not significant
A second group of subjects was instructed to make open-loop saccadic eye movements to the target location. Saccades performed immediately after the frame and target were extinguished showed no significant effect of frame position (effect size = −0.01° ± 0.13°, Figure 2B, solid line; Table 1). This finding replicated the general pattern of sensorimotor responses described by Bridgeman et al. (1997) and extended them by demonstrating that immediate saccadic eye movements, like pointing movements of the hand, can be guided accurately to targets that are perceptually mislocalized. However, when subjects were required to withhold this sensorimotor response during a 4-s delay period, the eventual saccadic eye movement did reflect a small but significant Roelofs effect (effect size = 0.60° ± 0.26°, Figure 2B, dashed line; Table 1). Again, this delayed sensorimotor Roelofs effect replicated the findings of Bridgeman et al. (1997).
A Mislocalization of the Target or of the Comparison Array?
To test the hypothesis that the perceptual Roelofs effect can be explained by a memory of the comparison array that is shifted in the direction of the frame, subjects were asked to indicate the remembered locations of the five items within the array of possible targets that was learned in complete darkness during the earlier training session. In experimental trials, a centered or offset frame was presented near the time that an auditory cue instructed the subject to make a saccadic eye movement to one of the remembered locations. If an offset frame caused a distortion in the memory of the reference array, the accuracy of the saccadic responses would be affected. This was indeed the case, with targets mislocalized in the same direction as the displacement of the offset frame (effect size = −1.61° ± 0.32°, Figure 3A, solid line; Table 1). Since this pattern of mislocalization for remembered targets was in the opposite direction of the normal Roelofs effect reported by Bridgeman et al. (1997) and replicated above (see Figure 2A), we refer to it as an inverse Roelofs effect for remembered space. This finding provides strong evidence that the perceptual errors associated with the normal Roelofs effect are most parsimoniously explained by the subject's comparison of the target location with a distorted memory of the comparison array. As a further test of this hypothesis, it is possible to use the pattern of mislocalizations evident with the inverse Roelofs effect for remembered space to predict a subject's perceptual report when comparing a target location with the inaccurately remembered comparison array. The resultant prediction for the perceptual Roelofs effect very closely matched the measured Roelofs effect (see Figure 3B), with a predicted effect size (1.61°) that did not significantly differ from the measured effect size (1.47° ± 0.32°). Thus, the inverse Roelofs effect for remembered space effectively accounts for the mislocalizations that occurred when subjects provided perceptual reports of the locations of targets presented within the context of an offset frame.
Figure 3 Inverse Roelofs Effect for Remembered Space
(A) An inverse Roelofs effect for immediate (solid line) and delayed (dashed line) sensorimotor responses toward remembered reference array locations, with a significant main effect of frame offset and a significant frame × delay interaction. When tested separately, the main effect of frame offset was significant for both immediate and delayed responses (Table 1; see also Figure S3).
(B) The inverse Roelofs effect for remembered space can be used to predict the pattern of the Roelofs effect for targets presented within an offset frame. For example, a frame offset to the right would cause the remembered comparison array to be mislocalized as being shifted approximately 1° to the right (from Figure 3A, solid line); a target presented at the center location of the comparison array (i.e., at the objective midline) would therefore be reported to lie approximately 1° to the left of the remembered center location. Computed in this way for all target and frame locations, the predicted Roelofs effect (gray lines and data points) closely matched the measured Roelofs effect for the perceptual judgment (black lines and data points, from Figure 2A, solid line), with a predicted effect size (1.61°) that did not significantly differ from the measured effect (1.47° ± 0.32°; t[9] = 0.44, n.s.). Furthermore, the measured Roelofs effect did not differ from the predicted effect for any individual frame position (left frame: t[9] = 0.39, n.s.; center frame: t[9] = 0.01, n.s.; right frame: t[9] = 0.36, n.s.).
Distortion of the Apparent Midline
Although the inverse Roelofs effect for remembered space provides an explanation for the perceptual mislocalization that occurs in the presence of an offset frame, the mechanism whereby the offset frame is capable of distorting remembered space remains to be explained. The locations of the items within the comparison array were learned in complete darkness and therefore could only be localized in egocentric coordinates, perhaps with respect to the subject's apparent midline (Mergner et al. 2001). Under normal conditions, the center of the visual field would serve as an accurate indicator of straight-ahead. However, the impoverished visual environment of the present experiment contained only the large rectangular frame, which might have served to attract the apparent midline in the direction of the frame's offset (Werner et al. 1953; Brosgole 1968; Brecher et al. 1972; Dassonville et al. 2004), dragging the spatial memory of the comparison array with it. To directly test the hypothesis that the offset frame in the current context is capable of biasing the apparent midline, subjects were asked to perform a version of the task in which they were simply asked to “look straight ahead” immediately after the presentation of a centered or offset frame. Subjects' reports of “straight-ahead” were indeed found to be affected by the presence of the frame, with the movements biased in the same direction as the offset frame (effect size = −1.08° ± 0.14°, with a negative value once again reflecting an effect in the direction opposite the normal induced Roelofs effect; Figure 4, solid line; Table 1).
Figure 4 Inverse Roelofs Effect for the Apparent Midline
An inverse Roelofs effect for immediate (solid line) and delayed (dashed line) sensorimotor responses toward the apparent midline, with a significant main effect of frame offset and a significant frame × delay interaction. When tested separately, the main effect of frame offset was significant for both immediate and delayed responses (Table 1; see also Figure S4).
These findings can also explain the absence of errors seen with immediate sensorimotor responses, if one assumes that the movements are guided within the same distorted frame of reference that is used to encode the target location. For example, a target presented at the subject's true midline in the presence of a left-shifted frame would be encoded by the brain as having been located a small distance to the right of the apparent midline (which itself has been pulled leftward by the frame; Figure 5A). If the corresponding sensorimotor response is guided within this same distorted reference frame, the eye or hand would be expected to move to a location just to the right of the distorted apparent midline (Figure 5B). In essence, the error in target localization would be exactly cancelled by the error in motor guidance, resulting in an accurate response. Thus, an accurate sensorimotor response is fully expected when the target and response are encoded within the same distorted map of space.
Figure 5 The Biased-Midline Hypothesis
(A) A depiction of the manner in which a target (red circle), located directly in front of the subject, would be perceived as being a small distance to the right of the subject's apparent midline (dotted line), which has itself been biased to the left in the presence of the left-shifted frame.
(B) An immediate open-loop sensorimotor response (pointing movement, as shown here, or saccade begun immediately after the target and frame are extinguished) would be accurate if the goal of the movement were encoded in the same distorted reference frame (that is, a small distance to the right of the distorted apparent midline).
(C) With the frame and target extinguished during an imposed delay, the apparent midline would drift back to veridical (gray arrows), dragging the remembered location of the target (gray circle) with it. A subsequent sensorimotor response aimed at the remembered target (located a small distance to the right of the now-veridical apparent midline) would result in a delayed sensorimotor Roelofs effect.
Transient Effects of the Illusion
In contrast to the stable Roelofs effect with delayed perceptual responses (see Figure 2A, dashed line), we found that the inverse Roelofs effect for remembered space was diminished (to an effect size = −0.87° ± 0.28°) when a 4-s delay was imposed between the frame presentation and the saccade to a remembered item in the comparison array (see Figure 3A, dashed line). Similarly, the effects of an offset frame on the apparent midline diminished during a delay imposed after the frame was extinguished (to an effect size = −0.56° ± 0.15°; see Figure 4, dashed line). These findings demonstrate that the distortions of the apparent midline and remembered space are transient, decreasing over time when the offset frame is no longer visible. However, even after a delay of 4 s, responses were still somewhat biased by the preceding frame, indicating either an extended time course during which the effects of the frame dissipate or a hysteresis that prevents the apparent midline from becoming fully veridical in the absence of visual input.
The transient nature of the apparent midline distortion can also provide an explanation for the increase in Roelofs effect seen when a delayed saccade is made to a target presented within the offset frame (see Figure 2B, dashed line). As an example, let us once again assume a target presented at the subject's true midline, in the presence of a left-shifted frame. During the imposed delay, it is reasonable to assume that the memory of the target's location would be encoded with respect to the distorted apparent midline (Mergner et al. 2001)—in our example, the target would be remembered as being a small distance to the right of the apparent midline, which has been pulled leftward by the frame (see Figure 5A). After the frame is removed and its distorting influences diminish, the apparent midline would drift back toward its veridical orientation under the influence of vestibular (Fischer and Kornmueller 1930; Morant 1959) and proprioceptive (Karnath 1999) inputs, dragging the remembered target location with it. The delayed response would then be directed to this incorrectly remembered location, just to the right of the newly corrected apparent midline (see Figure 5C). If this account were true, one would expect the normal Roelofs effect for sensorimotor responses to increase during a delay by an amount comparable to the decrease in the inverse Roelofs effect for delayed movements directed to the apparent midline or items in the remembered comparison array. Indeed, the current studies found the sensorimotor Roelofs effect to increase 0.61° during the imposed delay (that is, from −0.01° to 0.60°; see Figure 2B, solid versus dashed lines), while the inverse Roelofs effect decreased 0.74° for movements to items in the comparison array (see Figure 3A, solid versus dashed lines) or 0.52° for movements to indicate the apparent midline (see Figure 4, solid versus dashed lines). In contrast, one would not expect an imposed delay to have any effect on a perceptual report of target location, since the relative relationship of the remembered target and the remembered comparison array would remain unchanged as the apparent midline returned to veridical.
To more closely examine the hypothesis that the increase in the Roelofs effect for delayed sensorimotor responses is due to a drift of the apparent midline back to veridical after the frame is extinguished, a group of subjects performed a version of the delayed saccade task in an experiment in which, on half of the trials, the frame continued to be visible during the 4-s delay period, disappearing only when the subject received the verbal cue to respond. In the other half of the trials, the frame and target were extinguished simultaneously, with the subject sitting in complete darkness during the delay. When the frame was absent during the delay, the eventual response was significantly affected by frame position (Figure 6, dashed line; Table 1), replicating the results from our previous delayed saccade task (see Figure 2B, dashed line). In contrast, for those trials in which the frame was present during the delay, no effect of frame position was evident (see Figure 6, dotted line; Table 1). Thus, it seems that the continued presence of the frame maintains the apparent midline in a biased orientation, such that the errors in target encoding are cancelled by the errors of motor guidance even after a delay. Since the transient nature of the Roelofs effect is specifically not a function of the delay from target presentation to response (but rather depends on the delay from frame offset), these findings argue against the hypothesis of Bridgeman et al. (1997) that the transience reflects a lack of memory for target location within a system that guides the sensorimotor responses.
Figure 6 Effect of the Frame during the Delay Period
Effect of frame offset on delayed saccadic eye movements, for trials in which the frame was either extinguished at the start of the delay period (brief frame, dashed line), or was present throughout the delay (extended frame, dotted line). There was a significant frame × delay interaction; when tested separately, the main effect of frame offset was not significant for the extended frame duration, but was significant for the brief duration, replicating the results shown in Figure 2B, dashed line (Table 1; see also Figure S5).
Reevaluating the Need for Separate Perception and Action Systems
While the present findings provide an alternative explanation for the behavioral dissociation of Roelofs illusion, it could still be argued that they do not completely rule out the possibility of separate systems for perception and action. For example, it could be that there does exist a context-independent “action” system whose only function is to guide movements aimed immediately and directly toward a currently visible target, and a “perceptual” system capable of guiding all other movements (e.g., movements to remembered targets, to mirror-image locations of currently visible targets [Dassonville et al. 2004], or to indicate straight-ahead, all of which reflect the errors associated with Roelofs effect). If this were true, then it would be useful to contrast the capabilities of the action system with those of the perceptual system under equivalent conditions (i.e., for movements guided immediately and directly to currently defined targets). To do this, we designed an experiment in which subjects were asked to make saccadic eye movements to targets that were defined purely through the use of contextual cues that could serve as targets only for the presumed perceptual system, if the action system truly operates in a context-independent fashion. Specifically, stimuli consisted of three corners (and two sides) of a rectangle, with the target location defined as the missing corner (Figure 7A). These stimuli were then presented within a large rectangular frame that was centered or offset from the subject's midline. The pattern of mislocalizations seen with these allocentrically defined targets was identical to that seen with real targets (compare Figure 7B to Figure 2B), with no Roelofs effect evident for immediate responses (Figure 7B, solid line; Table 1), but a significant effect evident for responses delayed by 4 s (Figure 7B, dashed line; Table 1). Thus, if separate action and perception systems do exist, it would seem that they are not differently abled with regard to Roelofs effect after all. Instead, both would be capable of guiding immediate movements accurately in spite of the Roelofs effect, with the action system simply immune to the Roelofs distortions, while the perceptual system would be required to guide movements within the same distorted reference frame as the target is encoded, so that the errors cancel, as described above. While it is technically possible that the brain would maintain two such redundant systems for guiding movements, it seems improbable. Instead, a more parsimonious explanation for the behavioral dissociation that accompanies Roelofs effect is provided by the brain's use of a single reference frame whose origin (the apparent midline) is transiently distorted by the presence of an offset frame for both perceptual judgments and sensorimotor responses.
Figure 7 A Roelofs Effect for Allocentrically Defined Targets
(A) Visual display used to define allocentric targets; subjects were instructed to move the eyes to the missing corner of the partial rectangle (gray circle, not seen by subject). During experimental trials, this stimulus array was presented within a large rectangular frame that was either centered or offset left or right of the subject's midline.
(B) Effect of frame offset on immediate (solid line) and delayed (dashed line) sensorimotor responses to targets defined allocentrically, with a significant main effect of frame offset and a significant frame × delay interaction. When tested separately, the main effect of frame offset was not significant for immediate responses, but was significant for delayed responses (Table 1; see also Figure S6)
Further Evidence for the Use of Contextual Information in Motor Control
As is the case for many illusions, the distortion of visual space associated with Roelofs illusion would seem to be a by-product of the brain's use of contextual cues that—under normal circumstances—would provide additional information that could allow for the creation of a more accurate neural representation of the world. After all, most perceptual judgments and movements are made within the context of a well-lit, highly structured visual scene, the center of which would normally provide an accurate indicator of straight-ahead. Given this, it would be somewhat surprising if the beneficial information that is provided by contextual cues under normal circumstances were used for perception but not for motor control. Indeed, many previous investigations have demonstrated that contextual cues do affect the guidance of movements, even those directed to currently visible targets. For example, the accuracy and kinematics of open-loop pointing movements are greatly affected by the presence of a small distractor (Howard and Tipper 1997; Tipper et al. 1997; Gangitano et al. 1998) or a well-lit, highly structured visual scene (Foley 1975; Conti and Beaubaton 1980; Blouin et al. 1993; Toni et al. 1996). This has also been demonstrated using paradigms in which the visual representation of target location is first distorted by altering the relationship between actual eye position and the brain's representation of eye position (e.g., by paralyzing the extraocular muscles with curare [Matin et al. 1982], stretching them [Stark and Bridgeman 1983], fatiguing them [Shebilske 1984], or vibrating them [Velay et al. 1994]). Although these distortions of represented eye position have been shown to cause errors in open-loop pointing movements aimed at targets presented in otherwise complete darkness, the presence of a highly structured visual scene significantly reduces the magnitude of these errors. Contextual cues are also used by the oculomotor system to minimize the errors of saccadic eye movements directed toward targets presented near the time of a preceding saccade (Honda 1993, 1999; Dassonville et al. 1995). Furthermore, several other studies have clearly demonstrated that illusion-causing contextual cues can affect the dynamic characteristics of pointing and grasping movements (Smeets and Brenner 1995; Brenner and Smeets 1996; Gentilucci et al. 1997; van Donkelaar 1999; Jackson and Shaw 2000; Westwood et al. 2001; Bartelt and Darling 2002) and the accuracy of eye movements (Festinger et al. 1968; Binsted and Elliott 1999; Both et al. 2003; McCarley et al. 2003; Sheliga and Miles 2003).
Additional Evidence against a Simple Perception/Action Dissociation
Although previous authors have suggested that the perceptual effects of Roelofs illusion could be explained by a distortion of the apparent midline and egocentric reference frame (Werner et al. 1953; Brosgole 1968; Brecher et al. 1972; Dassonville and Bala 2004; Dassonville et al. 2004), we have demonstrated here that this same transient distortion can also provide a full, precise, and mechanistic explanation of the immediate and delayed sensorimotor effects of Roelofs illusion. By extending this hypothesis to include dynamic visual displays, a similar mechanism can also be used to explain the behavioral dissociation seen with illusions of induced motion (Bridgeman et al. 1981; Wong and Mack 1981). Most important, this hypothesis accounts for both phenomena without relying on an assumption of separate neural maps of space for perception and action. Given this, the behavioral dissociation evident with these illusions cannot be used as evidence that exclusively supports the existence of a perception/action dissociation in visual processing.
Of course, several other behavioral studies can still be pointed to as evidence for a perception/action dissociation in visual processing. However, many of these studies have recently come under intense scrutiny, with some researchers failing to replicate previously reported dissociations once important control conditions were included (Honda 1990; Dassonville et al. 1992; Pavani et al. 1999; Franz et al. 2000; Franz 2003). Other researchers have proposed alternative explanations for obvious behavioral dissociations by pointing out that the perception and action tasks differed along other dimensions as well (e.g., semantic versus pragmatic requirements [Jeannerod 1997], relative versus absolute judgments [Vishton et al. 1999], allocentric versus egocentric reference frames [Bruno 2001], and size versus position judgments [Smeets and Brenner 2001]). Similarly, in studies that have purported to demonstrate a perception/action dissociation in patients with dorsal and ventral lesions, it can be argued that the behavioral tests used to characterize the deficits also suffered from these same confounds. For example, Dijkerman et al. (1998) found that a patient (DF) with a ventral lesion was impaired in a task that required her to reach for and grasp an object by placing her fingers in two or three circular holes whose locations were varied from trial to trial. Although these findings led Dijkerman et al. (1998) to conclude that movements like these must be controlled by a ventral perceptual system that happens to operate within an allocentric reference frame, it is also possible to interpret these data as suggesting that the lesion simply caused a specific deficit in allocentric encoding rather than a general deficit in perception. This same patient has also been found to be impaired in perceiving the visual pitch of a plane tilted from vertical, even though that same plane causes a distortion of her perception of vertical eye level, just as it does in healthy subjects (Servos et al. 1995). Thus, although DF demonstrates a dissociation in her ability to use information concerning visual pitch, it is a dissociation of two perceptual measures and specifically not a dissociation of perception and action.
While it seems clear that there do exist at least some examples of dissociations in the accuracy of various behavioral responses from normal subjects and patients, a great deal of evidence now suggests that these dissociations cannot simply be attributed to separate systems for perception and action. Indeed, the dorsal and ventral processing streams are both composed of a myriad of functionally distinct and highly interconnected visual processing areas, each with its own mechanisms for representing various aspects of the visual world. Each visuomotor task would undoubtedly rely on the processing capabilities of a subset of these areas, with different tasks relying on different subsets depending on their precise requirements. With this in mind, it seems overly simplistic to consider visuomotor behavior as being derived from the function of only one of two distinct processing streams. Rather, it is more plausible that flexible functional networks would form among the areas required to play a role in the completion of the task at hand. The characteristics of the behavioral performance would then be dependent on the representational idiosyncrasies of those areas involved (McGraw et al. 2003).
Several previous studies of the perceptual and motor effects associated with various visual illusions have indicated an apparent dissociation of visual pathways for perception and action, with perception generally found to be prone to illusions to which actions are immune. These conclusions, however, are not without controversy; as described above, several other studies have questioned the perception/action dissociation attributed to many illusions, after contrary evidence or alternative explanations were produced. A notable exception to this has been the induced Roelofs effect, where the presumption of a perception/action dissociation has remained unquestioned since it was originally proposed (Bridgeman et al. 1997). The results presented here, however, point to a brain mechanism for spatial localization that can fully and precisely explain the behavioral dissociation of the induced Roelofs effect without requiring the existence of separate neural systems for perception and action. The visual image of a large frame, whose center is offset left or right of an observer's midline, was demonstrated to cause a transient distortion of an observer's egocentric reference frame by biasing the apparent midline. Within this distorted reference frame, objects are perceived to be located in a direction shifted opposite that of the frame offset. The fact that movements of the eyes and hands can be accurately directed to this misperceived target location can be explained by a cancellation of errors that occurs when the movement is guided within the same distorted reference frame. Thus, these findings indicate that both perceptual judgments and motor responses are based upon either a single map of space or separate maps that are equally prone to the distortion caused by the Roelofs effect.
Materials and Methods
Subjects
In each experiment, ten subjects (undergraduate students of the University of Oregon) provided informed consent to participate and were compensated with either course credit or a small monetary payment, as per a protocol approved by the University of Oregon Committee for the Protection of Human Subjects/Institutional Review Board.
Visual display
Subjects were placed in a completely darkened room and presented with a visual display that was back-projected (Cine7 projector, Barco, Kuurne, Belgium) onto a screen measuring 128 × 96 cm, positioned 122 cm from the eyes. Visual targets were small (0.35° of visual angle, 100-ms duration) red spots, located −4°, −2°, 0°, 2°, or 4° from the subject's midline, at eye level. During experimental trials, targets were presented within a large red unfilled frame (21° horizontal × 8.5° vertical, 1° thickness; 1,000-ms duration) that was either centered with respect to the subject's midline or shifted 5° left or right of the midline. All visual images were presented on a black background, with the high contrast of the Barco Cine7 projector preventing subjects from seeing the edges of the screen.
Eye movement monitoring
Head and binocular eye positions were monitored at 250 Hz with an eye tracker (Eyelink; SensoMotoric Instruments, Needham, Massachusetts, United States) that allowed head-free measurement of gaze (precision = 0.01°); however, target placement was such that head movements contributed to only a small fraction of the total gaze displacement on any trial. To start each session (and as necessary throughout each session), eye-tracker calibration was performed using a 3 × 3 grid of targets spaced 13.5° apart in the horizontal dimension and 10.5° apart in the vertical dimension. For each subject, the average fixation error across the nine calibration targets was required to be 1° or less before beginning the subsequent practice and experimental trials; thus, absolute tracking errors within this calibration field were at most 1° in magnitude and were typically only 0.5°. In addition, subjects began each experimental trial by directing the eyes to a fixation point and pressing the space bar of a keyboard to indicate readiness. Upon this signal, the eye-tracker computer performed an adjustment of the calibration to correct for any drift that had occurred since the onset of the previous trial; that is, the calibration was adjusted so that the signal of eye position matched the known location of the fixation point. In experiments requiring eye movement responses, the gaze signals from the two eyes were averaged to yield a single representation of gaze direction as the dependent variable.
Behavioral tasks
Each experiment was preceded by a set of practice trials (36–71 trials) in which subjects performed the appropriate task (see below) in the absence of the large Roelofs-inducing rectangular frame. Feedback was provided at the end of each practice trial to assist subjects in improving their performance. For all experiments, feedback included the illumination of a small circle at the target location. For the experiment in which subjects provided a button press to report the perceived target identity, a computer-generated voice also provided auditory feedback to indicate the correct target identity. For all experiments in which subjects indicated the target position with a saccadic eye movement, feedback following each practice trial also included the illumination of a small square to indicate the final gaze position; subjects were instructed to use the feedback in an attempt to minimize the distance between the target and final gaze positions. No feedback concerning response accuracy was ever provided during the experimental trials.
To test the perceptual effects of Roelofs illusion (see Figure 2A; see also Figure S1A), subjects were first trained to recognize targets presented in each of the five possible target locations. Each trial began with a fixation point (centered horizontally, 8.5° above eye level) that was extinguished 1150–1650 ms before the onset of the target (100-ms duration). A computer-generated voice (“Respond,” presented just before or 4 s after the target) provided subjects with a temporal cue to press one of five keys on the computer keyboard to indicate the identity of the target based on its perceived location (using the right hand, thumb = extreme left target, little finger = extreme right target, etc.). Throughout each trial, subjects were required to maintain gaze within an invisible window of 4° centered on the fixation point, even after the fixation point was removed. At the end of each practice trial, the target was displayed again to provide visual feedback, and the computer-generated voice provided a verbal indication of the target's actual location. Subsequent experimental trials had a similar time course, except for the inclusion of a large frame (1,000-ms duration) that was illuminated 900 ms before target onset (frame and target were extinguished simultaneously). Subjects in this and all other tasks were explicitly instructed to ignore the presence of the large frame when making their judgments of target location.
Similar trials were used to test the sensorimotor effects of Roelofs illusion (see Figure 2B; see also Figure S2A), with the exception that subjects were instructed to make a saccadic eye movement to the target location after being cued to “Respond” by the computer-generated voice. After making any necessary eye movements to fixate the remembered target location, subjects ended each trial by pressing the “Enter” key on the keyboard (this final gaze position was used as the subject's indication of target location). Subjects in this version of the task were never informed that there were only five possible target locations.
To test the effects of Roelofs illusion on remembered visual space (see Figure 3A; see also Figure S3A), subjects were instructed to make eye movements to the remembered locations of the five possible targets. During practice trials in which no frames were presented, the visual target was replaced with a computer-generated voice providing the identity of the target location (“One” = extreme left target, “Five” = extreme right target, etc.). After the computer-generated cue to “Respond” (presented just before or 4 s after the cue for target identity), subjects moved their eyes to the remembered location of the target and ended the trial by pressing the “Enter” key. Feedback during practice trials was provided in the way of an illumination of the correct target location and a small square indicating the final gaze position for that trial. In subsequent experimental trials, the large rectangular frame was presented 900 ms before the onset of the auditory target-identity cue, and no feedback was provided.
To test the effects of Roelofs illusion on the apparent midline (see Figure 4; see also Figure S4A), subjects were instructed to make eye movements to look straight-ahead when cued to “Respond” by the computer-generated voice. To prevent the fixation point from providing information about the actual midline in this version of the task, the horizontal position of the fixation point was varied randomly from trial to trial (−3°, −1°, 1°, or 3° from midline).
To determine whether the delayed sensorimotor Roelofs effect was modulated by the presence of the frame during the imposed delay period (see Figure 6; see also Figure S5A), all trials contained an imposed delay of 4 s between target presentation and the subsequent computer-generated “Respond” command. In half of the trials, the rectangular frame (1-s duration) was extinguished simultaneous with the target (these trials exactly replicated those used to originally measure the delayed sensorimotor Roelofs effect; see Figure 2B, dashed line). In the remaining trials, the frame (5-s duration) remained illuminated until the onset of the computer-generated “Respond” command.
To test the effects of Roelofs illusion on saccades directed toward targets defined allocentrically (see Figure 7; see also Figure S6A), stimuli consisted of three small circles (connected by two thin lines), indicating three of the four corners of a small rectangle whose size and orientation was varied randomly from trial to trial. The partial rectangle was positioned so that the missing corner was located −4°, −2°, 0°, 2°, or 4° from the subject's midline, at eye level. Subjects were instructed to move their eyes to the location of the missing corner when cued to “Respond.” To accommodate the larger space required to define the target location allocentrically, the Roelofs-inducing frame was enlarged (28° horizontal × 14° vertical, 1° thickness) in this version of the experiment.
Statistical analysis
In each experiment, the signed magnitudes of localization errors (i.e., the difference between the actual and reported locations of the target in the horizontal dimension, with six repetitions for each trial type) were analyzed with a full-factorial analysis of variance, in a 5 (target location) × 3 (frame position) × 2 (response delay) design (see Figures 2, 3, and 7), a 5 (target location) × 3 (frame position) × 2 (frame duration) design (see Figure 6), or a 4 (fixation location) × 3 (frame position) × 2 (response delay) design (see Figure 4). In the present analyses, only the effects of frame position, frame duration, and response delay are considered. The effect of target location has been explored elsewhere (Dassonville and Bala 2004).
Supporting Information
Figure S1 Time Line and Results for the Perceptual Roelofs Effect
(A) Time line of task events for immediate (black) and delayed (gray) perceptual judgments of target location. Note that in this and all other experiments, feedback was presented only during practice trials, and the frame was presented only during experimental trials.
(B) Effect of frame location on immediate (solid line) and delayed (dashed line) perceptual judgments of target location for each of five target locations.
(C) Effect of frame location on immediate (solid line) and delayed (dashed line) perceptual judgments of target location for each of ten subjects.
(579 KB TIF).
Click here for additional data file.
Figure S2 Time Line and Results for the Sensorimotor Roelofs Effect
(A) Time line of task events for immediate (black) and delayed (gray) sensorimotor responses.
(B) Effect of frame offset on immediate (solid line) and delayed (dashed line) sensorimotor responses for each of five target locations.
(C) Effect of frame offset on immediate (solid line) and delayed (dashed line) sensorimotor responses for each of ten subjects.
(1.1 MB TIF).
Click here for additional data file.
Figure S3 Time Line and Results for the Inverse Roelofs Effect on Remembered Space
(A) Time line of task events for immediate (black) and delayed (gray) sensorimotor responses toward remembered reference-array locations.
(B) An inverse Roelofs effect for immediate (solid line) and delayed (dashed line) sensorimotor responses toward remembered reference-array locations, for each of five target locations. The nonlinear effect of target location has been addressed elsewhere (Dassonville and Bala 2004).
(C) An inverse Roelofs effect for immediate (solid line) and delayed (dashed line) sensorimotor responses toward remembered reference array locations, for each of ten subjects.
(2.5 MB TIF).
Click here for additional data file.
Figure S4 Time Line and Results for the Inverse Roelofs Effect on the Apparent Midline
(A) Time line of task events for immediate (black) and delayed (gray) sensorimotor responses toward the apparent midline.
(B) An inverse Roelofs effect for immediate (solid line) and delayed (dashed line) sensorimotor responses toward the apparent midline, for each of ten subjects.
(856 KB TIF).
Click here for additional data file.
Figure S5 Time Line and Results for Testing the Effects of Frame Duration
(A) Time line of task events for delayed sensorimotor responses, for trials in which the frame was either extinguished at the start of the delay period (brief frame, black) or was present throughout the delay (extended frame, gray).
(B) Effect of frame offset on delayed sensorimotor responses, for trials in which the frame was either extinguished at the start of the delay period (brief frame, dashed line), or was present throughout the delay (extended frame, dotted line), for each of five target locations.
(C) Effect of frame offset on delayed sensorimotor responses, for trials in which the frame was either extinguished at the start of the delay period (brief frame, dashed line) or was present throughout the delay (extended frame, dotted line), for each of ten subjects.
(4.7 MB TIF).
Click here for additional data file.
Figure S6 Time Line and Results for the Roelofs Effect on Allocentrically Defined Targets
(A) Time line of task events for immediate (black) and delayed (gray) sensorimotor responses to targets defined allocentrically.
(B) Effect of frame offset on immediate (solid line) and delayed (dashed line) sensorimotor responses to targets defined allocentrically, for each of five target locations.
(C) Effect of frame offset on immediate (solid line) and delayed (dashed line) sensorimotor responses to targets defined allocentrically, for each of ten subjects.
(1.8 MB TIF).
Click here for additional data file.
We thank B. Kauwe, C. Durbin, and Y. Lee for assistance in data collection, A. Summer for his programming skills, K. Stewart for setting up the lab, and A. Awh for her artistic talents. We also thank P. van Donkelaar, E. Awh, B. Bridgeman, S. Keele, J. Schlag, M. Schlag-Rey, and M. Clark for helpful comments on the manuscript. Partially supported by the National Science Foundation grant BCS-9996264 (PD).
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. PD conceived and designed the experiments. JKB performed the experiments. PD and JKB analyzed the data. PD wrote the paper.
Academic Editor: Martin S. Banks, University of California, Berkeley
Citation: Dassonville P, Bala JK (2004) Perception, action, and Roelofs effect: A mere illusion of dissociation. PLoS Biol 2(11): e364.
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| 15510224 | PMC524248 | CC BY | 2021-01-05 08:28:08 | no | PLoS Biol. 2004 Nov 26; 2(11):e364 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020364 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1551022510.1371/journal.pbio.0020365Research ArticleNeurosciencePrimatesRepresentation of Attended Versus Remembered Locations in Prefrontal Cortex Nonmemory Signals in the Prefrontal CortexLebedev Mikhail A lebedev@neuro.duke.edu
1
Messinger Adam
1
Kralik Jerald D
1
Wise Steven P
1
1Laboratory of Systems Neuroscience, National Institute of Mental HealthBethesda, MarylandUnited States of America11 2004 26 10 2004 26 10 2004 2 11 e36528 4 2004 23 8 2004 This is an open-access article distributed under the terms of the Creative Commons Public Domain Declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose2004This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
Paying Attention to Memory
A great deal of research on the prefrontal cortex (PF), especially in nonhuman primates, has focused on the theory that it functions predominantly in the maintenance of short-term memories, and neurophysiologists have often interpreted PF's delay-period activity in the context of this theory. Neuroimaging results, however, suggest that PF's function extends beyond the maintenance of memories to include aspects of attention, such as the monitoring and selection of information. To explore alternative interpretations of PF's delay-period activity, we investigated the discharge rates of single PF neurons as monkeys attended to a stimulus marking one location while remembering a different, unmarked location. Both locations served as potential targets of a saccadic eye movement. Although the task made intensive demands on short-term memory, the largest proportion of PF neurons represented attended locations, not remembered ones. The present findings show that short-term memory functions cannot account for all, or even most, delay-period activity in the part of PF explored. Instead, PF's delay-period activity probably contributes more to the process of attentional selection.
Persistent activity of neurons in an area of the frontal lobe - the prefrontal cortex - is often proposed to underlie short- term memory. Mikhail Lebedev and colleagues provide an alternative explanation
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Introduction
Jacobsen (1935, 1936) first discovered that damage to the primate prefrontal cortex (PF) appeared to cause a short-term memory deficit. In his experiments, monkeys and chimpanzees with bilateral damage to PF failed to retrieve food from one of two opaque cups when the food had been out of sight for even a few seconds. Intact animals could find the food 5 min or more after they had last seen it. Pribram et al. (1952) later identified the part of PF responsible for this deficit as area 46, also known as the dorsolateral prefrontal cortex (PFdl). More recently, temporary inactivations of portions of PFdl caused what appeared to be a short-term memory loss in localized regions of space (Funahashi et al. 1993a).
Once the concept of working memory (Baddeley 1986) became established in contemporary neuroscience (see Postle et al. 2003), these neuropsychological findings contributed to the theory that PF functions in working memory (Goldman-Rakic 1987) and, in some extreme formulations, only in working memory. In the 1990s this theory developed a wide following, and the idea that PFdl functions in spatial working memory, with other parts of PF functioning in different kinds of working memory, became the predominant theory of PF function, especially for nonhuman primates. As important, the concept of working memory used by proponents of this theory focused mostly on the short-term maintenance of information, and rather less on the manipulation or monitoring of such information or on the use of that information for decisions. Accordingly, we refer to the former aspect of working memory as maintenance memory to distinguish it from the broader concept and do not use the phrase working memory elsewhere in this report. Note, however, that when we use the phrase maintenance memory, many authorities would use “working memory” instead.
Consistent with the idea that PF functions predominantly in maintenance memory, delay-period activity in PF has often been interpreted as a memory trace (e.g., Funahashi et al. 1989; Romo et al. 1999; Constantinidis et al. 2001). The phrase delay-period activity applies to neuronal activity that follows the transient presentation of an instruction cue and persists until a subsequent “go” or “trigger” signal. The description of delay-period activity in PFdl appeared very early in the history of behavioral neurophysiology (Fuster and Alexander 1971; Kubota and Niki 1971; Fuster 1973), and, in accord with the maintenance-memory theory, some PF cells appear to buffer activity representing remembered information, even when distracting stimuli appear during the delay period (di Pellegrino and Wise 1993b; Miller et al. 1996; Moody et al. 1998). Although the interpretation of delay-period activity in terms of the short-term memory of a stimulus has a long history, many studies have explored alternatives.
Neurophysiological experiments designed to explore alternatives to the maintenance-memory interpretation of delay-period activity first attempted to dissociate sensory from motor signals. These studies showed that PFdl neurons preferentially reflected sensory signals, which supported the idea that these neurons encode stimulus memory over the short term. For example, one influential study used the “antisaccade” task (Funahashi et al. 1993b), in which a stimulus in one direction (from a central fixation point) instructed an eye movement in the opposite direction. More than twice as many PFdl neurons represented the location of the sensory stimulus as represented the target (or direction) of movement. In another experiment, when a given spatial cue guided two different reaching movements, motor factors affected PFdl neurons only rarely and weakly compared to neurons in the premotor cortex (di Pellegrino and Wise 1993b), especially when viewed at a population level (Wise et al. 1996a). These results supported the idea that more delay-period activity in PFdl reflected the memory of sensory cues than represented motor preparation or movement targets, but did not explore other alternative interpretations of delay-period activity.
Neuroimaging studies have provided support for some of these alternatives. At first, neuroimaging studies appeared to back the maintenance-memory theory of PF function, which bolstered the interpretation of PF's delay-period activity in the context of that theory. After an initial period of nearly uniform support, however, subsequent neuroimaging studies have suggested that PFdl plays a role in aspects of attention and other functions instead of, or in addition to, maintenance memory. Indeed, one recent report disputed whether PF plays any role in short-term memory at all. To quote the investigators, “no part of frontal cortex, including PF, stores mnemonic representation[s] . . . reliably across distracted delay periods. Rather, working memory storage . . . is mediated by a domain-specific network in posterior cortex” (Postle et al. 2003). Passingham and his colleagues have used the phrases attention to action, attention to intention, and attentional selection to describe certain PFdl functions (Rowe et al. 2000; Rowe and Passingham 2001). Petrides and his colleagues have, likewise, emphasized a role for PFdl in monitoring items in memory (Owen et al. 1996; Petrides et al. 2002). These alternative views of PF function point to a role in top-down control of attention and are supported by other neuroimaging and neuropsychological findings implicating PF in attentional functions (see Discussion).
In sum, then, neuroimaging and neuropsychological findings bring into question the interpretation of PFdl's delay-period activity mainly in terms of maintenance memory. Previous neurophysiological experiments have ruled out motor factors, such as motor planning and the representation of the targets of movement, for most of PFdl's delay-period activity, but have typically lacked control over spatial attention. The present experiment tested an alternative to the maintenance-memory interpretation of PFdl's delay-period activity by pitting the representation of a remembered location against the representation of an attended location, when either location could serve as the target of an upcoming saccadic eye movement.
Results
Two monkeys performed the task depicted in Figure 1A. Briefly, the monkeys maintained fixation on a spot presented at the center of a video screen, called the fixation point. A solid gray circle then appeared at a fixed distance from the fixation point in any one of the four cardinal directions (Figure 1A, part a): left, right, up, or down from center. Next, as central fixation continued, the gray circle revolved clockwise or counterclockwise around the fixation point, moving along a circular trajectory (arrow in Figure 1A, part b). It then stopped at one of the four cardinal directions from center, after having revolved 90°, 180°, 270°, or 360° (Figure 1A, part b). After a variable delay period of 1.0–2.5 s, the circle brightened or dimmed for 150 ms (Figure 1A, part c) and then disappeared (Figure 1A, part d). The change in the circle's brightness served as the trigger signal for a saccadic eye movement (arrows in Figure 1A, part d). On control trials, the circle either did not move or revolved 360° and stopped at its initial location for that trial. During those trials, both dimming and brightening of the circle instructed a saccade toward its location. During other trials, dimming and brightening of the circle guided both the timing of the response and the choice between two alternative saccade targets.
Figure 1 Task and Behavior
Behavioral task (A) and representative horizontal and vertical eye position records (B). (A) Each trial began when the monkeys pressed a button to make a fixation point (FP) appear at the center of the video monitor. Some time after the monkeys fixated the FP (dashed lines), a gray circle (depicted here as white) appeared at one of four peripheral locations. The figure illustrates its appearance at the 0° location (part a). The monkeys had to remember this location later in the task; hence we termed it the remembered location. On most trials, the circle subsequently revolved around the FP to a different location, as the monkeys maintained central fixation. The figure illustrates its termination at the 90° location (part b). A small change in the circle's luminance (part c) signaled the monkeys where to look next. This cue persisted for 150 ms, then disappeared. Because the monkeys depended on this subtle and brief cue for both timing and targeting information, we termed this the attended location. If the circle dimmed (dark gray, part c, top), the monkeys had to make a saccade to the attended location (Att-trials, part d, top). If the circle brightened (starburst, part c, bottom), the monkeys had to make a saccade to the remembered location (Rem-trials, part d, bottom). After saccade initiation, the central FP disappeared and, if the monkeys made a saccade to the correct location, a new FP appeared there (not shown). The monkeys had to fixate the new FP and, after it dimmed, release the button to produce a fruit juice reward. (Monkey drawing courtesy of Dr. Michael Shadlen.)
Brightening of the circle indicated that the monkeys should make a saccade to the circle's initial location on that trial, which the monkeys had to remember in order to perform the task correctly (Figure 1A, parts c and d, bottom). Accordingly, we called these trials remembered-location trials (Rem-trials). Dimming of the circle signaled that the monkeys should make an eye movement to its current location (Figure 1A, parts c and d, top). We called these trials attended-location trials (Att-trials), for the following reasons. As a key feature of the experimental design, the circle's brightness changed only subtly and remained visible in its new form only briefly. Because the monkeys could not predict whether the circle would brighten or dim and because that subtle, short-lived event provided essential information about the time and target of the response, the monkeys had to attend to the circle intently during the period preceding the trigger signal. As a result of the central fixation requirement, this attention was necessarily covert, although it seems likely that the monkeys would have attended overtly to the circle (i.e., fixated it), had they been allowed to do so. Indeed, the monkeys did so during training. The Discussion takes up the issues of divided attention, multiple motor plans, default motor plans, and other interpretational issues.
By varying the final location of the circle from trial to trial, we could test for significant spatial tuning for attended locations, and by varying the initial location of the circle, we could test for significant spatial tuning for remembered locations. In addition, we tested the monkeys' performance in a “no-memory” condition, which had the same the sequence of events as in the standard version of the task. In the “no-memory” condition, however, the initial location of the circle remained marked by a stationary stimulus identical to the circle that revolved around the fixation point.
Behavior
Figure 1B shows selected eye-position records, matched to the trials illustrated in Figure 1A. Table 1 shows that both monkeys achieved a high level of performance on this challenging task. For Rem-trials, these data show that the monkeys remembered the circle's initial location, and—because they could not know the trial type in advance of the trigger signal—they must have also done so for Att-trials.
Table 1 Task Performance and Reaction Times for Each Monkey
The percentage of correctly executed trials comes from the trials on which the monkey maintained fixation until the trigger signal occurred and then performed a saccade to the instructed (correct) or some other (incorrect) location. The reaction times come from correct trials only. Means (± SEM) are presented for different angular differences between the remembered and attended locations (0°, 90°, or 180°). For control trials, which correspond to a 0° difference (360° revolutions excluded), Att-trials are trials on which the circle dimmed, and Rem-trials are those on which the circle brightened
Table 1 also shows the reaction times for each monkey. Taking the two monkeys together, saccades to the remembered location began approximately 36 ms later than those to the attended location, a difference that was highly significant (Wilcoxon rank sum test, p < 0.001). We can only speculate about the cause of this difference, but reaction times on Rem-trials may have been longer because attention had to be disengaged from the circle's location and reoriented to the remembered one prior to the response. For the “no-memory” condition (not given in Table 1), reaction times for Att-trials increased approximately 16 ms compared to the standard version of the task, whereas reaction times for Rem-trials decreased approximately 22 ms (both highly significant differences, Wilcoxon rank sum test, p < 0.001). These data are consistent with the idea that each of the two marked locations attracted attention in the no-memory condition, whereas the monkeys directed most of their covert attentional resources to the attended location in the standard version of the task. We acknowledge, however, that there are other interpretations of these data. On control trials, for example, when the saccade was always toward the circle, saccade initiation was approximately 18 ms slower when the circle brightened (as it did on Rem-trials) than on trials when it dimmed (as it did on Att-trials). Thus, factors other than the orientation of attention probably contributed to reaction-time differences.
Single-Neuron Analysis
Figure 2 illustrates the activity of a neuron tuned to the attended location during the delay period. Only activity collected during correctly executed trials appears in any of the analyses presented in this report. The figure shows histogram and raster displays of neuronal activity aligned on the trigger signal for Att-trials (Figure 2A) and Rem-trials (Figure 2B), arranged in the form of a matrix, as illustrated and labeled in Figure 2C. Delay-period activity, enclosed by the red rectangles in Figures 2A and 2B, varied with the attended location (columns), but not with the remembered location (rows). The firing rate during the delay period was highest when the monkey attended to the 90° location (up from screen center, see Figure 1A, part b). We called this the cell's preferred location. The lowest firing rate occurred when the monkey attended to the 270° location, termed the least preferred location.
Figure 2 Example Neuron Representing the Attended Location
In (A–C), the four rows correspond to different remembered locations and the four columns to different attended locations (see key in [C]). (A and B) PETHs and raster displays aligned on the trigger signal (vertical line). In the rasters, each dot represents a neuronal spike, and each line of dots shows a sequence of spikes during a single behavioral trial. (A) Trials in which the stimulus dimmed and the monkey made a saccade to the attended location (Att-trials). (B) Trials in which the stimulus brightened and the monkey made a saccade to the remembered location (Rem-trials). The activity of this neuron depended on where the monkey attended, with a preferred location of 90°. Note the large variation in firing rate from column to column (across the attended locations) and relative constancy of rate within columns (across remembered locations). (C) Compact representation of spatial tuning pattern shown in (A) and (B), combined. Each circle's area is proportional to the average firing rate during the 800-ms period immediately preceding the trigger signal (red rectangle in [A] and [B]). Note that the major diagonal of this firing-rate matrix, running from the upper left to the lower right corner, corresponds to the control trials, which lacked a memory requirement. F, maximal firing rate; sp/s, spikes per second.
For each neuron, we assessed the extent of spatial tuning for the attended location with an index called attended-location index (IAtt), which measured the variability in discharge rate among attended locations. We assessed the extent of spatial tuning for the remembered locations with a related index called remembered-location index (IRem) (see Materials and Methods). A neuron was considered spatially tuned if IAtt, IRem, or both significantly exceeded 1.0 (randomization test, p < 0.01; see Materials and Methods). We classified neurons as attention cells if IAtt attained statistical significance but IRem did not, as memory cells for the opposite result, and as hybrid cells if both indexes showed statistical significance.
Figure 3A–3C shows examples of an attention cell, a memory cell, and two hybrid cells. (Figures S1–S3 show the trial-by-trial activity for each of these four cells, both before and after the trigger signal.) Neurons tuned to the attended location (attention cells) dominated the neuronal sample in both monkeys, comprising 61% of cells spatially tuned during the pretrigger delay period (Table 2). Neurons tuned to the remembered location (memory cells) made up 16% of the spatially tuned neurons, and those tuned to both locations (hybrid cells) amounted to 23%. For 27% of the hybrid cells, the attended and remembered locations associated with the highest firing rate were the same (Figure 3C, part a); in the remaining 73% of the hybrid cells, these preferred locations differed (Figure 3C, part b).
Figure 3 Example Firing Rate Matrices and a Scatter Plot of Tuning Indexes
PFdl neurons with different classes of spatial tuning. Firing rate matrices (A–C) in the format of Figure 2C; (E) gives the key. Tuning selectivity indexes (IAtt and IRem) and firing rate scale (F) appear adjacent to each firing rate matrix. (A) A neuron tuned to the attended location (different from the cell shown in Figure 2). (B) A neuron tuned to the remembered location. Its firing rate primarily varied across rows. (C) Two cells tuned to both the attended and remembered locations (hybrid neurons). One neuron (part a) exhibited a high firing rate when either the attended or remembered location was at 270°. The other neuron (part b) showed its highest activity when the remembered location was at 180°, but was inhibited when that was the attended location. (D) Scatter plot of spatial tuning indexes for attended (IAtt) and remembered (IRem) locations for each spatially tuned neuron in both monkeys. The different neuronal classes are color coded as in (A–C): blue corresponds to attention cells, red to memory cells, and green to hybrid cells.
Table 2 Cell Classification
Number of neurons that significantly (p < 0.01) encoded the attended location (Attention), the remembered location (Memory), or both locations (Hybrid) during the 800 ms immediately prior to the trigger signal
Figure 3D illustrates the degree of tuning for both the attended (IAtt) and remembered (IRem) locations. Each data point on the scatter plot represents a single spatially tuned neuron (both monkeys combined). Tuning for the remembered location (red symbols) was both weaker and less frequent than tuning for the attended location (blue symbols). Note that hybrid cells (green symbols) fill most of the space between the other two classes and that relatively few cells represent a single location exclusively. For example, many of the neurons classed as memory cells show some sensitivity to the attended location, albeit not a statistically significant one by the test that we employed. For the entire group of spatially tuned neurons (n = 303, both monkeys and all three cell classes combined), the mean selectivity indexes (± SEM) for the attended and remembered locations were IAtt = 1.84 ± 0.08 (median = 1.39, interquartile range [IQR] = 0.73) and IRem = 1.21 ± 0.02 (median = 1.08, IQR = 0.23), which differed significantly at the p < 0.001 level (Wilcoxon matched-pairs test). Table 3 shows comparable data for each cell class and Figure S4 gives similar data for various combinations of these classes. The selectivity for the attended location also exceeded that for the remembered one when expressed in terms of firing rates. For the attended location, the difference in firing rate between the preferred and least preferred locations averaged 8.8 ± 0.5 spikes/s, which was significantly greater than the 5.3 ± 0.3 spikes/s for the remembered location (Wilcoxon matched-pairs test, p < 0.001).
Table 3 Spatial Tuning Indexes Early Versus Late in the Trial
Tuning indexes (mean ± SEM) were calculated from both the 800 ms immediately preceding circle movement (Early, I) and the 800 ms immediately preceding the trigger signal (Late, IAtt, IRem). For both attention and hybrid cells, spatial tuning to the attended location was significantly stronger (Wilcoxon matched-pairs test) late in the trial, when the monkeys awaited the trigger signal. Values for memory tuning (IRem) appear for completeness, not for statistical testing. See also Figure S4
We examined whether these results merely reflected the presence of a stimulus in the monkey's visual field and found strong evidence to the contrary. We compared tuning for the circle's location during the 800 ms before the circle started moving (called the early period) and during the last 800 ms of the delay period, immediately prior to the trigger signal (the late period). (Figures S5 and S6 show activity during a slightly different early period than measured here, but they illustrate the same basic result.) Despite the fact that the sensory inputs were identical in screen-centered, allocentric, retinocentric, fixation-centered, head-centered, and body-centered coordinates, the activity of PFdl neurons and their degree of spatial tuning differed in these two task periods. This result rules out a purely sensory response. For the entire PFdl sample, the late tuning index (1.29 ± 0.03) significantly exceeded the early one (1.16 ± 0.02; p < 0.001; Wilcoxon matched-pairs test). This measure is devoid of any bias caused by a cell's tuning properties in one task period or the other, but it includes the contribution of the spatially untuned cells. When we restricted the comparison to neurons that had any type of significant spatial tuning, in either the early or late periods, the late tuning index (1.76 ± 0.07) continued to exceed the early one (1.42 ± 0.05) significantly (p < 0.001). Most important, we obtained similar results for neurons with significant tuning to the circle's location, which characterizes attention and hybrid cells (1.83 ± 0.08 late versus 1.46 ± 0.05 early; p < 0.001). Table 3 and Figure S4 present this analysis for all cell classes, alone, and in various combinations. Note that these indexes do not reflect a generalized increase in firing rate: They were normalized to remove the effects of firing rate per se. The section entitled Population Analysis presents a confirmatory result in terms of activity levels. Further confirming this result on a cell-by-cell basis, significant spatial tuning to the circle's location occurred more frequently during the late delay period (256 attention and hybrid cells) than during the early one (194 cells, of which 41 lost their spatial tuning in the late period). Thus, the representation of the circle's location in PFdl grew stronger around the time of the trigger signal, when it was important for the monkeys to attend to the circle. These findings rule out the mere presence of the circle in something akin to a visual receptive field as a complete account of the tuning of attention and hybrid cells.
Histological Analysis
Figures 4 and 5 show the locations of the cells in each class: Figure 4 as a function of electrode-penetration sites for both monkeys and Figure 5 as section reconstructions for monkey 2. The attention cells were concentrated more ventrolaterally than either the memory or the hybrid cells. Neurons located ventrolateral to the fundus of the principal sulcus (n = 551) were predominantly attention cells (28% to 2% memory and 5% hybrid cells, with 65% lacking spatial tuning, both monkeys combined). Neurons dorsomedial to the fundus (n = 412) fell into the three cell classes approximately equally (8% attention, 9% memory, and 10% hybrid cells, with 73% lacking spatial tuning). These regional differences within PFdl were highly significant for each monkey (p < 0.0001, χ2 test). Cells with significant memory signals (memory and hybrid cells, combined) composed 70% of the spatially tuned population in dorsomedial PFdl, but only 20% in ventrolateral PFdl.
Figure 4 Surface Projections Showing the Location of Neurons in Each Class
All hemispheres are displayed so that rostral is to the left and dorsomedial is up. Reconstructed surface projections of the left hemispheres of monkey 1 (A) and monkey 2 (B). (C) Surface projection of the (inverted) right hemisphere of monkey 1. (D) A lateral view of the hemisphere shown in (C), with the region included in (C) approximated by the dashed box. The dotted ellipse encloses the cells deemed to lie inside the PFdl by histological analysis, but does not correspond to the cytoarchitectonic boundaries of area 46.
Figure 5 Section Reconstructions for Monkey 2
(A–G) Coronal sections taken at the planes indicated in the surface drawing (H). Dashed lines mark the borders between PFdl (area 46) and area 12. Solid lines show the tracks of the marking pins (irregular outlines in sections [B] and [C]) and the estimated location of electrode penetrations. Colored hash marks show the estimated depth of neurons in each class, using the same color code as in Figures 3 and 4. Longer hash marks indicate simultaneous recordings of more than one neuron of the same class. (H) Lateral view of left PF depicting surface projections of spatially tuned neurons. Black circles show the locations of pin holes used for localization, and gray squares show their predicted locations.
Based on a cytoarchitectonic analysis conducted on two of the three hemispheres, all of the cells situated ventrolateral to the fundus of the principal sulcus were located within area 46 and none were located in area 12. The area 46/12 architectonic boundary was first described by Walker (1940) and was subsequently confirmed with different methods (Preuss and Goldman-Rakic 1991). This boundary could be discerned in both monkeys as a distinct thinning of the internal granular layer in area 12 compared to area 46 and a more substantial departure in that area from the classic, homotypical appearance typical of area 46. The reconstructed location of recording sites showed that the small group of cells located caudomedially in both monkeys (see Figure 4B and 4C) was located in the postarcuate cortex (area 6) and in area 8, as indicated by the agranular and dysgranular cytoarchitecture of these two regions, respectively. This small group of cells was eliminated from the present analysis.
Population Analysis
Figure 6 displays the degree of spatial tuning for the different cell classes in the form of population histograms. The analysis of attention tuning (Figure 6A and 6B) used the 800 ms immediately preceding the trigger signal to measure mean firing rates for different attended locations. We excluded control trials from this analysis. These rates were then ranked from the largest (i.e., the preferred attended location) to the smallest (the least preferred location). For each neuron, the preferred location chosen by this analysis was designated as preferred for all task periods displayed in the population histograms. (Similar results were obtained when the ranking was done for each individual task period.) The left side of the figure shows the mean attention signal for both attention (Figure 6A) and hybrid (Figure 6B) cells. After a transient response to the appearance of the circle (at a latency of approximately 100 ms), neuronal activity in both of these cell classes remained elevated when the circle stopped at the preferred location (blue curve) and became slightly suppressed when it was at the least preferred location (black curve).
Figure 6 Attention and Memory Signals in Population Histograms
(A) and (B) Representation of an attention signal by attention cells (A) and hybrid cells (B). (C) and (D) Representation of a memory signal by memory cells (C) and hybrid cells (D). In each panel, activity is shown centered on the appearance of the circle (left vertical line), on the time that the circle stopped moving (middle vertical line), and on the trigger signal (right vertical line). Attention and memory signals are reflected in the degree of separation in the average population histograms for different ranks. In (A) and (B), the data for the period immediately prior to the end of the circle's movement have been eliminated because the circle came from different initial locations.
The right side of Figure 6 shows the mean memory signal for memory (Figure 6C) and hybrid (Figure 6D) cells. These population histograms were calculated on the basis of preferred remembered locations, ranked according to the pretrigger modulation. This location was then designated “preferred” for all task periods displayed in the plots. For memory cells (Figure 6C), the population averages were almost identical when the circle remained stationary at its initial location and that location did not yet need to be remembered. That is, on average it did not matter noticeably whether the circle initially appeared at a cell's preferred location or at its least preferred location (Figure 6C, red versus black curves). This finding is somewhat surprising because prior studies suggested that PFdl's memory cells had activity that began shortly after stimulus onset and continued throughout the delay period. In our memory cells, spatial tuning did not develop to any appreciable extent until after the circle began revolving around the central fixation point. This result shows that tuning to the remembered location developed during the trial and was not a simple replica of the tuning pattern during the initial presentation of the circle. Hybrid cells (Figure 6D) exhibited a weak spatial signal following the appearance of the circle consistent with their memory tuning prior to the trigger. Note that after the circle stopped moving, memory cells showed less of a difference between preferred and least preferred locations than did attention cells (Figure 6C versus 6A). This finding supports the results presented in Tables 2 and 3 and Figure 3D, which show a predominance of nonmemory signals (see also Figure S4).
Population representations of the attended and remembered locations were further analyzed using a neuron-dropping analysis. Neuron-dropping curves express the strength of spatial tuning as the ability to estimate a spatial variable from the activity of a neuronal ensemble, as a function of ensemble size. We randomly selected an ensemble from the population of recorded PFdl neurons and used a single trial of activity from each cell to estimate both the attended and remembered locations. The findings of the neuron-dropping analysis agree with those from the analysis of single-cell activity and the population histograms and thus provide independent support. However, neuron-dropping analysis offers several advantages over the population histograms, in addition to providing confirmation of those results. In neuron-dropping, the estimation of either an attended or remembered location does not depend on any assumptions about the nature of the spatial tuning curve or the relative importance of very active cells versus those showing less activity. It does not ascribe any special significance to increases in activity relative to baseline (excitation) versus decreases (inhibition) or to the most preferred and least preferred locations. Each cell's activity contributes to the population estimation for all locations regardless of the direction of its modulation relative to baseline and whether that modulation significantly differs from baseline levels. Furthermore, the computation makes no assumption about any relationship between tuning for attended locations and remembered ones. This analysis also has the advantage that its results are expressed as a percentage of correct estimations by the neuronal ensemble, thereby facilitating comparison with the monkeys' performance, which in this experiment always exceeded 75% correct and sometimes approached 100% (Table 1).
Figure 7 shows the neuron-dropping curves for each cell class (A–C) and all spatially tuned neurons combined (D) in monkey 1. Neuron-dropping curves for monkey 2 showed similar results, and Figure S7 presents the data for both monkeys combined. As expected, the neuron-dropping curves computed for attention cells yielded much better estimations of the attended location than the remembered one (see Figure 7A, blue versus red curves). Note, however, that the attention cells also provided a better-than-chance estimation of the remembered location. This result reflects the fact that many cells with significant tuning for the attended location also showed some tuning for the remembered location (see blue data points in Figure 3D with IRem > 1.0). Figure 7A also confirms the comparison of activity early versus late in the trial (blue versus gray curves), providing further evidence against a purely sensory account of this subpopulation's activity. Also as expected, memory cells yielded a better estimation of the remembered location than the attended one (Figure 7B, red versus blue curves), but these cells, too, yielded a fairly reliable estimation of the other spatial variable. Neuron-dropping curves for hybrid neurons showed comparable estimations for both locations (Figure 7C). When all spatially tuned neurons were combined (Figure 7D; see also Figure S7D), the resultant neuron-dropping curves showed that PFdl activity was a much more reliable estimator of the attended location than the remembered one.
Figure 7 Neuron-Dropping Curves for Different Subpopulations of PFdl Neurons in Monkey 1
Each curve represents the percentage of correct single-trial estimations of location as a function of the number of neurons in the assembled populations. The curves show predictions of the attended locations (blue lines) or remembered locations (red lines) during the 800 ms immediately preceding the trigger signal, after the circle had stopped revolving around the central fixation point. Also shown is the estimation for the 800-ms period immediately preceding the onset of the circle's movement (gray lines). The dotted line indicates the chance level of estimation, 25% correct. Neuron-dropping curves are shown for neurons tuned to the attended location (A), the remembered location (B), both locations (C), and all spatially tuned neurons (D). (E) and (F) Dynamic changes in estimations of the attended (blue) and remembered (red) locations for 20 spatially tuned neurons (marked by the dashed gray line and arrows), using a 200-ms sliding window. Dashed and solid lines in (E) and (F) are shown for consistency with Figure 8. Note that the estimations in (D) are higher than in (E) and (F) because the former is based on an 800-ms interval, and the latter are based on only a 200-ms interval.
The same analysis was applied to the ventromedial and dorsolateral regions within the PFdl, described in the section entitled Histological Analysis, above (not shown). The ventrolateral subpopulation of PFdl neurons (see Figure 4A–4C) overwhelmingly represented the attended location. The dorsomedial subpopulation represented both locations comparably, with estimation of the attended location being slightly better in one monkey and estimation of the remembered location being slightly better in the other. Of the two subpopulations, the dorsomedial neurons showed a more reliable estimation of the remembered location.
We also used a neuron-dropping analysis to examine the ensemble's properties during response selection and execution. Figure 7E and 7F show these time-dependent neural-estimation curves for monkey 1; Figure 8 does so for both monkeys combined. Note from Figure 7D–7F that the time-estimation curves come from a random sample of neurons, much smaller than the sampled population, to avoid the effects of signal saturation. The estimations at each time point reflect activity averaged over the previous 200 ms. Prior to the trigger signal, the estimation of the attended location (blue curves in Figures 7E, 7F, 8D and 8E) was superior to that of the remembered location (red curves) for all spatially tuned neurons, as well as for attention cells (Figure 8A). This finding is consistent with the greater number and stronger spatial tuning of attention than memory cells.
Figure 8 Time-Dependent Changes in Estimating the Attended Location and Remembered Location, for Both Monkeys Combined
Solid lines, trials in which the monkeys made a saccade to the attended location; dashed lines, trials in which the monkey made a saccade to the remembered location. Blue lines, estimation of the attended location; red lines, estimation of the remembered location. All records are centered on the onset of the trigger signal (using data for the 200 ms prior to that time). Vertical lines at t > 0 show the average saccade latency on Att-trials (solid) and Rem-trials (dashed). The thick bar at the bottom of the plots shows the approximate onset of the peripheral fixation spot, which the monkeys continued fixating beyond the limit of the plot. Estimations for each monkey were calculated using the same methods as for Figures 7E and 7F, except that the ensemble size for monkey 2 was 60 neurons. This number of neurons was chosen to avoid ceiling effects (i.e., 100% correct). The plotted curves show the average for the two monkeys. Location estimations for attention (A), memory (B), hybrid cells (C), and all spatially tuned neurons on Att-trials (D) and Rem-trials (E). Above the plots are schematic depictions of an example trial, of the type illustrated in Figure 1A. The red “R” marks the remembered location. In both D and E, prior to the trigger signal (left schematic), the monkeys fixated (dashed lines) centrally and covertly attended to the circle (yellow spot at the attended location). During this period, estimation of the attended location exceeded that of the remembered location. Following the saccade, the monkeys fixated a peripheral light spot (right schematic) and attended to this target to detect when it dimmed. On Att-trials (D), the monkeys' gaze shifted to the attended location, and the ensemble's estimation of this now overtly attended location improved (solid blue curve), while the representation of the now irrelevant, remembered location gradually decayed (solid red curve). On Rem-trials (E), the monkeys' gaze (dashed lines) and focus of attention (yellow spot) shifted to the (previously) remembered location. The estimation of this location consequently improved (red dashed curve), while the estimation of the previously attended (and now irrelevant) location gradually decayed. Abbreviations: Att, attended; Rem, remembered.
On Att-trials, the estimation of the attended location (solid blue curves in Figures 7E and 8A–D) improved following the dimming of the circle and remained elevated during the saccade to that location. This improvement continued for the initial 200 ms of fixation there. Then the signal decreased. Note that the monkey maintained fixation at the target location for at least 1.0 s after the saccade. In contrast, the estimation of the remembered location on Att-trials (solid red curves) gradually decreased following the trigger signal. The fading of this representation most likely reflected the fact that the remembered location was no longer behaviorally relevant.
On Rem-trials (dashed curves in Figures 7F, 8A–8C, and 8E), the circle's brightening instructed a saccade to the remembered location (marked by the red “R” in Figure 8E). We expected that redirecting attention toward the saccade target (yellow spot in Figure 8E, right) would degrade the neuronal representation of the formerly attended location and improve the representation of the formerly remembered—but eventually fixated—one. The estimation of the attended location initially improved on Rem-trials following the trigger signal there (blue dashed curves in Figures 7F, 8A–8C, and 8E). However, in accord with our expectation, that estimate decreased dramatically in accuracy after saccade onset, as the attended location became behaviorally irrelevant. In contrast, the estimation of the formerly remembered (and soon to be fixated) location (red dashed curves) improved sharply (Figure 8E), especially in attention cells (Figure 8A). Thus, PFdl neurons became more reliable encoders of that location. Given that these averages “look back” 200 ms, this development must have preceded the saccade.
On both Att-trials and Rem-trials, the neuronal ensemble remained a reliable indicator of the saccade target relatively long after the target had been acquired (see solid blue and dashed red curves in Figures 7E, 7F, and 8). This signal might encode the fixated location, which could be important for monitoring performance, as suggested for nearby areas of frontal cortex (Stuphorn et al. 2000; Ito et al. 2003). Alternatively, the saccade target may have been represented because the monkeys attended to the fixation spot at this location, so that when it dimmed they could quickly release the button to produce their reward (see Materials and Methods, below, for a description of that aspect of the task).
Discussion
In tasks involving short-term memory requirements, delay-period activity in PFdl has consistently been interpreted in terms of the maintenance-memory theory of PF function (e.g., Funahashi et al. 1989; Romo et al. 1999; Constantinidis et al. 2001), despite the existence of viable alternatives. However, our results show that much of PFdl's delay-period activity in such tasks reflects nonmemory functions. Accordingly, the maintenance-memory theory of PF function (Goldman-Rakic 1987, 1990), taken to its extreme, fails to account for PFdl's delay-period activity. Indeed, we found that, compared to the remembered location, the attended location was more frequently and more robustly encoded at both the neuronal and population levels. The present results thus support extensive neuropsychological (Rueckert and Grafman 1996; Stuss et al. 1999; Koski and Petrides 2001, 2002) and neuroimaging (Corbetta et al. 1993; Gitelman et al. 1999; Kastner et al. 1999; Rosen et al. 1999; Cabeza and Nyberg 2000; Hopfinger et al. 2000, 2001; Vandenberghe et al. 2000; Astafiev et al. 2003; Small et al. 2003; Thiel et al. 2004; Woldorff et al. 2004) research that points to a much more general role for PF than encompassed by the maintenance-memory theory, including the top-down control of selective attention.
Interpretational Issues and Limitations
The present experiment is the first neurophysiological study to achieve a degree of independent control over both spatial attention and spatial memory, so a detailed consideration of both its advantages and limitations is in order. A complete dissociation of these two spatial variables is probably impossible, but we achieved this goal to a considerable degree. Our experimental design, however, has several limitations and raises a number of questions. For example, is what we call attention really attention? We have elaborated on our usage of the term attention in the Results section. Although we did not quantify the degree of attention, it seems to us a reasonable assumption that the monkeys attended to the circle, given that its brightening or dimming was subtle, brief, and crucial to their correct performance. Moreover, the reaction-time data are consistent with the idea that the monkeys attended to the circle in the period immediately prior to the trigger signal. The remaining interpretational questions to be addressed, then, are: Do monkeys devote any attentional resources to what we call the remembered location? Do they “remember,” in some sense, what we call the attended location? Does the activity we interpret in terms of attention or memory reflect motor factors? And, given that the monkeys could anticipate and predict rewards, do the signals reflect these processes? We address each of these four questions, in turn, in the remainder of this section.
First, although we contend that the monkeys must have devoted substantial attentional resources to the location of trigger signal, this does not necessarily rule out additional covert allocations of attention to the remembered location. However, there was no stimulus or expected signal at the remembered location to warrant the allocation of attentional resources there. In addition, the demands of fixating the central location (overt attention), while attending covertly to a stimulus located in peripheral visual space, make it unlikely that attention was further divided (Hunt and Kingstone 2003; Muller et al. 2003). Accordingly, although we cannot completely rule out the possibility that the monkeys attended to the remembered location during the delay period, it seems implausible that they did so. If one adopts the view that they did, then some or all of the neurons we class as memory cells might instead have activity better interpreted as reflecting some aspect of highly divided attention.
Second, the monkeys were required to remember the place where the circle first appeared on each trial, and their performance shows that they did so. Did they also “remember” the attended location? There is ample precedent for skepticism about the proposition that monkeys are not remembering some location. However, there is no basis for assuming a “memory” of a currently visible stimulus. It seems especially unlikely that the monkeys “remembered” the attended location in the context of the requirement that they centrally fixate while attending somewhere and remembering somewhere else.
Third, we cannot rule out the participation of neurons we class as attention or memory cells in a variety of processes involved in preparing or planning the movement or selecting the response target. Prior to the trigger signal, the monkeys may have prepared to make a movement to the remembered location, to the attended location, to both, or to neither. Cisek and Kalaska (2002) have shown that some neurons in the premotor cortex encode a possible movement target before a particular one has been specified, but their experiment has yet to be done for PFdl neurons. In view of prior evidence arguing against interpreting much of PFdl's delay-period activity in terms of motor signals (Funahashi et al. 1989, 1993b; di Pellegrino and Wise 1993b; Asaad et al. 1998; Romo et al. 1999; Constantinidis et al. 2001) and the absence of a contemporary “motor theory” of PF function, the present experiment was not designed to address this issue. Future work along these lines, perhaps combining the design of di Pellegrino and Wise (1993b) with the present one, might be indicated by the present results. We believe, however, that a simple “motor” explanation for most of PFdl's delay-period activity is an unlikely outcome of such studies. A “motor” interpretation probably does, however, account for a small proportion of PFdl's delay-period activity, consistent with the results of Funahashi et al. (1993b). On certain assumptions about a default motor plan, such neurons could have the tuning properties of the hybrid cell illustrated in Figure 3C, part a. It is important to emphasize, however, that the present experiment tested whether the maintenance-memory theory could account for all delay-period activity in PFdl. It cannot. We view this result as supporting an important role for PF in the top-down control of attention. If one takes a motor theory of PF function more seriously than most expert opinion currently does, then it is possible to interpret the present result as indicating a role in context-dependent response or goal selection or in terms of the preparation of movements to remembered targets versus current stimuli. Neither interpretation is consistent with an interpretation of PFdl's delay-period activity entirely in terms of a maintenance-memory function.
Fourth, we need to consider the possibility that the neural signals we observed reflect the prediction or anticipation of reward. Maunsell (2004) has recently pointed out that neural signals interpreted as arising from attention could instead reflect reward anticipation or prediction (and vice versa). In the present study, however, reward-related information processing could not have accounted for the properties of attention cells because, until the trigger signal, one alternative place (the remembered location) was associated with reward to the same degree as the attended location.
Enhancement Effects
The general term attention has been used to cover many disparate concepts, including the effects of attention on sensory processing and the mechanisms that mediate those influences. We emphasize that the present finding differs from previous ones describing effects of attention on phasic, sensory-like responses. Often called the enhancement effect, the finding that sensory responses are larger when a stimulus or location is more attended was first described for the superior colliculus (Wurtz and Goldberg 1972) and has been repeatedly demonstrated for many cortical areas, including PFdl (Mikami et al. 1982; Boch and Goldberg 1989; di Pellegrino and Wise 1993a; Rainer et al. 1998; DeSouza and Everling 2004). In some instances, and especially in frontal cortex, the enhancement effect depends on the attended location being the target of a movement (Goldberg and Bushnell 1981), but in other cases it does not (Bushnell et al. 1981). It has often been suggested that the source of attention effects, including the enhancement effect, match enhancement, and related phenomena, depends on signals emanating from PF (Miller et al. 1996; Kastner et al. 1999; Reynolds et al. 1999) or from the frontal eye field (Thompson et al. 1997; Moore and Fallah 2004). The present results are consistent with this idea. They cannot, however, be considered as yet another example of the enhancement effect, which involves attention-dependent augmentation of a phasic sensory response.
Neurons Encoding Both Attended and Remembered Locations
Most neurons did not encode an attended or remembered location exclusively; rather, they exhibited varying degrees of tuning for both variables. The neuron-dropping curves (see Figure 7) show that attention cells were able to make limited, but above-chance, estimations of the remembered location and vice versa. As can be seen from the spatial tuning indexes in Figure 3D, few individual neurons were pure attention or memory encoders (data points along the axes). Thus, the population of spatially tuned cells can be viewed as a continuum with attention and memory cells at the extremes, and hybrid cells in between.
Interestingly, the neuron-dropping curves for the hybrid cells (see Figures 7C and 8C) showed effective estimation of both the attended and remembered locations. Hybrid neurons with dissimilar preferences for the two locations facilitated such estimations. For instance, the neuron shown in Figure 3C, part b had a low firing rate when the monkey attended to the 180° location and a high firing rate when it remembered that place. Hybrid cells with dissimilar preferences can resolve the ambiguity inherent in cell activity like that illustrated in Figure 3C, part a, which cannot distinguish between attended and remembered locations.
Previous Neurophysiological Studies
Previous neurophysiological studies of PFdl's delay-period activity have been interpreted in terms of the maintenance-memory theory. However, the lack of control over spatial attention in these studies raises questions about these interpretations. Constantinidis et al. (2001), for example, trained monkeys to make delayed saccades toward the location of the brighter of two visual stimuli that briefly flashed on the video screen. They reported that the activity of PFdl neurons reflected the brightness of the stimuli. Although these authors interpreted their findings as demonstrating a purely sensory-mnemonic function for PFdl neurons, brighter stimuli, being more salient, are well known to attract attention to their location.
Similar problems affect the interpretation of data from the “antisaccade” task (Funahashi et al. 1993b). In their antisaccade task, Funahashi et al. trained a monkey to respond to a stimulus to the left of a fixation point by making a saccade to the right and vice versa. They interpreted their data as demonstrating a function for PFdl in spatial memory because the largest number of neurons reflected the stimulus location rather than the movement target. They showed that during the delay period, when nothing was present on the screen, some neurons reflected where the stimulus had occurred, and these were interpreted as memory cells. Note, however, that where ever the stimulus appeared, whether in antisaccade or prosaccade trials, it served as an attention attractor. If the response to that signal persisted, then interpreting it exclusively as a sensory memory trace would be problematic. Many studies suggest that, for neurons in PF, the history of what has happened or the context in which it happens often affects neuronal activity in an important and persistent way (Rainer et al. 1998; Asaad et al. 2000; Wallis and Miller 2003), sometimes regardless of relevancy (Chen et al. 2001). Such persistent signals can be viewed as components of working memory in a general sense, but not in the narrow sense implied by the concept of maintenance memory.
Neuroimaging and Neuropsychological Results from Humans
Based on the idea that the principal or exclusive function of PFdl is to support maintenance memory (Goldman-Rakic 1987), many neuroimaging papers on PF, including PFdl, have been interpreted as supporting this theory of PF function (see, for example, Courtney et al. 1996, 1997, 1998; Druzgal and D'Esposito 2003; Inoue et al. 2004). This idea has been defended (Goldman-Rakic 2000), but a number of alternatives have been suggested. For example, several neuroimaging findings support a role for PF in the control of attention, and brain lesion studies also show attentional deficits after damage to various parts of PF (Corbetta et al. 1993; Rueckert and Grafman 1996; Gitelman et al. 1999; Kastner et al. 1999; Rosen et al. 1999; Stuss et al. 1999; Cabeza and Nyberg 2000; Hopfinger et al. 2000, 2001; Vandenberghe et al. 2000; Koski and Petrides 2001, 2002; Astafiev et al. 2003; Small et al. 2003; Thiel et al. 2004; Woldorff et al. 2004; see also a recent review by Wood et al. 2003).
In general, top-down attention has been assumed to result from signals emanating from the frontal cortex and biasing more posterior areas to favor some channels of information over others, and some neuroimaging papers have supported this idea (Chawla et al. 1999; Kastner et al. 1999; Corbetta and Shulman 2002; Nakahara et al. 2002; Pessoa et al. 2003). In addition, a role in attentional selection and the related concepts of attention to action and attention to intention have been stressed as an alternative to the maintenance-memory theory of PF function (Rowe et al. 2000; Rowe and Passingham 2001; Lau et al. 2004). Similarly, monitoring the items in short-term memory has been put forward as a principal function of PFdl, and this also is primarily an attentional function (Owen et al. 1996; Petrides et al. 2002). Along these lines, a recent study by Nobre et al. (2004) indicated that PF plays a role in directing attention to locations within mental representations.
Neuropsychological Results from Monkeys
Previous research on monkeys has also suggested a role for PF (or nearby parts of the frontal lobe) in the orientation of spatial attention. Welch and Stuteville (1958) produced trimodal (auditory, visual, and tactile) neglect-like effects following ablations in the depths of the arcuate sulcus, including what was likely part of PF (although not PFdl). Rizzolatti et al. (1983) reported neglect for space beyond a monkey's reach after lesions targeting area 8. However, for at least one of the two monkeys they studied, the lesion may have included the area studied here. Deuel and Farrar (1993) also produced neglect-like symptoms by making cortical lesions that included much of the same region, and roughly similar observations have been interpreted as motor neglect (Heilman et al. 1995). PF lesions also caused attention-like deficits in a conditional motor learning task (M.F.S. Rushworth et al., personal communication).
In the context of the present results, the finding that inactivation of parts of PFdl (Funahashi et al. 1993a) produced what were termed “mnemonic scotomas” deserves reconsideration. In that experiment, a transient cue served as the target of a saccade after a delay period. Following local inactivations within PFdl, the monkeys in that study continued to make most of their responses to sites near the cue's remembered location, even with 3-s and 6-s delays after the disappearance of the cue (see their Figures 5, 9, and 13). The monkeys made the vast majority of their responses in the correct direction, but a few saccades fell outside the target zone. This inaccuracy contributed to significantly increased variance in the endpoints of the saccades, and Funahashi et al. (1993a) concluded on this basis that the monkeys were unable to remember the cue's location. We suggest, as an alternative explanation of their results, that their monkeys had a deficit in detecting the stimulus at the cued location, directing attention there, or maintaining their attention at the cued location. Thus, the results interpreted as “mnemonic scotomas” might be better understood as a localized neglect-like phenomenon or some combination of attention and memory deficits. This suggestion finds support in the results of a recent study in humans with PF lesions. Hornak et al. (2004) reported a failure of such patients to pay attention to information on a screen, and this problem accounted for their behavioral deficits. Therefore, the results of Funahashi et al. (1993a) provide little support for either the maintenance-memory theory of PF function or the interpretation of its delay-period activity in terms of that theory.
The present results agree better with those of Rushworth et al. (1997), who found that monkeys could remember nonspatial stimuli across relatively long delay periods after bilateral removal of the part of PF theorized to maintain such memories. The present results also agree with Petrides (2000), who found that PFdl lesions do not affect the short-term memory for objects (as measured by a susceptibility to increasing delay periods), but do cause impairments in the ability to monitor which items have been selected from a group (as measured by a susceptibility to increasing group size).
Conclusions
The present study reexamined the interpretation of PFdl's delay-period activity in terms of the maintenance-memory theory. We found that other factors are more important than mnemonic ones. The present results do not argue against a short-term memory function for PF, as one among many contributions to behavior. Nor should they lead to the dismissal of interpretations of some delay-period activity in PF, or some neuroimaging signals from that region, in terms of short-term memory. However, spatial memory signals occur less frequently in PFdl than the maintenance-memory theory predicts. Our data thus accord better with neuroimaging and neuropsychological studies indicating that PF plays a major role in attentional selection, including the monitoring of information and actions (Owen et al. 1996; Rowe et al. 2000; Rowe and Passingham 2001; Petrides et al. 2002; Manly et al. 2003; Lau et al. 2004).
How do our findings mesh with the fact that damage to PF appears to produce deficits in short-term memory, as Jacobsen (1935, 1936) first showed nearly 70 years ago? One possibility is that lesion studies speak more to the inability of other areas to compensate for the loss of PF than to the priority of functions within that region. Another is that an attentional deficit would likely have an important effect on the performance of tasks typically used to assess short-term memory in monkeys, such as matching-to-sample or delayed-response tasks, especially if monkeys use selective attention as a strategy for solving the problems posed by such tasks (see di Pellegrino and Wise 1993b; Awh and Jonides 2001).
Although attention could account for many findings about PF, we do not aim to replace one monolithic theory of PF function—the maintenance-memory theory—with an equally monolithic “attention theory.” Delay-period activity appears to reflect the learning and implementation of behavior-guiding rules (Wise et al. 1996b; White and Wise 1999; Wallis et al. 2001, Wallis and Miller 2003), categorization of events and stimuli (Freedman et al. 2001, 2003), prediction of forthcoming events (Rainer et al. 1999), task selection (Hoshi et al. 1998; Asaad et al. 2000), and adaptive actions within structured-event sequences (Barone and Joseph 1989; Quintana and Fuster 1999; Ninokura et al. 2003, 2004; Hoshi and Tanji 2004), among other cognitive functions. According to one view, PF functions in general intelligence for the solution of any and all difficult cognitive problems (Duncan and Owen 2000). Gaffan (2002) has likewise argued that PF resembles a global workspace, in the sense used by Baars et al. (2003), implying a lack of domain selectivity. The present result, by showing that PFdl's delay-period activity lacks an account solely in terms of maintenance memory, supports these ideas to some extent. However, the finding of regional specializations among different parts of the PFdl (see Figure 4), in accord with similar findings (Ninokura et al. 2003, 2004; Hoshi and Tanji 2004), suggests that various parts of PF contribute to this global workspace differently, each by making some selective contribution to PF's overall function. Taken together, these observations suggest that delay-period activity in PF reflects functions extending far beyond maintenance memory to include all of the behaviors important to the life of primates.
Materials and Methods
Behavioral task, apparatus, and single-unit recordings
We trained two rhesus monkeys (Macaca mulatta) to perform the task. Each monkey sat in a primate chair in front of a computer monitor placed 57 cm from the monkey's eyes. We recorded eye position with an infrared oculometer and sampled at 250 Hz. The monkeys pressed a waist-high button with their right hand to start each trial and did not release the button until the end of the trial. Once the monkeys pressed the button, a 0.2° fixation point appeared at the center of the screen. After they had fixated this stimulus for 1.0–1.5 s, a 2° solid, gray circle appeared 8° from the center of the screen in one of four places. Figure 1A, part a illustrates the right (0°) location. After another 1.0–1.5 s, the circle revolved from this initial location to one of four final places (Figure 1A, part b) at 90°/s along a circular trajectory centered on the fixation point. For monkey 1, the circle revolved 90° or 180° either clockwise or counterclockwise. For monkey 2, the circle revolved 90°, 180°, or 270° either clockwise or counterclockwise. After the circle stopped, a 1.0 to 2.5-s delay period ensued. Then a trigger signal occurred, which provided an instruction as to the saccade target, as well as a “go” cue for the saccade. The trigger signal consisted of a 150-ms-long change in the circle's brightness (Figure 1A, part c), followed by its disappearance (Figure 1A, part d). If the circle dimmed, the saccade had to be directed to the circle's final (and current) location on that trial; if the circle brightened, the saccade had to be directed to the circle's initial location on that trial. After the monkeys started a saccade, the central fixation spot disappeared. If the monkeys made a saccade to the correct location, a new 0.2° fixation spot appeared there, and the monkeys had to fixate this spot for 1.0–1.5 s, after which it dimmed. The monkeys could then release the button to produce a fruit juice reward. If the monkeys broke fixation prior to the trigger signal, made an incorrect saccade, or released the button prematurely, the trial was cancelled, and the monkeys could begin a new trial. In control trials, the circle either did not move (both monkeys) or returned to its initial location (360° movement, either clockwise or counterclockwise, monkey 2 only), and the monkeys had to make a saccade to the location of the circle whether it dimmed or brightened. The initial and final locations of the circle and whether it brightened or dimmed were selected pseudorandomly, as was the duration of the delay period and the direction in which the circle revolved around the central fixation point. The monkeys had to complete one correct trial of each type (32 in all, including control trials) before repeating a trial type.
After the monkeys learned the task, we implanted recording chambers over the left (monkeys 1 and 2) and right (monkey 1) PFdl. For monkey 1, we used a single-electrode microdrive to obtain single-neuron activity records; for monkey 2, we used a microdrive that independently moved up to seven electrodes. During recordings in monkey 1, we intentionally biased the selection of task-related neurons toward those with delay-period activity. In monkey 2, we recorded the activity of all isolated neurons, regardless of whether they were task related.
For histological reconstruction of recording sites, we examined Nissl-stained sections of 40 μm thickness from the right hemisphere in monkey 1 and the left hemisphere in monkey 2.
Quantification of tuning
We represented firing rate data in a 4 × 4 matrix, Fij, with rows (i) corresponding to the remembered location and columns (j) to the attended location (Figures 2, 3A–3C, S1–S3, S5, and S6). We assessed tuning for the remembered locations by comparing the variability of firing rate between trials in different rows with the variability of firing rate between trials from the same row. To avoid the influence of across-column modulations (i.e., an attention effect), both between-row and within-row variabilities were calculated only for matrix elements from the same column, one column at a time, and then we averaged these results. This procedure amounts to comparing different remembered locations, while holding the attended location fixed. To quantify the strength of tuning for the remembered location, we computed a ratio of between-row variability and within-trial type variability:
(1)
where l1 and l2 index individual trials, i, j, and k are matrix indexes that take on the values of 0°, 90°, 180°, and 270°, Fij (l) is the firing rate on the lth trial for which position i was the remembered location and position j was the attended location, and N1 and N2 are total number of elements in the respective sums. Control trials were excluded from the calculation by not considering the diagonal elements of Fij (i = j, j = k).
We evaluated tuning to the attended location similarly by comparing across-column variability with within-column variability, one row at a time. The strength of representation of the attended location, was quantified as:
(2)
We used two task periods to compute the single trial firing rates Fij (l). To classify neurons into those representing remembered versus attended location, we used an 800-ms period preceding the trigger signal. We also evaluated spatial tuning (I) during the final 800-ms period before the circle started to move. (Figures S5A and S6A illustrate this “early” period slightly differently, averaging activity in an interval from 200 ms to 1,000 ms after the appearance of the circle.) The IRem or IAtt ratios approximated unity for untuned neurons and increased with tuning strength. To measure statistical significance, we used a randomization test. Trials were randomly shuffled among different remembered or attended locations, and the indexes were recomputed. This procedure was repeated 1,000 times to yield a distribution of index values from which we computed a probability p. We chose a statistical significance level of p < 0.01 to classify neurons as tuned for either IRem, IAtt, both, or neither (untuned).
Population histograms
We computed the population histograms of Figure 6 by first determining each neuron's preferred location, using firing rates during the 800 ms preceding the trigger signal. Then we ranked the trials as belonging to the preferred location, the next most preferred, the third most preferred, and the least preferred location. This ranking was then applied to the other task periods. Next we calculated peri-event time histograms (PETHs) for each rank, separately for each neuron. Averages of these single-neuron PETHs yielded the population histograms. To avoid biasing average histograms by statistical noise in the ranks, we used one half of the trials to compute the ranks and the other half to compute the histograms. If the spatial preference of a neuron merely reflected noise, this procedure tended to nullify the influence of the neuron on the population average. We ranked attended and remembered locations in separate computations.
Neuron-dropping curves
Neuron-dropping curves (Figures 7A–7D and S7) estimated how well ensembles of PF neurons represented the remembered and attended locations of the circle (Wessberg et al. 2000). We excluded control trials, in which the circle either did not move or moved 360°, from this analysis. The method measured the probability that the attended and remembered locations could be correctly estimated using a single trial of activity from a neuronal ensemble as a function of its size. The calculation started with a random selection of n neurons from a population. Then, for a given condition (e.g., a remembered location i of 0° and an attended location j of 90°), we selected one trial of that condition randomly from each neuron (test trials). All the other trials for that neuron contributed to a look-up table of firing rates. This look-up table consisted of a matrix of average firing rates <Fij> for remembered locations, i, and attended locations, j. The differences between firing rates in the look-up table and the rate on the selected trial were rank ordered, with a smaller rank signifying a closer match. We then summed the ranks rij across individual neurons and took the remembered and attended locations associated with the lowest combined rank as the population estimation. The estimated remembered location either agreed or disagreed with the actual remembered location of the selected trial, as did the estimated attended location in a separate computation. Repeating this procedure for a given number of neurons, n, more than 2,400 times—each time starting with a randomly selected set of test trials (more than 200 trials from each of the 12 conditions; four controls excluded)—yielded a percentage of correct estimations of the attended and remembered locations. We then calculated neuron-dropping curves for ensembles of size one to the total number of neurons, but typically the range 1–100 sufficed to capture the main features of the population estimation.
To assess the representation of attended and remembered locations during the delays (see Figure 7A–7D), we calculated neuron-dropping curves for the 800-ms period immediately preceding the onset of circle movement (gray curves in Figure 7A–7D) and the 800-ms period immediately preceding the trigger signal (colored curves). Finally, we evaluated the time course of changes in these estimations, using neuron-dropping curves for a 200-ms window, which moved in 50-ms steps along the trigger-aligned records (Figures 7E, 7F, and 8). The 200-ms window measured activity immediately before the time point plotted, to prevent the artifactual early appearance of a signal detection, and thus represents a “backward-looking” average.
Supporting Information
Figure S1 Rasters and Histograms from a Representative Attention Cell
The activity matrix is the same as in Figure 3A, measured in the 800 ms immediately prior to the trigger signal. This neuron is not the same as that illustrated in Figure 2. Beneath the activity matrix, the rasters and histograms for each attended and remembered location are displayed in the format of Figure 2A.
(103 KB PPT).
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Figure S2 Rasters and Histograms from a Representative Memory Cell
The activity matrix is the same as in Figure 3B, measured in the 800 ms prior to the trigger stimulus. Format as in Figure S1.
(95 KB PPT).
Click here for additional data file.
Figure S3 Rasters and Histograms from Two Representative Hybrid Cells
The activity matrix in (A) is the same as in Figure 3C, part a; the one in (B) is the same as in Figure 3C, part b. Format as in Figure S1.
(151 KB PPT).
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Figure S4 Activity Early Versus Late in the Delay Period
A table of tuning indexes is given at the top for each of the cell classes (plotted in the bottom part of the figure), combinations of those classes, and other groups of cells as described in the left column. These population averages are divided into two groups of columns, those on the left showing data for the period before the circle began rotating (early) and those on the right showing data for the period after it had stopped and the monkey awaited the trigger signal (late). In the plot, the dashed line shows the median values, the dotted line shows the upper IQR.
(56 KB PPT).
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Figure S5 Activity Early Versus Late in the Delay Period
Same PFdl neuron as in Figure 2. The activity matrix in (C) comes from the data in (A), and the matrix in (D) comes from the data in (B), in the format of Figure 2C. In (A), the red boxes enclose the measured period for the preferred location, 800 ms prior to the beginning of the circle's movement (200–1,000 ms after circle onset). In (D), the box shows the 800 ms immediately prior to the trigger stimulus. Note that the column-to-column variation in C necessarily results from chance variation because at that time the circle's final location is unknown. The figure shows, by example, that the spatial tuning in the period just before the triggering event strongly exceeds that before the circle begins moving, thus ruling out a strictly sensory account for spatial tuning (see also Figure S4). Note that after circle movement, responses to the circle were greater at the cell's preferred location (90°) but smaller at the least preferred location (270°).
(188 KB PPT).
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Figure S6 Activity Early Versus Late in the Delay Period
Same PFdl neuron as in Figure S1, in the format of Figure S5. The red boxes show the measured period for the cell's preferred location in both (A) and (B).
(156 KB PPT).
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Figure S7 Neuron-Dropping Curves for the Two Monkeys Combined
Format as in Figure 7A–7D.
(46 KB PPT).
Click here for additional data file.
This work was supported by the Division of Intramural Research of the National Institute of Mental Health. We thank Dr. Andrew R. Mitz for engineering support, Mr. Jim Fellows for assistance in behavioral training, and Mr. Alex Cummings for preparing the histological material.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. MAL and SPW conceived and designed the experiment. MAL, AM, and JDK performed the experiment. MAL, AM, JDK, and SPW analyzed the data. MAL, AM, JDK, and SPW wrote the paper.
Academic Editor: Wolfram Schultz, University of Cambridge
Current address: Center for Neuroengineering, Department of Neurobiology, Duke University Medical Center, Durham, North Carolina, United States of America
Citation: Lebedev MA, Messinger A, Kralik JD, Wise SP (2004) Representation of attended versus remembered locations in prefrontal cortex. PLoS Biol 2(11): e365.
Abbreviations
Att-trialattended-location trial
IAttattended-location index
IQRinterquartile range
IRemremembered-location index
PETHperi-event time histogram
PFprefrontal cortex
PFdldorsolateral prefrontal cortex
Rem-trialremembered-location trial
==== Refs
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| 15510225 | PMC524249 | CC0 | 2021-01-05 08:21:17 | no | PLoS Biol. 2004 Nov 26; 2(11):e365 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020365 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1551022610.1371/journal.pbio.0020366Research ArticleCell BiologyMolecular Biology/Structural BiologyMammalsUnanticipated Antigens: Translation Initiation at CUG with Leucine Cryptic Translation of Antigenic PeptidesSchwab Susan R
1
Shugart Jessica A
1
Horng Tiffany
1
Malarkannan Subramaniam
1
Shastri Nilabh nshastri@socrates.berkeley.edu
1
1Division of Immunology, Department of Molecular and Cell BiologyUniversity of California, Berkeley, CaliforniaUnited States of America11 2004 26 10 2004 26 10 2004 2 11 e36624 5 2004 24 8 2004 Copyright: © 2004 Schwab 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.
Where to Start? Alternate Protein Translation Mechanism Creates Unanticipated Antigens
Major histocompatibility class I molecules display tens of thousands of peptides on the cell surface for immune surveillance by T cells. The peptide repertoire represents virtually all cellular translation products, and can thus reveal a foreign presence inside the cell. These peptides are derived from not only conventional but also cryptic translational reading frames, including some without conventional AUG codons. To define the mechanism that generates these cryptic peptides, we used T cells as probes to analyze the peptides generated in transfected cells. We found that when CUG acts as an alternate initiation codon, it can be decoded as leucine rather than the expected methionine residue. The leucine start does not depend on an internal ribosome entry site–like mRNA structure, and its efficiency is enhanced by the Kozak nucleotide context. Furthermore, ribosomes scan 5′ to 3′ specifically for the CUG initiation codon in a eukaryotic translation initiation factor 2–independent manner. Because eukaryotic translation initiation factor 2 is frequently targeted to inhibit protein synthesis, this novel translation mechanism allows stressed cells to display antigenic peptides. This initiation mechanism could also be used at non-AUG initiation codons often found in viral transcripts as well as in a growing list of cellular genes.
Proteins have been identified for which a unique translational machinery makes use of unconventional start codons
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Introduction
Immune surveillance by cytotoxic T cells (CTLs) is a key mechanism for detecting and eliminating abnormal cells. These include cells infected with viruses or bacteria, and those that have suffered tumorigenic transformations (Townsend and Bodmer 1989). The antigen receptors of CTLs probe the repertoire of peptide/major histocompatibility complex (MHC) class I complexes on the target cell surface. Target cells display peptides derived from virtually all cellular translation products; the presence of foreign peptides, such as those derived from viral proteins, can trigger a T cell response. Each cell presents tens of thousands of distinct peptides as potential ligands for the CTL antigen receptor (Rammensee et al. 1993; Engelhard 1994). Most peptides are represented at fewer than ten copies per cell, and by some estimates only three copies of the antigenic peptide are sufficient for target cell lysis (Purbhoo et al. 2004). CTLs are thus a very sensitive probe for the peptides displayed by MHC class I.
The antigen-presenting cells (APCs), which include almost all nucleated cells, are also very efficient in generating peptides for display by MHC class I (Pamer and Cresswell 1998; Princiotta et al. 2003). In fact, they are so efficient that the complex mixture of peptides on the cell surface includes some peptides that should in theory never have been translated in the first place (Shastri et al. 2002). These peptides, referred to as “cryptic,” are derived from the 5′ and 3′ “untranslated” regions of the RNA or from alternate translational reading frames. Cryptic peptides have been identified as targets for CTLs specific for tumors as well as virus-infected cells (Mayrand and Green 1998; Cardinaud et al. 2004). Several studies have shown that these peptides can arise in tumor cells and cultured cell lines despite the absence of conventional AUG codons (Malarkannan et al. 1995a; Dolstra et al. 1999; Malarkannan et al. 1999; Ronsin et al. 1999). Recently, using a transgenic approach we demonstrated that such peptides can also be expressed in a variety of normal cells and can elicit CTL responses (Schwab et al. 2003). Remarkably, a distinct translation mechanism appeared to be responsible for their generation, because it was capable of decoding the CUG initiation codon as leucine rather than the expected methionine residue.
How APCs generate peptides using non-AUG codons remains obscure. It is believed that cells express only one class of initiator tRNA, RNAi
Met, which is specific for AUG and is always charged with the methionine residue (Peabody 1989; Rajbhandary and Chow 1995). 40S ribosomes are preloaded with RNAi
Met and other initiation factors even before they approach the mRNA to be translated. Initiation at non-AUG codons is therefore thought to be caused by “wobble” in the pairing of the non-AUG codon with the anticodon of the RNAi
Met (Peabody 1989). This mispairing results in incorporation of the methionine residue at the non-AUG initiation codon. How cells initiate translation with a nonmethionine residue is thus not explained by current translational theory. It is nevertheless important to understand this mechanism not only because antigenic peptides can arise from non-AUG initiated translation, but also because expression of a growing number of genes appears to be mediated by translation initiated at non-AUG codons.
In this study, we used T cells as probes to analyze the translation mechanism that allows the generation of CUG-initiated antigenic peptides and decodes CUG as the leucine rather than the methionine residue. We found some similarities, but also key differences, between the translation mechanisms mediating initiation at conventional AUG versus CUG codons.
Results/Discussion
Decoding of the CUG Initiation Codon as Leucine Does Not Depend upon the mRNA Sequence
We had previously shown both in transfected cell lines and in a transgenic mouse model that CUG can be decoded as leucine when it serves as the initiation codon for the (CTG)-TFNYRNL peptide (the initiation codon is in parentheses and the remaining amino acids are in single-letter code) (Malarkannan et al. 1999; Schwab et al. 2003). Although there are numerous examples of non-AUG initiation codons, this is to our knowledge the only known instance in which the identity of the first residue was investigated and found not to be methionine, with the exception of initiation directed by cricket paralysis virus-like internal ribosome entry sites (CPV-IRES). Normally the RNAi
Met occupies the P site of the ribosome, where translation initiation begins. In contrast, the CPV-IRES binds the ribosome and positions it precisely so that initiation begins in the A site, without requiring RNAi
Met (Jan and Sarnow 2002). In the cricket paralysis virus, initiation begins with alanine encoded by GCU, and in the Plautia stali intestine virus initiation begins with glutamine encoded by CAA (Sasaki and Nakashima 2000; Wilson et al. 2000). Because there was no obvious IRES-like sequence in the transgene we had used, and non-CUG leucine codons failed to direct efficient translation, we suspected that a different mechanism might account for initiation at the CUG codon (Schwab et al. 2003). Therefore we first asked whether the leucine start was dependent upon the mRNA sequence.
To address this question, we identified the first amino acid of CUG-initiated peptides that were presented by MHC class I molecules and thus detectable by appropriate T cells. In this assay, we cotransfected cells with cDNA constructs encoding the peptide as well as the MHC molecule that binds and presents the peptide on the cell surface. Binding to the MHC protects the initiation residue from being removed by cellular proteases, which can trim antigenic peptides in the cytoplasm or the endoplasmic reticulum (Kloetzel 2004; Rock et al. 2004). We then extracted the peptides translated in the cells and separated them by reverse-phase high performance liquid chromatography (RP-HPLC), using conditions in which the methionine-initiated peptide elutes at a different time from the leucine-initiated peptide. Finally, we assayed the HPLC fractions for the presence of the peptide. We added to each fraction a T cell hybridoma that cross-reacts with the methionine and the leucine-initiated forms of the peptide, as well as appropriate APCs that will display the peptide on their MHC molecules. We measured the T cell response to each fraction. By comparing the retention time of the T cell-stimulating fractions from the cell extract with the retention time of synthetic peptides, we can determine the identity of the peptide made by the cells. This assay has several advantages over conventional assays used to detect initiating amino acids: MHC molecules protect the first amino acid from cleavage, T cells can detect nonmethionine residues with high sensitivity, and we can analyze the products of translation initiation in vivo.
To determine if decoding of the CUG initiation codon as leucine was influenced by 5′ or 3′ untranslated regions (UTRs) of the mRNA, we transfected COS-7 cells with cDNA encoding the Kb MHC molecule and the *(CTG)-TFNYRNL* peptide ([CTG]YL8). We refer to this as the xYL8 model. We placed the peptide in three different contexts: first, in the pcDNA1 vector; second, upstream of the IRES in the pIRES2-eGFP vector; and, finally, in the 5′ UTR of green fluorescent protein (GFP) in the pcDNA1 vector. The peptides translated in the transfected cells were extracted and fractionated by HPLC. Each fraction was tested for the presence of the leucine-initiated LTFNYRNL (LYL8) peptide and the methionine-initiated MTFNYRNL (MYL8) peptide using BCZ103 T cells and Kb-expressing L cells (a fibroblast cell line) as APCs. With each construct we found a single peak of antigenic activity that eluted in the same fraction as the synthetic LYL8 peptide (Figure 1A–1C). In contrast, when the cells were transfected with a construct encoding the ATG-initiated peptide ([ATG]-TFNYRNL), the single peak of antigenic activity eluted in fractions identical to those containing the synthetic MYL8 peptide (Figure 1A and 1D). This result rules out the possibility that the apparent use of leucine was due to post-translational modification of the MYL8 peptide, which caused it to coelute with the LYL8 peptide. We conclude that the cells were capable of decoding the initiating CTG codon as leucine regardless of the 5′ or 3′ sequences flanking the LYL8 coding sequence.
Figure 1 The CUG Initiation Codon Is Decoded as Leucine Independent of RNA Sequence
(A) The indicated synthetic peptides mixed with extracts from untransfected COS-7 cells were separated by RP-HPLC. Each fraction was tested for BCZ103 T cell-stimulating activity with Kb+B7.2+ L cells as APCs. After overnight incubation, the β-galactosidase induced in activated T cells was measured using the substrate chlorophenol red-β-pyranoside, which yields a colored product with absorbance at 595 nm. The arrows indicate the reproducible peak elution times for the MYL8 and the LYL8 peptides. Injections of buffer alone (Buffer) were carried out under identical conditions, and the fractions were assayed in parallel to ensure absence of cross-contamination between runs.
(B–D) Extracts from COS-7 cells transfected with cDNA encoding Kb and the indicated constructs were separated by RP-HPLC. Fractions were tested for BCZ103 T cell-stimulating activity as in (A).
(E) The indicated synthetic peptides mixed with extracts from untransfected COS-7 cells were separated by RP-HPLC. Each fraction was tested for the specific DBFZ T cell-stimulating activity with Db+B7.2+ L cells as APCs as in (A). The arrows indicate the reproducible peak elution times for the MM9 and the LM9 peptides.
(F and G) Extracts from COS-7 cells transfected with cDNA encoding Db and the indicated constructs were separated by RP-HPLC. Fractions were tested for DBFZ T cell-stimulating activity as in (E).
(H) A range of concentrations of the indicated synthetic peptides was tested for BCZ103 T cell-stimulating activity with Kb+B7.2+ L cells as APCs.
(I) A range of concentrations of the indicated synthetic peptides was tested for DBFZ T cell-stimulating activity with Db+B7.2+ L cells as APCs.
We next tested whether the LYL8 coding sequence itself enabled the leucine start. We examined the initiating amino acid used for a different peptide presented by the Db MHC class I molecule that satisfied the conditions required for our assay: that an MHC molecule present the peptide, that HPLC allow distinction between the leucine- and methionine-initiated forms, and that a T cell cross-react with the peptides with leucine or methionine residues at the first position. When COS-7 cells were transfected with cDNA constructs encoding the Db MHC molecule and the *(CTG)-SNEN-METM peptide derived from the influenza nucleoprotein, only the leucine-initiated LM9 peptide was detected in the HPLC-fractionated cell extracts (Figure 1E and 1F). We again assessed whether the apparent use of leucine could be due to post-translational modification of the methionine-initiated peptide. We transfected cells with a construct containing the ATG initiation codon in place of the CTG codon. Analysis of cell extracts after HPLC fractionation now revealed a single peak of antigenic activity that eluted in the same fractions as the synthetic MM9 peptide (Figure 1E and 1G). Similar results were also obtained with the (CTG)-SHL8 peptide that was presented by the Db MHC class I molecule (Malarkannan et al. 1995b) (unpublished data). We conclude that the peptide sequence itself was irrelevant to the decoding of the CTG initiation codon as leucine.
At present it is difficult to quantify the fraction of the total translated material that is initiated with leucine, because the different peptides may have different stabilities in the cell. Furthermore, the T cell hybridomas could respond to the methionine- and leucine-initiated peptides with differing sensitivities. Indeed, the BCZ103 T cell hybridoma responds to LYL8 approximately 30-fold better than to MYL8 (Figure 1H). In contrast, the DBFZ T cell hybridoma recognizes its leucine- or methionine-initiated cognate peptides with comparable sensitivity (Figure 1I). Nonetheless, translational initiation with the leucine residue is readily detected.
In previous studies, we explored the possibility that leucine was used as the first amino acid because the ribosome may have begun at an upstream alternate initiation codon (there are no upstream ATGs in these constructs) and read through the stop codon before the CTG initiation codon in the LYL8 coding sequence. We showed that increasing the number of stop codons upstream of CTG from one to six had no effect on LYL8 expression, and that substituting the CTG codon with other leucine-encoding triplets essentially ablated peptide expression (Malarkannan et al. 1999; Schwab et al. 2003). We assessed the possibility of translational read-through in the different model systems used here. If read-through were responsible for LYL8 expression, one would predict that expression of the downstream LYL8 would be proportional to expression of the upstream sequence. To test this hypothesis, we made DNA constructs in which the LYL8 coding sequence was placed directly after the stop codon terminating translation of another peptide, SSVVGVWYL (SVL9) (Mendoza et al. 1997). We then placed the [SVL9*LYL8] cassette in-frame (R0) with and out-of-frame (R1) with an ATG initiation codon (Figure 2A). These constructs were transfected into cells along with the appropriate MHC molecules, and peptide expression was assayed with the 30NX/B10Z T cell hybridoma specific for the SVL9/Db complex (Figure 2B) and the BCZ103 T cell hybridoma specific for the LYL8/Kb complex (Figure 2C). T cells were added directly to the transfected cells without an intervening extraction step. Cells expressing the R0 cassette were highly active as APCs. Shifting the cassette out-of-frame with the initiating ATG in the R1 construct dramatically reduced expression of the SVL9 peptide. Remarkably, the cells transfected with either the R0 or the R1 constructs were equivalent in their ability to stimulate the LYL8-specific T cells (Figure 2C). To confirm that the CTG initiation codon was decoded as leucine, we analyzed HPLC fractionated cell extracts (Figure 2D). Again, a single peak of activity was found in the fractions that matched the leucine-initiated LYL8 synthetic peptide. Thus, translation of the LYL8 peptide was independent of upstream conventional translation initiation events, and translational read-through events were not detected.
Figure 2 Expression of the Cryptic LYL8 Peptide Is Independent of the Efficiency of Upstream Translation Initiation Events
(A) The nucleotide sequences of R0 and R1 constructs encode the SVL9 peptide followed by a termination codon and the LYL8 peptide. In the R0 construct, the SVL9 peptide is in frame with an ATG initiation codon. In the R1 construct, a single nucleotide is inserted after the ATG codon and causes the SVL9*LYL8 coding sequence to be out-of-frame with the ATG. The in-frame translation products are underlined and arrows indicate the potential initiation codons.
(B and C) The R0 and R1 constructs were transfected into Lmtk– cells along with the appropriate MHC molecule. They were tested for SVL9/Db expression using the 30NX/B10Z hybridoma (B) and LYL8/Kb expression using the BCZ103 T cell hybridoma (C).
(D) Extracts from COS-7 cells transfected with cDNA encoding Kb and the indicated constructs were separated by RP-HPLC. Fractions were tested for BCZ103 T cell stimulating activity as in Figure 1.
We also considered the possibility that leucine was used as the first amino acid because of an RNA modification that introduced an AUG immediately upstream of the peptide-coding sequence. However, the experiments below show that the 5′ UTR influences the leucine start because it is affected by the Kozak context, by the presence of an upstream hairpin, and by the presence of upstream initiation codons. Together, these findings demonstrate that the mRNA remained intact.
The Kozak Context Affects the Efficiency of Initiation at CUG
The efficiency of initiation at a given AUG codon depends on the identity of the surrounding nucleotides. These nucleotides, commonly referred to as the “Kozak context,” have a substantial influence on protein synthesis. Kozak found that
GCCACCAUG
G is optimal, and that the nucleotides at positions –3 and +4 are the most influential, while the nucleotide at the –6 position exerts a smaller effect. Changing these nucleotides can change protein expression by 20-fold (Kozak 1987a, 1987b). To determine whether the leucine start was affected by the nucleotides surrounding the CUG initiation codon, and to allow better prediction of probable CUG initiation codons, we varied the nucleotides at positions –6, –3, and +4 relative to the CUG codon.
We inserted synthetic oligonucleotides *(
NCCNCCCTG
NCC)SEL8* into the pcDNAI vector, where N represents the degenerate nucleotides flanking the CTG initiation codon for the SLVELTSL (SEL8) peptide presented by the Kb MHC molecule to bm1BZ19.4 T cells (Malarkannan et al. 1996). We transfected COS-7 cells with plasmid DNA from 96 individual randomly picked bacterial colonies together with the cDNA for Kb. When the transfected cells were tested for their ability to stimulate bm1BZ19.4 T cells, we noticed a substantial variation in the T cell response, suggesting that the plasmids differed in their ability to express the SEL8 peptide (Figure 3A). As a negative control, none of the cells transfected with each of the 96 plasmid DNAs encoding the minigene *(
NCCNCCCCC
NCC)SEL8* stimulated the T cells, demonstrating that initiation activity was restricted to the CTG codon (Figure 3B). To identify which nucleotides were associated with the variation in peptide expression, we determined the nucleotide sequences of three sets of 18 CUG-initiated constructs that yielded high, intermediate, or low T cell responses (Figure 3C). As summarized in the panels in Figure 3D, among the plasmids that yielded high responses, 70% had T at position –6, 75% had A at position –3, and 80% had G at +4. Conversely, among the plasmids that yielded low responses, these nucleotides were infrequent. Thus, the optimal context for the CUG mediated initiation is
TCCACCCUG
G, which is in close agreement with Kozak's consensus sequence (
GCCACCAUG
G) for the AUG start and extends earlier findings that showed that an A at +5 and U at +6 can also enhance initiation at the CUG codon (Boeck and Kolakofsky 1994; Grunert and Jackson 1994). Furthermore, the fact that CUG initiation activity was influenced by the Kozak context provides additional evidence that the CUG codon was decoded during translation initiation rather than translation elongation.
Figure 3 The Optimal Nucleotide Context for the CUG Initiation Codon
(A and B) The indicated degenerate oligonucleotides were cloned into the pcDNA1 vector. “N” represents any one of T, A, C, and G nucleotides. The CTG or CCC initiation codons are boxed and the peptide coding sequence is indicated by [SEL8]. 96 randomly picked plasmids for the CTG-initiated peptide and an equal number for the CCC-initiated peptide were purified. The plasmids were transfected into COS-7 cells along with the Kb MHC class I molecule, and the T cell response was measured. Each bar represents the T cell response to cells transfected with an individual plasmid.
(C) Three sets of 18 representative plasmids, each yielding high, intermediate, and low responses (as shown) were selected for nucleotide sequencing.
(D) Summary of the nucleotide sequences of plasmids yielding high, intermediate, and low responses. The left, middle, and right panels, respectively, correspond to the plasmids shown in (C). Each panel shows the percent of each nucleotide found at the –6, –3, and +4 degenerate positions indicated by the “N” in A. For example, the upper left square shows that, of the high T cell-stimulating plasmids, the –6 position was T for 67%, A for 6.7%, C for 20%, G for 6.7%, a pyrimidine (T or C) for 87%, and a purine (A or G) for 13%.
An Excellent Kozak Context Enhances Both the CUG/Leucine and the CUG/Methionine Starts
In the above model, because the initiation codon was not included within the final SEL8 antigenic peptide product protected by the MHC molecule, the identity of the amino acid residue specified by the CUG initiation codon could not be determined. Thus, we could not distinguish whether the Kozak context affected the leucine start, the methionine start, or both. To resolve this question, we turned to the (CTG)YL8 model, in which the predominant T cell-stimulating activity is the leucine-initiated LYL8 peptide (see Figure 1A–1C). At the –6 and –3 positions, we placed the best (T, A) and the worst (G, T) nucleotides. We were unable to vary the +4 position from the original A, because that would alter the peptide's second amino acid and likely affect its detectability by the BCZ103 T cell hybridoma.
We first transfected cells with the two constructs as well as the appropriate Kb MHC cDNA. After 2 d the transfected cells were assayed for their ability to stimulate the BCZ103 T cell. Cells expressing the LYL8 peptide with its CTG initiation codon in the “Excellent Kozak” context (T at –6, A at –3) were superior to those with the CTG codon in a “Poor Kozak” context (G at –6, T at –3) in stimulating the T cell response (Figure 4A). Next, we extracted peptides from the cells expressing the two constructs and analyzed the antigenic activities after HPLC fractionation. Again, a single peak of activity corresponding to the leucine start was detected in the extract of cells expressing the “Poor Kozak” construct (Figure 4B). In contrast, in the extract from cells expressing the “Excellent Kozak” construct not only was the total amount of the LYL8 peptide higher, but a new activity peak corresponding to the methionine-initiated MYL8 peptide was also clearly detected. By comparing the T cell response to the cell extracts with the response to known quantities of synthetic peptides, we determined that the construct with the CTG initiation codon in an “Excellent Kozak” context yielded approximately 6-fold more LYL8 peptide than the construct with CTG in a poor context. The amount of MYL8 peptide increased as well, but the change cannot be quantified, because MYL8 was undetectable in extracts of cells transfected with the construct containing the CTG initiation codon in the “Poor Kozak” context (Figure 4B). We conclude that the Kozak context enhanced not only the overall efficiency of the CTG/leucine start, but also the ability of the CTG codon to be decoded in the conventional “wobble” mode as the methionine residue.
Figure 4 The Kozak Context Enhances the Leucine as well as the “Wobble” Methionine Start
(A) Lmtk– cells were transfected with Kb cDNA and the indicated “Excellent” and “Poor” constructs encoding the (CTG)YL8 peptide. They were tested for LYL8/Kb expression using the BCZ103 T cell hybridoma.
(B) Extracts from COS-7 cells transfected with cDNA encoding Kb and the indicated constructs were separated by RP-HPLC. Fractions were tested for BCZ103 T cell-stimulating activity with Kb+B7.2+ L cells as APCs. The arrows indicate the peak elution positions for the MYL8 and the LYL8 peptides. T cell responses to fractions collected after injecting sample buffer alone (Buffer) are also shown to indicate absence of cross-contamination between runs.
Ribosomes Scan 5′ to 3′ for the CUG Initiation Codon
In most cases, ribosomes bind mRNA at the 5′ cap and scan in the 3′ direction for the first AUG in an appropriate Kozak context. Thus, for approximately 90% of mRNA transcripts, the 5′-most AUG initiates protein synthesis (Kozak 1991). In order to develop predictive algorithms for the CUG initiation codon, we asked whether ribosomes similarly scanned for the CUG/leucine start. We took advantage of the fact that a heat-stable hairpin in the mRNA blocks 40S ribosomal scanning (Kozak 1986, 1989a). We designed a hairpin based on the one Kozak used to trap scanning 40S ribosomes (Kozak 1989b). It extends Kozak's original sequence in order to maintain stability at 37 °C, and includes a bulge to prevent the longer hairpin from targeting the mRNA as a potential substrate for RNA interference. We placed the hairpin 42 nucleotides upstream of the initiation codon. To control for nonspecific effects, such as RNA stability, we also included GFP under the control of an IRES element downstream of the peptide-coding sequence.
We first transfected COS-7 cells with constructs encoding the ATG-initiated MYL8 peptide and another encoding MYL8 downstream of the heat-stable hairpin. We titrated the transfected cells and assayed the T cell response to the peptides presented on the cell surface. As expected, the presence of the hairpin inhibited MYL8 expression (Figure 5A). This effect was not due to the hairpin destabilizing the mRNA, because GFP expression as measured by flow cytometry of the same cells was not decreased by the presence of the hairpin (Figure 5B). Next, we performed the same experiment with COS-7 cells transfected with the CTG-initiated peptide with and without an upstream hairpin sequence and found that the hairpin inhibited translation of LYL8 as well (Figure 5C). Again, the level of GFP expression was similar in the cells transfected with constructs with or without the hairpin (Figure 5D). Similar inhibition of both ATG- and CTG-initiated translation was also observed with a second set of constructs in which the hairpin was placed 68 nucleotides upstream of the initiation codon, making it less likely that the hairpin interfered with a potential IRES-like ribosomal landing pad (unpublished data). Both conventional, ATG-mediated and cryptic, CTG-mediated translation events were disrupted by upstream hairpins, suggesting that both require ribosomal scanning in the 5′-to-3′ direction.
Figure 5 The CUG Start Is Blocked by a Heat-Stable Hairpin in the 5′ UTR
COS-7 cells were transfected with cDNA encoding Kb and the indicated constructs. (A and C) The cells were titrated and peptide expression was tested with BCZ103 T cells. (B and D) GFP expression in the transfected cells was assayed by fluorescence-activated cell sorting. GFP fluorescence (shaded histograms) is not observed in untransfected cells (or in cells transfected with a vector not encoding GFP [unpublished data]).
A Set of Ribosomes Is Scanning Specifically for the CUG/Leucine Start
We next asked whether ribosomes responsible for the CUG/leucine start were scanning specifically for CUG initiation codons, or whether they were able to start at conventional AUG initiation codons as well. To address this question, we placed “decoy” ATG and CTG codons upstream of and out of frame with the CTG codon initiating expression of the peptide, and asked whether their presence affected peptide translation.
As a positive control, we transfected cells with a construct encoding the ATG-initiated MYL8 and another encoding the same MYL8 peptide but with three ATGs upstream of and out of frame with the peptide (ATG)3ATG. The control constructs had CAGs instead of ATGs, because the CAG codon does not possess initiation activity. As expected, the presence of upstream out-of-frame ATGs dramatically reduced ATG-initiated MYL8 peptide expression. The reduction in MYL8 peptide was seen both when the transfected cells were used directly to stimulate T cells and when peptides from the transfected cells were extracted, separated by HPLC, and then assayed with T cells (Figure 6A and 6B). This result is in complete agreement with the scanning model of translation initiation. The marked reduction in peptide expression occurs because ribosomes initiate translation at the first AUG and traverse the downstream peptide-coding region in the wrong reading frame; the ribosomes that missed the first AUG would start at the second or the third AUG and also traverse the peptide coding region in the wrong reading frames (Bullock and Eisenlohr 1996; Bullock et al. 1997).
Figure 6 Ribosomes Are Scanning Specifically for the CUG/Leucine Start
(A, C, and E) Lmtk– cells were transfected with the indicated constructs and Kb cDNA. After 2 d they were tested for MYL8/Kb or LYL8/Kb expression using the BCZ103 T cell hybridoma. Error bars represent the standard deviation of three replicate wells. (ATG)3ATG (solid circles, A) denotes the ATG-initiated peptide preceded by three ATGs upstream of and out of frame with the peptide; (CAG)3ATG (open circles, A) is the identical DNA construct but the upstream ATGs were replaced with CAG. (ATG)3CTG (solid circles, C) denotes the CTG-initiated peptide preceded by three ATGs upstream of and out of frame with the peptide; (CAG)3CTG (open circles, C) is the identical DNA construct but the upstream ATGs were replaced with CAG. (CTG)3CTG (solid circles, E) denotes the CTG-initiated peptide preceded by three CTGs upstream of and out of frame with the peptide; (CAG)3CTG (open circles, E) is the identical DNA construct but the upstream CTGs were replaced with CAG.
(B, D, and F) Extracts from COS-7 cells transfected with cDNA encoding Kb and the indicated constructs were separated by RP-HPLC. Fractions were tested for BCZ103 T cell-stimulating activity with Kb+B7.2+ L cells as APCs. Arrows indicate the peak elution positions of the MYL8 and the LYL8 peptides. Points on graphs correspond to those in (A), (C), and (E).
We then transfected cells with a construct encoding (CTG)YL8 and another encoding (CTG)YL8 with three ATGs upstream of and out of frame with the peptide (ATG)3CTG. When the transfected cells were used directly to stimulate T cells, the upstream ATGs had little effect (Figure 6C). However, HPLC analysis of the peptides produced in transfected cells revealed that the upstream ATGs virtually abolished expression of the MYL8 peptide, whereas LYL8 expression was not affected (Figure 6D). Thus, upstream out-of-frame ATG initiation codons inhibited the conventional “wobble” CUG/methionine start, but not the CUG/leucine start.
Finally, we transfected COS-7 cells with constructs encoding (CTG)YL8 with three CTGs upstream of and out of frame with the peptide (CTG)3CTG. When the transfected cells were used directly to stimulate T cells, we saw a small but consistent inhibition (Figure 6E). Remarkably, HPLC analysis of the transfected cell extracts showed that only LYL8 expression was decreased without any change in the expression of the MYL8 peptide (Figure 6F). The observation that upstream ATGs inhibit the wobble start but not the leucine start, and that upstream CTGs inhibit the leucine start but not the wobble start, suggests that a separate set of ribosomes is scanning for the CUG/leucine start, distinct from the ribosomes used for the methionine start.
Note, however, that the upstream CUGs, despite an “Excellent Kozak” context, inhibited the leucine start weakly. This effect contrasts with the inhibition caused by the upstream AUGs on the AUG/methionine or the CUG/methionine starts and suggests that other features are required for an efficient CUG/leucine start. Interestingly, one form of the ASCT2 amino acid transporter is initiated with multiple CUG and GUG codons in close proximity (Tailor et al. 2001). This redundancy may be required if any given non-AUG codon is used inefficiently. Furthermore, many mRNAs with CUG starts have GC-rich regions immediately downstream from the initiation codon and have been hypothesized to form hairpins that cause the ribosome to pause long enough to recognize the CUG codon (Kozak 1990).
The Leucine Start Is Enhanced in the Presence of Phosphorylated Eukaryotic Translation Initiation Factor 2α
Finally, we were interested to know whether the leucine start requires eukaryotic translation initiation factor 2 (eIF2), which is responsible for loading the RNAi
Met onto the 40S ribosome. Cells target eIF2 by phosphorylating its α subunit (eIF2α) to inhibit protein synthesis in response to a number of stress signals, including viral infection, starvation, and the accumulation of unfolded proteins. Ribosomes release eIF2-guanosine diphosphate (GDP) after the AUG initiation codon is reached, and GDP is exchanged for guanosine triphosphate (GTP) with the assistance of another protein, eIF2B, before eIF2 can be used for another round of translation initiation. When eIF2α is phosphorylated, it binds eIF2B with unusually high affinity and thus prevents subsequent nucleotide exchange. Because eIF2B is limiting in the cell, phosphorylation of only a fraction of eIF2α can substantially inhibit translation globally (Hershey and Merrick 2000).
To approach this question, we transfected HeLa cells with (CTG)YL8 or (ATG)YL8 constructs. We then assayed peptide expression in cells that had or had not been treated to induce phosphorylation of eIF2α. It was a challenge to induce phosphorylation of eIF2α for long enough to see an effect on peptide expression without causing substantial toxicity. Furthermore, we could not disrupt peptide/MHC assembly in the endoplasmic reticulum, a requirement that ruled out standard reagents such as dithiothreitol, thapsigargin, and tunicamycin. We also did not want to inhibit peptide elongation, which ruled out amino acid starvation.
The optimal treatment for our purposes was sodium arsenite (NaAs). Arsenite reacts with sulfhydryl groups and causes phosphorylation of eIF2α presumably by inducing an unfolded protein response, although the precise mechanism remains unknown (Brostrom and Brostrom 1998). We transfected HeLa cells with DNA encoding the CTG and ATG-initiated peptides. After 12 h, we treated the cells with 50 μM NaAs for 4 h before assaying them for expression of eIF2α and peptides. Western blot analysis confirmed that the amount of phosphorylated eIF2α in NaAs-treated cells was enhanced (Figure 7A). As a control, the amount of tubulin in the cells remained unchanged.
Figure 7 The Leucine Start Is Enhanced in the Presence of Phosphorylated eIF2α
HeLa cells transfected with cDNA encoding Kb together with cDNA encoding either the ATG- or CTG- initiated peptides were treated for 4 h with 50 μM NaAs, with brefeldin A (BfA), or left untreated (UT).
(A) Transfected cells treated with NaAs or without (UT) were lysed and tested for phosphorylation of eIF2α by Western blot and for tubulin as a loading control.
(B) The transfected cells were titrated and tested for their ability to stimulate BCZ103 T cells.
We assayed the HeLa cells for peptide expression using the BCZ103 T cell hybridoma (Figure 7B). We found that expression of the ATG-initiated MYL8 peptide was reduced by NaAs, as expected. The reduction was dramatic because the effect of NaAs was equivalent to the effect of brefeldin A, which stops protein transport from the endoplasmic reticulum to the Golgi and thus prevents any new peptides from trafficking to the cell surface. Surprisingly, expression of the CTG-initiated LYL8 peptide increased upon NaAs treatment, although it too was inhibited by brefeldin A treatment. This result was consistent in six independent experiments. The difference in ATG versus CTG initiation is not likely due to a unique effect of NaAs that somehow stabilizes LYL8 and not MYL8, because an alternative method of inducing phosphorylation of eIF2α using β-interferon and polyIC (Savinova and Jagus 1997; Kaufman 2000), gave similar reproducible results (unpublished data). We conclude that, in contrast to initiation at conventional AUG codons, initiation at the CUG/leucine codon was eIF2α-independent.
The effect of eIF2α phosphorylation on the leucine start strikingly mirrors the effect of eIF2α phosphorylation on proteins whose synthesis is directed by the CPV-IRES, which does not require eIF2 (Wilson et al. 2000). Intriguingly, eIF2-independence of the CUG start is consistent with the observation of Donahue et al. (1988) that mutations in a Zn(II) finger domain of eIF2β permit initiation at a UUG codon. The data implicates the nucleic acid-binding function of eIF2β in start-site selection (Donahue et al. 1988; Huang et al. 1997). Identification of the factors required for the CUG start will illuminate not only leucine initiation, but also the role of these components in the methionine start.
The CPV-IRESs are to date the only known sequences that allow eIF2-independent initiation in eukaryotic cells. Viruses employ a host of creative strategies to prevent phosphorylation of eIF2α (Kaufman 2000). Initiation at non-AUG codons, which is relatively common in viral transcripts, may provide a way to continue translation despite the lack of eIF2. Similarly, despite general translational inhibition during viral infection, cells need to continue generating antigenic peptides to flag down T cells. In addition to viral proteins and antigenic peptides, a number of regulatory cellular proteins have non-AUG initiation codons. For example, c-Myc has two distinct isoforms, the longer of which is initiated with CUG and may inhibit proliferation, as it is absent in a number of tumor-derived cell lines. Intriguingly, synthesis of the CUG-initiated form increases when cells reach high density, specifically when methionine is limiting (Hann et al. 1988; Hann et al. 1992). It should be interesting to test whether this and other CUG-initiated proteins have a leucine start. In addition, whether other non-AUG initiation codons such as GUG or ACG are decoded in a manner similar to the CUG codon described here remains to be determined.
In summary, we found that when CUG acts as an alternate initiation codon, it can be decoded as leucine as well as methionine. The leucine start does not depend on mRNA structure or sequence, but its efficiency can be enhanced by the Kozak context. A set of ribosomes is scanning 5′ to 3′ specifically for the CUG initiation codon. While the methionine start is inhibited when cells are treated with NaAs, the leucine start is enhanced, suggesting that leucine initiation is independent of eIF2. This novel translation initiation mechanism provides cells not only antigenic peptides but also a potential tool for translational control.
Materials and Methods
Cell lines
Lmtk–, COS-7, Kb+B7.2+ L, Db+B7.2+ L, BCZ103, 30NX/B10Z, and DBFZ cells have been described (Mendoza et al. 1997; Malarkannan et al. 1999). Cell lines were maintained at 37 °C with 5% CO2 in RPMI 1640 with 10% fetal bovine serum, 1 mM sodium pyruvate, 50 μM β-mercaptoethanol, 0.3 mg/ml glutamine, 100 U/ml penicillin, and 100 μg/ml streptomycin (normal medium). HeLa cells were obtained from ATCC (#CCL-2; Manassas, Virginia, United States), and cultured in Eagle's minimal essential medium modified with Earle's balanced salt solution, nonessential amino acids, 2 mM L-glutamine, 1 mM sodium pyruvate, 1500 mg/l sodium bicarbonate (ATCC #30–2003), 10% fetal bovine serum, and 10 μg/ml ciprofloxacin.
Plasmid construct sequences
Sequences for constructs depicted in Figure 1 are as follows. CTG-YL8 in the BstXI/XbaI sites of the pcDNA1 vector (Invitrogen, Carlsbad, California, United States),
5′-TGTGTAGCTGACCTTCAACTACCGGAATCTATAGCTAG-3′; CTG-YL8 in the EcoRI/BamHI sites of the pIRES2-eGFP vector (Clontech, Palo Alto, California, United States),
5′-AATTAGACGAAGGTCTAGCTGACCTTCAACTACCGTAACCTGTAGATC-3′; CTG-YL8 in the HindIII/BamHI sites of the pcDNA1 vector with GFP in the EcoRI site,
5′-AGCTAGCTGACCTTCAACTACCGGAATCTATAGATCGATC-3′; ATG-YL8 in the EcoRI/BamHI sites of the pIRES2-eGFP vector,
5′-AATTAGACGAAGGTCTAGATGACCTTCAACTACCGTAACCTGTAGATC-3′; CTG-M9 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGCTGAGCAACGAGAACATGGAGACCATGTAGTGCACTAG-3′; and ATG-M9 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGATGAGCAACGAGAACATGGAGACCATGTAGTGCACTAG-3′.
Sequences for constructs depicted in Figure 2 are as follows. R0 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGATGAGCAGCGTCGTCGGCGTTTGGTACCTCTAGCTGACCTTCAACTACCGGAATCTCTAG-3′; and R1 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGATGGAGCAGCGTCGTCGGCGTTTGGNACCTCTAGCTGACCTTCAACTACCGGAATCTCTAG-3′.
Sequences for constructs depicted in Figure 3 are as follows. CTG-initiated peptide in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGNCCNCCCTGNCCAGTGTTGTTGAATTCTCCAGCCTCTAG-3′; and CCC-initiated peptide in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGNCCNCCCCCNCCAGTGTTGTTGAATTCTCCAGCCTCTAG-3′.
Sequences for constructs depicted in Figure 4 are as follows. “Excellent Kozak” CTG-YL8 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGTCGACCCTGACCTTCAACTACCGGAATCTCTAG-3′; and “Poor Kozak” CTG-YL8 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGGCGTCCCTGACCTTCAACTACCGGAATCTCTAG-3′.
Sequences for constructs depicted in Figure 5 are as follows. CTG-YL8 or ATG-YL8 in the pIRES2-eGFP vector, as in Figure 1 hairpin CTG-YL8 or ATG-YL8 in the pIRES2-eGFP vector (sequence from 5′ cap to start of peptide, whose sequence is as in Figure 1):
5′-GCTAGCGCTACCGGACTCAGATCGTGTCCGGATTTGGGGCGCGTGGTGGCGGCTTTTCGCGCGCGCGACGCGTCGCGCGCGCGTTTTGCCGCCACCACGCGCCCCTTTAGTACTTGAGCTCAAGCTTCGAATTAGACGAAGGTCTAG-3′.
Sequences for constructs depicted in Figure 6A and 6B are as follows. CAG3ATG-YL8 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGAACCCAGGGTCGACCCAGGACCCAGGTAGTCGACCATGACCTTCAACTACCGGAATCTCTAG-3′; and ATG3ATG-YL8 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGAACCATGGGTCGACCATGGACCATGGTAGTCGACCATGACCTTCAACTACCGGAATCTCTAG-3′.
Sequences for constructs depicted in Figure 6C and 6D are as follows. CAG3CTG-YL8 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGAACCCAGGGTCGACCCAGGACCCAGGTAGTCGACCCTGACCTTCAACTACCGGAATCTCTAG-3′; and ATG3CTG-YL8 in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGAACCATGGGTCGACCATGCACCATGGTAGTCGACCCTGACCTTCAACTACCGGAATCTCTAG-3′.
Sequences for constructs depicted in Figure 6E are as follows. CAG3CTG-YL8 in the HindIII/XbaI sites of the pcDNA1 vector mutated to alter the two CTGs in the 5′ UTR to CAG,
5′-AGCTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTTAGAAACTGACCTTCAACTACCGGAATCTCTAG-3′; and CTG3CTG-YL8 in the HindIII/XbaI sites of the pcDNA1 vector mutated to alter the two CTGs in the 5′ UTR to CAG,
5′-AGCTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACTGGATTACAAACTGGATTACAAACTGGATTTAGAAACTGACCTTCAACTACCGGAATCTCTAG-3′
Sequences for constructs depicted in Figure 6F are as follows. CAG3CTG-YL8 in the HindIII/XbaI sites of the pcDNA1 vector,
5′-AGCTACAAACAGGNTTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTTAGAAACTGACCTTCAACTACCGGAATCTCTAG-3′; and CTG3CTG-YL8 in the HindIII/XbaI sites of the pcDNA1 vector,
5′-AGCTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACAGGATTACAAACTGGATTACAAACTGGATTACAAACTGGATTTAGAAACTGACCTTCAACTACCGGAATCTCTAG-3′.
Sequences for constructs depicted in Figure 7 are as follows. CTG-YL8 in the in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGTAGCTGACCTTCAACTACCGGAATCTGTAGCTAG-3′; ATG-YL8 in the in the BstXI/XbaI sites of the pcDNA1 vector,
5′-TGTGAAAAACAGGCCAAACAGGCCAAACAGGAAGATGACCTTCAACTACCGGAATCTCTAG-3′.
Transfections
The DEAE-dextran transfection method was used in Figures 2B and 2C, 3, 4A, 6A, 6C, and 6E. It has been described previously (Serwold et al. 2001). Briefly, Lmtk– or COS-7 cells were transfected in 96-well plates (1 × 104 cells per well) with the indicated concentration of plasmid DNA, 0.1 mg/ml DEAE-dextran, 0.1 mM chloroquine, 10 ng/ml MHC class I cDNA, 5 ng/ml B7.2 cDNA, and 10% NuSerum (Collaborative Biomedical Products, Becton Dickinson, Bedford, Massachusetts, United States) in RPMI 1640. After 90 min, the cells were shocked with 10% DMSO in PBS for 2 min. After 2 d incubation in normal medium, T cells (1 × 105 cells per well) were added to assay peptide expression. GeneJuice (Novagen, Madison, Wisconsin, United States) transfection reagent was used in Figures 1, 2D, 4B, 5, 6B, 6D, 6F, and 7. It was used according to the manufacturer's instructions, except that we used 8 ml of medium, 8 μl of GeneJuice, 1.33 μg of MHC class I DNA, and 1.33 μg of peptide DNA per 10-cm dish. Peptide expression in the transfected cells was assayed after 2 d by titrating intact cells or after fractionating the cell extracts by HPLC.
T cell assay
The T cell assay has been described previously (Sanderson and Shastri 1994). Briefly, Lac Z-inducible T hybridomas (1 × 105 cells) were incubated with APCs in 96-well plates for 6–24 h. The response, accumulation of intracellular β-galactosidase, was measured with the substrate chlorophenol red-β-D-galactopyranoside (CPRG). The product was measured with a 96-well plate reader at 595 nm and 655 nm as the reference wavelength.
HPLC
The HPLC assay has been described previously (Serwold et al. 2001). Briefly, 2 d after transfection, cells were lysed in 10% formic acid, and the lysate was passed through a 10 kDa cutoff filter (Millipore, Bedford, Massachusetts, United States). The <10 kDa fraction was injected onto a 2.1 × 250 mm C18 column (Vydac, Hesperia, California, United States) and separated by RP-HPLC, with 0.1% TFA in water as the polar buffer and 0.1% TFA in acetonitrile as the nonpolar buffer. Three-drop fractions (except analysis of xM9, with five-drop fractions) were collected in 96-well plates, dried in a vacuum centrifuge, and analyzed by the addition of APCs (5 × 104 per well) and T cell hybridomas (1 × 105 cells per well).
eIF2α phosphorylation
Cells were transfected with GeneJuice (Novagen) as described above, but the transfection medium was left on for only 4 h before the cells were lifted and split into multiple dishes with fresh medium. Cells were allowed to rest for 12 h before sodium arsenite treatment. They were treated with 50 μM NaAs (Sigma, St. Louis, Missouri, United States), 1× GolgiPlug containing brefeldin A (PharMingen, San Diego, California, United States), or left untreated for 4 h. The cells were then lifted and counted. For the T cell assay, they were titrated in a 96-well plate. The assay was as described above, except that 1× GolgiPlug was added in order to “freeze” the cells in their state at the end of treatment. For the Western blot, they were incubated on ice for 5–10 min in lysis buffer (20 mM HEPES [pH 7.5], 150 mM NaCl, 1% Triton X-100, 10% glycerol, 1 mM EDTA, 10 mM tetrasodium pyrophosphate, 100 mM NaF, 17.5 mM β-glycerophosphate, 0.4 U/ml aprotinin, 10 μg/ml leupeptin, 1 mM PMSF, 0.1 mM pepstatin A, and complete protease inhibitor cocktail [Roche, Basel, Switzerland]). The lysate was spun for 15 min at 4 °C, and the supernatant was transferred to a tube containing an equal volume of 2× SDS-PAGE sample buffer (100 mM Tris-HCl [pH 6.8], 20% glycerol, 4% SDS, bromophenol blue, and 5% β-mercaptoethanol). The sample was then heated in water just off the boil for 5 min, separated on a 10% SDS-PAGE gel, and transferred to a nitrocellulose membrane. The membrane was blocked for 1 h at room temperature in TBS–0.1% Tween 20–5% bovine serum albumin (TBS, 0.02 M Tris-HCl [pH 7.6] with 0.137 M NaCl), incubated for 1 h with primary antibody (#44–728, at a 1:2000 dilution; Biosource, Camarillo, California, United States) in TBS–0.1% Tween 20–5% bovine serum albumin, washed four times for 5 min with TBS–0.1% Tween 20, incubated for 40 min with secondary antibody (anti-rabbit-HRP #NA934V, at a 1:30,000 dilution; Amersham, Little Chalfont, United Kingdom), washed four times for 5 min with TBS–0.1% Tween 20, incubated for 5 min in substrate (SuperSignal West Femto Maximum Sensitivity Substrate, #34095; Pierce Biotechnology, Rockford, Illinois, United States), and exposed to film. An antibody to α-tubulin (#sc-5546; Santa Cruz Biotechnology, Santa Cruz, California, United States) was used as a loading control.
We thank P. Sarnow and E. Jan (Stanford University) for discussions and advice, D. King for peptide synthesis, S. Bakkour, M. Hutchinson, and Y. Ow for excellent technical assistance, and T. Serwold and G. Hammer for thoughtful suggestions. This research was supported by grants to N. Shastri from the NIH.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. SRS, JS, SM, and NS conceived and designed the experiments. SRS, JS, TH, and SM performed the experiments. SRS, JS, TH, SM, and NS analyzed the data. SRS contributed reagents/materials/analysis tools. SRS and NS wrote the paper.
Academic Editor: Marc Jenkins, University of Minnesota
Citation: Schwab SR, Shugart JA, Horng T, Malarkannan S, Shastri N (2004) Unanticipated antigens: Translation initiation at CUG with leucine. PLoS Biol 2(11): e366.
Abbreviations
APCantigen-presenting cell
CPV-IREScricket paralysis virus-like internal ribosome entry site
CTLcytotoxic T cell
eIF2eukaryotic translation initiation factor 2
eIF2αeIF2 α subunit
GDPguanosine diphosphate
GFPgreen fluorescent protein
GTPguanosine triphosphate
HPLChigh performance liquid chromatography
IRESinternal ribosome entry site
MHCmajor histocompatibility complex
NaAssodium arsenite
RNAiMetmethionyl initiator RNA
RP-HPLCreverse-phase HPLC
UTRuntranslated region
==== Refs
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| 15510226 | PMC524250 | CC BY | 2021-01-05 08:28:07 | no | PLoS Biol. 2004 Nov 26; 2(11):e366 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020366 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1551022710.1371/journal.pbio.0020367Research ArticleImmunologyInfectious DiseasesMicrobiologyDanio (Zebrafish)Tuberculous Granuloma Formation Is Enhanced by a Mycobacterium Virulence Determinant Mycobacteria Promote GranulomasVolkman Hannah E
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Sherman David R
3
Ramakrishnan Lalita lalitar@u.washington.edu
2
4
5
1Molecular and Cellular Biology Graduate Program, University of WashingtonSeattle, WashingtonUnited States of America2Department of Microbiology, University of WashingtonSeattle, WashingtonUnited States of America3Department of Pathobiology, University of WashingtonSeattle, WashingtonUnited States of America4Department of Immunology, University of WashingtonSeattle, WashingtonUnited States of America5Department of Medicine, University of WashingtonSeattle, WashingtonUnited States of America11 2004 26 10 2004 26 10 2004 2 11 e36718 6 2004 24 8 2004 Copyright: © 2004 Volkman 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 Clear View of Mycobacterial Infection
Granulomas are organized host immune structures composed of tightly interposed macrophages and other cells that form in response to a variety of persistent stimuli, both infectious and noninfectious. The tuberculous granuloma is essential for host containment of mycobacterial infection, although it does not always eradicate it. Therefore, it is considered a host-beneficial, if incompletely efficacious, immune response. The Mycobacterium RD1 locus encodes a specialized secretion system that promotes mycobacterial virulence by an unknown mechanism. Using transparent zebrafish embryos to monitor the infection process in real time, we found that RD1-deficient bacteria fail to elicit efficient granuloma formation despite their ability to grow inside of infected macrophages. We showed that macrophages infected with virulent mycobacteria produce an RD1-dependent signal that directs macrophages to aggregate into granulomas. This Mycobacterium-induced macrophage aggregation in turn is tightly linked to intercellular bacterial dissemination and increased bacterial numbers. Thus, mycobacteria co-opt host granulomas for their virulence.
A zebrafish model of mycobacterium infection demonstrates that formation granulomas - immune structures composed of macrophages - requires a bacterial gene, indicating that mycobacteria exploit granuloma formation for infection
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Introduction
Infection with pathogenic mycobacteria is thought to proceed through a series of defined steps. Mononuclear cells present at or recruited to sites of infection phagocytose bacteria and migrate deeper into tissues. Then additional macrophages and other immune cells are recruited to form complex, tightly aggregated structures called granulomas (Adams 1976; Dannenberg 1993; Teitelbaum et al. 1999; Geijtenbeek et al. 2003; Peters and Ernst 2003; Tailleux et al. 2003; Cosma et al. 2004). Granuloma macrophages subsequently undergo differentiation into epithelioid cells, so called owing to their closely apposed cellular membranes (Adams 1976; Dannenberg 1993; Cosma et al. 2004). Production and maintenance of granulomas is essential to the control of tuberculosis in murine models and humans (Kaufmann 2000; Flynn and Chan 2001; Lawn et al. 2002). However, despite residence at the site of a robust focal immune response, the bacilli within granulomas are not always eradicated (Cosma et al. 2003; Cosma et al. 2004). The relative contributions of host and pathogen determinants to the migration and aggregation of macrophages and the formation and maintenance of granulomas are not understood.
While considerable progress has been made in identifying Mycobacterium virulence determinants (Glickman and Jacobs 2001; Cosma et al. 2003; Smith 2003), our overall understanding of mycobacterial pathogenesis remains rudimentary. Virulence determinants are generally studied by examining mutant bacterial strains in cultured macrophage monolayers or by static assessment of bacterial numbers and tissue pathology at different time points during in vivo infection. During in vivo infection, spatially separated individual mononuclear cells are infected, migrate into tissues, and serve as a nidus for cellular aggregation (Teitelbaum et al. 1999; Davis et al. 2002; Geijtenbeek et al. 2003; Tailleux et al. 2003). The steps and dynamics of bacterially mediated host-cell interactions that impact the outcome of infection through production of chemokines, cytokines, adhesion molecules, and their receptors cannot be elucidated by tissue culture studies and static assessments in vivo. To address these issues, we utilize a novel model of Mycobacterium infection in zebrafish. Zebrafish embryos and larvae (henceforth we will refer to both stages as embryos) are naturally susceptible to infection by Mycobacterium marinum, and we have previously shown that their optical transparency may be used to monitor the cellular dynamics of infection in real time (Davis et al. 2002). Using differential interference contrast (DIC) video and fluorescence microscopy, we have monitored macrophage chemotaxis to M. marinum, its phagocytosis, transit of infected macrophages into tissues, and the recruitment of additional macrophages to initiate granulomas that have the pathological hallmarks and bacterial gene expression profile characteristic of tuberculous granulomas in adult animals.
In this study, we use the zebrafish infection model to probe the cellular mechanisms of virulence of the Mycobacterium RD1 locus, an approximately 10-kb region missing from all attenuated bacille Calmette-Guérin (BCG) vaccine strains but present in virulent M. tuberculosis isolates (Mahairas et al. 1996; Behr and Small 1999). The RD1 locus encodes a specialized secretion system for the putative virulence effector proteins ESAT-6 and CFP-10, also located within the locus (Tekaia et al. 1999; Pallen 2002; Hsu et al. 2003; Pym et al. 2003; Stanley et al. 2003; Guinn et al. 2004). The M. tuberculosis RD1 deletion mutant has a growth defect in the mouse model of tuberculosis (Lewis et al. 2003), and studies using cultured macrophages and other in vitro systems have identified complex phenotypes that may account for its in vivo attenuation (Hsu et al. 2003; Stanley et al. 2003; Guinn et al. 2004). In vitro assays have suggested that RD1 may contribute to mycobacterial cytotoxicity to macrophages and epithelial cells, thus enabling bacterial spread between cells or transit across epithelial barriers (Hsu et al. 2003; Guinn et al. 2004). Others have proposed that the RD1 region mediates dampening of host innate immune responses in macrophages (Stanley et al. 2003). It is unclear how each of these individual in vitro phenotypes contributes to the complex sequence of events that ultimately lead to bacterial persistence in granulomas. We used the zebrafish-M. marinum infection model to elucidate the precise steps at which infection with wild-type (WT) and RD1 mutant bacteria differ. Our data suggest that the RD1 locus independently mediates macrophage aggregation and intercellular bacterial spread via host cell death within aggregates. These steps are associated with increased bacterial numbers and enhanced virulence, lending support to the idea that mycobacteria actually promote and exploit granuloma formation for the establishment of infection.
Results
The M. marinum RD1 Mutant Is Attenuated for Growth in Cultured Macrophages and Adult Frogs
The genes in the M. marinum RD1 region are homologous to those in M. tuberculosis (for instance, their ESAT-6 and CFP-10 proteins are 97% and 91% identical, respectively) and the regions in the two organisms are syntenic (http://www.sanger.ac.uk/Projects/M_marinum/; Figure 1). We derived an M. marinum RD1-deficient mutant with essentially the same deletion as the M. tuberculosis RD1 mutant described previously (Figure 1) (Lewis et al. 2003). Like the M. tuberculosis RD1 mutant (Lewis et al. 2003), the M. marinum mutant (referred to as ΔRD1) was attenuated for growth in mouse and human monocyte/macrophage cell lines (Figure 2A and unpublished data). ΔRD1 was also attenuated for growth in an adult leopard frog infection model (Figure 2B) in which WT M. marinum causes chronic granulomatous infection (Ramakrishnan et al. 1997). Specifically, significantly fewer ΔRD1 bacteria were recovered from spleens and livers of infected frogs at 2, 8, and 24 wk postinfection (Figure 2B and unpublished data). ΔRD1-infected frogs also had poorly formed macrophage aggregates at 8 wk postinfection, in contrast to the well-defined granulomas resulting from WT infection (unpublished data). Thus, by previously evaluated parameters, the RD1 region plays identical roles in the virulence of M. tuberculosis and M. marinum.
Figure 1 The RD1 Regions in M. tuberculosis and M. marinum Are Homologous and Syntenic
The white arrows represent the RD1 region deleted from M. tuberculosis. The black arrow represents a predicted open reading frame not present in M. tuberculosis. Rv3874 and Rv3875 are also known as cfp-10 and esat-6, respectively. Numbers represent the percent amino acid identities between the corresponding proteins of the two organisms.
Figure 2
M. marinum ΔRD1 Is Attenuated In Vitro and In Vivo
(A) Growth of M. marinum WT and ΔRD1 in J774 cells. Each time point represents the average of triplicate values. Error bars are ± standard error of the mean (SEM).
(B) WT and ΔRD1 bacterial numbers in frog spleens. Each time point represents the average colony counts from 3–5 frogs. Error bars are ± SEM (* p ≤ 0.05, ** p = 0.016, unpaired Student's t-test). Infecting doses were 5.8 × 105 CFU for WT and 1.2 × 106 CFU for ΔRD1.
M. marinum ΔRD1 Infection of Zebrafish Embryos Results in Reduced Macrophage Aggregation
We injected fluorescent WT or ΔRD1 bacteria via the caudal vein directly into the bloodstream of 30 h postfertilization embryos (Figure 3A), which were then monitored for survival and bacterial load (Figure 3B and 3C; Materials and Methods) (Davis et al. 2002). In contrast to WT bacteria, ΔRD1 failed to kill the embryos during the 12 d monitoring period (Figure 3B). Consistent with this difference in mortality, ΔRD1 bacterial growth was attenuated as compared to WT bacteria in the embryos (Figure 3C).
Figure 3 ΔRD1 Is Attenuated in Zebrafish Larvae
(A) Diagram of the zebrafish embryo/larva. Arrows indicate the two injection sites used in this study.
(B) Survival of embryos infected with ΔRD1 (410 CFU) or WT bacteria (250 CFU) and null-injected embryos.
(C) Whole embryo bacterial counts of WT- and ΔRD1-infected embryos. Infecting doses: 32 CFU for WT, 36 CFU for ΔRD1. Error bars are ± SEM (** p = 0.0075 comparing 7-d postinfection WT to 7-d postinfection ΔRD1; * p = 0.05 comparing 9-d postinfection WT to 9-d postinfection ΔRD1, unpaired Student's t-test).
(D) Time of aggregate formation, showing delayed aggregation in the ΔRD1-infected embryos (n = 13) as compared to WT-infected embryos (n = 15). Infecting doses: 131 CFU for WT, 301 CFU for ΔRD1.
(E) Whole embryo bacterial counts of WT- and ΔRD1-infected embryos on day of aggregate formation. Infecting doses: 36 CFU for WT, 78 CFU for ΔRD1. Error bars are ± SEM (*** p = 0.0008, unpaired Student's t-test; ΔRD1 n = 28, WT n = 29).
(F) Fluorescent image of WT-infected embryo at 6 d postinfection with two aggregates (arrows). Scale bar, 200 μm.
(G) WT-infected embryos with higher magnification overlay of fluorescent and DIC images showing an aggregate (arrow) with individual infected macrophages that are migrating toward aggregate (arrowheads). Scale bar, 50 μm.
(H) Fluorescent image of ΔRD1-infected embryo at 6 d postinfection that has not formed any aggregates. Note the numerous infected macrophages throughout the head, body, and tail. Arrowhead and close-up insert (scale bar, 50 μm) show infected macrophages close to each other, but not aggregating. Scale bar, 200 μm.
(I) ΔRD1-infected embryo under higher-magnification overlay of DIC and fluorescent images showing three individual infected macrophages (arrowheads). Scale bar, 50 μm.
To understand the cellular basis of ΔRD1 attenuation, we undertook real-time microscopic monitoring of the infection process with WT and mutant bacteria. WT infection of the embryos is characterized by the transit of infected macrophages into tissues where macrophages are recruited to form granulomas within 3–5 d postinfection (Figure 3D, 3F, and 3G) (Davis et al. 2002). In contrast, while ΔRD1 infected macrophages also migrated from the circulation to the tissues (Figure 3H), fewer, if any, aggregates formed, and the kinetics of their formation were delayed compared to the WT-infected cells (Figure 3D). Several highly infected individual macrophages were found scattered throughout the tissues, often close to each other (Figure 3H and 3I). This is in sharp contrast to the case of WT infection, in which infected macrophages are nearly always found in aggregates (Davis et al. 2002). Aggregates that formed in ΔRD1-infected embryos were more transient than those in WT-infected embryos, often dissociating into individual infected macrophages (Figure 3D and unpublished data). Also, the ΔRD1 aggregates remained small in contrast to WT aggregates, which often increased dramatically in size (Figure 4, compare images in [A] to those in [B]). This finding suggests that RD1 is required not only to initiate aggregate formation but for an ongoing recruitment of macrophages into the aggregate.
Figure 4 Progression of Aggregates a WT Aggregate (A), and a ΔRD1 Aggregate (B)
(A) WT aggregates shown on the first day of aggregate formation (t = 0 h); 24 h after aggregate formation (t = 24 h); and 48 h after aggregate formation (t = 48 h).
(B) ΔRD1 aggregates shown at the same time points as in (A).
A 60× water lens was used for all photomicrographs except the image in (A) t = 48 h, which was taken with a 40× lens. Scale bar represents 50 μm.
Since M. marinum ΔRD1 is attenuated for growth in the embryos (see Figure 3C), we considered the possibility that this mutant strain did not replicate enough to reach the threshold bacterial numbers that might be required to stimulate host pathways for macrophage aggregation. In that case, the inability of ΔRD1 to induce macrophage aggregation would be a simple consequence of its primary replication defect in the embryos. This scenario would predict that the number of bacteria required for aggregate formation would be similar in WT and ΔRD1 infection. To investigate this possibility, we infected embryos with similar numbers of the two bacterial strains and examined them daily for aggregate formation. On the day each embryo developed an aggregate(s), it was lysed and bacterial colony-forming units (CFU) determined. The bacterial load at which macrophage aggregation first occurred was over 4-fold higher in ΔRD1- than WT-infected embryos (see Figure 3E). These results show that ΔRD1 infection is associated with a primary aggregation defect that is not a consequence of its decreased replication in macrophages.
The RD1 Locus Specifically Mediates Macrophage Aggregation
Macrophages are rapidly recruited to the site of WT M. marinum infection, where they phagocytose the bacteria, migrate to the tissues, and form aggregates (Davis et al. 2002). Since macrophage migration and aggregation are likely mediated by as yet ill-defined chemotactic networks, we asked if the RD1 locus also affected other chemotactic macrophage functions. Macrophage recruitment is most stringently assessed by injecting bacteria into the hindbrain ventricle, an isolated cavity devoid of macrophages in the absence of bacteria (see Figure 3A) (Herbomel et al. 1999; Davis et al. 2002). Similar numbers of macrophages migrated to the hindbrain ventricle in response to the injection of WT and ΔRD1 bacteria at 4 h postinfection, and most of the bacteria had been phagocytosed in both cases (Figure 5A; unpublished data). Therefore, the RD1 locus does not affect macrophage chemotaxis to the bacteria or phagocytic capabilities.
Figure 5 Normal Macrophage Chemotaxis to Initial Sites of ΔRD1 Infection
Overlay of DIC and fluorescent images showing the hindbrain ventricle (hv) of infected embryos. The hindbrain ventricle/brain (hv/b) boundary indicated by a white dashed line.
(A) ΔRD1-infected embryo 4 h postinfection with individual infected macrophages marked by arrowheads.
(B) ΔRD1-infected embryo 5 h postinfection in which individual infected macrophages (arrowheads) have migrated from the hindbrain ventricle and into the brain.
(C) WT-infected embryo 24 h postinfection with macrophages beginning to aggregate (white arrow) in the hindbrain ventricle. A second out-of-focus aggregate is to the left (yellow arrow). Scale bar, 100 μm.
The abundance of ΔRD1-infected macrophages in tissues following bloodstream infection (see Figure 3H and 3I) suggested that the RD1 locus is not required for tissue migration following infection. However, tissue migration can also be examined more stringently following the ventricle injection assay (Davis et al. 2002). 5 h after infection of the ventricle, many of the ΔRD1-infected macrophages had entered the brain tissue (Figure 5B). By 24 h, most of the macrophages were widely disseminated throughout the tissues (unpublished data). Indeed, the lack of aggregation by RD1-infected macrophages led to their enhanced tissue dissemination compared to WT-infected macrophages, which had often formed aggregates within the ventricle itself by 24 h postinfection (Figure 5C). Likely as a result, the WT-infected macrophages were slower to migrate out of the ventricle than ΔRD1-infected macrophages. Even when they did migrate out of the ventricle, they often formed aggregates in the adjacent brain tissue and did not disseminate into the trunk and tail as rapidly as did the ΔRD1-infected macrophages. In summary, the ventricle infections showed that the RD1 locus is not required for macrophage chemotaxis to the site of infection, bacterial phagocytosis, or tissue migration of infected macrophages. Furthermore, this assay highlighted the difference in the aggregation of WT- and ΔRD1-infected macrophages from very early in infection.
ΔRD1-Infected Macrophages Can Receive, but Not Send, Signals That Promote Aggregation
The aggregation defect of ΔRD1-infected macrophages suggests that they lack the capacity to either produce or receive signals that mediate aggregation of macrophages during WT infection. To begin to dissect the nature of the missing signal(s), we infected embryos with red-fluorescent WT bacteria and allowed aggregates to form. These embryos were then superinfected with green-fluorescent ΔRD1 or WT bacteria (Figure 6). Both superinfecting strains were phagocytosed by individual macrophages, which migrated in similar numbers to preexisting aggregates within 4 h (Figure 6A and 6B). These data indicate that ΔRD1-infected macrophages can receive signals produced by WT-infected macrophages and migrate rapidly toward aggregates.
Figure 6 Superinfection with WT Bacteria Rescues ΔRD1 Aggregation Defect
(A and B) Embryos with aggregates at 3d postinfection with 85 CFU red-fluorescent WT bacteria are shown 4 h after superinfection with green-fluorescent strains of either ΔRD1 (134 CFU) (A) or WT (169 CFU) (B) bacteria. Superinfecting strains were injected at sites distant from the aggregates, and pictures were taken outside of injection regions. Arrowheads indicate macrophages infected with superinfecting strain. Scale bar, 100 μm.
(C) Embryo infected with 171 CFU green-fluorescent ΔRD1 for 4 d shown 4 h post-superinfection with 364 CFU of red-fluorescent ΔRD1. Arrowheads point to macrophages infected with each of the bacterial strains. Scale bar, 200 μm.
(D) Embryo infected with 171 CFU green-fluorescent ΔRD1 for 4 d shown 4 h after superinfection with 363 CFU of red-fluorescent WT bacteria. Arrow points to macrophage aggregate. Scale bar, 200 μm.
(E) Higher magnification image of aggregate (arrow) in (D) showing green fluorescent ΔRD1 and red fluorescent WT bacteria. Arrowhead points to WT-infected macrophage outside the aggregate. Scale bar, 50 μm.
(F and G) Embryo infected with green fluorescent ΔRD1, superinfected with red fluorescent WT (as in D and E) shown at 24 h post-superinfection (F), and the same aggregate at 48 h post-secondary infection (G). Scale bars, 50 μm. All panels are fluorescent images.
In a reciprocal experiment, embryos were first infected with green-fluorescent ΔRD1 bacteria, and after 4 d, when there were abundant individual infected macrophages (but no aggregates) in the tissues, the embryos were superinfected with either WT or ΔRD1 red-fluorescent bacteria. As expected, both superinfecting strains were rapidly phagocytosed by uninfected macrophages. ΔRD1 superinfection did not cause aggregate formation, and individual macrophages carrying both the original or superinfecting ΔRD1 were scattered throughout the tissues (Figure 6C). In contrast, WT-infected macrophages induced the aggregation of preexisting ΔRD1-infected macrophages as early as 4 h after superinfection (Figure 6D, 6E, and 7). These newly formed aggregates were often composed mostly of ΔRD1-infected macrophages with only a few WT-infected macrophages in them (Figure 7). All aggregates had at least some WT-infected macrophages. Furthermore, ΔRD1/WT aggregates that formed developed normally, increasing in size and recruiting both ΔRD1- and WT-infected macrophages (Figure 6F and G). Thus, this experiment confirmed that ΔRD1-infected macrophages receive but do not send aggregation signals and have no intrinsic chemotactic defects. Furthermore, it appears that WT-infected macrophages are required to serve as a nidus for each aggregate, suggesting that they create a chemotactic gradient that recruits macrophages.
Figure 7 Superinfection with WT Bacteria Rescues ΔRD1 Aggregation Defect over Time
Embryos were injected with fluorescent ΔRD1 (green) at 1 d postfertilization. 3 d post-primary infection, embryos were injected with fluorescent WT (red) and followed for 24 h post-secondary infection. Approximate injection sites are shown with green and red arrows for ΔRD1 and WT bacteria, respectively. Box in top panel indicates the magnified field in fluorescent images. Inset panel at 24-h time point is a magnified image of the starred aggregate. Scale bar, 125 μm.
Macrophage Aggregation Is Tightly Linked to Intercellular Bacterial Spread
Having demonstrated that ΔRD1 infection results in both reduced aggregation and lower bacterial numbers, we next pursued experiments to determine the relationship between these two phenotypes. In contrast to the notion that a primary reduction in bacterial numbers obviated the need for aggregation (see Figure 3E), we found that more ΔRD1 than WT bacteria were required for aggregates to form. Therefore, we sought to determine if, conversely, the aggregation defect resulted in reduced bacterial numbers.
One way that aggregation could impact bacterial numbers is by facilitating the spread of bacteria to uninfected macrophages that are recruited to the aggregates. If so, then aggregate formation should correlate with a dramatic increase in the number of infected macrophages and bacterial burdens. To test this hypothesis, we assessed the number of infected macrophages and bacterial numbers in relation to the time of aggregate formation (Figure 8). We enumerated daily by microscopy the number of infected macrophages during the course of infection starting at 1 d postinjection of bacteria and continuing up to 2 d after aggregates formed (Figure 8A). We counted as day 0 the first day of aggregation. During WT infection, the number of infected macrophages did not change significantly until aggregates formed (Figure 8A). However, upon aggregation, the number of infected macrophages increased dramatically (Figure 8A). Similarly, the number of viable bacteria also did not increase until after aggregation occurred 3–5 d postinfection (Figure 8B). Taken together, these data suggest that during WT infection, macrophage aggregation promotes intercellular bacterial spread and an increased bacterial burden.
Figure 8 Macrophage Aggregation Correlates with Bacterial Dissemination during WT Infection
(A) Enumeration of infected macrophages in embryos by fluorescent and DIC microscopy after infection with green-fluorescent bacteria. Infecting doses: 151 CFU for WT, 301 CFU for ΔRD1. Time points are in reference to day of aggregate formation, which is set at 0. 15 WT infected embryos and 13 ΔRD1 embryos were monitored. The graph represents all 15 WT embryos, but only the 7/13 ΔRD1 infected embryos that formed aggregates over the course of the experiment. Error bars are ± SEM. (*p = 0.0136 comparing WT day 0 and WT day –2; ** p = 0.0053 comparing WT day 1 and WT day –2, unpaired Student's t-test).
(B) Whole embryo bacterial counts following WT infection (*** p ≤ 0.0003, 5 d postinfection and 8 d postinfection, respectively, compared to 3 d postinfection, unpaired Student's t-test).
In the case of ΔRD1 infection, macrophage aggregation did not result in an increase in the number of infected macrophages (Figure 8A). This difference could be solely due to the ongoing defect in macrophage recruitment by the ΔRD1-containing aggregates. It could also involve additional pathways that result in decreased bacterial spread to uninfected macrophages in the aggregates. In either case, this result suggests that while aggregation is required for intercellular bacterial spread, it is not sufficient. Additional RD1-mediated events must occur to facilitate spread after aggregation.
WT Aggregates Have More Cell Death Than ΔRD1 Aggregates
Having established that RD1 is involved in macrophage recruitment to aggregates, we sought to determine if it also affects intercellular bacterial spread by additional means. The M. tuberculosis RD1 locus is thought to promote intercellular bacterial spread in confluent cultured macrophage monolayers by promoting death of infected cells and subsequent phagocytosis of the released bacteria by surrounding cells (Guinn et al. 2004). Therefore, we hypothesized that RD1 might operate similarly in the embryo aggregates to mediate bacterial spread by facilitating cell death. For this assessment, we achieved comparably sized aggregates with the two strains by infecting embryos with 6.6-fold more ΔRD1 than WT bacteria, and performed terminal deoxynucleotidyl transferase–mediated deoxyuridine triphosphate nick end labeling (TUNEL) staining on whole infected embryos to visualize dead and dying cells. The TUNEL reaction labels double-stranded DNA breaks that can occur during apoptosis and certain forms of necrosis (Gavrieli et al. 1992). WT infected embryos had more aggregates with TUNEL-positive cells (15 of 23) than did ΔRD1-infected embryos (6 of 22) (Figure 9). Contingency table analysis revealed that WT aggregates were 2.3 times more likely to contain TUNEL-positive cells than ΔRD1 aggregates (p = 0.017, Fisher's exact t-test). The TUNEL-positive cells were often M. marinum-infected (Figure 9A). Furthermore, TUNEL-positive infected cells were found almost exclusively within aggregates. Taken together, our data suggest that the RD1 locus first mediates macrophage aggregation and subsequently promotes cell death within the aggregates.
Figure 9 WT Aggregates Are More Likely to Have TUNEL-Positive Cells Than ΔRD1 Aggregates
Representative fluorescent images of aggregates following TUNEL staining of 6-d postfertilization embryos infected with 71 green-fluorescent WT (A), or 474 green-fluorescent ΔRD1 (B) bacteria. TUNEL staining is imaged with red fluorescence, and colocalization with green-fluorescent bacteria appears yellow. Scale bar, 100 μm.
The RD1 Locus Continues to Mediate Granuloma Formation During Long-Term Infection
We have previously used the zebrafish embryo model to demonstrate that granulomas can be initiated solely by interactions of mycobacteria with innate immunity (Davis et al. 2002). However, their maturation and an enhancement in their mycobacteriocidal potential likely requires the participation of adaptive immunity (Flynn and Chan 2001; Davis et al. 2002). Thus, the zebrafish embryo model has been useful to separate the effects of innate and adaptive immunity on granuloma formation (Davis et al. 2002). Since both the M. tuberculosis and M. marinum RD1 mutants exhibit a sustained attenuation during chronic infection of adult animals (see Figure 2B) (Lewis et al. 2003), we wished to determine if the early aggregation defect we had discovered using the zebrafish embryo model impacts granuloma formation and maturation later in infection. We infected embryos with low doses of either WT or ΔRD1 bacteria and confirmed infection microscopically at 6 d postfertilization. Using these low infection doses, we could raise a very few WT-infected embryos to adulthood. In contrast, the mortality of the ΔRD1-infected embryos was no different from that of uninfected embryos during a 32 d observation period (see Figure 3B) (unpublished data). At 32 d, the fish were assessed by tissue histopathology. Mycobacteria were identified within the granulomas in all of the surviving fish, showing that they were chronically infected (Figure 10). WT-infected fish had highly organized granulomas, both caseating and noncaseating in roughly equal proportions (Figure 10A and 10C), with bacteria located predominantly in the caseum (Figure 10B and 10D). These granulomas appeared identical to granulomas resulting from infection of adult zebrafish (Cosma et al. 2004). In contrast, ΔRD1-infected fish had only a few granulomas (Figure 10E and 10F), all of which were noncaseating and markedly different even from WT noncaseating granulomas (Figure 10C and 10E). The WT-induced granulomas were compact and were composed of tightly packed cells that displayed the indistinct cytoplasmic borders and abundant eosinophilic cytoplasm characteristic of epithelioid cells (Figure 10C) (Adams 1976; Bouley et al. 2001). In contrast, the ΔRD1-induced aggregates had more loosely aggregated cells, with evidence of epithelioid transformation only in the centers of some (Figure 10E).
Figure 10 ΔRD1 Infection Is Associated with Persistent Defects in Granuloma Organization
Tissue histology of 32-d postfertilization fish infected with either 21 WT (A–D) or 9 ΔRD1 (E–F) bacteria (doses were not significantly different p = 0.15) at 1 d postfertilization. Arrows indicate granulomas and loose aggregates, arrowheads indicate caseum. Hematoxylin and eosin staining are shown in (A), (C), and (E), and modified acid-fast staining is shown in (B), (D), and (F). (A) Organized caseating WT granulomas (arrow) with central caseum (arrowhead). (B) WT granuloma showing mycobacteria predominantly in caseum with a few within epithelioid cells. (C) Noncaseating but highly organized WT M. marinum-induced granulomas showing the expected few bacteria within cells in (D). (E) Large, loose, and poorly organized macrophage aggregate of ΔRD1-infected fish with evidence of epithelioid transformation only in the center (denoted by *). (F) A few mycobacteria in the ΔRD1 aggregates. Scale bar, 100 μm. Images in (A–D) were taken with a 40× lens, whereas those in (E) and (F) were taken with a 20× lens.
In summary, the ΔRD1-induced macrophage aggregates in infected embryos raised to adulthood had the same lack of organization as the lesions resulting from infection of adult animals (unpublished data) (Sherman et al. 2004). These studies link our early real-time observations of phenotypes in the context of innate immunity alone to these seen later in infection. It appears that while some macrophage aggregation does occur in the absence of RD1, this locus continues to mediate aspects of macrophage chemotaxis and/or differentiation that contribute to granuloma architecture even as the infection becomes chronic.
Discussion
We used the zebrafish-M. marinum infection model to identify the steps at which the Mycobacterium RD1 virulence locus impacts the infection process. We found that two steps are independently affected: macrophage aggregation into granulomas and intercellular spread therein. Promotion of cell death within these aggregates appears to be at least one of the means by which RD1 affects intercellular spread. By comparing WT and ΔRD1 infection in real time, we have uncovered the promotion of granuloma formation as a mechanism of Mycobacterium virulence.
The RD1 locus has been the recent subject of attention following its discovery as a major factor in the attenuation of BCG (Pym et al. 2002; Lewis et al. 2003) and the potential of an M. tuberculosis RD1-defective strain as a candidate vaccine for tuberculosis (Hsu et al. 2003; Pym et al. 2003). Subsequent studies suggested that it encodes a novel specialized secretion system for specific virulence effectors (Hsu et al. 2003; Pym et al. 2003; Stanley et al. 2003; Guinn et al. 2004). Deletion of the RD1 locus in M. tuberculosis and M. marinum results in reduced bacterial numbers during infection of cultured macrophages and adult animals (Hsu et al. 2003; Lewis et al. 2003; Stanley et al. 2003; Guinn et al. 2004; this study). Different in vitro studies have implicated the RD1 locus and its effectors ESAT-6 and CFP-10 in a variety of functions including lysis of cultured macrophage in confluent monolayers to promote intercellular spread (Guinn et al. 2004), disruption of artificial membranes (taken as a surrogate for lysis of host epithelial cell layers) (Hsu et al. 2003), and dampening of macrophage proinflammatory responses (Stanley et al. 2003). Whether these in vitro activities operate in vivo and how they impact virulence are not known. As is the case with virtually all Mycobacterium virulence determinants, the precise steps at which RD1 impacts virulence have not been elucidated.
The Mycobacterium infection model used here allows monitoring of the earliest individual stages of infection in real-time (Davis et al. 2002). Using this model, we were able to confirm that RD1 promotes macrophage death in vivo. Additionally, we have shown that the RD1 locus affects an unanticipated earlier step in pathogenesis, macrophage aggregation. Aggregation of infected cells is independent of bacterial replication within individual macrophages and distinct from other macrophage functions such as their chemotaxis to the bacteria and migration back to deeper tissues.
We speculate that RD1 mediates aggregation via its secreted effectors, which presumably interact with components of host macrophage signaling pathways to modulate macrophage aggregation. Some combination of chemokines, cytokines, and adhesion molecules is likely to be affected. Our superinfection experiments suggest a model by which RD1 impacts cellular signaling and aggregation. Because the ΔRD1-induced aggregates that form upon superinfection with WT bacteria always have at least one WT-infected macrophage, the RD1-induced signal likely diffuses from the infected macrophage to attract other macrophages to it to form aggregates. As ΔRD1-infected macrophages can receive but not send signals for aggregation, RD1 is likely required to induce expression of a chemotactic molecule but not its receptor.
The formation of the tuberculous granuloma requires a complex cascade of interrelated signals that mediate cell recruitment, adhesion, and differentiation. In our model, ΔRD1 infection results in alterations of all three processes. The initial lack of aggregation suggests a specific defect in the ability of ΔRD1-infected macrophages to recruit additional macrophages to form aggregates. Our real-time monitoring showed that ΔRD1-infected macrophages fail to aggregate even when they are in close proximity, suggesting that the primary defect in ΔRD1-infected macrophages is in the ability to send chemotactic signals for aggregation. On the other hand, our finding that ΔRD1-infected macrophage aggregates are more transient than WT ones may implicate both chemotactic and adhesion defects. This idea is further supported by the finding that the ΔRD1-induced lesions in the adult fish are composed of loosely aggregated macrophages with little epithelioid differentiation. However, a primary defect in the ability of ΔRD1-infected macrophages to send chemotactic signals could affect subsequent expression of adhesion molecules (Peters and Ernst 2003). Therefore we propose that the Mycobacterium RD1 locus induces infected macrophages to send chemotactic signals for aggregation of macrophages, which in turn affect adhesion and other downstream events that result in granuloma formation. Granuloma formation is not completely blocked upon infection with a ΔRD1 strain, as has been shown previously in the murine model of M. tuberculosis infection and in patient studies of disseminated BCG infection (Emile et al. 1997; Sherman et al. 2004). However, our data indicate that RD1 influences early aggregation events that seem to extend into later stages of infection.
Our data further suggest a model in which bacterial dissemination is facilitated by recruitment into the aggregates of uninfected macrophages that provide new habitats for further bacterial growth. Some ways in which incoming macrophages become infected could include transfer of bacteria between macrophages along membranous tethers (Davis et al. 2002), actin-based motility of extravacuolar bacteria leading to intercellular transfer (Stamm et al. 2003), and release of bacteria from dying infected cells. These dead cells could either release bacteria for phagocytosis by neighboring cells or be engulfed in their entirety (Ramakrishnan and Falkow 1994; Davis et al. 2002). All of these modes of bacterial transfer are likely to be enhanced by the close juxtaposition of macrophages within aggregates. Our data are consistent with earlier reports suggesting that RD1 mediates bacterially induced toxicity to host cells (Hsu et al. 2003; Guinn et al. 2004). While TUNEL staining is not a conclusive indication of apoptosis, it is most often associated with programmed cell death. In vitro studies indicate that apoptosis leads to bacterial cell death; however, our experiments indicate a correlation between host cell death and bacterial dissemination (Fratazzi et al. 1999). Since we did not observe TUNEL-positive infected cells prior to aggregation or outside of the aggregates, we believe that aggregation precedes cell death. Mechanistically, it is possible that RD1 effectors modulate impinge upon distinct signaling pathways for cell aggregation and death. Alternatively, RD1 may impact a common molecule, such as tumor necrosis factor, that affects both processes (Locksley et al. 2001). Other modes of bacterial transfer may also contribute to bacterial dissemination, and these may or may not be mediated by RD1.
Our examination of early infection events in vivo may serve to identify relevant findings from the in vitro studies. For instance, our data do not support the model that RD1 contains a cytolysin for epithelial cell barriers that allows mycobacteria to penetrate directly into deeper tissues (Hsu et al. 2003). Rather, these findings corroborate previous work from our laboratory and others showing that systemic dissemination of mycobacteria is effected mainly by trafficking of infected host mononuclear cells (Teitelbaum et al. 1999; Davis et al. 2002; Geijtenbeek et al. 2003; Tailleux et al. 2003; Cosma et al. 2004). We show, furthermore, that RD1 is not required for this early event. Another in vitro study describes the dampening of several macrophage innate immune responses, including the cytokine tumor necrosis factor, by WT but not RD1-mutant M. tuberculosis (Stanley et al. 2003). While this may be true in vivo as well, our functional approach shows that there is not a global dampening of chemotactic and innate immune responses by WT mycobacteria. Rather there is an RD1-mediated enhancement of macrophage aggregation and death.
Ultimately, our studies reveal that Mycobacterium expresses specific virulence factors that enhance macrophage aggregation into granulomas, starting very early after infection. This effect correlates with bacterial dissemination and an increase in the bacterial burden. Granulomas are thought to be primarily protective host immune structures that provide a focused immune response to restrict mycobacteria. According to prevailing models, recruitment and activation of additional macrophages provide a concentrated source of immune effectors that thwart the bacteria. The specific differentiation of macrophages into epithelioid cells with tightly interdigitated intercellular membranes helps sequester the infection. While there is clear evidence that granulomas are necessary for protection, there is increasing evidence that they are incompletely effective (Flynn and Chan 2001; Cosma et al. 2003; Cosma et al. 2004). We have recently shown that superinfecting mycobacteria traffic rapidly into preestablished granulomas, yet can survive therein (Cosma et al. 2004). The present study showing that mycobacteria promote the formation of these structures to enhance their dissemination reveals an even greater complexity in the granuloma's role in the pathogenesis of tuberculosis.
Materials and Methods
Construction of M. marinum strains
To generate a M. marinum RD1 mutant, PCR fragments immediately upstream (1,004 bp) and downstream (1,296 bp) of the region to be deleted (see Figure 1) were amplified from genomic DNA and cloned into the plasmid pKO, to flank a kanamycin resistance determinant (Sherman et al. 2001). The resulting plasmid, pJC2, was used to generate a RD1 deletion mutation in M. marinum as described (Ramakrishnan et al. 2000; Lewis et al. 2003). Both WT and ΔRD1 strains were transformed with plasmids containing transcriptional fusions of genes encoding either red-fluorescent protein (dsRed2) or green-fluorescent protein (gfp) to a constitutive M. marinum promoter as described (Chan et al. 2002; Cosma et al. 2004).
Macrophage infection assays
J774 mouse macrophage-like cells and THP1 human macrophage-like cells were grown and prepared for infection as described (Chan et al. 2002; Guinn et al. 2004). Infection with M. marinum and determination of intracellular bacterial counts was done as described (Chan et al. 2002).
Frog infections
Frogs were injected intraperitoneally with M. marinum, and tissue bacterial counts were obtained as described (Ramakrishnan et al. 1997).
Zebrafish embryo infections
Zebrafish embryos were maintained and injected with M. marinum strains as described (Davis et al. 2002).
Microscopy of embryos
DIC and video microscopy were performed using a Nikon E600 (Nikon, Tokyo, Japan) equipped with 10×, 20×, and 40× magnifications, or a Nikon DIC 60× water “fluor” objective. Fluorescent as well as black and white images were collected with a Photometrics CoolSnap “cf” camera (Roper Scientific, Trenton, New Jersey, United States). Overlays of DIC and fluorescent images and video compilations were produced by using Metamorph software as described (Davis et al. 2002).
Determination of whole embryo bacterial counts
Individual embryos were placed in microcentrifuge tubes containing 100 μl of embryo medium containing 20 μg/ml kanamycin for 1 h at room temperature. This medium was removed by aspiration and replaced with 150 μl of 0.25% Trypsin-EDTA. After incubation for 6–8 h at room temperature, Triton X-100 was added to a 0.1% final concentration, and the tubes were sonicated for 10 min in an ultrasonicator (Bransonic Ultrasonic Cleaner 1510R-NT; Branson Ultrasonics, Danbury, Connecticut, United States). The entire sample from each tube was plated onto individual 7H11 solid media plates containing 20 μg/ml kanamycin.
TUNEL assay
5 d following infection, embryos were fixed in 4% paraformaldehyde in PBS overnight, dehydrated in methanol for a minimum of 24 h at 4 °C, rehydrated in PBS in a graded series of 5-min washes (in 75% methanol in PBS, 50% methanol in PBS, and 25% methanol in PBS), and washed four or five times in PBST (0.5% Tween 20 in PBS). Embryos were permeabilized using 10 μg/ml proteinase K in PBST for 30 min at 37 °C, postfixed in 4% paraformaldehyde in PBS for 20 min, washed five times for 5 min each in PBST, and twice for 5 min each in TTase Buffer (25 mM Tris-HCl [pH 6.6], 0.2M sodium cacodylate, 0.25 mg/ml BSA, and 0.2% Tween 20) plus 1 mM CoCl. Embryos were then incubated with TUNEL enzyme (#1767305; Roche, Basel, Switzerland) and TUNEL label mix (#1767291, Roche) according to the manufacturer's specifications. Primary antibody staining with sheep anti-fluorescein (#1426338 at 1/10,000; Roche) was done in Western blocking solution (#1921673, Roche) overnight at 4 °C. Secondary antibody staining with horseradish peroxidase-conjugated rabbit anti-sheep (#313035047 at 1/500; Jackson Immunoresearch, Bar Harbor, Maine, United States) was done for 2 h at RT. Detection was done with Tyramide Amplification Signal kit with AlexaFluor 555 (Molecular Probes #T30953; Molecular Probes, Eugene, Oregon, United States) according to the manufacturer's specifications.
Tissue histology of adult fish
Fish were fixed in Dietrich's fixative (30% ethanol, 10% formalin, and 2% glacial acetic acid in deionized water) and sectioning and staining were performed by Histo-Tec (Hayward, California, United States).
Statistics.
Statistics were calculated using GraphPad InStat version 3.05.
This paper is dedicated to Stanley Falkow on the occasion of his seventieth birthday. We thank Christine Cosma and David Tobin for discussions and critique of the manuscript, Richard Burmeister for figure graphics, Greg Cox (Molecular Probes) for providing materials and advice for the tyramide protocols, Jessica Young for her initial observations on apoptosis in granulomas, Kathryn Klein and Kristi Guinn for assistance with the macrophage and frog experiments, and Reiling Liao and Kathryn Klein for assistance in strain construction. Support was provided by National Institutes of Health grants R01 AI36396 and AI054503 and an Ellison Medical Foundation New Scholar in Global Infectious Diseases award to LR, and National Institutes of Health grants HL64550 and HL68533 to DRS. HC was supported in part by PHS NRSA T32 GM07270 from the National Institute of General Medical Sciences.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. HEV, HC, DB, and LR conceived and designed the experiments. HEV, HC, DB, and LR performed the experiments. HEV, HC, DB, DRS, and LR analyzed the data. JCWC and LR contributed reagents/materials/analysis tools. HEV, HC, DB, DRS, and LR wrote the paper.
Academic Editor: Shizuo Akira, Osaka University
Citation: Volkman HE, Clay H, Beery D, Chang JCW, Sherman DR, et al. (2004) Tuberculous granuloma formation is enhanced by a Mycobacterium virulence determinant. PLoS Biol 2(11): e367.
Abbreviations
BCGbacille Calmette-Guérin
CFUcolony-forming units
DICdifferential interference contrast
SEMstandard error of the mean
TUNELterminal deoxynucleotidyl transferase–mediated deoxyuridine triphosphate nick end labeling
WTwild-type
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| 15510227 | PMC524251 | CC BY | 2021-01-05 08:21:21 | no | PLoS Biol. 2004 Nov 26; 2(11):e367 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020367 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1551022810.1371/journal.pbio.0020368Research ArticleEcologyInfectious DiseasesEpidemiology/Public HealthArthropodsPlasmodiumThe Risk of a Mosquito-Borne Infectionin a Heterogeneous Environment Mosquito-Born Disease in SpaceSmith David L
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Dushoff Jonathan
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McKenzie F. Ellis
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1Fogarty International Center, National Institutes of HealthBethesda, MarylandUnited States of America2Ecology and Evolutionary Biology, Princeton UniversityPrinceton, New JerseyUnited States of America11 2004 26 10 2004 26 10 2004 2 11 e3686 1 2004 24 8 2004 Copyright: © 2004 Smith et al.2004This is an open-access article distributed under the terms of the Creative Commons Public Domain declaration, which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
Predicting Risk of Mosquito-Borne Disease in Variable Environments
A common assumption about malaria, dengue, and other mosquito-borne infections is that the two main components of the risk of human infection—the rate at which people are bitten (human biting rate) and the proportion of mosquitoes that are infectious—are positively correlated. In fact, these two risk factors are generated by different processes and may be negatively correlated across space and time in heterogeneous environments. Uneven distribution of blood-meal hosts and larval habitat creates a spatial mosaic of demograPhic sources and sinks. Moreover, mosquito populations fluctuate temporally, forced by environmental variables such as rainfall, temperature, and humidity. These sources of spatial and temporal heterogeneity in the distribution of mosquito populations generate variability in the human biting rate, in the proportion of mosquitoes that are infectious, and in the risk of human infection. To understand how heterogeneity affects the epidemiology of mosquito-borne infections, we developed a set of simple models that incorporate heterogeneity in a stepwise fashion. These models predict that the human biting rate is highest shortly after the mosquito densities peak, near breeding sites where adult mosquitoes emerge, and around the edges of areas where humans are aggregated. In contrast, the proportion of mosquitoes that are infectious reflects the age structure of mosquito populations; it peaks where old mosquitoes are found, far from mosquito breeding habitat, and when mosquito population density is declining. Finally, we show that estimates for the average risk of infection that are based on the average entomological inoculation rate are strongly biased in heterogeneous environments.
A modeling approach reveals that incorporating the demography and behavior of mosquitoes can substantially change estimates of the risk of infection from diseases such as malaria
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Introduction
Understanding the spatiotemporal distribution of risk for mosquito-borne infections is an important step in planning and implementing effective infection control measures (Greenwood 1989; Charlwood et al. 1998; Chadee and Kitron 1999; Focks et al. 1999; Mendis et al. 2000; Carter 2002; Killeen et al. 2003). Remote sensing, geographical information systems, and predictive algorithms have made it possible to develop coarse-grained maps of vector habitat (Pope et al. 1994; Beck et al. 1997; Kitron 1998; Rogers et al. 2002), and epidemiological studies have identified statistical risk factors for human infection or disease (Snow et al. 1998; Ghebreyesus et al. 2000; Snow and Gilles 2002). Mathematical models can bridge the gaps between landscape ecology, vector biology, and human epidemiology, linking large-scale maps to individual risk in local human populations at spatial scales ranging from 10 m up to 10 km. At these spatial scales, transmission dynamics for vector-borne infections are linked to the seasonal dynamics, demography, and behavior of adult female mosquitoes, as well as the spatial distribution of larval habitat and blood hosts (Bidlingmyer 1985). Given a map of potential or actual mosquito sources and human habitation, what factors determine where and when the risk of a mosquito-borne infection is highest?
The risk of a mosquito-borne infection is estimated by the entomological inoculation rate (EIR): the number of bites by infectious mosquitoes per person per day (Macdonald 1957). EIR is the product of the human biting rate (HBR)—the number of bites by vector mosquitoes per person per day—and the proportion of mosquitoes that are infectious (PIM) (e.g., for malaria transmission, the sporozoite rate) (Birley and Charlwood 1987). We focus on the processes that generate patterns in the two components of EIR in temporally and spatially heterogeneous mosquito populations. We show that HBR and PIM peak at different times and places. We also show that estimates of average EIR in variable environments generate biased estimates of the relationship between EIR and the proportion of humans that are infected (Dye and Hasibeder 1986).
We develop theory to illustrate simple patterns in the EIR in heterogeneous environments, focusing on EIR's separate components. We follow the a priori approach of Ross, developing simple mathematical models as tools for qualitative and quantitative reasoning (McKenzie 2000). We develop a basis for micro-epidemiological models for mosquito-borne infections that can be combined with surveys of larval habitat to map the local risk of mosquito-borne infections (Greenwood 1989). Effective use and refinement of such maps depend on an understanding of the dynamics and behavior of specific mosquito populations and the transmission of specific infectious agents (Focks et al. 1999).
Results
Temporal Heterogeneity
Fluctuating mosquito density affects EIR through changes in HBR: transmission increases as mosquito density increases. Following an increase in the rate at which adult mosquitoes emerge, mosquito density and HBR peak (illustrated in Figure 1). The peak in EIR and the density of infected mosquitoes follow the peak in total mosquito density because it takes time for an infectious agent to spread through the human and mosquito populations. Increased HBR leads to secondary increases in the proportion of infected humans, and thus to increases in PIM. As the density of infected mosquitoes declines, decreasing transmission is followed by a decline in the prevalence of infection in humans.
Figure 1 Dynamics with Temporal Heterogeneity
The components of EIR follow different trends when mosquito populations vary temporally. Mosquito density (solid black) forms the dominant component of HBR. The density of infected mosquitoes (solid gray) peaks shortly after the density of mosquitoes (dotted vertical lines align the peaks). In contrast, the proportion of infectious mosquitoes (dashed) peaks while the mosquito population is declining. Seasonal mosquito emergence was modeled to have an long-term average
M/H ≈ 2 (K = 2 and H = 1). The ticks on the x-axis mark the peaks of the wet and dry seasons.
In contrast, larger fluctuations in PIM are generated by the shifting age distribution in fluctuating mosquito populations. Adults emerge uninfected, but they become infected some time after biting infectious humans. Growing populations are dominated by young, uninfected mosquitoes, while shrinking populations are dominated by older mosquitoes. Since the proportion of mosquitoes that are infected and infectious increases with the age of the mosquito, PIM is a proxy for the age distribution of mosquito populations. As populations decline, surviving mosquitoes continue to bite and oviposit but few young mosquitoes emerge, so declining populations have a larger fraction of old mosquitoes. Thus, PIM increases during the dry season as mosquito populations, HBR, and EIR decline.
Spatial Heterogeneity
The distribution of adults is determined by the distribution of larval habitat, the distribution of blood hosts, and the alternating activities of blood-meal-seeking and oviposition. When mosquito emergence rates and human population distributions are constant over time, the distribution of mosquitoes reaches a static spatial distribution. We focus on the patterns that form along a transect.
In Figure 2, we assume a single point source for mosquitoes and a homogeneous distribution of humans. In Figure 3, the same number of adult mosquitoes emerges, but the spatial distribution of larval emergence is uniform along the transect and the distribution of humans varies: human density is low at one end, high at intermediate locations, and intermediate at the opposite end, approximating a small town with fewer dwellings on the edge nearest a swampy area. In Figure 4 we combine the two kinds of spatial heterogeneity.
Figure 2 Statics with Homogeneous Humans and Heterogeneous Mosquitoes
The components of EIR follow different trends when larval habitat is distributed at a single point and humans are uniformly distributed (the gray background illustrates the human distribution).
(A) Mosquito density (solid) declines monotonically, but PIM (dashed) increases monotonically. The density of infected mosquitoes (Z, dotted) also declines monotonically.
(B) HBR (solid) and EIR (dashed) both decline monotonically away from the source, reflecting the steep gradient in mosquito density.
(C) The density of infected humans (dashed) and prevalence of infection in humans (solid) also decline monotonically (the curves coincide).
Figure 3 Statics with Heterogeneous Humans and Homogeneous Mosquitoes
HBR and EIR reflect mosquito movement and human distribution patterns when larval habitat is evenly distributed but humans have a low–high–medium distribution, such as a town with rural and suburban populations on either side (the gray background illustrates the human distribution).
(A) Mosquito density (solid) is highest in town, peaks at the edges of town, and dips just outside of town. PIM (dashed) and the density of infected mosquitoes (Z, dotted) follow similar patterns.
(B) HBR (solid) and EIR (dashed) are both high on the low-density side of town and lowest on the medium-density side of town, with peaks just inside town and troughs just outside of town.
(C) The density of infected humans (dashed) and the prevalence of infection in humans (solid) peak at the edge of town, but prevalence of infection in humans is less variable than HBR or EIR.
Figure 4 Statics with Heterogeneous Humans and Mosquitoes
When human density increases smoothly away from a larval habitat (the gray background illustrates the human distribution), the patterns of EIR components reflect heterogeneity in the distribution of larval habitat and human populations.
(A) Mosquito density (solid) peaks an intermediate distance away from the source. The peak density of infected mosquitoes (Z, dotted) is further from the source because PIM (dashed) increases monotonically away from the source.
(B) HBR (solid) decreases monotonically away from the source, reflecting mosquito density, but EIR (dashed) has a minor peak away from the source.
(C) The density of infected humans (dashed) peaks away from the source, but the prevalence of infection in humans (solid) remains relatively constant near the source, dropping off sharply further away.
Gradients in EIR Away from Larval Habitat
When mosquitoes emerge from a point source, the density of mosquitoes tends to decline with distance from larval habitat, such as a gradient along a transect away from a swamp or river (Figure 2A). The shape of the gradient is determined by the emergence rate of adult mosquitoes, the mortality of existing mosquitoes, and random drift away from the source. In contrast, PIM increases monotonically away from the source because of a shift in the age distribution and parity of mosquitoes (Figure 2B). Young mosquitoes tend to be close to their birthplace because they have moved less; older mosquitoes have moved more and so are dispersed further from the source, on average. The spatial distribution of HBR and EIR reflect the gradients in mosquito density, not the gradient in PIM (Figure 2A and 2B). The prevalence of infection in humans declines monotonically with distance from the mosquito source (Figure 2C).
Heterogeneous Distributions of Humans
When human populations are distributed heterogeneously, but the larval habitat of mosquitoes is distributed uniformly, adult mosquito distributions become heterogeneous because mosquitoes tend to aggregate around humans. Whether this leads to an increase in HBR depends on whether mosquito distributions become more aggregated than the distribution of their human hosts. HBR tends to increase when searching mosquitoes move rapidly through sparse human populations and linger in areas with dense human populations. Thus, mosquito distributions tend to become more aggregated than human distributions when the mosquito species is long-lived with long daily flight distances (see below).
We illustrate this principle for one particular set of parameters that leads to increased mosquito aggregation. The human population is distributed heterogeneously in blocks of low, high, and medium density, approximating a town with a rural population on one side and an intermediate-density population on the other. The distribution of adult mosquitoes is influenced by the distribution of humans (Figure 3A). Aggregations of mosquitoes form spontaneously at the edges of human settlements simply because mosquitoes tend to move until they find a host. We note that the major peaks in HBR are away from town, where human population density is lowest, and at the edge of town, where human population density is highest (Figure 3B). EIR also peaks at the edge of town, but it is lowest on the low-human-density side of town. With these movement rules, the mosquitoes found on the side of town with low human density tend to be younger, hence PIM is low (Figure 3A). The prevalence of infection in humans is lowest overall in the patches with low human density (Figure 3C). This model also makes the surprising prediction that the risk of infection is lowest just outside the edge of town: the sharp difference in human density at the edge leads to a strong tendency for mosquitoes to be drawn into, rather than away from, town, decreasing HBR and PIM (Figure 3B and 3C).
Heterogeneous Larval Habitat and Human Population
When mosquitoes and humans are distributed unevenly, the distribution of mosquitoes and risk may be dominated either by proximity to larval habitats and gradients away from them or by the tendency of mosquitoes to aggregate around humans. The realized pattern depends on the relative distribution of larval habitat and humans, and whether mosquito aggregation around humans increases HBR. We illustrate one kind of pattern for parameters that lead to increased HBR. In this case, human density increases away from larval habitat. The density of mosquitoes peaks a short distance from the source, and the density of infected mosquitoes peaks slightly further away (Figure 4A). HBR declines monotonically away from the source, but EIR peaks at an intermediate distance (Figure 4B). The density of infected humans peaks well away from the source, but the fraction of infected humans remains relatively constant near the source, declining abruptly at distances beyond the peak in infected humans (Figure 4C). Despite the sharp peaks in risk, PIM displays a robust monotonic increase with distance away from the source (Figure 4A). If the gradient is reversed, so that human density decreases with the distance away from larval habitat, mosquitoes remain close to the source and mosquito aggregation is exaggerated, compared with Figure 2 (data not shown).
Measuring EIR in Heterogeneous Environments
Variability in EIR across a landscape can lead to systematic bias in the estimation of risk. In Figure 5, we plot local EIR and its components against the local prevalence of infection in humans for the individual patches in Figures 2–4. We also plot the average EIR for each transect. In addition, we overlay the temporal patterns from Figure 1 as a phase diagram. We note that local EIR and local prevalence of infection in humans at equilibrium,
x¯, have a clear nonlinear relationship given by the following formula:
Figure 5 The Relationship between EIR and Human Prevalence, with Heterogeneity
(A) EIR and the prevalence of infection in humans have a tidy relationship among patches; each small symbol is from a single patch in Figures 2–4. The relationship, given by equation 1, is plotted in gray. The phase plane of the dynamic relationship over time from Figure 1 is plotted with dashed lines. Average EIR is plotted against the average prevalence (large symbols). Predicting the average prevalence of human infection from average EIR leads to underestimates.
(B–D) The density of infectious mosquitoes (Z) (B), HBR (HBR = aM/H) (C), and PIM (PIM = Z/M) (D) are plotted against the proportion of humans who are infected and infectious. PIM is a particularly bad measure of the risk of infection; in heterogeneous habitats, it peaks far from larval habitat, where mosquito density and prevalence of infection in humans is lowest. This accounts for the large number of points where PIM is high, but the proportion of infectious humans is low.
In contrast, the relationship between average EIR and average prevalence of infection in humans is biased, such that average prevalence always falls below the true relationship (Figure 5A). The bias is due to an inherent mathematical property of nonlinear relationships known as Jensen's inequality (Krantz 1999). Since the relationship between EIR and the prevalence of infection in humans is concave down, aggregating estimates of EIR in variable habitat will always underestimate the true relationship, sometimes spectacularly (Ruel and Ayres 1999).
The local density of infectious mosquitoes (Figure 5B) and the local HBR (Figure 5C) provide reasonably good estimates of risk. In both cases, spatial heterogeneity in human density or PIM is a substantial source of variability in measures of average risk. In contrast, PIM displays no clear pattern along the transect (Figure 5C). The patches in which PIM is high but the prevalence of infection in humans is low are all far from larval habitat.
Sensitivity Analysis
The patterns illustrated in Figures 2–4 are based on a single set of entomological parameters in order to facilitate comparisons among situations in which only the distributions of mosquitoes and hosts vary. The distribution of risk will change for different values of the parameters. We explored the effects of mosquito movement and the duration of the incubation period on the distribution of risk (below and Protocol S1).
The tendency of mosquitoes to aggregate at the edges of a town or away from larval habitat depends on mosquito searching behavior and demography. Three important parameters that affect these patterns are the maximum daily flight distance of a mosquito, mosquito longevity, and mosquito searching efficiency. The distribution of a mosquito cohort initially reflects the distribution of larval habitat. As mosquitoes search for hosts, the distribution of the cohort shifts to reflect the distribution of human hosts. These tendencies are also reflected in the static spatial distributions of mosquitoes. The distribution of long-lived mosquitoes with long daily flight distances will tend to reflect the underlying distribution of humans, while the distribution of short-lived mosquitoes with short flight distances will tend to reflect the distribution of larval habitat. Mosquito searching efficiency determines the relative rates of movement through habitats that vary in human density. A strong tendency for mosquitoes to aggregate at the edges of dense human populations occurs when mosquitoes move quickly through areas that are sparsely populated by humans and linger in areas that are heavily populated. In other words, mosquitoes tend to become more aggregated than their hosts, increasing HBR, when mosquito searching is relatively inefficient at low human densities.
The distribution of relative risk also changes with the time required for incubation of the infectious agent, with mechanically transmitted agents at one extreme. When all else is equal, HBR is higher in areas in which human density is low, since human population density is in the denominator of HBR. On the other hand, HBR may decline in low-human-density areas because mosquitoes tend to move up a gradient of human population density in search of a blood-meal host. Such migration will tend to lower the average age of mosquitoes in low-human-density patches, especially near the edge of a town. This will tend to lower PIM for infectious agents with a long incubation period. In contrast, PIM for mechanically transmitted infectious agents will not be as strongly affected, so in comparison, the relative risk may be higher at that same edge of town.
Discussion
EIR is generally considered to be the best estimate of the risk of mosquito-borne infections, but EIR varies over space and time. EIR varies spatially because larval habitat and blood-meal hosts are heterogeneously distributed across a landscape. Temporal variability is generally driven by weather, especially rainfall, temperature, and humidity. To compound the problem, heterogeneity in human feeding over short distances can be caused by vector preferences for individual humans based on odor or other cues (Takken and Knols 1999; Kelly 2001). Heterogeneous biting has important implications for the dynamics and control of mosquito-borne infections (Dietz 1980; Dye and Hasibeder 1986; Woolhouse et al. 1997).
Heterogeneous biting also has important implications for the measurement of EIR. Estimates of EIR may vary substantially over short distances depending on the place and time at which the measurement is made. Depending on the method used, EIR may also vary with the relative attractiveness of the human bait. Our mathematical models have shown that average EIR in heterogeneous environments gives a strongly biased estimate of average risk, even when local estimates of EIR provide a perfect measure of local risk. The bias is unavoidable because the relationship between EIR and the proportion of humans who are infected is nonlinear, which leads to a bias due to Jensen's inequality (Krantz 1999). A similar bias is likely to arise when estimating risk for other infectious diseases, a problem that is pervasive and generally underappreciated in epidemiology and public health (Ruel and Ayres 1999). Therefore, mathematical models are an indispensable tool for the design and interpretation of field studies (Becker 1989).
Mathematical models provide a sound approach to understanding risk and planning for control in heterogeneous environments, especially when the models are based on the ecology of the local vector populations and a sound understanding of the entomological parameters relevant for transmission (Killeen et al. 2000a, 2000b). Creating micro-epidemiological maps for the distribution of risk would involve mapping larval habitat and humans, and combining these maps with an understanding of the temporal dynamics, blood-meal-seeking behavior, and oviposition habits of mosquitoes. A critical assumption of the models described here is that mosquitoes are able to oviposit everywhere. Vector species may be very selective about where they oviposit, forcing a return to larval habitat to oviposit between successive bites. Thus, the heterogeneous distribution of oviposition sites may also affect the distribution of risk.
A dominant component of EIR is the density of mosquito vectors relative to human density. Our models show that mosquito densities and the proportion of humans who carry a mosquito-borne infection decline with distance away from larval habitat because of random movement and mosquito mortality. Such patterns have been documented by numerous field studies (Trape et al. 1992; Hii et al. 1997; Charlwood et al. 1998; Clarke et al. 2002; Minakawa et al. 2002; Keating et al. 2003; Staedke et al. 2003; Konradsen et al. 2003; van der Hoek et al. 2003). The steepness of the gradient in EIR varies, depending on the ecology of the vector (Hii et al. 1997).
Unlike the patterns in human biting, the proportion of mosquitoes that are infectious depends on the age structure of the mosquito population. The likelihood of infection in mosquitoes shows a strong association with the age or parity of mosquitoes (Lines et al. 1991). The average age differs in growing, stable, and declining populations (Aron and May 1982). Our models also predict that the proportion of infectious mosquitoes increases monotonically with the distance away from sources of emerging adults; young, pre-gravid mosquitoes are found more frequently near larval habitat, while older mosquitoes are found further away. Such patterns have also been observed in the field (Charlwood et al. 1998).
Mosquito aggregation around dense human populations depends on the details of mosquito searching behavior. Long-lived mosquitoes with long flight distances tend to become more aggregated than their human hosts over intermediate distances. For example, EIR may peak at the edges of a village, as has been documented by one field study (Ribeiro et al. 1996). At larger spatial scales, increasing human density may decrease EIR; one field study concluded that human density was protective against disease (Snow et al. 1998). We have emphasized heterogeneous biting that arises from proximity to larval habitat and from mosquito aggregation due to blood-meal-seeking behavior. In our models, aggregation is generated by the tendency of mosquitoes to migrate more slowly when blood-meal hosts are readily available. Aggregation in human biting may be enhanced if mosquitoes fly toward humans that are more attractive at medium and long distances (Ansell et al. 2002; Mukabana et al. 2002). It remains to be seen how these factors interact; for instance, at what distances are preferred hosts more attractive to mosquitoes (Ansell et al. 2002)?
The use of remote sensing and GIS provides a potentially powerful tool for understanding the distribution of mosquito-borne infections at large spatial scales, but dynamics and control of mosquitoes and mosquito-borne infections occur locally. These technologies will be most effective if they are coupled with micro-epidemiological models of malaria, dengue, and other mosquito-borne infections (Greenwood 1989). Such models can predict variability in local risk based on the distribution of larval habitat, the distribution of humans, and the demography and behavior of the local vectors. To generate realistic predictions for the distribution of risk, it is necessary to understand where and when adult mosquitoes will emerge, and how blood-meal-seeking and the distribution of humans will affect the distribution of HBR. It follows that a knowledge of mosquito demography and behavior should play a central role in the surveillance and control of mosquito-borne infections.
Materials and Methods
We use mathematical models strategically, to illustrate general principles that may apply to many mosquito-borne infections, not to make predictions about the distribution of a particular infectious agent or the incidence of disease. The models we present and analyze are based on the models for malaria infection developed by Ross (1911). We generate a suite of complex models by elaboration, adding a realistic incubation period, temporal heterogeneity, mosquito movement, patchy space, and spatial heterogeneity (Black and Singer 1987). By comparing models, we associate an effect with a factor. First, we allow mosquito birth rates to vary temporally, and focus on the temporal changes in the components of EIR (Aron and May 1982). Next, we illustrate how spatial variability in the distribution of larval habitat generates source–sink relationships in landscapes and leads to variability in the spatial distribution of HBR and PIM. Then, we explore the consequences of heterogeneous human distributions. Host-seeking behavior by mosquitoes can produce mosquito distributions that are more (or less) aggregated than the distribution of humans, generating an uneven distribution in risk. Thus, we develop conceptual models to illustrate which components of the vector biology determine the distribution of risk.
The model
Let x denote the proportion of humans who are infected and infectious and H denote the population density of humans. We assume that the human infectious period is exponentially distributed with average duration of infection 1/r. Thus, we are following Ross in developing a model for infection ignoring superinfection, immunity, and clinical disease (Fine 1975; Aron and May 1982; Cohen 1988; Dietz 1988).
We extend the Ross model by adding temporal variability in mosquito density. Let ɛ(t) denote the rate adult female mosquitoes emerge from larval habitat; we do not assume that the emergence of adults is explicitly linked to the density of adult mosquitoes. Let M denote the population density of mosquitoes, Z the density of infectious mosquitoes, and z = Z/M the proportion of mosquitoes that are infectious. We assume that the mosquito lifespan is exponentially distributed with a mean lifetime of 1/g d.
We incorporate a realistic incubation period by subdividing the incubation period into n stages of equal duration; the proportion of mosquitoes that are infected and incubating in stage k is denoted yk, and the density of mosquitoes in that stage is Yk. We assume the incubation period has mean of 1/q d. The probability of surviving the incubation period is (qn/(qn + g))n (approximately e
−g/q for large n), and the duration of the incubation period (for surviving mosquitoes) has a Gamma distribution with mean 1/q and variance 1/(q
2
n); for the numerical simulations, we use n = 64 (Protocol S1). The larger n is, the smaller the variance is. In the limit as n approaches infinity, the dynamics approach a fixed time delay.
Let a denote the human feeding rate, the number of human bites per mosquito per day, b denote the probability an uninfected human becomes infected from a single bite from an infectious mosquito, and c denote the probability that a mosquito becomes infected from biting an infectious human host.
The transmission dynamics of mosquito-borne infections are complex, and it is easy to lose sight of what terms such as EIR and HBR actually mean. HBR is the number of bites received by a human each day. Thus, it is the product of the human feeding rate, a—the number of human blood meals per mosquito per day—and the number of mosquitoes per human (i.e., HBR = aM/H). Therefore, when mosquito density changes, HBR changes proportionally. In contrast, EIR is the number of infectious bites per human per day. Thus, it is the product of PIM and HBR (i.e., EIR = zHBR = azM/H). Table 1 lists variable and parameter names and other important terms for the models.
Table 1 Variables and Parameters Used in the Model
The dynamic process is embedded into a spatial context by subdividing a landscape into a set of patches linked by the movement of mosquitoes. The subscript i is added to variable names to denote the value in the i
th patch. Thus, Hi denotes local human population density and xi the local prevalence of infection in humans. Similarly, Mi denotes local mosquito population density, and Zi denotes the density of infectious mosquitoes. The density of infected mosquitoes in patch i and incubation stage k is denoted Yi,k. This deterministic approach to incorporating space has some limitations (Mollison 1984, 1986; Durrett and Levin 1994a, 1994b).
Larval habitat and human distributions form a template that determines mosquito distributions and the distribution of risk. The emergence rate of adults in the i
th patch is ɛi(t); the emergence of adult female mosquitoes depends predictably on time and location. Following emergence, female mosquitoes spread into surrounding areas seeking blood hosts; they feed, oviposit, and then repeat the cycle. We assume that heterogeneity in larval habitat takes the form of differences in quality of larval development rather than availability of places to oviposit. In other words, we assume that suitable sites for oviposition are distributed homogeneously throughout the habitat, but that patches may vary in the successful development of adults. Some patches may produce no adults. Heterogeneity in the availability of oviposition habitat would affect the distribution of risk because mosquitoes would alternate between finding a place to oviposit and finding a blood meal. If oviposition were not possible in most patches, those that allowed oviposition would become focal points for mosquito aggregation. Thus, these results apply mainly to mosquito species for which heterogeneous availability of oviposition sites is relatively unimportant for the distribution of risk.
We assume that humans do not move among patches. The density of humans and the productivity of the larval habitat may vary over space. As we change the distribution of humans and larval habitat to explore the effects of spatial heterogeneity, we hold the total emergence rate of adult mosquitoes per human constant; only the distribution of humans and adult mosquito emergence changes.
We assume that mosquitoes are more likely to stay in a patch if they encounter a human, and that they are more likely to find humans where humans are more abundant. Let Φ(Hi) denote the per capita emigration rate of mosquitoes away from patch i regardless of infection status. We assume that Φ(H) is a decreasing function of H; the more humans, the less likely mosquitoes are to leave a patch in search of another blood-meal host. Thus, mosquitoes move more rapidly through patches with low human densities. A parameter, κi,j, describes the fraction of mosquitoes leaving patch i that fly to patch j, and Σjκi,j = 1. Thus, the rate that mosquitoes move from patch i to patch j is Φ(Hi)κi,jMi.
The transmission dynamics are described by the following set of equations:
This patch-based modeling framework is suitable for modeling an array or grid of contiguous habitat or an arbitrary network of patches.
Numerical solutions
Our intent is to focus on the effects of temporal and spatial heterogeneity. Consequently, we have used a single set of mosquito life-history parameters and a single duration of infection in humans. The parameters are roughly consistent with Anopheles gambiae and the infectious period for malaria (a = 0.3; b = c = 0.5; 1/g = 1/q = 10 d). The human infectious period for this case is 100 d (r = 0.01), roughly consistent with malaria.
Constant mosquito populations were modeled using a constant birthrate, ɛi(t) = Kig, while temporal heterogeneity was modeled using the seasonal forcing function ɛi(t) = Kig(1 sin(2πt/365)). In a homogeneous landscape, Ki is the long-term average density per patch, often called the carrying capacity. Throughout, K was chosen such that the average number of mosquitoes per human across all patches was 2, i.e., Σi
Mi/Σi
Hi = 2. Figure 1 was generated using a single patch. Initial conditions were x = 0.01 and Yi,k = Zi = 0. We generated numerical solutions for 4 y and plotted the last three.
For Figures 2–4, we focused on the relatively simple patterns that form along a spatial transect, a linear array of seventeen patches that can be thought of as a long, rectangular island. We have assumed that κi,j = 0 unless two patches are adjacent, and we plot the values at equilibrium. We assume that no humans live in the patches at the extreme ends of the transect, and that all of the mosquitoes leaving one of these edges return to the adjacent patch; thus κ1,2 = κ17,16 = 1, a reflective boundary. Otherwise, we assume that mosquitoes move in either direction at random; thus, κi,j = 0.5 for i = 2…16 and j = i ± 1. Mosquito migration was described by the function
Φ(Hi) = ζe
−θHi. In Figures 2–4, we used ξ = 10 and θ = 4. These correspond to a maximum daily flight distance (i.e., without humans) of about ten patches per day.
Adult mosquito emergence for Figures 2 and 4 was gK(P − 2) in patch 1 (K = 2 and P = 17); no adults emerged within other patches. The adult emergence rate for Figure 3 was gK in each patch with humans (K = 2 in patches 2–16).
For Figure 2, human density was 1.0 in patches 2–16. For Figure 3, human density was 0.2 in patches 2–6, 1.8 in patches 7–11, and 1.0 in patches 12–16. For Figure 4 human density was (0,1,2,3,…,15,0)/120. Otherwise, the parameters were the same as in Figure 1.
Supporting Information
Protocol S1 Additional Methods
(285 KB PDF).
Click here for additional data file.
We thank Rebecca Freeman Grais, Gerry Killeen, and Peter Billingsley for discussion and comments.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. DLS developed and analyzed the model. DLS, JD, and FEM wrote the paper.
Academic Editor: Andy P. Dobson, Princeton University
Citation: Smith DL, Dushoff J, McKenzie FE (2004) The risk of a mosquito-borne infection in a heterogeneous environment. PLoS Biol 2(11): e368.
Abbreviations
HBRhuman biting rate
EIRentomological inoculation rate
PIMproportion of infectious mosquitoes
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| 15510228 | PMC524252 | CC0 | 2021-01-05 08:21:17 | no | PLoS Biol. 2004 Nov 26; 2(11):e368 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020368 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1551022910.1371/journal.pbio.0020369Research ArticleNeuroscienceSystems BiologyPrimatesCaenorhabditisMotifs in Brain Networks Motifs in Brain NetworksSporns Olaf osporns@indiana.edu
1
Kötter Rolf rk@hirn.uni-duessseldorf.de
2
1Department of Psychology and Programs in Cognitive and Neural Science, Indiana UniversityBloomington, IndianaUnited States of America2C. and O. Vogt Brain Research Institute and Institute of Anatomy II, Heinrich Heine UniversityDüsseldorfGermany11 2004 26 10 2004 26 10 2004 2 11 e36914 4 2004 26 8 2004 Copyright: © 2004 Sporns and Kötter.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.
Only Connect: The Functional Architecture of Brain Connectivity
Complex brains have evolved a highly efficient network architecture whose structural connectivity is capable of generating a large repertoire of functional states. We detect characteristic network building blocks (structural and functional motifs) in neuroanatomical data sets and identify a small set of structural motifs that occur in significantly increased numbers. Our analysis suggests the hypothesis that brain networks maximize both the number and the diversity of functional motifs, while the repertoire of structural motifs remains small. Using functional motif number as a cost function in an optimization algorithm, we obtain network topologies that resemble real brain networks across a broad spectrum of structural measures, including small-world attributes. These results are consistent with the hypothesis that highly evolved neural architectures are organized to maximize functional repertoires and to support highly efficient integration of information.
Analysis of characteristic patterns of connectivity in neuroanatomical datasets suggests that nervous systems evolved to maximize functional repertoires and support highly efficient integration of information
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Introduction
The complex vertebrate brain has evolved from simpler networks of neurons over a time span of many millions of years. Brain networks have increased in size and complexity (Jerison 1973; Butler and Hodos 1996; Kaas 2000; Krubitzer 2000), as have the flexibility of interactions with the environment and the range of potential behaviors that can be generated (Changizi 2003). Most of the rules governing the evolutionary process toward more complex brains are still unknown, although the central roles of modularization (Kaas 2000), conservation of wiring length (Cherniak 1994; Chklovskii et al. 2002), and of the elaboration of network connectivity (Laughlin and Sejnowski 2003) are becoming increasingly evident.
Systematic investigations of neuronal connectivity in the nematode Caenorhabditis elegans (White et al. 1986) and of large-scale interregional pathways in the mammalian cerebral cortex of rat (Burns et al. 2000), cat (Scannell et al. 1995; Scannell et al. 1999; Hilgetag et al. 2000; Kötter and Sommer 2000), and macaque monkey (Felleman et al. 1991; Young 1993; Hilgetag et al. 2000; Stephan et al. 2000) have demonstrated that the topology of these networks is neither entirely random nor entirely regular. Instead, analysis of structural and functional data has shown (Hilgetag et al. 2000; Sporns et al. 2000; Stephan et al. 2000; Sporns and Zwi 2004) that these networks can be characterized by a high degree of clustering, with short path lengths linking individual components, thus exhibiting small-world properties (Watts and Strogatz 1998; Watts 1999) as do many other complex networks (Strogatz 2001; Albert and Barabasi 2002). These structural attributes are instrumental in generating functional specialization (Zeki 1978; Passingham et al. 2002) and functional integration (Bressler 1995; Tononi et al. 1998; McIntosh 2000; Varela et al., 2001; Friston 2002), and they support a large repertoire of complex and metastable dynamical states (Bressler and Kelso 2001; Sporns and Tononi 2002; Sporns 2004). Fluctuating and distributed patterns of dynamical interactions among functionally specialized areas result in rapid switches in functional and effective connectivity (McIntosh et al. 1999; Büchel and Friston 2000; McIntosh et al., 2003; Brovelli et al. 2004). The structural and functional anatomy of brain networks reflects the dual challenges of extracting specialized information and integrating the information in real time (Tononi and Sporns 2003).
What rules underlie the organization of the particular types of networks that we see in complex brains? It is likely that, as networks become more complex, already existing simpler networks are largely preserved, extended, and combined, while it is less likely that complex structures are generated entirely de novo. One hypothesis states that complex and highly evolved networks arise from the addition of network elements in positions where they maximize the overall processing power of the neural architecture. This could be achieved by increasing the number of existing processing configurations or by introducing new processing configurations that add to the robustness or range of cognitive and behavioral repertoires. We may gain insight into the rules governing the structure of complex networks by investigating their composition from smaller network building blocks. Those building blocks are called “motifs” (in analogy to driving elements that are elaborated in a musical theme or composition), and they have been examined in the context of gene regulatory, metabolic, and other biological and artificial networks (Milo et al. 2002; Milo et al. 2004). Motifs occur in distinct motif classes that can be distinguished according to the size (M) of the motif, equal to the number of nodes (vertices), and the number and pattern of interconnections. For a more formal definition of motifs and related concepts, see Materials and Methods.
While the most common definition of network motifs is based on their structural characteristics (Milo et al. 2002), structural motifs of neuronal networks form the physical substrate for a repertoire of distinct functional modes of information processing. In brain networks, a structural motif may consist of a set of brain areas and pathways that can potentially engage in different patterns of interactions depending on their degree of activation, the surrounding neural context or the behavioral state of the organism. Thus, we propose a distinction between structural and functional motifs. Structural motifs quantify anatomical building blocks, whereas functional motifs represent elementary processing modes of a network (Figure 1). In this paper, functional motifs refer to specific combinations of nodes and connections (contained within structural motifs) that may be selectively recruited or activated in the course of neural information processing. Sorting all possible structural motifs within a network as a function of motif class yields a motif frequency spectrum that records the number of distinct motifs in each structural motif class. Given the motif frequency spectrum, one can easily obtain the motif number, defined as the total number of distinct occurrences of any motif of size M, and the motif diversity, defined as the number of classes that are represented within the network by at least one example.
Figure 1 Definition of Structural and Functional Motifs, and Motif Detection
(A) From a network, we select a subset of three vertices and their interconnections, representing a candidate structural motif.
(B) The candidate motif is matched to the 13 motif classes for motif size M = 3. Numbers refer to the ID. The candidate motif is detected as a motif with ID = 13. In detecting structural motifs, only exact matches of candidate motif and motif class are counted.
(C) A single instance of a structural motif contains many instances of functional motifs. Here, a structural motif (M = 3, ID = 13) is shown to contain, for example, two distinct instances of the functional motif ID = 9, one motif ID = 2, and one motif ID = 7. Many other distinct instances of functional motifs are present that are not shown in the figure. Note that, in order to be counted as a functional motif of size M = 3, all three vertices of the original structural motif must participate. For a very similar distinction between structural and functional motifs (“interlaced circuits”) and an illustration see Ashby (1960), p. 53.
Clearly, the number of vertices (N) and edges (K) within a large network has a strong effect on the motif number and diversity of its constituent structural and functional motifs. But even if N and K are held constant, different connection patterns will result in different repertoires of such network motifs, expressed in terms of both number and diversity. These considerations lead us to formulate hypotheses concerning the rules for brain network organization in terms of network motifs. We hypothesize that neuronal networks have evolved such that their repertoire of potential functional interactions (functional motifs) is both large and highly diverse, while their physical architecture is constructed from structural motifs that are less numerous and less diverse. A large functional repertoire facilitates flexible and dynamic processing, while a small structural repertoire promotes efficient encoding and assembly.
We investigate this hypothesis first by performing an analysis of structural and functional motifs in various brain networks. We compare the motif properties of real brain networks with random networks and with networks that follow specific connection rules such as neighborhood connectivity (lattice networks). We identify some motif classes that occur more frequently in real brain networks, as compared to random or lattice topologies. Second, by rewiring random networks and imposing a cost function that maximizes functional motif number, network topologies are generated that resemble real brain networks across a broad spectrum of structural measures, including small-world attributes. The results of our analyses are consistent with the hypothesis that complex brain networks maximize functional motif number and diversity while maintaining relatively low structural motif number and diversity.
Results
Motif Frequency Analysis
We obtained complete structural motif frequency spectra for large-scale connection matrices of macaque visual cortex, macaque cortex, and cat cortex, for motifs sizes of M = 2, 3, 4, and 5 (estimations). In addition, we obtained motif frequency spectra for the matrix of interneuronal connections (“chemical synapses”) of C. elegans, for motif sizes M = 2, 3, and 4 (estimations). For each neural connectivity matrix we generated equivalent (N, K) random and lattice matrices, preserving degree distributions (n = 100; see Materials and Methods), and we obtained their structural motif frequency spectra for comparison. Thus, statistical significance of a motif can only be reached if it occurs in significantly increased proportions with respect to both random and lattice reference cases.
Table 1 summarizes the data for structural and functional motif number. Large-scale connection matrices exhibit a consistent statistical trend. Their structural motif number is relatively low, and their functional motif number is relatively high, with both measures approaching the corresponding values of lattice networks. All of these brain networks contain a very high proportion of connected motifs (e.g., 53.2% for M = 3 in macaque visual cortex versus 24.6% in corresponding random networks). All neuronal networks (all cortical networks and C. elegans) showed maximal functional motif diversity for all motif sizes examined (values of 2, 13, 199, and 9,364 for M = 2 to 5). Their structural motif diversity tended to be submaximal. For example, the structural motif diversity of macaque cortex was significantly reduced in comparison to random matrices (168, compared to 198 ± 1 for random networks at M = 4). This tendency was especially pronounced for higher values of M (e.g., 3,697 for macaque visual cortex, compared to 8,887 ± 112 for random networks at M = 5).
Table 1 Structural and Functional Motif Number for Cortical Connection Matrices and Corresponding Random and Lattice Matrices
Numbers are actual values (for real matrices) and mean and standard deviation (in parentheses, for random and lattice matrices, n = 100)
Figure 2 shows motif frequency spectra for structural motifs (M = 3, M = 4) found within the network of the macaque visual cortex and C. elegans and their corresponding reference cases. Spectra of macaque and C. elegans networks are both less similar to random networks than to lattice networks. For M = 3, in the case of the macaque visual cortex, some motif counts appear decreased over random networks (e.g., motif identity number [ID] = 1,…,6) while other motif counts appear increased (e.g., ID = 9) over both random and lattice networks. Table 2 and Figure 3A summarize structural motifs whose motif counts were significantly increased in brain networks as compared to both random networks and lattice networks of identical degree distributions, for sizes M = 2, 3, and 4. Given motif frequencies from samples of n = 100 random or lattice networks, we calculated z-scores for the corresponding motifs in neuronal networks. Only structural motifs that were significantly increased (z > 5.0, p < 0.0001) in real networks as compared to both random and lattice networks are tabulated. Despite variations in size, areal composition, species, and collating authors, specific motif classes consistently emerged across several different cortical networks. Figure 3 displays those structural motifs that were consistently encountered in all three cortical connection matrices. Particularly noteworthy is the consistent appearance of motif ID = 9 (M = 3) in all cortical matrices examined in this study. The appearance of this motif cannot be explained by a higher proportion of reciprocal (mutual) edges (a motif of size M = 2): While random networks contain fewer such edges, lattice networks contain an equally high proportion of such edges (for example, macaque visual cortex has 69 single edges and 121 double edges, while a sample of 100 comparison lattice networks contains 70.6 ± 4.71 single edges and 120.2 ± 2.36 double edges). No motif of size M = 2 was significantly increased in frequency for any of the connection matrices in this study (Table 2). Furthermore, other motifs containing double edges (e.g., ID = 6, 12, etc.) were not increased. A different set of significantly increased structural motifs was found for C. elegans. Motif ID = 9 was not significantly increased in frequency, while two other non-connected motifs (ID = 4 and 6) occurred more frequently than expected.
Figure 2 Comparison of Structural Motif Frequency Spectra for Macaque Visual Cortex and C. elegans
(A) Spectra for structural motifs of size M = 3.
(B) Spectra for structural motifs of size M = 4.
Figure 3 Structural Motifs that Occurred in Significantly Increased Numbers at Motif Sizes M = 3 and M = 4
(A) Structural motifs found in all three large-scale cortical networks analyzed in this study (see Table 2).
(B) Structural motifs found in networks optimized for functional motif number (see Table 4). Numbers refer to the motif's ID.
Table 2 Structural Motifs That Are Significantly Increased in Brain Networks
See Figure 3 for displays of the significant motifs (shown with their ID). Note that no significant differences are found for any of the networks at M = 2. Numbers are giving actual values (for real matrices) and mean and standard deviation (in brackets, for random and lattice matrices, n = 100). All z-scores > 5.0, with a single exception noted by asterisk (cat, M = 3, lattice)
Table 4 Significantly Increased Structural Motifs of Optimized Networks
Compare motif ID with those shown in Figure 3 and Table 2. As in Table 3, all networks were optimized for high functional motif number (M = 3, N = 30, K = 311, mean and standard deviation for n = 10 exemplars). Optimizations and comparisons of macaque and cat matrices produce similar results (unpublished data)
Table 3 Structural Motif Number and Networks Optimized for Functional Motif Number
All networks were optimized for high functional motif number (M = 3, N = 30, K = 311, mean and standard deviation for n = 10 exemplars)
Each vertex (brain area) participates in a subset of the structural motifs that compose the entire network. We asked whether individual brain areas participate in similar or different sets of motifs and whether motif participation might reveal functional relationships. We define the motif fingerprint of a brain area as the number of distinct structural motifs of size M that the area participates in. Motif fingerprints characterize brain areas, as do other structural and functional features (Passingham et al. 2002), and they are directly related to other connectional metastructures forming various kinds of network participation indices (Kötter and Stephan, 2003).
Figure 4 shows polar plots of motif fingerprints (M = 3) for several visual areas of macaque visual cortex. Motif ID = 9 was the only motif found to be significantly increased over both random and lattice networks, but it was increased for only five visual areas (V1, V3, V4, MSTd, and DP). All of these areas showed highly similar motif fingerprints characterized by a specific ratio of motif classes 9, 12, and 13 (Figure 4A and 4C). Other areas, such as V2, V4t, and PITv show very different motif fingerprints (Figure 4A), and cluster analysis reveals them as members of clusters of visual areas participating in a different set of motifs. For example, most inferotemporal areas as well as visually related prefrontal areas 46 and FEF belong to a separate cluster with motif fingerprints that differ significantly from those of all other cortical areas (Figure 4B).
Figure 4 Motif Fingerprints for Motif size M = 3 in Macaque Visual Cortex
(A) Motif fingerprints for five areas with significantly increased motif ID = 9 (V1, V3, V4, MSTd, DP, names in bold) as well as areas V2, V4t, and PITv. Polar plots display the motif participation number for 13 motif classes with M = 3 (see Figure 1). Note that, despite differences in the absolute motif participation numbers, areas V1, V3, V4, MSTd and DP show highly similar motif fingerprints.
(B) Hierarchical cluster analysis of motif fingerprints. The Pearson correlation coefficients between all pairs of motif fingerprints were used in a consecutive linking procedure using Euclidean distances based on the farthest members of each cluster (for details see Kötter and Stephan [2003]). Areas with more similar motif fingerprints are linked at smaller distances. The five areas with significantly increased motif ID = 9 are indicated in bold typeface.
(C) Hierarchical cluster analysis of single area motif frequency spectra using the same procedures on orthogonal data of (B). Motif classes 9, 12, and 13 covary across the 30 visual areas and form a distinct branch of the cluster tree.
Optimization of Motif Number
We hypothesized that high functional motif number and diversity represent important ingredients in the global organization of cortical networks, and that a selective advantage for these two properties might contribute to the generation of other significant structural properties. To test this hypothesis we applied an evolutionary algorithm (Sporns et al. 2000) that selects for networks with high functional motif number, while rewiring their connectivity. All simulations were carried out with networks of size N = 30, K = 311 (matching macaque visual cortex), in generations of 10 individuals, with a low rewiring rate of one connection per generation and a survivor rate of one network per generation, over 2,000 generations. Convergence was robust and consistent structural features of optimized connection matrices were observed.
Figure 3B, Figure 5, Table 3, and Table 4 summarize results obtained from the optimizations. When maximizing functional motif number (Figure 5A), we obtained networks that closely resembled real brain networks with respect to their structural and functional motif number, motif diversity (unpublished data), structural motif frequency spectrum, and the specific structural motifs that occurred with significantly increased frequency (Tables 3 and 4). Optimizing functional motif number invariably resulted in a significant decline in the number of structural motifs. Figure 3B illustrates the set of structural motifs that appeared in significantly increased numbers after optimizing functional motif number. Note the appearance of motifs that are identical or highly similar to those obtained from an analysis of large-scale cortical matrices. These structural similarities are observed for the motif size at which the networks were optimized (M = 3) as well as at lower and higher motif sizes (Table 4). In contrast, when maximizing structural motif number, we obtained networks with strikingly different structural attributes (Figure 5B) that bore no resemblance to real brain networks. We found no overlap with real networks of significantly enhanced motifs at any of the motif sizes we examined.
Figure 5 Properties of Networks (n = 10) Optimized for Structural and Functional Motif Number
(A) Maximization of functional motif number (N = 30, K = 311). Each maximization starts from different random initial conditions, including a different set of 10 random networks. From left to right, each graph shows plots of functional motif number, structural motif number, motif frequency spectrum (M = 3) of optimized networks, and clustering coefficient.
(B) Maximization of structural motif number (N = 30, K = 311). Graphs are as in (A). Compare the motif frequency spectrum in (A) with the corresponding plot for the macaque visual cortex in Figure 2A (first row, left bar graph). Initially, random networks in generation 1 exhibited frequency spectra identical to those for random networks in Figure 2A (first row, middle panel).
To further characterize these networks, we calculated their clustering coefficient and their path length to determine if they exhibited small-world properties (Figure 5). We found that networks that maximized functional motif number also had clustering coefficients that were much higher than those of random networks (γ = 0.5288 ± 0.0201 for optimized networks; γ = 0.4323 ± 0.0073 for random networks), while their path lengths remained relatively short (λ = 1.7891 ± 0.0275 for optimized networks; λ = 1.9300 for a nearest-neighbor lattice network). Both measures closely approximated those of macaque visual cortex (γ = 0.5313, λ = 1.7256). In contrast, networks that maximized structural motif number had clustering coefficients that were indistinguishable from those of random networks (γ = 0.4273 ± 0.0029), and were significantly lower than that of macaque visual cortex.
Discussion
The importance of a large repertoire of functional circuits for flexible and efficient neural processing has long been recognized (Walter 1953; Ashby 1960) and has recently received renewed theoretical and experimental attention (Tononi et al. 1999; Tononi and Sporns 2003). In this paper we investigate the building blocks of brain networks and how their composition and topological patterning enables flexible neural function. Our hypotheses and analysis rest upon a fundamental distinction between structural and functional motifs. In this work, functional motifs refer to the different patterns or combinations of nodes and connections that could occur within the constraints of a given structural motif. We do not assume anything about their function, or which functional motif is actually selected by physiological mechanisms. We only assume that a particular structural motif is necessary to support a repertoire of functional motifs that may, or may not, be called upon for neuronal computations. Our hypothesis is that the connection patterns of real brain networks maximize functional motif number and diversity, thus ensuring a large repertoire of functional or effective circuits, while they minimize the number and diversity of structural motifs, thus promoting efficient assembly and encoding. We observe that the functional motif number of a variety of real brain networks is very high compared to equivalent random networks, while their structural motif number is comparably low. We then demonstrate that optimization of functional motif number can yield networks that resemble real brain networks in several structural characteristics, including their motif frequency spectra, motifs that occur in significantly increased numbers, and small-world measures.
The functional implications of some network structures—such as reciprocal, convergent, and divergent connections or cycles—have been discussed in the context of network participation indices (Kötter and Stephan 2003) and network complexity (Sporns et al. 2000). Various large-scale cortical connection matrices examined in this study and collected by different authors and from different species, exhibit striking commonalities in their global patterning and motif compositions. Particularly interesting is the increased occurrence of a single motif at M = 3 (ID = 9; see Figure 3) and its expanded versions at M = 4 (ID = 46, 95, 148, 178). These motifs essentially form of a chain of reciprocally connected units, while pairs of connections linking the ends of the chain are absent. In functional terms, units in these motifs are highly integrated with their neighbors, while some pairs of units remain more segregated from each other and do not communicate directly. Thus, this motif type combines two major principles of cortical functional organization, integration and segregation (Tononi et al. 1998; Friston 2002), and it may be associated with a specific type of neural dynamics (Zhigulin 2003). The occurrence of this motif type is not due to an artifact of recording or collating connection pathways, as it also appears in increased proportion in optimized and rewired networks (see Table 4). In contrast to large-scale cortical networks, the invertebrate network of C. elegans exhibits very different patterns that are less indicative of high integration and segregation. At M = 3, motif ID = 9 does not occur in higher-than-expected numbers, while other motifs (ID = 4 and ID = 6) are increased. Our results suggest that large-scale cortical connection matrices form a distinct family (Milo et al. 2004) of networks that can be characterized by their motif frequency spectra, while invertebrate neuronal networks do not appear to belong to this family.
Optimizing functional motif number yields networks that resemble real brain networks across a broad spectrum of structural measures, including several that did not appear to be linked in trivial ways to the optimized measure. Increasing the functional motif number tends to lead to a concomitant decrease in structural motif number, as individual connections become locally dense, thus increasing the abundance of motifs with more local connections and thus greater functional diversity. We note that maximal numbers of functional motifs are not reached in ideal lattices (nearest-neighbor connectivity); rather, optimized networks routinely exhibit functional motif numbers that exceed those of ideal lattices, and they belong to a general class of networks that maintain a mixture of “local” and “long-range” connectivity. Importantly, even though structural and functional motifs are directly related (each structural motif contains a fixed set and spectrum of functional motifs), optimizing structural and functional motif number yielded strikingly different connection topologies.
Optimizing functional (but not structural) motif number produced a tendency toward the emergence of small-world attributes (high clustering coefficient and short path length), a mode of connectivity that promotes functional cooperation, recurrent processing, and efficient information exchange (Sporns et al. 2004). High clustering is due to “locally dense” connectivity promoting fewer, denser, and functionally more potent motifs. An admixture of “long-range” connections, which is compatible with achieving very high functional motif number, serves to maintain short minimal paths throughout the network. Interestingly, networks optimized for complexity (Tononi et al. 1994; Sporns et al. 2000) also exhibit small-world attributes, conserve wiring length, and produce motif frequency spectra similar to those of networks optimized for functional motif number (including a significantly increased abundance of motif ID = 9, M = 3; unpublished data). In turn, networks optimized for functional motif number have significantly higher complexity than random networks, while those optimized for structural motif number are much less complex. Thus, it appears that several criteria for optimality (complexity, clustering coefficient, wiring length, functional motif number) favor similar global network architectures that are all characterized by two coexisting organizational principles, functional segregation and functional integration. The functional motif frequency spectrum provides a sophisticated way of characterizing subtypes of such networks geared at more specific functional modes of information processing.
Materials and Methods
Formal definitions
All networks and network motifs in this paper are described as graphs of units (called nodes or vertices) with directed (i.e., nonsymmetrical) connections (called edges).
A “motif” is a connected graph or network consisting of M vertices and a set of edges (maximally M
2 – M, for directed graphs, minimally M – 1 with connectedness ensured) forming a subgraph of a larger network. For each M there is a limited set of distinct motif classes. For M = 2, 3, 4, and 5, the corresponding numbers of motif classes are 2, 13, 199, and 9,364 (Harary and Palmer 1973). See Figure 1B for an illustration of the set of 13 motif classes for motifs of size M = 3.
A “structural motif” of size M is composed of a specific set of M vertices that are linked by edges (Figure 1A). The resulting network of size M is called a “structural motif” because a larger network could be structurally assembled from a finite set of such motifs. Essentially, structural motifs form the structural building blocks of larger networks. Our definition of structural motifs is identical to the definition of motifs introduced in Milo et al. (2002).
A structural motif provides the complete anatomical substrate for possible functional interactions among its constituent vertices. However, in real neuronal networks, not all structural connections participate in functional interactions at all times. As different edges or connections become functionally engaged, different “functional motifs” emerge within a single structural motif. The former (functional) refers to “processing modes” or “effective circuits,” while the latter (structural) refers to “anatomical elements” or “building blocks.” The existence of different functional motifs greatly enhances the processing power of any neuronal architecture. We then distinguish structural motifs from functional motifs that form a set of subgraphs of the structural motif. All such functional motifs consist of the original M vertices of the structural motif, but contain only a subset of its edges (see Figure 1C for examples). Note that a fully connected structural motif such as ID = 13 for M = 3 contains the maximal number of functional motifs. For each exemplar of a structural motif of a specific motif class, there is a fixed complement of constituent potential functional motifs (essentially forming a look-up table of potential functional circuits). Thus, the functional motif frequency spectrum is easily obtained from the structural motif frequency spectrum, without the need for additional motif detection.
This definition implies that functional motifs are more naturally applied to networks with vertices that contain multiple neurons or neuronal populations. In the present study, our main focus is on motifs of large-scale connection matrices; data for the single neuron network of C. elegans are provided in Table 1 for statistical comparison only.
A “connected motif” is a structural motif that forms a strongly connected graph. In a connected motif, all constituent vertices can be reached from all other constituent vertices. Such a motif, in principle, allows all vertices to exert causal effects on each other. For M = 3, motifs with ID = 7, 9, 10, 12, and 13 are connected motifs.
A “motif frequency spectrum” records the number of occurrences of each motif of a given class for a size M. The motif frequency spectrum for structural motifs is obtained by motif detection. The motif frequency spectrum for functional motifs can be obtained from the structural spectrum by simple multiplication with the characteristic number of functional motifs for the respective structural motif.
“Motif number” is the total number of all motifs of all classes (for a given size M) encountered in a network. The motif number is obtained as the sum over the motif frequency spectrum, either structural or functional.
“Motif diversity” is the total number of all motif classes (for a given size M) encountered in a network. The motif diversity is obtained as the number of all motif classes for which the frequency spectrum is greater than zero.
“Motif participation number” is the number of instances of a given motif class that a particular vertex participates in. For example, if a vertex participates in 12 distinct motifs with M = 3, ID = 13, it has a motif participation number of 12 for this particular motif.
The “motif fingerprint” is the spectrum of motif participation numbers for all motifs of a given size M that a particular vertex participates in. The motif fingerprint is equivalent to a motif frequency spectrum for a single vertex of the network.
Neurobiological data sets.
All datasets used in this study are available in Matlab format at http://www.indiana.edu/~cortex/CCNL.html. Some of the matrices used in this study have been modified to remove areas with few known connections, or areas that are not part of the cerebral cortex. We note, however, that the nature of the data reported in this paper does not critically depend on these small changes, which usually affected only very small subset of the areas and connections. The connection matrix of the macaque visual cortex is based on Felleman et al. (1991), and was modified as follows. The connections of areas {PITd, PIT, PITv}, {CITd, CIT, CITv}, and {STPp, STP, STPa} were consolidated by eliminating PIT, CIT, and STP and assigning their connections to {PITd, PITv}, {CITd, CITv}, and {STPp, STPa}, respectively. Areas MIP and MDP were eliminated due to lack of connectional information. The modified matrix has N = 30 and K = 311. The connection matrix of the macaque cortex is based on Young (1993). Two areas, HIPP (the hippocampus) and AMYG (the amygdala) were deleted from the matrix, resulting in N = 71 and K = 746. The connection matrix of cat cortex was transcribed from Scannell et al. (1999). For the large-scale analysis, density information was discarded and all pathways were encoded as either present or absent. For the analysis of intracortical pathways, we discarded the hippocampus and all thalamocortical pathways. The resulting matrix has N = 52 and K = 820. The connection matrix of C. elegans (White et al. 1986) was retrieved from http://www.wormbase.org and is described at http://elegans.swmed.edu/parts/neurodata_readme.txt. It contains data for the nerve ring and very anterior section of the ventral cord for two individual hermaphrodite worms (JSH, N2U). We used data of all chemical synapses from both individuals, discarding data on gap junctions (electrical synapses), resulting in a matrix of N = 197 neurons and K = 1,974 directed connections. Other studies used matrices with N = 282 (Watts and Strogatz, 1998), N = 280 (Milo et al., 2004), or N = 252 (Milo et al., 2002). Despite these variations, our results on motifs in C. elegans are consistent with those of these earlier studies.
Currently available datasets are likely to contain errors or missing connections that have not been investigated and do not take into account possible intersubject variability or rank-ordered or graded connection densities or strengths. While these issues have not been addressed systematically, some exploratory analyses suggest that the results reported in this paper are invariant with respect to small variations in connection patterns.
Reference cases: random and lattice networks.
A statistical evaluation of motif frequencies depends on a choice of reference cases (“null hypotheses”). Milo et al. (2002) generated random networks with identical structural motif frequencies at level M – 1 in order to perform statistical comparisons at level M. This corrected for the “carrying over” of significant motif components from lower to higher levels and allowed detection of the level of M at which significant structures emerged. The choice of reference cases in this paper reflects the specific question we ask about motifs in brain networks: Independent of the level M, how do the motif number, diversity, and composition of real brain networks compare to other network topologies, specifically to both random and lattice networks? We constrain the comparison by fixing the size of the networks (N and K) and by imposing equal degree distributions on all comparison networks (see also Milo et al. 2004). We note that the additional reference case of the lattice network led to the exclusion of motifs that occur in increased numbers simply because of local clustering of connections (Artzy-Randrup et al. 2004; Milo et al. 2004a).
Random and lattice matrices that preserve the in-degree and out-degree for each vertex are generated from the original anatomical connection matrices by a Markov-chain algorithm (Maslov and Sneppen 2002; Milo et al. 2002). For random matrices, a pair of vertices (i
1,j
1) and (i
2,j
2) is selected for which ci
1j1 = 1, ci
2j2 = 1, ci
1j2 = 0, and ci
2j1 = 0. Then we set ci
1j1 = 0, ci
2j2 = 0, ci
1j2 = 1, and ci
2j1 = 1. This is repeated until the connection topology of the original matrix is randomized.
For lattice matrices, the same Markov procedure is employed but swaps are only carried out if the resulting matrix has nonzero entries that are located closer to the main diagonal (thus approximating a lattice or ring topology). This algorithm is implemented as a probabilistic optimization using a weighted cost function.
Numerical methods.
All graph theory methods used in this paper—including those for calculating clustering coefficients and path lengths (Sporns 2002)—as well as motif detection algorithms are available in Matlab format at http://www.indiana.edu/~cortex/CCNL.html. In some cases, for large networks or high values of M, we employed random sampling to estimate motif frequency spectra and their associated values for motif number and diversity. We selected different sample sizes to ensure convergence of these estimates and performed up to ten separate runs to generate good estimates. The evolutionary algorithms used in this study for optimizing structural and functional motif numbers of networks were similar to the algorithm described in Sporns et al. (2000). Briefly, motif number was calculated for generations of ten individuals. The single individual with the highest motif number was selected and copied; all other individuals were deleted. The next generation was composed of the single survivor and nine rewired copies (using a rewiring rate of one connection). The first generation was composed of ten random networks. The rewiring procedure typically proceeded for 2,000 generations, changing only the connection pattern or topology. N, K, and the original degree distribution were conserved.
We thank John Tuley (supported through Indiana University's Science, Technology, and Research Scholar's Program) for help in implementing motif detection algorithms. This work was supported by US government contract NMA201–01-C-0034 to OS, and DFG GRK 320 and Forschungskommission, Medizinische Fakultät, HHU Düsseldorf to RK. The views, opinions, and findings contained in this paper are those of the authors and should not be construed as official positions, policies, or decisions of NGA or the US government.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. OS and RK conceived and designed the experiments. OS and RK analyzed the data. OS and RK contributed reagents/materials/analysis tools. OS and RK wrote the paper.
Academic Editor: Karl J. Friston, University College London
Citation: Sporns O, Kötter R (2004) Motifs in brain networks. PLoS Biol 2(11): e369.
Abbreviations
IDmotif identity number
Knumber of edges
Mmotif size
Nnumber of vertices
==== Refs
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| 15510229 | PMC524253 | CC BY | 2021-01-05 08:28:08 | no | PLoS Biol. 2004 Nov 26; 2(11):e369 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020369 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1551023010.1371/journal.pbio.0020383Research ArticleEcologyEvolutionZoologyBirdsMeasuring Global Trends in the Status of Biodiversity: Red List Indices for Birds Red List Indices for BirdsButchart Stuart H. M stuart.butchart@birdlife.org
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Stattersfield Alison J
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Bennun Leon A
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Shutes Sue M
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Akçakaya H. Resit
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Baillie Jonathan E. M
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Stuart Simon N
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Hilton-Taylor Craig
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Mace Georgina M
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1BirdLife InternationalCambridgeUnited Kingdom2Applied Biomathematics, SetauketNew YorkUnited States of America3Institute of Zoology, Zoological Society of LondonLondonUnited Kingdom4CI/CABS-IUCN/SSC Biodiversity Assessment Unit, Center for Applied Biodiversity Science, Conservation InternationalWashington, District of ColumbiaUnited States of America5IUCN Red List Programme, IUCN/SSC United Kingdom OfficeCambridgeUnited Kingdom12 2004 26 10 2004 26 10 2004 2 12 e38325 5 2004 10 9 2004 Copyright: © 2004 Butchart 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.
Taking Stock of Biodiversity to Stem Its Rapid Decline
The rapid destruction of the planet's biodiversity has prompted the nations of the world to set a target of achieving a significant reduction in the rate of loss of biodiversity by 2010. However, we do not yet have an adequate way of monitoring progress towards achieving this target. Here we present a method for producing indices based on the IUCN Red List to chart the overall threat status (projected relative extinction risk) of all the world's bird species from 1988 to 2004. Red List Indices (RLIs) are based on the number of species in each Red List category, and on the number changing categories between assessments as a result of genuine improvement or deterioration in status. The RLI for all bird species shows that their overall threat status has continued to deteriorate since 1988. Disaggregated indices show that deteriorations have occurred worldwide and in all major ecosystems, but with particularly steep declines in the indices for Indo-Malayan birds (driven by intensifying deforestation of the Sundaic lowlands) and for albatrosses and petrels (driven by incidental mortality in commercial longline fisheries). RLIs complement indicators based on species population trends and habitat extent for quantifying global trends in the status of biodiversity. Their main weaknesses are that the resolution of status changes is fairly coarse and that delays may occur before some status changes are detected. Their greatest strength is that they are based on information from nearly all species in a taxonomic group worldwide, rather than a potentially biased subset. At present, suitable data are only available for birds, but indices for other taxonomic groups are in development, as is a sampled index based on a stratified sample from all major taxonomic groups.
An index is developed from the IUCN Red List that measures the overall threat status of taxa and reveals that the status of the world's birds has deteriorated since 1988
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Introduction
The world's biodiversity is diminishing rapidly (Balmford et al. 2003; Jenkins et al. 2003). At the 2002 World Summit on Sustainable Development, the nations of the world agreed to pursue more effective implementation of the objectives of the Convention on Biological Diversity (CBD) in order to achieve a significant reduction in the current rate of loss of biological diversity by 2010 (Secretariat of the Convention on Biological Diversity 2003).
The European Union has adopted the more ambitious target of halting the loss of biodiversity by 2010 (European Union 2001). We do not yet have an adequate way of monitoring progress towards achieving this target. However, the CBD Conference of the Parties at its Seventh Meeting adopted Decision VII/8, which included recommendations to develop indicators for measuring trends in the components of biodiversity based on (1) trends in extent of selected biomes, ecosystems, and habitats; (2) trends in abundance and distribution of selected species; (3) change in status of threatened species; (4) trends in genetic diversity of domesticated animals and cultivated plants; and (5) coverage of protected areas (CBD 2004). None of these alone is adequate, but together they provide powerful measures of global trends in the status of biodiversity.
Here we address the third of this suite of indicators, using changes in the threat status of species as measured by the categories of the World Conservation Union (IUCN) Red List. The IUCN Red List is widely recognised as the most objective and authoritative listing of species that are globally at risk of extinction (Lamoreux et al. 2003; Hambler 2004). Species are assigned to Red List categories (see Abbreviations section) through detailed assessment of information against a set of objective, standard, quantitative criteria (IUCN 2001; Table 1). Thousands of scientists, many of whom are members of IUCN Specialist Groups and the IUCN Species Survival Commission network, provide extensive information for assessments. Over the last few years, the IUCN Red List has been developed into a global programme to monitor the extent and rate of biodiversity degradation. The programme is currently overseen by four partner organisations: the IUCN Species Survival Commission, BirdLife International, NatureServe, and the Center for Applied Biodiversity Science at Conservation International, with additional partners being recruited, in particular to provide plant and marine expertise. Red List Authorities are appointed to ensure consistent categorisation between species and groups and for organising independent scientific review. A Red List ‘Standards and petitions' subcommittee monitors the process and resolves challenges and disputes to listings.
Table 1 Simplified Overview of Thresholds for the IUCN Red List Criteria
NA, not applicable
One of the goals of the programme is to provide a global index of the changing state of biodiversity (IUCN 2004). However, previous attempts to use the IUCN Red List to provide answers about the rate of loss of biodiversity suffered from many limitations (Cuarón 1993; Smith et al. 1993), and a number of problems with the general approach have been identified (Burgman 2002; Possingham et al. 2002; but see Lamoreux et al. 2003). We show, using data from birds, how the limitations can be overcome, and we present for the first time Red List Indices (RLIs) that are robust, temporally sensitive, representative, and comprehensive. These provide unique baseline data on the rate of loss of biodiversity against which progress towards meeting the CBD 2010 target can be judged. They also allow finer-scale resolution of trends in particular biogeographic realms, ecosystems, and habitats.
Results
The total number of extant threatened and Near Threatened birds listed on the IUCN Red List has changed relatively little over the four complete assessments of all the world's birds, increasing from 1,664 species in 1988 to 1,990 species in 2004. However, large numbers of species have moved between categories, particularly in the earlier assessments (Table 2). Most of these category changes have been a consequence of improved knowledge (including improved consistency of interpretation of information against the Red List criteria) or revised taxonomy. However, a significant proportion of species (equating to 2.4%–7.3% of threatened or Near Threatened species in each assessment) have moved between categories because of genuine improvement or deterioration in status. The RLI for birds illustrates the combined effect of these genuine status changes, to provide a simple metric of the changing overall status of the world's birds, in terms of their relative projected extinction risk as estimated using the categories of the IUCN Red List. This shows that there has been a steady and continuing deterioration in the threat status of the world's birds between 1988 and 2004, with an overall change in the index value of −6.90% over this period (Figure 1; see Table 2). No change would indicate that the average status of all bird species was the same as in 1988. To put this into context, if 10% of species in the categories from Near Threatened to Critically Endangered had deteriorated in status sufficiently to be uplisted one category to a higher category of threat between 1988 and 2004, the index would have changed by −7.8%, and if 50% of such species had deteriorated by one category the index would have changed by −27.4% (Figure 2). The error bars for the 2004 RLI value (based on the projected number of genuine status changes for the 2000−2004 period yet to be detected owing to information time lags; see Discussion) show that the estimated recent RLI trends are likely to be fairly robust.
Figure 1 The RLI for All Bird Species
Sample size: 250 genuine status changes/2,469 species in categories Extinct in the Wild to Near Threatened in at least one assessment.
Error bars for 2004 RLI value based on estimated number of genuine status changes for 2000–2004 not yet detected owing to information time lags (see Materials and Methods for further details).
Figure 2 The RLI for All Bird Species in 1988–2004 Compared to Hypothetical Indices
Hypothetical indices show trends if no species had changed category, and if 10% or 50% of species in the categories from Near Threatened to Critically Endangered had been uplisted to a higher category of threat or downlisted to a lower category of threat over the period.
Table 2 Number of Species in Each IUCN Red List Category as Published in Collar and Andrew (1988), Collar et al. (1994), BirdLife International. (2000, 2004c), and the Number of Species Undergoing Genuine Status Changes in Each Period
Table includes categories for Houbara bustard (C. undulata) and Saker falcon (F. cherrug) that were revised by BirdLife International for the 2004 IUCN Red List but subsequent to BirdLife International. (2004c); see Materials and Methods
a Includes categories retrospectively adjusted owing to category revisions coded as ‘genuine status change since first assessment'
CD, Conservation Dependent; CR, Critically Endangered; DD, Data Deficient; EN, Endangered; EW, Extinct in the Wild; EX, Extinct; LC, Least Concern; NE, Not Evaluated; NR, Not Recognised; NT, Near Threatened; PE, Possibly Extinct; VU, Vulnerable
To examine trends in the status of the most threatened species (i.e., those closest to extinction), the index was calculated using weights for each category related to the relative extinction risk associated with them (Figure 3; see Materials and Methods). This shows a levelling out of the decline in the index value during 2000–2004 (although the error bars indicate that in the next few years the belated discovery of genuine status changes for this period could reduce this apparent levelling out). This was because for those species that underwent genuine status changes in the categories of highest extinction risk (those that have the greatest influence on the index value when calculated in this way), the number of species that deteriorated in status during this period was balanced by the number that improved in status owing to conservation action. Specifically, two Critically Endangered species became Extinct (or Possibly Extinct) in the wild (Hawaiian crow [Corvus hawaiiensis] and Spix's macaw [Cyanopsitta spixii]), and five Endangered species became Critically Endangered, but this was offset by seven species that improved in status as a result of conservation efforts (including, e.g., Polynesian megapode [Megapodius pritchardii], Christmas Island hawk-owl [Ninox natalis], and Christmas Island white-eye [Zosterops natalis]; BirdLife International 2004c).
Figure 3 The RLI for All Bird Species with Categories Weighted by Relative Extinction Risk
Sample size: 250 genuine status changes/2,469 species in categories Extinct in the Wild to Near Threatened in at least one assessment. Error bars for 2004 RLI value based on estimated number of genuine status changes for 2000–2004 not yet detected owing to information time lags (see Materials and Methods for further details).
The RLI can be broken down by biogeographic realm (Figure 4), ecosystem, habitat type (Figure 5), and for particular species groups (Figures 6 and 7). These show that the threat status of birds has deteriorated worldwide, with a more-or-less similar rate and proportional extent of deterioration in the Nearctic, Neotropical, Palearctic, Afrotropical, and Australasian/Oceanic realms. The RLI for the Indo-Malayan realm showed a steeper rate of decline during the 1990s (see Figure 4). Declines in the index for three major ecosystems (terrestrial, freshwater, and marine) and two terrestrial habitat types (forest and shrubland/grassland) all show a broadly similar pattern (see Figure 5), although the declines in the freshwater environment appear to have been the most severe. Finally, RLIs for selected subsets of species (including those relevant to particular international treaties) highlight the severity of the worsening situation of the world's albatrosses and large petrels in recent years (see Figures 6 and 7).
Figure 4 RLIs for Birds in Different Biogeographic Realms
Sample sizes: Neotropical, 49 genuine status changes/834 species in categories Extinct in the Wild to Near Threatened in at least one assessment; Afrotropical, 41/394; Australasian/Oceanic, 53/614; Palearctic, 34/238; Nearctic, 9/92; Indo-Malayan, 100/585.
Figure 5 RLIs for Birds in Different Habitats
Sample sizes: terrestrial, 206 genuine status changes/2,329 species in categories Extinct in the Wild to Near Threatened in at least one assessment; freshwater, 31/226; marine, 12/133; shrubland/grassland, 45/481; forest, 169/1,513.
Figure 6 RLIs for Three Bird Families with High Conservation Profiles
Sample sizes: game birds, 15 genuine status changes/123 species in categories Extinct in the Wild to Near Threatened in at least one assessment; raptors, 10/93; parrots, 19/148.
Figure 7 RLIs for Three Species Groups Targeted by Particular International Conservation Treaties: The Ramsar Convention on Wetlands, the CMS, and the ACAP under the CMS
Sample sizes: waterbirds, 36 genuine status changes/238 species in categories Extinct in the Wild to Near Threatened in at least one assessment; albatrosses and petrels, 6/28; migrants, 50/313.
Discussion
How Fast Are We Losing Avian Biodiversity?
Bird species are being driven Extinct by increasing human impacts on the planet. In total, 129 bird species have been classified as Extinct since 1500, with an additional four species listed as Extinct in the Wild, but surviving in captive populations (BirdLife International 2004b, 2004c). Additionally, 18 Critically Endangered species are considered Possibly Extinct by BirdLife International. (2004b, 2004c; see Materials and Methods). Of these confirmed and likely extinctions, nine have occurred during the period 1988–2004 (BirdLife International, unpublished data). However, it is very difficult to produce robust estimates of recent extinction rates and to quantify how they have changed over short timescales. This is because extinction is difficult to detect once species become very rare (Diamond 1987; Reed 1996), and tiny populations of species potentially doomed by habitat loss or other threats may persist for many decades (Turner 1994; Brooks et al. 1997, 1999). For these reasons, extinction rates perform weakly as indicators of the current state of biodiversity (Balmford et al. 2003).
By contrast, the RLIs presented here provide a robust, sensitive measure of the rate at which the world's birds are changing in relative projected extinction risk, as classified using the categories of the IUCN Red List. The indices show that the overall threat status of the world's birds has deteriorated steadily over the last 16 y. The RLI value has changed by −6.90% over this period. However, it should be noted that owing to the arbitrary nature of the weights applied to each category to calculate the score, this percentage decline is not directly comparable with percentage declines reported for population-based indices such as the Living Planet Index (Loh 2002) or the United Kingdom headline indicator for wild bird populations (Gregory et al.2003).
When the RLI is weighted by the relative extinction risk associated with each category in order to emphasise trends in the status of the most threatened species, the rate of decline of the index value appears to have levelled off in recent years (see Figure 3), owing to the number of such species deteriorating in status being balanced by the number improving. Nevertheless, it should be emphasised that one Critically Endangered species went Extinct in the Wild in the wild during the period (Hawaiian crow [C. hawaiiensis]), and another is highly likely to have done so (Spix's macaw [C. spixii]; BirdLife International 2004c). These are potentially irretrievable losses to genetic diversity.
How can we interpret the RLI in relation to the CBD's target of reducing the rate of loss of biodiversity by 2010? The interpretation is different for measures of the state of biodiversity (e.g., total area of remaining forest) and measures of the rate of change in this state (e.g., annual percentage forest loss). For indices based on proportional change in a measure (plotted on a negative scale as with the RLI), if the measure is one of state, a significant diminution in downward trend would show that the target has been met. If the measure is one of rate of change of state, however, the target is not met until we see a positive trend, not just a decelerating decline. Some of the Red List criteria are based on absolute population size or range size, while others are based on rates of decline in these values or combinations of absolute size and rates of decline. These criteria are used to assign species to Red List categories that can be ranked according to relative projected extinction risk, and the RLI is calculated from changes between these categories. Hence an RLI value relates to the rate at which species are slipping towards extinction at a particular time. To show that the 2010 target has been met, the RLI must therefore show a positive trend. A downward trend, even if diminishing, shows that the slide of species towards extinction is accelerating, not slowing down. The negative trends in the RLI values (see Figure 1) thus show that in 2004 we are losing biodiversity at an increasing rate.
The RLIs show some interesting regional variations. The index for birds in the Indo-Malayan realm shows a sharp decline during the 1990s (see Figure 4). This was a result of the intensifying destruction of forests in the Sundaic lowlands of Indonesia, which escalated particularly in the late 1990s and led to predictions of almost total loss of lowland forest in Sumatra by 2005 and in Kalimantan by 2010 (Holmes 2000; BirdLife International 2001). As a consequence of these increasing rates of habitat loss, many species were uplisted to higher categories of threat under criterion A (rapid population declines). However, it is notable that there has been a significant deterioration in the threat status of birds of shrubland/grassland habitats as well as forest, and in the two other major ecosystems (freshwater and marine), indicating that birds in a broad spectrum of environments are under threat.
RLIs can be calculated for particular species groups that have specific conservation or policy significance. For example, there are particularly active conservation networks for game birds (e.g., World Pheasant Association), raptors (e.g., World Working Group on Birds of Prey), and parrots (e.g., Loro Parque and World Parrot Trust), and the threat status of all three of these species groups is deteriorating, with steeper declines in the index value for parrots in the earlier part of the period (see Figure 6). In addition, there are several international conservation treaties targeting particular suites of species (the Ramsar Convention on Wetlands, the Convention on Migratory Species [CMS], and the Agreement on the Conservation of Albatrosses and Petrels [ACAP] under the CMS) for which disaggregated RLIs provide a metric against which to judge their success in improving the fortunes of the species involved. The RLI for albatrosses and large petrels shows how dramatically their threat status has deteriorated in recent years (see Figure 7). This is closely linked to the expansion of commercial longline fisheries (both legal and illegal), which causes incidental mortality of albatrosses and other seabirds when they get caught on baited hooks and drown (Tuck et al. 2001; 2003; BirdLife International 2004b). The total reported effort from fleets in the southern oceans has been well over 250 million hooks per year since the early 1990s, with some fleets expanding rapidly in the last decade (Tuck et al. 2003). Models for at least some albatross species show clear links between population declines and these increases in longline fishing effort (Tuck et al. 2001). Mitigation measures are effective (Løkkeborg 2001), and the RLI will provide a useful measure by which to judge the effectiveness of the implementation of ACAP, following its entry into force in 2004.
It should be noted that setting all disaggregated index values to a common baseline in 1988 obscures any changes prior to this period (see, e.g., Pauly 1995). For example, although the Indo-Malayan realm has shown the most severe recent index declines, ‘only' six extinctions occurred there between 1500 and 1988, whereas at least 62 bird species are known to have gone Extinct in the Australasian/Oceanic realm during the same period, and 40 in the Afrotropical realm (BirdLife International 2000). Similarly, the terrestrial ecosystem has suffered far more extinctions since 1500 (115) than the freshwater (17) or marine ecosystems (five), but all are set to a common baseline in 1988.
Category Weights
The RLI is based on the number of species in each Red List category. In order to make the index sensitive, not just to the total number of threatened species, but also to the changes in category assigned to each species, each category was given a weighting. We used an ‘equal-steps' approach (with incremental increases from one for Near Threatened through to five for Extinct) to reflect the ordinal ranks of the categories, whereby each step from Least Concern to Extinct indicates that at least one measure of extinction risk has become worse. The advantage of this approach is that it is simple, and the trends in the resulting index are driven by a relatively large number of species (hence producing a more robust and representative index). This is because a species moving from Least Concern to Near Threatened contributes just as much to the changing score as a Critically Endangered species going Extinct, and the numbers of species in each category (and the number moving in and out of each category) increases disproportionately from Critically Endangered to Least Concern (see Table 2).
However, steps between lower categories of threat represent smaller increases in extinction risk than steps between higher categories. Therefore we also tested an ‘extinction risk' approach, with each category weighted according to its relative extinction risk based on the quantitative thresholds for each of its criteria (Table 3). Although this approach also relies on some assumptions (e.g., about the type of extinction risk curve, and the extinction risk associated with Near Threatened), it is based on the principles of extinction dynamics, in contrast to the equal-steps approach.
Table 3 Weights for Red List Categories Critically Endangered, Endangered, and Vulnerable, Based on Relative Extinction Risk Associated with Various Red List Criteria
The most important difference between the two approaches is the effect of status changes in less-threatened or nonthreatened species. The equal-steps approach gives an index that is heavily influenced by movements of species among the lower categories of threat. The extinction risk approach gives an index that is largely influenced by movements of species among the higher threat categories. For example, if a Vulnerable species improves in status and becomes Near Threatened, and at the same time, a Critically Endangered species goes Extinct, the RLI based on equal-steps weights registers no change, but the index based on extinction risk weights shows a substantial decrease. Downlisting of a Vulnerable species to Near Threatened might represent a very substantial population increase, whereas extinction of a Critically Endangered species might represent the loss of very few individuals. The latter is arguably more significant in terms of genetic diversity, but the former might be more important as an indicator of wider biodiversity trends. Thus, the extinction risk weights emphasise the loss of biodiversity owing to imminent or potential extinctions of species, whereas the equal-steps weights allow the index to capture large changes in the populations of less-threatened species.
For the RLI for complete taxonomic groups, and for disaggregating the index to show trends for subsets of species, for example, in particular realms or ecosystems we used the equal-steps approach because the number of species moving between the higher threat categories (those effectively driving trends when an ‘extinction risk' weighting is used) was too small to be meaningful in disaggregated indices. Only 23% of all genuine status changes (58 species in total) involved moves in or out of the highest threat categories. However, for examining trends in the species closest to extinction, we used the weights based on relative extinction risk.
Weaknesses of RLIs
The usefulness of the IUCN Red List as an indicator of trends in the status of biodiversity (e.g., Smith et al. 1993) has been previously questioned on the grounds that (1) the categories are subjective; (2) taxonomic treatment is uneven, and listings are biased towards attractive, spectacular, high-profile, or better-known species; and (3) most species move between categories because of changes in knowledge or taxonomy, not as a consequence of genuine improvement or deterioration in status (Cuarón 1993; Burgman 2002; Possingham et al. 2002; but see Lamoreux et al. 2003).
The first of these problems has been addressed since 1994, when quantitative and objective categories and criteria for the IUCN Red List were introduced (IUCN 1994, 2001). The second problem can be overcome by calculating indices only for taxonomic groups in which all species have been comprehensively assessed and reassessed (as shown here) or by developing indices based on a stratified sample from diverse taxonomic groups (see below). The third problem has already been addressed because since 2001 the IUCN Red List has required clear documentation of the reason for any reclassification (IUCN 2001). Hence, movements of species between categories owing to knowledge, taxonomy, or other ‘nongenuine' reasons can be easily excluded when calculating the index.
RLIs have a fairly coarse level of resolution of status changes because of the broad nature of Red List categories. Populations in the wild may have to undergo quite significant changes in size, trend, or distribution before crossing the thresholds to qualify for a higher or lower Red List category and, hence, before changing the RLI value. This is inherent in using the Red List categories rather than more precise parameters such as estimates of population size. It is not always true, however: The Red List criteria allow for species to be assessed as threatened on the basis of projected declines, and thus changes in status can reflect new or emerging threats in anticipation of population or range changes. We suggest that the disadvantage of coarse resolution is outweighed by the advantage of using a system that allows all the world's species in a taxonomic group to be assessed, rather than just a (potentially biased) subset for which adequately detailed information is available.
Insensitivity of the index to status changes may also arise from time lags between changes in a species' population or range and changes in the RLI value, because of delays before detection of the status change, and/or before this knowledge becomes available to assessors. This is potentially more problematic, but several factors act to mitigate it. The Red List Programme partners have a large and expanding network of scientists across the world providing detailed and up-to-date information for an increasing number of species. Furthermore, with improving channels of communication (in particular, the increasing use of the World Wide Web to solicit information, for example, BirdLife's Web-based Globally Threatened Bird discussion forums; BirdLife International 2004a), we expect that such delays will diminish. For birds, the data support this: whereas just 42% of genuine status changes between 1988 and 1994 were detected in 1994 (with 43% detected during 1994–2000 and 15% detected during 2000–2004), 88% of changes during 1994–2000 were detected in 2000, and just 12% were detected in the subsequent 4 y. Using the data from the 1994–2000 period (because information gathering has improved considerably since 1988–1994), we can estimate the likely number of genuine status changes for 2000–2004 that have not yet been detected (six; see Materials and Methods) and, hence, estimate the possible degree of error associated with the 2004 RLI value. The results show that it may be an under- or overestimate by 0.21%–0.37% (see Figure 1): a small and acceptable margin of error. In future, we anticipate smaller retrospective adjustments to the index values, and a smaller and more predictable error associated with the most recent index value. The major advantage of backtracking status changes to the appropriate time period is that the index trends do not get distorted by the belated discovery of genuine status changes, which, for example, might result from the exhaustive research that takes place when a Red Data Book is published (e.g., BirdLife International 2001). This arguably outweighs the disadvantage that the slope of the index between two particular dates may change slightly in future releases of the index.
How robust are RLIs? A potential criticism is that they are based on status changes in small numbers of species. However, between 1988 and 2004 the RLI declined by a degree equivalent to almost 10% of species in the categories Near Threatened to Critically Endangered deteriorating in status sufficiently to be uplisted by one category to a higher category of threat. Although relatively few in number (250), these status changes are the most important among the world's birds in terms of changes in projected extinction risk. We therefore suggest that the declines shown by the RLI since 1988 represent very significant losses to global biodiversity.
Relatively large numbers of species changed categories in 1994 and 2000 owing to improvements in knowledge and improved consistency of interpretation of information against the Red List criteria (see Table 2). This was because of the introduction of quantitative criteria for assigning species to categories in 1994 (Collar et al. 1994; IUCN 1994) and the mapping of all threatened species and more rigorous justification for Near Threatened status in 2000 (BirdLife International 2000). By 2000–2004, only 6.7% of threatened and Near Threatened species changed category owing to improved knowledge (see Table 2). Nevertheless, it is true that a small proportion of species may be sufficiently poorly known that there is uncertainty over their status and whether this has changed over time. If this introduces any bias, it may be towards an overoptimistic RLI trend. This is because well-studied species (with better data and hence more certain Red List assessments) may be more likely to be those receiving conservation attention and, hence, improving in status (or at least deteriorating less rapidly). All data used in Red List assessments for birds (e.g., population size, trends, etc.) are coded for data quality, and in future the RLI will also be calculated separately for species with high-quality data, in order to test whether such biases exist.
Strengths of RLIs
The greatest strength of the RLIs presented here is that they are based on comprehensive and complete assessments of nearly all species in a taxonomic group across the world (just 0.8% of birds are listed as Data Deficient and hence excluded from the calculation of the RLI). Most other global indicators based on, for example, population estimates, are derived from data biased towards common, well-studied species in the developed world, particularly Europe and North America. For example, the Living Planet Index (Loh 2002) is based on indices for populations in marine, freshwater, and forest ecosystems. However, 70% of the 195 populations contributing to the freshwater ecosystem are in Europe or North America, while just 18% of the 282 populations contributing to the forest ecosystem index are in the tropics, where the greatest biodiversity is found (Loh 2002). Similarly, in a global index based on data from 936 amphibian populations from 37 countries around the world, 89% of populations (835) were from Europe or North America, and just 2.2% (21) were from Asia and 5.5% (51) from South/Central America (Houlahan et al. 2000). By contrast, the RLI for birds is based on trends for nearly all the world's 10,000 bird species. RLIs for other completely assessed taxonomic groups are in development (see below).
At present, indicators based on more representative suites of species are only available for particular countries or regions, such as the United Kingdom headline indicator for birds (Gregory et al. 2003) and the Pan-European Common Bird Index (BirdLife International 2004b; Gregory et al. 2004). Indices based on population trends (particularly at the regional scale) generally include few species that are rare, localised, or difficult to survey, including those most susceptible to extinction. RLIs can incorporate status changes in such species because the Red List process is an effective system for making meaningful inferences from data that are imprecise or incomplete.
Species-based indicators such as the RLI arguably provide far more powerful measures of biodiversity loss than other indicators proposed for measuring progress towards the 2010 target (CBD 2004). Trends in the extent of biomes and habitats are of necessarily coarse resolution and take no account of the distribution of biodiversity within and between habitats; trends in the genetic diversity of domesticated animals and cultivated plants provide measures related to only a tiny proportion of biodiversity; and trends in the coverage of protected areas are a measure of responses to biodiversity loss rather than a measure of the state of biodiversity.
Future Steps
At present, data are only available for birds to produce the sorts of indices shown here. By 2010 at least two complete global assessments will also be available, and RLIs calculated for all the world's mammals (about 5,000 species), amphibians (about 5,700 species), and hopefully some plant and marine groups. Additional indices, and an aggregation of RLI trends in multiple groups, will provide a more representative picture of the changing state of biodiversity. In recognition that this will take some time to implement, the IUCN Red List Programme is also developing a sampled RLI based on a stratified sample of about 3,000 species from all major taxonomic groups, biogeographic realms, ecosystems, and Red List categories. This will provide an index that may be more representative of trends in the threat status of all biodiversity. We suggest that RLIs will have a key role to play alongside other types of indicators in assessing progress towards reducing the rate of, or halting, the loss of biodiversity.
Materials and Methods
IUCN Red List assessments for birds
BirdLife International (formerly the International Council for Bird Preservation) has been responsible for providing the assessments of the world's 10,000 or so species of birds for the IUCN Red List since 1963. Since 1988, BirdLife has assessed every species of bird on a regular basis, and birds are regarded as the most comprehensively documented class of organisms on the Red List. BirdLife is the official Red Listing Authority for birds, and assessments are based on data gathered from the BirdLife Partnership of organisations in over 100 countries around the world, from published and unpublished literature, and from information provided by a worldwide network of over 1,000 species experts (BirdLife International 2000, 2004c).
The principal categories on the IUCN Red List are: Extinct, Extinct in the Wild, Critically Endangered, Endangered, Vulnerable, Near Threatened, and Least Concern (IUCN 2001). Since all bird species have been assessed, none is listed as Not Evaluated, and only 78 (0.8%) are listed as Data Deficient. In addition, two terms used by BirdLife have not yet been adopted for more general application in the IUCN Red List. Possibly Extinct is a tag applied to those Critically Endangered species that are, on the balance of evidence, ‘likely to be Extinct, but for which there is a small chance that they may still be extant, and hence they should not be listed as Extinct until local or unconfirmed reports have been discounted, and adequate surveys have failed to find the species' (BirdLife International 2004c). As there are taxonomic revisions between assessments, ‘Not Recognised' is applied to taxa in those assessments when they were not treated as full species (BirdLife International 2004c).
Data from which to calculate the indices were derived from four complete assessments of the status of the world's birds by Collar and Andrew (1988), Collar et al. (1994), and BirdLife International (2000, 2004c), plus from reviews of two species (Houbara bustard [Chlamydotis undulata] and Saker falcon [Falco cherrug]) whose categories were revised for the 2004 IUCN Red List too late to be included in BirdLife International (2004c). Information was also taken from partial assessments submitted by BirdLife to the 2002 and 2003 IUCN Red Lists (IUCN 2002, 2003). The 1988 assessment predated quantitative Red List criteria (IUCN 1994), and only the qualitative categories ‘threatened' and Near Threatened were used. Therefore, for species categorised as threatened in 1988, the category assigned in 1994 was applied to the 1988 assessment, with an appropriate category assigned for species that underwent genuine status changes during the period (see below).
Identifying genuine status changes between Red List assessments
Published lists of numbers of species in different Red List categories cannot simply be used to calculate the index, for several different reasons. For example, changing knowledge and taxonomy result in many category changes, but such revisions are not indicative of changes in the conservation status of species' populations. Hence, to identify those species changing categories between assessments for relevant reasons, a ‘reason for change' code was assigned for each recategorisation. These mutually exclusive codes were (1) recent genuine status change, (2) genuine status change since first assessment, (3) knowledge, (4) criteria revision, and (5) taxonomy. These last three codes were used for changes not relevant for calculating the indices.
‘Recent genuine status change' was applied to species that had undergone a genuine improvement or deterioration in status in the period since the previous assessment. This included species qualifying because of population declines (under IUCN Red List criterion A), particularly those with long generation times, for which more than half of the period during which the change occurred was subsequent to the previous assessment. This code was also applied in a few cases where species entered the Red List as a result of their elevation from subspecies to species level, but for which there had been a genuine status change when the taxon was compared to the equivalent population of the original species. For species categorised as threatened in 1988 and Critically Endangered, Endangered, or Vulnerable in 1994, genuine changes in status between these two assessments were identified by searching the account in Collar et al. (1994) and associated unpublished information for evidence of genuine status changes that had occurred in the previous 6 y.
‘Genuine status change since first assessment' was applied to species that had undergone a genuine improvement or deterioration in status in the period since the first complete assessment, but prior to the last assessment. This code denoted genuine changes in status that were not detected at the time they occurred. For example, Syrian serin (Serinus syriacus) was uplisted from Near Threatened to Vulnerable in 2004 because of the discovery that populations had declined during a drought in 1998–1999. This information was unavailable during the 2000 assessment, so the species was recategorised in 2004 and given this ‘reason for change' code (BirdLife International 2004c). For cases such as these, the Red List category for earlier assessments was back-cast using the improved understanding of earlier population sizes, trends, and ranges. This also applied to (a) extinctions that occurred after 1988; (b) species where no (or an incorrect) status change was recorded, but subsequent knowledge indicated that a genuine status change had occurred; (c) species for which an improvement in status did not immediately lead to a category revision because of the application of the ‘5-y rule' (whereby under the IUCN Red List guidelines downlisting to a lower category of threat should not occur until all of the criteria of the higher category have ceased to apply for 5 y or more; IUCN 2001; Red List Standards and Petitions Subcommittee 2003).
‘Knowledge' was applied to species recategorised owing to new information on, for example, population and range size, declines, ecological attributes, threats, or conservation efforts. This included information published or known before the last assessment, but only made available to, or discovered by, assessors since the last assessment. For example, Madagascar plover (Charadrius thoracicus) was uplisted from Near Threatened to Vulnerable in 2004 because its population was estimated to number as few as 750 individuals. However, the evidence suggests that the population may have been this small since before 1988 (BirdLife International 2004c). This code was also applied in cases where a species changed category owing to improved consistency of interpretation of information against the Red List criteria. ‘Criteria revision' was applied in cases when species changed category owing to revisions to the definitions of the IUCN Red List criteria (IUCN 2001). ‘Taxonomy' was applied in cases when species changed category owing to taxonomic ‘lumping' or ‘splitting' or for newly described species.
Calculating index values
The number of species in each Red List category for each complete assessment and the number of species that changed categories as a result of genuine status changes were used to determine the index value in the following way: (1) For species assessed in two consecutive assessments (i.e., excluding any listed as Not Recognised, Not Evaluated, or Data Deficient in either or both assessments), the total numbers of species in each category in the earlier assessment (excluding Extinct and Possibly Extinct, but including those species retrospectively reassigned categories owing to genuine status changes that were identified subsequently; see above) were multiplied by a weight, and these were summed to give a total score, T, for each assessment. The weights were set as Near Threatened = 1, Vulnerable = 2, Endangered = 3, Critically Endangered = 4, Extinct in the Wild = 5 (see below). (2) Over each period between complete assessments (1988–1994, 1994–2000, and 2000–2004) the net number of genuine changes to the total in each category was calculated, multiplied by the weights above (with Possibly Extinct and Extinct = 5), and summed to calculate the proportional change in the total score, P. (3) The value of the index (I) was set to 100 in 1988. For subsequent assessments I was calculated by multiplying −P for the previous period by the previous index value (see Table S1 for values for T, P, and I for each index).
Mathematically, the method can be described as follows, where T is total score; Nc (ti) is the number of species in category c at time ti, where ti is the year of the ith assessment (assessments are not necessarily made every year); Wc is the weight for category c; P is proportional genuine change; Iti is the value of the index at time ti; Cat(ti, s) is the category of species s at time ti; Wc is the weight for category c; Gs = 1 if change (from t
(i−1) to ti) in category of species s is genuine (otherwise Gs = 0).
where Iti−1 = 100 for the first year of assessment.
The Red List categories are ordinal ranks, whereby each step from Least Concern to Extinct indicates that at least one measure of extinction risk has become worse. The ‘equal-steps' weights listed above reflect the ordinal ranks of the categories. However, the steps between lower categories (e.g., Near Threatened to Vulnerable) translate to smaller increases in extinction risk than steps between higher categories (e.g., Endangered to Critically Endangered). Therefore we also calculated the aggregated RLI using weights based on the relative extinction risk associated with each category. Several of the quantitative thresholds in the Red List criteria can be used to obtain approximate values for the relative risk of extinction (for species at the lower boundary of that category). The most obvious is criterion E, which is based on quantitative analysis of extinction probability. The quantitative thresholds in criterion E change for both extinction probability and time frame for the three categories, and depend on generation length (e.g., the threshold for Endangered is a probability of extinction in the wild greater than 20% within 20 y or 5 generations). Taking a 3-generation time frame, a generation length set arbitrarily at 5 y, and assuming a constant annual risk of extinction, the 3-generation probabilities are approximately 0.5, 0.13, and 0.016 for Critically Endangered, Endangered, and Vulnerable, respectively (H. R. Akçakaya, unpublished data). However, most extinctions do not occur as a result of random catastrophes, as implied by the assumption of the constant annual risk of extinction. Many are preceded by declines, resulting in sigmoid extinction risk curves (with probability of extinction as a function of time). For such cases, the 3-generation probabilities are approximately 0.5, 0.1, and 0.025 for Critically Endangered, Endangered, and Vulnerable, respectively (see Table 3). Comparable extinction risks can also be calculated based on other Red List criteria (except A, for which there is no obvious method). Assuming that the number of mature individuals (in criteria C1 and D), range or extent of occurrence (criterion B1), and area of occupancy (criterion B2) are inversely related to risk of extinction, and fixing the risk of extinction for Critically Endangered at 0.5, it is possible to calculate the probabilities for categories Endangered and Vulnerable (see Table 3). Based on the geometric average of these estimates, the weights for Critically Endangered, Endangered, and Vulnerable are determined as 0.5, 0.05, and 0.005 (see Table 3). The weight for Extinct (and hence Extinct in the Wild and Possibly Extinct) is by definition 1.0. The weight for Near Threatened is set at 0.0005, keeping the same proportion as among the weights for the three threatened categories.
Calculating error bars
We calculated, using the following method, the possible range of error associated with the latest (2004) RLI value owing to time lags before genuine status changes are detected (see Discussion). We estimated how many such undetected category changes there may be for 2000–2004 using the 1994–2000 data (information gathering has improved considerably in recent years, so comparisons with time lags for the 1988–1994 period are not meaningful). In total, 128 genuine changes for 1994–2000 were identified in 2000, and an additional 17 (13.3%) were identified in the subsequent 4 y. This suggests that an additional six category changes (13.3% of 45 genuine status changes identified in 2004) may be belatedly detected for 2000–2004. We randomly selected six species from the 9,453 species that did not undergo category changes from 2000 to 2004, with a maximum of two species per category. We ran 10,000 simulations of six species moving to categories of higher extinction risk, with probabilities for each number of category steps set by the distribution of category changes for 35 ‘uplisted' species in 2000–2004. The maximum value for P (proportional genuine change) from these simulations gave the lower error bar for the 2004 RLI value. Similarly, we ran 10,000 simulations of six species moving to categories of lower extinction risk (with probabilities for each number of category steps set by the distribution of category changes for ten ‘downlisted' species in 2000–2004), and took the minimum value for P to give the upper error bar. These are very similar to the minimum and maximum values for P derived by simulating an additional six species moving in a direction (and by a number of categories) in proportion to the distribution of these values for all 45 species that underwent genuine status changes in 2000–2004 (see Table S2).
Disaggregating indices
One of the purposes of the RLIs is to illustrate trends over time in the threat status of species in different biogeographic realms, ecosystems and families or species groups. Species were assigned (based on native distributions, excluding cases of vagrancy) to one or more biogeographic realms (Palearctic, Afrotropical, Indo-Malayan, Nearctic, Neotropical, and Australasian/Oceanic) following the boundaries mapped by Newton (2003) except that Australasian was pooled with Oceanic, and Antarctic was excluded. Where a species was assigned to more than one realm, it was included in calculating the score (T) for each of those realms. This is because a species could potentially undergo genuine changes in status in any or all realms in which it occurs. However, so that trends in indices for particular realms reflect changes in the threatening processes operating within each particular realm (rather than threats operating elsewhere in the range of the species), species were only included in the calculation of P for a particular realm if the genuine status change had been driven by factors operating in that realm. For example, Saker falcon (F. cherrug) occurs in the Palearctic, Indo-Malayan, and Afrotropical realms and was included in the score calculations for each of these. However, recent declines have been driven by factors operating on the breeding grounds in Central Asia (Environmental Research and Wildlife Development Agency, unpublished data; BirdLife International 2004c), so the genuine change was only calculated for the Palearctic realm. By contrast, the black-browed albatross (Thalassarche melanophrys) has declined as a result of incidental capture in commercial longline fisheries in oceans in the Afrotropical, Neotropical, and Australasian/Oceanic realms (Robertson and Gales 1998; BirdLife International 2004c), and so this genuine change was incorporated into the calculation of P for all three realms.
The index was disaggregated for ecosystem (terrestrial, marine, and freshwater) and for two terrestrial habitat types (forest and shrubland/grassland; see below) in a similar way. Species were included in the calculation of T for all ecosystems and habitats for which they were scored, but only included in the calculation of P for a particular ecosystem or habitat if the genuine status change had been driven by threatening processes operating in that ecosystem or habitat. Species were only assigned to a habitat type if this was of critical or major importance (i.e., the species typically occurs in no other habitat, or just one other habitat at some point in its life cycle).
To exemplify how the approach can be used for taxonomic subsets of species, RLIs were also calculated for several high-profile species groups with specific conservation interest groups: raptors (Falconiformes), game birds (Galliformes), and parrots (Psittaciformes); and for species groups relevant to particular international conservation treaties: waterbirds (as listed in Wetlands International 2003) covered by the Ramsar convention, migrant species covered by the CMS, and albatrosses (Diomedeidae) and large petrels (Macronectes spp. and Procellaria spp.) covered by the ACAP under the CMS.
Sample sizes in the figure legends give, for the subset of species plotted, the total number of category changes owing to genuine status changes during 1988–2004 (but note that a small number of species underwent genuine status changes in more than one period between assessments) and the total number of species in categories Extinct in the Wild, Critically Endangered, Endangered, Vulnerable, and Near Threatened in at least one assessment during the period (and that are taxonomically recognised at present).
Supporting Information
Table S1 Index Values: Values for T, P, and I for Each Period and for Each Index
(66 KB DOC).
Click here for additional data file.
Table S2 Calculating Error Bars: Simulated P-Values (Proportional Change in the Index Score T) Used to Determine Error Bars for 2004 RLI Value
Lists the simulated p-values (proportional change in the index score T) based on the assumption that an additional six genuine changes occurred from 2000 to 2004 but have not yet been identified owing to time lags in knowledge (see Materials and Methods). Six species were randomly selected from those that did not change category from 2000 to 2004 (n = 9,453 species), with a maximum of two species from each category. For each species, the number and direction of category changes were randomly assigned with probabilities (1) based on the change in categories for the ten species that underwent genuine status changes and were downlisted to a lower category of threat during 2000–2004 (‘only down'); (2) based only on the 35 species that were uplisted to a higher category of threat (‘only up'); (3) based on all 45 species (‘both up and down'); and (4) based on all 45 species with probabilities that were set individually for each threat category (‘category dependent,' so that, e.g., the probability of an Least Concern species being downlisted to a lower category of threat was zero). In each case, the procedure was repeated 10,000 times to calculate the minimum, maximum, mean, and standard deviation of the simulated p-value.
The upper error bars for the RLI were determined by the minimum simulated p-value for cases when all six species were downlisted to lower categories of threat (shown in red in the table). The lower error bars were determined by the maximum simulated p-value for cases when all six species were uplisted to higher categories of threat (shown in blue in the table). In both cases the values are close to those calculated if the six species changed category, with probabilities based on the direction and number of category changes for all 45 species, and encompass those derived using the method based on category-dependent probabilities.
(35 KB DOC).
Click here for additional data file.
For helpful comments on the methodology and for improving earlier drafts we thank Rhys Green, Andrew Balmford, Nigel Collar, Ulf Gärdenfors, Richard Gregory, Nigel Leader-Williams, John Pilgrim, Arco van Strien, and an anonymous referee. For help with data management we thank Martin Sneary, Mark Balman, and Mike Evans. We are grateful to the Netherlands Ministry of Agriculture, Nature and Food Quality, Directorate-General for International Cooperation, Netherlands Ministry of Foreign Affairs, National Science Foundation, Swiss Development Corporation, and the Rufford Foundation for funding that supported some of the work presented here. We thank the many hundreds of experts and organisations that contributed information used in Red List assessments over many years, which have allowed this analysis to be possible. In particular we acknowledge the extraordinary contribution made by Nigel Collar, whose work on Red Listing the world's birds laid the foundations (and much of the brickwork) for the analyses presented here.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. SHMB, AJS, LAB, HRA, JEMB, SNS, CHT, and GMM contributed to the development of methodology. SHMB, AJS, and SMS analyzed the data. SHMB wrote the paper.
Academic Editor: Walt V. Reid, Millennium Ecosystem Assessment
Citation: Butchart SHM, Stattersfield AJ, Bennun LA, Shutes SM, Akçakaya HR, et al. (2004) Measuring global trends in the status of biodiversity: Red List Indices for birds. PLoS Biol 2(12): e383.
Abbreviations
ACAPAgreement on the Conservation of Albatrosses and Petrels
CBDConvention on Biological Diversity
CMSConvention on Migratory Species
IUCNWorld Conservation Union
RLIRed List Index
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| 15510230 | PMC524254 | CC BY | 2021-01-05 08:21:16 | no | PLoS Biol. 2004 Dec 26; 2(12):e383 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020383 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020390SynopsisEcologyInfectious DiseasesEpidemiology/Public HealthArthropodsPlasmodiumPredicting Risk of Mosquito-Borne Disease in Variable Environments Synopsis11 2004 26 10 2004 26 10 2004 2 11 e390Copyright: © 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 Risk of a Mosquito-Borne Infection in a Heterogeneous Environment
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Malaria remains one of the greatest threats to global health, infecting more people than ever before. Confined mainly to the tropical areas of Africa, Asia, and Central America, malaria hits Africa the hardest; the poverty-stricken lands of sub-Saharan Africa account for 90% of malaria infections worldwide. Despite ongoing efforts to battle the disease—by controlling mosquito populations, reducing human contact, and developing drug prevention and treatment—the crisis continues to worsen.
The primary variables affecting risk of infection are the rate at which humans are bitten and the proportion of mosquitoes that are infectious. These two factors are often regarded as positively correlated, meaning that if the percentage of infectious mosquitoes increases, so will the human biting rate. But in a new study, David Smith, Jonathan Dushoff, and F. Ellis McKenzie challenge this assumption. Using a mathematical modeling approach to examine the relative contributions of the two factors across different landscapes and seasons, the authors show that the factors are not positively correlated. In fact, their calculations show that the rate humans are bitten and the proportion of infectious mosquitoes peak at different times and places.
Their modeling results suggest that the standard metric to estimate risk of infection—the number of times an infectious mosquito bites a person per day, called the entomological inoculation rate (EIR)—is flawed when variable conditions are taken into account. Using the average EIR to estimate average risk of infection in variable environments generates biased estimates because there is not a direct correlation between EIR and the proportion of humans who are infected.
The distribution of humans and suitable habitat for mosquito larvae varies across the landscape. And the density of mosquito populations varies seasonally, rising and falling with changes in rainfall, temperature, and humidity. Temporal and spatial variations in mosquito populations affect the rate humans get bitten, the number of infectious mosquitoes, and the risk of infection. To understand how these space- and time-induced variations in mosquito populations shape the epidemiology of human infection, Smith and colleagues developed a set of mathematical models that calculate the relative impact of different parameters, in order to determine which factors most influence where and when risk of infection is highest.
First, they evaluated what factors affect the primary components of the EIR: the human biting rate and the proportion of infectious mosquitoes. As expected, the model predicts that fluctuations in mosquito density influence the EIR by changing the human biting rate. As more people are bitten, more people become infected; consequently, more mosquitoes feed on infected humans and so become infectious. Only adult mosquitoes transmit infection, so as mosquito populations age, the proportion of infectious mosquitoes increases. During the dry season, few mosquitoes are born, and so while the human biting rate and EIR decline, the proportion of infectious mosquitoes increases.
Because mosquito populations are densest near breeding sites—where younger mosquitoes outnumber adults—the human biting rate and the number of bites by infectious mosquitoes per person per day reflect shifts in mosquito density, not in the proportion of infectious mosquitoes. The model predicts that human biting rate is highest shortly after mosquito population density peaks, typically either near breeding sites or where human density is highest. The proportion of infectious mosquitoes, on the other hand, reflect the age of the mosquito population: it peaks where older mosquitoes are found—farther from breeding sites—and when populations are declining.
By mapping larval habitats against the local risk of mosquito-borne infections, Smith and colleagues conclude, epidemiological models can be developed to predict risk for local populations. Their results make the case that mathematical models can help public health officials calculate risk of infectious diseases in heterogeneous environments—that is, real world conditions—when vector ecology and the parameters of transmission are well characterized. Any plan to prevent and control the spread of mosquito-born infections would clearly benefit from paying attention to mosquito demography and behavior.
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020397SynopsisMolecular Biology/Structural BiologyMammalsWhere to Start? Alternate Protein Translation Mechanism Creates Unanticipated Antigens Synopsis11 2004 26 10 2004 26 10 2004 2 11 e397Copyright: © 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.
Unanticipated Antigens: Translation Initiation at CUG with Leucine
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In the spirit of good health, cells are constantly subjecting their protein contents to immunological surveillance by cytotoxic (killer) T cells. Tens of thousands of major histocompatibility complex (MHC) class I molecules cradle peptides (bits of proteins) on cell surfaces, and T cells detect any suspicious peptides with extreme sensitivity. If a cell is infected with a virus, peptides created from viral DNA will end up on the cell's surface as antigens, triggering immunological red flags.
Most—but not all—of the peptides presented by MHC class I molecules are created by conventional cellular mechanisms: with the help of a ribosome, three mRNA nucleotides (a codon) are decoded into a corresponding amino acid, which is strung as the next link on an elongating peptide. Most peptides begin with the amino acid methionine, coded by the mRNA nucleotide triplet A-U-G (AUG). But some peptides are “cryptic,” arising from normally untranslated regions of mRNA or initiated with codons other than AUG.
Previous studies suggested that an unconventional translation mechanism creates some cryptic peptides. But how? And why? Only one type of translation initiator, transfer RNA (tRNA), specific for AUG and loaded with a methionine molecule, is known. Protein synthesis beginning at alternate codons has been attributed to imprecise pairing between the methionine translation initiator and mRNA. This, however, does not explain proteins that do not begin with methionine.
Only two mechanisms for building non-methionine-initiated peptides have been discovered. In a new study, Susan R. Schwab et al. characterize one of them, the CUG-initiated translation of a peptide starting with leucine instead of methionine.
The authors explored cellular translation by engineering cells to create peptides of interest and present them through matching MHC molecules on the cells' surfaces. Then, by harnessing the exquisite sensitivity of T cells to probe for antigens on MHC molecules, they could identify which peptides were created under different experimental conditions.
Their findings point to a unique translation mechanism. In the other known example of a non-methionine-initiated peptide, translation beginning at GCU or CAA is guided by a specific folded structure of mRNA nucleotides called the internal ribosome entry site. Schwab et al. have found that no similar structure is necessary for CUG-initiated translation. However, similar to the standard mechanism of AUG initiation, they found that ribosomes do scan for CUG. Additionally, the presence of a specific ribosome-binding sequence in mRNA (the “Kozak context”) near a CUG site can enhance the efficiency of initiation there.
Schwab et al. have also suggested a possible purpose for this translation mechanism. Under stress, cells can down-regulate conventional translation, which curbs the production of viral proteins in the event of an infection but also suppresses the creation of antigens needed to flag down T cells for an immune response. Here, Schwab et al. report that peptides starting with leucine were produced in the absence of the protein eIF2, which normally aids in AUG-initiated peptide synthesis. Cells under stress slow conventional translation by restraining the function of eIF2. Therefore, CUG-initiated translation, which works without eIF2, might provide an out for stressed cells needing to create peptides. This alternative could be a great way to avoid pumping out viral proteins and still create antigens for T cell surveillance—unless, of course, viruses take advantage of the loophole for their own peptide production.
| 0 | PMC524256 | CC BY | 2021-01-05 08:21:16 | no | PLoS Biol. 2004 Nov 26; 2(11):e397 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020397 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020407SynopsisNeurosciencePrimatesPaying Attention to Memory 11 2004 26 10 2004 26 10 2004 2 11 e407Copyright: © 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.
Representation of Attended Versus Remembered Locations in Prefrontal Cortex
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If you could peer inside someone else's head, you'd see a scrunched-up gelatinous mass of tissue, weighing roughly a kilogram, homogeneous to the naked eye—in other words, a brain. The seeming uniformity of the overlying cerebral cortex, which has so outstripped other parts of the brain over the course of evolution that it makes up more than 80% of the brain, is belied by centuries of painstaking neuroscience. Some of the most compelling early evidence that parts of the cortex are specialized in their duties came from gun-shot wounds during the first world war. For instance, bullets lodged in the back of the brain disrupted sight in discrete portions of the visual scene, prompting insights into the localization and function of visual cortex.
The study of the front of the brain has a similar history of injury leading to insight. Phineas Gage, a railroad worker, had a 3.5-foot-long tamping iron blow straight through his frontal lobes and turned from a responsible, mild-mannered geek into an unruly exhibitionist overnight. Parts of the prefrontal cortex that he damaged have since been much studied for their involvement in motivation and emotional control.
More recent work has implicated other parts of the prefrontal cortex in working memory. Working memory is famously illustrated by your ability to temporarily remember a seven-digit telephone number, roughly the amount of information that you can store on-line in working memory for the duration of a task like phoning for a pizza.
Monkeys can be trained to remember information much like you remember a phone number, and then use the memory for gaining a reward (usually juice rather than pizza). They can learn to remember the specific location of a briefly flashed target on a screen and then, when cued, make an eye movement to look directly at that location. Previous research has shown that neurons in the prefrontal cortex maintain high rates of activity while monkeys remember the target location, and gradually the idea that the prefrontal cortex specializes in maintaining these transient memories has risen to dominance over other ideas about its functions.
In this issue of PLoS Biology, Mikhail Lebedev and his colleagues challenge this prevailing view with evidence that most prefrontal cortex neurons may not be so closely tied to working memory after all. As in previous research, they also trained monkeys to make an eye movement to a remembered target, but instead of only seeing one target, the monkeys saw two potential target locations during the course of the task. The monkeys had to pay attention to one of the potential targets, but this was not necessarily the one they would have responded to and was not the one they had to remember. To perform the task successfully, the animals had to engage their working memory, but most of the neurons the researchers recorded increased their activity selectively to the target that was the focus of attention.
Despite decades of research, the degree to which one region of the brain can be thought of as dedicated exclusively to a particular function is still much debated. These results do not refute the idea that the prefrontal cortex plays an important role in working memory. However, the authors suggest that this area may be more important in focusing the attention needed to remember that phone number, rather than actually holding that number in your mind.
| 0 | PMC524257 | CC BY | 2021-01-05 08:21:17 | no | PLoS Biol. 2004 Nov 26; 2(11):e407 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020407 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020410SynopsisImmunologyInfectious DiseasesMicrobiologyDanio (Zebrafish)A Clear View of Mycobacterial Infection Synopsis11 2004 26 10 2004 26 10 2004 2 11 e410Copyright: © 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.
Tuberculous Granuloma Formation Is Enhanced by a Mycobacterium Virulence Determinant
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Fighting an infection might seem to be a battle between David and Goliath, given the relative sizes of bacterial infectious agents and the animals they infect. But on closer examination it is more often a chess match between two skilled opponents who have the uncanny ability to anticipate each other's moves. Mycobacterium tuberculosis causes tuberculosis (TB) in people, and related species that infect other animals are used as model systems for the study of TB. Much progress has been made in identifying the armaments (or virulence factors) of the bacteria. But the interplay, or chess match, between the bacterium and the animal it infects is much less clear. One of the host's first moves against the mycobacterium is the formation of a granuloma. Granulomas are tightly aggregated structures that consist of macrophages—one of the first lines of defense of the immune system—within which the infecting bacterium grows. Besides these and related cells that are present at the site of infection, additional macrophages and other immune cells are recruited in the formation of the granuloma. Although granulomas are required for the elimination of the infection, Lalita Ramakrishnan and colleagues have now shown that the bacteria have a game plan of their own.
Mycobacteria co-opt granulomas for their growth and spread
One problem in understanding the interaction between the mycobacterium and the host has been that it occurs deep in the lung of the infected animal, which makes it difficult to analyze how each of the animal or bacterial factors affect the strategic interplay between the host and pathogen. To overcome this limitation, Ramakrishnan and colleagues used zebrafish embryos, which are transparent and can be infected by a relative of the TB pathogen, M. marinum. This enables the researchers to watch cells as they are recruited into the granuloma.
Some of the virulence factors of mycobacteria are encoded in an area of the genome called the RD1 locus. In a mouse model, a strain of the bacteria missing RD1 causes far less pathology than a strain with the full complement of genes. The RD1 locus is also absent in the bacterial strain M. bovis that is used as an attenuated TB vaccine. But the precise role of RD1 in infection remains obscure.
By visualizing in zebrafish infections of a virulent strain of M. marinum and a strain with an RD1 deletion, Ramakrishnan and colleagues have observed that RD1 is actually required for granuloma formation but isn't needed for the bacteria to infect macrophages. What's more, macrophages that are infected with mycobacteria that contain RD1 produce a signal that further recruits macrophages to granulomas. This might seem an odd virulence strategy, as macrophages are required for mycobacterial elimination. But in this ongoing chess match, the virulent mycobacterium exploits the host's defense—granuloma formation—by providing additional macrophages for the bacteria to infect.
The end game of the chess match remains unclear. While granulomas are required for protection against mycobacteria, they are not completely effective. Thus, these bacteria have developed a strategy to recruit the normally defensive cells of the host to their advantage, but it remains to be shown what tips the balance between the macrophages' ability to clear the infection and their unwitting participation in the development of TB.
| 0 | PMC524258 | CC BY | 2021-01-05 08:21:21 | no | PLoS Biol. 2004 Nov 26; 2(11):e410 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020410 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020411SynopsisNeuroscienceSystems BiologyPrimatesCaenorhabditisOnly Connect: The Functional Architecture of Brain Connectivity Synopsis11 2004 26 10 2004 26 10 2004 2 11 e411Copyright: © 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.
Motifs in Brain Networks
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Imagine three cities, A, B, and C, splayed across the landscape to form a triangle, with each connected to the other two by two-lane roads. Such an arrangement of cities and roads constitutes a structural network. On any given day traffic may flow, say, only from A to B to C, or in both directions between A and B but from C only to A, or in both directions between all three, or any one of ten other arrangements. Within this structural network, then, there are 13 possible functional networks. If these cities are embedded within a larger network of routes and destinations, their particular triangular traffic pattern represents a “motif” of connectivity, akin to a recurring musical motif within a larger symphony.
Such connectivity networks are central to information processing in the brain, and understanding the recurring structural and functional motifs they contain is one way to begin to dissect how the symphony of brain function is composed. In this issue, Olaf Sporns and Rolf Kötter identify several common motifs in real brain networks, and show that brains tend to maximize the number of functional motifs while keeping the number of structural motifs relatively low.
Figure 1 The authors began with the frequency of motifs of different sizes (two, three, four, or five nodes) found in the visual cortex and whole cortex of the macaque monkey, the cat cortex, and the nervous system of the nematode Caenorhabditis elegans. For comparison, they generated matrices that contained an equivalent number of components (nodes and connections), but whose connections were either random or lattice-like, in which all nearest neighbors were connected. They found that, compared to the artificial networks, the biological ones were relatively low in structural diversity. For instance, macaque visual cortex contained instances of 3,697 different motifs with five nodes, versus 8,887 for equivalent random networks. Functionally, however, unlike the artificial systems, the biological systems were maximally diverse, with the maximum functional motif diversity (e.g., 13 for three vertices and 9,364 for five vertices) observed in all motif sizes they investigated.
The researchers also found some intriguing patterns within this maze of connectivity. For instance, not all motifs were found in equal numbers. A common functional motif for three vertices was for both A and C to communicate back and forth with B, but not with each other. This structure allows B to function as an integrator of signals from A and C, while keeping the activities of A and C distinct from one another. This kind of structure is widespread throughout the nervous system.
The authors then ran an evolutionary algorithm on their artificial networks. They showed that by selecting for maximal functional motif number, the structure of the artificial systems quickly came to resemble the structure of the real ones, with dense local connections and relatively fewer long-distance ones. Such a structure, termed “small world” connectivity, promotes cooperation between functional units, and efficient information exchange. Taken together, these results suggest that one factor that may drive the evolution of neural architecture is the maximization of functional connectivity within a network of relatively few neural actors.
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020413SynopsisEvolutionZoologyBirdsTaking Stock of Biodiversity to Stem Its Rapid Decline Synopsis12 2004 26 10 2004 26 10 2004 2 12 e413Copyright: © 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.
Measuring Global Trends in the Status of Biodiversity: Red List Indices for Birds
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Far more species exist in the fossil record than inhabit Earth today. An estimated 94% of all bird species that ever lived, for example, are now extinct. So why is species extinction of urgent concern today? Though species come and go over evolutionary time, mass extinctions are relatively rare. Biologists believe they have occurred only five times, arising from relatively short-lived cataclysmic natural forces like astronomical or volcanic events. We are now on the brink of the Sixth Great Extinction, and we humans are largely to blame. For thousands of years, humans have retooled the landscape, an endeavor that has rarely coincided with the life history needs of local flora and fauna: over 150 bird species alone have vanished since 1500.
As our capacity to alter the landscape has mushroomed, species have started disappearing faster than biologists can identify and document them. Mindful of this crisis, nearly 200 countries (under the Convention on Biological Diversity, or CBD) agreed to staunch the loss of biodiversity by 2010, with the European Union raising the bar to halt biodiversity loss by that time. To meet this goal, biologists need reliable metrics to monitor global trends in biodiversity. Stuart Butchart et al. describe a new model for generating such indices to measure trends in extinction risk for complete classes of organisms, starting with the world's 10,000 bird species. Their “Red List Index” measures changes in overall extinction risk over time for all bird species worldwide. Similar indices are already being developed to track other groups, including mammals and amphibians, and in the future will hopefully be developed for some plant and invertebrate groups.
In 2002, the CBD proposed that efforts to monitor global trends in biodiversity start by developing indicators to evaluate trends in biodiversity components, such as ecosystems and habitats, abundance and distribution of selected species, and change in threat status of species. Butchart et al. focus on evaluating trends in changes in threat status (extinction risk), relying on categories developed by the World Conservation Union (IUCN) Red List. Species are placed in categories on the Red List ranging from extinct to “least concern,” according to criteria that take into account their population size, population trends, and range size. Thousands of scientists from around the world feed these assessments, which have been widely used to measure the degree of degradation of biodiversity.
Rufous-collared Kingfisher: Deforestation threatens its survival (Photo: Jakob Wijkema)
To use the Red List to track biodiversity trends over time, Butchart et al. collected data from four complete assessments of the world's birds over sixteen years, supplemented by other sources. The number of threatened and near threatened species increased from 1,664 species in 1988 to 1,990 species in 2004, but many species moved between categories. To calculate the real net increase in extinction risk for the world's birds over this time, the authors first identified reasons for these category switches to remove biases introduced by factors irrelevant to genuine changes in species status; category changes owing to better knowledge, for example, do not reflect real changes in conservation status. They also accounted for time lags between status changes, and category changes owing to delays in knowledge becoming available to Red List assessors.
The authors argue that the Red List Index provides a simple measure of trends in the status of avian species worldwide, in terms of their overall extinction risk. Overall, the index shows “a steady and continuing deterioration in the threat status of the world's birds between 1988 and 2004.” Though the extinction risk has improved for some species, it has deteriorated for others, with “particularly steep declines” in recent years for Asian birds—resulting from massive deforestation in Indonesia—and for seabirds such as albatrosses and petrels, which drown on the hooks of commercial long-line fisheries.
Butchart et al. argue that Red List Indices complement indicators based on population trends, because although the indices show coarser temporal resolution, they have much better geographic representation; they're based on nearly all species in a group worldwide rather than on a potentially biased subset. Both types of species-based indicators show finer ecological resolution in tracking biodiversity loss than indicators like habitat or biome trends. Thus, the Red List Index provides a baseline for tracking progress toward the 2010 target. But having a reliable indicator is only the first step. Without an international commitment to halt the advancing extinction crisis, biodiversity will continue to decrease. The United States is the only industrialized nation that has not signed on to this effort.
| 0 | PMC524260 | CC BY | 2021-01-05 08:21:16 | no | PLoS Biol. 2004 Dec 26; 2(12):e413 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020413 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020414SynopsisNeurosciencePsychologyHomo (Human)One Brain, One Vision Synopsis11 2004 26 10 2004 26 10 2004 2 11 e414Copyright: © 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.
Perception, Action, and Roelofs Effect: A Mere Illusion of Dissociation
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Not all devices that measure the same property do it in the same way—a clock might use a spring system or it might be digitally synchronized to a transmitted signal. Although both have the same goal of reporting accurate time, each is subject to different errors. Sometimes even the same device uses different systems to measure the same property. A relatively simple device like a camera will use one sensor system to capture light intensity for an image and a second sensor to capture light intensity for making automatic adjustments of aperture and flash. It does not seem outlandish, therefore, that the brain might also have developed multiple sensory systems to achieve different goals. Indeed, an influential hypothesis has argued that people use two separate visual processing systems in much the same way as a camera—one for creating our perception of the world and another for guiding our actions within it.
One line of evidence supporting this dual hypothesis comes from an illusion known as Roelofs effect. Usually, people are pretty good at judging the location of even a small object. But if the small object is surrounded by a large frame and the frame itself is not centered in front of the person who is judging it, the viewer will perceive the object as shifted in a direction opposite that of the frame. This may not in itself be surprising, but the same person who perceives an offset of the object where none exists is nonetheless able to grasp it without difficulties.
Figure 1 In this issue of PLoS Biology, Paul Dassonville and his colleagues reexamine the seeming dissociation of visual analysis for perception and action, and call it into question. Through a careful quantitative analysis of the conditions under which the Roelofs effect occurs, they find that it traces not to an illusory perception of the object location but to an illusory perception of self. The large frame, presented under experimental conditions in which subjects sit in darkness without access to a normal rich sensory environment, actually causes people to incorrectly perceive their own centers as rotated towards the frame and therefore to conclude that the small object is offset with respect to themselves. This may seem like a subtle distinction, and yet, since it is the observer's frame of reference that is altered, that same distorted frame of reference will be used to guide movement. Thus, the error in movement planning should cancel the error in perception, and people should have no trouble reaching for the object despite their misperception, which is indeed what is observed.
Others have questioned the hypothesis that two separable neural systems process the visual world for perception and action, but this study removes one of the strongest pieces of evidence in its favor with a precise alternative explanation. No two brains may see the world identically, but the authors suggest that it may be time to concede that a single brain, at least, has the same world view.
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1551470010.1371/journal.pbio.0020329Research ArticleBioengineeringBiophysicsNeuroscienceNoneSerial Block-Face Scanning Electron Microscopy to Reconstruct Three-Dimensional Tissue Nanostructure Serial Block-Face SEMDenk Winfried denk@mpimf-heidelberg.mpg.de
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Horstmann Heinz
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1Max Planck Institute for Medical ResearchHeidelbergGermany11 2004 19 10 2004 19 10 2004 2 11 e32923 5 2004 29 7 2004 Copyright: © 2004 Denk and Horstmann.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.
Reconstructing Neural Circuits in 3D, Nanometer by Nanometer
Three-dimensional (3D) structural information on many length scales is of central importance in biological research. Excellent methods exist to obtain structures of molecules at atomic, organelles at electron microscopic, and tissue at light-microscopic resolution. A gap exists, however, when 3D tissue structure needs to be reconstructed over hundreds of micrometers with a resolution sufficient to follow the thinnest cellular processes and to identify small organelles such as synaptic vesicles. Such 3D data are, however, essential to understand cellular networks that, particularly in the nervous system, need to be completely reconstructed throughout a substantial spatial volume. Here we demonstrate that datasets meeting these requirements can be obtained by automated block-face imaging combined with serial sectioning inside the chamber of a scanning electron microscope. Backscattering contrast is used to visualize the heavy-metal staining of tissue prepared using techniques that are routine for transmission electron microscopy. Low-vacuum (20–60 Pa H2O) conditions prevent charging of the uncoated block face. The resolution is sufficient to trace even the thinnest axons and to identify synapses. Stacks of several hundred sections, 50–70 nm thick, have been obtained at a lateral position jitter of typically under 10 nm. This opens the possibility of automatically obtaining the electron-microscope-level 3D datasets needed to completely reconstruct the connectivity of neuronal circuits.
A new method combines automated imaging with serial sectioning inside the chamber of a scanning electron microscope
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Introduction
Many cellular structures are so small that they can only be resolved in the electron microscope. Furthermore, it is often crucial to visualize and reconstruct the three-dimensional (3D) structure of biological tissue. One prime example of where 3D information is indispensable is in exploring the connectivity of local networks of neurons. While axonal and dendritic processes have been traced using the light microscope from the very beginning of cellular neuroscience (Cajal 1911), light microscopic tracing is only possible if staining is restricted to a small subset of cells, as results, for example, from the Golgi method (Golgi 1873) or from the mosaic expression of fluorescent proteins (Feng et al. 2000). However, in many cases, in order to understand computational algorithms, the reconstruction of a complete neural circuit may be necessary. For this, the resolution of the light microscope is insufficient because dendritic and axonal processes can have diameters that are substantially below the wavelength of light. This lack of resolution (1) results in the inability to resolve densely packed neighboring processes, which is absolutely necessary to reconstruct network topology, and (2) does not allow a sufficiently precise estimation of the neuronal geometry, which may be necessary for biophysical modeling of cellular behavior. So far, only the electron microscope (EM) can provide the spatial resolution needed to track neural processes or to identify synapses unambiguously. Most commonly used to image biological tissue is the transmission electron microscope (TEM) (Ruska and Knoll 1932), in which a broad beam of electrons is directed at a sample that is thin enough to allow a substantial fraction of the electrons to pass through and then be focused onto film or another electron-sensitive spatially resolving detector. Specimens are typically thin slices that are cut from blocks of plastic-embedded tissue, with the resulting electron micrographs providing a two-dimensional cross section through the tissue. Scanning electron microscopy (SEM) (Ardenne 1938a, 1938b), in which a tightly focused beam of electrons is raster-scanned over the specimen while secondary or backscattered electrons are detected, is used in biological imaging mostly as a surface visualization tool, creating a 3D appearance but no actual 3D datasets.
Truly 3D information in the TEM can be obtained using either tilt-series-based tomography (Hoppe 1981; Frank 1992; Baumeister 2002) or serial ultrathin sections (Sjostrand 1958; Ware and Lopresti 1975; Stevens et al. 1980). Tomography is a very promising technique for obtaining high-resolution structural data of macromolecules, organelles, and small cells but may not be applicable when larger volumes need to be reconstructed, because section thickness is limited to around 1 μm. In the high-voltage EM, somewhat thicker sections can be viewed, which facilitates the correlation with light microcopy (Martone et al. 2000).
Serial-sectioning TEM, which can be used to obtain 3D data of much thicker volumes than is possible with tomography, is a mostly mature technology and has contributed enormously to our understanding of the local 3D ultrastructure, for example of dendritic spines (Harris 1999). A whole animal, the nematode Caenorhabditis elegans has been reconstructed in this way (White et al. 1986). This is still considered a seminal effort, partly because serial sectioning is such a labor-intensive and time-consuming method, which requires intensive operator involvement in cutting sections, gathering data, and reconstructing volumes. The number of sections that need to be handled can be reduced by combining tomography with serial sectioning (Soto et al. 1994), but the need to manually handle the sections remains. For these reasons the number of larger-scale 3D serial reconstructions has been rather limited, even though many biological problems, not only the tracing of neural circuits, require truly 3D information.
Volume information equivalent to that from reconstructing serial sections can, of course, be obtained if the sections are imaged before being cut, that is, by repeatedly imaging the block face. Block-face imaging is used even in light microscopy (Odgaard et al. 1990; Ewald et al. 2002), where optical-sectioning techniques, such as confocal (Minski 1961) or multi-photon microcopy (Denk et al. 1990), are readily available. It is, of course, impossible to image the block face in the TEM. The SEM, as a surface-imaging technique, is, on the other hand, well suited for this task. This was recognized several decades ago by Leighton, who also constructed a microtome for cutting sections inside the microscope chamber (Leighton 1981). Imaging the block face removes not only the need to deal manually with ribbons of fragile sections but also the difficulty of aligning the images of sections, which are often distorted. The prevalent contrast mode in the SEM is the detection of so-called secondary electrons, which are low-energy electrons that are emitted when the primary electron beam strikes the sample surface. The secondary-electron signal depends strongly on the orientation of the surface, leading to topographic images that characteristically resemble obliquely illuminated solid objects. Since the microtome-cut block surface is devoid of topographic features, very little contrast is generated unless an additional preparatory step, such a plasma etching (Kuzirian and Leighton 1983; Hukui 1996), is used.
At the time of Leighton's original work, no stacks of volumetric data were presented. One reason might have been that low-vacuum SEMs (also called atmospheric [Robinson 1975; Danilatos 1980] or environmental SEMs; for a recent review see Donald [2003]), which can be used to image nonconducting specimens (see below), were not widely available. In the original report (Leighton 1981), the sample had to be removed from the SEM chamber for coating with a conducting layer. Furthermore, digital image acquisition, storage, and processing were in their infancy and quite limited in capacity.
In this paper we show, first, that by using backscattering contrast and low-vacuum operation we can obtain high-contrast images from cut block faces and, second, that in combination with a custom-designed microtome we can obtain 3D ultrastructural data with a resolution and from volumes appropriate for the 3D reconstruction of local neural circuits.
Results
As a first step, we explored whether sufficient contrast and stable images can be obtained from uncoated block faces of plastic-embedded tissue, prepared essentially as for TEM. There are a number of techniques known that allow imaging of nonconducting specimens in the SEM. One technique relies on choosing an accelerating voltage at which the introduction of charge by the electron beam is just balanced by the sum of backscattered and secondary electrons (for a review see Joy and Joy [1996]). We first tried the charge-balance method (electron energies around 600 eV) but found that the secondary-electron signal provides, not surprisingly, unsatisfactory contrast (data not shown). The secondary-electron signal is the only contrast available because low-energy backscattered electrons (BSEs) cannot be easily detected at such low voltages. Furthermore, residual charging, which may not be strong enough to preclude the formation of an image, can still lead to slight shifts between images by electrostatic beam deflection. This then destroys the alignment between successive images, which is one of the main reasons to establish serial block-face imaging.
Another set of techniques relies on providing ions in the specimen chamber to neutralize charge on the sample rather than avoiding net charge introduction by the electron beam. This can, for example, be achieved by maintaining a low concentration of gas in the chamber (Robinson 1975; Moncrieff et al. 1978) at a pressure (10–100 Pa) that is low enough for a substantial fraction of the beam's electrons to reach the sample unscattered and thus be able to form a tight focus. Ions needed for discharging the sample are generated by those electrons that do strike gas molecules or atoms.
The residual-gas method (also called low-vacuum or variable-pressure mode) can be used at higher accelerating voltages and is, therefore, compatible with BSE contrast. Since scattering of electrons is strongly dependent on the charge of the atomic nucleus, the BSE signal provides a clear distinction between heavy-metal-stained and unstained structures (Figures 1 and S1) that, after contrast reversal, look very similar to traditional transmission electron micrographs. Images of uncoated block faces (Figure 1) resemble scanning electron micrographs obtained from block faces of similar specimens coated with a very thin conducting film and imaged under high-vacuum conditions (Richards and ap Gwynn 1996). Our BSE images also demonstrate that the resolution under these conditions is sufficient to resolve structures such as synaptic vesicles (Figure 1A) or the array of actin filaments characteristic of skeletal muscle (Figure 1B). Synaptic contacts in cortical tissue can be clearly identified as well (Figure 1D and 1E).
Figure 1 Resolution and Contrast Using the Backscattered Electron Signal
(A and B) Presynaptic vesicles (SV) and postsynaptic folds (SF) are clearly visible (A) in a motor endplate preparation embedded in Spurr's resin. Similarly, the hexagonal array of actin filaments (AA) can be clearly resolved (B) in a different region from the same image (both images were smoothed using the ImageJ “smooth” command). Imaging conditions for (A) and (B): electron energy, 7.5 keV; spot, 3.5; chamber pressure, 30 Pa (H2O); pixel dwell time, 30 μs. The scanning resolution was 6.7 nm/pixel.
(C) The effect of beam exposure on the block surface. Note the increased brightness and the lack of chatter in the central region (inside the dashed rectangle), from which a stack was acquired at higher resolution before taking the image shown. The tissue was rat neocortex embedded in Spurr's resin. Imaging conditions for (C): electron energy, 7.5 keV; spot, 3; digital resolution for stack acquisition, 26.7 nm/pixel; dwell time, 30 μs.
(D and E) Cortical tissue embedded in Epon. Synapses (SD) are clearly discernable (E). Imaging conditions for (D) and (E): electron energy, 7.5 keV beam current; spot, 3; chamber pressure, 30Pa (H2O); pixel dwell time, 30 μs. The scanning resolution was 9.5 nm/pixel.
Note that more backscattering corresponds to darker pixels in (A), (B), (D), and (E) but to brighter pixels in (C).
These results show that we can obtain sufficient contrast from uncoated block faces. On this basis we decided to construct an ultra-microtome appropriate for sequential sectioning inside the sample chamber of an SEM. There are a number of special requirements for such a microtome. (1) The position of the block has to remain stable or be returned to the same location after each image is taken in order to ensure alignment of subsequent images, which is one of the primary objectives of serial block-face imaging. (2) The distance between the block face and the SEM objective lens has to be sufficiently small to allow high-resolution imaging and the efficient collection of backscattered electrons under low-vacuum conditions. (3) The block face has to be perpendicular to the optical axis of the electron optical column to keep the whole block face in focus; for all commercial SEM instruments this means horizontal orientation. (4) The operation of the microtome must be remotely controllable to allow automation. (5) The microtome has to be compatible with low vacuum. Finally, (6) the range of the fine advance mechanism has to be at least several hundred microns to permit continuous sectioning of volumes large enough to be of interest in the study of local neuronal circuits. Conditions 1, 2, and 3 rule out the modification of a conventional ultra-microtome, in which the sample block, its face oriented vertically, is moved against a stationary knife. Condition 2, in addition, rules out the use of a conventionally mounted diamond knife, since the boat would protrude upwards, colliding with the BSE detector and even with the objective lens.
We, therefore, decided to construct a microtome de novo (Figure 2; for details see Materials and Methods), which does share some design features with the instrument built by Leighton (1981). A custom knife that could fit under the detector was designed in cooperation with the Diatome company and fabricated by Diatome. To meet condition 1 above, the knife is moved for cutting. In the z-direction, sample advance rather than knife advance is used in order to keep the cutting plane, and hence the location of the block surface, constant. This removes the need for refocusing the SEM, thereby contributing to image stability and registration. To avoid sliding friction, crossed leave flexures were used for the knife arm and for the sample advance mechanism. To provide advance motion with sufficiently fine resolution, we used a lever mechanism that scaled the motion of a motorized micrometer down by a factor of roughly 1/9. To minimize heat production, which can lead to thermal drift and is hard to dissipate in vacuum, we used a direct-current motor drive.
Figure 2 SEM Microtomy
(A) Principle of SBFSEM operation: (1) a SEM image is taken of the surface of the plastic-embedded tissue preparation (amber trapezoid). (2) Then with a diamond knife (blue) an ultrathin slice is cut off the top of the block. (3) After retraction of the knife, the next picture is taken. The pictures shown are from an actual stack (cerebellar cortex) but are not successive slices; rather, they are spaced by five images (about 315 nm) to make the changes more apparent.
(B) Usually cut-off slices pile up on the top of the knife. Protruding into the picture from the right is a puffer pipette, occasionally used to remove debris from the knife.
(C and D) The mechanical design for the in-chamber microtome is shown in an overview (C) and a close-up of knife and sample (D) in renderings from the computer-aided design software. Most parts are nonmagnetic stainless steel (grey). A large-motion leveraged piezo actuator (green part on the left) drives the knife holder back and forth. The custom diamond knife (light blue) is clamped in a special holder. The sample (amber) advance is driven via a lever by a direct-current-motor-driven micrometer (dark blue). The retraction during the backwards knife motion is again piezo actuated (green cylinder in the lower right of [C]). Bearing springs are brown. The BSE detector (red) is depicted schematically above the sample. Not shown is the lateral positioning mechanism.
Preparation of samples for the serial block-face SEM (SBFSEM) was done using procedures common for preparing samples for viewing in the TEM (see, for example, Hayat 2000). Since SBFSEM does not allow contrast enhancement after cutting, which is often used in the TEM, we tested several methods of enhancing the contrast of the whole block and found that exposing the tissue to uranyl acetate (see Materials and Methods and also Hayat [2000], p. 342ff) leads to excellent contrast in BSE mode (see Figure 1).
We could reliably cut serial sections thicker than about 50 nm, the exact lower thickness limit depending on the embedding material and the beam exposure (an upper thickness limit was not established). When trying to cut thinner sections the actual thickness became uneven or the knife would skip every other cut, as recognized by the lack of change in structural detail. Another indication of uneven cutting is alternating brightness of the whole images or image regions. The reason for this is that the backscattering efficiency generally increases after beam exposure (see Figure 1C), which may be because a selective ablation of the embedding matrix leads to an effective increase in the heavy-metal concentration.
Usually the cut-off slices pile up on the top surface of the knife (see Figure 2B). Only rarely does a sliver get deposited on the block surface. When this happens it results in the loss of only one image since the sliver is reliably removed by the next passage of the knife. During the cutting of the stack used for Figure 3A and 3B, three instances of deposited debris occurred (white horizontal streaks in Figure 3B). Currently efforts are underway to devise methods (such as using a brief puff of gas from a glass pipette, such as can be seen in Figure 2B) to reliably remove the debris from the knife after each cut.
Figure 3 3D Datasets: Five Slices
(A) Five slices from a stack containing a total of 365 slices at 63-nm section thickness; same tissue as in Figure 1A and 1B. Note beginning of myelin sheath (MS) in the lowest slice. Imaging conditions as in Figures 1A and 1B except resolution is 13.4 nm/pixel.
(B) Reslice of the same dataset along the red line show in the top image of (A). Arrows point to the presynaptic ending (PS) and the z-band (ZB). Image corners in (A) touch the reslice (B) at the depths at which they were taken.
(C and D) Cerebellar tissue displayed at low (C) and high (D) resolution; note nuclear envelope (NM). Note differences in lateral and vertical resolution. Imaging conditions for (C) and (D): electron energy, 7.5 keV; spot size, 3.5; digital resolution, 12.7 nm/pixel.
We found, somewhat surprisingly, that cutting quality was often better in the area scanned by the electron beam than outside (see Figure 1C), presumably because of a modification of the mechanical properties of the embedding material. We have successfully cut a number of different embedding materials (Araldite, Epon, and Spurr) and tissue types (mammalian muscle, cortex, cerebellum, retina, zebrafish brain, and fly brain) using our SBFSEM setup. Figure 3 shows examples of 3D datasets.
Since lateral registration between successive slices is crucial for the applicability of the SBFSEM technique for automated 3D reconstruction, we quantified the registration using cross correlation. Figure 4 shows the registration precision throughout a stack of images from muscle tissue. The fluctuations are mostly around 10 nm in size (standard deviation). Large fluctuations (greater than 60 nm) are seen occasionally but can be traced to temperature drifts or are spurious values caused by debris on the block face. Some of the apparent position shifts and fluctuations do not, furthermore, represent registration errors but are caused by systematic or random pattern shifts. An example is the shift of the central cloud of points in Figure 4B, which is caused by the tilt of the actin fibers from the block-face normal.
Figure 4 The Alignment of Successive Images in a Stack
Shifts between images were quantified using the positions of the peaks of the cross correlation (see Materials and Methods); same dataset as in Figure 3A and 3B.
(A) The peak shifts in x-direction are shown for five different subregions distributed over the field of view. Four of the regions have a size of 256 × 256 pixels, one has a size of 512 × 512 (black trace). The peaks around slices 59 and 202 are caused by slice debris on the block face (see also streaks in Figure 3B).
(B) The x/y displacement for the 512 × 512 region is shown in a scatter plot. For the central cluster the standard deviations are 10.9 nm and 11.8 nm for x and y, respectively.
The depth resolution depends, of course, on the section thickness but also on the depth below the sample surface from which the BSE signal originates, which, in turn, scales with the electron penetration (see chapter 3 of Goldstein et al. [2003]). For our early experiments we had used the electron energy of 7.5 keV because lower voltages gave unsatisfactory signals. At 7.5 keV the resolution along the z-axis is not very good, as is apparent from Figure 3D. To improve the z-resolution one could conceivably use deconvolution techniques because the point spread function contains a sharp edge and hence high spatial frequencies along the z-axis, even if the electron penetration into the sample is large. The reason is that while a structural detail can contribute to the signal if buried in the sample, the contribution from that detail drops immediately to zero as soon as the slice containing the detail is removed.
Electron penetration depends strongly (Kanaya and Okayama 1972) on the energy (scaling as E
1.67). This means, for example, that at 4 keV the depth is reduced to about one-third of that at 7.5 keV. The actual value for the depth penetration is difficult to estimate for a composite material such as plastic-embedded heavy-metal-stained tissue. For a detailed discussion of the issues surrounding depth penetration see, for example, chapter 3 of Goldstein et al. (2003). We, therefore, decided to operate the SBFESM at lower voltages. In order to obtain sufficient signal at the lower electron energy, where the efficiency of semiconductor-diode BSE detectors declines steeply (Funsten et al. 1997), we replaced the detector amplifier with an instrument originally designed to detect single ion-channel currents (commonly called a patch-clamp amplifier [Hamill et al. 1981]) and found that we could now get satisfactory images for electron energies of 4 keV. In Figure 5 the depth resolutions at 7.5 and 4 keV are directly compared for the same sample. It is particularly encouraging that at 4 keV it is possible to recognize clearly membranes that are parallel to the block surface (en-face membranes), which is crucial for the successful reconstruction of cellular topology.
Figure 5 Energy Dependence of the Depth Resolution
The lateral resolution does not change very much as the electron energy is reduced from 7.5 keV (A) to 4 keV (B), but the resolution along the z-direction is dramatically different (C). The lines between (A), (B), and (C) indicate the z-positions in the stack from which (A) and (B) were taken. In the high-resolution view (lower panel in [C]) membranes that were en-face (EM) in the original slices can be clearly recognized. The nominal slice thickness was 55 nm. Tissue is rat cortex. Imaging conditions: dwell time, 25 μs; spot sizes, 3.5 and 2.8 for 4 and 7.5 keV, respectively.
Discussion
We have shown that fully automated acquisition of truly 3D datasets at nanoscopic resolution is possible with serial block-face imaging in the SEM. The lateral resolution is sufficient to recognize most cellular organelles and synaptic specializations and does not appear to be limited by the beam spot diameter but by the spread of the beam in the sample (Kanaya and Okayama 1972; see also Joy and Joy 1996). This spread could be further reduced by using lower beam energies, provided that more sensitive detectors for such low electron energies can be obtained (Funsten et al. 1997). Lower beam energies also would further improve the z-resolution, even though at some point elemental contrast in the BSE signal begins to decline (Joy and Joy 1996). The resolution is, in practice, also limited by the radiation dose that a specimen can sustain. Since at lower electron energies the beam's energy is deposited into a rapidly shrinking volume, heating effects could become an issue. Nonetheless, it appears conceivable that nearly isotropic resolution can be achieved if the sectioning thickness can be reduced to around 20 nm (see below), with imaging then done at primary electron energies of around 2 keV. Because the registration between successive slices (see Figure 4) is mostly better than the resolution, the 3D data stacks can be used without further alignment and distortion correction (for the complete set of raw data see Datasets S1–S20; slices through this dataset are shown in Figures S2–S4) . This is crucial if automated reconstruction is to be performed, since alignment of serial sections often requires manually identified landmarks.
It would be highly desirable to reliably cut sections thinner than 50 nm, which appears to be the current limit in our hands. The exact reason for this thickness limit is not clear as yet. Much thinner sections have been cut from plastic blocks (Frosch et al. 1985), albeit under atmospheric pressure with the sections floated onto water. An important difference between standard ultra-microtomy and SBFSEM is that, because of the inevitable exposure of the block face to the electron beam, the mechanical properties of the block surface are changed, affecting cutting of subsequent sections. While at very high doses these effects are deleterious, they can be helpful at intermediate levels for suppressing chatter (see Figure 1C). To suppress chatter and to achieve thinner sectioning, we have begun to use the oscillating-knife technique (Studer and Gnaegi 2000) (see Figures 5 and S2–S4). It might also help to reduce the sample temperature, which, in addition to affecting cutting properties directly by changing the polymer stiffness, might substantially improve the resistance to radiation damage (Lamvik 1991). SBFSEM might ultimately allow a smaller section thickness than is routinely possible with serial sectioning for the TEM, since there the mechanical integrity of the cut sections has to be ensured. Alternatively, one might use nonmechanical surface-ablation techniques such as plasma etching, reactive or focused ion beam etching, or ion milling to achieve smaller depth increments. Nonmechanical techniques do, however, suffer from a dependence of the ablation rate on the composition, which is, by the very nature of embedded tissue, rather inhomogeneous.
In spite of the similarity in appearance, it is important to keep in mind a number of differences between transmission imaging of sections and backscattered SBFSEM. First, in the SEM, a large fraction of the entire beam energy is deposited inside the sample, leading to much increased radiation damage per primary electron. This is partly counteracted by the fact that BSE imaging is a “dark field” technique and, therefore, each detected electron carries more information. Furthermore, because the primary-electron energies can be lower by a large factor in the SEM (4 keV) than in the TEM (typically about 80 keV but routinely as high as 300 keV and up to 3 MeV in special cases), scattering cross sections are much larger in the SEM. This may, however, not always translate into improved contrast, since in the SEM only electrons scattered by angles larger than 90° can contribute to the image, while rather small deflections are enough to remove an electron from the beam in the TEM. A major practical advantage of SEM block-face imaging is that there is no need to manually handle sections, and no occlusion occurs by EM-grid bars. On the other hand, it is, unlike in TEM, impossible to reimage a section at higher resolution. Finally, it is unlikely that SEM surface imaging will ever reach the lateral resolution that can be achieved by imaging thin sections in the TEM.
The total volume that can be reconstructed by SBFSEM is currently limited in the lateral dimension by the digital resolution available on commercial SEM instruments. It should, however, be straightforward to increase the digital resolution by modifying the scan and data-collection cir-cuitry. Eventually, off-axis electron-optical aberrations will become significant, but the total field of view can then be increased by mechanical translation of the microtome and tiling of multiple images. In the z-direction the stack height that can be cut continuously is, first, limited by the travel of the fine advance. Second, and more fundamentally, the cutting pyramid becomes unstable and too compliant if it is too high. However, a single step of image realignment after retrimming and repositioning will allow the continuation in the z-direction for almost unlimited distances.
A major practical limitation is, of course, the acquisition speed of the SEM, which is ultimately dependent on the required signal-to-noise ratio (RSN). We can estimate the minimally achievable voxel dwell time (τd) using the backscattering coefficient (η) as follows:
where IB is the beam current and e is the elementary charge. The available beam current depends on the electron-gun type, the desired resolution, and the electron energy, but a value of IB = 1 nA is realistic for our purposes. We set η to 0.1, which is the value for carbon and thus a lower limit since backscattering is, of course, higher for the heavy-metal-stained areas (Drescher et al. 1970; see also chapter 3 in Goldstein et al. [2003]). To get RSN =100 we then need a dwell time of 16 μs, allowing data rates slightly above 50,000 voxels/s. A cube 200 μm on a side imaged at a resolution of 10 nm × 10 nm × 50 nm, which corresponds to 1.6 teravoxels, would then require a total scan time of 25,600,000 s, which is on the order of one year. However, the tracing of axons probably can, with the appropriate staining, be achieved at 20-nm lateral resolution and with an RSN of ten or less. This reduces the estimated time by a factor of 400, to less than one day. While in some cases the resolution provided by conventional (tungsten filament) electron guns may be sufficient, we feel that the long-term stability of field-emission emitters is essential for imaging large volumes.
The approach described here will speed up the collection of medium-to-high resolution 3D electron microscopic datasets by several orders of magnitude. The acquired data will, in addition, not require time-consuming and error-prone alignment and distortion correction. This should have wide-ranging applications not only in biomedical research but also in materials characterization (Alkemper and Voorhees 2001). We are particularly interested in the complete reconstruction of local neural circuits such as those that underlie the detection of motion in the retina (Barlow et al. 1964; Euler et al. 2002). This requires the imaging of volumes containing at least one complete dendritic tree and is therefore virtually impossible using conventional electron microscopic methods. The data quality using current staining techniques is good enough to manually trace neuronal processes in many cases (see Figure S5). One of the major challenges will be the automation of data analysis, which could well require the development of novel or the further optimization of existing staining techniques that highlight the plasma membranes or the extracellular space (Brightman and Reese 1969).
It is quite likely that scanning-probe methods such as atomic-force or near-field microscopy could be used instead of SEM to image the block face. It would be particularly interesting if multiple fluorescent dyes could be detected and discriminated in this way since they still provide unmatched specificity in labeling biological samples.
Materials and Methods
Imaging
All data shown were taken on a environmental SEM with a field-emission electron gun (QuantaFEG 200, FEI, Eindhoven, the Netherlands) mostly at an electron energy of 7.5 keV (exceptions as noted, see Figures 5 and S2–S4, Datasets S1–S20, and Video 2). For data in Figures 5 and S2–S4, Datasets S1–S20, and Video 2, a highly sensitive current amplifier was used (Axopatch200B, Axon Instruments, Union City, California , United States) to amplify the current from the solid-state backscattered electron detector (type L2, K. E. Developments, Cambridge, United Kingdom). The beam current values for the parameters used were roughly interpolated from manufacturer's data, yielding estimated beam currents of 190, 430, and 880 pA for spot sizes of 2.5, 3, and 3.5, respectively, at a beam energy of 7.5 keV, and 150, 330, and 645 pA for spot sizes of 2.5, 3, and 3.5, respectively, at a beam energy of 4 keV.
Video 2 Cortical Tissue
A movie sequence through a stack of block-face images from cortical tissue (same dataset as in Figure 5). The beginning and the second half of the stack were taken at 4 keV electron energy, the middle part at 7.5 keV (see also Figure 5C). The dimensions of this volume are 11.64 μm laterally and 9 μm vertically (see also Figure S5).
Video 1 Neuromuscular Junction
A movie sequence through a stack of block-face images from muscle tissue (same dataset as in Figures 1A, 1B, 3A, and 3B).
Specimen preparation
Muscle tissue was prepared as described in Schwarz et al. (2000). For the preparation of rodent brain tissue the animals were perfused transcardially first with 30 ml of phosphate-buffered saline and then with 40 ml of fixative solution (4% paraformaldehyde in 0.1M PBS [pH 7.4]). The brain tissue was then removed and kept in fixative over night at 4 °C. After being washed twice in PBS, tissue slices (0.2 to 1.5 mm thick) were cut on a vibratome (752 M Vibroslice, Campden Instruments, Leichester, United Kingdom) and kept for 24 h in PBS at 4 °C. Pieces about 1.5 mm in size were then excised and washed three times for 30 min each in cacodylate buffer at pH 7.4.The tissue was postfixed for 2 h in 2% osmium tetroxide/1.5% potassium ferric cyanide in aqueous solution at room temperature. Then the tissue was subjected to a contrast enhancement step by soaking it over night in a solution of 4% uranyl acetate in a 25% methanol/75% water mixture (Stempak and Ward 1964) at room temperature. After that the tissue was dehydrated in a methanol sequence (25%, 70%, 90%, and 100% for 30 min each) followed by infiltration of the epoxy (Spurr, Epon 812, or Araldite, all from Serva, Heidelberg, Germany) monomer (epoxy/methanol 1:1, for 3 h rotation at room temperature; epoxy/methanol 3:1, overnight at 4°C; pure epoxy, 3 h rotating at room temperature). Polymerization was 48 h at 60 °C for Epon and at 70 °C for Spurr and Araldite. The block face was trimmed to a width of several hundred microns and a length of about 500 μm using either a conventional microtome or a sharp knife. SEM images of the untrimmed block face can be used to select the desired field of view before the final trimming step producing the desired small cutting pyramid.
Data analysis
Reslicing of image stacks (see Figures 2B–2D and 5C, as well as S2–S4) was done using the ImageJ reslicing command, which interpolates the z-axis data so that the digital resolution matches that of the lateral direction. For calibration of the z-axis, see below. Image shifts (see Figure 4) were measured by cross-correlating subregions (256 × 256 or 512 × 512) of subsequent slices. The peak positions were determined by first normalizing the cross correlations, then raising the values to the 64th power, and finally calculating the barycenter. All calculations were performed using ImageJ (version 1.32g). The neurite reconstruction shown in Figure S5 was done using Amira 3.1 (Mercury Computer Systems, TGS Unit, Düsseldorf, Germany).
Microtome
The microtome was constructed using mostly custom-machined parts made from nonmagnetic stainless steel. The leave springs were made out of bronze. The specimen advance contained a lever mechanism that reduced the motion of the motorized micrometer (M227.10 with controller C862, Physik Instrumente, Karlsruhe, Germany) by a factor of 0.11. This scaled the position uncertainty of the motorized micrometer (50 nm) down to a value 5.5 nm. Retraction of the sample during reverse motion of the diamond knife was driven by a closed-loop piezo element (P841.10, with controller E-610.S0, Physik Instrumente). The cutting motion was driven by a large-displacement piezo element (PX-1500, Piezojena, Jena, Germany). Suspension of the microtome on steel balls sliding on sapphire plates allowed lateral positioning driven by piezo-actuated slip-stick motors (Picomotor 8321-V, New Focus, San Jose, California, United States). The microtome was controlled using a computer interface designed originally for electrophysiology applications (1401 power, CED, Cambridge, United Kingdom) using scripts written in the Spike2 programming environment (CED). Analog voltages that were generated by the computer interface drove the cutting and the retraction piezos. The specimen-advance motor was controlled via serial interface. During automated stack acquisition the QuantaFEG 200 microscope was controlled using a modified keyboard that allowed simulated key pressings via a serial interface. Both serial interface connections were driven by commands in Spike2 software scripts.
The diamond knife used was custom made by Diatome, derived from their ultra 35° type. The cutting edge was 1.5 mm long. Unlike in the standard knife, in which the diamond is soldered to a piece of hard metal—increasing the clearance height necessary above the cutting edge and thereby increasing the working distance—our diamond was directly clamped in a custom-made stainless-steel holder. The clearance angle was fixed at 6°. The section thickness values quoted were calculated using the nominal micrometer position change and the mechanical reduction ratio of the advance mechanism. For some of the data (Figures 5 and S2–S5; Datasets S1–S20) the knife was oscillated (about 300 nm pp at 12 kHz) along the line of the cutting edge using a modified, piezo-driven knife holder.
Supporting Information
Dataset S1 Cortical Tissue Slices 1–99
(248.1 MB ZIP).
Click here for additional data file.
Dataset S2 Cortical Tissue Slices 100–199
(252.6 MB ZIP).
Click here for additional data file.
Dataset S3 Cortical Tissue Slices 200–299
(252.7 MB ZIP).
Click here for additional data file.
Dataset S4 Cortical Tissue Slices 300–399
(252.6 MB ZIP).
Click here for additional data file.
Dataset S5 Cortical Tissue Slices 400–499
(251.9 MB ZIP).
Click here for additional data file.
Dataset S6 Cortical Tissue Slices 500–599
(252.2 MB ZIP).
Click here for additional data file.
Dataset S7 Cortical Tissue Slices 600–699
(253.7 MB ZIP).
Click here for additional data file.
Dataset S8 Cortical Tissue Slices 700–799
(255.9 MB ZIP).
Click here for additional data file.
Dataset S9 Cortical Tissue Slices 800–899
(256.1 MB ZIP).
Click here for additional data file.
Dataset S10 Cortical Tissue Slices 900–999
(253.8 MB ZIP).
Click here for additional data file.
Dataset S11 Cortical Tissue Slices 1,000–1,099
(252.6 MB ZIP).
Click here for additional data file.
Dataset S12 Cortical Tissue Slices 1,100–1,199
(252.6 MB ZIP).
Click here for additional data file.
Dataset S13 Cortical Tissue Slices 1,200–1,299
(251.9 MB ZIP).
Click here for additional data file.
Dataset S14 Cortical Tissue Slices 1,300–1,399
(251.8 MB ZIP).
Click here for additional data file.
Dataset S15 Cortical Tissue Slices 1,400–1,499
(250.7 MB ZIP).
Click here for additional data file.
Dataset S16 Cortical Tissue Slices 1,500–1,599
(251.4 MB ZIP).
Click here for additional data file.
Dataset S17 Cortical Tissue Slices 1,600–1,699
(252.7 MB ZIP).
Click here for additional data file.
Dataset S18 Cortical Tissue Slices 1,700–1,799
(250.5 MB ZIP).
Click here for additional data file.
Dataset S19 Cortical Tissue Slices 1,800–1,899
(253.4 MB ZIP).
Click here for additional data file.
Dataset S20 Cortical Tissue Slices 1,900–2,000
(254.9 MB ZIP).
Click here for additional data file.
Figure S1 Muscle Tissue
Complete field of view for dataset underlying Figure 1A and 1B. Grayscale is inverted from data taken; no smoothing or contrast enhancement was applied.
(10.8 MB TIF).
Click here for additional data file.
Figure S2 Large Volume of Cortical Tissue
Bottom slice of a stack of 2,000 images taken at 4 keV. Slice thickness was 55 nm. Spotsize was 3.4. Pixel size is 26.7 nm. The pixels correspond to the original data. The area shown corresponds to 54.8 × 47.3 μm. The raw data can be found as numbered TIF images in Datasets S1–S20.
(10.6 MB TIF).
Click here for additional data file.
Figure S3 Large Volume of Cortical Tissue: X-Resliced Stack
Same volume data as used for Figure S2. The stack was resliced along the horizontal dotted line shown in Figure S2. In the vertical direction the data were interpolated so that each slice now corresponds to slightly more that two pixels. Horizontal white lines are slices with deposited debris. The total stack height was 110 μm.
(8.2 MB TIF).
Click here for additional data file.
Figure S4 Large Volume of Cortical Tissue: Y-Resliced Stack
Same as Figure S3 but now resliced along the vertical dotted line in Figure S2.
(7.1 MB TIF).
Click here for additional data file.
Figure S5 Neurite Reconstruction
Manual reconstruction of selected processes in cortical tissue (data from Video 2 and Figure 5). Blue, portion of proximal apical dendrite; green, secondary dendrite with three synaptically connected axons (yellow, ocher, and mauve). Insets show the synaptic contacts. Also shown is a passing axon that is not synaptically connected within the volume analyzed. Only the lower part of the stack, which was taken at 4 keV electron energy, was used.
(17.5 MB TIF).
Click here for additional data file.
We thank David Tank and Bert Sakmann for important inspiration; Jürgen Tritthart for the development of electronic hardware and software; Manfred Hauswirth, Harald Klemke, Heribert Lill, and Michael Sandmeier for precision machining; Veit Witzemann and Ulrike Mersdorf for providing the muscle sample; JoAnn Buchanan, John Heuser, Tom Reese, Rasmus Schröder, and Stephen Smith for stimulating discussions; Axel Borst, Peter Detwiler, Thomas Euler, and Rainer Friedrich for valuable suggestions on the manuscript; and the application laboratories of LEO, Oberkochen, and FEI, Eindhoven, for access to their microscopes for exploratory experiments.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. WD conceived and designed the experiments. WD and HH performed the experiments. WD analyzed the data. WD and HH contributed reagents/materials/analysis tools. WD wrote the paper.
Academic Editor: Kristen M. Harris, Medical College of Georgia
Citation: Denk W, Horstmann H (2004) Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLoS Biol 2(11): e329.
Abbreviations
3Dthree-dimensional
BSEbackscattered electron
EMelectron microscope
SBFSEMserial block-face scanning electron microscope
SEMscanning electron microscopy
TEMtransmission electron microscope
==== Refs
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Biomed Digit LibrBiomedical Digital Libraries1742-5581BioMed Central London 1742-5581-1-11550715910.1186/1742-5581-1-1EditorialTrue good Greenberg Charles J 1charles.greenberg@yale.edu1 Harvey Cushing/John Hay Whitney Medical Library, Yale University, 333 Cedar Street, PO Box 208014, New Haven, CT, 06850-8014, USA2004 20 9 2004 1 1 1 24 6 2004 20 9 2004 Copyright © 2004 Greenberg; licensee BioMed Central Ltd.2004Greenberg; 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.
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"The open society, the unrestricted access to knowledge, the unplanned and uninhibited association of men for its furtherance – these are what may make a vast, complex, ever growing, ever changing, ever more specialized and expert technological world, nevertheless a world of human community [1]." –J. Robert Oppenheimer (1904–1967)
Biomedical scientific communities increasingly articulate concern about the unsustainable status quo of traditional publishing paradigms [2], feeding an ongoing debate and consideration of alternative publishing models [3]. Seizing an opportune moment to contribute to the ongoing assessment and refinement of scholarly publishing in biomedical education, research, and patient care, an energetic group of librarians and faculty researchers endeavour to launch Biomedical Digital Libraries.
While traditional biomedical library concern revolves around the role of collection stewardship and delivering published knowledge to students, scholars, researchers, and clinicians, information professionals in library or information center settings are also concerned with the cultivation of their own knowledge domains and evidence-based library practice [4,5]. Perhaps more than any other knowledge profession, librarians understand that their own opportunities for collaboration and barrier-free exchange of ideas and research results has dramatically altered and ultimately improved the provision of services and resource management in their professional environment.
Open access scientific literature arrived in several pre-print guises over the previous two decades and in a recent contemporary commercial model with BioMed Central [6] (BMC). Separating itself from the pre-print unfiltered era, BMC provides biomedical researchers with peer review, retention of copyright, permanent redundant digital archiving in repositories such as PubMed Central (PMC) [7], and rapid global distribution of their ideas. Harnessing the innovations of the web, BMC also provides online submission, article history, and support for multiple languages. To sustain and expand an open access business model and maintain timely equitable global access, BMC publishing income derives from a combination of author fees, institutional memberships, and advertising.
BMC now has 425 institutional members in 40 countries [8]. Researchers from member institutions have the right to publish an unlimited number of research articles in journals published by BMC without paying any article processing charges. Because of the BMC institutional membership, biomedical librarians and information professionals have unexpectedly been thrust into a position of advocacy for an alternative publishing model. More often than not, librarians are more aware than their faculty or researchers that open access does not mean the absence of peer review. In a web-based information age of unfiltered content and one-stop search engine shopping, both biomedical scientists and information professionals are justifiably concerned that the open access movement without peer review simply adds to the morass of unfiltered, unproven hyperbole. Attention to peer review provides credibility, and BMC even offers their journals the opportunity to publish review reports and preliminary drafts for each article as "publication history."
The decision to found a BMC journal for the world of organized biomedical information was both spontaneous and practical. At the core of the founding of Biomedical Digital Libraries is the conviction that open access will push biomedical librarianship forward in new and improved ways. Biomedical Digital Libraries provides a legitimate alternative to traditional specialty journals in the field, which have subscription fees and assumption of copyright by the publisher. This journal will stress peer-reviewed open access to research and practice in digital collection and services settings and will permit rapid and unimpeded dissemination of knowledge, only weeks after manuscript submission. Over 30 information professionals and biomedical scholars will be engaged as editorial staff to conduct blinded peer review reports for original research, as well as integrate commentaries, resource reviews, and debates into a forum for the discussion of unique considerations of biomedical information needs. These include both opportunities and constraints presented by health care settings, including collaborative initiatives with information technology and informatics partners.
We hope the advocates, philosophers, caretakers, and architects of biomedical library digital content take immediate advantage of rapid peer-review and publication, extensive BMC content promotion, permanent URL, redundant public archiving, and retention of copyright when they submit to Biomedical Digital Libraries. Beyond our immediate narrow spheres of digital library practice and service, the community of open knowledge has the immediate and timely potential to inspire, inform, and create value on a global scale through permanent, uninhibited access.
Some seek good in authority, others in scientific research, others in pleasure. Others, who are in fact nearer the truth, have considered it necessary that the universal good, which all men desire, should not consist in any of the particular things which can only be possessed by one man, and which, when shared, afflict their possessor more by the want of the part he has not, than they please him by the possession of what he has. They have learned that the true good should be such as all can possess at once, without diminution and without envy, and which no one can lose against his will [9].
– Blaise Pascal(1623–1662)
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Oppenheimer J. Robert Science and the common understanding 1954 New York,, Simon and Schuster 120
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McLellan Faith Publishers face backlash over rising subscription costs: High prices have led some US institutions to cancel subscriptions to, or even boycott, scientific journals The Lancet 2004 363 44 45 14727612 10.1016/S0140-6736(03)15248-8
Bexon N Brice A Booth A Eldredge JD Using research in practice; Evidence-based librarianship: what might we expect in the years ahead? Health Info Libr J 2003 20 240 243 14641498 10.1111/j.1471-1842.2003.00463.x
Eldredge JD Evidence-based librarianship: what might we expect in the years ahead? Health Info Libr J 2002 19 71 77 12389603 10.1046/j.1471-1842.2002.00369.x
Ltd BioMed Central BioMed Central Open Access Charter
PubMed Central
Ltd BioMed Central BioMed Central Institutional Members
Pascal Blaise Eliot Charles W Thoughts The Harvard Classics translated by W. F. Trotter. Vol. XLVIII, Part 1. The Harvard Classics. New York: P.F. Collier & Son, 1909–14; Bartleby.com, 2001.
| 15507159 | PMC524353 | CC BY | 2021-01-04 16:38:25 | no | Biomed Digit Libr. 2004 Sep 20; 1:1 | utf-8 | Biomed Digit Libr | 2,004 | 10.1186/1742-5581-1-1 | oa_comm |
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Virol JVirology Journal1743-422XBioMed Central London 1743-422X-1-61550716010.1186/1743-422X-1-6ResearchComparisons of the M1 genome segments and encoded μ2 proteins of different reovirus isolates Yin Peng 12pyin2002@hotmail.comKeirstead Natalie D 13nkeirste@uoguelph.caBroering Teresa J 45teresa.broering@umassmed.eduArnold Michelle M 46michelle_arnold@student.hms.harvard.eduParker John SL 47jsp7@cornell.eduNibert Max L 46max_nibert@hms.harvard.eduCoombs Kevin M 1kcoombs@ms.umanitoba.ca1 Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, MB, R3E 0W3 Canada2 Thrasos Therapeutics, Hopkinton, MA 01748 USA3 Department of Pathobiology, Ontario Veterinary College, Guelph, ON, N1G 2W1 Canada4 Department of Microbiology and Molecular Genetics, Harvard Medical School, Boston, MA, 02115 USA5 Massachusetts Biologic Laboratories, Jamaica Plain, MA 02130-3597 USA6 Virology Training Program, Division of Medical Sciences, Harvard University, Cambridge, MA 02138 USA7 James A. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853 USA2004 23 9 2004 1 6 6 29 7 2004 23 9 2004 Copyright © 2004 Yin et al; licensee BioMed Central Ltd.2004Yin 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 reovirus M1 genome segment encodes the μ2 protein, a structurally minor component of the viral core, which has been identified as a transcriptase cofactor, nucleoside and RNA triphosphatase, and microtubule-binding protein. The μ2 protein is the most poorly understood of the reovirus structural proteins. Genome segment sequences have been reported for 9 of the 10 genome segments for the 3 prototypic reoviruses type 1 Lang (T1L), type 2 Jones (T2J), and type 3 Dearing (T3D), but the M1 genome segment sequences for only T1L and T3D have been previously reported. For this study, we determined the M1 nucleotide and deduced μ2 amino acid sequences for T2J, nine other reovirus field isolates, and various T3D plaque-isolated clones from different laboratories.
Results
Determination of the T2J M1 sequence completes the analysis of all ten genome segments of that prototype. The T2J M1 sequence contained a 1 base pair deletion in the 3' non-translated region, compared to the T1L and T3D M1 sequences. The T2J M1 gene showed ~80% nucleotide homology, and the encoded μ2 protein showed ~71% amino acid identity, with the T1L and T3D M1 and μ2 sequences, respectively, making the T2J M1 gene and μ2 proteins amongst the most divergent of all reovirus genes and proteins. Comparisons of these newly determined M1 and μ2 sequences with newly determined M1 and μ2 sequences from nine additional field isolates and a variety of laboratory T3D clones identified conserved features and/or regions that provide clues about μ2 structure and function.
Conclusions
The findings suggest a model for the domain organization of μ2 and provide further evidence for a role of μ2 in viral RNA synthesis. The new sequences were also used to explore the basis for M1/μ2-determined differences in the morphology of viral factories in infected cells. The findings confirm the key role of Ser/Pro208 as a prevalent determinant of differences in factory morphology among reovirus isolates and trace the divergence of this residue and its associated phenotype among the different laboratory-specific clones of type 3 Dearing.
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Background
RNA viruses represent the most significant and diverse group of infectious agents for eukaryotic organisms on earth [1,2]. Virtually every RNA virus, except retroviruses, must use an RNA-dependent RNA polymerase (RdRp) to copy its RNA genome into progeny RNA, an essential step in viral replication and assembly. The virally encoded RdRp is not found in uninfected eukaryotic cells and therefore represents an attractive target for chemotherapeutic strategies to combat RNA viruses. A better understanding of the structure/function relationships of RNA-virus RdRps has been gained from recent determinations of X-ray crystal structures for several of these proteins, including the RdRps of poliovirus, hepatitis C virus, rabbit calicivirus, and mammalian orthoreovirus [3-6]. However, the diverse and complex functions and regulation of these enzymes, including their interactions with other viral proteins and cis-acting signals in the viral RNAs, determine that we have hardly scratched the surface for understanding most of them.
The nonfusogenic mammalian orthoreoviruses (reoviruses) are prototype members of the family Reoviridae, which includes segmented double-stranded RNA (dsRNA) viruses of both medical (rotavirus) and economic (orbivirus) importance (reviewed in [7-9]). Reoviruses have nonenveloped, double-shelled particles composed of eight different structural proteins encasing the ten dsRNA genome segments. Reovirus isolates (or "strains") can be grouped into three serotypes, represented by three commonly studied prototype isolates: type 1 Lang (T1L), type 2 Jones (T2J), and type 3 Dearing (T3D). Sequences have been reported for all ten genome segments of T1L and T3D, as well as for nine of the ten segments of T2J (all but the M1 segment) (e.g., see [10,11]). Each of these segments encodes either one or two proteins on one of its strands, the plus strand. After cell entry, transcriptase complexes within the infecting reovirus particles synthesize and release full-length, capped plus-strand copies of each genome segment. These plus-strand RNAs are used as templates for translation by the host machinery as well as for minus-strand synthesis by the viral replicase complexes. The latter process produces the new dsRNA genome segments for packaging into progeny particles. The particle locations and functions of most of the reovirus proteins have been determined by a combination of genetic, biochemical, and biophysical techniques over the past 50 years (reviewed in [8]).
Previous studies have identified the reovirus λ3 protein, encoded by the L1 genome segment, as the viral RdRp [6,12-14]. Protein λ3 is a minor component of the inner capsid, present in only 10–12 copies per particle [15]. It has been proposed to bind to the interior side of the inner capsid, near the icosahedral fivefold axes, and recent work has precisely localized it there [16,17]. In solution, purified λ3 mediates a poly(C)-dependent poly(G)-polymerase activity, but it has not been shown to use virus-specific dsRNA or plus-strand RNA as template for plus- or minus-strand RNA synthesis, respectively [14]. This lack of activity with virus-specific templates suggests that viral or cellular cofactors may be required to make λ3 fully functional. Within the viral particle, where only viral proteins are known to reside, these cofactors are presumably viral in origin. The crystal structure of λ3 has provided substantial new information about the organization of its sequences and has suggested several new hypotheses about its functions in viral RNA synthesis and the possible roles of cofactors in these functions [6]. Notably, crystallized λ3 uses short viral and nonviral oligonucleotides as templates for RNA synthesis to yield short dsRNA products [6].
The reovirus μ2 protein has been proposed as a transcriptase cofactor, but it remains the most functionally and structurally enigmatic of the eight proteins found in virions. Like λ3, μ2 is a minor component of the inner capsid, present in only 20–24 copies per particle [15]. It is thought to associate with λ3 in the particle interior, in close juxtaposition to the icosahedral fivefold axes, but has not been precisely localized there [16,17]. A recent study has shown that purified μ2 and λ3 can interact in vitro [18]. The M1 genome segment that encodes μ2 is genetically associated with viral strain differences in the in vitro transcriptase and nucleoside triphosphatase (NTPase) activities of viral particles [19,20]. Recent work with purified μ2 has shown that it can indeed function in vitro as both an NTPase and an RNA 5'-triphosphatase [18]. The μ2 protein has also been shown to bind RNA and to be involved in formation of viral inclusions, also called "factories", through microtubule binding in infected cells [18,21-23]. Nevertheless, its precise function(s) in the reovirus replication cycle remain unclear. Other studies have indicated that the μ2-encoding M1 segment genetically determines the severity of cytopathic effect in mouse L929 cells, the frequency of myocarditis in infected mice, the levels of viral growth in cardiac myocytes and endothelial cells, the degree of organ-specific virulence in severe combined immunodeficiency mice, and the level of interferon induction in cardiac myocytes [24-29]. The complete sequence of the M1 segment has been reported for both T1L and T3D [23,30,31]. However, computer-based comparisons of the M1 and μ2 sequences to others in GenBank have previously failed to show significant homology to other proteins, so that no clear indications of μ2 function have come from that approach. Nevertheless, small regions of sequence similarity to NTP-binding motifs have been identified near the middle of μ2, and recent work has indicated that mutations in one of these regions indeed abrogates the triphosphatase activities of μ2 [18,20].
For this study, we performed nucleotide-sequence determinations of the M1 genome segments of reovirus T2J, nine other reovirus field isolates, and reovirus T3D clones obtained from several different laboratories. The determination of the T2J M1 sequence completes the sequence determination of all ten genome segments of that prototype strain. We reasoned that comparisons of additional M1 and μ2 sequences may reveal conserved features and/or regions that provide clues about μ2 structure and function. The findings provide further evidence for a role of μ2 in viral RNA synthesis. We also took advantage of the newly available sequences to explore the basis for M1/μ2-determined strain differences in the morphology of viral factories in reovirus-infected cells.
Results and Discussion
M1 nucleotide and μ2 amino acid sequences of reovirus T2J and nine other field isolates
We determined the nucleotide sequence of the M1 genome segment of reovirus T2J to complete the sequencing of that isolate's genome. T2J M1 was found to be 2303 base pairs in length (GenBank accession no. AF124519) (Table 1). This is one shorter than the M1 segments of reoviruses T1L and T3D [23,30,31], due to a single base-pair deletion in T2J corresponding to position 2272 in the 3' nontranslated region of the T1L and T3D plus strands (Fig. 1, Table 1). Like those of T1L and T3D, the T2J-M1 plus strand contains a single long open reading frame, encoding a μ2 protein of 736 amino acids (Fig. 2, Table 1), having the same start and stop codons (Fig. 1), and having a 5' nontranslated region that is only 13 nucleotides in length (Table 1). Because of the single-base deletion described above, the 3' nontranslated region of the T2J M1 plus strand is only 82 nucleotides in length, compared to 83 for T1L and T3D (Table 1). Regardless, M1 has the longest 3' nontranslated region of any of the genome segments of these viruses, the next longest being 73 nucleotides in S3 (reviewed in [32]).
Table 1 Features of M1 genome segments and μ2 proteins from different reovirus isolates
Reovirus isolatea
M2 or μ2 propertyb T1Lc T2J T3Dd T3De T1C11 T1C29 T1N84 T2N84 T2S59 T3C12 T3C18 T3C44 T3N83
Accession no.: X59945 AF124519 M27261 AF461683 AY428870 AY428871 AY428872 AY428873 AY428874 AY551083 AY428875 AY428876 AY428877
total nuc 2304 2303 2304 2304 2304 2304 2304 2304 2304 2304 2304 2304 2304
5' NTR 13 13 13 13 13 13 13 13 13 13 13 13 13
3' NTR 83 82 83 83 83 83 83 83 83 83 83 83 83
total AA 736 736 736 736 736 736 736 736 736 736 736 736 736
mass (kDa) 83.3 84.0 83.3 83.2 83.2 83.3 83.4 83.3 83.5 83.2 83.3 83.3 83.4
pI 6.92 7.44 6.98 6.89 7.10 7.09 6.98 6.92 6.96 6.89 6.92 7.09 7.01
Asp+Glu 85 84 85 85 84 84 85 85 84 85 85 84 85
Arg+Lys+His 102 105 102 101 103 103 102 102 100 101 102 103 103
a Abbreviations defined in text.
b nuc, nucleotides; NTR, nontranslated region; AA, amino acids; pI, isoelectric point.
c All indicated values are the same for the T1L M1 and μ2 sequences obtained for the Brown laboratory clone [31] (indicated GenBank accession number), the Nibert laboratory clone [23]; GenBank accession no. AF461682), and the Coombs laboratory clone (this study).
d T3D M1 and μ2 sequences for the Joklik laboratory clone [30] (indicated GenBank accession number), and the Cashdollar laboratory clone [23]; GenBank accession no. AF461684).
e T3D M1 and μ2 sequences for the Nibert laboratory clone [23] and the Coombs laboratory clone (this study).
Figure 1 Sequences near the 5' (A) and 3' (B) ends of the M1 plus strands of 14 reovirus isolates. The start and stop codons are indicated by bold and underline, respectively. The one-base deletion in the 3' noncoding region of the T2J sequence is indicated by a triangle. Positions at which at least one sequence differs from the others are indicated by dots. GenBank accession numbers for corresponding sequences are indicated between the clones' names and 5' sequences in "A". Clones are: T1L (type 1, Lang), T1C11 (type 1, clone 11), T1C29 (type 1, clone 29), T1N84 (type 1, Netherlands 1984), T2J (type 2, Jones), T2N84 (type 2, Netherlands 1984), T2S59 (type 2, simian virus 59), T3D (type 3, Dearing), T3C12 (type 3, clone 12), T3C18 (type 3, clone 18), T3C44 (type 3, clone 44), and T3N83 (type 3, Netherlands 1983). T1L clones were obtained from Dr. E.G. Brown (Brown) or our laboratories (Coombs/Nibert). T3D clones were obtained from Drs. W.K. Joklik, L.W. Cashdollar (Joklik/Cashdollar) and our laboratories (Coombs/Nibert).
Figure 2 Alignment of the deduced μ2 amino acid sequences of T1L, T2J, T3D, and various field isolates. The single-letter amino acid code is used, and only the T1L μ2 sequence from the Brown laboratory is shown in its entirety. For other isolates, only those amino acids that differ from this T1L sequence are shown. Clones arranged in same order as in Fig. 1; the second T1L μ2 sequence is from the Nibert and Coombs laboratories, the first T3D μ2 sequence is from the Joklik and Cashdollar laboratories, and the second T3D μ2 sequence is from the Nibert and Coombs laboratories. Amino acid positions are numbered above the sequences. Some symbols represent various nonconservative changes among the isolates: *, change involving a charged residue; § change involving an aromatic residue; †, change involving a proline residue; ‡, change involving a cysteine residue. Residue 208, which has been previously shown to affect microtubule association by μ2, is indicated by a filled diamond. Residues 410–420 and 446–449, which have been previously identified as NTP-binding motifs are indicated by filled circles. Consecutive runs of wholly conserved residues ≥ 15 amino acids in length are indicated by the lines numbered 1 to 8.
To gain further insights into μ2 structure/function relationships, we determined the M1 nucleotide sequences of nine other reovirus field isolates [33,34]. The M1 segments of each of these viruses were found to be 2304 base pairs in length (GenBank accession nos. AY428870 to AY428877 and AY551083), the same as T1L and T3D M1 (Fig. 1). Like those of T1L, T2J, and T3D, the M1 plus strand from each of the field isolates contains a single long open reading frame, again encoding a μ2 protein of 736 amino acids (Fig. 2) and having the same start and stop codons (Fig. 1). Their 5' and 3' nontranslated regions are therefore the same lengths as those of T1L and T3D M1 (Table 1). As part of this study, we also determined the M1 nucleotide sequences of the reovirus T1L and T3D clones routinely used in the Coombs laboratory. We found these sequences to be identical to those recently reported for the respective Nibert laboratory clones [23].
Further comparisons of the M1 nucleotide sequences
The T2J M1 genome segment shares 71–72% homology with those of both T1L and T3D (Table 2). This makes T2J M1 the most divergent of all nonfusogenic mammalian orthoreovirus genome segments examined to date, with the exception of the S1 segment, which encodes the attachment protein σ1 and which shows less than 60% nucleotide sequence homology between serotypes [35,36]; reviewed in [11]. In contrast, the homology between T1L and T3D M1 is ~98%, among the highest values seen to date between reovirus genome segments from distinct field isolates [11,31,34,37-39].
Table 2 Pairwise comparisons of M1 genome segment and μ2 protein sequences from different reovirus isolates
Identity (%) compared with reovirus isolatea
Virus isolate T1Lb T1Lc T2J T3Dd T3De T1C11 T1C29 T1N84 T2N84 T2S59 T3C12 T3C18 T3C44 T3N83
T1Lb -- 99.9f 80.8 98.6 98.8 99.2 98.0 98.4 98.8 96.3 98.8 99.0 98.0 98.2
T1Lc 99.9f -- 81.0 98.8 98.9 99.3 98.1 98.5 98.9 96.2 98.9 99.2 98.1 98.4
T2J 71.6 71.6 -- 80.0 80.2 80.4 80.3 80.2 80.4 81.5 80.2 80.3 80.3 80.4
T3Dd 97.8 97.9 70.9 -- 99.6 98.6 97.4 97.8 98.2 95.5 99.6 98.5 97.4 98.0
T3De 97.9 98.0 71.0 99.7 -- 98.8 97.6 98.0 98.4 95.7 100 98.6 97.6 98.1
T1C11 98.7 98.7 71.3 97.1 97.1 -- 98.0 98.4 98.8 96.1 98.8 99.6 98.0 98.8
T1C29 96.3 96.4 71.1 95.8 95.8 95.5 -- 97.3 97.8 95.7 97.6 97.8 100 97.0
T1N84 96.3 96.3 70.8 95.7 95.8 95.9 94.5 -- 98.5 95.7 98.0 98.2 97.3 97.4
T2N84 97.1 97.1 71.0 96.5 96.6 96.7 95.4 96.5 -- 96.2 98.4 98.6 97.8 97.8
T2S59 89.8 89.9 71.3 89.2 89.3 89.2 89.4 89.1 89.7 -- 95.7 95.9 95.7 95.1
T3C12 97.8 97.9 71.0 99.7 99.9+ 97.2 95.7 95.7 96.6 89.3 -- 98.6 97.6 98.1
T3C18 98.8 98.9 71.2 97.3 97.4 99.4 95.8 95.8 96.8 89.4 97.4 -- 97.8 98.6
T3C44 96.5 96.6 71.1 95.9 95.9 95.7 99.7 94.6 95.5 89.4 95.9 96.0 -- 97.0
T3N83 97.7 97.8 71.4 96.4 96.4 98.6 94.7 94.9 95.8 88.5 96.4 98.4 95.0 --
a Abbreviations defined in text.
b T1L M1 and μ2 sequences for the Brown laboratory clone [31]; GenBank accession no. X59945).
c T1L M1 and μ2 sequences for the Nibert laboratory clone [23]; GenBank accession no. AF461682) and the Coombs laboratory clone (this study).
d T3D M1 and μ2 sequences for the Joklik laboratory clone [30]; GenBank accession no. M27261), and the Cashdollar laboratory clone [23]; GenBank accession no. AF461684).
e T3D M1 and μ2 sequences for the Nibert laboratory clone [23]; GenBank accession no. AF461683) and the Coombs laboratory clone (this study).
f Values for M1-gene sequence comparisons are shown below the diagonal, in bold; values for μ2-protein sequence comparisons are shown above the diagonal.
The M1 genome segments of the nine other reovirus isolates examined in this study are much more closely related to those of T1L and T3D than to that of T2J (Table 2), as also clearly indicated by phylogenetic analyses (Fig. 3 and data not shown). Such greater divergence of the gene sequences of T2J has been observed to date with other segments examined from multiple reovirus field isolates [11,34,37-39]. Type 2 simian virus 59 (T2S59) has the next most broadly divergent M1 sequence, but it is no more similar to the M1 sequence of T2J than it is to that of the other isolates (Table 2, Fig. 3). In sum, the results of this study provided little or no evidence for divergence of the M1 sequences along the lines of reovirus serotype (Fig. 3), consistent with independent reassortment and evolution of the M1 and S1 segments in nature. Upon considering the sources of these isolates [34], the results similarly provided little or no evidence for divergence of the M1 sequences along the lines of host, geographic locale, or date of isolation (Fig. 3). These findings are consistent with ongoing exchange of M1 segments among reovirus strains cocirculating in different hosts and locales. Similar conclusions have been indicated by previous studies of other genome segments from multiple reovirus field isolates [11,34,37-39]. The M1 nucleotide sequence of type 3 clone 12 (T3C12) is almost identical to that of the T3D clone in use in the Coombs and Nibert laboratories, with only a single silent change (U→C) at plus-strand position 1532 (i.e., 99.9+% homology). However, several of the T3C12 genome segments show distinguishable mobilities in polyacrylamide gels (data not shown), confirming that T3C12 is indeed a distinct isolate.
Figure 3 Most parsimonious phylogenetic tree based on the M1 nucleotide sequences of the different reoviruses. Sequences for T1L and T3D clones from different laboratories are shown (laboratory source(s) in parentheses). Horizontal lines are proportional in length to nucleotide substitutions.
Further comparisons of the μ2 protein sequences
The T2J μ2 protein shares 80–81% homology with those of both T1L and T3D (Table 2, Fig. 2). Consistent with the M1 nucleotide sequence results, this makes T2J μ2 the most divergent of all nonfusogenic mammalian orthoreovirus proteins examined to date, with the exception of the S1-encoded σ1 and σ1s proteins, which show less than 55% amino acid sequence homology between serotypes [35,36]; reviewed in [11]. In contrast, the homology between T1L and T3D μ2 approaches 99%, among the highest values seen to date between reovirus genome segments from distinct isolates [11,31,34,37-39]. Also consistent with the M1 nucleotide sequence results, the μ2 proteins of the nine other reovirus isolates examined in this study are much more closely related to those of T1L and T3D than to that of T2J (Table 2, Fig. 3), affirming the divergent status of the T2J μ2 protein. The μ2 protein sequence of T3C12 is identical to that of the T3D clone in use in the Coombs and Nibert laboratories. In addition, the μ2 protein sequence of T1C29 is identical to that of T3C44. These are the first times that reovirus proteins from distinct isolates have been found to share identical amino acid sequences [11,32,34,37-39], reflecting the high degree of μ2 conservation.
The encoded μ2 proteins of the twelve reovirus isolates are all calculated to have molecular masses between 83.2 and 84.0 kDa, and isoelectric points between 6.89 and 7.44 pH units (Table 1). This range of isoelectric points is the largest yet seen among reovirus proteins other than σ1s [11], but is largely attributable to the divergent value of T2J μ2 (others range only from 6.89 to 7.10). The substantially higher isoelectric point of T2J μ2 is explained by it containing a larger number of basic residues (excess arginine) than do the other isolates (Table 1).
Comparisons of the twelve μ2 sequences showed eight highly conserved regions, each containing ≥ 15 consecutive residues that are identical in all of the isolates (Fig. 2). The highly conserved regions are clustered in two larger areas of μ2, spanning approximately amino acids 1–250 and amino acids 400–610. Conserved region 5 in the 400–610 area encompasses the more amino-terminal of the two NTP-binding motifs in μ2 (Fig. 2) [18,20]. The other NTP-binding motif is also wholly conserved, but within a smaller consecutive run of conserved residues. The region between the two motifs is notably variable (Fig. 2). Conserved region 5 also contains the less conservative of the two amino acid substitutions in T1L-derived temperature-sensitive (ts) mutant tsH11.2 (Pro414→His) [40]. The pattern of conserved and variable areas of μ2 was also seen by plotting scores for sequence identity in running windows over the protein length (e.g., [32]). In addition to the conserved regions described above, areas of greater than average variation are evident in this plot, spanning approximately amino acids 250–400 and 610–736 (the carboxyl terminus) (Fig. 4). The 250–400 area is notable for regularly oscillating between conserved and variable regions (Fig. 4). The two large areas of greater-than-average sequence conservation, spanning approximately amino acids 1–250 and 400–610 (Fig. 4), are likely to be involved in the protein's primary function(s). The more variable, 250–400 area between the two conserved ones might represent a hinge or linker of mostly structural importance.
Figure 4 Window-averaged scores for sequence identity among the T1L, T2J, and T3D μ2 proteins. Identity scores averaged over running windows of 21 amino acids and centered at consecutive amino acid positions are shown. The global identity score for the three sequences is indicated by the dashed line. Two extended areas of greater-than-average sequence variation are marked with lines below the plot. Two extended areas of greater-than-average sequence conservation are marked with lines above the plot. Eight regions of ≥ 15 consecutive residues of identity among all twelve μ2 sequences from Fig. 2, as discussed in the text, are numbered above the plot. The Ser/Pro208 determinant of microtubule binding is marked with a filled diamond. The two putative NTP-binding motifs are marked with filled circles.
As indicated earlier, μ2 is one of the most poorly understood reovirus proteins, from both a functional and a structural point of view. For example, atomic structures are available for seven of the eight reovirus structural proteins, with μ2 being the missing one. Thus, in an effort to refine the model for μ2 structure/function relationships based on regional differences, we obtained predictions for secondary structures, hydropathy, and surface probability. PHD PredictProtein algorithms suggest that μ2 can be divided into four approximate regions characterized by different patterns of predicted secondary structures (Fig. 5C). An amino-terminal region spans to residue 157, a "variable" region spans residues 157 to 450, a "helix-rich" region spans residues 450 to 606, and a carboxyl-terminal region spans the sequences after residue 606. The amino-terminal region contains six predicted α-helices and three predicted β-strands, and is highly conserved across all twelve μ2 sequences. The "variable" region is the most structurally complex and contains numerous interspersed α-helices and β-strands. The "helix-rich" region contains seven α-helices and is highly conserved across all twelve μ2 sequences. The carboxyl-terminal region varies across all three serotypes. Overall, the μ2 protein is predicted to be 48% α-helical and 14% β-sheet in composition, making it an "α-β " protein according to the CATH designation [41]. Interestingly, most tyrosine protein kinases with SH2 domains are also "α-β " proteins by this designation. The T1L and T3D μ2 hydropathy profiles were identical to each other. Both show numerous regions of similarity to the hydropathy profile of the T2J μ2. However, there also are several distinct differences between the T1L and T2J profiles (Fig. 5). Alterations in amino acid charge at residues 32, 430 to 432, and 673 in the T2J sequence account for the major differences in hydrophobicity between T2J and the other serotypes. In addition, the carboxyl-terminal 66 residues show multiple differences in hydropathy. The surface probability profiles of each of the three serotype's μ2 proteins are identical (Fig. 5) and show numerous regions that are highly predicted to be exposed at the surface of the protein as well as regions predicted to be buried.
Figure 5 Secondary structure predictions of μ2 protein. (A) Hydropathicity index predictions of T2J (- - -) and T1L (-----) μ2 proteins, superimposed to accentuate similarities and differences. Hydropathy values were determined by the Kyte-Doolittle method [72], using DNA Strider 1.2, a window length of 11, and a stringency of 7. (B) Surface probability predictions of the T2J μ2 protein, determined as per Emini et al. [73], using DNASTAR. The predicted surface probability profiles of T1L and T3D (not shown) were identical to T2J. (C) Locations of α-helices and β-sheets were determined by the PHD PredictProtein algorithms [74], and results were graphically rendered with Microsoft PowerPoint software., α-helix;., β-sheet;—, turn. Differences in fill pattern correspond to arbitrary division of protein into four regions; N, amino terminal; V, variable; H, helix-rich; C, carboxyl terminal. The locations of variable regions are indicated by the thick lines under the domain representation.
The MOTIF and FingerPRINTScan programs were used to compare the highly conserved regions of μ2 with other sequences in protein data banks (ProSite, Blocks, and ProDomain). The results revealed that several of the conserved regions in μ2 share limited similarities with members of the DNA polymerase A family and with the SH2 domain of tyrosine kinases. The sequence YEAgDV in μ2, located in conserved region 2 (Fig. 2), is similar to the "YAD" motif of DNA polymerase A from a number of different bacteria (e.g., YEADDV in Deinococcus radiodurans). The YAD motif is located in the exonuclease region of DNA polymerase A, a region which also functions as an NTPase and enhances the rate of DNA polymerization [42]. The SH2 domain of tyrosine kinases was the highest score hit for the conserved regions of μ2 with FingerPRINTScan. Four of the five motifs in the 100 amino acid SH2 domain matched the μ2 sequence. The SH2 domain mediates protein-protein interactions through its capacity to bind phosphotyrosine [43]. The protein motifs found by focusing on the conserved regions of μ2 provide supportive evidence that this protein is involved in nucleotide binding and metabolism. However, the described similarities did not match with greater than 90% certainty and no other significant homologies were detected. The inability to identify higher-scoring GenBank similarities, first noted when sequences of the T3D and T1L M1 genes were reported [30,31] attests to the uniqueness of this minor core protein.
Biochemical confirmations
In an effort to provide biochemical confirmation of the predicted variation in the different isolates' μ2 proteins, we analyzed the T1L, T2J, and T3D proteins by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and immunoblotting. Despite the slightly larger molecular mass calculated from its sequence (Table 1), T2J μ2 displayed a slightly smaller relative molecular weight on gels than T1L and T3D μ2 (Fig. 6A). This aberrant mobility may reflect the higher isoelectric point of T2J μ2 (Table 1). Polyclonal anti-μ2 antibodies that had been raised against purified T1L μ2 [44] reacted strongly with both T1L and T3D μ2, but only weakly with T2J μ2 (Fig. 6B), despite equal band loading as demonstrated by Ponceau S staining. These antibody cross-reactivities correlated well with the predicted protein homologies (Table 2).
Figure 6 SDS-PAGE and immunoblot analyses of virion and core particles. Proteins from gradient-purified T1L (1), T2J (2), and T3D (3) particles were resolved in 5–15% SDS-polyacrylamide gels as detailed in Materials and methods. Gels were then fixed and stained with Coomassie Brilliant Blue R-250 and silver (A). Alternatively, proteins from the gels were transferred to nitrocellulose, probed with anti-μ2 antiserum (polyclonal antibodies raised against T1L μ2, kindly provided by E. G. Brown), and detected by chemiluminescence (B). Virion proteins are indicated to the left of panel A, except for μ2, which is indicated between the panels.
Factory morphologies among reovirus field isolates
We took advantage of the new M1/μ2 sequences to extend analysis of the role of μ2 in determining differences in viral factory morphology among reovirus isolates [23]. Sequence variation at μ2 residue Pro/Ser208 was previously indicated to determine the different morphologies of T1L and T3D factories: Pro208 is associated with microtubule-anchored filamentous factories, as in T1L and the Cashdollar laboratory clone of T3D, whereas Ser208 is associated with globular factories, as in the Nibert laboratory clone of T3D [23]. For the previous study we had already examined the factories of T2J and some of the nine other isolates used for M1 sequencing above. We nonetheless newly examined the factories of all ten isolates in the present study, using the same stocks used for sequencing. T3C12 was the only one of these isolates that formed globular factories; the remainder, including T2J, formed filamentous factories (Fig. 7, Table 4). This finding is consistent with the fact that T3C12 is the only one of these isolates that has a serine at μ2 residue 208, like T3D from the Nibert laboratory; the remainder, like T1L and T3D from the Cashdollar laboratory, have a proline there (Fig. 2, Table 4) [23]. Thus, although the results identify no additional μ2 residues that may influence factory morphology, they are consistent with the identification of Pro/Ser208 as a prevalent determinant of differences in this phenotype among reovirus isolates.
Figure 7 Viral factory morphology as demonstrated by the distribution of μNS in cells infected with various reovirus isolates. CV-1 cells were infected at 5 PFU/cell with the isolate indicated above each panel, fixed at 18 h p.i., and immunostained with μNS-specific rabbit IgG conjugated to Alexa 594. Size bars, 10 μm.
Table 4 Properties of different reovirus isolates
Virus isolatea Virus factory morphologyb Amino acid at μ2 position 208
T1L filamentousc Proc
T2J filamentousd Pro
T3De filamentousc Proc
T3Df globularc Serc
T1C11 filamentous Pro
T1C29 filamentous Pro
T1N84 filamentousd Pro
T2N84 filamentousd Pro
T2S59 filamentousd Pro
T3C12 globulard Ser
T3C18 filamentousd Pro
T3C44 filamentous Pro
T3N83 filamentousd Pro
a Abbreviations defined in the text.
b Determined by immunofluorescence microscopy as described in the text.
c Reported in Parker et al. [23].
d Reported in supplementary data of Parker et al. [23].
e T3D clone from the Cashdollar laboratory.
f T3D clone from the Nibert laboratory.
Factory morphologies and M1/μ2 sequences of other T3D and T3D-derived clones
T3D clones from the Nibert and Cashdollar laboratories have been shown to exhibit different factory morphologies based on differences in the microtubule-binding capacities of their μ2 proteins and the presence of either serine or proline at μ2 residue 208 [23]. We took the opportunity in this study to examine additional T3D clones. The clones from some laboratories formed globular factories in infected cells whereas those from other laboratories or the American Type Culture Collection formed filamentous factories (Fig. 8, Table 5). T3D-derived ts mutants tsC447, tsE320, and tsG453 [45] formed filamentous factories (Fig. 8, Table 5). Other ts mutants were not examined; however, [46] have shown evidence that tsF556 [45] forms filamentous factories as well.
Figure 8 Viral factory morphology as demonstrated by the distribution of μNS in cells infected with T3D clones obtained from different laboratories or with T3D-derived ts clones. Laboratory sources are indicated in parentheses. CV-1 cells were infected at 5 PFU/cell with the clone indicated above each panel, fixed at 18 h p.i., and immunostained with μNS-specific rabbit IgG conjugated to Alexa 488. Size bars, 10 μm.
Table 5 Properties of different T3D and T3D-derived clones
Positions of variation in T3D μ2
Virus isolate Laboratory source Virus factory morphology
150 208 224 372
T3D Niberta globularb Gln Serb Glu Ile
T3D Coombsa globular Gln Ser Glu Ile
T3D Schiffa globular Gln Ser Glu Ile
T3D Tylera globular Gln Ser Glu Ile
T3D Cashdollarc filamentousb Arg Prob Glu Met
T3D Duncanc filamentous Arg Pro Glu Met
T3D Shatkin filamentous Gln Pro Ala Ile
T3D ATCC filamentous Gln Pro Glu Ile
tsC447 Coombsc filamentous Gln Pro Glu Ile
tsE320 Coombsc filamentous Gln Pro Glu Ile
tsG453 Coombsc filamentous Gln Pro Glu Ile
a Origin traceable to B. N. Fields laboratory.
b Reported in Parker et al. [23].
c Origin traceable to W. K. Joklik laboratory; derived from T3D; sequences of tsC447 (GenBank accession no. AY428878), tsE320, and tsG453 are identical.
We additionally determined the M1 sequences of the wild-type and ts T3D clones newly tested for factory morphology. All clones with globular factories have a serine at μ2 position 208 whereas all those with filamentous factories have a proline there (Table 5). These findings provide further evidence for the influence of residue 208 on this phenotypic difference.
All wild-type T3D clones with globular factories were recently derived from a Fields laboratory parent whereas all wild-type or ts T3D clones with filamentous factories were derived from parents in other laboratories. (Although extensively characterized by both Fields (e.g., [47,48]) and Joklik (e.g., [49,50]), the original T3D-derived ts mutants in groups A through G were generated in the Joklik laboratory [45]). This correlation suggests that formation of filamentous factories is the ancestral phenotype of reovirus T3D and that the Ser208 mutation in T3D μ2 was established later, in the Fields laboratory. As we noted in a previous study [23], several other laboratories reported evidence for filamentous T3D factories in the 1960's (e.g., [51,52]), following its isolation in 1955 [53]. Since microtubules were noted to be commonly associated with T3D factories in Fields laboratory publications from as late as 1973 [54], but not in one from 1979 [55], the μ2 Ser208 mutation was probably established in, or introduced into, that laboratory during the middle 1970's. Investigators should be alert to these different lineages of T3D and their derivatives for genetic studies. For example, reassortant 3HA1 [56] contains a T3D M1 genome segment derived from clone tsC447, and its factory phenotype is filamentous (data not shown).
Additional genome-wide comparisons of T1L, T2J, and T3D
Several types of genome-wide comparisons of T1L, T2J, and T3D have been reported previously [11]. For this study we examined the positions and types of nucleotide mismatches in these prototype isolates in order to gain a more comprehensive view of the evolutionary divergence of their protein-coding sequences. Most mismatches between T2J and either T1L or T3D segments, ~68%, are in the third codon base position, while ~21% are in the first position and ~11% are in the second position. Each of these mismatch percentages was converted to an evolutionary divergence value by multiplying mismatch percentage by 1.33 [31] (Table 3). These values have been used to argue that the homologous T1L and T3D genome segments diverged from common ancestors at different times in the past, with the M1 and L3 segments having diverged most recently and the M2, S1, S2, and S3 segments having diverged longer ago [31]. The consistently high values for divergence at third codon base positions among pairings with T2J genome segments (Table 3) indicate that all ten T2J segments diverged from common ancestors substantially before their respective T1L and T3D homologs. Relative numbers of synonymous and nonsynonymous nucleotide changes identified in pairwise comparisons of the coding sequences of these isolates (Table 3) support the same conclusion.
Table 3 Pairwise comparisons of variation at different codon positions in reovirus genome segments
Variation (%) in the long open reading frame of genome segment
Codon position Isolate pair L1 L2 L3 M1 M2 M3 S2 S3 S4
firsta T1L:T2J 16.9 19.9 12.2 24.6 11.1 25.3 13.7 25.5 13.1
T2J:T3D 16.7 20.4 12.7 26.1 10.7 25.0 14.0 25.5 13.9
T1L:T3D 2.4 15.4 1.4 1.5 6.0 7.6 6.1 6.6 4.0
seconda T1L:T2J 5.3 8.0 3.3 11.8 1.7 10.0 4.1 8.4 5.1
T2J:T3D 5.1 7.5 3.2 11.8 1.7 9.6 4.1 8.0 5.5
T1L:T3D 0.8 3.5 0.3 0.4 2.1 2.0 0.0 2.2 1.1
thirda T1L:T2J 77.1 83.7 79.4 80.1 81.5 81.2 74.0 79.1 73.8
T2J:T3D 76.7 77.4 79.1 81.0 82.7 83.0 73.0 73.9 76.7
T1L:T3D 12.9 76.1 7.5 6.5 53.3 39.2 53.6 48.1 21.9
syn.b T1L:T2J 88.3 90.2 89.6 85.8 90.0 87.1 83.8 90.2 81.9
T2J:T3D 87.5 84.2 89.3 87.0 89.3 89.8 83.6 85.4 84.2
T1L:T3D 15.0 85.9 8.8 7.9 59.3 46.4 63.1 58.2 25.8
nonsyn.b T1L:T2J 5.9 9.1 3.8 12.6 2.6 11.8 4.8 10.2 6.2
T2J:T3D 5.9 8.9 3.9 13.1 3.2 11.5 4.7 9.6 6.8
T1L:T3D 0.8 5.0 0.3 0.5 1.2 2.0 0.7 1.3 1.3
cons.c T1L:T2J 60.0 66.3 57.1 63.8 50.0 60.6 50.0 60.8 73.5
5.0 8.7 2.5 12.2 1.3 10.7 2.9 8.5 6.8
T2J:T3D 62.7 64.5 56.1 64.6 65.2 60.5 52.0 60.8 71.1
5.1 8.6 2.5 12.9 2.1 10.0 3.1 8.5 7.4
T1L:T3D 36.4 77.4 88.9 80.0 50.0 62.5 100 40.0 63.6
0.6 5.6 0.6 1.1 1.1 2.8 1.2 1.0 1.9
noncon.c T1L:T2J 18.1 10.7 17.9 17.0 11.1 18.9 20.8 17.6 14.7
1.5 1.4 0.8 3.3 0.3 3.3 1.2 2.5 1.4
T2J:T3D 18.6 9.9 19.3 16.3 13.0 16.8 20.0 15.7 21.1
1.5 1.3 0.9 3.3 0.4 2.8 1.2 2.2 2.2
T1L:T3D 18.2 8.6 11.1 0.0 12.5 3.1 0.0 20.0 27.3
0.3 0.6 0.1 0.0 0.3 0.1 0.0 0.5 0.8
S1 not included because of uncertainty in where to place gaps.
a Values determined for each pairwise comparison as: # base changes / total such positions × 100.
b Values determined as # of observed changes/ # of positions at which changes could have occurred × 100.
c Upper value indicates proportion of all amino acid substitutions that are conservative or nonconservative (using CLUSTAL W analysis with BLOSUM weighting); semi-conservative substitutions not included. Lower bold value indicates proportion of indicated types of alterations as a percentage of total number of amino acids within whole protein.
The types of amino acid substitutions within each of the prototype isolates' proteins were also examined. Pairwise analyses showed that most substitutions in most proteins were conservative (Table 3). Nonconservative substitutions were relatively rare in most proteins' pair-wise comparisons. For example, comparison of the T1L and T3D μ2 proteins showed none (0.0%) of the 10 amino acid substitutions were nonconservative, and most T1L:T3D comparisons gave low nonconservative substitution values ranging from 0.1–0.5% of total amino acid residues within the respective proteins. However, some genes, most notably M1, M3, and S3, demonstrated higher nonconservative variation, with values approaching 3.5% of total amino acid residues. Most of these higher nonconservative substitution values were observed when T2J proteins were compared to either T1L or T3D proteins. In addition, in many proteins, the majority of nonconservative substitutions were located within the amino-terminal portions (first ~20%) of the respective proteins (data not shown).
The frequencies with which different redundant codons are used to encode certain mammalian amino acids are non-random (reviewed in [57]). This phenomenon is mirrored by different abundances of the complementary tRNA molecules in mammalian cells. For example, CG pairs are underrepresented in mammalian genomes and common in their "rare" codons (see Table 6). A recent study revealed that many RNA viruses of humans display mild deviations from host codon-usage frequencies and that these deviations are more prominent among viruses with segmented genomes [57]. However, reoviruses were not included in that study. By examining reovirus isolates T1L, T2J, and T3D, for which whole-genome sequences are now available, we found that codons that qualify as rare in mammals are not rare in reovirus (Table 6). Moreover, the few codons that qualify as rare in reovirus (ACC, AGC, CCC, CGG, CUC, and GCC; data not shown) are common in mammals. The basis and significance of these deviations remain unknown, but could have impacts on the rates of translation of reovirus proteins. It is perhaps notable in this regard that the four most highly expressed reovirus proteins (μ1, σ3, μNS, and σNS) have the lowest average frequencies of codons that are rare in mammals (Table 6). Thus, incorporation of rare codons into reovirus coding sequences could be a mechanism of dampening the expression of certain viral proteins.
Table 6 Codon-usage frequencies in reovirus for eight codons that are rare in mammals
Frequencies of selected codons in coding sequences of:a
Mammalian genomes Reovirus genomes Individual reovirus genome segments (major protein encoded by each)
Codon AAb Expc Mus Bos Homo T1L T2J T3D L1 (λ3) L2 (λ2) L3 (λ1) M1 (μ2) M2 (μ1) M3 (μNS) S1 (σ1) S2 (σ2) S3 (σNS) S4 (σ3)
ACG Thr 0.25 0.11 0.13 0.11 0.23 0.30 0.24 0.17 0.28 0.22 0.27 0.17 0.16 0.30 0.38 0.26 0.20
CCG Pro 0.25 0.11 0.12 0.11 0.17 0.20 0.17 0.12 0.20 0.15 0.27 0.20 0.14 0.18 0.25 0.07 0.11
CGU Arg 0.17 0.09 0.08 0.08 0.20 0.22 0.24 0.22 0.19 0.14 0.25 0.19 0.31 0.12 0.16 0.21 0.29
CUA Leu 0.17 0.08 0.09 0.08 0.15 0.13 0.14 0.18 0.13 0.14 0.19 0.09 0.18 0.16 0.09 0.05 0.16
GCG Ala 0.25 0.10 0.11 0.11 0.24 0.26 0.26 0.29 0.22 0.30 0.31 0.15 0.16 0.25 0.30 0.10 0.29
GUA Val 0.25 0.12 0.11 0.12 0.18 0.17 0.15 0.20 0.23 0.12 0.15 0.23 0.14 0.23 0.17 0.14 0.23
UCG Ser 0.17 0.05 0.06 0.06 0.14 0.17 0.14 0.13 0.14 0.18 0.16 0.11 0.03 0.13 0.18 0.20 0.16
UUA Leu 0.17 0.06 0.07 0.07 0.20 0.18 0.20 0.32 0.20 0.16 0.23 0.14 0.07 0.18 0.32 0.13 0.16
mean - 0.21 0.09 0.10 0.09 0.19 0.20 0.19 0.22 0.20 0.19 0.21 0.18 0.16 0.21 0.22 0.16 0.18
a As fraction of all codons for the particular amino acid. Bold, value higher than that in any of the indicated mammals; underlined, value more than double that in any of the indicated mammals.
b Amino acid encoded by the codon
c Expected frequency if codons for each amino acid are used randomly (assuming equal A, C, G, and U contents and no di- or trinucleotide bias).
Methods
Cells and viruses
Reoviruses T1L, T2J, T3D, and T3C12 were Coombs and/or Nibert laboratory stocks. Other reovirus isolates were provided by Dr. T. S. Dermody (Vanderbilt University). Virus clones were amplified to the second passage in murine L929 cell monolayers in Joklik's modified minimal essential medium (Gibco) supplemented to contain 2.5% fetal calf serum (Intergen), 2.5% neonatal bovine serum (Biocell), 2 mM glutamine, 100 U/ml penicillin, 100 μg/ml streptomycin, and 1 μg/ml amphotericin B, and large amounts of virus were grown in spinner culture, extracted with Freon (DuPont) or Vertrel-XF (DuPont), and purified in CsCl gradients, all as previously described [19,58].
Sequencing the M1 genome segments
All oligonucleotide primers were obtained from Gibco/BRL. Genomic dsRNA was extracted from gradient-purified virions with phenol/chloroform [59]. Strain identity was confirmed by resolving aliquots of each in 10% SDS-PAGE gels and comparing dsRNA band mobilities [60]. Oligonucleotide primers corresponding to either the 5' end of the plus strand or the 5' end of the minus strand were as previously described [40]. Additional oligonucleotides for sequencing were designed and obtained as needed. cDNA copies of the M1 genes of each virus were constructed by using the 5' oligonucleotide primers and reverse transcriptase (Gibco/BRL). The cDNAs were amplified by the polymerase chain reaction [61] and resolved in 0.7% agarose gels [59]. The bands corresponding to the 2.3-kb gene were then excised, purified, and eluted with Qiagen columns, using the manufacterer's instructions. Sequences of the respective cDNAs were determined in both directions by dideoxynucleotide cycle sequencing [62-64], using fluorescent dideoxynucleotides.
Sequences at the termini of each M1 segment were determined by one or both of two methods. For some isolates, sequences near the ends of the segment were determined by modified procedures for rapid amplification of cDNA ends (RACE) as previously described [32,65]. In addition, the sequences at the ends of all M1 segments were determined in both directions by a modification of the 3'-ligation method described by Lambden et al. [66]. Briefly, viral genes from gradient-purified virions were resolved in a 1% agarose gel, and the M segments were excised and eluted with Qiagen columns as described above. Oligonucleotide 3'L1 (5'-CCCCAACCCACTTTTTCCATTACGCCCCTTTCCCCC-3'; phosphorylated at the 5' end and blocked with a biotin group at the 3' end) was ligated to the 3' ends of the M segments according to the manufacterer's directions (Boehringer Mannheim) at 37°C overnight. The ligated genes were repurified by agarose gel and Qiagen columns to remove unincorporated 3'L1 oligonucleotide and precipitated overnight with ice-cold ethanol. The precipitated genes were dissolved in 4 μl of 90% dimethyl sulfoxide. cDNA copies of the ligated M1 genes were constructed by using oligonucleotide 3'L2 (5'-GGGGGAAAGGGGCGTAATGGAAAAAGTGGGTTGGGG-3') and gene-specific internal oligonucleotide primers designed to generate a product of 0.5 to 1.2 kb in length. These constructs were amplified by PCR, purified in 1.5% agarose gels, excised, and eluted as described above. Sequences of these cDNAs were determined with gene-specific internal oligonucleotides and with oligonucleotide 3'L3 (5'-GGGGGAAAGGGGCGTAAT-3') by dideoxy-fluorescence methods.
Sequence analyses
DNA sequences were analyzed with DNASTAR, DNA Strider, BLITZ, BLAST, and CLUSTAL-W. Phylogenetic analyses were performed using the PHYLIP programs . DNAPARS (parsimony) (Fig. 3) and DNAML (maximum likelihood) (data not shown) produced essentially identical trees. These programs were run using the Jumble option to test the trees using 50 different, randomly generated orders of adding the different sequences. In addition, DNAPENNY (parsimony by brand-and-bound algorithm) generated a tree with the same branch orders as DNAPARS and DNAML. RETREE and DRAWGRAM were used to visualize the tree and to prepare the image for publication. Final refinement of the image was performed with Illustrator. Synonymous and nonsynonymous substitution frequencies were calculated according to the methods of Nei and Gojobori [67] as applied by Dr. B. Korber at . Codon frequencies in the M1 coding sequences were determined using the COUNTCODON program maintained at . Values for codon frequencies in mammalian genomes were obtained from the Codon Usage Database maintained at
Protein sequence analyses were performed using the GCG programs in SeqWeb version 2 (Accelrys). Multiple sequence alignments were done with PRETTY. Determinations of molecular weights, isoelectric points, and residue counts were done with PEPTIDESORT. Determinations of percent identities in pairwise comparisons were done with GAP. Plots of sequence identity over running windows of different numbers of amino acids (Fig. 4 and data not shown) were generated with PLOTSIMILARITY, and the image for publication was refined with Illustrator (Adobe Systems). In addition, protein sequences were analysed for conservative and nonconservative substitutions by pairwise CLUSTAL-W analyses, using BLOSUM matrix weighting [68].
SDS-PAGE
Gradient-purified virus and core samples were dissolved in electrophoresis sample buffer (0.24 M Tris [pH 6.8], 1.5% dithiothreitol, 1% SDS), heated to 95°C for 3–5 min, and resolved in a 5–15% SDS-PAGE gradient gel (16.0 × 12.0 × 0.1 cm) [69] at 5 mA for 18 h. Some sets of resolved proteins were fixed, and stained with Coomassie Brilliant Blue R-250 and/or silver [70].
Immunoblotting
Gradient-purified viral and core proteins were resolved by SDS-PAGE as described above, and sets of resolved proteins were transferred to nitrocellulose membranes with a Semi-Dry Transblot manifold (Bio-Rad Laboratories) according to the manufacturer's instructions. Transfer of all proteins was confirmed by Ponceau S staining. Nonspecific binding was blocked in TBS-T (10 mM Tris [pH 7.5], 100 mM NaCl, 0.1% Tween 20) supplemented with 5% milk proteins, and the membranes probed with polyvalent anti-μ2 antibody (a kind gift from Dr. E. G. Brown, University of Ottawa). Membranes were washed with TBS-T, reacted with horseradish peroxidase-conjugated goat anti-rabbit IgG (Jackson ImmunoResearch Laboratories), and immune complexes detected with the enhanced chemiluminescence system (Amersham Life Sciences) according to the manufacturer's instructions.
Infections and IF microscopy
CV-1 cells were maintained in Dulbecco's modified Eagles medium (Invitrogen) containing 10% fetal bovine serum (HyClone Laboratories) and 10 μg/ml Gentamycin solution (Invitrogen). Rabbit polyclonal IgG against μNS [71] was purified with protein A and conjugated to Alexa Fluor 488 or Alexa Fluor 594 using a kit obtained from Molecular Probes and titrated to optimize the signal-to-noise ratio. Cells were seeded the day before infection at a density of 1.5 × 104/cm2 in 6-well plates (9.6 cm2/well) containing round glass cover slips (18 mm). Cells on cover slips were inoculated with 5 PFU/cell in phosphate-buffered saline (PBS) (137 mM NaCl, 3 mM KCl, 8 mM Na2HPO4 [pH 7.5]) containing 2 mM MgCl2. Virus was adsorbed for 1 h at room temperature before fresh medium was added. Cells were further incubated for 18–24 h at 37°C before fixation for 10 min at room temperature in 2% paraformaldehyde in PBS or 3 min at -20°C in ice-cold methanol. Fixed cells were washed with PBS three times and permeabilized and blocked in PBS containing 1% bovine serum albumin and 0.1% Triton X-100. Antibody was diluted in the blocking solution and incubated with cells for 25–40 min at room temperature. After three washes in PBS, cover slips were mounted on glass slides with Prolong (Molecular Probes). Samples were examined using a Nikon TE-300 inverted microscope equipped with phase and fluorescence optics, and images were collected digitally as described elsewhere [23]. All images were processed and prepared for presentation using Photoshop (Adobe Systems).
Authors' Contributions
PY and NDK participated equally in designing primers and determining the T2J M1 sequence; TJB, MMA, and JSLP determined the M1 sequences of the T3C12 clone and other labs' T3D clones, as well as factory morphologies of all clones; and all authors participated in writing the manuscript. MLN and KMC are the principal investigators and KMC determined the M1 sequences of the other field isolates and ts mutants.
Acknowledgments
We thank T. S. Dermody for suggesting and providing virus isolates used in this work, J. N. Simonsen for helpful comments, and members of their laboratories for critical reviews of the manuscript. We also thank S. Taylor of the Canadian Science Centre for Human and Animal Health Core DNA Sequencing Facility, the University of Calgary Core DNA Sequencing Facility, and the University of Manitoba Department of Medical Microbiology Core DNA Sequencing Facility.
This research was supported by grants MT-11630 and GSP-48371 from the Canadian Institutes of Health Research (to K. M. C.), NIH grant R01 AI-47904 (to M. L. N.), a junior faculty research grant from the Giovanni Armenise-Harvard Foundation (to M. L. N.), and NIH grant K08 AI52209 (to J. S. L. P.). N. D. K. was the recipient of a Natural Sciences and Engineering Research Council Post-Graduate Scholarship from the Government of Canada and T. J. B. received additional support from NIH grant T32 AI07061 to the Infectious Disease Training Program at Harvard Medical School.
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| 15507160 | PMC524354 | CC BY | 2021-01-04 16:38:33 | no | Virol J. 2004 Sep 23; 1:6 | utf-8 | Virol J | 2,004 | 10.1186/1743-422X-1-6 | oa_comm |
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Nutr Metab (Lond)Nutrition & Metabolism1743-7075BioMed Central London 1743-7075-1-71550716110.1186/1743-7075-1-7ReviewMetabolic aspects of low carbohydrate diets and exercise Peters Sandra J 1sandra.peters@brocku.caLeBlanc Paul J 1pleblanc@brocku.ca1 Faculty of Applied Health Sciences, Brock University, St. Catharines, ON, Canada L2S 3A12004 30 9 2004 1 7 7 22 9 2004 30 9 2004 Copyright © 2004 Peters and LeBlanc; licensee BioMed Central Ltd.2004Peters and LeBlanc; 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.
Following a low carbohydrate diet, there is a shift towards more fat and less carbohydrate oxidation to provide energy to skeletal muscle, both at rest and during exercise. This review summarizes recent work on human skeletal muscle carbohydrate and fat metabolic adaptations to a low carbohydrate diet, focusing mainly on pyruvate dehydrogenase and pyruvate dehydrogenase kinase, and how these changes relate to the capacity for carbohydrate oxidation during exercise.
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Review
Exercise, an acute bout of muscular activity, requires an expenditure of energy above resting levels. This required mechanical energy is provided through the conversion of metabolic fuels into ATP, the base currency of chemical energy. Once produced, ATP is the only direct form of energy that is transferred and utilized by the contractile apparatus within the muscle. Fats are the predominant fuel source of resting skeletal muscle and during exercise, there is a complex interaction between skeletal muscle fat and carbohydrate (CHO) metabolism (see [1] for review). When evaluating the effects of exercise on skeletal muscle fuel utilization, there are many facets that must be taken into consideration. These include intensity and duration of the bout of exercise and the training status of the subjects. During low intensity physical activity (25% maximal oxygen uptake (VO2max)), fat supplies the majority of metabolic fuel to exercising skeletal muscle [2]. As physical activity increases to moderate levels (65–70% VO2max), there is a shift to more reliance on CHO, specifically muscle glycogen [2]. However, at this level of physical activity, fat oxidation becomes increasingly important as the duration of exercise increases [2] or as training status improves [3]. The studies presented in this review utilize moderately active subjects (maximal oxygen uptake, 50–60 ml·kg-1·min-1) exercising at a workload of 65–75% VO2max for 30–48 min.
The sources of chemical energy that fuel exercising skeletal muscle are available through endogenous depots (intramuscular glycogen and triglycerides) or exogenous sources (plasma glucose and free fatty acids). In turn, these exogenous and endogenous fuel sources are replenished through dietary intake. As a result, there is an important relationship between diet and fuel metabolism in skeletal muscle.
Diets low in carbohydrate content have become increasingly popular as a method of weight loss. These diets that limit daily dietary carbohydrate intake are termed low-carbohydrate diets (LCD). When evaluating the effects of LCD, there are a couple of factors that must be considered, as they may influence the measured outcome. These include the composition of the diet (since a LCD may replace the missing CHOs with either protein or fat), and the duration of the dietary period. For the purpose of this review, LCD will refer primarily to high-fat low-carbohydrate isocaloric diets with <50 g of CHO per day, with a composition of 3–8% CHO, 22–46% protein, and 51–75% fat, and consumed for 3–6 days.
The present paper will briefly review human skeletal muscle metabolism during exercise and the importance of dietary CHO for metabolic energy production. It has been well documented that diets low in carbohydrates result in several metabolic and hormonal adaptations that improve fat oxidation and promote glycogen sparing in exercising skeletal muscle (see [4] for review). However, the mechanism(s) responsible for these changes in exercising skeletal muscle are still debatable, but could be the result of up-regulated fat and/or down-regulated carbohydrate metabolism. The emphasis of the present paper is on adaptive skeletal muscle CHO and fat metabolism in humans, and will compare recent studies that examine the effects of altered diets on key enzymes and how fatty acid composition and re-feeding of carbohydrates following these altered diets affect these enzymes. Data from other mammals are cited where necessary.
Regulation of carbohydrate oxidation by low-carbohydrate diet
Role of pyruvate dehydrogenase
In order to understand the regulation of carbohydrate oxidation, the regulation of the mitochondrial enzyme pyruvate dehydrogenase (PDH) must be carefully considered. PDH is a multi-enzyme complex which catalyzes the irreversible oxidative decarboxylation of glycolytically-derived pyruvate to acetyl-coenzyme A (acetyl-CoA; Fig. 1) Because it is highly regulated, it plays a pivotal role in determining the proportion of acetyl-CoA which is derived from carbohydrate sources, thereby regulating flux through carbohydrate oxidation and indirectly determining the rate of fat oxidation. The amount of PDH in its active form (PDHa) determines its activity and regulation is achieved through reversible phosphorylation, catalyzed by an intrinsic PDH phosphatase (PDP), which dephosphorylates and activates PDH, and PDH kinase (PDK), which phosphorylates and inhibits PDH [5]. The E1 subunit of PDH has three known phosphorylation sites, with the first site being necessary for inactivation of the complex, and the other two sites acting as barrier sites to hinder phosphatase activation [6].
Figure 1 Activation of pyruvate dehydrogenase enzyme complex control by a phosphorylation and dephosphorylation cycle.
Each of the covalent regulatory enzymes of PDH is subject to allosteric regulation. Phosphorylation of the complex is catalyzed by a family of four PDK isoforms (PDK1-4) which differ in their responsiveness to allosteric inhibition by pyruvate or activation by energy charge (ATP/ADP ratio), redox (NADH/NAD+ ratio), and acetyl-CoA-to-free CoA ratio (see [7] for review). In addition, the kinases differ in their specificity for the different phosphorylation sites [7]. Thus, the relative activities of the PDK isoform population will determine the response of the PDH complex in acute situations. An intrinsic pair of phosphatases (PDP1 and 2) catalyze the dephosphorylation and activation of PDH [8]. PDP1 is the isoform which is activated in the presence of increasing concentrations of Ca2+ ions (as would be expected during exercise), while PDP2 is activated when insulin levels are increased during dietary manipulations [8].
At rest, PDH is mainly phosphorylated and inactive due to high energy charge, redox, and acetyl-CoA-to-free CoA ratio and low pyruvate concentration, which maintain a high PDK activity. Phosphatase activity is low at rest, due to low intramuscular Ca2+ levels. During exercise, Ca2+ release from the sarcoplasmic reticulum is the primary stimulus that coarsely activates PDH whereas changes to pyruvate concentration, energy charge, and possibly redox fine-tune this activation (see [9] for review), in order to match PDH activation to the demand for CHO oxidation [10].
In addition to the importance of intramitochondrial effectors to the acute regulation of PDH activation in the first few seconds or minutes, long-term or chronic alterations to the activation state of PDH can be accomplished through stable changes in the absolute levels of PDK and/or PDP. The rate of activation of PDH is dependent on the activity ratio of PDK and PDP, and changes in the expression of either covalent modifier would alter the rate of activation or inactivation of PDH. These chronic alterations occur over hours or days and are independent of acute changes in intramitochondrial effector concentrations.
Effects of low-carbohydrate diet
In 1993, Putman and co-workers undertook a study to examine the effects of a short term low-carbohydrate diet on activation of skeletal muscle PDHa activity during moderately intense exercise (75% VO2max) [11]. In this study, a 6 d LCD was compared to a high-carbohydrate diet, shifting reliance from the two extremes, either towards fat or towards carbohydrate oxidation. Subjects completed muscle glycogen depleting exercise and then consumed either a LCD (< 3% energy from carbohydrate) or a high-carbohydrate diet (86% carbohydrate) for 6 d. At the end of the dietary intervention, subjects exercised at 75% VO2max. The subjects exhausted in ~47 min following the LCD, and exhaustion coincided with hypoglycemia (~2.4 mM) and low levels of muscle glycogen (~32 mmol glucosyl units/kg dry muscle), indicating that that skeletal muscle and liver glycogen stores were limiting under these conditions and at this intensity of exercise. Following the high-carbohydrate diet, exercise was terminated at the same time as the LCD trial, and their blood glucose concentrations were maintained at ~5 mM throughout the exercise duration. Skeletal muscle glycogen content decreased during exercise but was still ~250 mmol glucosyl units/kg dry muscle at the end of exercise. At the onset of exercise during the high-carbohydrate trial, PDHa activity increased maximally in the first 15 minutes of exercise, reflecting the increased energy demand for carbohydrate oxidation at this workload. However, following the LCD, PDHa activity was maximally activated in the first 15 minutes of exercise, but the activation did not achieve the same levels as during the high-carbohydrate trial, effectively impairing the capacity for carbohydrate oxidation and possibly promoting fat oxidation for the duration of exercise at this workload (Fig. 2). The authors were unable to adequately explain the difference in PDHa activity between the trials based on acute changes in the concentrations of intra-mitochondrial effectors, suggesting that chronic regulation of the complex could be playing a role.
Figure 2 Skeletal muscle pyruvate dehydrogenase in its active form (PDHa) at rest and during exercise in low carbohydrate (LCD) and high carbohydrate (HCD) diets. * denotes significance from LCD. Adapted from Putman et al. [11].
Subsequent studies demonstrated adaptive alterations at the level of PDK with resultant changes in PDH activation. PDK activity was adaptively increased in human skeletal muscle following 6 days of a LCD [12] (Fig. 3). PDK activity increased in as little as 24 hr and continued to increase in a linear fashion throughout the 6 d diet [13]. The increased PDK activity in human skeletal muscle was associated with increased PDK4 mRNA and protein expression, which was maximally increased after 24 h [13]. These studies suggest a selective increase in PDK4 expression with LCD. The increase in PDK activity during the LCD was associated with impaired glucose clearance from the blood in response to an oral glucose load in health young men [14]. Following as little as 56 h on the LCD, the 90 min area under the blood glucose and plasma insulin concentration vs. time curves increased 2-fold and 1.25-fold, respectively, during an oral glucose tolerance test [14].
Figure 3 Pyruvate dehydrogenase kinase (PDK) activity during six days of a LCD. a Significantly different from day 0. b Significantly different from day 1. Adapted from Peters et al. [12,13].
These increased levels of PDK4 protein and PDK activity would be expected to render the complex resistant to activation during exercise, as observed by Putman et al. [11] for two reasons: 1) increased multi-site phosphorylation of the PDH complex, and/or 2) decreased sensitivity of the complex to regulation by pyruvate. Increased PDK activity would be expected to enhance multi-site phosphorylation of the E1 subunit and make the complex more resistant to dephosphorylation and activation by the phosphatase [6]. Under normal dietary conditions the predominant isoform in human skeletal muscle is PDK2, which has a greater affinity for phosphorylation of site 1 (the inactivating site) of the E1 subunit [15-17]. However, as the population of PDK4 isoform increased, there would be enhanced phosphorylation of the 2nd (barrier) site, since this isoform has a greater affinity for both site 1 and site 2 [15-17]. As well, PDK2 has a greater sensitivity to inactivation by pyruvate than PDK4 [18]. Thus at the onset of exercise with increased glycolytic flux, the increased levels of PDK4 protein would render the complex more resistant to activation due to increased PDK4 kinase activity even in the face of elevated muscle pyruvate concentrations [19].
A confounding factor in the Putman study was that subjects had undergone intense glycogen depleting exercise protocols prior to both dietary interventions, so the initial levels of skeletal muscle glycogen and glycogen utilization was considerably lower following the LCD [11]. In a subsequent study, subjects were asked to refrain from intense exercise throughout the study, and a LCD (~3% carbohydrate) was compared to a mixed diet (~55–60% carbohydrate) instead of a high-carbohydrate diet [20]. Subjects followed each 6 d dietary intervention with 30 min exercise at a slightly lower workload (65% VO2max). The object of the study was to match as closely as possible the glycogen utilization during exercise between the two trials. Although the initial skeletal muscle glycogen concentration was still ~50% lower in the LCD compared to the mixed diet, skeletal muscle glycogen utilization and pyruvate accumulation were similar during the 30 min of exercise in both trials. Unlike the attenuated activation of PDHa at the onset of exercise which was observed in the Putman study [11], these authors observed that the activation during exercise was identical between the two conditions. Thus, in spite of the fact that PDK activity and PDK4 isoform would be expected to increase to a similar extent as previous studies [13], these effects were overridden when initial muscle glycogen levels were higher and glycolytic flux to pyruvate was maintained [20]. It is clear from these studies that the intensity and duration of the exercise play a role in the regulatory changes observed during exercise following a LCD. As exercise intensity increases, the demand for muscle and liver glycogenolysis and muscle carbohydrate oxidation increases. These stores are not fully replenished following a very low carbohydrate diet, and therefore during intense exercise glycogenolytic flux and PDH activation are decreased following a LCD.
Effect of fatty acid composition of low-carbohydrate diet
The studies presented in this review demonstrate that LCDs decrease the activation of PDH in skeletal muscle at rest and during exercise, mediated through increased PDK activity and isoform expression. However, not all LCDs are created equally, and there is increasing interest in the composition of the fatty acids consumed. Recently, it has been demonstrated that substituting only ~12% of the fat in a LCD (~3% carbohydrate; 75% fat) with fish oils, which are high in omega-3 unsaturated fatty acids, attenuated the diet-induced increase in PDK activity in human skeletal muscle [21] (Fig. 4). These results are similar to earlier work in rodents, with the key difference being that the diet-induced increase in rat skeletal muscle PDK activity was completely abolished with the addition of fish oil [22]. In fact, the increase in PDK activity following a 28 d LCD diet could be completely reversed in as little as 24 h when fish oils were introduced into the high-fat diet [22]. Surprisingly, in both rat and human skeletal muscle in the resting and basal state, PDHa activity was not affected by the inclusion of fish oils suggesting that the total fat content of the diets was more important in determining the conversion of the complex in the basal state [22]. However, there is evidence from animal studies that a LCD which is rich in fish oils enhances muscle carbohydrate oxidation and glucose disposal in response to a challenge such as an insulinemic/euglycemic clamp. Jucker et al. [23] fed rats one of three experimental diets to study the effects on muscle metabolism: a LCD diet rich in safflower oil; a LCD rich in fish oil; or a high-carbohydrate (control) diet. They found that the safflower-fed rats were insulin resistant compared to control or the fish oil-fed rats. The increased whole body glucose disposal in the fish oil-fed rats correlated with increased insulin-stimulated muscle disposal of glucose through oxidation as determined with stable isotope tracer technology [23]. Thus, it would appear that the deleterious effects of high-fat feeding on carbohydrate oxidation and glucose disposal may be ameliorated when the dietary composition of fatty acids are considered carefully. The effect of altered fat composition on skeletal muscle metabolism during exercise has yet to be examined.
Figure 4 Pyruvate dehydrogenase kinase (PDK) activity before and after three days of a LCD with and without n3 fatty acids. a Significantly different from pre diet. b Significantly different from post LCD diet. Adapted from Turvey et al. [21].
Effect of re-feeding of carbohydrate following low-carbohydrate diet
In humans, there is little information on how rapidly the LCD-adapted increase in PDK activity and PDK4 protein may be reversed with carbohydrate re-feeding. Most re-feeding studies have used prolonged fasting as a perturbation, and very little work has been done in human skeletal muscle. In rodents, early studies in cardiac muscle indicated that re-feeding following 6 h starvation recovered PDHa activity to ~75% of normal levels in as little as 1–2 h. However, as the duration of the starvation period increased, the time course of the response to re-feeding was longer, in such that after 48 h of starvation, PDHa activity recovered to only ~25% of control values after 4 h [24]. In later rodent studies, this increasing resistance to PDH complex activation was accompanied by increased PDK activity, which correlated with the duration of the fast or high-fat diet [25,26]. Following 48 h starvation and re-feeding, PDK activity and PDK4 protein in skeletal muscle decreased ~50–60% in approximately 4 h of re-feeding [27]. However, little is known about the time course reversion of PDK activity and PDK isoform expression following a LCD in human skeletal muscle.
In human skeletal muscle, Pilegaard et al. [28] recently examined changes in PDK4 mRNA concentrations in human skeletal muscle following fasting and re-feeding. Subjects fasted for 20 h and then were given either a high-carbohydrate meal or a high-fat meal. In muscle biopsies taken 1 h after the re-feeding meal, these authors found increased transcription rate and mRNA concentration of the PDK4 isoform regardless of the composition of the meal. Based on rodent studies of PDK activity, these data were unexpected, since it would be expected that the high-carbohydrate meal would suppress PDK4 gene expression. These data suggested that the skeletal muscle PDK 4 gene was very sensitive to metabolic disturbances. However, without measurement of PDK or PDH activity, the study gave little information regarding how quickly the fasting-induced increase in PDK activity was reversed with carbohydrate re-feeding. A recent study examining carbohydrate re-feeding following a 6 d LCD indicates that PDK activity is rapidly reversed and PDHa activity has fully recovered in as little as 3 h in resting human skeletal muscle [29]. Thus, the adaptive change in PDK activity observed in human skeletal muscle is rapidly reversed with re-feeding of carbohydrates, regardless of potential changes in PDK4 mRNA expression [28].
Regulation of fat oxidation by low-carbohydrate diet
There is little information regarding the skeletal muscle adaptation on "the fat side" to a LCD. In human skeletal muscle, most studies restrict their measurements to gene expression or mRNA concentrations of the pertinent enzymes involved in fat oxidation, and very few have measured the more physiologically relevant concentrations of enzyme activity or protein concentration. Still, there is evidence in human skeletal muscle for increased activities of several regulatory enzymes and proteins in skeletal muscle fatty acid uptake and oxidation following high fat diets or LCD. Key steps include delivery of fatty acids to the muscle through muscle lipoprotein lipase (LPL), sarcolemmal fatty acid transporters and plasma membrane fatty acid binding proteins (FAT/CD26 and FABPpm respectively), mitochondrial uptake and oxidation through carnitine palmitoyl transferase I (CPT I), fatty acid beta-oxidation (marker enzyme β-hydroxy acyl CoA dehydrogenase (β-HAD)), and general oxidative capacity (marker enzyme citrate synthase (CS)).
In response to a 4 week adaptation to a high fat (~62% fat) moderate LCD (~20% CHO), skeletal muscle LPL activity increased almost 2-fold, increasing fatty acid availability to the muscle and increasing intramuscular triglyceride content significantly [30]. In terms of muscle fatty acid uptake, there is evidence that the FAT/CD36 protein and mRNA were increased modestly (1.25-fold) after only 5 d on a moderate LCD (20% CHO), while FABPpm gene expression and protein content were unaffected by the diet [31]. In general, muscle uptake of fatty acids and very low density lipoprotein triglycerides, as well as plasma fatty acid oxidation were higher during exercise following a fat-rich LCD (21% CHO) when exercise training was combined with the diet perturbation [32].
In human studies, skeletal muscle CPT I is unaffected by LCD. This was demonstrated at the level of maximal enzyme activity following a 6 d LCD (~3% CHO) [12], and mRNA levels following a 5 d LCD (19% CHO) [31]. However, in skeletal muscle of rats fed a high-fat diet, CPT I enzyme activity capacity was increased up to 1.3 to 2-fold at 10 weeks, depending on the fatty acid composition of the diet [33]. In another rat study, increased gene expression of CPT I mRNA appears to be restricted to type I slow oxidative muscle fibers, since a significant increase was only documented in the soleus muscle, and not the extensor digitorum longus following 8 weeks of a high-fat LCD (0% CHO) [34]. Taken together, these studies suggest that the short term 5–6 d LCD perturbation may not be prolonged enough to evoke a significant change in activity or gene expression of this enzyme which regulates transport of fatty acids into the mitochondria for oxidation. This is further supported by the fact that in well trained human subjects, maximal CPT activity was modestly increased following a prolonged (4 week) very low LCD (<20 g CHO), although it is not clear from this data whether this measurements included CPT I and CPT II activity together [35].
Increased activity of a key marker enzyme for fatty acid beta-oxidation has been observed in human skeletal muscle during prolonged LCD perturbations as well. Although a 6 d LCD (3% CHO) did not alter β-HAD activity [12], Helge et al. [36] observed increased β-HAD activity following a 4 week LCD (20% CHO) perturbation in untrained subjects. However, they found no increase in either whole body VO2max or CS activity, suggesting that the increase in beta-oxidation was specific rather than a generalized increase in oxidative capacity. Similarly, a more carbohydrate restricted diet (3% CHO) for 6 d did not alter CS activity in human skeletal muscle [12]. In contrast, results from some rat studies have demonstrated modest increases in CS activity of approximately 20% [37-39], with the largest increases demonstrated in type IIb fibers [40]. Although the increase in β-HAD activity in human skeletal muscle and possibly CS in rat muscle could potentially suggest an increase in oxidative capacity, recent research has demonstrated that there was no difference in human skeletal muscle mitochondrial density (as determined by electron microscopy), even though there was an increase in fat oxidation at rest and during incremental exercise following a 5 week high fat LCD (25–30% CHO) [41].
Conclusions
In summary, following a 6 d LCD in human subjects, PDHa activation is attenuated during intense exercise and this is due at least in part to increased PDK activity and PDK4 gene expression. This decreased activation of PDHa decreases carbohydrate and increases fat oxidation during exercise. PDK activity increases in as little as 24 h on a LCD, and PDK activity increases linearly over the 6 d. Impaired glucose clearance in response to an oral glucose tolerance test was observed in healthy subjects following only 56 h of LCD, but this may be dependent on the fatty acid composition of the diet. With re-feeding of carbohydrates, PDK activity drops to pre-diet levels in 3 h, although this does not appear to correlate with mRNA concentration. If intense exercise is restricted and muscle glycogen stores and utilization rates are preserved during the LCD, the activation of the PDH complex is similar to that following a mixed diet.
The up-regulation of enzymes involved in muscle fatty acid uptake and fat oxidation appears to be slower to response to a LCD perturbation. In addition, these adaptations appear to be of a smaller magnitude. In human studies there is evidence that muscle uptake of fatty acids is up-regulated by LCD through increased maximal activity of LPL and increased FAT/CD36. However, the maximal rate of mitochondrial transport of fatty acids through CPT I appears to be resistant to adaptive changes in response to the diet. In addition, although increased maximal β-HAD activity has been documented in response to LCD, there is no evidence that the overall oxidative capacity is elevated following a LCD in human skeletal muscle.
Acknowledgements
S.J. Peters is supported by the National Science and Engineering Research Council (NSERC), and P.J. LeBlanc is supported by an NSERC post-doctoral fellowship.
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| 15507161 | PMC524355 | CC BY | 2021-01-04 16:37:45 | no | Nutr Metab (Lond). 2004 Sep 30; 1:7 | utf-8 | Nutr Metab (Lond) | 2,004 | 10.1186/1743-7075-1-7 | oa_comm |
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BMC MedBMC Medicine1741-7015BioMed Central London 1741-7015-2-371547391210.1186/1741-7015-2-37Research ArticleSignificance of MDR1 and multiple drug resistance in refractory human epileptic brain Marchi Nicola 1marchi@marionegri.itHallene Kerri L 1hallenk@ccf.orgKight Kelly M 1kightk@ccf.orgCucullo Luca 1cuculll@ccf.orgModdel Gabriel 2moeddeg@ccf.orgBingaman William 2bingamb@ccf.orgDini Gabriele 1dinig@ccf.orgVezzani Annamaria 3vezzani@marionegri.itJanigro Damir 12janigrd@ccf.org1 Cerebrovascular Research Center, The Cleveland Clinic, Cleveland, OH, 44195, USA2 Department of Neurological Surgery, The Cleveland Clinic, Cleveland, OH, 44195, USA3 Department of Neuroscience, Mario Negri Institute for Pharmacological Research, Milano, Italy2004 9 10 2004 2 37 37 19 4 2004 9 10 2004 Copyright © 2004 Marchi 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 multiple drug resistance protein (MDR1/P-glycoprotein) is overexpressed in glia and blood-brain barrier (BBB) endothelium in drug refractory human epileptic tissue. Since various antiepileptic drugs (AEDs) can act as substrates for MDR1, the enhanced expression/function of this protein may increase their active extrusion from the brain, resulting in decreased responsiveness to AEDs.
Methods
Human drug resistant epileptic brain tissues were collected after surgical resection. Astrocyte cell cultures were established from these tissues, and commercially available normal human astrocytes were used as controls. Uptake of fluorescent doxorubicin and radioactive-labeled Phenytoin was measured in the two cell populations, and the effect of MDR1 blockers was evaluated.
Frozen human epileptic brain tissue slices were double immunostained to locate MDR1 in neurons and glia. Other slices were exposed to toxic concentrations of Phenytoin to study cell viability in the presence or absence of a specific MDR1 blocker.
Results
MDR1 was overexpressed in blood vessels, astrocytes and neurons in human epileptic drug-resistant brain. In addition, MDR1-mediated cellular drug extrusion was increased in human 'epileptic' astrocytes compared to 'normal' ones. Concomitantly, cell viability in the presence of cytotoxic compounds was increased.
Conclusions
Overexpression of MDR1 in different cell types in drug-resistant epileptic human brain leads to functional alterations, not all of which are linked to drug pharmacokinetics. In particular, the modulation of glioneuronal MDR1 function in epileptic brain in the presence of toxic concentrations of xenobiotics may constitute a novel cytoprotective mechanism.
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Background
Failure to respond to therapeutic concentrations of antiepileptic drugs (AEDs) is the usual basis for defining multiple drug resistant epilepsy, but the mechanisms underlying resistance to AEDs are still largely unknown. It is generally believed to be a multifactorial phenomenon, depending on both pharmacodynamic and pharmacokinetic mechanisms. The electrical and synaptic properties of neurons in epileptic human tissue are reported to undergo changes that may result in decreased susceptibility to some AEDs [1]. Multidrug resistance in epilepsy may also result from inadequate intraparenchymal AED concentrations due to poor penetration of the blood-brain barrier (BBB).
Recent findings suggest that the molecular mechanisms of clinically defined multiple drug resistance involve drug-efflux transporters such as the ATP-binding cassette subfamily B member 1 (ABCB1), also known as MDR1 or P-glycoprotein (P-gp) [2-4]. Specifically, in epileptic brain, genes associated with multiple drug resistance are overexpressed in the endothelial cells that constitute the BBB [5,6]. MDR1 is also overexpressed in neurons [4,7] and astrocytes (in which MDR1 is normally not measurable) from lesions associated with active epileptogenic foci in human and rodent brain [8-10].
The link between MDR1 overexpression and drug resistance in epilepsy is still poorly understood [6,11]. Thus, while localization of the drug extrusion pump in the BBB is consistent with reduced penetration of AEDs into the CNS, it is not known if or how the presence of MDR1 in the parenchyma affects drug delivery and distribution, or whether it is involved in different cellular functions. Evidence from several groups suggests that MDR1 diminishes the apoptotic response induced by growth factor withdrawal [12], decreases complement-mediated cytotoxicity ([13] and impairs the activation of caspase-dependent cell death pathways [14,15]. Reports indicate that all these events occur in epileptic tissue, and they are thought to be at least partly responsible for seizure-associated neuronal cell death. In addition, we recently found that epileptic astrocytes that overexpress MDR1 are devoid of p53, a proapoptotic factor [8].
In this study we have evaluated the relationship between neuronal and astrocytic MDR1 expression and the capacity of the cells to survive cytotoxic insults, using drug resistant epileptic human specimens. Our results suggest that overexpression of MDR1 leads to functional alterations in the CNS that may be linked to both drug pharmacokinetics and neuroglial survival in injured brain.
Methods
Human tissue
Human subjects were used as donors of cortical tissue samples. The investigation conformed to the principles outlined in the Declaration of Helsinki. Patient consent was obtained as per Institutional Review Board instructions before collection of the specimens. All the experiments involved small portions of human neocortical or hippocampal tissue, which were excised for therapeutic reasons from patients with pharmacoresistant epilepsy (see Table 1 for patient identification). Temporal lobe tissue was taken from the inferior or middle temporal gyrus during standard temporal lobectomy; frontal or parietal lobe samples were chosen from the most epileptogenic areas, as determined by chronic subdural grid or intraoperative electrocorticographic (EEG) recordings. Handling of the excised tissue depended on the experiment to be conducted, as described below.
Cell isolation and primary cultures
Astrocyte cell cultures were established, as described by Marroni et al. [8,9,16], from cerebral cortical tissue obtained during temporal lobectomies (n = 3) conducted to relieve medically intractable seizures (see Table 1 for details on patients, ID# 12, 13, 14). The cells were passaged up to three times before use. MDR1 expression was not affected by the number of passages [8,9,16].
Commercially available normal human astrocytes were used as controls (ACBRI 371, Applied Cell Biology Research Institute, Kirkland, WA, USA, and Clonetics, Biowhitaker, Walkersville, MD, USA).
Immunohistochemistry
To investigate MDR1 protein expression and cellular distribution in human epileptic tissue, slide-mounted sections (10 μm thickness) from frozen brain tissue (Table 1, patient ID# 1–11; 3 slices per patient) were double immunostained as previously described [8,9,16]. The primary antibodies used were mouse monoclonal anti-P-Glycoprotein (C494) (1:40, Calbiochem-Novabiochem Corporation, San Diego, CA, USA), human polyclonal anti-P-Glycoprotein (1:100, Calbiochem-Novabiochem Corporation, San Diego, CA, USA), mouse monoclonal anti-neuronal nuclei (NeuN) (1:500, Chemicon International, Temecula, CA, USA), rabbit polyclonal anti-neurofilament (NF) (1:200, Chemicon International, Temecula, CA, USA) and rabbit anti-cow glial fibrillary acidic protein (GFAP) (1:200, DAKO Corporation, Carpinteria, CA, USA). Secondary antibodies were chosen according to the primary antibody hosts: Texas red dye-conjugated affinipure donkey anti-mouse IgG (1:50, Jackson Immunoresearch Laboratories Inc., West Grove, PA, USA), and Fluorescein isothiocyanate (FITC)-conjugated affinipure donkey anti-mouse and anti-rabbit IgG (1:200, Jackson Immunoresearch Laboratories Inc., West Grove, PA, USA). Sections were coverslipped on glass slides using Vectashield mounting medium with DAPI (Vector, Burlingame, CA, USA) and analyzed by fluorescent microscopy.
Cell counting
For quantitative evaluation of neurons and astrocytes expressing MDR1 in epileptic tissue, we chose three 1600 μm2 fields at random in each tissue slice (3 slices per patient, n = 11 patients; see Table 1, patient ID# 1–11). Within each field, NeuN or GFAP positive cells co-expressing MDR1 were counted using NIH Software and Photoshop 6 (Adobe), and the number was expressed as a fraction of the total number of neurons and astrocytes, respectively, in that field. Numbers for each field were then averaged for every slice, and the mean value for each patient is given in Fig. 1B,1D.
Doxorubicin uptake
Astrocytes from epileptic tissue (Table 1, patient ID# 12, 13, 14) or commercially available control human astrocytes were cultured in 8-well chamber-slides. At confluence, the cells (approximately 8 × 104 per well) were treated overnight with 1μM XR9576, a specific MDR1 blocker [17,18], or for 2 h with 50 μM verapamil, a non-specific MDR1 blocker [19,20]. Further sets of astrocytes from epileptic tissue and controls were incubated as above but in the absence of blockers. Fluorescent red doxorubicin [21] was then added to all the cultures for 1, 2, 3, 5, 7 and 24 h. Incubation was stopped by rinsing twice with PBS and the cells were fixed overnight at 4°C in 4% formalin in PBS (pH 7.4). They were mounted and coverslipped the next day using Vectashield mounting medium. Doxorubicin uptake was analyzed by fluorescent microscopy (Leica Leitz DM-RXE, Wetzlar, Germany) using NIH Image Software. For each well, four fields (1600 μm2) were randomly analyzed and optical density measurements were averaged to obtain representative data. To quantify the doxorubicin in the cells, the fluorescence in each sample was compared with standard solutions of doxorubicin (10 nM-10 μM). Data were analyzed using Origin Lab 7 software.
14C-Phenytoin uptake
14C-Phenytoin uptake was measured in cultured astrocytes from epileptic tissue (Table 1, patient ID# 12, 13, 14) and in control astrocytes, as described by Meyer et al. [22]. The cells were cultured in 30-mm Petri dishes (approximately 106 cells) and incubated at 37°C with 1 ml of T3 cell buffer (Tris-HCl 50 mM, NaCl 120 mM, KCl 50 mM, pH 7.4) containing 10 μM 14C-Phenytoin (Specific activity = 9.57 μCi/μmol). The incubation was terminated after 10 s, 30 s, 1 min, 5 min or 10 min by adding 1 ml of ice-cold T3 buffer. The cells were washed with 1 ml of ice-cold T3 buffer and solubilized with 1% (w/v) Triton X-100 for 1 h at 37°C. Intracellular radioactivity was measured using a scintillation cocktail (Packard Ultima Gold, ECN, Costa Mesa, CA, USA).
Acute in vitro toxicity
Brain slices (500 μm) were cut using a vibratome from dysplastic human cortex and temporal lobe epilepsy brain specimens (Table 1, patient ID# 9,10,11). Slices (n = 6 per patient) were maintained in vitro as previously described [23,24]. A further set of 6 slices was obtained from 3 naïve rats as previously described [25]. Slices (n = 2 per patient per experimental condition) were incubated for 2 h in artificial CSF containing, in mM: NaCl 124; KCl 3; CaCl2 1; MgCl2 1.4; NaHCO3- 26; KH2PO4 1.25; glucose 10, with or without 3 μM XR9576. A toxic concentration (375 μM) of Phenytoin (PHE) was then added for 5 h [22]. An additional set of slices was kept for 7 h in artificial CSF only, and electrophysiological measurement of activity was used to assess tissue viability throughout the experiment. Live/Dead Viability/Cytotoxicity solution (Molecular Probes L3224, Eugene, OR, USA) was used to quantify cell death or survival; EthD-1, a component of the solution, enters cell nuclei through damaged membranes, producing a bright red fluorescence in dead cells. The 2 mM EthD-1 stock solution (20 μl) was added to 10 ml of 1X sterile PBS. At the end of the experiment, each slice was washed with PBS and incubated with 2 ml of the above solution for 10 min under continuous oxygenation. The slices were then fixed in 4% formalin in PBS overnight at 4°C and cryoprotected by 30% sucrose. Three 20 μm slices were cryosectioned from each 500 μm slice and analyzed by fluorescent microscopy. DAPI was used to assess the total number of cells per slice, and GFAP and NeuN were used to identify glia and neurons (see 'Immunohistochemistry'). The number of EthD-1 positive cells was reckoned in 3 randomly chosen fields (1600 μm2) within each slice. These values were averaged for each slice and expressed as percentages of the average number of DAPI-positive cells in the chosen fields.
Evaluation of glioneuronal damage
To evaluate the relationship between MDR1 positive cells and nuclear morphology (DAPI staining), 10 μm slices from 11 patients (Table 1, patient ID# 1–11) were obtained as described in 'Immunocytochemistry'. Small and condensed nuclei indicate apoptosis or irreversible cell damage, while large nuclei with diffuse DNA (DAPI) staining are typical of healthy cells. MDR1 positive cells with diffuse DNA staining (healthy cells) were counted over three randomly chosen fields in each slice and analyzed using NIH Software and Photoshop. Numbers for each field were averaged for every slice; the corresponding mean value is given in figure 3B.
Statistical analysis of data
Data were expressed as means ± SEM. The level of significance between means was estimated by ANOVA (Origin 6.0. Microcal). Differences with p < 0.05 were considered significant.
Results
Results were obtained from 14 patients (50% female) affected by intractable seizures. The mean patient age was 16.4 years (range 8 months – 49 years; SE = 4.6). For details, see Table 1.
MDR1 expression in human epileptic brain tissue
Figure 1 shows representative micrographs of MDR1 expression in endothelial, glial and neuronal cells from epileptic human brain specimens (Table 1, patient ID# 1–11). The findings are consistent with previous work demonstrating that MDR1 expression in multiple drug resistant brains is confined to the cortical lesion site [4,7-9,16]; this was consistently observed in all epileptic samples in the present study. Thus, relatively normal brain distant from the dysplastic tissue can be used as "control". Abundant MDR1 immunopositive endothelial cells (thin arrows in A) were observed in epileptic cortex, as well as immunopositive parenchymal and perivascular astrocytes (arrowheads in A) double-labeled with GFAP, a specific glial marker. Out of 107 GFAP-positive astrocytes, 91 (85%) showed MDR1 staining (Figure 1B). We also examined MDR1 expression in neurons from epileptic tissue, identified by NeuN and NF immunoreactivity (Fig. 1C). Approximately 169 out of 264 NeuN-positive neurons (64%) showed MDR1 staining (Figure 1D).
Role of MDR1 expression in drug extrusion by astrocytes
To determine whether MDR1 expression in 'epileptic' astrocytes results in enhanced extrusion of xenobiotics compared to 'normal' astrocytes, we measured the cellular uptake of PHE and doxorubicin, two established substrates of P-glycoprotein [19,20,26,27] (Table 1, patient ID# 12, 13, 14; Fig. 2). We used 1 μM red fluorescent doxorubicin [21] and visualized its cellular distribution by fluorescent microscopy (Fig. 2A). We previously showed by western blot analysis that 'normal' astrocytes have lower levels of P-gp than 'epileptic' astrocytes [8,9]. Doxorubicin uptake was reduced in astrocytes from epileptic tissue compared to control astrocytes (p < 0.05). This effect was abolished by the specific blocker XR9576 (1 μM) [17,18], or by the less specific antagonist verapamil (50 μM), indicating active MDR1-mediated extrusion of doxorubicin by epileptic glia.
Fig. 2B shows that uptake of 10 μM 14C-Phenytoin was significantly lower in astrocytes from epileptic tissue than in control astrocytes, and the difference was maximal after 10 min incubation with the AED (p < 0.05). The difference was abolished in the presence of 1 μM XR9576, indicating MDR1-mediated efflux of PHE in epileptic astrocytes. The MDR1 blockers did not affect doxorubicin or Phenytoin uptake in control astrocytes (not shown). Neither Phenytoin nor doxorubicin treatment induced toxicity in cell cultures under our experimental conditions.
MDR1 and cell survival
MDR1 is involved in detoxification mechanisms that protect cells from xenobiotics [28], apoptosis [12] and other cellular stresses [13-15]. To investigate whether MDR1 expression in astrocytes and neurons from epileptic tissue enhances survival of toxic or injurious events, we exposed neocortical slices from human epileptic (Table 1, patient ID# 9, 10, 11) and rat brain to concentrations of PHE higher than those reported to induce toxicity in cultured rat astrocytes [22]. Bar histograms (Figure 3A) indicate that slices of human epileptic cortex exposed for 5 h to 375 μM PHE showed no cellular toxicity, as assessed by co-localization of the nuclear marker DAPI with EthD-1, a marker of cell damage. Conversely, significant cell loss (p < 0.05) was observed in rat brain slices under these experimental conditions. When MDR1 activity was blocked by 3 μM XR9576, PHE induced cell damage in the human epileptic cortex to an extent similar to that in rat brain tissue. Neurons and astrocytes, identified using NeuN and GFAP respectively, were similarly affected by PHE (Fig. 3A). The MDR1 inhibitor XR9576 alone (3μM) did not affect tissue viability (data not shown).
Figure 3B shows a significant positive correlation (R = 0.4, p < 0.006) between MDR1 expression and cell integrity, as measured by morphological evaluation of nuclear condensation (DAPI staining) [29,30]. Quantification of the cells retaining nuclear DNA integrity showed that no DNA damage occurred in 85% of glia and 66% of neurons expressing MDR1, suggesting a novel role for MDR1 in protecting neurons and glia from toxic agents.
Discussion
The main finding was that MDR1 might have different roles depending on the location in the brain where it is expressed. Thus, in addition to overexpression in endothelial cells, which is likely to affect the penetration of AEDs into the brain, MDR1 is also overexpressed in the parenchyma, where it might have a cytoprotective role, extruding otherwise toxic concentrations of xenobiotics from the intracellular compartment.
MDR1 expression in epileptic brain
In agreement with previous findings, we report here that MDR1 is highly expressed in vessels of the BBB and in parenchymal cells (histochemically identified as astrocytes and neurons) in drug refractory epilepsy of different etiologies [4,7-9,11,27]. Pharmacological evidence suggests that MDR1 overexpression in blood vessels of the BBB has the crucial role of extruding AEDs from brain to blood [19,20,27,31], and this phenomenon may contribute to failure of antiepiletic treatments. In this study, we focused on the effects of MDR1 expression in parenchymal neurons and astrocytes from pharmacoresistant epileptic tissue.
MDR1 expression in astrocytes: drug uptake studies
We found that PHE and doxorubicin uptake by astrocytes from human epileptic tissue is reduced in comparison with normal astrocytes. The difference is abolished when MDR1 function is blocked, indicating that these drugs are efficiently extruded by "epileptic" astrocytes by a P-gp mediated mechanism. We suggest that this might contribute to decreasing the AED brain levels only if it occurs in perivascular astrocytes. Thus, perivascular astrocytes impinging on blood vessels may act as an additional barrier to drug penetration into the brain in regions where BBB permeability is transiently altered, for example during epileptic activity [32,33] (Fig. 4). In contrast, MDR1 overexpression by parenchymal glia would result in enhanced extrusion of substrates into the brain extracellular space; this is not compatible with a decrease in the concentration of AEDs at their neuronal targets, suggesting that it subserves a different function (see below).
MDR1 expression in neurons and parenchymal glia: relationship to cell survival
We show in this paper that MDR1 is expressed in immunocytochemically identifiable neurons and astrocytes in brain slices from refractory human epilepsy patients. We have previously reported that basic apoptotic mechanisms may be defective in glia from epileptic tissue, since the pro-apoptotic proteins p53 and p21 could not be detected in "epileptic" astrocytes [8,9,16]. This evidence, together with overexpression of MDR1, suggests that "epileptic" astrocytes have gained a distinct survival advantage. This is supported by the marked enhancement of Phenytoin cytotoxicity in both glia and neurons when MDR1 function is blocked. The conclusion is consistent with the findings of Bittigau et al. [34] that various AEDs induce apoptotic neuronal cell death in developing naïve rat brain at plasma concentrations relevant to seizure control in humans; activators of MDR1 transcription prevented these effects.
Finally, we found a positive correlation between neuronal and astrocytic expression of MDR1 and lack of nuclear condensation, a marker of apoptosis and irreversible cell damage. Thus, expression of MDR1 in glia and neurons may protect the cells against toxic xenobiotics or against endogenous compounds that enter the brain in pathological conditions.
Conclusions
In conclusion, as summarized in figure 4, our findings indicate a possible new function for MDR1. In normal brain, MDR1 operates at the blood-brain barrier, regulating the plasma/brain exchange of xenobiotics. In epileptic brain, the levels of astrocytic, neuronal and endothelial MDR1 are abnormal, possibly leading to altered brain penetration/distribution of drugs. Perivascular astrocytes may also contribute to this phenomenon. In addition to its drug extrusion effect at the BBB, which may be relevant for pharmacoresistance in epilepsy, this protein may have a role in neuroglial survival under hostile conditions such as those occurring in epileptic brain. The overexpression of multiple drug resistance could be the consequence of an altered mechanism of apoptotic cell death; this hypothesis is supported by the finding that changes in multiple drug resistance gene expression correlate with negative regulation of p53 and other pro-apoptotic genes [8].
Abbreviations
AEDs: anti-epileptic drugs
BBB: blood-brain barrier
DOX: doxorubicin
GFAP: glial fibrillary acidic protein
MDR1: multiple drug resistance protein
NeuN: neuronal nuclei
NF: neurofilament
PHE: Phenytoin
Competing interests
The authors declare that they have no competing interests.
Author's contributions
NM and LC carried out the pharmacological experiments and data analysis.
KLH and KMK obtained surgical resections, established astrocytic cell cultures and performed the immunohistochemical and cell counting studies.
GM performed the acute in vitro toxicity experiments.
WB provided the surgical specimens.
GD provided additional input and editing.
AV and DJ designed and co-ordinated some of the experiments.
They also contributed equally to the preparation of the manuscript.
DJ, the PI of the study, co-ordinated and supervised most of the personnel involved in this project.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
The authors would like to thank Drs. P. Schwartzkroin and J. Engel for their helpful comments on an earlier version of this manuscript. They would also like to thank Dr. David Norris from Xenova Limited for the MDR inhibitor. LC was supported in part by a grant from ARDF (Alternatives Research and Development Foundation). This work was supported by NIH-2RO1 HL51614, NIH-RO1 NS 43284 and NIH-RO1 NS38195 to DJ, and by FIRB (RBNE01NR34_007) to AV.
Figures and Tables
Figure 1 Immunohistochemical detection of MDR1 expression in human drug-refractory epileptic brain. Panels A-B show MDR1 expression at the BBB. Widespread GFAP immunoreactivity (green) co-localizes with MDR1 (red). Nuclei are stained blue with DAPI. Note that both parenchymal and perivascular astrocytes express MDR1 (arrowheads), as do endothelial cells of the brain capillaries (thin arrows). The box graph in B illustrates the percentage of GFAP-positive astrocytes (GFAP) in samples from 11 patients (Table 1, 1–11) that also expressed MDR1. Data points (circles), mean value (triangle), range (horizontal bars) and standard errors (° SE) are shown together with the 50th percentile value. Panels C-D show the neuronal expression of MDR1. Double immunostaining with MDR1 and two neuronal markers (neurofilament, NF and NeuN) reveals that MDR1 is expressed in a subpopulation of epileptic neurons. Arrows point to MDR1 negative neurons, while arrowheads indicate the more frequently-occurring MDR1 positive neurons. Approximately 64% of cortical neurons (n = 264) were positive for MDR1. Quantitative analysis in D was obtained from 11 patients. Patient values (circles), mean (triangle), range (horizontal bars) and standard errors (± SE) are shown. The 50th percentile is also indicated in the box graph.
Figure 2 Uptake of doxorubicin and phenytoin by astrocytes: effect of MDR1 blockade. Panel A shows 1 μM doxorubicin uptake in astrocytes from epileptic human brain (n = 3 patients) and controls. Note that uptake was decreased in "epileptic" astrocytes compared to normal astrocytes, and this difference was abolished when MDR1 inhibitors (1 μM XR9576 or 50 μM verapamil) were added. Micrographs depict red fluorescent doxorubicin uptake in the various experimental conditions as assessed by fluorescence microscopy. Panel B shows the time-course of intracellular accumulation of 14C-Phenytoin in "epileptic" astrocytes and controls. Note that 14C-Phenytoin uptake into epileptic astrocytes reached a plateau after 10 s incubation, while uptake in control astrocytes was greater at each time point and reached a plateau after 10 min incubation (p < 0.01 vs. control; n = 3). 14C-Phenytoin uptake in "epileptic" astrocytes returned to control level in the presence of 1 μM XR9576 (°p < 0.01 vs. control''; ^p < = 0.01 vs. "epileptic'' astrocytes+XR9576).
Figure 3 Glioneuronal MDR1 expression and resistance to Phenytoin induced cytotoxicity. Histograms in A show data (mean ± SE, n = 3) obtained using cortical slices from human epileptics (Table 1, ID# 9,10,11), or naïve rat cortical slices, treated for 5 h with 375 μM Phenytoin (PHE) ± 2 h preincubation with 3 μM XR9576. Note that PHE toxicity (as illustrated in the micrographs) was apparent in normal rat brain slices, and was greatly exacerbated in human epileptic tissue treated with the MDR1 blocker (p < 0.01). Micrographs depict immunohistochemical evidence of PHE-induced cytotoxicity in GFAP-positive astrocytes and NeuN-positive neurons as assessed by their co-localization with EthD-1, a marker of cell damage. All the cells (astrocytes and neurons) were assessed by DAPI staining. Note that the combination of PHE + XR9576 increased the percentage of injured cells (red) as compared to PHE alone. Panel B shows enlarged nuclei (identified by DAPI) in cells expressing (MDR1 positive) or not expressing (MDR1 negative) MDR1 protein. Note that small condensed nuclei (seen in MDR1 negative cells) reflect apoptosis or irreversible cell damage. In contrast, large nuclei with diffuse DNA staining (seen in MDR1 positive cells) are typical of healthy cells. The graph shows the positive correlation between cells with healthy nuclei and MDR1 expression (n = 34 independent values from slices obtained from 11 patients; p < 0.006).
Figure 4 Model of the proposed role of cell specific MDR1 expression in epileptic brain. Under physiological conditions, when the blood-brain barrier is intact, overexpression of MDR1 (and possibly other drug resistance proteins [5,9]) in endothelial cells causes active net extrusion of drugs from the brain into the vascular lumen (left panel, (1)). A fraction of the AED molecules bypassing the MDR1 barrier (see Fig. 1A) will diffuse into the lipophilic membranes of parenchymal neurons and glia. MDR1 expression in these cells will lead to diminished intracellular sequestration of drugs and may increase their interstitial levels [27]. However, since the total amount of AED in the epileptic tissue is reduced in the first instance by active BBB extrusion, free AED in the extracellular space may still remain below therapeutic concentrations (left panel, (2) and (4)). In addition, MDR1 overexpression in parenchymal astrocytes and neurons affords protection against toxic concentrations of xenobiotics (left panel (2) and (4)). During the transient opening of the BBB due to epileptic activity, AEDs may be back-fluxed into the blood stream by MDR1 expressed at the glial end-feet of perivascular astrocytes, constituting a "second defense barrier" in the brain (left panel, (3)). Right panels A and B schematically summarize these possible roles of MDR1 in epileptic human brain.
Table 1 Information on patients affected by various forms of epilepsy whose brain specimens were used for the experiments (ICC = Immunocytochemistry and Immunohistochemistry, TOX = Phenytoin toxicity, UP = drug uptake).
ID # Sex Age (years) Use Pathology
1 M 8 months ICC Parieto-Occipital-Frontal cortical dysplasia, Right Hemispherectomy
2 F 49 ICC Temporal Lobe Epilepsy, Hippocampal atrophy
3 F 10 ICC Left Hippocampal sclerosis
4 F 3 ICC Cortical Dysplasia, Right Hemispherectomy
5 M 7 ICC Left Cortical Dysplasia
6 F 4 ICC Right Frontoparietal Epilepsy
7 M 1 ICC Left Frontal Lobe Epilepsy
8 M 25 ICC Right Temporal Lobe Epilepsy
9 M 45 TOX, ICC Temporal Lobe Epilepsy
10 F 4 TOX, ICC Cortical Dysplasia
11 F 36 TOX, ICC Temporal Lobe Epilepsy
12 M 24 UP Left Frontal Lobe Epilepsy
13 F 14 UP Cortical Dysplasia
14 M 7 UP Left Temporal/Frontoparietal Epilepsy
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| 15473912 | PMC524356 | CC BY | 2021-01-04 16:03:34 | no | BMC Med. 2004 Oct 9; 2:37 | utf-8 | BMC Med | 2,004 | 10.1186/1741-7015-2-37 | oa_comm |
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BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-5-751546268410.1186/1471-2164-5-75Research ArticleExtreme conservation of noncoding DNA near HoxD complex of vertebrates Sabarinadh Chilaka 1sabarinadhch@yahoo.comSubramanian Subbaya 1subree@stanford.eduTripathi Anshuman 1anshu411@rediffmail.comMishra Rakesh K 1mishra@ccmb.res.in1 Centre for Cellular and Molecular Biology, Uppal Road, Hyderabad 500 007, India2004 6 10 2004 5 75 75 23 4 2004 6 10 2004 Copyright © 2004 Sabarinadh et al; licensee BioMed Central Ltd.2004Sabarinadh 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
Homeotic gene complexes determine the anterior-posterior body axis in animals. The expression pattern and function of hox genes along this axis is colinear with the order in which they are organized in the complex. This 'chromosomal organization and functional correspondence' is conserved in all bilaterians investigated. Genomic sequences covering the HoxD complex from several vertebrate species are now available. This offers a comparative genomics approach to identify conserved regions linked to this complex. Although the molecular basis of 'colinearity' of Hox complexes is not yet understood, it is possible that there are control elements within or in the proximity of these complexes that establish and maintain the expression patterns of hox genes in a coordinated fashion.
Results
We have compared DNA sequence flanking the HoxD complex of several primate, rodent and fish species. This analysis revealed an unprecedented conservation of non-coding DNA sequences adjacent to the HoxD complex from fish to human. Stretches of hundreds of base pairs in a 7 kb region, upstream of HoxD complex, show 100% conservation across the vertebrate species. Using PCR primers from the human sequence, these conserved regions could be amplified from other vertebrate species, including other mammals, birds, reptiles, amphibians and fish. Our analysis of these sequences also indicates that starting from the conserved core regions, more sequences have been added on and maintained during evolution from fish to human.
Conclusion
Such a high degree of conservation in the core regions of this 7 kb DNA, where no variation occurred during ~500 million years of evolution, suggests critical function for these sequences. We suggest that such sequences are likely to provide molecular handle to gain insight into the evolution and mechanism of regulation of associated gene complexes.
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Background
Eukaryotic genome contains a large excess of non-coding sequences. Conservation of these sequences among species is a strong indication of their functional significance. With the availability of genome sequences it is possible to identify such sequences taking a comparative genomics approach [1-4]. The clusters of homeotic genes, which are expressed in a coordinated manner [5], are among the most conserved regions of the vertebrate genome. Clustering of genes that are regulated in a linked manner has been noticed in several other cases [6,7]. However, the molecular mechanism behind such coordination in regulation is not yet understood. Several mechanisms have been proposed that link the organization of homeotic genes and the spatio-temporally controlled expression [8]. Colinearity in hox complexes was first discovered in Drosophila [9] and later studies on the bithorax complex have demonstrated the role of chromatin organization in its regulation [10]. Recent studies on the HoxD complex suggest a role for higher order chromatin organization in the regulation of this complex involving up to 20 kb upstream region [11].
Results and discussion
We compared genomic regions flanking hox complexes in order to identify conserved regions with potential regulatory function. Here we report that the upstream regions of HoxD complexes of human, mouse, rat, sacred baboon, horn shark, zebra fish and puffer fish contain long stretches of extremely conserved sequences. In the 25 kb region upstream of the HoxD complex from these organisms we found an extremely conserved region spread in three blocks located within 7 kb from the 3' end of the Evx-2 gene. These conserved regions, designated as Conserved Region 1, Conserved Region 2 and Conserved Region 3 (CR1, CR2 and CR3) (Fig. 1) show a degree of conservation not seen before among distant species. Detailed analysis of each region spanning to several hundred base pairs, in particular the CR2 shows several stretches of 100 % conservation, Fig. 2. We also noticed longer stretches of conservation among mammals, which gradually shortens as we go towards lower vertebrates, defining the core of each conserved region, across the vertebrate classes, see Additional file 1. This and the fact that in case of shark, as compared to mammals, the intervening sequence lengths between CR2 and CR3, and CR1 and Evx-2 is shorter by ~1300 bp and ~600 bp, respectively (Fig. 1) suggest that starting from the shorter conserved regions, additional unique sequences have progressively been acquired and conserved during the evolution of primates from lower vertebrates. This may reflect the molecular basis of conservation and elaboration of Hox gene regulation during evolution of these species [12].
Figure 1 Schematic representation of sequence conservation in the HoxD upstream region. Human sequence (AC009336; from position 56601 to 64095) was compared to the corresponding sequences of Papio hamadryas (AC116665), Heterodontus francisci (AF224263), Mus musculus (AC015584), Fugu rubripes (CAAB01000449) and Rattus norvegicus (NW_042732). Sequences that are conserved across vertebrates are shown as blocks. The conservation extends beyond these blocks within primates and rodents. ESTs found in the database corresponding to this region are also shown. ESTs mapping to CR3 are BB838602 from mouse 8 cell embryo and BU129154 from chicken 36 stage limb; and those mapping to CR1 are AA620964 from human testis; BB332383, BB335110, BB334358, BB333569 from 6 and10 days mouse neonate medulla oblongata and BU255316 from chicken 36 stage limb.
Figure 2 Comparison of conserved regions from human, mouse and shark. Conserved bases of mouse and shark are shown as '.' and '-' indicates indels. Underlined sequences of human indicate primers that were used for amplification of the corresponding sequence from different vertebrates.
Universal occurrence of these sequences in all vertebrate classes was confirmed by their amplification using primers from human HoxD complex (Figure 3) followed by Southern hybridization and sequencing (unpublished observation). Furthermore, using CR1, CR2 or CR3 as query we searched genomic sequences of variety of eukaryotes in available databases. This search indicated that these sequences are single copy and vertebrate specific. While these conserved regions appear to be a key component of the HoxD complex of all vertebrates looked at, we did not find such a degree of conservation in the flanking regions of other hox complexes (HoxA, B and C) of vertebrates. In order to trace back the evolutionary origin of such sequences, it will be of interest to investigate occurrence of these sequences at the corresponding region in the hox complexes of species of urochordata, cephalochordata or even agnatha. In the tunicate Oikopleura dioca, where hox genes are dispersed but the spatial pattern seen in other animals is still present [13], we did not find CR1, CR2 or CR3. Also, we did not find any significant conserved region corresponding to these CRs in the amphioxus genomic region that contains the cluster of hox genes. It appears, therefore, that these extremely conserved sequences have originated in the vertebrates where the hox complex has additional distinct features of tight clustering compared to the insect hox clusters and the temporal colinearity, not seen in invertebrates.
Figure 3 Conservation of CR1, CR2 and CR3 in all vertebrate classes. PCR amplification of different vertebrate genomic DNA samples using primers designed based on the human sequence. Lanes: M – size marker indicated in bp, hu – human, mo – mouse, ch – chicken, co – cobra, fr – frog and zf – zebra fish. The arrows indicate the corresponding products that have been confirmed by direct sequencing as well as Southern hybridization using human CRs as probe.
Several recent reports using comparative genomics approach have identified conserved non-coding regions among different vertebrates [14-16] but none to the degree that we report here. The mechanism that may require such a high degree of conservation is not known. It is not, therefore, immediately clear what precisely is the role of these sequences. EST database search revealed that part of CR1 and CR3 are transcribed without any significant ORF but no EST corresponding to CR2 or any other part of the 7 Kb region was found, Fig. 1. A possible mechanism could involve RNA from this region that may function by base pairing to the genomic target sites. If that is the case, such high conservation could be expected. Role of transcription in the regulation of bithorax complex is emerging from recent studies [17].
Conclusions
While such an extreme conservation of several hundred nucleotides over half a billion years in a region that does not code for any known proteins certainly implicates essential role for such sequences, probably in the regulation of HoxD complex, no known regulatory element requires such extreme conservation extending up to hundreds of base pairs. It is, therefore, likely that these elements could be components of a novel mechanism common to all vertebrates that regulates this gene complex. We are tempted to suggest that such a strongly conserved region from fish to human linked to a gene complex that is known to determine body axis formation may be the key determinant of molecular basis of early ontogeny. Early embryos of all vertebrates show striking similarity and we suggest that these elements may control the early expression pattern of HoxD which leads to similar pattern of the embryo shape. The gradient of conservation seen in this region from fish to human may further signify the evolutionary history of this locus and diversification of the morphological features along the anterior-posterior body axis of the vertebrate classes.
Methods
Sequence analysis
The genomic sequences that contained Evx-2 and any of the Hoxd genes were downloaded and annotated using gene/ORF prediction tools. Similar approach was used for other hox complexes. Homology searches of the upstream sequences of HoxD region from human (AC009336; from nucleotide 56601 to 64095) was carried out using the BLAST program of NCBI. The sequences that showed significant homology were further used to analyze the extent of homology by BLAST 2 program. The conserved regions from each sequence was obtained and subjected to multiple sequence analysis using Clustal X. In order to identify the expressed sequences corresponding to the conserved sequence, the conserved sequences along with the unique sequences were BLASTed against EST databases (human, mouse and dbEST).
The contigs that showed significant homology to the upstream sequences of human HoxD were annotated using the tBLASTx program and searching the translated amino acid sequence in the Swissprot database. Repeat masker program was used to look for repeat content. Genebank sequences used in this study are as follows: AC116665 Papio hamadryas, AF224263 Heterodontus francisci, AC015584 Mus musculus, AC009336 Homo sapiens, CAAB01000449 Fugu rubripes and NW_042732 Rattus norvegicus.
DNA isolation, PCR amplification, sequencing and Southern hybridization
For the isolation of genomic DNA blood samples of human, chick and cobra (Naja naja) were used while liver tissue of mouse and muscle tissue of frog (Bufo melanostictus) and zebra fish were used. Standard protocol of DNA isolation was followed which included lysis, RNase A and proteinase K digestions followed by phenol/chloroform extraction and precipitation. Concentration and quality of the genomic DNA was checked on 0.7% agarose gel and UV absorption spectrophotometry. Based on the sequence of conserved regions primers were designed to amplify the three regions CR1, CR2 and CR3.
Primers used in this study to amplify conserved regions from different vertebrate species were:CR1 forward- GAGGCTGTTCACACTGGTGG,CR1 reverse- ATCATGCTCTCTGATGGACC,CR2 forward- GCATCGTAATCAGTTCGGTC,CR2 reverse- TGATACAAGCTGATACCGTC,CR3 forward- GCTATTCAAAATGTTATTTGAG and CR3 reverse- CTGTAATGAAGAAAAGATTTATG.
The 25 μl reaction was performed using 100 ng template DNA and 5 pmol each of forward and reverse primers. PCR protocol was as follows: initial denaturation step of 94°C for 3 min was followed by 35 cycles of 94°C for 1 min, 57°C for 1 min and 72°C for 1.30 min and final extension step at 72°C for 7 min. Authenticity of the PCR products was confirmed by direct sequencing and Southern hybridization, using the corresponding human DNA as probe.
Note
An earlier version of this article was deposited in the 'Deposited Research' section of Genome Biology, , [18]. While this manuscript was in reviewing process, a report comparing human genome to several other mammalian sequences identified many highly conserved noncoding sequences [19]. Interestingly, this study also identified CR2 as uc.108 near HOXD and, in agreement to our observation, noted only a "core" conserved region in fish, suggesting that additional parts of the ultraconserved region were innovations after the common ancestor with fish.
Authors' contributions
CS carried out the sequence analysis, PCR amplification and Southern analysis. SS participated in sequence analysis and DNA isolation from several organisms. AT carried out the sequencing of PCR products and participated in the sequence alignments. RKM conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Size and degree of conservation of CR1, CR2 and CR3 in different vertebrates. Core of conserved regions and extended conserved regions between indicated species is shown as length of sequence and degree of conservation. Non-overlapping blocks of vertebrate conservation is indicated based on human, baboon, rat, mouse and shark comparison.
Click here for file
Acknowledgements
This work was supported by a young investigators grant (RGY0316/2001-M) from Human Frontier Science Program to RKM.
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| 15462684 | PMC524357 | CC BY | 2021-01-04 16:32:42 | no | BMC Genomics. 2004 Oct 6; 5:75 | utf-8 | BMC Genomics | 2,004 | 10.1186/1471-2164-5-75 | oa_comm |
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BMC PediatrBMC Pediatrics1471-2431BioMed Central London 1471-2431-4-201546182510.1186/1471-2431-4-20Research ArticleMorphine for elective endotracheal intubation in neonates: a randomized trial [ISRCTN43546373] Lemyre Brigitte 1blemyre@ottawahospital.on.caDoucette Joanne 2doucette@hhsc.caKalyn Angela 2kalyn@hhsc.caGray Shari 3grays@hhsc.caMarrin Michael L 2marrin@mcmaster.ca1 Department of Pediatrics, Division of Neonatology, University of Ottawa, Ottawa, Canada2 Department of Pediatrics, Division of Newborn Medicine, Hamilton Health Sciences Corporation, McMaster University Medical Center, Hamilton, Canada3 Department of Pharmacy, Hamilton Health Sciences Corporation, McMaster University Medical Center, Hamilton, Canada2004 5 10 2004 4 20 20 1 6 2004 5 10 2004 Copyright © 2004 Lemyre et al; licensee BioMed Central Ltd.2004Lemyre 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
Elective endotracheal intubations are still commonly performed without premedication in many institutions. The hypothesis tested in this study was that morphine given prior to elective intubations in neonates would decrease fluctuations in vital signs, shorten the duration of intubation and reduce the number of attempts.
Methods
From December 1999 to September 2000, infants of all gestations admitted to a level III neonatal intensive care unit and requiring an elective endotracheal intubation were randomly assigned to receive morphine 0.2 mg/kg IV or placebo 5 minutes before intubation. Duration of severe hypoxemia (HR< 90/min and Sp02<85%), duration of procedure, duration of hypoxemia (Sp02<85%), number of attempts and change in mean blood pressure were compared between groups.
Results
34 infants (median 989 g and 28 weeks gestation) were included. The duration of severe hypoxemia was similar between groups. Duration of procedure, duration of hypoxemia, number of attempts and increases in mean blood pressure were also similar between groups. 94% of infants experienced bradycardia during the procedure.
Conclusion
We failed to demonstrate the effectiveness of morphine in reducing the physiological instability or time needed to perform elective intubations. Alternatives, perhaps with more rapid onset of action, should be considered.
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Background
Endotracheal intubation is a painful and stressful procedure, which is associated with acute increases in blood pressure and intracranial pressure, bradycardia and hypoxemia [1]. These physiologic changes are potentially of sufficient magnitude to produce the reperfusion injury and venous congestion associated with intraventricular hemorrhage (IVH) and periventricular leukomalacia (PVL) [2,3]. It has been clearly demonstrated that newborn infants feel pain. More so, premature infants likely have an increased sensitivity to pain [4], which can lead to chronic pain or neurobehavioral and developmental sequelae [5,6].
Most premature infants and many term infants admitted to neonatal intensive care units (NICU) will require one or more endotracheal intubations during their stay. In 1994, 84% of Canadian NICUs, including ours, rarely or never used premedication for elective intubations [7]. In 2000, the majority of units used premedication 50–75% of the time in infants greater than 30 weeks gestation, but only rarely in those 30 weeks gestation or less [8]. Perceived lack of evidence of benefits and fear of side effects were reasons.
A literature review revealed six randomized controlled trials [9-14], comparing various combinations of premedications, which have enrolled one hundred and thirty newborn infants. Bradycardia can be ameliorated by atropine [9,10] or glycopyrrolate [11]. Increases in intracranial pressure can be dampened by muscle relaxants [9-12]. Analgesics, which seem warranted, have been minimally studied alone [13], but seem to limit the increase in blood pressure when combined with muscle relaxants [11]. A recent metaanalysis concludes that overall, premedication appears beneficial, either in stabilizing vital signs or decreasing the duration of the procedure, but data is limited about which medications are best to achieve optimal conditions [15].
We reviewed our policy, which did not include premedication for elective endotracheal intubations, in light of the current evidence. As morphine has been used for years in neonates with apparent safety and efficacy for pain and as staff in our unit were comfortable with this medication, we aimed to evaluate the efficacy of morphine, in achieving better intubation conditions and success while maintaining vital signs stability.
Methods
Study population
Infants of all gestations, admitted to McMaster University Medical Center level III NICU and considered likely to need an elective oral or nasotracheal intubation during their hospital stay, were candidates for inclusion in this study. Families were approached for consent as soon as possible after birth when an elective intubation during their hospital stay seemed likely: if their infant(s) was less than 30 weeks gestation, already ventilated (as endotracheal tubes are frequently changed after 10 days if clinical deterioration from a respiratory standpoint), was on NCPAP for respiratory distress or was needing an elective surgery. Others were approached when an elective intubation was needed. At the time of this study, our unit was a 33-bed level 3 NICU, caring for both inborn and outborn patients, and the referral center for 25000 annual deliveries, with 900–1000 admissions per year.
Infants were excluded if they met any of the following conditions: 1) absence of an intravenous access, 2) upper airway anomaly potentially leading to a difficult intubation, 3) cyanotic heart disease, 4) upper gastrointestinal obstruction (which would require a rapid sequence intubation) or 5) concurrent opioid administration.
Study intervention
Infants requiring an elective intubation were randomly assigned to receive either morphine 0.2 mg/kg IV or placebo (0.9% NaCl), given over 1 minute, followed 5 minutes later by the intubation. This larger dose of morphine was chosen for the perceived acuity of pain produced by an intubation; a larger dose may be more effective to decrease the struggling by infants during the procedure, which is caused by pain. Infants were randomized according to a computer-generated random number table with random block sizes. Morphine and placebo were supplied in identical unidose vials, labeled PIN Rx, which were prepared by one pharmacist according to the randomization sequence and placed in sealed, consecutively numbered envelopes, which were opened just before intubation. Thus, randomization occurred just prior to intubation.
Three to four minutes after receiving the study medication, infants were preoxygenated with 100% 02 and hand-ventilated with a self-inflatable bag for 1–2 minutes prior to intubation. Infants having their endotracheal tube replaced were ventilated through their existing tube until it was removed. Vital signs (HR, BP, Sp02) were captured to a laptop computer from the infant's monitor (PC Express, Spacelabs Inc., Redmond WA) every 5 seconds (except blood pressure which was obtained with a self inflating cuff every minute) using Procom Plus Communication Software, from the time the study medication was given (which was considered the baseline) to 5 minutes after the infant's vital signs returned to pre-procedure values. One of three investigators, not involved in the procedure collected the following data manually: duration of the procedure (defined as the time between insertion of the laryngoscope in the mouth to confirmation of endotracheal tube placement by auscultation) and the number of intubation attempts (defined as number of times the laryngoscope was inserted in the mouth). If there was more than one attempt, the clock continued between attempts and was stopped only when tube placement was confirmed by auscultation. In our NICU, the preferred method of intubation is via the nasotracheal route if mechanical ventilation is expected for more than a few hours.
All team members performed the intubations: staff neonatologists a, neonatal fellows b, pediatric residents c, clinical nurse specialists d, clinical nurse specialist students e and transport nurses f. After 2 unsuccessful attempts by a junior team member (c,d,e,f), a more experienced intubator (a,b) was called.
Institutional ethics committee approval and informed consent from the parents were obtained for this study.
Outcome measures
The study aimed to test the hypothesis that morphine 0.2 mg/kg would decrease fluctuations in vital signs, shorten the duration of the procedure and reduce the number of attempts. The primary outcome was the duration of severe hypoxemia, defined as Sp02 < 85% with a HR< 90/min. This was felt to be the most undesirable side effect of endotracheal intubation as cerebral blood flow in neonates is highly dependent upon heart rate. Secondary outcomes included: (1) duration of the procedure, (2) duration of hypoxemia (Sp02 < 85%), (3) number of attempts, (4) maximum change in blood pressure from baseline, (5) occurrence of bradycardia (HR<90/min).
Sample size
The study group's impression was that a majority of infants experience some degree of severe hypoxemia during an elective intubation, which was clinically undesirable. It was estimated to be 30 seconds, based on experience. In order to detect a one standard deviation difference in duration of severe hypoxemia between the 2 groups (α = 0.05, 2-sided, β = 0.2), 17 patients per group were required.
Statistical analysis
Because the distribution of the main outcome was skewed and groups were small, continuous variables were compared using the Mann-Whitney U test. Dichotomous variables were compared using Fisher's exact test or Chi-square test. A p value < 0.05 (2-sided) was considered significant for the primary outcome; p < 0.01 was considered significant for secondary outcomes to account for multiple analyses in a small sample. Level of experience of the intubator, birth weight and gestational age were separately explored as potential confounders of the primary outcome using ANOVA or linear regression.
Results
Patients were recruited from December 1999 to September 2000. Patient flow in the study is depicted in figure 1. Two hundred and fifteen infants were identified as potential candidates for the study. Ninety-nine of them never required an elective intubation but 35 did, they were missed, as parents or investigators were not available at the time. Eighty-one families were approached for consent. Consent was obtained for 64 infants of whom 34 were enrolled and randomized. Thirty were not randomized: 13 never required an intubation and 17 elective intubations were missed, mainly because they happened at night, when investigators were not on site. Missed patients had similar gestation, birth weight and reason for intubation as those enrolled. All patients randomized received the intervention and data from all randomized patients were analyzed. Physiological stability was maintained in all infants, between the time the study drug was given, to the time the endotracheal intubation was performed.
Figure 1 Flow of patients at each stage of the study
Baseline characteristics are presented in Table 1. Both groups had similar birth weight, gestation, and baseline vital signs. Importantly, the number of primary intubations/failed extubation and changes of endotracheal tube (which is usually considered easier) were similar between groups. All intubations were nasotracheal. Results of the primary and secondary outcomes analysis are presented in Table 2. Only 8/17 infants in the treatment group and 7/17 in the control group experienced some degree of severe hypoxemia. The median duration of severe hypoxemia was similar between groups. An outlier (severe hypoxemia lasting for 300 seconds) was identified in the treatment group. Considering the small number of patients, this outlier was taken out and the data reanalyzed, but this did not change the results significantly. The level of experience of the intubator, birth weight and gestation were entered separately in a regression model, but none was a significant contributor to the variance of the results.
Table 1 Baseline characteristics of included patients *Values expressed as medians (interquartile range)
Morphine group n = 17 Control group n = 17
Birth weight, grams* 1065 (731.5, 2043) 904 (689, 1535.5)
Gestation, weeks* 28 (26, 33) 27 (26, 30)
Gender male/female, n 11/6 9/8
Age at randomization, days* 3 (0.61, 16) 8 (0.63, 13)
Primary intubation/failed extubation, n 7 7
Change of endotracheal tube, n 10 10
Baseline HR, bpm* 152 (142.5, 157.5) 161 (151.5, 166.5)
Baseline Sp02, %* 94 (92.5, 95) 94 (92.5, 98)
Baseline BP, mm Hg* 38.5 (35.25, 44.75) 37.5 (33.25, 44.5)
Baseline fi02, %* 40 (27, 45) 32 (25, 41.25)
Experienced intubator, n 9 7
Junior intubator, n 8 10
Table 2 Primary and secondary outcomes results *Values expressed as medians and interquartile range
Morphine group Control group p value
Duration of severe hypoxemia, seconds* 10 (0, 62.5) 5 (0, 45) 0.45
Duration of hypoxemia, seconds* 235 (82.5, 340) 90 (20, 187.5) 0.04
Duration of procedure, seconds* 271 (57.5, 418.5) 94 (62, 215.5) 0.27
Maximum increase in mean BP from baseline, mm Hg* 18 (9, 24.25) 20 (11.75, 28) 0.65
Number of attempts, n* 2 (1, 3.5) 1 (1, 2.5) 0.34
Intubation achieved at first attempt, n 7 9 0.49
Intubation needing rescue intubator, n 7 4 0.27
Bradycardia during procedure, n 16 12 0.175
All patients in the treatment group and 14/17 in the control group experienced hypoxemia (Sp02 < 85%) during intubation. The median duration of hypoxemia was 235 sec in the treatment group and 90 sec in the control group (p = 0.04). Because of our small sample and the likelihood of finding a significant result by chance alone when assessing multiple outcomes, it was decided a priori that a p value of 0.01 would be considered significant for secondary outcomes. Nevertheless, this represents an interesting but somewhat worrisome trend. No difference was found in the maximal increase in blood pressure. Ninety-four percent of patients experienced bradycardia (HR<90/min) during the procedure with no difference between groups.
The median duration of the procedure was 271 sec in the treatment group and 94 sec in the control, which was not statistically significant. Roughly half of the infants required more than one attempt to achieve successful intubation and the clock was not stopped between attempts. Number of attempts in the treatment group (median 2), was similar to controls (median 1); total number of attempts was 38 in the premedicated infants versus 31 in the controls. Success rate at first attempt or need to call a more senior intubator after 2 failed attempts did not differ between groups. Because of the higher than usual dose of morphine that was used, we monitored the need to increase ventilator support over the next 24 h, in infants having their tubes changed, but found no difference between groups.
Discussion
Newborn infants, especially premature ones have adverse physiological responses to routine care procedures [2,4]. Endotracheal intubation is a stressful procedure, associated with physiologic instability [9-14]. Our data also show this instability, with 94% of infants experiencing bradycardia and the mean blood pressure increasing by as much as 46%.
Our hypothesis was that a moderate dose of morphine would facilitate intubation and stabilize vital signs better than placebo. Our data does not support this hypothesis. No significant difference was identified between the treatment and the control group in any prespecified outcome. The choice of severe hypoxemia as the primary outcome, although clinically very important, significantly limited the number of observations and increased the possibility of a type 2 error, as few infants met the criteria defining this outcome. The onset of action of morphine is about 5 minutes in infants, but the peak action occurs only at 15 to 30 minutes [16], perhaps too long for a procedure such as an intubation, as it does not lead to sufficient relaxation to permit adequate airway visualization. Although there was no formal assessment of the level of sedation of our infants done, bedside nurses reported not being able to discriminate between groups 5 minutes after injection of the study drug.
The only trend we identified was the duration of hypoxemia, which appeared longer in the treatment group. Most desaturations were in the mid 70's to low 80's range, but this is still a worrisome finding. We were unable to identify if birth weight, gestation or experience level of the intubator were significant contributors. Our sample size likely did not permit to identify such a contributor. Although morphine may not be potent enough to significantly relax infants to permit quicker and easier intubations, it may lead to decreased functional residual capacity in partially sedated infants, which could account for prolonged desaturations. The hypoxemia could have been compounded by the use of self-inflating bag and masks, which cannot provide a positive end-expiratory pressure (PEEP). Also, the larger dose of morphine used in this study could have contributed to this potential problem, by further decreasing the FRC in partially sedated infants. This trend is in keeping with the finding that, although not statistically significant, median duration of the procedure was 3 times as long in the treatment group as in the controls.
Ninety four percent of infants experienced bradycardia, mostly vagal, during their intubation. As cerebral blood flow in infants is greatly dependent on heart rate, our data adds to the current knowledge that including atropine in the premedication appears warranted. Although there may be concern that atropine could mask hypoxia-induced bradycardia, the now universal use of oxygen saturation monitors should ensure that hypoxemia is identified.
Previous trials have used various combinations of drugs for premedication and overall, they suggest that premedication is effective and safe. Kelly [9] and Barrington [10], using atropine and a muscle relaxant, demonstrated a reduction in vagal bradycardia and a dampening in the rise in intracranial pressure. The use of a muscle relaxant without an analgesic would now be considered unacceptable practice. Friesen [12] compared atropine alone to atropine and a non-standardized anesthetic and pancuronium in stable term infants preoperatively. The treatment group had less increase in intracranial pressure. This study included only stable infants. Pokela [11] compared 10 infants randomly allocated to glycopyrrolate and pethidine to 10 infants who received glycopyrrolate, alfentanil and suxamethonium. The addition of a muscle relaxant decreased both the duration of hypoxemia and the duration of the procedure by half. Only experienced physicians performed the intubations, which limits generalizability. The durations of procedure and hypoxemia in our morphine group were similar to their pethidine group. Buthada [13] compared thiopenthal in anesthetic doses to placebo in infants over 2 kg. Intubations were shorter and heart rate and blood pressure were more stable in the treatment group. Oei [14] compared morphine, atropine and suxamethonium to awake intubations in 20 infants. Interestingly, even when residents with little or no neonatal experience performed the intubation, the duration of the procedure was significantly shorter and the number of attempts halved in the premedicated group. Barrington [17] used atropine, fentanyl and succinylcholine in 269 consecutive intubations and reported no major complication; no data was available on duration of procedure or vital signs stability. Few very small infants were enrolled in these trials and most used a combination of premedication, which makes comparison with our trial difficult.
Our study has several limitations. First, our sample size is relatively small, which precludes us from eliminating a type 2 error. We began this project with the assumption that severe hypoxemia would occur for about 30 seconds, which was not the case. An observational study would have been useful before making this assumption. Although limited in size, results of this trial should be useful for future investigators and clinicians in their choice of premedication. Second, due to limited resources (unfunded trial), as this study was planned as a pilot, to assess feasibility and adequacy of equipment to obtain data, we decided not to stratify for gestational age. This could have been very useful in refining the findings, as more immature infants may respond differently to premedication in general and have less strength to struggle during an unpremedicated or not sufficiently premedicated painful procedure. Third, as we wanted to mimic our actual NICU practices, in view of modifying such practices, we did not restrict the study intubations to very experienced operators. As a result, there was substantial variability in the level of experience between individuals. Given our small number of patients, this might have impacted on the outcomes. Fourth, several eligible infants were not enrolled. This was due to unavailability of either trial investigators or parents, as many intubations occurred at night. The infants enrolled and those not enrolled had similar birth weights, gestation and reason for intubation, which is reassuring, but does not eliminate the potential for enrolment bias.
Conclusions
Infants are entitled to effective pain management strategies [18]. It seems only humane to premedicate infants when possible, for known stressful and painful procedures, as we would for older children and adults. Overall, our findings suggest that morphine probably is not the analgesic of choice or insufficient on its own for elective endotracheal intubations. A more rapid onset analgesic like remifentanil, along with atropine should be evaluated and the role of muscle relaxants needs to be better defined. Infants should be stratified either by gestational age or birth weight, to capture differences in their response to premedication and to intubation. Objective measures of pain like the Premature Infant Pain Profile (PIPP) score [19] and/or endocrine indicators of stress should be included in outcomes, which should remain focused primarily on the short-term comfort of the infants but also their safety. Long-term physiologic and clinical outcomes should be incorporated into the trial design. Consideration should be given to including various levels of experience of intubators to increase generalizability and applicability of the findings to units where residents and other allied health professionals are trained to intubated infants.
Abbreviations
HR heart rate, BP blood pressure, Sp02 oxygen saturation, ETT endotracheal tube, IVH intraventricular hemorrhage, PVL periventricular leukomalacia, NICU Neonatal Intensive Care Unit, PEEP positive end-expiratory pressure
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
BL led the study design and manuscript preparation and contributed to data collection. MM contributed to the study design and manuscript preparation. JD contributed to the study design, manuscript preparation and data collection. AK contributed to data gathering and manuscript editing. SG prepared the study medication and contributed her pharmaceutical expertise to the choice of medication dose for the study. All authors read and approved the final manuscript.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgments
The authors would like to thank the Chalmers Research Group, Children's Hospital of Eastern Ontario Research Institute for peer review of this manuscript and statistical analysis of the data.
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| 15461825 | PMC524358 | CC BY | 2021-01-04 16:31:00 | no | BMC Pediatr. 2004 Oct 5; 4:20 | utf-8 | BMC Pediatr | 2,004 | 10.1186/1471-2431-4-20 | oa_comm |
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BMC Med EthicsBMC Medical Ethics1472-6939BioMed Central London 1472-6939-5-510.1186/1472-6939-5-5Research ArticleUnder-representation of developing countries in the research literature: ethical issues arising from a survey of five leading medical journals Sumathipala Athula 14spjuats@iop.kcl.ac.ukSiribaddana Sisira 24nipuna@stmail.lkPatel Vikram 3vikram.patel@lshtm.ac.uk1 Section of Epidemiology, Institute of Psychiatry, Kings College, London SE5 8AF UK2 Sri Jayewardenepura Postgraduate Teaching Hospital, Thalapathpitiya, Nugegoda, 10250, Sri Lanka3 London School of Hygiene & Tropical Medicine, London, UK4 Forum for Research and Development in Sri Lanka2004 4 10 2004 5 5 5 22 4 2004 4 10 2004 Copyright © 2004 Sumathipala et al; licensee BioMed Central Ltd.2004Sumathipala 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 is widely acknowledged that there is a global divide on health care and health research known as the 10/90 divide.
Methods
A retrospective survey of articles published in the BMJ, Lancet, NEJM, Annals of Internal Medicine & JAMA in a calendar year to examine the contribution of the developing world to medical literature. We categorized countries into four regions: UK, USA, Other Euro-American countries (OEAC) and (RoW). OEAC were European countries other than the UK but including Australia, New Zealand and Canada. RoW comprised all other countries.
Results
The average contribution of the RoW to the research literature in the five journals was 6.5%. In the two British journals 7.6% of the articles were from the RoW; in the three American journals 4.8% of articles were from RoW. The highest proportion of papers from the RoW was in the Lancet (12%). An analysis of the authorship of 151 articles from RoW showed that 104 (68.9%) involved authorship with developed countries in Europe or North America. There were 15 original papers in these journals with data from RoW but without any authors from RoW.
Conclusions
There is a marked under-representation of countries in high-impact general medical journals. The ethical implications of this inequity and ways of reducing it are discussed.
==== Body
Background
National and international bodies concerned with research ethics need to confront the greatest ethical challenge-the enormous inequities in global health research [1]. Thus, less than 10% of the world's research resources are earmarked for 90% of the health problems [2]. Though 93% of the world's burden of preventable mortality occurs in developing countries, too little research funding is targeted to health problems in those countries [3]. This divide in research funding is mirrored by concerns regarding a divide in the proportion of publications arising from medical research in developing countries. A recent survey of six leading psychiatric journals revealed that only 6% of the articles originated from, or described data arising from, regions of the world that accounted for over 90% of the global population [4]. Following this paper, the issue of under-representation of developing countries was debated and discussed in many journals and by journal editors [5-7].
The aim of this study is to investigate the publication bias beyond the field of psychiatry to determine the overall contribution of different regions of the world to the medical literature published in high-impact journals and, in particular, to quantify the developing world's contribution.
Methods
The method used is the same as that which was used by two of the authors (AS and VP) in a recent survey of the international representation in the psychiatric literature [4]. A retrospective survey was conducted of all issues in one calendar year (the most recent, complete set available in the medical library in Colombo where data collection took place) of the following journals: BMJ, Lancet, NEJM, Annals of Internal Medicine & JAMA. These journals were selected because they have the highest impact amongst general medical journals [8]. These journals lay claim to their global legitimacy for many reasons: frequent publication, high impact, long history, credibility of the publisher, large numbers of full time editorial staff, membership of the International Committee of Medical Journal Editors, and influential joint statements [9]. The year for which data was collected was 2000 for all journals, except JAMA for which it was 1999 (all issues in year 2000 were not available). All articles, excluding the specified ones in each journal were reviewed. In the BMJ we excluded obituaries, multi-media, personal views, Minerva, news and soundings. In the Lancet we excluded Dissecting Room and news. In the Annals, we excluded on Being a doctor, Current clinical issues, Medical writings, Book notes, Ad Libitum and persona. In the NEJM, we excluded book reviews, This week in the journal and Abstracts. In JAMA, we excluded Medical news and Perspectives, Peace of my mind, JAMA hundred years ago, Abstracts, FDA, CDC, poetry and medicines, Books journals, New media, World in medicine and the section titled "from the JAMA websites". In the Lancet, editorials and commentaries were pooled together, because the commentaries in the Lancet resemble editorials in the other journals in terms of their contents. None of the other four journals had commentaries section.
For the allocation of regions of the world, we categorized countries into four regions: UK, USA, OEAC (Other Euro-American countries) and RoW (Rest of the World). OEAC were European countries other than the UK but including Australia, New Zealand and Canada. RoW comprised all other countries including Eastern Europe, Central and South America, Asia and Africa. We scrutinized each article to examine the country of the authors' affiliation address with a view to categorizing them into relevant regions of the world. All authors were noted including multiple authors in large multi-center studies. We also scrutinized the methods section of all the original articles to ascertain the origin of data with special emphasis on whether the research was carried out in RoW countries. The affiliation of the first, last and corresponding authors was also noted. We worked with a negative bias against the USA and the UK from where the journals originated. Therefore articles, which included authors from the RoW, were considered as arising from the RoW even if the first author is from the UK, USA or OEAC. Similarly, articles from the OEAC, which involved collaborations from the UK or USA, were included in the OEAC category. In the event of a collaborative study between the USA and the UK, the allocation to region was based on the institutional affiliation of the first author. The RoW category included collaborative studies between any country in the RoW and developed nations.
In some cases the origin of the author was difficult, particularly when there were two places named as their attached institutions. For an example when one was in USA while the other is in Kenya. We used our best guess in these instances. For an example the two authors AS and VP in this paper were based in RoW at the time we did this research but were employed in UK but with strong affiliations to the RoW countries where they were born and did their research. Attempts to analyse the nationality of the authors was therefore abandoned.
Results
The contribution of the RoW to the research literature surveyed in these five high-impact journals was 6.5%. In the two British journals, 7.6% of the articles were from the RoW, whilst the proportion in the three American journals was 4.8%. This averages hides the fact that there is considerable variation between journals; thus, around 3.5% of articles in the two journals of national medical associations of the UK (BMJ) and USA (JAMA) were from the RoW as compared to 12% in the Lancet articles (Table 1). Indeed, more than half the articles from the RoW were published in just one journal, the Lancet (Table 2).
Table 1 The contribution of regions to the research literature in five leading journals
BMJ Lancet NEJM JAMA ANNALS Total
Editorials 261 3504 124 102 39 876
UK 160 61.4% 167 47.7% 10 8.0% 02 1.9% 01 2.4% 340 38.8%
USA 38 14.6% 87 24.9% 97 78.3% 97 95.0% 35 90.0% 354 40.4%
OEAC1 56 21.4% 89 25.4% 14 11.3% 02 1.9% 03 7.6% 164 18.7%
RoW2 07 2.6% 07 2.0 % 03 2.4% 01 0.9% 00 0.0% 18 2.6%
Original papers 322 307 218 227 115 1189
UK 216 67.0% 66 21.5 % 06 2.7% 04 1.8% 03 2.6% 295 24.8%
USA 22 7.0% 38 12.4% 107 49.1% 173 76.2% 81 70.4% 421 35.4%
OEAC 76 23.6% 136 44.3 % 78 35.8% 42 18.5% 23 20.0% 355 29.9%
RoW 08 2.4% 67 21.8% 27 12.4% 08 3.5% 08 7.0% 118 9.9%
Correspondence 1118 10435 894 605 251 3911
UK 829 74% 374 35.8% 30 3.4% 13 2.1% 04 1.6% 1250 32%
USA 69 6% 141 13.5% 601 67.2% 506 83.6% 183 72.9% 1500 38.4%
OEAC 174 16% 400 38.3% 212 23.7% 71 11.7% 49 19.5% 906 23.2%
RoW 46 4% 128 12.2% 51 5.7% 15 2.5% 15 6.0% 255 6.5%
Review articles 286 50 65 36 66 503
UK 195 68.2% 17 34% 04 6.2% 01 2.7% 01 1.6% 218 43.3%
USA 29 10.2% 15 30% 48 73.8% 28 78.0% 61 92.4% 181 36%
OEAC 54 18.8% 14 28% 13 20.0% 04 11.1% 04 6.0% 89 17.7%
RoW 08 2.8% 04 08% 00 0.0% 03 8.2% 00 0.0% 15 3%
Others3 47 208 149 145 27 576
UK 31 66.0% 68 32.8% 03 02.0% 00 00.0% 00 00.0% 102 17.7%
USA 08 17.0% 34 16.3% 118 79.3% 120 82.7% 25 92.6% 305 53%
OEAC 04 8.5% 78 37.5% 22 14.7 % 16 11.0% 01 3.7% 121 21%
RoW 04 8.5% 28 13.4% 06 4.0% 09 6.2% 01 3.7% 48 8.3%
Global total 2034 1958 1450 1115 498 7055
RoW total 73 3.6% 234 12% 87 6% 36 3.2% 24 4.8% 454 6.4 %
1. OEAC (Other Euro-American countries), OEAC were European countries other than the UK, Australia, New Zealand and Canada.
2. RoW comprised all other countries (i.e. all countries in Eastern Europe, Central and South America, Asia and Africa)
3. Others include: for The Lancet: case reports, view points, public letters, essays, public health, violence in health, department of medical history, the world, world ideas, health and human rights, development of ethics, eponymous, clinical picture, reportage, adverse drug reactions, personal papers, medicine and law, personal papers; for the JAMA: Patients relationships, grand rounds, clinical cross roads, rational clinical examinations, medicine and media, commentary, updates, letters from counters, public opinion and health, medical literature, health law and ethics, clinical cross roads; for the NEJM: images, clinical problem solving, case records from Massachusetts general hospital, clinical implications of basic research, sounding board, clinical problem solving, special articles, for the BMJ: drug point, practice and results, quality of life, history, practice point, lessons of every week; for the Annals: past present and future, time and medicine, social means of medicine, technology of time, personal time, media and publication, NIH conference, in the balance, abroad.
4. The Lancet had 52 editorials and 298 commentaries. Editorials were written in house.
5. The Lancet had 262 research letters. We did not include these either in the correspondence or with the Original papers category. Other journals did not have such a category to compare.
Table 2 Proportion of articles contributed by different regions of the RoW category to the total number of editorials, original articles and reviews.
BMJ Lancet NEJM JAMA Annals Total1(%)
India 2 1 2 0 0 05 (3)
China 2 5 6 1 1 15 (10)
Other Asian 6 8 3 2 0 19 (12)
Sub Saharan Africa 8 25 2 1 0 36 (24)
Latin America 2 11 4 5 2 24 (16)
Middle East/North Africa 0 6 1 0 0 07 (5)
Japan 0 8 5 0 4 17 (11)
Israel 3 6 4 1 0 14 (9)
Multi national 0 8 3 2 1 15 (10)
Total2 (%) 23 (15) 78 (52) 30 (20) 12 (8) 8 (5) 151
1 The % figures in this column represent the contribution of the specific country or region to the RoW papers in the table
2 The % figures in this row represent the contribution of the specific journal to the total RoW papers in the table.
Note: This analysis only includes Original Articles, Editorials and Review Papers
Within journals, variations in regional contributions from other regions were also notable. Thus, the proportion of articles from the UK was highest in the two journals published in the UK (BMJ and Lancet) while the proportion of articles from the USA was highest in the three journals published in the USA. Table 2 shows the relative contribution of different regions of the RoW category to the total number of editorials, original articles and reviews. Two developed countries (Japan and Israel) contribute a fifth of the literature from RoW, while the two most populous countries in the world (India and China) contribute about 13% together. A detailed analysis of the authorship of the 151 RoW articles showed that 104 (68.9%) involved collaborative authorship with developed countries in Europe or North America; only 43 (31.1%) were entirely independent efforts from the RoW.
There were 118 original papers with at least one author from the RoW. Forty-five (38%) of them had a first author from the RoW; 32 (27%) had a last author from the RoW; and 36 (30%) had a corresponding author from the RoW. Only 25 (21%) of them had first, last and corresponding authors all from the RoW. There were 15 original papers in these journals with data from the RoW but without any authors from the RoW; of these 15, nine were in Lancet, four in BMJ and one each in JAMA and NEJM. Thus, the majority of the original articles originating from the RoW had contribution from the developed world authors.
Discussion
This study presents findings of a survey of articles published in five high-impact general medical journals with the objective of describing the developing world's contribution to research literature over a single calendar year.
Our way of classifying countries into developed (UK, USA, OEAC) and developing countries (RoW) has obvious inadequacies but we followed the same method adopted in an earlier paper [4]. Other euro-American countries (OEAC) shared many cultural and economic features. Rest of the world (RoW) included Eastern Europe, which although culturally related to Western Europe was not economically on the same level, and Japan, which was highly developed economically but did not share many cultural factors with OEAC.
The key finding of our survey is that, only 6.5% of the publications in these journals have authors from countries where 90% of the world's population lives. There is a severe under representation of biomedical research from a vast section of the world in these five journals. In addition, there are a small but significant number of articles with data from the developing world without a single author from these countries. This is a troublesome finding that some would refer as 'safari research'. It is a separate ethical issue and journal editors need to look at it carefully.
The reasons for under representation of researchers based in developing countries may include research barriers such as lack of funding, poor facilities, limited technical support and inadequate training. Many researchers from developing countries do not speak English as their first language. Fear of rejection by the journals, uncertainty about which journal would be best to publish research, a lack of the culture of publication, competing clinical commitments, different ministry and donor driven agendas for research, are some of the unseen barriers facing developing country researchers (10). The editors of leading medical journals may not have paid sufficient attention to these barriers, real and perceived, that clinical researcher in developing countries face [11].
We acknowledge that many developing country researchers choose to publish their work in national or regional journals that are not as high-impact as the journals we have reviewed. However, many researchers, irrespective of the country of their origin, also prefer to publish their work in journals with a high impact factor and circulation. This, inevitably, leads to a focus on leading journals published from the UK or USA. However, journals may be under some pressure to publish material, which is relevant to the majority of their readership. Thus, it is not surprising that journals from the UK have the majority of articles from UK institutions and similarly, journals from the USA tend to have most of their articles from US institutions. The BMJ admits that although the BMJ aspires to be more international, they cannot forget that they reach 80% doctors in Britain [12]. However all these journals are financially highly successful in global markets. Their international success brings responsibilities to the global community they serve and profits from [11].
Our findings are in agreement with other published findings in this area [13]. In a study of randomised controlled trials published in leading medical journals many of the diseases afflicting the south are understudied [14]. Even in the field of tropical medicine there were few contributions originating from countries with a low human development index (HDI) [15]. Another study, where the number of biomedical articles were normalized to the number of publications per million population, also shows an under representation of Asia, Africa and South America. The authors demonstrated that the number of biomedical publications increase according to the economic ranking of the country [16]. The same authors have shown in a similar study that publications per million population are more closely related to gross national product (GNP) and research and development expenditure [17]. The inescapable conclusion of this research is that USA, UK and other European countries dominate biomedical research, in part because of their wealth and investment in research. Irrespective of the method used to categorize countries in developing world, (by GNP, HDI or any other method), generation of new knowledge in biomedical research in these nations is insufficient. In a recent Nature paper on science publications Japan occupies 4th place, Israel 15th, China 19th, and India 22nd in the rank order of nations based on their share of top 1% of highly cited publications. Unsurprisingly the USA and UK occupies the two top positions [18].
There are many reasons to strive for a more just international distribution of biomedical research in leading journals. The burden of disease in the world falls heavily on developing countries and the pattern of this burden is likely to change in the next twenty years. Diseases like TB, HIV, Malaria, Dengue, and viral hemorrhagic fevers are now no longer tropical with increase in international travel, global warming, refugees, economic and military intervention and conflicts. Newly emerging infections from tropics such as SARS and bird flu can have devastating effects far away from tropics. In addition, diseases such as diabetes and obesity can no longer be considered as diseases in the developed world. As the impact and burden of these diseases are more in developing countries more research publications are needed from South.
Clinicians and policy makers in many developing countries have limited access to international journals because medical libraries often need to make a choice from a number of journals due to financial constraints. Often, it is the high-impact journal, which is subscribed to. Thus, the proportion of international representation in these leading journals may be a crucial factor in influencing health policies in many countries. The importance of research goes well beyond its impact on health policies [11]. Thus, research on the epidemiology and management of diseases in different health systems raises the probability of identifying risk factors for diseases and identifying innovative approaches to their management. This fact was well reflected in the multi-center eclampsia trial [19]. Until this trial was carried out in Africa, South America and India, the subject of using magnesium sulfate in the management of eclampsia was controversial. The other good example is the only meningitis B vaccine in the world, which was developed by the Carlos J. Finlay Institute in Cuba and now saves lives all over the world [20].
Providing free journals electronically to the developing countries is a commendable step in correcting the thirst for new information [21]. However the one-way flow of information by making journals electronically free to developing world is unlikely to be sufficient [22]. By providing journals free to 'RoW', and propagating research which has been conducted in countries where only 10% of the disease burden is experienced is itself a moral and ethical issue.
Ultimately, we believe that strengthening the health research capacity in developing world and providing reasonable opportunities for publications arising from the developing world are critical, not only for achieving biomedical research publication equity, but also advancing medical science.
Competing interests
We would like to state here that our conflict of interest if at all would be due to the fact that we come from the developing world.
Authors' contributions
All authors were involved in all the components of this paper, right from the start, in formulating and developing the idea, collecting the data, drafting the first version and revising it and approving the final version.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Ms Lakshmi Abeygoonawardane for her assistance in data collection and analysis. Dr Suwin Hewage for recollection and reanalysis of the data. We also would like to thank Dr Jennifer Keiser who reviewed our paper for BMC Medical Ethics.
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| 15461820 | PMC524359 | CC BY | 2021-01-04 16:31:54 | no | BMC Med Ethics. 2004 Oct 4; 5:5 | utf-8 | BMC Med Ethics | 2,004 | 10.1186/1472-6939-5-5 | oa_comm |
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BMC Med EthicsBMC Medical Ethics1472-6939BioMed Central London 1472-6939-5-510.1186/1472-6939-5-5Research ArticleUnder-representation of developing countries in the research literature: ethical issues arising from a survey of five leading medical journals Sumathipala Athula 14spjuats@iop.kcl.ac.ukSiribaddana Sisira 24nipuna@stmail.lkPatel Vikram 3vikram.patel@lshtm.ac.uk1 Section of Epidemiology, Institute of Psychiatry, Kings College, London SE5 8AF UK2 Sri Jayewardenepura Postgraduate Teaching Hospital, Thalapathpitiya, Nugegoda, 10250, Sri Lanka3 London School of Hygiene & Tropical Medicine, London, UK4 Forum for Research and Development in Sri Lanka2004 4 10 2004 5 5 5 22 4 2004 4 10 2004 Copyright © 2004 Sumathipala et al; licensee BioMed Central Ltd.2004Sumathipala 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 is widely acknowledged that there is a global divide on health care and health research known as the 10/90 divide.
Methods
A retrospective survey of articles published in the BMJ, Lancet, NEJM, Annals of Internal Medicine & JAMA in a calendar year to examine the contribution of the developing world to medical literature. We categorized countries into four regions: UK, USA, Other Euro-American countries (OEAC) and (RoW). OEAC were European countries other than the UK but including Australia, New Zealand and Canada. RoW comprised all other countries.
Results
The average contribution of the RoW to the research literature in the five journals was 6.5%. In the two British journals 7.6% of the articles were from the RoW; in the three American journals 4.8% of articles were from RoW. The highest proportion of papers from the RoW was in the Lancet (12%). An analysis of the authorship of 151 articles from RoW showed that 104 (68.9%) involved authorship with developed countries in Europe or North America. There were 15 original papers in these journals with data from RoW but without any authors from RoW.
Conclusions
There is a marked under-representation of countries in high-impact general medical journals. The ethical implications of this inequity and ways of reducing it are discussed.
==== Body
Background
National and international bodies concerned with research ethics need to confront the greatest ethical challenge-the enormous inequities in global health research [1]. Thus, less than 10% of the world's research resources are earmarked for 90% of the health problems [2]. Though 93% of the world's burden of preventable mortality occurs in developing countries, too little research funding is targeted to health problems in those countries [3]. This divide in research funding is mirrored by concerns regarding a divide in the proportion of publications arising from medical research in developing countries. A recent survey of six leading psychiatric journals revealed that only 6% of the articles originated from, or described data arising from, regions of the world that accounted for over 90% of the global population [4]. Following this paper, the issue of under-representation of developing countries was debated and discussed in many journals and by journal editors [5-7].
The aim of this study is to investigate the publication bias beyond the field of psychiatry to determine the overall contribution of different regions of the world to the medical literature published in high-impact journals and, in particular, to quantify the developing world's contribution.
Methods
The method used is the same as that which was used by two of the authors (AS and VP) in a recent survey of the international representation in the psychiatric literature [4]. A retrospective survey was conducted of all issues in one calendar year (the most recent, complete set available in the medical library in Colombo where data collection took place) of the following journals: BMJ, Lancet, NEJM, Annals of Internal Medicine & JAMA. These journals were selected because they have the highest impact amongst general medical journals [8]. These journals lay claim to their global legitimacy for many reasons: frequent publication, high impact, long history, credibility of the publisher, large numbers of full time editorial staff, membership of the International Committee of Medical Journal Editors, and influential joint statements [9]. The year for which data was collected was 2000 for all journals, except JAMA for which it was 1999 (all issues in year 2000 were not available). All articles, excluding the specified ones in each journal were reviewed. In the BMJ we excluded obituaries, multi-media, personal views, Minerva, news and soundings. In the Lancet we excluded Dissecting Room and news. In the Annals, we excluded on Being a doctor, Current clinical issues, Medical writings, Book notes, Ad Libitum and persona. In the NEJM, we excluded book reviews, This week in the journal and Abstracts. In JAMA, we excluded Medical news and Perspectives, Peace of my mind, JAMA hundred years ago, Abstracts, FDA, CDC, poetry and medicines, Books journals, New media, World in medicine and the section titled "from the JAMA websites". In the Lancet, editorials and commentaries were pooled together, because the commentaries in the Lancet resemble editorials in the other journals in terms of their contents. None of the other four journals had commentaries section.
For the allocation of regions of the world, we categorized countries into four regions: UK, USA, OEAC (Other Euro-American countries) and RoW (Rest of the World). OEAC were European countries other than the UK but including Australia, New Zealand and Canada. RoW comprised all other countries including Eastern Europe, Central and South America, Asia and Africa. We scrutinized each article to examine the country of the authors' affiliation address with a view to categorizing them into relevant regions of the world. All authors were noted including multiple authors in large multi-center studies. We also scrutinized the methods section of all the original articles to ascertain the origin of data with special emphasis on whether the research was carried out in RoW countries. The affiliation of the first, last and corresponding authors was also noted. We worked with a negative bias against the USA and the UK from where the journals originated. Therefore articles, which included authors from the RoW, were considered as arising from the RoW even if the first author is from the UK, USA or OEAC. Similarly, articles from the OEAC, which involved collaborations from the UK or USA, were included in the OEAC category. In the event of a collaborative study between the USA and the UK, the allocation to region was based on the institutional affiliation of the first author. The RoW category included collaborative studies between any country in the RoW and developed nations.
In some cases the origin of the author was difficult, particularly when there were two places named as their attached institutions. For an example when one was in USA while the other is in Kenya. We used our best guess in these instances. For an example the two authors AS and VP in this paper were based in RoW at the time we did this research but were employed in UK but with strong affiliations to the RoW countries where they were born and did their research. Attempts to analyse the nationality of the authors was therefore abandoned.
Results
The contribution of the RoW to the research literature surveyed in these five high-impact journals was 6.5%. In the two British journals, 7.6% of the articles were from the RoW, whilst the proportion in the three American journals was 4.8%. This averages hides the fact that there is considerable variation between journals; thus, around 3.5% of articles in the two journals of national medical associations of the UK (BMJ) and USA (JAMA) were from the RoW as compared to 12% in the Lancet articles (Table 1). Indeed, more than half the articles from the RoW were published in just one journal, the Lancet (Table 2).
Table 1 The contribution of regions to the research literature in five leading journals
BMJ Lancet NEJM JAMA ANNALS Total
Editorials 261 3504 124 102 39 876
UK 160 61.4% 167 47.7% 10 8.0% 02 1.9% 01 2.4% 340 38.8%
USA 38 14.6% 87 24.9% 97 78.3% 97 95.0% 35 90.0% 354 40.4%
OEAC1 56 21.4% 89 25.4% 14 11.3% 02 1.9% 03 7.6% 164 18.7%
RoW2 07 2.6% 07 2.0 % 03 2.4% 01 0.9% 00 0.0% 18 2.6%
Original papers 322 307 218 227 115 1189
UK 216 67.0% 66 21.5 % 06 2.7% 04 1.8% 03 2.6% 295 24.8%
USA 22 7.0% 38 12.4% 107 49.1% 173 76.2% 81 70.4% 421 35.4%
OEAC 76 23.6% 136 44.3 % 78 35.8% 42 18.5% 23 20.0% 355 29.9%
RoW 08 2.4% 67 21.8% 27 12.4% 08 3.5% 08 7.0% 118 9.9%
Correspondence 1118 10435 894 605 251 3911
UK 829 74% 374 35.8% 30 3.4% 13 2.1% 04 1.6% 1250 32%
USA 69 6% 141 13.5% 601 67.2% 506 83.6% 183 72.9% 1500 38.4%
OEAC 174 16% 400 38.3% 212 23.7% 71 11.7% 49 19.5% 906 23.2%
RoW 46 4% 128 12.2% 51 5.7% 15 2.5% 15 6.0% 255 6.5%
Review articles 286 50 65 36 66 503
UK 195 68.2% 17 34% 04 6.2% 01 2.7% 01 1.6% 218 43.3%
USA 29 10.2% 15 30% 48 73.8% 28 78.0% 61 92.4% 181 36%
OEAC 54 18.8% 14 28% 13 20.0% 04 11.1% 04 6.0% 89 17.7%
RoW 08 2.8% 04 08% 00 0.0% 03 8.2% 00 0.0% 15 3%
Others3 47 208 149 145 27 576
UK 31 66.0% 68 32.8% 03 02.0% 00 00.0% 00 00.0% 102 17.7%
USA 08 17.0% 34 16.3% 118 79.3% 120 82.7% 25 92.6% 305 53%
OEAC 04 8.5% 78 37.5% 22 14.7 % 16 11.0% 01 3.7% 121 21%
RoW 04 8.5% 28 13.4% 06 4.0% 09 6.2% 01 3.7% 48 8.3%
Global total 2034 1958 1450 1115 498 7055
RoW total 73 3.6% 234 12% 87 6% 36 3.2% 24 4.8% 454 6.4 %
1. OEAC (Other Euro-American countries), OEAC were European countries other than the UK, Australia, New Zealand and Canada.
2. RoW comprised all other countries (i.e. all countries in Eastern Europe, Central and South America, Asia and Africa)
3. Others include: for The Lancet: case reports, view points, public letters, essays, public health, violence in health, department of medical history, the world, world ideas, health and human rights, development of ethics, eponymous, clinical picture, reportage, adverse drug reactions, personal papers, medicine and law, personal papers; for the JAMA: Patients relationships, grand rounds, clinical cross roads, rational clinical examinations, medicine and media, commentary, updates, letters from counters, public opinion and health, medical literature, health law and ethics, clinical cross roads; for the NEJM: images, clinical problem solving, case records from Massachusetts general hospital, clinical implications of basic research, sounding board, clinical problem solving, special articles, for the BMJ: drug point, practice and results, quality of life, history, practice point, lessons of every week; for the Annals: past present and future, time and medicine, social means of medicine, technology of time, personal time, media and publication, NIH conference, in the balance, abroad.
4. The Lancet had 52 editorials and 298 commentaries. Editorials were written in house.
5. The Lancet had 262 research letters. We did not include these either in the correspondence or with the Original papers category. Other journals did not have such a category to compare.
Table 2 Proportion of articles contributed by different regions of the RoW category to the total number of editorials, original articles and reviews.
BMJ Lancet NEJM JAMA Annals Total1(%)
India 2 1 2 0 0 05 (3)
China 2 5 6 1 1 15 (10)
Other Asian 6 8 3 2 0 19 (12)
Sub Saharan Africa 8 25 2 1 0 36 (24)
Latin America 2 11 4 5 2 24 (16)
Middle East/North Africa 0 6 1 0 0 07 (5)
Japan 0 8 5 0 4 17 (11)
Israel 3 6 4 1 0 14 (9)
Multi national 0 8 3 2 1 15 (10)
Total2 (%) 23 (15) 78 (52) 30 (20) 12 (8) 8 (5) 151
1 The % figures in this column represent the contribution of the specific country or region to the RoW papers in the table
2 The % figures in this row represent the contribution of the specific journal to the total RoW papers in the table.
Note: This analysis only includes Original Articles, Editorials and Review Papers
Within journals, variations in regional contributions from other regions were also notable. Thus, the proportion of articles from the UK was highest in the two journals published in the UK (BMJ and Lancet) while the proportion of articles from the USA was highest in the three journals published in the USA. Table 2 shows the relative contribution of different regions of the RoW category to the total number of editorials, original articles and reviews. Two developed countries (Japan and Israel) contribute a fifth of the literature from RoW, while the two most populous countries in the world (India and China) contribute about 13% together. A detailed analysis of the authorship of the 151 RoW articles showed that 104 (68.9%) involved collaborative authorship with developed countries in Europe or North America; only 43 (31.1%) were entirely independent efforts from the RoW.
There were 118 original papers with at least one author from the RoW. Forty-five (38%) of them had a first author from the RoW; 32 (27%) had a last author from the RoW; and 36 (30%) had a corresponding author from the RoW. Only 25 (21%) of them had first, last and corresponding authors all from the RoW. There were 15 original papers in these journals with data from the RoW but without any authors from the RoW; of these 15, nine were in Lancet, four in BMJ and one each in JAMA and NEJM. Thus, the majority of the original articles originating from the RoW had contribution from the developed world authors.
Discussion
This study presents findings of a survey of articles published in five high-impact general medical journals with the objective of describing the developing world's contribution to research literature over a single calendar year.
Our way of classifying countries into developed (UK, USA, OEAC) and developing countries (RoW) has obvious inadequacies but we followed the same method adopted in an earlier paper [4]. Other euro-American countries (OEAC) shared many cultural and economic features. Rest of the world (RoW) included Eastern Europe, which although culturally related to Western Europe was not economically on the same level, and Japan, which was highly developed economically but did not share many cultural factors with OEAC.
The key finding of our survey is that, only 6.5% of the publications in these journals have authors from countries where 90% of the world's population lives. There is a severe under representation of biomedical research from a vast section of the world in these five journals. In addition, there are a small but significant number of articles with data from the developing world without a single author from these countries. This is a troublesome finding that some would refer as 'safari research'. It is a separate ethical issue and journal editors need to look at it carefully.
The reasons for under representation of researchers based in developing countries may include research barriers such as lack of funding, poor facilities, limited technical support and inadequate training. Many researchers from developing countries do not speak English as their first language. Fear of rejection by the journals, uncertainty about which journal would be best to publish research, a lack of the culture of publication, competing clinical commitments, different ministry and donor driven agendas for research, are some of the unseen barriers facing developing country researchers (10). The editors of leading medical journals may not have paid sufficient attention to these barriers, real and perceived, that clinical researcher in developing countries face [11].
We acknowledge that many developing country researchers choose to publish their work in national or regional journals that are not as high-impact as the journals we have reviewed. However, many researchers, irrespective of the country of their origin, also prefer to publish their work in journals with a high impact factor and circulation. This, inevitably, leads to a focus on leading journals published from the UK or USA. However, journals may be under some pressure to publish material, which is relevant to the majority of their readership. Thus, it is not surprising that journals from the UK have the majority of articles from UK institutions and similarly, journals from the USA tend to have most of their articles from US institutions. The BMJ admits that although the BMJ aspires to be more international, they cannot forget that they reach 80% doctors in Britain [12]. However all these journals are financially highly successful in global markets. Their international success brings responsibilities to the global community they serve and profits from [11].
Our findings are in agreement with other published findings in this area [13]. In a study of randomised controlled trials published in leading medical journals many of the diseases afflicting the south are understudied [14]. Even in the field of tropical medicine there were few contributions originating from countries with a low human development index (HDI) [15]. Another study, where the number of biomedical articles were normalized to the number of publications per million population, also shows an under representation of Asia, Africa and South America. The authors demonstrated that the number of biomedical publications increase according to the economic ranking of the country [16]. The same authors have shown in a similar study that publications per million population are more closely related to gross national product (GNP) and research and development expenditure [17]. The inescapable conclusion of this research is that USA, UK and other European countries dominate biomedical research, in part because of their wealth and investment in research. Irrespective of the method used to categorize countries in developing world, (by GNP, HDI or any other method), generation of new knowledge in biomedical research in these nations is insufficient. In a recent Nature paper on science publications Japan occupies 4th place, Israel 15th, China 19th, and India 22nd in the rank order of nations based on their share of top 1% of highly cited publications. Unsurprisingly the USA and UK occupies the two top positions [18].
There are many reasons to strive for a more just international distribution of biomedical research in leading journals. The burden of disease in the world falls heavily on developing countries and the pattern of this burden is likely to change in the next twenty years. Diseases like TB, HIV, Malaria, Dengue, and viral hemorrhagic fevers are now no longer tropical with increase in international travel, global warming, refugees, economic and military intervention and conflicts. Newly emerging infections from tropics such as SARS and bird flu can have devastating effects far away from tropics. In addition, diseases such as diabetes and obesity can no longer be considered as diseases in the developed world. As the impact and burden of these diseases are more in developing countries more research publications are needed from South.
Clinicians and policy makers in many developing countries have limited access to international journals because medical libraries often need to make a choice from a number of journals due to financial constraints. Often, it is the high-impact journal, which is subscribed to. Thus, the proportion of international representation in these leading journals may be a crucial factor in influencing health policies in many countries. The importance of research goes well beyond its impact on health policies [11]. Thus, research on the epidemiology and management of diseases in different health systems raises the probability of identifying risk factors for diseases and identifying innovative approaches to their management. This fact was well reflected in the multi-center eclampsia trial [19]. Until this trial was carried out in Africa, South America and India, the subject of using magnesium sulfate in the management of eclampsia was controversial. The other good example is the only meningitis B vaccine in the world, which was developed by the Carlos J. Finlay Institute in Cuba and now saves lives all over the world [20].
Providing free journals electronically to the developing countries is a commendable step in correcting the thirst for new information [21]. However the one-way flow of information by making journals electronically free to developing world is unlikely to be sufficient [22]. By providing journals free to 'RoW', and propagating research which has been conducted in countries where only 10% of the disease burden is experienced is itself a moral and ethical issue.
Ultimately, we believe that strengthening the health research capacity in developing world and providing reasonable opportunities for publications arising from the developing world are critical, not only for achieving biomedical research publication equity, but also advancing medical science.
Competing interests
We would like to state here that our conflict of interest if at all would be due to the fact that we come from the developing world.
Authors' contributions
All authors were involved in all the components of this paper, right from the start, in formulating and developing the idea, collecting the data, drafting the first version and revising it and approving the final version.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Ms Lakshmi Abeygoonawardane for her assistance in data collection and analysis. Dr Suwin Hewage for recollection and reanalysis of the data. We also would like to thank Dr Jennifer Keiser who reviewed our paper for BMC Medical Ethics.
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BMC ImmunolBMC Immunology1471-2172BioMed Central London 1471-2172-5-231545857410.1186/1471-2172-5-23Methodology ArticleGeneration of competent bone marrow-derived antigen presenting cells from the deer mouse (Peromyscus maniculatus) Davenport Bennett J 1bennettdavenport@yahoo.comWillis Derall G 2Derall.Willis@stmarygj.orgPrescott Joseph 13jprescott@salud.unm.eduFarrell Regina M 1reginafarrell2@hotmail.comCoons Teresa A 12Teresa.Coons@stmarygj.orgSchountz Tony 12tschount@mesastate.edu1 Department of Biological Sciences, Mesa State College, 1100 North Ave., Grand Junction, CO 81501, USA2 Saccomanno Research Institute, St. Mary's Hospital, 2530 N. 8th Street, Wellington Bldg. 4, Ste. 100, Grand Junction, CO 81501, USA3 Infectious Disease and Inflammation Program, Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM 87131, USA2004 30 9 2004 5 23 23 27 6 2004 30 9 2004 Copyright © 2004 Davenport et al; licensee BioMed Central Ltd.2004Davenport 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 infections with Sin Nombre virus (SNV) and related New World hantaviruses often lead to hantavirus cardiopulmonary syndrome (HCPS), a sometimes fatal illness. Lungs of patients who die from HCPS exhibit cytokine-producing mononuclear infiltrates and pronounced pulmonary inflammation. Deer mice (Peromyscus maniculatus) are the principal natural hosts of SNV, in which the virus establishes life-long persistence without conspicuous pathology. Little is known about the mechanisms SNV employs to evade the immune response of deer mice, and experimental examination of this question has been difficult because of a lack of methodologies for examining such responses during infection. One such deficiency is our inability to characterize T cell responses because susceptible syngeneic deer mice are not available.
Results
To solve this problem, we have developed an in vitro method of expanding and generating competent antigen presenting cells (APC) from deer mouse bone marrow using commercially-available house mouse (Mus musculus) granulocyte-macrophage colony stimulating factor. These cells are capable of processing and presenting soluble protein to antigen-specific autologous helper T cells in vitro. Inclusion of antigen-specific deer mouse antibody augments T cell stimulation, presumably through Fc receptor-mediated endocytosis.
Conclusions
The use of these APC has allowed us to dramatically expand deer mouse helper T cells in culture and should permit extensive characterization of T cell epitopes. Considering the evolutionary divergence between deer mice and house mice, it is probable that this method will be useful to other investigators using unconventional models of rodent-borne diseases.
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Background
Hantaviruses (family Bunyaviridae) are rodent-borne and can cause hemorrhagic fever with renal syndrome (HFRS4) or hantavirus cardiopulmonary syndrome (HCPS) [1]. While HFRS is usually associated with Eurasian hantaviruses, HCPS is caused by any of several recently described New World hantaviruses [2-4]. In North America, the great majority of HCPS cases have occurred in the western United States and Canada and were caused by Sin Nombre virus (SNV).
Patients afflicted with HCPS exhibit pronounced pulmonary inflammation due to capillary leak syndrome, with the consequent hypotension often leading to rapid decline and death [5]. Virus is found in the lungs of infected humans, but without discernible cytopathology, and mononuclear infiltrates are observed that produce proinflammatory cytokines, including IL-2, IL-4, IFN-γ, TNF and lymphotoxin (LT) [6], suggesting that HCPS is an immunopathologic response to the virus. To date, more than 370 infections with hantavirus have been documented in the United States, with a 36% fatality rate.
Deer mice (Peromyscus maniculatus) are the principal reservoir host of SNV [4,7]. As is usual with some natural hosts, SNV infection of deer mice does not result in discernible pathology [8]. Infection parallels that of humans, with virus infecting capillary endothelial cells in many tissues, including the lungs, but without conspicuous cytopathology. However, in contrast to human HCPS, no pulmonary inflammation, capillary leakage, or mononuclear infiltrates are observed, and most, if not all, deer mice remain persistently infected for the remainder of their lives [9].
Deer mice are among the most common mammals in North America, found from the subarctic to central Mexico, except for the Atlantic seaboard and the southeast United States where other peromyscine species predominate [10,11]. Serosurveys of natural rodent populations suggest that hantavirus infections occur throughout the range of deer mice [7,12-15], which thus poses a potential threat to individuals who are in contact with these rodents. In addition, deer mice and other peromyscine rodents have been shown to harbor other human pathogens [16-28].
Very little is known about the mechanism by which the deer mouse immune system engages SNV because few reagents and methodologies have been developed and no susceptible inbred deer mice are available. The only useful immunological data that can be acquired is by use of serology; infected deer mice produce a neutralizing IgG response that is inadequate to clear the virus [8,9,29]. We previously cloned several deer mouse cytokine genes [30-32], but quantitative assays for the detection of the expression of these genes have not been developed. These limitations have made it difficult to determine what immunological events occur that impair an effective immune response without pathology. In some viral infections, persistence has been shown to occur because of impairment of helper and cytotoxic T cell responses, antigen presenting cell (APC) function, and development of APC from bone marrow progenitors [33-37]. Currently, none of these functions can be evaluated in deer mice.
Recent advances in hematopoietic stem cell research have identified an important role for granulocyte-macrophage colony stimulating factor (GM-CSF) in the expansion and maturation of bone marrow cells into competent APC [38-40]. We previously cloned a partial cDNA representing deer mouse GM-CSF and found that one of its receptor-binding domains is nearly identical to that of the common laboratory house mouse (Mus musculus) [30]. This led us to hypothesize that house mouse GM-CSF, which is commercially-available, might be useful in expanding and differentiating deer mouse bone marrow cells into competent APC. If so, then it should be possible to generate large pools of APC from individual deer mice that could be aliquotted and frozen for use in long-term T cell cultures, which would preclude the necessity for inbred deer mice. We present evidence that such cells can be propagated in vitro and that they are capable of processing antigen and stimulating antigen-sensitized autologous T cells. This technique could provide sufficient APC, such that conventional T cell cloning and peptide-mapping experiments could be performed. In addition, because deer mice (New World rodents) and house mice (Old World rodents) are divergent by 25 to 50 million years [41], it is possible that this approach may be useful to investigators using other unconventional rodent models of infectious diseases.
Results
Cloning of the 5' end of deer mouse GM-CSF
We used RACE to obtain the complete 5' end of GM-CSF. This sequence was translated using the default translation table within MacVector. The polypeptide is predicted to have a 25 residue signal peptide based upon orthologous sequences from other species [42-45] (Figure 1). The receptor-binding domains of deer mouse and house mouse GM-CSF share 13/15 identical residues. This region forms the α-helix (helix A) that binds with high affinity to β chain subunit of the GM-CSF receptor complex that is shared with the IL-3 and IL-5 receptors [46-49].
Figure 1 Amino acid alignment of deer mouse (DM), cotton rat (CR), house mouse (HM) and human (HU) GM-CSF. Polypeptides were aligned with the clustal algorithm in Macvector. Conserved (light shading) and identical (dark shading) amino acids are enclosed in boxes. The 25-residue signal peptide is enclosed in box A. Helix A, which binds to the β chain subunit of the GM-CSF receptor, is enclosed in box B. Deer mouse and house mouse GM-CSF share 13 of 15 identical residues in this domain.
Morphologic characteristics of bone marrow-derived APC
Deer mouse bone marrow cultures contained mostly cells that appeared dead or dying after 24 hours in culture with GM-CSF. However, at 48 hours clusters of cells were apparent, while control wells without GM-CSF had fewer live cells than at 24 hours. By day 3, adherent stromal cell foci were conspicuous, while semiadherent and nonadherent cells were more evident and these became the prominent cells for the duration of culture. Day 12 bone marrow cells incubated for an additional 48 hours were large, ranging from 12 to 18 μm in diameter, and possessed macropinocytic vesicles and processes (Figure 2A). Although the method that was employed selects for DC in the house mouse [39], the deer mouse cells appeared to resemble macrophages, with abundant cytoplasmic vesicles, rather than dendritic cells, with lamellipodia or characteristic long processes extending from the cell. (S. K. Chapes, pers. comm.). However, the cells' exact definition will not be complete until better phenotypic characterization is possible. Treatment of the cells with recombinant TNF diminished the macropinocytic vesicles (Figure 2B).
Figure 2 Morphologic characteristics of deer mouse bone marrow-derived APC. Day 14 bone marrow cells cultured in GM-CSF were processed by cytospin and stained with Wright's stain. The cells exhibited conspicuous cytoplasmic vesicles and small processes (A). Cells collected on day 12 and incubated for 48 hours with 20 ng/ml of hmTNF displayed less conspicuous cytoplasmic vesicles (B).
Proliferation of deer mouse cells to house mouse GM-CSF and human IL-2
Day 8 deer mouse bone marrow cells were cultured with various concentrations of house mouse GM-CSF. Two days later, proliferation was assessed (Figure 3A) and maximal proliferation was observed at about 0.5 ng/ml of GM-CSF. Deer mouse splenocytes proliferated in response to human IL-2 (Figure 3B). In this experiment, deer mouse splenocytes were cultured with a suboptimal concentration of PHA and various concentrations of recombinant human IL-2. Maximal proliferation occurred at 20 U/ml of IL-2. In another proliferation assay, in vitro deer mouse T cells that were collected 8 days after stimulation with APC and antigen exhibited slightly greater proliferation to IL-2 (data not shown).
Figure 3 Proliferation of deer mouse cells to recombinant cytokines. (A) After 8 days of incubation with GM-CSF, deer mouse bone marrow cells were washed and then cultured with dilutions of GM-CSF in duplicate for 48 hours, then proliferation assessed by MTS assay. The data are representative of four deer mice. (B) To assess proliferative capacity of deer mouse T cells to human IL-2, splenocytes were cultured with a suboptimal dose of PHA (2 μg/ml) and dilutions of recombinant human IL-2 in duplicate for 48 hours, and proliferation assessed by MTS assay. The data are representative of two deer mice.
Expression of MHC class II I-Eβ and TCRβC by deer mouse cells propagated in vitro
BM-APC and T cells were examined for the expression of orthologous I-Eβ and TCRβC, respectively, by RT-PCR (Figure 4). For I-Eβ, primers were designed from previously published deer mouse sequences [50], while primers for TCRβC were those that are described in this work. In each instance, products of the expected sizes were amplified. The amplified BM-APC product was cloned, sequenced, and verified to be I-Eβ.
Figure 4 RT-PCR of TCRβC and MHC class II I-Eβ in deer mouse cells. Total RNA was extracted from T cells and bone marrow-derived APC. Expression of the constant β chain of the TCR by the T cells and class II I-Eβ chain by the APC were detected by RT-PCR. β-Actin primers were used as controls for each sample.
BM-APC induce antigen-specific proliferation of autologous T cells
Deer mice were immunized with keyhole limpet hemacyanin (KLH), and 10 days later the lymph nodes, spleens and bone marrow were processed for in vitro expansion of polyclonal T cells (lymph node cells), while the bone marrow cells and splenocytes were frozen. Sera were tested for antibodies to KLH by ELISA and in each deer mouse tested the titer was greater than or equal to 8,000 (data not shown). For recall proliferation, KLH, in vitro-propagated T cells (14 days with IL-2) and BM-APC (14 days with GM-CSF) or freshly thawed splenocytes were cultured together for 72 hours, and proliferation was assessed by MTS assay (Figure 5). For each deer mouse, the BM-APC were between 10× to 20× more efficient at stimulating antigen-specific helper T cell proliferative responses. While each T cell line exhibited a 50% maximal stimulation in the presence of about 10 to 20 μg/ml antigen with splenocytes, 50% maximal stimulation was usually near 1 to 2 μg/ml antigen with BM-APC. In parallel experiments, cultures incubated with 20 ng/ml house mouse TNF did not exhibit noticeably different proliferative responses compared to control cultures (data not shown), despite morphological evidence suggesting an effect on macropinocytosis (Figure 2).
Figure 5 BM-APC stimulate helper T cell proliferation. Deer mice were immunized with 20 μg of KLH subcutaneously and 10 days later the lymph nodes, bone marrow and splenocytes were retrieved for expansion of helper T cells and BM-APC. After expansion of these cells in culture, proliferation assays were performed comparing mitomycin-C-treated autologous splenocytes (SC) and BM-APC (BMC) for their capacity to stimulate T cells. In each instance, the BM-APC were more effective at stimulating T cell responses. The data are of two deer mice (DM212 and DM213).
Antibody augments BM-APC stimulation of T cells
Deer mouse antiserum raised against KLH and incubated with antigen for one hour prior to addition of cells increased the sensitivity of T cell proliferation (Figure 6), suggesting that Fc receptors are present on the surface of the BM-APC. The presence of antibody increased the 50% maximal T cell proliferation from one deer mouse (DM223) about 10-fold, from about 500 ng/ml without antibody to 50 ng/ml with antibody. Similarly, for another deer mouse (DM224) the presence of antibody was substantially more effective at inducing T cell proliferation, increasing 50% max 50-fold (from 50 ng/ml to about 1 ng/ml). Notably, the T cell response in DM223 was also less vigorous (50% max 500 ng/ml) without antibody compared to DM224 (50% max 50 ng/ml). The proliferative responses of six other deer mouse T cell lines were similar to those of these deer mice (data not shown).
Figure 6 Antigen-specific antibody augments BM-APC-induced T cell proliferation. T cell proliferation responses from deer mice 223 and 224 were assessed as described in Figure 5 using BM-APC. KLH-specific antiserum or normal deer mouse serum were diluted 1:2,000 in DMM-5 and incubated with dilutions of KLH for 1 hour in 96-well plates at room temperature. BM-APC and T cells were added to the wells and incubated 72 hours, and proliferation was assessed by MTS assay.
Discussion
To our knowledge, no previous efforts have been made to develop long-term cultures of T cells from unconventional laboratory rodents. The principal reason for this is that highly inbred strains, required for conventional long-term T cell work, are not available from rodents not routinely used in laboratory work. At least for deer mice, we have developed a method of fulfilling this need by using commercially-available house mouse GM-CSF. This cytokine apparently binds to the GM-CSF receptor on deer mouse cells such that it generates competent APC from the bone marrow. These cells are capable of processing and presenting soluble antigen to autologous antigen-specific helper T cells.
Our initial suspicions that house mouse GM-CSF might bind to deer mouse GM-CSF receptor was the result of previous work [30] in which we cloned a partial cDNA of deer mouse GM-CSF, including most of its A helix that is involved in binding to the β chain subunit of the receptor. We used 5' RACE to obtain the complete N-terminus and found that all but two of the residues from helix A are identical between the two species. Subsequent experiments demonstrated that GM-CSF induces proliferation of deer mouse bone marrow cells, and since GM-CSF is routinely used to generate APC from the bone marrow we hypothesized that it would do so with deer mouse bone marrow.
We used a method that has been shown to generate dendritic cells in house mice; however, the cells obtained from deer mouse bone marrow more closely resembled macrophages rather than DC. These cells contained many large macropinocytic vesicles, but conspicuous dendrites typical of DC were not observed. Microscopically, these cells also appeared sensitive to TNF, which decreased macropinocytosis, but it had no effect on the capacity of these cells to present antigen to T cells as has been reported for human DC derived from blood mononuclear cells [51]. TNF can induce a physiologic change in the APC from an active pinocytotic cell into one that becomes highly efficient at MHC class II antigen presentation, thus facilitating transition from the innate phase to the adaptive phase of the immune response. It is unclear why TNF treatment does not augment T cell proliferative responses with deer mouse APC, but it may be that species-specific differences in GM-CSF and TNF signaling occur that account for these disparities in APC development and behavior. It is also possible that TNF does not induce complete maturation of the cells into highly efficient APC, as has been reported for some DC [52]. It is currently impossible to phenotype these cells because no antibodies specific to deer mouse APC subpopulations, such as CD markers, are available, nor have genes for these markers been cloned, despite many attempts (unpublished observations), that might facilitate identification of these cells. Regardless, the cells are highly efficient at processing and presenting antigen, and inclusion of antigen-specific antibodies augments these functions.
Since the deer mice are outbred, this method requires the immunization and collection of cells from individual animals (Figure 7). These cells are derived from lymph nodes (T cell source), splenocytes (APC source) and bone marrow (APC source). Most of the recovered cells can be propagated in vitro and/or aliquotted and stored frozen so that viable cells can be used as necessary to propagate and characterize helper T cell lines. We routinely recover 107 bone marrow cells from a deer mouse, which is sufficient for freezing 5 vials at 2 × 106 cells each. Each vial is used to seed a 100 mm bacterial Petri dish, which produces about 107 BM-APC at 14 days of culture. For deer mice, the most significant limitation for cells is from the spleen. Although deer mice are slightly smaller than BALB/c mice, their spleens are disproportionately small (unpublished observations). We routinely recover 7 × 106 splenocytes from a deer mouse, while BALB/c house mice usually provide 10-fold more. Because of this limitation, we have begun to use BM-APC to propagate T cells. This method involves culturing of bone marrow cells with GM-CSF for 10 days, then freezing aliquots of 106 cells. Three days before T cell restimulation, the 10-day BM-APC are thawed and cultured with GM-CSF, then used for restimulation with fresh antigen in one well of a 24-well plate. The T cells are fed fresh IL-2 DMM-5 at two-day intervals for expansion.
Figure 7 Schematic overview of the process for culturing autologous deer mouse BM-APC and T cells. Ten days post immunization, lymph nodes, spleens and bone marrow are harvested from euthanized deer mice. The lymph node cells are cultured with antigen for four days, while the splenocytes and bone marrow cells are frozen at -70°C. On day 4, the blasting lymph node T cells are recovered and cultured with fresh antigen and thawed splenocytes (without mitomycin-C treatment). Simultaneously, bone marrow cells are thawed and cultured with GM-CSF. Expansion of the T cells is performed with huIL-2 and the BM-APC with GM-CSF for 14 days. These cells are then used for proliferation experiments.
We have used this method to establish nine T cell lines, six specific for KLH and three specific for SNV nucleocapsid antigen (data not shown). Based upon typical cell yields, it should be possible to assay several thousand wells on 96-well plates, which we estimate to be sufficient for many T cell activities, including cloning, peptide epitope mapping, TCR variable gene segment usage, and cytokine profiling.
We believe the methods described in this work will allow the characterization of antigen presentation and T cell responses in infected deer mice. Many viruses impair pathways involved in APC and T cell functions so that they can evade a sterilizing immune response. With hantaviruses and their rodent hosts, millions of years of evolution have presumably allowed a coadaptation of the viruses and host immune responses such that pathology does not occur and the virus is not eliminated. It is possible that hantaviruses possess some as yet unidentified mechanism for suppressing an aggressive inflammatory immune response in rodent hosts, which is ineffective in human infections and often leads to inflammatory immunopathology.
Because of the substantial evolutionary divergence of deer mice and house mice (about 25–50 million years) [41], it is likely that this method could be used with many divergent rodent species, and thus useful for examining APC and T cell responses in a variety of rodent systems, including natural hosts and animal models of disease.
A limitation of this approach is that BM-APC lose their ability to proliferate in the presence of GM-CSF after four to six weeks, similar to what has been observed with house mouse bone marrow-derived cells [53,54]. Since a finite number of bone marrow cells can be harvested, this limitation prevents indefinite propagation of deer mouse T cells. It is possible that competent BM-APC might be propagated indefinitely by the introduction of oncogenes, such as transforming retroviruses [55]. Alternatively, other house mouse or human hematopoietic cytokines that are commonly used to propagate bone marrow progenitor cells may bind to deer mouse receptors. For example, human or house mouse Flt3 ligand is active on both human and house mouse cells, suggesting that one or both would have an effect on deer mouse cells as well. In this manner, large numbers of progenitor cells might be produced in vitro for storage and then thawed, as needed, for culturing in GM-CSF to produce functional APC.
Conclusions
We have developed a method for generating large numbers of competent antigen presenting cells from deer mouse bone marrow using house mouse GM-CSF. This method resulted in the production of antigen-specific T cell lines from outbred deer mice. Inclusion of antigen-specific antibody in cultures augments T cell proliferation, suggesting the APC express Fc receptors. This method will allow characterization of APC and T cells in deer mice and may be extended to other rodent species that are important in infectious disease research.
Methods
Deer mice
The deer mice used in these experiments were from a colony of animals established with deer mice trapped in western Colorado [30]. All procedures were approved by the Mesa State College Institutional Animal Care and Use Committee and in accordance with the Animal Welfare Act.
Cloning of the deer mouse GM-CSF 5' cDNA
The 5' end of the deer mouse GM-CSF cDNA was obtained by using RACE. Briefly, a primer (Table 1) was designed from a partial cDNA of deer mouse GM-CSF [30] and used to amplify the 5' end according to manufacturer's directions (SMART RACE, BD CLONTech, Palo Alto, CA) using con A-activated spleen cell culture cDNA. The fragment was cloned into pGEM-T Easy (Promega, Madison, WI) and sequenced using the Big Dye Terminator sequencing kit (Applied Biosystems, Foster City, CA) and an ABI 310 DNA Analyzer, and the sequence was deposited into Genbank (AY247762). The signal peptide and receptor-binding domain was identified by comparison to house mouse GM-CSF [49]. GM-CSF polypeptides from the house mouse (X02333), cotton rat (Sigmodon hispidus, AAL55394) and human (NP_000749) were aligned using MacVector's (Accelrys, San Diego, CA) clustal algorithm.
Table 1 Primers used in this work1
Gene Forward Reverse Size (bp)
I-Eβ GTC ATT TCT ACA ACG GGA CG TCT CCG CTG CAC AAT GAA GC 242
TCRβC AGG ACC TGA GCA AGG TGA GC GCA CAG CAT ACA GGG TGG CC 474
β-Actin ATG TAC GTA GCC ATC CAG GC TCT TGC TCG AAG TCT AGG GC 283
GM-CSF 5' RACE N/A GTT GCC CCG TAG GCC CTT CTC ATA TAA CT 273
1All sequences are listed 5' to 3'.
Cloning of the deer mouse T cell receptor β constant domain cDNA
Total RNA from activated splenocytes was reverse-transcribed using an oligo-dT primer and Superscript II (Invitrogen, Carlsbad, CA). TCRβC cDNA sequences from house mouse, rat and human were aligned with MacVector. PCR primers (Table 1) were designed from highly conserved regions within the alignment. PCR was performed on activated splenocytes with 95°C for 30 sec, 58°C for 30 sec, and 72°C for 1 min for 35 cycles. The amplified fragment was cloned and sequenced as described above, and deposited into Genbank (AY307417).
Immunization of deer mice
Deer mice were bilaterally immunized subcutaneously at the base of the tail with 20 μg of KLH (Sigma Chemical Co, St. Louis, MO) emulsified in CFA (Sigma). Ten days later, draining lymph nodes, spleens and bone marrow were recovered for in vitro experiments. For production of high-titer KLH antiserum, deer mice were immunized i.p. with 20 μg of KLH emulsified in CFA and boosted with 20 μg in IFA one month later. Sera were collected 7 days after boosting.
Processing of tissues from immunized deer mice
Immunized deer mice were euthanized by cervical dislocation and the draining lymph nodes, spleens and bone marrow from individual animals were separately collected in Hank's balanced salt solution for processing. The lymph nodes served as a source of antigen-specific T cells, while the splenocytes were treated with ammonium chloride (Cambrex Bioproducts, Walkersville, MD) to lyse RBCs, then frozen in 10% DMSO/5% FBS deer mouse medium (DMM-5: 5% FBS, RPMI-1640 supplemented to 315 mOsm [with 2.5 ml of 5 M NaCl/L], 2.5 μg/ml Fungizone, 100 U/ml penicillin, 100 μg/ml streptomycin, 50 μg/ml gentamicin, 50 μM β-ME, 10 mM HEPES, 2 mM L-glutamine) in aliquots for use as autologous APC for additional rounds of in vitro T cell stimulation. The bone marrow cells were collected from tibiae and femurs, washed twice in DMM-5, and aliquotted at 2 × 106 cells per vial in 1 ml of 10% DMSO/DMM-5 and stored at -70°C.
Bone marrow culture
Bone marrow-derived APC (BM-APC) were generated with modification of a previously described method for dendritic cells (DC) [39]. One vial of bone marrow cells (2 × 106) was quick-thawed in a 37°C water bath and cultured without washing in 100 mm bacterial Petri dishes in DMM-10 containing 20 ng/ml recombinant house mouse GM-CSF (R&D Systems, Minneapolis, MN) at 37°C under 7% CO2. Fresh GM-CSF/DMM-10 was provided on days 3, 6, 8, 10, and 12 for the generation of APC. Cells were collected with a scraper for use in experiments. Cells were processed by cytospin and stained with Wright's stain for morphological examination.
Assessment of T cell sensitivity to human IL-2
Deer mouse splenocytes depleted of RBC by ammonium chloride treatment were incubated with a suboptimal dose of PHA (2 μg/ml) (Sigma) in DMM-5 and recombinant human IL-2 (R&D Systems) for 48 hours. Proliferation was determined by MTS assay (Cell Titer-96 AQ, Promega). The means and standard deviations of duplicate samples were calculated, with the mean of cells without IL-2 subtracted from sample means.
Assessment of T cell receptor and MHC class II expression
Total RNA was extracted from 14 day T cell and BM-APC cultures (Versagene RNA, Gentra Systems, Minneapolis, MN) and converted into cDNA. Class II expression of the bone marrow cells was assessed by PCR using a forward primer from exon 2 and a reverse primer that overlaps the boundaries of exons 2 and 3 of deer mouse I-Eβ (Table 1[50]). The amplified fragment was cloned and sequenced as described above. T cells were defined by PCR amplification of the TCRβC chain using the primers listed above (forward, exon 1; reverse, exon 2). β-Actin expression was assessed for each population.
ELISA serology
Sera were collected at euthanasia by cardiac puncture. Plates were coated with 5 μg/ml KLH in PBS overnight and washed 5× with wash buffer (PBS-0.1% TWEEN-20). Plates were then blocked with blocking buffer (5% nonfat powdered milk in wash buffer) for 1 hour at room temperature. The sera and remaining reagents were diluted in blocking buffer. Sera were incubated in duplicate for 2 hours at room temperature, followed by goat anti-P. leucopus IgG (H&L) (KPL, Gaithersburg, MD) for 1 hour, then horse anti-goat IgG-HRP conjugate for 1 hour (Vector, Burlingame, CA). ABTS substrate (Sigma) was incubated for 15 min, and plates were read at 414 nm. Means were calculated with the background (1:100 normal deer mouse serum) subtracted.
In vitro helper T cell expansion
In vitro stimulation of helper T cells was performed essentially as described elsewhere [56,57]. Lymph nodes from immunized deer mice were made into single-cell suspensions by gently disrupting the capsule between the ends of sterile frosted microscope slides. The cells were washed twice in HBSS and plated at 5 × 106 cells per well (24 well plate) with 20 μg/ml KLH in DMM-5. After a 4 day incubation, the lymph node cells were collected and washed twice in DMM-5. The number of recovered lymph node cells varied between animals, but between 2 × 105 and 5 × 105 cells were recovered and plated with fresh antigen and 3 × 106 thawed autologous splenocytes in DMM-5 in 24 well plates in 1 ml of DMM-5. At 2 day intervals, cultures were fed by removing 750 μl of media and replacing it with DMM-5 containing 20 U/ml of recombinant human IL-2. When cultures were greater than 80% confluent, cells were passaged 1:2 into additional wells or into T25 tissue culture flasks. This process was continued for 14 days to expand T cells. Cultures were also restimulated at two week intervals with fresh mitomycin-C treated autologous splenocytes as above, or 2 × 106 BM-APC to continue propagation of T cell lines.
Functional assessment of bone marrow-derived APC
BM-APC were examined for functional capacity to process and present KLH to sensitized autologous deer mouse T cells expanded in culture. For these experiments, mitomycin-C treated BM-APC (104) or splenocytes (2 × 105) were used to stimulate 105 T cells in the presence of KLH in 96-well plates. In other experiments, the effects of house mouse tumor necrosis factor (20 ng/ml) were evaluated on APC morphology and capacity to stimulate T cell proliferation. Lastly, antisera to KLH were produced in deer mice and used to assess the capacity of the BM-APC to capture and process antigen for presentation to T cells. In these experiments, antiserum or normal deer mouse serum were diluted to 1:2,000, a saturating dilution in ELISA as described above, with KLH and incubated for 1 hour at room temperature. BM-APC and T cells were then added and the cultures incubated for 72 hours prior to determining proliferative responses by MTS. Means and standard deviations were calculated from duplicate samples.
List of abbreviations
HFRS, hemorrhagic fever with renal syndrome; HCPS, hantavirus cardiopulmonary syndrome; APC, antigen presenting cell; SNV, Sin Nombre virus; GM-CSF, house mouse GM-CSF; DC, dendritic cell; CFA, complete Freund's adjuvant; RT-PCR, reverse transcription polymerase chain reaction; MTS, 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium
Authors' contributions
BD conducted bone marrow cell culture work. DGW and TAC performed RT-PCR experiments. JP cloned and sequenced the TCRβ cDNA. RMF cloned and sequenced the MHC class II cDNA. TS immunized deer mice and generated T cell lines.
Acknowledgments
We are indebted to Charles H. Calisher and Barry J. Beaty for providing cell culture supplies, and to Deb Kraft, Tom Regan and Jan Kelly (Community Hospital, Grand Junction, CO) for preparing and staining cytospin samples. Funding for this work was provided by grants from the National Institutes of Health (AI25489), the St. Mary's Hospital Foundation (Grand Junction, CO), the βββ Biological Honor Society, the MSC chapter of Sigma Xi, and the MSC School of Natural Sciences and Mathematics.
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| 15458574 | PMC524361 | CC BY | 2021-01-04 16:28:17 | no | BMC Immunol. 2004 Sep 30; 5:23 | utf-8 | BMC Immunol | 2,004 | 10.1186/1471-2172-5-23 | oa_comm |
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BMC MicrobiolBMC Microbiology1471-2180BioMed Central London 1471-2180-4-371538505410.1186/1471-2180-4-37Research ArticleThe vaa locus of Mycoplasma hominis contains a divergent genetic islet encoding a putative membrane protein Boesen Thomas 12tboesen@bioxray.dkEmmersen Jeppe 3je@bio.auc.dkBaczynska Agata 1agata@medmicro.au.dkBirkelund Svend 1chlam@biobase.dkChristiansen Gunna 1gunna@medmicro.au.dk1 Department of Medical Microbiology and Immunology, University of Aarhus, DK-8000 Aarhus C, Denmark2 Department of Molecular Biology, Science Park, University of Aarhus, Gustav Wieds Vej 10C, DK-8000 Aarhus C, Denmark3 Department of Biotechnology, Aalborg University, DK-9000 Aalborg, Denmark2004 22 9 2004 4 37 37 14 3 2004 22 9 2004 Copyright © 2004 Boesen 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 Mycoplasma hominis vaa gene encodes a highly variable, surface antigen involved in the adhesion to host cells. We have analysed the structure of the vaa locus to elucidate the genetic basis for variation of vaa.
Results
Mapping of vaa on existing physical maps of five M. hominis isolates by pulsed field gel electrophoresis revealed that vaa is located in a genomic region containing the majority of other characterized membrane protein genes of M. hominis. Sequencing of an 11 kb region containing the vaa locus of M. hominis isolate 132 showed the presence of conserved housekeeping genes at the borders of the region, uvrA upstream and the hitABL operon downstream to vaa. Analysis of 20 M. hominis isolates revealed that the vaa upstream region was conserved whereas the downstream region was highly variable. In isolate 132 this region contained an open reading frame (ORF) encoding a putative 160 kDa membrane protein. Homologous ORFs were present in half of the isolates, whereas this ORF, termed vmp (variable membrane protein), was deleted from the locus in the remaining isolates. Compellingly, the conserved upstream region and variable downstream region of vaa correlates with the genetic structure of vaa itself which consists of a conserved 5' end and a variable 3' end containing a variable number of exchangeable sequence cassettes.
Conclusion
Our data demonstrate that the vaa locus contains a divergent genetic islet, and indicate pronounced intraspecies recombination. The high variability level of the locus indicate that it is a chromosomal 'hot spot', presumably important for sustaining diversity and a high adaptation potential of M. hominis.
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Background
The mycoplasmas are wall-less prokaryotes characterized by small genomes (580 – 2200 kb) and a low G+C content, generally below 30%. They are the smallest self-replicating organisms known with cell diameters normally in the range of 0.3–0.8 μm [1], and are observed as parasites of insects, plants, animals and humans with strict host specificities. As a consequence of the direct exposure of proteins located on the surface of the cytoplasmic membrane to the surrounding environment, antigenic variation of surface proteins is observed among mycoplasmas. The often chronic nature of mycoplasmal infections is thought to be a consequence of evasion of the humoral immune response by the variation displayed by these coat proteins [2].
Mycoplasma hominis is an opportunistic human pathogen observed as a commensal of the urogenital tract. Primarily, urogenital infections giving rise to spontaneous abortions, pelvic inflammatory disease, and acute pyelonephritis have been associated with M. hominis, but extragenital infections resulting in infant meningitis, arthritis, and septicemia have been reported [3].
M. hominis is a very heterogeneous species as measured by a pronounced antigenic variation [4-7]. The molecular basis for antigen variation of M. hominis surface proteins has been elucidated in some cases. The large membrane protein (lmp) gene family displays size variation by insertion/deletion of intragenic repeats of approximately 500 bp. The lmp genes are arranged in two clusters, lmp1-2 and lmp3-4 in the M. hominis genome of most analysed isolates with a distance between the clusters of more than 110 kb [8]. At least one member of the lmp family is expressed in each of the M. hominis isolates tested and decrease in the number of repeats were found to correlate to the amount of spontaneous agglutination of M. hominis cells [9,10].
The vaa (variable adherence-associated) gene encodes a size and phase variable M. hominis adhesin [11-14]. Phase variation is accomplished by variation in the number of bases in a poly-A tract situated in the 5'-end of the gene [12]. This is presumably achieved by slipped strand mispairing with a frequency of 10-3–10-4. In the ON-state 8 adenines are observed in the poly-A tract, whereas 7 or 9 results in the out-of-frame OFF-state [12]. A single vaa gene is present in each M. hominis isolate [15]. The size of Vaa observed in different isolates ranges from 28 kDa to 72 kDa. This size variation is the consequence of a variable number of homologous, exchangeable cassette sequences located in the 3' end of vaa [11,13]. Each cassette encodes approximately 110 aa containing a coiled-coil motif and 1 to 5 cassettes have been observed in different Vaa proteins. The Vaa protein is a rod-shaped, monomeric protein and the cassettes are presumed to form homologous, 'spike'-formed binding domains arranged in parallel in the three-dimensional structure [16]. Based on the cassette composition, 6 distinct vaa gene types have been observed in more than 100 analysed clinical isolates [13,14]. The mechanism behind this variation is unknown, but duplication/deletion of cassettes followed by divergence of cassette sequences has been suggested [14]. Comparison of the homology between cassettes showed that the cassette sequences could be divided arbitrarily into 5 cassette types based on sequence identity. Analysis of the cassette organization in different isolates revealed that intraspecies recombination resulting in the exchange of cassette sequences could be an alternative mechanism for variation of Vaa [13].
To obtain a better understanding of the genomic basis for variation of vaa and variation mechanisms in M. hominis in general, the vaa locus was characterized by mapping of the genomic position in five isolates and sequencing of a 11 kb region containing the vaa gene from isolate 132. Furthermore, the vaa locus of 20 M. hominis isolates was investigated by PCR and sequencing. In contrast to the more conserved vaa upstream region this analysis revealed that the downstream region also exhibits major variation caused by insertion/deletion and sequence variation of a large ORF encoding a putative membrane protein. Thus the vaa locus seems to constitute a 'hot spot' for variation in the M. hominis genome.
Results
Genomic localization of the vaa gene
The vaa gene was mapped on exsisting physical and genetic maps of 5 M. hominis isolates: 132, 4195, 7488, PG21, and 93 (Fig. 1A) [8]. Chromosomal DNA from the isolates was digested by the restriction endonucleases SmaI, BamHI, XhoI, SalI, and ApaI and the fragments were separated by pulsed field gel electrophoresis (Fig. 1B). The fragments were transferred to nitrocellulose and hybridized with three (α-32P)dATP-labelled DNA fragments representing different parts of selected vaa genes (see materials and methods). All probes hybridized to a single fragment in all digests, corresponding to the same region of the genome for all 5 isolates (Fig. 1A and 1B). The fragments were located in a genomic region near the gyrB gene (Fig. 1A). A number of other M. hominis genes encoding membrane proteins (p75, p120 and p120', see Fig. 1A) were also positioned in this region of the genome [8,17,18].
To further analyse the variability of the vaa locus, restriction endonuclease analysis was performed. Southern blotting of HindIII and EcoRI cleaved genomic DNA separated with ordinary agarose gel electrophoresis from the 5 isolates using probe 2 was made (Fig. 2A and 2B). The probe recognized a band of 6.0 kb in the isolates 132 and 4195 and a band of 6.3 kb in isolates 7488, PG21, and 93 in the HindIII digest (Fig. 2A). The band size difference between the isolates could be attributed to the fact that the HindIII site relative to the ATG start codon in the vaa genes of isolates 7488, PG21, and 93 was located 243 bp further upstream compared to the HindIII site in isolates 132 and 4195. This indicates that the HindIII site upstream vaa is conserved. Bands of diverging size were observed in the isolates for the EcoRI digest using this probe (data not shown). The band differences observed could be explained by the presence or absence of an EcoRI site in the variable vaa gene. Using a probe comprising the cassette region of the vaa category 3 (vaa-3) gene (probe 4) band size variation was observed in the 5 isolates for both enzymes (Fig. 2B, data not shown). The results of the Southern blotting experiments confirmed that vaa is present as a single copy in the genome and indicated sequence variation in the vaa locus.
Amplification and sequencing of the vaa locus of M. hominis 132
As the mapping and restriction endonuclease analysis of vaa indicated a variable locus, we decided to sequence this genomic region of the M. hominis genome to determine the cause of the variability. A HindIII/EcoRI restriction map of the vaa locus of isolate 132 was made using the Southern blotting results (Fig. 3A). The sizes of most of the HindIII and EcoRI fragments including the up- and downstream regions of vaa were 4.2 kb or below. These fragments were thus suitable for amplification by inverse PCR. The genomic DNA was cleaved by HindIII or EcoRI and religated. Outward pointing oligonucleotide primers located in the vaa gene were used in PCR on the religated template in order to amplify regions outside the gene (Fig. 3A). PCR products of the expected sizes were observed and sequenced bidirectionally. A contig of approximately 8 kb was assembled. In order to expand the contig, a new round of inverse PCR was performed using new primer sets located in each end of the contig. The upstream region was expanded using the HindIII cleaved and religated template. To expand the downstream region, chromosomal DNA cleaved with BglII and religated was used as template. Sequencing of the expanded regions revealed that an ORF showing high similarity to the uvrA gene by database search was located approximately 5 kb upstream to vaa. The annotation of this ORF as uvrA, the gene encoding excinuclease ABC subunit A, was based on homology alone as this gene has not yet been characterized in mycoplasmas. Furthermore, the conserved hitB gene, part of the hitABL operon, was identified in the opposite end of the vaa locus (Fig. 3B). The hitABL operon comprises three highly conserved genes. The hitAB genes encode the P60 and P80 proteins, respectively. P60 and P80 form a membrane associated complex that interacts by an unknown mechanism with the evolutionary conserved, cytoplasmic HinT (histidine triad nucleotide-binding) protein encoded by hitL. This system was previously characterized in M. hominis by Henrich and coworkers [19-21]. The hitABL operon was located almost 5 kb downstream to the vaa gene of M. hominis 132 (Fig. 3B). Thus, the vaa locus is bordered by highly conserved housekeeping genes. A bidirectionally sequenced contig of 11.3 kb comprising the vaa locus was assembled (Fig. 3C).
Gene organization of the vaa locus of M. hominins 132
Analysis of the contig harboring the vaa locus revealed a number of open reading frames (Fig. 3B). At the border of the sequenced upstream region the uvrA gene, represented by 878 bp of the 5' end of the gene, is located. Between uvrA and vaa five ORFs, numbered 1 to 5, were detected, ORF2 encoding a putative protein of only 6 kDa (Fig. 3B). This ORF was included as proteins of similar size has been detected in other bacteria [22]. The transcriptional direction of these ORFs and uvrA was opposite that of vaa. The ORFs were positioned closely, ORFs 4 and 5 had a 16 bp intergenic region, and ORFs 2 and 3 had an intergenic region of 22 bp. ORFs 3 and 4 showed an overlap of 35 bp. Thus, ORFs 1 to 5 might constitute an operon. No obvious stem-loop structures with a putative rho-independent transcriptional termination function were observed immediately downstream to any of the ORFs. The hypothetical genes were employed in database searches. The ORF adjacent to uvrA, (ORF1), encoding a hypothetical 35 kDa protein, showed high similarity to a range of hypothetical proteins of similar size in the database. All of these proteins contained a HAD hydrolase superfamily motif. The highest similarity was to a hypothetical protein of Mycoplasma pulmonis (31% identity, 54% similarity in 268 aa). No significant homologues were found for ORFs 2 to 5. ORF5 was shown to encode a hypothetical protein containing an N-terminal signal peptide with a signal peptidase II cleavage site typical of prokaryotic prolipoproteins and may thus encode a lipoprotein having a size of 29 kDa and a pI of 9.6. Interestingly, a transmembrane helix was predicted in the C-terminal part of this putative lipoprotein using the program TMHMM (membrane probability of 1 for aa 243 to 252) [23].
The downstream region of vaa revealed the presence of a large open reading frame of 4 kb, ORF6, encoding a hypothetical protein with a molecular weight of 160 kDa (Fig. 3B). A secretory signal peptide was identified in the N-terminal part of the putative protein using the program SignalP [24]. A signal peptidase I cleavage site was identified between A24 and S25 (mean S value of 0.956 for aa 1–27), but as no gene encoding signal peptidase I has been observed in most of the sequenced mycoplasma genomes, the protein is most likely not processed [2,17]. A homopolymeric tract of 16 thymidine residues (poly-T tract) was located 77 bp upstream to the ATG start codon of ORF6, and a putative rho-independent stem-loop terminator structure (ΔG = -16.2 kcal/mol) was observed 23 bp downstream of ORF6. The deduced aa sequence of ORF6 was used in a database search and intriguingly, high similarity to the Lmp-1 and Lmp-3 proteins of M. hominis was found, the highest similarity was to Lmp-1 (28% identity and 48% similarity in 1241 aa, see additional file 1). Surprisingly, homology was also found to the myosin heavy chain protein of the slime mold Dictyostelium discoideum (20% identity and 40% similarity in 1083 aa), and other myosin proteins in the database. In the region between ORF6 and the hitABL operon, a tRNA(His) gene was identified by database search (Fig. 3B). The highest similarity observed was to the tRNA(His) of Bacillus subtilis. Intriguingly, the 5' end of the gene displayed a high similarity to the orthologue from Streptococcus pneumoniae (94% identity from bp 10 to 45), even higher than to the corresponding region in Bacillus subtilis (92% identity) and Mycoplasma pneumoniae (86% identity). The transcriptional direction of ORF6, tRNA(His) and the hitABL operon was opposite that of vaa in analogy to the ORFs of the vaa upstream region (Fig. 3B).
Variability of the vaa locus in 20 M. hominis isolates
To examine the variability of the vaa locus, PCR was performed on 20 M. hominis isolates representing different vaa types. Using a primer located in the conserved region of vaa and a primer located in the uvrA gene, a PCR product of 5.5 kb was amplified (Figs. 3 and 4B). All isolates gave rise to a band of identical size for the primer set (Fig. 4B). Furthermore, PCR was performed using the primer located in the conserved region of vaa and a primer located in ORF3 or ORF5. This amplified fragments of 4 kb and 0.6 kb, respectively, in all analysed isolates (Fig. 4B). The PCR results thus suggested that the upstream region is very conserved. Additionally, restriction endonuclease analysis of the 5.5 kb PCR fragment was made using the enzymes AluI and AseI, which cleaves at 5 and 8 sites, respectively, scattered over the entire fragment of isolate 132. This analysis revealed 13 and 3 digestion profiles, respectively, of the 20 isolates (data not shown). It was not possible to classify the profiles according to the vaa type or other known M. hominis groupings. Thus, despite a higly conserved organization and length of the ORFs in the vaa upstream region, there is an underlying sequence variation, presumably corresponding to the background variation level present in the M. hominis genome.
In contrast, when primers located in the conserved region of vaa and hitB, respectively, were used in PCR, a pattern revealing different product sizes was observed (Fig. 4C). The expected 5.5 kb PCR product was amplified in 5 isolates, 10 gave rise to bands of approximately 2 kb and 5 gave rise to larger bands of 7.5 and 8 kb (Fig. 4C). The size of the 2 kb products corresponded to the deletion of ORF6. This was verified by sequencing of the products from M. hominis PG21 and 93 (Fig. 5). Sequencing of the 8 kb and 7.5 kb PCR products from M. hominis 7488 and 4195, respectively, revealed ORFs of 6.5 kb and 5.5 kb showing homology to ORF6 (Figs. 5 and 6). Because of the apparent variability of this protein, ORF6 and the corresponding ORFs of M. hominis 7488 and 4195 were named vmp (variable membrane protein). The isolates were divided into vmp groups based on the above PCR results according to the size of the vmp gene observed in the different sized downstream PCR products. The vmp gene having a size of 4 kb was named vmp category 1 or simply vmp-1, and the isolates (indicated with green numbers in Fig. 4) giving rise to a 5.5 kb downstream PCR product, containing the vmp-1 gene, were categorized as having a vmp-1 gene type (Fig. 4C). Likewise, the vmp genes having a size of 5.5 kb and 6.5 kb were named vmp-2 and vmp-3, respectively, and the isolates giving rise to downstream PCR products of 7.5 and 8 kb (indicated in Fig. 4 by orange and magenta numbers, respectively) were categorized as having a vmp-2 and vmp-3 gene type, respectively (Fig. 4C). It was not possible to design a universal vmp primer set that would amplify a fragment from all the sequenced vmp genes due to the high sequence variation observed between the genes. Instead, a primer set amplifying a 0.6 kb fragment of vmp-1 was used for PCR of the 20 isolates. Four of the five genes categorized as vmp-1 gave rise to a strong band of 0.6 kb (Fig. 4D). The isolate 183 also categorized as having a vmp-1 gene type gave rise to a very faint band of 0.6 kb. A second primer set was designed that would amplify a 1.2 kb fragment from both vmp-2 and vmp-3 (Fig. 4E). Again, only four of the five isolates expected gave a product. The isolate SC4 categorized as having a vmp-1 gene type also gave a faint band with the vmp-2/3 primer set. The isolate 1572B did not give a product with the primer set, but was categorized as having a vmp-2 gene type because it gave rise to a downstream PCR product of approximately 7.5 kb. Thorough examination revealed that the size of the 1572B downstream PCR product was slightly smaller than that of isolate 4195. Thus, isolate 1572B may harbor a fourth vmp type. The vmp-2 and vmp-3 genes were flanked by a poly-T tract and a stem-loop terminator structure (ΔGs of -16.7 and -15.6 kcal/mol, respectively) showing high homology of the stem regions to that observed for vmp-1. The stem-loop structure was located approximately 500 bp downstream of the stop codon of vmp-2 but interestingly, the homology between vmp-2 and vmp-3 extends beyond the stop codon in vmp-2. Careful analysis reveals that a poly-A tract in the 3'-end of the vmp genes has an extra (9 total) adenine in vmp-2 compared to vmp-3, which causes a premature termination of translation of the vmp-2 gene. If the extra adenine of the poly-A tract was deleted the ORF would continue for approximately 500 bp, corresponding to vmp-3, and the termination codon would be situated close the putative rho-independent transcriptional termination stem-loop structure. The remaining 10 isolates were divided into two groups based on a genetic fingerprint in the vaa-hitABL intergenic region of isolates lacking vmp (Fig. 5). The genetic fingerprint was an insertion/deletion in the intergenic regions downstream to vaa. The vaa-hitABL intergenic region of isolate 93 was nearly identical to the corresponding region of isolate PG21, except for a deletion of approximately 300 bp shortly after the vaa terminator stem-loop structure (Δ1, Fig. 5). Two isolates (PG21 and 1621) gave the 2.2 kb downstream PCR product, whereas the remaining 8 isolates gave the 2 kb downstream PCR product of isolate 93 (Fig. 4B). The vmp type or absence of the vmp gene showed no correlation to the vaa type of the isolates. Surprisingly, the position of the vmp gene relative to the tRNA(His) gene was different for vmp-1 and vmp-2, the latter positioned between tRNA(His) and hitABL, whereas the more similar vmp-2 and vmp-3 genes were positioned identically (Fig. 5). A careful sequence analysis was performed on the insertion/deletion sites of the vmp genes to try to deduce a mechanism of insertion/deletion. The vmp-2 and vmp-3 genes seemed to be inserted at the poly-T tract in the 5' end and stem-loop terminator structure at the 3' end. When compared to the vaa-hitABL intergenic region of isolate PG21, the sequences flanking the insertion sites were identical in isolates 7488/4195 and PG21 and insertion did not result in deletion of part of the intergenic sequence. The insertion site was A/T rich, and sequence identity was observed in a small 8 bp thymidine-rich (vmp coding strand) sequence box between the insertion site in isolate PG21 and the stem region of the stem-loops of vmp-2 and vmp-3. Furthermore, a 165 bp deletion (Δ2 in Fig. 5) was observed in the vaa-tRNA(His) intergenic region of isolate 7488 compared to isolate PG21. This deletion was located immediately downstream to the region deleted in isolate 93. In contrast, analysis of the vmp-1 insertion site did not show insertion at the stem-loop and poly-T structures when compared to the vaa-hitABL intergenic regions of isolates PG21 and 93. Sequence regions of 60 bp downstream to the stem-loop structure and 90 bp upstream to the poly-T tract which did not show any homology to the vaa-hitABL intergenic region of isolate PG21 were observed at the borders of the vmp-1 gene. Interestingly, comparison of the insertion site of the vmp-1 region including the 60 bp and 90 bp bordering sequences with the vaa-hitABL intergenic region of isolate PG21 revealed that insertion resulted in a deletion in the intergenic sequence corresponding to the 300 bp deletion (Δ1 in Fig. 5) observed for isolate 93. The sequences flanking this region in isolate PG21 was A/T rich but did not show high homology to each other or to the insertion site of the vmp-2 and vmp-3 genes. In conclusion, no obvious direct or inverted repeat structures were observed indicating a mechanism of insertion other than homologous recombination. Isolates PG21 and 4195 shared identical vaa-hitABL intergenic regions outside the vmp-2 insertion (Fig. 5). These isolates carry distinct vaa gene types, PG21 having a three cassette vaa-1 type and 4195 having a two cassette vaa-3 type [13]. The distal 3' end cassette of these vaa genes shows high mutual similarity, whereas the remaining exchangeable cassettes of both genes are distinct (Fig. 5B). The 5' end including the first cassette of the vaa gene of isolate 4195 shows high similarity to the corresponding part of the vaa gene of isolate 132, harboring a different two cassette vaa gene type. The 3' end distal cassette of vaa from isolate 132 differs from that of isolates PG21 and 4195. Thus, the vaa type of isolate 4195 seems to be a chimera of the vaa types of isolates 132 and PG21 (Fig. 5B).
The GC content of the vaa and vmp genes of isolate 132 were 27% and 25% compared to a total of 25% for the 11.3 kb contig.
Characterization and detection of the Vmp protein
Alignments of the deduced Vmp-1 and Vmp-3 protein sequences revealed highest similarity in the C-terminal part (52% identity and 60% similarity in 382 aa). Half of this region was repeated once in Vmp-3 (Fig. 6B). The N-terminal part showed a lower, but significant overall similarity (33% identity and 41% similarity in 660 aa). In contrast, Vmp-2 and Vmp-3 showed almost complete conservation of the N-terminal part (93% identity in 1552 aa), whereas the C-terminal part showed a similarity corresponding to that between the Vmp-1 and Vmp-3 (55% identity and 69% similarity in 276 aa). The repeated region of Vmp-3 was only present in one copy in Vmp-2.
Sequence analysis revealed that the deduced Vmp proteins have a predominantly alpha-helical structure, and a coiled-coil region extending throughout almost the entire length of the proteins was identified (Fig. 6A and 6C). In Vmp-1 the coiled-coil motif extended from residues 35 to 1328 out of a total of 1404 residues. Likewise, the coiled-coil region of Vmp-2 spanned residues 28 to 1631 out of 1829 and residues 29 to 1869 out of 2168 residues of Vmp-3. The coiled-coil region contained numerous short disruptions of the predicted coiled-coil and alpha-helical structure (Fig. 6A and 6C). As this region showed high similarity to the Lmp proteins, the Lmp sequences were analysed for the presence of a coiled-coil region. Intriguingly, the Lmp proteins were shown to contain a coiled-coil region extending throughout most of the protein in analogy to the Vmps (data not shown).
A polyclonal antibody was raised against the distal C-terminal part of Vmp-1 from isolate 132 (Fig. 6B). This region shows low homology to the Vmp-2 and Vmp-3, and the antibody was applied in immunoblotting using antigen from 8 selected isolates (Fig. 7). The antibody reacted with a protein of 160 kDa from isolates 132, 5941, DC63 and SC4, in agreement with the predicted molecular weight of the protein encoded by the vmp-1 gene of these isolates. These data thus demonstrate that Vmp is expressed in M. hominis. Furthermore, the antibody reacted with a 100 kDa protein in all isolates except PG21. This is presumably a protein that has been shown previously to bind Ig-molecules unspecifically, and is not present in PG21 [25]. Apart from the 100 kDa protein the isolates PG21 and 93, having no vmp gene, and isolates 4195 and 7488 having a Vmp-2 and Vmp-3 type, respectively, did not react with the antibody, as expected from the low homology of the C-terminal region (Fig. 7).
Discussion
The presented analysis of the vaa locus reveals that it is a highly dynamic region of the M. hominis genome. The data indicate that variation in the 3' end of the vaa gene may be attributed recombinational events involving regions outside the gene. The insertion/deletion of the vmp gene downstream to vaa in different positions relative to the tRNA(His) gene, and the lack of correlation of vmp type and absence of vmp to vaa type suggests frequent recombination in this locus (Fig. 5). The finding that the two distinct vaa types of isolates PG21 and 4195 share 3' end cassettes and homologous downstream intergenic sequences, suggests that the vaa type of 4195 arose from intraspecies recombination (Fig. 5B). This event might have taken place between a M. hominis cell carrying a vaa type with a 5'end analogous to the vaa type of isolate 132 and a cell harboring a vaa type with a 3' end similar to that of PG21. Another M. hominis gene encoding a surface exposed lipoprotein, P120, was shown to contain a hypervariable and two semivariable domains [26]. This gene maps in close proximity to the vaa locus in the M. hominis genome (Fig. 1A). The groups of isolates carrying a specific hypervariable domain did not correlate with the vaa type [13,26]. Thus it is plausible that this region of the M. hominis genome harboring most of the characterized genes for membrane proteins is a genomic plasticity zone as previously suggested [18].
Based on these findings, recombination between different M. hominis subpopulations may be a general mechanism for the generation of antigen variation in this mycoplasma species. A necessity for intraspecies recombination is the transfer of DNA. No plasmids or phages have been observed for M. hominis, but the transfer of Tn916, presumably by conjugation, from a Streptococcus faecalis donor has been shown with low efficiency [27,28]. Conjugation between M. hominis cells has not been demonstrated. Chemically competent M. hominis were shown to be capable of uptake of homologous naked DNA. This was demonstrated by the transfer of tetracycline resistance from the DNA of a tetracycline resistant M. hominis isolate to a competent, sensitive isolate [29]. Thus, the knowledge regarding mechanisms of DNA uptake in M. hominis is sparse, and this subject needs to be addressed.
The location of vmp in close proximity to a tRNA gene is analogous to genetic elements of other bacteria. These elements, often referred to as genetic islets (<10 kb) or genetic islands (>10 kb), are variable sites when comparing genomes of different isolates of a given species. Often, genetic islets/islands carry pathogenesis factors and are specific for virulent clones of the species. Such factors include adhesins, toxins and restriction/modification systems. Frequently, the genetic elements are inserted into tRNA genes, show a GC content diverging from the surrounding regions and are flanked by repeated elements [30]. Although the vmp gene was located on either side of the tRNA(His) gene in isolates 132 and 7488, respectively, the GC content of vmp was similar to the remaining part of the vaa locus analyzed and the M. hominis genome in general (28%) and despite a thorough analysis, no obvious flanking structures such as direct or inverted repeats were observed which could indicate a site specific mechanism of insertion. Thus, the vmp gene may be mycoplasma specific and insertion/deletion of vmp at the vaa locus seems mediated by homologous recombination.
It was possible to amplify vmp fragments by PCR from four out of five isolates categorized as having a vmp-1 gene type and likewise for four out of five isolates having a vmp-2 or vmp-3 gene type. The pronounced heterogeneity observed between the vmp genes could explain the missing reaction of the remaining two isolates as being caused by sequence variation of the individual gene types as observed for a number of other M. hominis membrane protein genes, but it is also possible that additional vmp gene types exists.
The size and predicted structure of Vmp is interesting. The coiled-coil motif extending through most of the protein, is a highly versatile motif involved in protein-protein interactions [31]. This motif is found in proteins carrying out diverse functions such as structural proteins, transcription factors, translation factors and extracellular proteins [32]. The coiled-coil domains often mediate the oligomerization of proteins forming di-, tri-, tetra- or even pentamers [31]. Additionally, coiled-coil motifs in some cases are involved in intramolecular interactions forming highly stable, ridgid and compact structures. The length of the coiled-coil region in the primary structure of Vmp is comparable to that of eukaryotic class II myosins, proteins involved in movement along actin filaments [33]. Furthermore, a coiled-coil region of similar length was observed for the cytadherence related HMW2 protein of Mycoplasma pneumoniae. This protein is cytoplasmic, part of the primitive cytoskeleton of this mycoplasma and truncation of the gene resulted in loss of cytadherence [34]. HMW2 is believed to form dimers due to the coiled-coil region [35]. In contrast to HMW2, Vmp contains a C-terminal region having no coiled-coil motifs. Furthermore, a signal sequence involved in transmembrane translocation of proteins was identified in the Vmps, but not in HMW2. Thus, it is highly likely that the Vmp protein is located on the cell surface of M. hominis in contrast to the cytoplasmic HMW2.
The identification of a novel putative membrane protein displaying sequence variation is intriguing, and furthermore the remarkable size and structure displayed by the Vmp protein is interesting and should prompt investigations on the biological function of this protein in M. hominis.
Conclusions
We have demonstrated that in some isolates, the vaa locus of M. hominis contains a divergent genetic islet encoding a large, putative membrane protein called Variable membrane protein (Vmp). This genetic islet is only present in the locus of half of the 20 islolates tested, and three distinct, homologous Vmp types were observed. The composition of the locus was analysed and it was found that the vaa gene has a conserved upstream region and a highly variable downstream region, which contains the genetic islet. This locus organization corresponds to the organization of the vaa gene itself having a conserved 5' end and a variable 3' end. Thus, the mechanism underlying variation of the vaa gene seems to be intraspecies recombination exchanging variable regions of vaa and downstream regions of vaa, giving rise to a variable and dynamic 'hot spot' in the M. hominis genome.
Methods
Isolates and growth media
Twenty M. hominis isolates were analysed (PG21, 4195, 132, 5941, 1621, 7488, 93, 3105, 1572B, 2032B, 2347B, 7808, 7357, 4712, V2785, DC63, SC4, P2, 183, and P71). The M. hominis isolates were cultivated in BEa medium (heart infusion broth (Difco), 2.2% (w/v); horse serum, 15% (v/v); fresh yeast extract, 1.9% (w/v); benzylpenicillin, 40 IU ml-1; L-arginine, 0.23% (w/v); phenol red 0.0023% (w/v)). The pH of the medium was adjusted to 7.2 and the medium was sterilized by filtration [36]. The M. hominis isolates were harvested by centrifugation at 15,000 rpm for 45 min at culture volumes greater than 1.5 ml or at 20,000 rpm for 15 min for culture volumes smaller than 1.5 ml. E. coli OneShot competent cells and the pCRII plasmid vectors were used for TA-cloning (Invitrogen).
Pulsed field gel electrophoresis (PFGE)
PFGE was performed on genomic DNA from the five M. hominis isolates PG21, 4195, 132, 93 and 7488. The M. hominis isolates were grown in BEa medium to log phase and harvested. The cell pellets were washed and resuspended in PBS buffer (20 mM sodium phosphate, 250 mM NaCl, pH 7.4). Melted NA agarose (Amersham Pharmacia Biotech) was mixed with the cell suspension in a plastic mold on ice. The agaroseblocks hereby formed were incubated overnight with 1 mg/ml Proteinase K (Roche) in lysis buffer (1% Sarcosyl, 0.5 M EDTA, 10 mM Tris HCl, pH 9.5). Subsequently, each block was washed twice in lysis buffer followed by one wash in TE buffer (10 mM Tris HCl, 1 mM EDTA, pH 8.0) and cut into eight blocks of identical size. The blocks were digested overnight with 40 units of one of five restriction enzymes (SmaI, BamHI, XhoI, SalI, and ApaI) and 12 mg of BSA. Subsequently, the blocks were inserted into the slots of 1% NA agarose gels and the holes sealed with melted NA agarose. HindIII digested λ DNA and a λ DNA ladder (FMC) was used as molecular weight markers. The gels were used for PFGE using the CHEF-DRII separation system (Bio-Rad).
Preparation of DNA
DNA from the M. hominis isolates was isolated using the method described in [37]. Briefly, M. hominis cells were harvested and subsequently lysed on ice in a buffer containing 0.7% (w/v) N-laurylsarcocine, 10 mg RNase ml-1 (Sigma), 20 mM Tris pH 7.5 and 20 mM EDTA. Proteinase K (150 mg ml-1) was added and the cell lysate was incubated at 55°C for 2 hrs and 37°C for 1–2 hrs followed by phenol, phenol/chloroform and chloroform extractions [38]. DNA preparations from the isolates 1572B, 2032B and 2347B were made by Proteinase K (150 mg ml-1) treatment of harvested M. hominis at 55°C for 1 h. After the incubation the solution was heated to 100°C for 5 min to inactivate the enzyme. Plasmids from transformed E. coli were prepared as described in [38], for sequencing the phenol/chloroform extraction was omitted.
Southern blotting
PCR-products derived from different vaa types with sizes of 1220 bp (probe 1), 600 bp (probe 2), 800 bp (probe 3), and 660 bp (probe 4) were used for TA-cloning, performed according to manufacturers instructions (Invitrogen) [13]. Probe 1 contained most of the vaa-1 gene from M. hominis 7808, including the three cassettes III, IV and V [13]. Probe 2 contained the conserved 5' end and cassette III from the vaa-1 gene of M. hominis PG21 and probe 3 contained most of the vaa-3 gene of M. hominis V2785 including cassettes V and VII. TA-cloned PCR fragments or linear PCR fragments were used as DNA probes and labeled with radioactive (α-32P)dATP by nick-translation, performed as follows. 0.5–1 μg DNA was mixed with 1 × nick-translation buffer (50 mM Tris HCL (pH 7.2), 10 mM MgSO4, 0.1 mM DTT, 50 mg BSA, 60 mM of dTTP, dCTP, and dGTP respectively, 5 units of DNA polymerase I (Gibco), 0.5 ng DNase I (Roche), 20 mCi (α-32P)dATP (Du Pont) and ddH2O up to 50 μl. The reaction was incubated at 14–16°C for 1 h. Incorporation of radioactive nucleotides was verified by TLC and terminated by addition of TE-buffer with 0.5 M EDTA. The radioactive probes were denatured by heating to 100°C for 5 min and hybridization performed in 2 × SSC (1 × SSC is 0.15 M NaCl and 0.015 M sodium citrate), 0,5% SDS, 100 mg/ml yeast RNA, 5 × Denhardts solution (0.1% Ficoll, 0.1% BSA, 0.1% polyvinyl pyrollidone (Serva)) at 60°C in a hybridization oven. The membranes were washed in 6 × SSC and 0.5% SDS. The membranes were placed in sealed plastic bags and exposures of X-ray films were performed at room temperature or at -20°C.
Genomic DNA samples of the isolates PG21, 4195, 132, 93 and 7488 were cleaved with either HindIII or EcoRI and separated on 0.7% agarose gels. The gels were stained with ethidium bromide and photographed under UV irradiation. Preceding the alkaline denaturation, partial hydrolysis of the DNA in the PFGE gels was performed by soaking in a 0.25 M HCl solution to enhance the transfer of large DNA fragments. DNA transfer to Hybond-N membranes (Amersham Biosciences) was carried out as described in [38].
PCR
PCR was performed using the Expand™ High Fidelity PCR System from Roche according to the manufacturer's instructions, except for the amplification of the 1.2 kb vmp-2/3 PCR product where Taq polymerase was used (PE Biosystems). Custom oligonucleotide primers were purchased from DNA Technology (Aarhus, Denmark). PCR products were purified using the Wizard kit (Promega) according to manufacturers instructions. PCR conditions used for inverse PCR and amplification of downstream and upstream regions of the 20 isolates were as follows: 2 min at 92°C, 10 cycles of 10 s at 92°C, 30 s at 55°C, 8 min at 68°C, 20 cycles of 10 s at 92°C, 30 s at 55°C, 8 min at 68°C with 5 s added to the elongation time pr. cycle. Finally, an extension step of 7 min at 68°C was performed. The primers used for amplification of the 5.5 kb upstream product were F1 (CAGTACATGTTAATCCCAGAA GTATAGTTGG) and R1 (GCTGGATAATCGCCGTATGAACCTGC). The R1 primer was also used for amplification of the 4 kb and 0.6 kb PCR products in combination with the primers F2 (GGATCTTCTTTGTGGTCTTCC) and F3 (GGGATAGTTAGTAAAG TTGGAATAGCC), respectively. For amplification of the downstream region in the 20 isolates, the primers F4 (GCAGGTTCATACGGCGATTATCCAGC) and R4 (GCCACTTGCGGTTCTTCC) were used. For the amplification of the 0.6 kb vmp-1 PCR product, the primers F6 (CCACTGATACGTGATTTAAAAAGAAAAG) and R3 (GGTATTGTTTCTTTATCTAAGATGTTTTCAAATTC) were used with the following PCR conditions: 4 min at 94°C, 30 cycles of 15 s at 94°C, 30 s at 50°C, 1 min at 72°C and a final extension of 5 min at 72°C. For amplification of the 1.2 kb vmp-2/3 PCR product, similar conditions were used with an annealing temperature of 57°C and an elongation time of 2 min, and the primers were F5 (GAACAATTAAAAACATTAATTGGCTTAA GTGATG) and R2 (GTTTTATCTACATTGTTTTCGGATAAGG).
Restriction endonuclease analysis
The 5.5 kb upstream PCR products from the 20 analysed isolates were subjected to restriction endonuclease analysis employing the enzymes AluI and AseI (New England Biolabs) according to manufacturers instructions and analysed on 1 × TBE/2% agarose gels.
Sequencing
Sequencing reactions were carried out bidirectionally using the ABI PRISM Dye Terminator Cycle Sequencing Ready Reaction Kit (Perkin Elmer) on purified plasmid DNA (TA-cloned PCR products) or directly on the purified PCR products according to the instructions supplied by the manufacturer. Sequencing was performed on an ABI PRISM 377 DNA Sequencer from Perkin Elmer.
Cloning, expression and generation of polyclonal antibodies to a Vmp-1 fragment
Oligonucleotide primers (DNA technology, Aarhus, Denmark) were designed in order to amplify by PCR, the region of vmp-1 from isolate 132 encoding aa 1281 to 1404 of the Vmp-1 protein. Cloning and expression of the construct was performed using the pET-30 Ek/LIC vector according to manufacturers instructions (Novagen, Madison, USA). The His-tagged fusion protein was purified using a nickel chelated column (High Trap Sepharose, Amersham Pharmacia Biotech) under denaturing conditions as previously described [39]. Sera containing polyclonal antibody directed against the C-terminal Vmp-1 fragment was obtained by immunizing a rabbit three times intramuscularly with 20 mg of recombinant protein dissolved in Freunds complete adjuvant and three times intravenously with 20 mg protein dissolved in PBS. SDS-PAGE and immunoblotting were performed as previously described [13].
Computer analysis
Computer analysis of the obtained DNA sequences was performed using the Wisconsin Package Version 9.0, Genetics Computer Group (GCG), Madison, Wisc., sequence analysis software package [40]. Data base searches were performed using both NetBlast and FastA. Furthermore, the programs SignalP and TMHMM, both found at the website , were used to predict signal sequences and transmembrane helices, respectively [23,24]. Energy of putative rho-independent stem-loop terminator structures was calculated using the RNA mfold server at [41].
Accession numbers
The DNA sequences obtained in this study were deposited to the EMBL database under the following accession numbers: AJ416752, AJ545046 AJ629113, AJ629114 and AJ629115.
Authors' contributions
The individual parts of the work presented in the paper were conducted as follows: The ideas and designs of the experiments were developed by all the authors. Pulsed field gel electrophoresis and Southern blottings were performed by JE and TB. PCR, sequencing, and sequence analysis were performed by TB and AB. The fusion protein, polyclonal antisera and immunoblotting were made by TB. The manuscript was primarily written by TB and discussed with and approved by all authors.
Supplementary Material
Additional File 1
Multiple sequence alignment. Alignment of the three Vmp types and Lmp1 and Lmp3 from type strain PG21 using ClustalW.
Click here for file
Acknowledgements
This work was supported by the Danish Health Research Council (Grant 12-1620-1), Aarhus University Research Foundation, Novo Foundation, a Ph.D.-grant from the Faculty of Health Sciences, University of Aarhus (TB) and a grant from Vejle Amt (AB). We thank Inger Andersen and Karin Skovgaard for excellent technical assistance.
Figures and Tables
Figure 1 Mapping the vaa gene. The vaa gene was mapped on existing physical and genetic maps using pulsed field gel electrophoresis and Southern blotting [8]. A: the location of the vaa gene on the physical maps of five M. hominis isolates PG21, 4195, 132, 93 and 7488. The vaa gene mapped to the same genomic region for all isolates (shown in red). B: Pulsed field gel electrophoresis and Southern blotting results used for mapping of vaa in M. hominis 7488. Digests of four out of five enzymes used is shown. The probes 1 to 3 are denoted P1 to 3. The sizes of the bands reacting with the probes are indicated on the left side of the figure.
Figure 2 Restriction endonuclease analysis (REA) of the vaa locus. Southern blottings of HindIII cleaved genomic DNA of the 5 isolates separated by agarose gel electrophoresis and probed with sequences specific for the 5' end (probe 2, frame A) and 3' end (probe 4, frame B) of vaa, respectively.
Figure 3 Schematic drawing of the vaa locus of isolate 132. A: Restriction map of the vaa locus showing the cleavage sites for BglII (B), EcoRI (E) and HindIII (H). Fragments amplified by inverse PCR are shown as thick lines above the restriction map. B: Open reading frames of the vaa locus. The vaa gene is shown as a red arrow and show opposite transcriptional direction compared to the other ORFs. C: The PCR products amplified from isolate 132 are shown in cyan (upstream fragment) and purple (downstream fragment).
Figure 4 Up- and downstream PCR analysis of 20 M. hominis isolates and vmp PCR. A, Top: Schematic illustration of the open reading frames (indicated by open arrows) of the vaa locus of M. hominis isolate 132. Bottom: The position relative to the open reading frames of the primers used (indicated by small arrows). B, Agarose gel electrophoresis of the PCR reactions obtained using vaa upstream primer sets (F1, R1), (F2, R1) and (F3, R1) on the 20 M. hominis isolates indicated above the bands. The size of the PCR products and primer set used are indicated to the left. C, D and E, PCR reactions observed using the vaa downstream primer sets (F4, R4), (F6, R3) and (F5, R2), respectively. The (F6, R3) primer set was derived from vmp-1 and the (F5, R2) primer set (green arrows) was derived from the vmp-2 and vmp-3 genes of isolates 4195 and 7488. Isolates categorized as having vmp-1, vmp-2 and vmp-3 genes are indicated with green, orange and magenta coloring of letters, respectively.
Figure 5 Variation of the vaa downstream region. A: Schematic drawing of the sequenced vaa-hitABL intergenic regions of the five isolates. Genetic fingerprints consisting of deletions (Δ1–2) and insertions (▼) of 90 bp upstream and 60 bp downstream to vmp-1 are shown. Identical vaa downstream regions were shared between isolates 4195 and PG21. The vaa gene categories are indicated by suffix -1, -3 or -2. B: Schematic comparison of the Vaa types of isolates PG21, 4195, and 132. The exchangeable cassettes are numbered III, IV, V, VII, and VIII, respectively. The percentages of identical residues between different parts of the proteins are shown.
Figure 6 Comparison of Vmp-1 and Vmp-2. A and C: the predicted coiled-coil regions of Vmp-1 and Vmp-2, respectively. A threshold value of 0.5 is shown as a vertical dashed line. B: The identity (similarity) displayed by regions of the Vmp proteins. The C-terminal regions of the protein showed high mutual similarity. Green bars are shown below the repeated sequence of Vmp-2. A red bar indicates the fragment specific for Vmp-1 used for generation of a polyclonal antibody.
Figure 7 Detection of Vmp-1. Immunoblotting of selected isolates using the polyclonal antisera generated against the C-terminal part of Vmp-1 from isolate 132. Isolates 132, 5941, DC63 and SC4 show a sharp band around 160 kDa, thus demonstrating the expression of Vmp-1 in these isolates. The polyclonal antiserum additionally reacted with multiple bands around 100 kDa. These bands probably corresponds to a ~100 kDa M. hominis protein which previously has been shown to bind Ig-molecules unspecifically. This protein has not been observed in PG21. The right panel shows the coomassie stained, recombinant Vmp-1 C-terminal fragment used for immunization.
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| 15385054 | PMC524362 | CC BY | 2021-01-04 16:03:38 | no | BMC Microbiol. 2004 Sep 22; 4:37 | utf-8 | BMC Microbiol | 2,004 | 10.1186/1471-2180-4-37 | oa_comm |
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Thromb JThrombosis Journal1477-9560BioMed Central London 1477-9560-2-71545651310.1186/1477-9560-2-7Original Clinical InvestigationRelationship between CRP and hypofibrinolysis: Is this a possible mechanism to explain the association between CRP and outcome in critically ill patients? Zouaoui Boudjeltia Karim 1kaveroes@hotmail.comPiagnerelli Michael 2michael.piagnerelli@ulb.ac.beBrohée Dany 1dany.brohee@chu-charleroi.beGuillaume Michel 3michel.guillaume@chu-charleroi.beCauchie Philippe 1Philippe.Cauchie@chu-charleroi.beVincent Jean-Louis 2jlvincen@ulb.ac.beRemacle Claude 4remacle@bani.ucl.ac.beBouckaert Yves 5ybouckae@ulb.ac.beVanhaeverbeek Michel 1michel.vanhaeverbeek@chu-charleroi.be1 Experimental Medicine Laboratory, ULB 222 Unit, ISPPC, CHU A. Vésale, Montigny-le-Tilleul, Belgium2 Dept of Intensive Care Medicine, Erasme Hospital, Free University of Brussels, Belgium3 Dept of Cardiology, ISPPC, CHU A.Vésale, Montigny-Le-Tilleul, Belgium4 Institute of life sciences, Laboratory of cellular Biology, Université Catholique de Louvain, Louvain-La-Neuve, Belgium5 Dept of Intensive Care Medicine, Tivoli Hospital, La Louvière, Belgium2004 30 9 2004 2 7 7 11 8 2004 30 9 2004 Copyright © 2004 Boudjeltia et al; licensee BioMed Central Ltd.2004Boudjeltia 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-
Endothelial cell dysfunction may be implicated in the development of multiple organ failure (MOF) by a number of mechanisms. Among these, altered fibrinolysis promotes fibrin deposition, which may create microvascular alterations during inflammation. Elevated concentrations of C-reactive protein (CRP), especially when these persist over time, are correlated with an increased risk of MOF and death. CRP may inhibit fibrinolysis by inducing plasminogen activator inhibitor-1 (PAI-1) release from human aortic endothelial cells. Moreover, the administration of recombinant CRP in volunteers may increase circulating PAI-1 levels.
In this study, we tested the hypothesis that CRP is associated with hypofibrinolysis in intensive care patients with and without sepsis.
Methods-
We studied the association of inflammation and abnormal fibrinolysis in intensive care unit (ICU) patients with (n = 11) and without (n = 21) sepsis. The inflammatory response was assessed by serum concentration of C-reactive protein (CRP), a marker of the acute phase reaction, which increase rapidly in the inflammatory response, and the plasma fibrinolytic capacity was evaluated by the Euglobulin Clot Lysis Time (ECLT), determined by a new semi-automatic method.
Results-
ECLT was significantly higher in septic than non-septic patients (1104 ± 439 vs 665 ± 275 min; p = 0.002) and was significantly correlated with CRP concentration (R2 = 0.45; p < 0.001). In a multivariate analysis, CRP was the strongest predictor of ECLT (R2 = 0.51, F = 25.6, p < 0.001). In addition, the overall ICU length of stay was significantly correlated with CRP (R2 = 0.264, p = 0.003) and ECLT (R2 = 0.259, p = 0.003).
Conclusion-
In critically ill patients a significant correlation thus exists between plasma fibrinolytic capacity and serum CRP levels. Our data were obtained in the first 24 hours of ICU admission or of sepsis, thus, the relation between CRP and hypofibrinolysis appeared very quickly. This finding is compatible with a link between inflammation and abnormal fibrinolysis, and may explain the negative prognostic value of CRP in critically ill patients.
C-reactive proteinacute phase reactanteuglobulin clot lysis timeinflammationsepsisendothelium dysfunction.
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Background
Endothelial cells have a key role in the control of vascular permeability and vessel tone, coagulation and fibrinolysis, and inflammatory response [1]. There is an increasing body of evidence supporting the critical role of the vascular endothelium in the pathogenesis of multiple organ failure (MOF) in critically ill patients [2].
Endothelial dysfunction/or activation is associated with an imbalance in hemostatic functions. Endothelial cells are responsible for the release of tissue plasminogen activator (t-PA) and contribute to the release of plasminogen activator inhibitor-1 (PAI-1). Inhibition of the fibrinolytic system amplifies the pathogenic role of fibrin deposition during severe inflammation [3]. Multiple factors, including lipoproteins, cytokines, and inflammatory proteins can modulate the endothelial cells to produce t-PA and PAI-1 [4].
In infected patients, elevated concentrations of serum CRP are correlated with a risk of MOF and death [5], especially when these persist over time [5]. However, the possible biological involvement of CRP in the development of MOF and death is unknown.
CRP can act directly on endothelial cells, inducing, for example, the expression of intercellular adhesion molecule (ICAM)-1 [6] and the production of inflammatory cytokines such as interleukin- (IL)-6 [7]. It may also inhibit fibrinolysis by inducing PAI-1 release from human aortic endothelial cells [8]. Moreover, the administration of recombinant CRP in volunteers may increase circulating PAI-1 levels [9].
In this study, we tested the hypothesis that CRP is associated with hypofibrinolysis as measured by ECLT in intensive care patients with and without sepsis.
Material and methods
Subjects
After approval by the A. Vésale hospital ethics committee, we studied 32 ICU patients with severe sepsis (n = 11) or other diagnoses (n = 21). Infection definition required isolation of a microorganism from a normally sterile body site, concurrent with accompanying signs and symptoms of sepsis and decision of antibiotic therapy. Criteria for severe sepsis included signs of at least one organ dysfunction attributed to sepsis [10]. All patients (septic and non-septic) were enrolled in the first day of ICU admission to limit the delay of inflammatory response. The exclusion criteria were: antibiotics treatment in the non-septic group except for surgical prophylaxis, red blood cell transfusion in the last 72 h, active hemorrhage, hematological disorders, recent cytotoxic chemotherapy, burns, cardiogenic shock, cirrhosis, pregnancy. The simplified acute physiologic score (SAPS II score) [11] was determined in each patient during the first 24 hours after admission.
Blood samples
Blood samples were obtained during the first 24 hours of sepsis or on the first day of admission for non-septic patients. Serum samples were collected in vacuum tubes without anticoagulant. Plasma samples were harvested in citrated vacuum tubes and put in melting ice. Whole blood was collected on EDTA-treated tubes. CRP was evaluated by antibody-binding and turbidity measurement on SYNCHRON LX®. Fibrinogen was determined by thrombin time on a STA® automate (STAGO). Leukocyte and platelet counts were determined on a hemocytometer (CELL-DYN4000®, ABBOTT). All tests were performed on blood obtained from the same venipuncture.
Plasma fibrinolytic capacity
The Euglobulin Clot Lysis Time (ECLT), which is the most common test used to estimate the plasma fibrinolytic capacity, represents the balance between t-PA and PAI-1 activities [12]. ECLT was measured on fresh plasma the same day as other parameters by a method described elsewhere [13]. Briefly, we designed a completely computerized, semi-automatic, 8-channel device for measurement and determination of fibrin clot lysis (Lysis Timer, EREM, Belgium). The lysis time is evaluated by a mathematical analysis of the lysis curve and the results are expressed in minutes (range: 5 to 9999). The efficiency scores of the method are <4% in intra-assay and <7% in inter-assay.
Statistics
We used SigmaStat® software package (Jandle Scientific). The data are presented as mean ± SD. Correlation between variables was analyzed using a Pearson correlation test. A multivariate analysis was used with stepwise backward selection of the explicative variables. Sepsis was considered as a dichotomous variable while all other data were considered as continuous (CRP, fibrinogen, leukocyte, monocyte and platelet counts). ECLT was the dependent variable. A probability level of p < 0.05 was considered as statistically significant.
Results
The major cause of severe sepsis (9 patients) or septic shock (2 patients) was pneumonia (8 patients); angiocholitis was the cause in 1 patient, and in 2 patients the cause was not identified. In 8 patients (7 with pneumonia and 1 with angiocholitis), the infection was due to a Gram negative bacteria. Only 1 patient had documented bacteremia. Non-septic patients were admitted for postoperative surveillance (7 patients), intracerebral hemorrhage (3 patients), heart failure (3 patients), drug intoxication (3 patients), or aggravated chronic obstructive pulmonary disease (5 patients).
As expected, inflammatory parameters such as white blood cells and CRP levels, the SAPS II score and ECLT were higher in the septic than the non-septic population (Table 1). In an univariate analysis (in all patients), the ECLT was strongly correlated with serum CRP concentrations (R2 = 0.45; p < 0.001) with no perceptible threshold (Fig 1). Surprisingly, there was no relationship between the SAPS score and ECLT (R2 = 0.08; p = 0.15). In multivariate analysis, ECLT was best predicted by the CRP level (R2 = 0.51; F = 25.6; p < 0.001) and not significantly by sepsis or the fibrinogen concentration. Interestingly, the ICU length of stay was significantly correlated with CRP (R2 = 0.264, p = 0.003) and ECLT (R2 = 0.259, p = 0.003) in all patients, and in the survivors (R2 = 0.13, p = 0.05 and R2 = 0.3, p = 0.003, respectively).
Table 1 Population characteristics
Sepsis (n = 11) Non-sepsis (n = 21) p value
Age, years 68 ± 19 67 ± 17 0.95
SAPS II 47 ± 11 25 ± 14 0.001
ICU stay, days 11.6 ± 7.8 6.7 ± 6.8 0.07
Death, n (%) 2 (18) 3 (14) 0.57
Leukocytes (×103 cells/μl) 10.4 ± 4.5 10.9 ± 3.7 0.74
Monocytes (×103 cells/μl) 549 ± 225 711 ± 398 0.24
Platelets (×103 cells/μl) 207 ± 157 234 ± 94 0.54
Fibrinogen (mg/dl) 657 ± 123 445 ± 132 <0.001
CRP (mg/dl) 24.2 ± 10.5 7.6 ± 6.1 <0.001
ECLT (min) 1104 ± 439 665 ± 275 0.002
Mean ± SD; p value (t-stest).
SAPS : Simplified Acute Physiologic Score; ICU : Intensive Care Unit; CRP : C-Reactive Protein;
ECLT : Euglobulin Clot Lysis Test
Figure 1 Correlation between serum CRP levels and Euglobulin Clot Lysis Time.
Discussion
Many studies have demonstrated that sepsis is associated with endothelial cell dysfunction and promotes coagulation activation [14]. Although levels of t-PA antigen increase in sepsis, fibrinolysis is inhibited by increased levels of PAI-1. ECLT is, therefore, an interesting test, because it represents the balance between t-PA and PAI-1 activities. Previously considered as an imprecise method, we have been able to improve the precision and reproducibility of the test with a new semi-automatic device [13].
Inhibition of the fibrinolytic system may contribute to MOF, as fibrin can activate endothelial cells leading to a disorganization of the monolayer and the release of inflammatory cytokines [4]. Increased CRP levels are associated with worse outcomes and MOF in ICU patients [3]. The role of CRP on fibrinolysis is unknown in vivo. Our data suggest that CRP could itself be involved in the processes leading to endothelium dysfunction. The observed relationship does not prove a direct biological link between increasing CRP and hypofibrinolysis; however, indirect arguments exist in support of the concept.
Several in vitro studies have reported the direct effects of CRP on endothelial cells [6-8]. In vivo, Cleland et al. [15] reported a relationship between serum CRP levels and the forearm blood flow response to NG-monomethyl-L-arginine (L-NMMA), reflecting endothelial dysfunction. Bisoendial et al. reported that the administration of CRP in volunteers impairs the fibrinolytic balance [9]. In addition, CRP has a strong prognostic value in acute coronary syndromes [16]. In a non-selected population with no inflammatory syndrome (CRP below 1.5 mg/dl, n = 160), we also observed that ECLT was significantly correlated with serum CRP levels [17].
CRP could also act indirectly on endothelial cells via the action of monocytes and the release of tumor necrosis factor-α (TNF-α). TNF-α is a strong inducer of PAI-1 production in-vitro and in-vivo. This mechanism seems to be important in sepsis, as high plasma levels of PAI-1 are associated with poor outcome [18]. Moreover, an association between CRP and TNF-α has also been described [19]. CRP can induce the monocyte release of cytokines such as IL-1β, IL-6, and also TNF-α through Fc receptors (γRI/CD64, FcγRIIa/CD32) [20].
CRP also has essential biological functions. No polymorphism of either the gene coding sequence or of the protein itself has been described in humans [21]. Also, high levels of human CRP protect against lethal infection. Transgenic mice capable of produce human CRP are protected against lethal infection by Gram positive and negative bacteria, Szalai et al [22,23].
This work is a pilot study. We have chosen to include patients in the first day of ICU admission to limit the possible rapid effect of inflammatory response on fibrinolysis, especially in septic patients. Indeed, this particular patient population has inflammatory reaction before signs of severe sepsis and thus before their admission to ICU. In fact, we have studied ECLT test at the onset of the organ dysfunction and the inflammatory reaction. Other studies with serial measurement of ECLT in patients who developed nosocomial ICU infections are needed to study the time course of these events. Moreover, we could not definitively exclude that all patients in the non-septic groups were non infected. For example, some non-septic patients with decompensated COPD may have minor infections, despite the negative microbiology cultures and the absence of antibiotic therapy. Viral infections were also possible in some patients.
Moreover, it would be of great interest to determine the interactions between CRP and ECLT with IL-6, TNF-α and endothelium dysfunction markers such as soluble thrombomodulin and soluble von Willebrand factor.
Conclusion
Despite accumulating evidence that the inflammatory and coagulation systems are activated in sepsis, little is known about the mechanisms that ultimately lead to organ dysfunction and death. Our data were obtained in the first 24 hours of ICU admission or of sepsis, thus, the relation between CRP and hypofibrinolysis appeared very quickly. Prospective studies including the time course of CRP and hypofibrinolysis would provide additional information about this relationship.
Authors' contributions
KZB: Laboratory analysis, writing of the manuscript and design of the study.
MP: patients recruitment and design of the study.
DB: coordination and design analysis of the results.
MG: design of the study.
PC: laboratory analysis.
JLV: design of the study and analysis of the results.
CR: design of the study and analysis of the results.
YB: patients recruitment.
MV: statistical analysis and coordination.
Acknowledgements
This work was supported by grants from the Intercommunale de Santé Publique du Pays de Charleroi (Experimental Medicine Laboratory) and from the Erasme Foundation (M. Piagnerelli).
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| 15456513 | PMC524363 | CC BY | 2021-01-04 16:36:20 | no | Thromb J. 2004 Sep 30; 2:7 | utf-8 | Thromb J | 2,004 | 10.1186/1477-9560-2-7 | oa_comm |
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Nucl ReceptNuclear Receptor1478-1336BioMed Central London 1478-1336-2-71547947710.1186/1478-1336-2-7ResearchThe evolution of drug-activated nuclear receptors: one ancestral gene diverged into two xenosensor genes in mammals Handschin Christoph 12christoph_handschin@dfci.harvard.eduBlättler Sharon 1sharon.blaettler@unibas.chRoth Adrian 1adrian.roth@unibas.chLooser Renate 1renate.looser@unibas.chOscarson Mikael 1mikaeloscarson@yahoo.seKaufmann Michel R 1michel.kaufmann@unibas.chPodvinec Michael 1michael.podvinec@unibas.chGnerre Carmela 13carmela.gnerre@actelion.comMeyer Urs A 1urs-a.meyer@unibas.ch1 Division of Pharmacology/Neurobiology, Biozentrum of the University of Basel, Klingelbergstrasse 50-70, CH-4056 Basel, Switzerland2 (Present Address) Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA3 (Present Address) Actelion Pharmaceuticals Ltd., CH-4123 Allschwil, Switzerland2004 12 10 2004 2 7 7 8 9 2004 12 10 2004 Copyright © 2004 Handschin et al; licensee BioMed Central Ltd.2004Handschin 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
Drugs and other xenobiotics alter gene expression of cytochromes P450 (CYP) by activating the pregnane X receptor (PXR) and constitutive androstane receptor (CAR) in mammals. In non-mammalian species, only one xenosensor gene has been found. Using chicken as a model organism, the aim of our study was to elucidate whether non-mammalian species only have one or two xenosensors like mammals.
Results
To explore the evolutionary aspect of this divergence, we tried to identify additional xenobiotic sensing nuclear receptors in chicken using various experimental approaches. However, none of those revealed novel candidates. Ablation of chicken xenobiotic receptor (CXR) function by RNAi or dominant-negative alleles drastically reduced drug-induction in a chicken hepatoma cell line. Subsequently, we functionally and structurally characterized CXR and compared our results to PXR and CAR. Despite the high similarity in their amino acid sequence, PXR and CAR have very distinct modes of activation. Some aspects of CXR function, e.g. direct ligand activation and high promiscuity are very reminiscent of PXR. On the other hand, cellular localization studies revealed common characteristics of CXR and CAR in terms of cytoplasmic-nuclear distribution. Finally, CXR has unique properties regarding its regulation in comparison to PXR and CAR.
Conclusion
Our finding thus strongly suggest that CXR constitutes an ancestral gene which has evolved into PXR and CAR in mammals. Future studies should elucidate the reason for this divergence in mammalian versus non-mammalian species.
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Background
A gene superfamily of heme-proteins, the cytochromes P450 (CYP), encodes the main enzymatic system for metabolism of structurally diverse lipophilic substrates [1]. A subset of these CYPs can be activated or inhibited in the liver by a variety of xenobiotic and endobiotic compounds. Transcriptional activation of these CYPs is part of an adaptive response to exposure to drugs and other xenobiotics and has major clinical and toxicological implications. The enzymatic capacities of the affected CYPs are changed, leading to an altered metabolic profile in the liver [2]. The barbiturate phenobarbital (PB) is prototypical for a class of compounds that induce or repress hepatic CYPs and many other genes [3]. PB-responsive enhancer units (PBRU) have been identified in the 5'-flanking regions of several of these CYPs and transcription factors binding to those units could be isolated (reviewed in [4-7]). In mammals, the pregnane X receptor (PXR, official nomenclature NR1I2) and the constitutive androstane receptor (CAR, NR1I3), both belonging to the gene superfamily of nuclear receptors, have been identified to be involved in hepatic drug-induction [8-12].
Strikingly, in contrast to the two xenobiotic-sensing nuclear receptors in mammals, only one xenosensor has been found in non-mammalian species, e.g. chicken [13], fish (fugu Fugu rubripes [14] and zebrafish Danio rerio [15]) or the nematode Caenorhabditis elegans [16]. The amino acid sequence of the full-length chicken xenobiotic receptor (CXR, NR1I3) is about equally related to those of mammalian PXRs and CARs [17]. Moreover, chicken CXR and mammalian PXR and CAR as well as drug-inducible CYP enhancer elements from these species could be freely interchanged in transactivation and electrophoretic mobility shift assays suggesting evolutionary conservation of the fundamental hepatic drug-induction mechanisms from birds to man [18].
In this report, we studied the evolutionary aspects of these findings. Despite using various methods and techniques, we were unable to isolate further genes that encode chicken xenobiotic-sensing nuclear receptors confirming the hypothesis that non-mammalian genomes only have one xenosensor gene. Since PXR and CAR exhibit different typical features concerning their activation, localization and regulation [6,19], we examined the properties of CXR to see whether on the functional and structural level, the chicken xenosensor shares common aspects with one or both of the mammalian receptors. Our findings give important insights the evolution of hepatic detoxification systems that protect different species from toxic compounds in their particular diet and environment.
Results and Discussion
Orthologs of PXR and CAR have been isolated from man, monkey, pig, dog, rabbit, mouse and rat [15]. In non-mammalian species, only one xenosensor gene is found and sequence-wise, the corresponding receptors from chicken, zebrafish, fugu fish and C. elegans are about equally related to the mammalian PXRs and CARs (Fig. 1A). Of the 18 nuclear receptors in the fruitfly Drosophila melanogaster genome, DHR96 shares considerable similarity to the xenosensors but the functions of this receptor have not been elucidated yet. Although the African clawed frog Xenopus laevis has two nuclear receptors, benzoate X receptor α and β (BXRα/β, NR1I2), that are related to the xenobiotic-sensing nuclear receptors, the BXRs are pharmacologically distinct from PXR and CAR and do not respond to xenobiotics [15,20]. No drug-sensing nuclear receptors have thus been isolated in amphibians so far. Figure 1A shows the phylogeny of the xenobiotic-sensing nuclear receptors from different species. The completion of the rat genome allowed a global analysis of the nuclear receptors from three mammalian species, man, mouse and rat. In the nuclear receptor subfamily NR1I which includes the 1,25-dihydroxyvitamin D3 receptor (VDR, NR1I1) in addition to PXR and CAR, intron-exon junctions are highly conserved [21]. Human and rodent CARs and PXRs have the same number of introns. Moreover, apart from one intron which is found in the variable region 5' of the DNA-binding domain, all other seven introns are located in the same position on the corresponding genes, even in the ligand-binding domains that in the case of CAR and PXR are unusually divergent for nuclear receptor orthologs [22]. Using a chicken genomic library, we isolated the gene encoding CXR and analyzed its structure. Again, the number of introns in the CXR coding sequence was the same as those in the mammalian xenosensors and the intron-exon junctions occur at the same locations (Figure 1B). The apparent conservation of gene structures between the single chicken xenosensors and the two mammalian orthologs suggest a close relationship between these receptors and supports the hypothesis that CXR constitutes an ancestral gene in chicken from which two receptors diverged in mammals.
Figure 1 Phylogeny of xenobiotic-sensing nuclear receptors from different species. A, A non-rooted phylogenetic tree depicts the relationship between mammalian CARs and PXRs and non-mammalian intermediate receptors. The scale bar represents 0.1 amino acid substitutions per site. B, The sites of intron-exon junctions in the coding regions of CXR, PXR and CAR are highly conserved as depicted in an alignment of the amino acid sequences of these receptors.
To further test this hypothesis, we used different experimental approaches in order to isolate additional chicken xenobiotic-sensing nuclear receptors. Neither high- and low-stringency screening of a chicken liver cDNA library using CXR, CAR and PXR fragments as probes nor PCR-based strategies with degenerate primers designed on CAR and PXR alignments or degenerate primers based on generic nuclear receptor DNA-binding domains [23] resulted in the identification of novel chicken xenobiotic-sensing receptors (data not shown). The sequences of the previously unknown chicken orthologs for estrogen-related receptor γ (ERRγ, NR3B3) and a partial fragment of ear2 (NR2F6) that were found in these screens have been deposited (Genbank accession numbers AY702438 and AY702439, respectively).
If CXR in fact is the only chicken xenobiotic-sensing nuclear receptor, ablation of CXR expression or function is predicted to drastically reduce drug-induction of CYPs and other target genes. To reduce CXR expression, we designed RNAi oligonucleotides targeting CXR and stably expressed those in the chicken hepatoma cell line leghorn male hepatoma (LMH). LMH cells express endogenous CXR and retain induction of genes by PB-type inducer compounds and other drugs [18]. As shown in Figure 2A, endogenous mRNA levels of CXR were reduced about 60% by the RNAi. LMH cells expressing either control vector or CXR RNAi were subsequently transfected with drug-responsive enhancer elements from CYP2H1 [17], CYP3A37 [24], CYP2C45 [25] and δ-aminolevulinate synthase (ALAS-1) [26] and treated with vehicle or 400 μM PB for 16 hours. ALAS-1 is the first and rate-limiting enzyme in heme biosynthesis and its transcription is regulated by a variety of factors and stimuli, including PB-type inducers and other drugs [26,27]. In the case of ALAS-1, the 2-fold PB-induction was completely abolished by the CXR RNAi (Figure 2E). In contrast, PB-activation of the CYP2H1, CYP3A37 and CYP2C45 PBRUs was only partially reduced by 50 to 60% (Figure 2B,2C,2D). In these cases, reduction of CXR levels by 60% might not be enough. Alternatively, these findings could also be explained by the presence of additional drug-sensing signalling mechanism independent of CXR.
Figure 2 Reduced drug-induction of drug-responsive enhancer elements from CYP2H1, CYP3A37, CYP2C45 and ALAS1 in LMH cells stably expressing CXR RNAi. A, mRNA levels of endogenous CXR in LMH cells expressing pSUPER expression vector or CXR RNAi. CXR levels were measured by real-time PCR in LMH cells that stably express control vector or CXR RNAi. B–E, Phenobarbital-induction of drug-responsive enhancer elements from CYP2H1 (B), CYP3A37 (C), CYP2C45 (D) and ALAS1 (E) in LMH cells expressing pSUPER or CXR RNAi. LMH cells were transfected with the reporter gene plasmids and subsequently treated with vehicle or 400 μM PB for 16 hours before reporter gene levels were determined.
Thus, we used an alternative method that aimed at reducing CXR activity by designing dominant-negative CXR alleles. These CXR mutants were then tested in reporter gene assays on drug-responding enhancer elements. In our case, we generated three different CXR alleles (Figure 3A): first, we deleted the N-terminus since in some nuclear receptors, this part harbours a ligand-independent activation domain AF-1 [28,29]. Second, site-directed mutagenesis of the cysteine residues in the zinc-fingers of the DNA-binding domain results in a CXR mutant that is expected to lack DNA-binding but to retain its ability to bind activators and to heterodimerize with its partner retinoid X receptor (RXR, NR2B1/2/3). Third, helix 12 in the ligand-binding domain was deleted which harbours a ligand-dependent activation domain AF-2. Nuclear receptors that act as dominant-negative alleles due to the absence of a functional AF-2 domain have been observed in some diseases (e.g. see refs. [30,31]). These findings were subsequently used to generate various dominant-negative nuclear receptor mutants for cellular assays [32].
Figure 3 Drug-induction of the 264-bp PBRU is abolished by a dominant-negative CXR allele. A, CXR was subcloned into the pHook-2 expression plasmid (Hook-2) either full-length CXR in positive orientation (CXR+), negative orientation (CXR-), lacking its N-terminal amino acids 1–29 (ΔN-term), full-length CXR with four of its cysteine residues (cysteine 31, 34, 83 and 86) in the DNA-binding domain mutated (DBD) or lacking its C-terminal amino acids 383–391 containing the activation function AF-2 (ΔAF2). B, Electrophoretic mobility shift assays with mock in vitro transcribed/translated reticulocyte lysate (lane 1), expression plasmid pHook-2 (lane 2) and either expression plasmids for the different CXR alleles alone (lanes 3–7) or together with a pSG5-expression plasmid for chicken RXRγ (lanes 8–12). The arrow indicates the specific shift of CXR/RXR complexes with the radiolabeled CYP2H1 264-bp PBRU. C, pHook-2 expression plasmids without insert or containing the various CXR alleles were co-transfected with the CYP2H1 264-bp PBRU in the pBLCAT5 reporter vector as well as a lacZ-expression vector for normalization of transfection efficiencies into non-drug responsive CV-1 cells. After transfection, the cells were treated with either vehicle or 400 μM PB for 24 hours before cells were lysed and analysed for reporter gene expression and β-galactosidase expression. Values are the average of the relative CAT expression normalized for β-galactosidase levels of three independent experiments and error bars represent the standard deviation. D, pHook-2 expression plasmids without insert or containing the various CXR alleles were co-transfected with the CYP2H1 264-bp PBRU in the pBLCAT5 reporter vector into drug-responsive LMH cells expressing endogenous CXR. After transfection, the cells were treated with either vehicle or 400 μM PB for 24 hours before cells were lysed and analysed for reporter gene expression and β-galactosidase expression. Values are the average of the relative CAT expression normalized for β-galactosidase levels of three independent experiments and error bars represent the standard deviation.
First, the three CXR mutants were tested for their ability to bind to and activate a 264-bp PBRU isolated from the 5'-flanking region of chicken CYP2H1 [17,33]. As shown in electrophoretic mobility shift assays (Figure 3B), CXR can heterodimerize with RXR and bind to the 264-bp PBRU as wild-type, full-length receptor and when the N-terminal region from amino acid 1–29 (called ΔN-term) or the C-terminal region from amino acid 383–391 (referred to as ΔAF-2) are deleted, respectively (Figure 3B, lanes 8, 10 and 12). As expected, site-directed mutagenesis of four cysteine within the DNA-binding domain into alanine residues (denominated DBD) that participate in forming the zinc-finger domains abolishes protein-DNA interaction (lane 11). These results show that removal of the N-terminus or the C-terminus of CXR does not influence its binding to DNA. Subsequently, the CXR mutants were tested in CV-1 transactivation assays for functionality. The CV-1 monkey kidney cells constitute an excellent tool to study nuclear receptor function in a cellular system which does not express endogenous xenosensors, is not drug-inducible and thus has a very low background in these assays. Neither CXR lacking its C-terminal activation domain AF-2 (ΔAF-2) nor CXR with the mutated DNA-binding domain (DBD) are able to transactivate the CYP2H1 264-bp PBRU in CV-1 cell assays (Figure 3C). In contrast, removal of the N-terminus of CXR (ΔN-term) has no effect on its transactivation potential suggesting that no activation function AF-1 is present in these 29 amino acids. Finally, the test whether any of these CXR mutant alleles acts in a dominant-negative fashion is performed in the LMH cells which do express endogenous CXR and which are drug-inducible [18]. When co-transfected with the 264-bp PBRU, the CXR allele lacking a functional AF-2 domain (ΔAF-2) drastically decreases PB-induction of the PBRU (Figure 3D). In contrast, the DNA-binding domain (DBD) and the N-terminal truncated (ΔN-term) mutants have no effect. Similar results were obtained with PBRUs from other drug-responsive genes (data not shown). Together, the RNAi experiments and the findings using the dominant-negative CXR mutants show that functionally, CXR is the major drug-sensing nuclear receptor in chicken.
A significant difference between PXR and CAR in mammals is their mode of activation and their cellular localization [19]. PXR is strongly activated by a huge number of compounds. In contrast, CAR exhibits less promiscuity but high constitutive activity in most cellular assays [34]. However, CAR activity can be modulated by inverse agonists, agonists and different protein phosphorylation events [35]. In terms of activation, CXR is also highly promiscuous and normally has a low basal activity, thus pharmacologically more resembling a PXR-type than a CAR-type receptor [13,15]. Regulation of CAR activity can in part be explained by its unusual cellular localization. Both PXR and CAR undergo cytoplasmic-nuclear shuttling upon activation [36-40]. However, in contrast to PXR, CAR translocates after activation by PB, other xenobiotics or bilirubin for which no direct binding to the ligand-binding pocket was found. Although some progress in identifying CAR-interaction partners have been made recently [41,42], the mechanisms controlling the cytosolic-nuclear translocation are not clear. Interestingly, CAR translocation is independent of the C-terminal AF-2 function but instead requires the xenochemical response signal (XRS) LXXLXXL located between leucine 313 and leucine 319 in the human CAR sequence [37]. In contrast, cytoplasmic-nuclear translocation of VDR, the glucocorticoid receptor (GR, NR3C1) and the progesterone receptor (PR, NR3C3) is dependent on AF-2 suggesting a different mechanism for CAR shuttling [37,43]. A putative XRS (LLLLTEL) is also found in the CXR sequence between leucine 356 and leucine 362. Thus, to assess the relatedness of CXR to PXR and CAR in terms of cellular localization, we engineered different CXR-green fluorescent protein (GFP) fusion proteins. These were subsequently tested for functionality in CV-1 cell transactivation assays using the 264-bp PBRU as drug-sensitive enhancer. CXR with N-terminal, but not C-terminal GFP is activated by 400 μM PB and 10 μM clotrimazole after 16 hours of incubation (Figure 4A). Site-directed leucine to glycine mutagenesis in the CXR XRS reduces its ability to confer drug activation in these assays (Figure 4A).
Figure 4 Cellular localization of CXR in transiently transfected LMH cells. A, Full-length CXR, CXR with GFP attached at its C-terminus or at its N-terminus or N-terminal GFP-CXR fusion protein mutated in its xenochemical response signal (XRS) at positions 356, 359 and 362 were expressed in CV-1 cells together with a reporter plasmid containing the CYP2H1 264-bp PBRU. After transfection, the cells were treated with either vehicle, 400 μM PB or 10 μM clotrimazole before cells were lysed and analysed for reporter gene expression. Values are the average of three independent experiments and error bars represent standard deviations. B–F, LMH cells were transfected with either pEGFP-vector alone (B), expression vector for N-terminal GFP-CXR fusion protein treated with vehicle (C), 400 μM PB (D) or 0.1 μM okadaic acid (E) for 16 hours or GFP-CXR fusion protein with the xenochemical response signal mutation as described in Fig. 4A (F). Cells were stained with 300 nM DAPI in PBS and analysed for DAPI and GFP-specific light emissions at 461 nm and 507 nm using excitation wavelengths of 358 nm and 488 nm, respectively. Size bars stand for 20 μm.
Subsequently, N-terminal GFP-CXR was transiently expressed in LMH cells, the cells were counterstained with DAPI to stain the nuclei and GFP-CXR localization was compared to that of GFP-expression vector without insert. GFP was found to be evenly distributed throughout the cell (Figure 4B). As depicted in Figure 4C, GFP-CXR in vehicle-treated LMH cells is exclusively in the nucleus. Treatment of transiently transfected LMH cells with 400 μM PB for 16 hours leads to an increase of GFP-staining in the cytosol (Figure 4D). Similar observations have been made for a variety of nuclear receptors where activation stimulates their export from the nucleus and subsequent degradation in the cytosol [44,45]. Accordingly, PB-treatment of LMH cells results in decreased CXR protein levels in total cell lysates (Figure 5, lanes 1 and 2) and even more dramatic in nuclear extracts (Figure 5, lanes 3 and 4) suggesting that activated CXR protein is more rapidly exported from the nucleus and degraded of this receptor. Most nuclear receptors that are exported and degraded upon activation share a conserved KXFFK/RR motif between the two zinc-fingers in the DNA-binding domain that can serve as binding site for calreticulin which is involved in the nuclear export [45]. PXR, CAR and CXR also contain a KGFFRR-motif but whether calreticulin plays a role in nuclear export of these receptors remains to be investigated. The protein phosphatase inhibitor okadaic acid inhibits PB-induction of mammalian and chicken PBRUs [13,18,46,47]. In transiently transfected LMH cells, 100 nM okadaic acid prevents nuclear localization of CXR after 16 hours (Figure 4E). Moreover, protein levels of the GFP-CXR fusion protein were reduced. Okadaic acid treatment prevents the drug-induced cytosolic-nuclear translocation of CAR [36]. Our findings regarding CXR are therefore very reminiscent of those results. Furthermore, site-directed mutagenesis of the XRS reduces the nuclear localization of CXR (Figure 4F) but not as completely as XRS mutations of CAR in mouse primary hepatocyte cultures [37]. The nuclear-cytoplasmic redistribution of this CXR mutant correlates with the decrease in its ability to activate the 264-bp PBRU in transactivation assays (Figure 4A). Thus, although CXR is normally found in the nucleus like PXR, it shares some features with CAR concerning its localization after treatment with okadaic acid or when its XRS is mutated.
Figure 5 Nuclear CXR protein levels decrease after PB-treatment. LMH cells were treated with vehicle or 400 μM PB for 16 hours before cells were lysed and CXR protein levels in the total lysate (lanes 1 and 2) and in nuclear extracts (lanes 3 and 4) determined by Western blot. As controls, CV-1 cells were transfected with control vector or CXR expression vector (lanes 5 and 6). MW, molecular weight in kDa.
In primary human hepatocytes, glucocorticoids have a dual effect on the expression of the drug-inducible CYP3A4 that is regulated by both PXR and CAR [48]. At low concentrations, these compounds activate GR which subsequently induces transcript levels of PXR and CAR [49,50] whereas higher concentrations of glucocorticoids directly activate PXR [9,51]. We thus wanted to test whether the chicken CXR is regulated in the same way as the mammalian xenobiotic-sensing receptors. Treatment of LMH with 50 μM dexamethasone (Dex) for 16 hours did not alter CXR expression (Figure 6). Moreover, dexamethasone does not activate CXR directly, at least at this concentration [13]. In contrast, dexamethasone increases transcription of the chicken peroxisome-proliferator activated receptor α (PPARα, NR1C1), the chicken liver X receptor (LXR, NR1H3) and the chicken farnesoid X receptor (FXR, NR1H4). These receptors play important roles in maintaining hepatic bile acid, cholesterol and lipid homeostasis, respectively [52]. PXR, CAR and CXR have been found to be activated by bile acids and thus are involved in the regulation of the intrahepatic levels of lipid soluble compounds by stimulating metabolism and subsequent excretion of these compounds [12,53,54]. Therefore, activation of one of these receptors leads to changes in intrahepatic lipid levels which then potentially affects transcription of the other receptors. However, the regulatory network of these receptors is still under investigation.
Figure 6 Transcriptional regulation of chicken CXR, FXR, LXR and PPARα in LMH cells by glucocorticoids. LMH cells were treated for 16 hours with vehicle or 50 μM dexamethasone before cells were lysed and RNA was analysed by Northern blotting with probes for CXR, chicken PPARα, chicken LXR, chicken FXR or chicken glyceraldehyde 3-phosphate dehydrogenase (GAPDH).
Molecular modelling studies confirm the close relationship between chicken and fish xenosenors to mammalian PXR. X-ray structures of human PXR revealed several peculiarities of the PXR ligand-binding domain which are not found in other nuclear receptors [55,56]. First, PXR has an expanded β-sheet with two more strands. Moreover, helix 6 is completely and helix 7 partially unwinded which leaves a solvent-accessible hole in the ligand-binding pocket that is capped by an extension in helix 1–3. Although an extended β-sheet is not obvious in chicken and fish xenosensors, both receptors have long helix 1–3 inserts which could potentially induce partial unwinding of helix 6 and 7. Thus, molecular modelling of aligned amino acid sequences suggest enlarged ligand binding pockets for both fish and chicken xenobiotic-sensing receptors which could explain their high promiscuity [15]. In striking contrast, CARs not only lack an extended β-sheet but also have a much shorter helix 1–3 resulting in a more rigid and less promiscuous ligand binding pocket [15,57,58]. Therefore, the relatively high degree of promiscuity of CAR could at least partially be due to the ability of different compounds to trigger cytoplasmic-nuclear translocation of this receptor independent of direct binding [35]. The loop connecting helix 11 and 12 is much shorter in the CAR sequence than most other nuclear receptors [15,57]. This short loop might reduce the ability of helix 12 and AF-2 to reach an inactive conformation and thus could explain the constitutive activity of CAR [57]. CAR also has a shorter helix 12 than most other nuclear receptors [57]. Interestingly, helix 12 of CXR is very conserved to that of mammalian CARs in terms of amino acid composition and of length whereas the length of the zebrafish xenosensor helix 12 is intermediate between CARs and PXRs.
Conclusions
In summary, our results confirm that in contrast to mammals which have two xenobiotic-sensing receptor PXR and CAR, the genome of other species encodes for only one xenosensor. This hypothesis is supported by analysis in the fugu fish genome (data not shown), unsuccessful attempts to isolate further xenosenors in chicken and functional assays showing that ablation of CXR function drastically reduces drug-inducibility in a chicken hepatoma cell line. Our findings presented here and those of other laboratories imply that PXR and CAR origin from one ancestral gene which diverged into two genes in mammals. This ancestral gene, in chicken coding for CXR, is a promiscuous, PXR-like receptor. Thus, CXR and related receptors from fish are activated by a variety of different compounds [13,15]. Interestingly, in a comprehensive study of different classes of ligands on xenosensors from man, monkey, pig, dog, mouse, chicken and fish, CXR was one of the most promiscuous receptors in regard to the compounds tested [15]. Therefore, the ancestral xenosensors in non-mammalian species might have a broader substrate spectrum than their mammalian counterparts where the task for detoxification is split between two receptors [59]. On the other hand, CXR also shares some features with CAR that are not found in PXR: its short helix 12, the xenochemical response signal and in part its cellular localization after okadaic acid treatment. Finally, in contrast to both PXR and CAR, CXR is not regulated by glucocorticoid treatment in the chicken LMH cells suggesting that this regulation was acquired only after birds and mammals diverged from a common ancestor.
Evolution of drug-metabolizing CYPs and xenobiotic-sensing nuclear receptors is influenced by diet and exposure to other environmental chemicals. Accordingly, drug-induction is very species specific. This is reflected in the unusually divergent ligand-binding domains of PXRs and CARs orthologs [22]. When comparing PXRs and CARs from human, mouse and rat, nonsynonymous nucleotide substitution rates are considerably higher in comparison to any other nuclear receptor [21] and reflect the different evolutionary adaptations of these species to their specific environment. It is thus extremely puzzling why in non-mammalian species, one xenosensor is sufficient whereas two xenobiotic-sensing nuclear receptors have evolved in mammals. Furthermore, it is unclear why in addition to the ligand-activated PXR, mammalian genomes encode CAR, a nuclear receptor that is unorthodox in many ways. On one hand, CAR and PXR might just share the workload in hepatic detoxification of xenobiotics. On the other hand, evidence accumulated in recent years that both PXR and CAR have functions that go beyond detoxification. As example, PXR and CAR form an intricate network with other nuclear receptors and transcription factors to regulate hepatic cholesterol and bile acid homeostasis [60]. It is thus conceivable that these receptors have so-far unidentified functions in mammals which require two receptors and that are thus absent in non-mammalian species. Therefore, further insights into the evolution of drug-sensing nuclear receptors are extremely important in order to gain novel insights into the role of these factors in the physiology and pathophysiology of the liver.
Methods
LMH and CV-1 cell culture, transfection and reporter gene assays
Culture and transfection of LMH cells with FUGENE 6 Transfection Reagent (Roche Molecular Biochemicals, Rotkreuz, Switzerland) were performed as published [17,33]. Before transfections, LMH cells were kept in serum-free medium for 24 hours. CV-1 cell transactivation assays have been described in detail [17,33]. Sixteen or twenty-four hours after drug-treatment, cells were harvested and assays for CAT expression using a CAT ELISA Kit (Roche Molecular Biochemicals, Rotkreuz, Switzerland). CAT concentrations were normalized against β-galactosidase activities to compensate for different transfection efficiencies.
Isolation of the CXR gene
Chicken BAC filters (UK Human Genome Mapping Project Resource Center, UK) were hybridised with a probe encoding for CXR. Positive clones were purchased, digested with different restriction enzymes and Southern blots obtained using the same probe. Bands hybridising with the CXR probe were isolated, subcloned and CXR genomic information obtained by PCR using primers designed after the CXR mRNA sequence.
Site-directed mutagenesis
Mutagenesis was carried out using overlapping primers as described [17]. Mutated fragments were excised, cloned into new vectors and verified by sequencing.
Electrophoretic mobility shift assays
Electrophoretic mobility shift assays have been described in detail [33]. Proteins were expressed using the TNT in vitro transcription/translation kit (Promega, Wallisellen, Switzerland) before being subjected to non-denaturing SDS-polyacrylamide gel electrophoresis with [32P]-radiolabeled CYP2H1 264-bp PBRU.
Targeting of CXR in LMH cells by RNAi
Expression of CXR in LMH cells was repressed by RNAi as described [61]. In brief, a 19 bp fragment ranging from position 857 to 875 in the open reading frame of CXR was chosen for targeting. A double-stranded oligonucleotide containing this sequence and compatible ends for cloning into pSUPER was obtained by annealing single stranded oligonucleotides for the sense (GATCCCCGGATGGGGCTCTGGCCGGCTTCAAGAGAGCCGGCCAGAGCCCCATCCTTTTTGGAAA) and the anti-sense strand (AGCTTTTCCAAAAAGGATGGGGCTCTGGCCGGCTCTCTTGAAGCCGGCCAGAGCCCCATCCGGG) and subsequent ligation into pSUPER cut with BglII and HindIII (underlined letters refer to CXR-specific targeting sequence). After verification of the ligation product the pSUPER-CXR-RNAi expression cassette was cut out using BamHI and XhoI and subcloned into BglII/XhoI-digested pcDNA3 (Invitrogen, Carlsbad, USA). The ScaI-linearised construct was transfected into LMH cells using FUGENE 6 (Roche Molecular Biochemicals, Rotkreuz, Switzerland). Stable transfectants were selected by addition of 175 μg/ml G418 (PAA Laboratories, Pasching, Austria) to the cell culture medium. A control cell line was selected in parallel which was stably transfected with pcDNA3 carrying the empty pSUPER expression cassette. Reporter gene assays in LMH cells using the CXR-RNAi clones were performed using reporter constructs for CYP2H1, CYP3A37, CYP2C45 and ALAS-1 described previously [17,24-26].
Cellular localization studies
LMH cells were cultivated on glass cover slips and subsequently transfected with pEGFP-C1 or pEGFP-N1 expression plasmids (Clontech, Allschwil, Switzerland) before cells were either treated with vehicle, 400 μM PB or 0.1 μM okadaic acid for 16 hours. Cells were washed with PBS, fixed in 3% formaldehyde for 30 minutes, washed again with PBS, stained with 300 nM DAPI and subsequently mounted on glass slides. Digital images were captured using a Leica DC 300F camera (Leica, Nidau, Switzerland) mounted on a Leitz DMRB microscope with the Leica IM50 Image Manager program version 1.20. Figures were assembled with Adobe Photoshop version 5.0.
CXR antibodies, nuclear extracts and Western blots
CXR ligand-binding domain was expressed in bacteria, purified and injected into rabbits for antibody production according to standard procedures. Anti-CXR-ligand-binding domain antibody from rabbit serum was subsequently used in Western blots. LMH cells were grown under standard conditions and treated with vehicle or 400 μM PB overnight. Cells were subsequently washed with PBS and protein extracts prepared using RIPA buffer. As control, CV-1 cells were transfected with empty pSG5 expression vector or vector expressing CXR and subsequently lysed with RIPA buffer. Nuclear extracts were prepared as published [62].
Northern hybridisation
LMH cells were treated with the indicated compounds for 16 hours before total RNA was isolated using the TRIZOL Reagent (Life Technologies, Basel, Switzerland). Twenty μg of total RNA were subjected to electrophoresis and analysed in Northern hybridisations as described [17,33].
List of Abbreviations
CYP, cytochrome P450; PB, phenobarbital; PXR, pregnane X receptor; CAR, constitutive androstane receptor; CXR, chicken xenobiotic receptor; PBRU, phenobarbital-responsive enhancer unit; ALAS-1, δ-aminolevulinate synthase; AF-1/2, activation function-1/2; LXR, liver X receptor; PB, phenobarbital; XRS, xenochemical response signal; GFP, green fluorescent protein; PPAR, peroxisome-proliferator activated receptor; FXR, farnesoid X receptor.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
CH carried out the cellular localization assays, cloned the various CXR mutants, performed the reporter gene and the electrophoretic-mobility shift assays as well as the transcriptional regulation studies. SB did the various screens for further chicken xenobiotic-sensing nuclear receptors. AR performed the RNAi experiments. RL and MO isolated the CXR antibody and carried out the protein stabilization and localization assays. MRK helped with the RNAi experiments. MP and CG helped with the CV-1 cell transactivation assays. UAM conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
Acknowledgements
This work was supported by the Swiss National Science Foundation.
The mRNA sequences for chicken estrogen-related receptor γ (ERRγ) and a partial fragment of ear2 have been submitted to Genbank under accession numbers AY702438 and AY702439, respectively.
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| 15479477 | PMC524364 | CC BY | 2021-01-04 16:37:42 | no | Nucl Recept. 2004 Oct 12; 2:7 | utf-8 | Nucl Recept | 2,004 | 10.1186/1478-1336-2-7 | oa_comm |
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Genet Vaccines TherGenetic Vaccines and Therapy1479-0556BioMed Central London 1479-0556-2-141547390010.1186/1479-0556-2-14Short PaperImproved gene delivery to human saphenous vein cells and tissue using a peptide-modified adenoviral vector Work Lorraine M 1lmw3u@clinmed.gla.ac.ukReynolds Paul N 2paul.reynolds@adelaide.edu.auBaker Andrew H 1ab11f@clinmed.gla.ac.uk1 BHF Glasgow Cardiovascular Research Centre, Division of Cardiovascular & Medical Sciences, University of Glasgow, 44 Church Street, Glasgow, G11 6NT, UK2 Royal Adelaide Hospital Chest Clinic and Department of Medicine, University of Adelaide, Adelaide, South Australia, Australia2004 8 10 2004 2 14 14 10 9 2004 8 10 2004 Copyright © 2004 Work et al; licensee BioMed Central Ltd.2004Work 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 establishment of efficient gene delivery to target human tissue is a major obstacle for transition of gene therapy from the pre-clinical phases to the clinic. The poor long-term patency rates for coronary artery bypass grafting (CABG) is a major clinical problem that lacks an effective and proven pharmacological intervention. Late vein graft failure occurs due to neointima formation and accelerated atherosclerosis. Since CABG allows a clinical window of opportunity to genetically modify vein ex vivo prior to grafting it represents an ideal opportunity to develop gene-based therapies. Adenoviral vectors have been frequently used for gene delivery to vein ex vivo and pre-clinical studies have shown effective blockade in neointima development by overexpression of candidate therapeutic genes. However, high titers of adenovirus are required to achieve sufficient gene delivery to provide therapeutic benefit. Improvement in the uptake of adenovirus into the vessel wall would therefore be of benefit. Here we determined the ability of an adenovirus serotype 5 vector genetically-engineered with the RGD-4C integrin targeting peptide inserted into the HI loop (Ad-RGD) to improve the transduction of human saphenous vein smooth muscle cells (HSVSMC), endothelial cells (HSVEC) and intact saphenous vein compared to a non-modified virus (Ad-CTL). We exposed each cell type to virus for 10, 30 or 60 mins and measured transgene at 24 h post infection. For both HSVSMC and HSVEC Ad-RGD mediated increased transduction, with the largest increases observed in HSVSMC. When the experiments were repeated with intact human saphenous vein (the ultimate clinical target for gene therapy), again Ad-RGD mediated higher levels of transduction, at all clinically relevant exposures times (10, 30 and 60 mins tissue:virus exposure). Our study demonstrates the ability of peptide-modified Ad vectors to improve transduction to human vein graft cells and tissue and has important implications for gene therapy for CABG.
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Long term patency rates for CABG using autologous saphenous vein are poor, showing 1, 5 and 10 years post-CABG rates of 93%, 74% and 41%, respectively [1] and therefore represent a significant clinical problem. Long-term failures are due to neointima formation and superimposed atherosclerosis [2-4], a pathology that lacks a suitably efficient pharmacological therapy. Significant contributions of vascular smooth muscle cell (SMC) proliferation and migration have been documented [2-4]. Anti-proliferative strategies are in phase III clinical trial using decoy oligonucleotides to the transcription factor E2F, a strategy that has shown considerable promise pre-clinically [5,6] and also in early stage human trials [7]. We, and others have adopted the alternate strategy of gene therapy to prevent CABG failure [8]. CABG is an "ideal" clinical scenario for gene therapy since saphenous vein can be genetically modified ex vivo following leg harvesting and prior to coronary grafting. This unique "clinical window" has clear safety advantages over in vivo gene delivery since excess vector can be removed from the graft prior to coronary grafting. However, the clinical window is short (likely 10–60 minutes) and therefore necessitates the use of an efficient vector system for gene delivery. Adenoviral vectors have proven efficient for gene delivery in this context [9] although high titers are required to provide sufficient levels of gene delivery to achieve therapeutic gain using transgenes such as tissue inhibitor of metalloproteinases-3 [9], endothelial nitric oxide synthase [10] and p53 [11]. The latter study defined the rationale behind use of adenoviral vectors since long-term benefit on graft remodelling was shown at 3 months, even though the virus was only present for 2–4 weeks post grafting [11]. Any improvement in gene delivery above that mediated by adenoviral serotype 5 vectors would be very encouraging for clinical translation of pre-clinical therapies. To this end, a number of strategies have emerged including fiber switching (pseudotyping) and modification of adenovirus type 5 fibers with targeting peptides. Pseudotyping the fiber from adenovirus serotype 16, which binds CD46 [12], dramatically improves transduction to vascular cells including intact human saphenous vein allowing lower doses of vector to be used to achieve attractive levels of gene delivery to grafts ex vivo [13]. Likewise, gene delivery to vascular smooth muscle cells can be enhanced by incorporation of cell targeting peptides isolated by phage display into the HI loop of the adenovirus fiber [14], the preferred site for peptide insertion [15]. In the context of improved gene delivery mediated by the RGD-4C peptide, which was isolated by phage display and targets αv integrins [16], this has been shown for rabbit grafts [17] although the vast majority of data is based on gene delivery for cancer [18]. Since SMC show poor coxsackie and adenovirus receptor (CAR) availability [19], it is particularly relevant that the RGD-4C peptide may circumvent CAR deficiency on target cells to improve levels of transduction. In this study, we assess the ability of RGD-4C-modified adenovirus serotype 5 vectors to enhance gene delivery to human saphenous vein SMC and EC as well as to intact human saphenous vein ex vivo, the ultimate clinical target.
HSVEC were obtained by enzymatic collagenase digestion of human saphenous vein and maintained in endothelial cell complete media (TCS CellWorks, UK) supplemented with 20% (v/v) foetal calf serum (FCS; PAA laboratories, UK). HSVSMC were grown from medial explants from the same material and maintained in Dulbecco's modified Eagle's medium (DMEM) with 4500 mg/l glucose supplemented with 20% (v/v) FCS and 100 IU/ml penicillin, 100 μg/ml streptomycin and 2 mmol/l L-Glutamine. All cells were grown in a humidified atmosphere with 5% CO2 at 37°C. Cells were plated to reach 80% confluence 24 hours later. HSVEC or HSVSMC were infected in 96 well plates with increasing doses [plaque forming units (pfu) / cell] of Ad vectors for 10, 30, 60 mins at 37°C. The cells were washed twice in PBS and the media changed. 24 hours post-infection, the cells were again washed in PBS, lysed in PBS/0.2% Triton-X-100 and transduction quantified using the Wallac 1420 (Victor2) Multilabel Counter with recombinant eGFP (Clontech, Basingstoke, UK) as a standard. Reporter gene expression was normalised for total protein using the bicinchoninic acid (BCA) protein assay (Perbio, UK) with bovine serum albumin as standard, measured using a VICTOR2 plate reader. Exposure of HSVEC to Ad-CTL or Ad-RGD [50 plaque forming units (pfu) / cell] resulted in a time-dependent increase in the level of transduction (Figure 1A). At each time point studied (10, 30 or 60 mins), Ad-RGD mediated a significantly enhanced level of transgene expression compared to Ad-CTL (Figure 1A). Fluorescent microscopy demonstrated that control levels of infection with Ad-CTL were relatively high in HSVEC but further enhanced using the RGD-modified Ad (Figure 1A) at all time points tested. This is consistent with HSVEC expressing moderate CAR levels [14,19] allowing transduction of cells by Ad-CTL but the RGD-4C vector can further improve virus uptake. In HSVSMC, Ad-RGD again mediated a marked and significant enhancement in levels of transgene expression at all time points studied (Figure 1B). HSVSMC were much less permissive to non-modified Ad-CTL infection (Figure 1B), consistent with our previous observations [14], but enhanced with Ad-RGD to near 100% transduction in HSVSMC by fluorescence microscopy (Figure 1B). Again, this effect was evident at all virus:cell exposure time points – 10, 30 and 60 mins. For both HSVEC and SMC similar RGD-4C-mediated increases were observed with different viral doses (10 and 100 pfu/cell; not shown) thereby showing both time- and dose-dependence.
Figure 1 Transduction of saphenous vein cells and intact tissue. Ad-CTL and Ad-RGD expressing eGFP were incubated with (A) HSVEC and (B) HSVSMC for different times and gene expression quantified and normalised to protein. Representative fluorescent images are shown. (C) Intact human saphenous vein was incubated with luciferase-expressing vectors and expression quantified. *Indicates p < 0.05 vs Ad-CTL.
Based on the above we therefore assessed transduction in intact human saphenous vein. In order to quantify transgene expression accurately in tissue extracts we used luciferase-expressing viruses. Intact human saphenous veins were cleaned of surrounding connective tissue and cut into rings 3–4 mm in length. During preparation and infection, veins were maintained in wash medium (RPMI supplemented with 100 IU/ml penicillin, 100 μg/ml streptomycin and 2 mmol/l L-glutamine). Individual vein rings were incubated with Ad vectors for 10, 30 or 60 minutes (1 × 109 pfu / ring) before being washed twice in PBS and maintained in organ culture for 5 days. Rings were maintained in wash medium supplemented with 30% (v/v) FCS. Vein rings were snap frozen in liquid nitrogen and homogenised using a mortar and pestle for determination of reporter gene expression 5 days post-infection. Ex vivo homogenates were suspended in 100 μL reporter lysis buffer (RLB) and kept on ice for 1 hour before supernatants were analysed for luciferase expression using the Luciferase Assay System (Promega). 96 well plates were prepared using 10 μL/well of homogenate suspension diluted to a total volume of 100 μL with RLB. 100 μL of Luciferase Assay Reagent was added to each well and the plate immediately read for 10 seconds per well. Detection was achieved using a Wallac 1420 (VICTOR2) Multilabel Counter with recombinant luciferase (Promega) as a standard and normalised for total protein. Ad-RGDLuc mediated a time-dependent increase in the level of transgene expression that was evident at all exposure times studied – 10, 30 and 60 minutes (Figure 1C). This demonstrates that the RGD-4C-modification of Ad vectors can increase transduction to human saphenous vein, especially at short exposure times. The kinetics of virus binding in relation to time is therefore improved through the RGD-4C peptide and has direct implications for the design of gene therapy vectors for use in human CABG gene therapy procedures in the future. Although we have previously shown that non-modified Ad vectors transduce both endothelial and smooth muscle cells during graft gene delivery [9], and here show increased transduction of both cell types in vitro with RGD-modification, it will be important to fully define the uptake of the RGD-modified virus in the intact vein at the cellular level by immunotechniques. In broader terms, the design and tailoring of viruses for individual cardiovascular gene therapy applications is an important aspect of translation from pre-clinical to clinical gene therapy.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
LMW performed all isolated cell culture and vein transduction experiments. PNR produced the viruses and AHB supervised all work as principle investigator
The authors thank Nicola Britton and Margaret Cunningham for technical assistance. This work was supported by the Biotechnology & Biological Sciences Research Council (E17190 to A.H.B) and the British Heart Foundation (PG03/031 to A.H.B.)
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| 15473900 | PMC524365 | CC BY | 2021-01-04 16:39:08 | no | Genet Vaccines Ther. 2004 Oct 8; 2:14 | utf-8 | Genet Vaccines Ther | 2,004 | 10.1186/1479-0556-2-14 | oa_comm |
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Int J Behav Nutr Phys ActThe International Journal of Behavioral Nutrition and Physical Activity1479-5868BioMed Central London 1479-5868-1-141546267610.1186/1479-5868-1-14ResearchTracking of physical activity, fitness, body composition and diet from adolescence to young adulthood: The Young Hearts Project, Northern Ireland Boreham Colin 1ca.boreham@ulster.ac.ukRobson Paula J 2p.robson@ulster.ac.ukGallagher Alison M 2am.gallagher@ulster.ac.ukCran Gordon W 3g.cran@qub.ac.ukSavage J Maurice 4m.savage@qub.ac.ukMurray Liam J 3l.murray@qub.ac.uk1 School of Applied Medical Sciences and Sports Studies, University of Ulster, Jordanstown, Northern Ireland, BT37 0QB, United Kingdom2 Northern Ireland Centre for Food and Health (NICHE), University of Ulster, Coleraine, Northern Ireland, BT52 1SA, United Kingdom3 Department of Epidemiology and Public Health, Queen's University of Belfast, Belfast, Northern Ireland, BT12 6BJ, United Kingdom4 Department of Child Health, Queen's University of Belfast, Belfast, Northern Ireland, BT12 6BJ, United Kingdom2004 5 10 2004 1 14 14 27 5 2004 5 10 2004 Copyright © 2004 Boreham et al; licensee BioMed Central Ltd.2004Boreham 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 assumption that lifestyles formed early in life track into adulthood has been used to justify the targeting of health promotion programmes towards children and adolescents. The aim of the current study was to use data from the Northern Ireland Young Hearts Project to ascertain the extent of tracking, between adolescence and young adulthood, of physical activity, aerobic fitness, selected anthropometric variables, and diet.
Methods
Males (n 245) and females (n 231) were assessed at age 15 y, and again in young adulthood [mean (SD) age 22 (1.6) y]. At both timepoints, height, weight and skinfold thicknesses were measured, and physical activity and diet were assessed by questionnaire and diet history method respectively. At 15y, fitness was assessed using the 20 metre shuttle run, while at young adulthood, the PWC170 cycle ergometer test was used. For each measurement made at 15y, subjects were ranked into 'low' (L1; lowest 25%), 'medium' (M1; middle 50%) or 'high' (H1; highest 25%) categories. At young adulthood, similar categories (L2, M2, H2) were created. The extent of tracking of each variable over time was calculated using 3 × 3 matrices constructed using these two sets of categories, and summarised using kappa (κ) statistics.
Results
Tracking of diet and fitness was poor (κ ≤ 0.20) in both sexes, indicating substantial drift of subjects between the low, medium and high categories over time. The tracking of physical activity in males was fair (κ 0.202), but was poor in females (κ 0.021). In contrast, anthropometric variables such as weight, body mass index and sum of skinfolds tracked more strongly in females (κ 0.540, κ 0.307, κ 0.357 respectively) than in males (κ 0.337, κ 0.199, κ 0.216 respectively).
Conclusions
The poor tracking of fitness and diet in both sexes, and physical activity in females, suggests that these aspects of adolescent lifestyle are unlikely to be predictive of behaviours in young adulthood. In contrast, the fair to moderate tracking of anthropometric variables, particularly in females, suggests that attempts to reduce the ever increasing incidence of overweight and obesity in adults, should probably begin in earlier life.
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Background
Numerous epidemiological studies in adults have identified environmental and physiological risk factors that are associated with increased risk for cardiovascular disease (CVD). Among the many that have been identified [1], the major modifiable risk factors include physical inactivity, poor cardiorespiratory fitness, excess adiposity or obesity, and inappropriate dietary habits.
Although the clinically relevant effects of CVD are often not manifest until middle age or later, it is now generally well accepted that the disease is likely to have its antecedents in childhood [2-4]. In addition, children and adolescents have been shown to exhibit many of the potentially modifiable CVD risk factors that have been identified in adults. For example, of the 1015 adolescents aged 12y and 15y who participated in the first phase of the Northern Ireland Young Hearts Project, 18–34% were considered to have excess body fat, 24–29% had low physical activity levels, and 26–34% had poor cardiorespiratory fitness. Furthermore, mean total fat intakes were higher than desirable [5]. Similarly, in West Virginia, of the 5,887 school children who participated in the school-based Coronary Artery Risk Detection in Appalachian Communities (CARDIAC) Project, almost 43 percent were considered to be overweight, over a quarter were obese, and the high rate of obesity was positively associated with the prevalence of other CVD risk factors [6]. The conclusions drawn from these studies and others [7-9] have been largely unanimous: minimising the risk of morbidity or premature mortality associated with CVD in adulthood, should begin in childhood or adolescence.
However, if health promotion interventions in younger life are to have any hope of success, it must be assumed that physiological and behavioural risk factors exhibited in early life track into adulthood. Tracking has been defined as the maintenance of relative position in rank of behaviour over time, such that subjects who rank highly for unfavourable risk profiles at a young age are likely to maintain their ranks through into adulthood [10,11].
The aim of the current study was to use data from the Northern Ireland Young Hearts Project to ascertain the extent of tracking, between adolescence and young adulthood, of selected modifiable risk factors for CVD. Specifically, we investigated the tracking of physical activity, aerobic fitness, selected anthropometric variables, and diet.
Methods
Subjects
The Young Hearts Project (YH) is an ongoing longitudinal study evaluating the prevalence of CVD risk factors in young people living in Northern Ireland. Sampling procedures and methods used in the first two, school-based screening phases of the YH study have been described fully elsewhere [5]. Briefly, the initial screening (YH1), conducted in 1989/1990, surveyed 1015 adolescents (12-year old boys, n 251;12-year old girls, n 258; 15-year old boys, n 252; and 15-year old girls, n 254) randomly selected from post-primary schools. At that time, the resulting cohort represented a 2% sample of each of the two age populations in Northern Ireland. In 1992/93, a follow up study (YH2) was undertaken, in which subjects from the original 12 year old cohort were reassessed using procedures identical to those used in YH1. The response rate in the follow-up study was 90%. Between October 1997 and October 1999, all YH1 subjects were invited to participate in the third, hospital-based screening phase (YH3), and a 48.2% response rate was achieved. Reasons for the low response rate in YH3 have been described in full elsewhere [12]. Briefly, non-attenders reported that they were 'too busy', 'living outside Northern Ireland', 'busy with new job', 'couldn't be bothered' or 'didn't feel that the study was relevant to them'. As described by [12] and [13], attempts were made to determine the representativeness of the YH3 cohort by comparing the baseline YH1 data for those who participated in YH3, with the data obtained for those who declined to participate. YH3 participants tended to be from families with higher socio-economic status, and had lower BMI at baseline (YH1) than non-participants. Furthermore, males who declined to attend for screening at YH3, were fatter and reported a greater saturated fat intake at YH1 than YH3 male participants.
The analyses reported in the current paper are restricted to males (n 245) and females (n 231) for whom there were complete data sets at age 15y (either from YH1 or YH2) and at young adulthood [mean (SD) age 22.0 (1.6)y]. Ethical approval for each phase of the study was obtained from the Medical Research Ethical Committee of The Queen's University of Belfast, and written informed consent was obtained from all subjects prior to participation.
Anthropometry
Each subject's height, weight and skinfold thicknesses were measured at all study timepoints. Standing height was measured to the nearest millimetre using a Harpenden portable stadiometer (Holtain, UK), and body weight was measured to the nearest 0.1 kg using an electronic balance (Seca, Germany; 200 kg × 0.1 kg). For both measurements, subjects wore light indoor clothing and no shoes. Body mass index (BMI) was then calculated as weight (kg)/ [height (m)]2. Skinfold thicknesses were measured to the nearest millimetre using Harpenden callipers at four sites (biceps, triceps, subscapular, suprailiac). Two measurements were taken at each site and the average was recorded. The sum of the four skinfolds thicknesses was then calculated for each subject.
Dietary intake
At all study timepoints, dietary data were obtained using the diet history method [14]. This consisted of a detailed, open-ended one-to-one interview, the purpose being to ascertain the habitual weekly food intake of each subject. The diet history method was used for two reasons. Firstly, in subjects aged 15y, the diet history has been shown to provide more valid estimates of energy intake at the group level than weighed records [15]. Secondly, given that a complete diet history can be obtained from a subject in approximately one hour, it was the most feasible and cost-effective method for obtaining detailed dietary information from the YH1 and YH2 school-based cohorts. The method was used again in YH3 in order to maintain continuity. Reported energy and macronutrient intakes were calculated using computerised databases based on UK food composition tables as previously described [16,12]
Physical activity
At age 15y, habitual physical activity was assessed by self-report questionnaire, and scored according to the method of [17]. This method assessed the extent of daily participation in activities that were based around a typical school day. Each activity was assigned a score from 1–100, based on its frequency, intensity and duration.
As the school-based questionnaire was not relevant to the young adult subjects, a modification [18] of the Baecke questionnaire was used in YH3 to quantify habitual work activity, sports activity and non-sports leisure activity. For each of the three activity components, scores based on a five-point Likert scale were calculated and summed, giving total possible scores ranging from 3–15.
Aerobic fitness
Aerobic fitness at age 15y was assessed by the 20 metre shuttle test (20MST). In order to estimate maximal aerobic capacity, or VO2max (ml/kg/min), the number of laps completed by each subject in this maximal endurance test was entered into a sex-specific regression equation, based on data obtained in the Northern Ireland Fitness Survey [17].
As it was not feasible to conduct the 20MST at young adulthood (due to a lack of space in the hospital setting), VO2max was assessed using the Physical Work Capacity at a heart rate of 170 beats per minute (PWC170) cycle ergometer test [19]. PWC170 was calculated as the workload corresponding to a heart rate of 170 bpm, and expressed per kg body weight. The volume of oxygen consumed and the heart rate were monitored throughout the test (Quinton Metabolic Cart, Quinton, USA). For each subject, a straight line was fitted to three pairs of data (heart rate in bpm, VO2 in ml/kg/min), and this was used to estimate VO2max at the age-adjusted maximum heart rate [12].
Statistical analyses
All data were analysed using SPSS version 11.0.1 (SPSS Inc, Chicago, USA). Means and standard deviations were used to summarise the data for physical characteristics, aerobic fitness, physical activity scores and energy and macronutrient intakes of males and females at age 15y and young adulthood.
Tracking of each of these variables over time was assessed by determining the extent to which subjects who were placed into low, medium and high categories at age 15y, maintained their ranking in young adulthood. Owing to the fact that different techniques were used to measure physical activity and aerobic fitness at each timepoint, a method based on ranks, rather than actual measurements, was employed for assessing the tracking of these variables. Tracking of the other variables was also assessed using the rank based method because of its relative simplicity, and its ability to show the numbers of subjects making the transition between low, medium and high categories [20]. For example, in order to study the tracking of physical activity in females from age 15y to young adulthood, the group of 225 girls aged 15y was divided into three classes by physical activity score: lowest 25% (L1); middle 50% (M1); highest 25% (H1). Rather than using pre-determined fixed values, each class was defined by the first and third empirical quartiles. In young adulthood, the female group was divided into three similar classes; L2, M2 and H2. Using these two sets of classifications, a 3 × 3 tracking matrix was constructed; the entry in a specific cell being the number of subjects belonging to the corresponding classes at age 15y and at young adulthood (see Figure 1 for examples). This approach provides a broad picture of the relative changes in a particular variable over time, such that a matrix with relatively small off-diagonal elements provides evidence of 'good' tracking. For the purposes of this study, the degree of tracking was summarised by a weighted kappa (κ) value, and interpreted according to [21] as follows: κ ≤ 0.20, poor tracking; κ 0.21–0.40, fair; κ 0.41–0.60, moderate; κ 0.61–0.8, good; κ 0.81–1.0, very good. This procedure was undertaken separately for males and females to assess the tracking, between age 15y and young adulthood, of energy and macronutrient intakes, height, weight, BMI, skinfold thicknesses, aerobic fitness and physical activity scores.
Figure 1 Examples of 3 × 3 tracking matrices constructed for the calculation of κ values for (a) height in females, and (b) physical activity scores in females.(a) Height in females (κ 0.813) (b) Physical activity score in females (κ 0.021) L1 and L2 represent lowest 25% of the cohort at baseline and follow-up respectively; M1 and M2 represent middle 50% of the cohort at baseline and follow-up respectively; H1 and H2 represent the highest 25% of the cohort at baseline and follow-up respectively. The entry in a specific cell indicates the number of subjects belonging to the corresponding classes at baseline and at follow-up.
Results
The physical characteristics, aerobic fitness and physical activity levels of the Northern Ireland Young Hearts cohort at age 15y and at follow-up (young adulthood) are summarised in Table 1. At young adulthood, weight, height, BMI and skinfold thicknesses were significantly greater than at age 15y in males and females. In both sexes, VO2max assessed at young adulthood was significantly lower than at age 15y. At age 15y, males and females were 4.8% and 8.4% heavier than the British age-specific reference population, while at young adulthood, they were 7.9% and 9.9% heavier respectively. Details of the reference populations are described in Annex 1 of the 'Dietary Reference Values for Food Energy and Nutrients for the United Kingdom' [22].
Table 1 Physical characteristics, fitness and physical activity levels at age 15y, and at young adulthood (mean age 22.0y).
Males Females
Baseline Follow-up Baseline Follow-up
n Mean SD n Mean SD n Mean SD n Mean SD
Weight (kg) 245 59.2 8.9 245 75.5*** 11.5 231 56.9 9.1 231 64.3*** 11.7
Height (m) 245 1.70 0.07 245 1.78*** 0.07 231 1.62 0.06 231 1.64*** 0.06
Body mass index (kgm-2) 245 20.4 2.4 245 23.8*** 3.1 231 21.7 3.2 231 23.8*** 4.1
Biceps skinfold (mm) 245 4.73 2.23 244 5.54*** 3.42 231 8.00 2.92 230 9.57*** 5.27
Triceps skinfold (mm) 245 9.21 4.59 244 10.28** 5.41 231 15.97 4.49 230 17.84*** 5.94
Subscapular skinfold (mm) 245 7.75 3.75 244 12.94*** 5.22 231 11.57 4.77 230 15.14*** 6.17
Suprailiac skinfold (mm) 245 10.30 6.58 244 15.87*** 7.43 231 14.08 5.73 230 16.01*** 6.98
Sum of skinfolds (mm) 245 32.00 16.07 244 44.63*** 18.76 231 49.61 15.62 230 58.56*** 20.76
VO2maxa 241 52.07 5.96 225 38.93*** 8.70 228 41.05 5.48 212 26.90*** 5.43
Physical activity scoreb 242 28.27 14.44 243 7.95 1.38 227 17.71 12.59 229 7.40 1.20
a VO2max at age 15y was derived from the number of 20 metre shuttle run laps completed by each subject. At follow-up, VO2max was extrapolated from the results of a cycle ergometer test (Physical Work Capacity at a heart rate of 170 bpm; PWC170).
b Physical activity scores at age 15y were calculated according to the method of Riddoch et al (1991). At follow-up, a modification (Pereira et al, 1997) of the Baecke questionnaire was used. At age 15y, the maximum possible activity score was 100, while at follow-up, scores could range from 3–15.
For each sex, differences between variables measured at age 15y and young adulthood were assessed using paired t-tests. *** P < 0.001 ** P < 0.01.
The energy and macronutrient intakes reported by the Young Hearts cohort at age 15y, and at follow-up, are presented in Table 2. At young adulthood, the males reported significantly lower intakes of energy (MJ/d; P 0.04), total fat (g/d and % energy; both P < 0.001) and total carbohydrate (g/d and % energy; both P < 0.001) than at age 15y. In contrast, intakes of protein (g/d and % energy; both P < 0.001) reported by males at young adulthood were significantly greater than at age 15y. Similar patterns were observed for females, with the exception that % energy derived from total carbohydrate did not change significantly between age 15y and young adulthood.
Table 2 Energy and macronutrient in takesa reported at age 15y, and at young adulthood (mean age 22.0y).
Males (n 245) Females (n 231)
Baseline Follow-up Baseline Follow-up
Mean SD Mean SD Mean SD Mean SD
Energy (MJ/d) 13.5 3.2 13.0* 3.5 9.4 2.6 8.3*** 2.4
Protein (g/d) 95.0 25.6 101.2** 27.9 63.9 18.6 68.5** 21.4
% energy from protein 12.0 1.9 12.6*** 2.3 11.6 2.1 13.4*** 2.9
Total fat (g/d) 137.1 38.5 113.2*** 38.3 96.8 30.3 73.3*** 25.0
% energy from fat 37.4 4.3 32.1*** 5.5 37.7 4.3 32.5*** 6.0
Carbohydrate (g/d) 411.6 100.3 368.6*** 110.5 289.6 82.2 253.6*** 87.1
% energy from carbohydrate 48.8 4.6 45.7*** 7.2 49.2 4.9 49.1NS 6.5
a At both timepoints, energy and macronutrient intakes were assessed using the diet history method.
For each sex, differences between variables measured at age 15y and young adulthood were assessed using paired t-tests. *** P < 0.001 ** P < 0.01 NS not significant
Table 3 summarises the extent of tracking of physical characteristics, fitness and physical activity levels between age 15y and young adulthood, in males and females. In males, tracking of height was moderate, while in females, it was very good. Figure 1(a), which illustrates the 3 × 3 matrix constructed for the tracking of height in females between age 15y and young adulthood, demonstrates that there was very little drift of subjects between low, medium and high categories over time; hence the relatively high κ value. In both sexes, tracking of BMI was moderate. In males, the tracking of weight, four skinfold thicknesses (biceps, triceps, subscapular, suprailiac) and sum of skinfolds was fair (κ 0.21–0.40) between age 15y and young adulthood. The magnitude of the κ values obtained for biceps and subscapular skinfold thicknesses in females were also greater than in males, while triceps and suprailiac skinfold thicknesses tracked to a similar extent in both sexes. In males, the tracking of aerobic fitness (VO2max) was poor, but was greater than the κ value obtained for the females (κ 0.150 vs κ 0.076). A similar pattern was observed for physical activity scores (κ 0.202 vs κ 0.021).
Table 3 Tracking of physical characteristics, fitness and physical activity levels between age 15y and young adulthood (mean age 22.0y)
Males Females
n κ P n κ P
Weight (kg) 245 0.337 <0.0001 231 0.540 <0.0001
Height (m) 245 0.444 <0.0001 231 0.813 <0.0001
Body mass index (kgm-2) 245 0.422 <0.0001 231 0.452 <0.0001
Biceps skinfold (mm) 244 0.224 <0.0001 230 0.403 <0.0001
Triceps skinfold (mm) 244 0.292 <0.0001 230 0.287 <0.0001
Subscapular skinfold (mm) 244 0.274 <0.0001 230 0.371 <0.0001
Suprailiac skinfold (mm) 244 0.223 <0.0001 230 0.202 <0.0001
Sum of skinfolds (mm) 244 0.216 <0.0001 230 0.357 <0.0001
VO2maxa 222 0.150 <0.0001 209 0.076 0.128
Physical activity scoreb 240 0.202 <0.0001 225 0.021 0.669
a VO2max at age 15y was derived from the number of 20 metre shuttle run laps completed by each subject. At follow-up, VO2max was extrapolated from the results of a cycle ergometer test (Physical Work Capacity at a heart rate of 170 bpm; PWC170).
b Physical activity scores at age 15y were calculated according to the method of Riddoch et al (1991). At follow-up, a modification (Pereira et al, 1997) of the Baecke questionnaire was used.
κ indicates extent of tracking, and can be interpreted as follows: κ < 0.20, poor tracking; κ 0.21–0.40, fair; κ 0.41–0.60, moderate; κ 0.61–0.8, good; κ 0.81–1.0, very good (Altman, 1991).
The extent of tracking of energy and macronutrient intakes reported at age 15y and at young adulthood is presented in Table 4. In males, the κ values for energy, protein, total fat and total carbohydrate were poor, ranging from 0.019 (% energy from protein) to 0.169 (energy). Similarly, κ values observed in the females ranged from 0.051 (% energy from fat) to 0.202 (protein).
Table 4 Tracking of energy and macronutrient intakesa between age 15y and young adulthood (mean age 22.0y).
Males Females
n κ P n κ P
Energy (MJ/d) 245 0.169 <0.0001 231 0.154 0.001
Protein (g/d) 245 0.169 <0.0001 231 0.202 <0.0001
% energy from protein 245 0.019 0.683 231 0.098 0.039
Total fat (g/d) 245 0.117 0.011 231 0.152 0.001
% energy from fat 245 0.143 0.002 231 0.051 0.282
Carbohydrate (g/d) 245 0.114 0.013 231 0.120 0.011
% energy from carbohydrate 245 0.117 0.011 231 0.063 0.182
a At both timepoints, energy and macronutrient intakes were assessed using the diet history method.
κ indicates extent of tracking, and can be interpreted as follows: κ < 0.20, poor tracking; κ 0.21–0.40, fair; κ 0.41–0.60, moderate; κ 0.61–0.8, good; κ 0.81–1.0, very good (Altman, 1991).
Discussion
The current paper describes the extent of tracking for a range of behavioural and biological risk factors for CVD, between adolescence (15y) and young adulthood (22y) in 245 males and 231 females from Northern Ireland.
In relation to nutrient intakes, the poor tracking between 15 and 22 years revealed in this study reflects previous findings in this cohort between 12 and 15 years [20]. This suggests that individual dietary patterns exhibited at 15 years are unlikely to be predictive of dietary intakes at young adulthood. Intuitively, this lack of tracking is to be expected, as the transition from adolescence to adulthood is characterised by considerable physical, cognitive and psychosocial change. To date, however, there has been little evidence for tracking or otherwise of diet in this age group. Reasonably good dietary tracking has been reported for younger pre-school children [23], but this is not surprising given the high degree of control over diet exerted by parents in this age group. Reasonably high tracking coefficients for diet in the Amsterdam Growth and Health Longitudinal Survey were reported by Kemper et al. [24], but these were between the ages of 13 and 32 years. Although it is difficult to draw direct comparisons between studies due to differences in methodologies, one possibility for the poor tracking reported in the present study might be a particularly high degree of mis-reporting of intake in 15 year-old adolescents. This has been noted previously in relation to this cohort, particularly in relation to 'under-reporting' in 15 year-old females [20]. It is also possible that the low κ values obtained for the dietary intakes in the present study indicate that adolescence is, indeed, associated with rapidly changing and erratic patterns of nutrient intake. Adolescents take increasing control of what, when and where they eat and typically consume a greater proportion of their total intake outside the home. Concerns about changing body shape and adiposity may also prompt sudden changes in eating behaviour.
While adolescence is widely regarded to be a time of transition, it could also be argued that young adulthood is an equally important time of change, especially with regard to dietary habits. This is a time when people in this age group are likely to move out of home, go to university, start a family or to encounter other environmental or psychosocial factors that influence food intakes. Thus it is possible that the poor maintenance of ranks that we have observed in this study has arisen simply because we attempted to assess tracking between two very unstable periods of time in the life-cycle.
It is also possible that at least part of the explanation for poor dietary tracking in a cohort of this nature lies in the unsuitability of the diet history method for this purpose. Although the diet history method has shown good validity at the group level in adolescents, it is prone to significant problems of precision at the individual level [15]. Moreover, as it assesses perception and memory of usual diet and is susceptible to socially desirable responding [25], it is possible that changes in memory and motivation over time may contribute to poor tracking. Finally, it is entirely feasible that diet simply does not track well between two time points several years apart. Certainly, the data presented in this study suggest that individual dietary patterns reported at 15 years are unlikely to be predictive of energy and nutrient intakes reported at 22 years. It is clear, therefore, that individual subjects cannot be targeted for long-term dietary intervention based solely on data obtained at 15 years of age.
Both physical fitness and physical activity are now accepted as independent risk factors for several chronic diseases. The identification of low levels of fitness and/or activity at an early stage in the lifecourse might, therefore, enable early remedial strategies, provided that a degree of tracking for these risk factors is demonstrable. The results of the present study fail to provide such evidence, with poor tracking being demonstrated for fitness in both sexes, and poor tracking in females and only moderate levels of tracking in males for activity. By and large, these results are in keeping with the handful of other studies which have examined tracking of fitness and activity in this age group [26,27]. While the mechanisms responsible for this lack of stability between adolescence and early adulthood remain obscure, it is tempting to speculate that similar influences are responsible for the poor tracking of both diet and physical activity/fitness. For example, while much activity during adolescence is organised and school-based, by the time the individual reaches early adulthood, activity is likely to be more a matter of choice. In this respect, it is interesting to note that studies of the tracking of physical activity/fitness in both younger [28] and older [29,30] age groups than that of the present study, show generally higher levels of tracking between time points.
In contrast to diet and physical activity/fitness, anthropometric variables relating to body weight and adiposity showed stronger and consistent tracking, particularly in females. Good tracking of BMI from adolescence to young adulthood has been noted in previous studies [31,24,33], with stronger tracking for females also highlighted. The results of the present study thus confirm the potential utility of identifying adolescents at the age of 15 years who are at risk of persistent obesity, and targeting such adolescents with appropriate long-term lifestyle advice. Our results for diet, physical activity and fitness, however imply greater instability from adolescence to young adulthood, and consequently the need for shorter-term, ameliorative strategies based on regular monitoring of these behaviours and attributes.
Competing Interests
The authors declare that they have no competing interests.
Authors' contributions
CB conceived of the study, participated in its design and co-ordination and co-drafted the manuscript. PR supervised the collection of dietary data and co-drafted the manuscript. AG and GC carried out the statistical analysis. LM participated in the design and co-ordination of the project. JS conceived of the study and participated in its design and co-ordination. All authors read and approved the final manuscript.
Acknowledgments
This study was supported by grants from The British Heart Foundation and The Wellcome Trust.
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| 15462676 | PMC524366 | CC BY | 2021-01-04 16:37:47 | no | Int J Behav Nutr Phys Act. 2004 Oct 5; 1:14 | utf-8 | Int J Behav Nutr Phys Act | 2,004 | 10.1186/1479-5868-1-14 | oa_comm |
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Int J Behav Nutr Phys ActThe International Journal of Behavioral Nutrition and Physical Activity1479-5868BioMed Central London 1479-5868-1-151546267910.1186/1479-5868-1-15ResearchPerceived personal, social and environmental barriers to weight maintenance among young women: A community survey Andajani-Sutjahjo Sari 1saria@unimelb.edu.auBall Kylie 1kball@deakin.edu.auWarren Narelle 1n.warren1@pgrad.unimelb.edu.auInglis Victoria 1vinglis@deakin.edu.auCrawford David 1dcraw@deakin.edu.au1 Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, AUSTRALIA2004 5 10 2004 1 15 15 6 5 2004 5 10 2004 Copyright © 2004 Andajani-Sutjahjo et al; licensee BioMed Central Ltd.2004Andajani-Sutjahjo 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
Young women are a group at high risk of weight gain. This study examined a range of perceived personal, social and environmental barriers to physical activity and healthy eating for weight maintenance among young women, and how these varied by socioeconomic status (SES), overweight status and domestic situation.
Methods
In October-December 2001, a total of 445 women aged 18–32 years, selected randomly from the Australian electoral roll, completed a mailed self-report survey that included questions on 11 barriers to physical activity and 11 barriers to healthy eating (relating to personal, social and environmental factors). Height, weight and socio-demographic details were also obtained. Statistical analyses were conducted mid-2003.
Results
The most common perceived barriers to physical activity and healthy eating encountered by young women were related to motivation, time and cost. Women with children were particularly likely to report a lack of social support as an important barrier to physical activity, and lack of social support and time as important barriers to healthy eating. Perceived barriers did not differ by SES or overweight status.
Conclusions
Health promotion strategies aimed at preventing weight gain should take into account the specific perceived barriers to physical activity and healthy eating faced by women in this age group, particularly lack of motivation, lack of time, and cost. Strategies targeting perceived lack of time and lack of social support are particularly required for young women with children.
barriersphysical activityhealthy eatingweight maintenanceoverweightobesityyoung women
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Introduction
In many developed countries, overweight and obesity have reached epidemic proportions [1-8]. One group at particular risk of weight gain and the development of obesity is young women[2,9,10]. In the US, for example, one study that tracked weight in a large population sample over a 10-year period found that major weight gain (increased body mass index (BMI) > 5 kg/m2) was twice as common in women (5.3%) as in men (2.3%) [2]. A recent study of almost 9,000 women aged 18–23 years in Australia showed that 41% of the sample gained more than 5% of their BMI baseline over a four-year period (1996–2000) [9]. This risk of weight gain and the development of obesity places young women at increased risk of a range of chronic medical conditions and diseases, such as hypertension, type-2 diabetes, cardiovascular disease, and certain cancers [11].
In an effort to reverse the current global epidemic of overweight and obesity, strategies to promote increased physical activity and to encourage healthy eating have been promoted in many countries [12-15]. In Australia, for instance, individuals are encouraged to consume diets that are low in fat, high in fibre and rich in fruits and vegetables[13], and to participate in at least 30-minutes of moderate-intensity activities at least five days/week [12]. Despite such efforts, many young women do not meet the current physical activity recommendations [16] and their diets are less than optimal. For example, mean daily intakes of fruits and vegetables fall well below recommended levels [17] and 50% of young Australian women are consuming at least one takeaway meal per week, which is likely to be high in energy density [9]. Poor compliance with dietary and physical activity guidelines is not unique to Australia [18-20]. In addition, recent work we have conducted suggests that many young women do not consider the kinds of lifestyle changes that are being recommended as feasible for them in the context of their daily lives [21]. An understanding of the perceived barriers faced by young women in achieving healthy lifestyle changes is therefore important.
Most existing studies examining perceived barriers to physical activity and healthy eating have focused on the general population,[18,22-25]. with few specifically considering the perceived barriers experienced by those at particular risk of weight gain, such as young women. However, the perceived barriers faced by young women are likely to differ from those faced by other groups, such as by men or older women. For example, a study in the USA showed that women more frequently report 'tiredness' and 'time' as significant perceived barriers to healthy habits than do men, and that this may be partly attributable to their domestic situation [25]. In addition, young women are more likely than older women to experience particular life events (e.g. leaving family homes, starting work, entering a marital or de facto relationship, and becoming mothers) that may influence their physical activity and dietary habits [26,27].
As well as perceiving different barriers to those faced by other groups in the population, the perceived barriers to increasing physical activity and improving diet that young women face may vary according to their social and personal circumstances. For example, having children is likely to impact on a women's ability to adopt healthy habits [21,28,29]. In addition, persons of lower socioeconomic status (SES) may have poorer access to parks, walking or jogging trails, and gym equipment than those of higher SES [25]. Access to good quality, inexpensive healthy foods has also been reported to be more limited among persons of low SES; for instance, the cost of healthy foods has been reported to be greater for those living in deprived areas. [30,31]. A number of studies have suggested that a lack of knowledge is a greater barrier to eating a healthy diet among those of lower education level [22,23]. Being overweight can also be perceived as a significant barrier to physical activity [32]. However, whether or not these factors are perceived as barriers to physical activity and healthy eating among young women is unknown.
In order to develop appropriate and effective obesity prevention strategies for young women it is important to understand the barriers they perceive in attempting to control their weight. The aim of this study was to examine perceptions of a range of personal, social and environmental barriers to physical activity and healthy eating, specifically related to weight maintenance, among young women, and how these vary by domestic situation, SES and overweight status.
Methods
Participants
A total of 445 women provided data for this study. Initially, a sample of 1200 women aged 18–32 years was selected from the Australian Electoral Roll using a stratified random sampling procedure, with strata based on the number of eligible cases in each of the eight States/Territories of Australia. As voting is compulsory for Australian adults, the electoral roll provides a complete record of population data on Australian residents aged 18 years and over. Excluding those who had moved and left no forwarding address, the study achieved a response rate of 41% (462 women participated), which is comparable to response rates reported in similar postal surveys with this age group [33,34]. Data from 17 women who were pregnant were excluded.
The socio-demographic characteristics of the sample are reported in full elsewhere [21]. Briefly, 42% of the respondents were tertiary-educated. Half of the women were married and one in three had at least one child. One in three respondents was classified as overweight or obese. The socio-demographic profile of the sample was comparable to that of women of similar age (18–44 y) who participated in the most recent (2001) Australian National Health Survey [35].
Procedures
A questionnaire was developed and pilot-tested with a convenience sample of 10 women in the same age group as participants. The questionnaire, a study description, an invitation to participate, a consent form and a reply-paid envelope for returns were mailed to the study sample of women in October 2001. Non-responders were sent a reminder postcard two weeks later and a second reminder with replacement questionnaire a further three weeks later.
Measures
The participants completed the following questions.
Socio-demographic background
The socio-demographic questions included domestic situation (household composition) and education. Domestic situation was assessed by asking 'Who lives with you?' with response options: No-one, I live alone; Partner/spouse; Own children; someone else's children; parents; brothers/sisters; Other adult relatives; and Other adults who are not family members. This was subsequently re-categorized as living with parental family; living alone/share 'flatting'; living with partner (no children); or living with children (including those living with partner and child/ren, and single mothers). Education level (highest level of schooling: still at school, primary school, some high school, completed high school, technical/trade school certificate/apprenticeship, or University/tertiary qualification) was subsequently categorized as tertiary educated or not tertiary educated and used as an indicator of SES.
Body weight
Women were asked to self-report their height and weight and this information was used to calculate body mass index (BMI = weight (kg)/height (m2)). Self-reported height and weight have been shown to provide a reasonably valid measure of actual height and weight for the purpose of investigating relationships in epidemiological studies [36]. Women were categorised as overweight (BMI ≥ 25) or not overweight (BMI < 25) [11].
Perceived barriers to weight maintenance
Young women's perceptions of barriers to weight maintenance were assessed using 22 items. Participants were asked 'How important are the following as barriers to you keeping your weight at the level you want?' The complete list of barrier items is included in Tables 1 and 2. These items were based on a review of the literature investigating barriers to weight maintenance behaviours in other population groups [22-25]. There were two sets of perceived barriers assessed, those related to physical activity and those to healthy eating. For each set of questions, participants were asked about access to information; motivation; enjoyment; skills; partner support and children's support (where relevant); friends' support; access; cost; time due to job demands; and time due to family commitments as possible barriers. Response options for all barrier items were: Not a barrier; A somewhat important barrier; A very important barrier; Not applicable. For analyses, responses Not applicable and Not a barrier were combined.
Table 1 Perceived barriers to physical activity (N = 445)
Barriers to physical activity Factor loadings Not a barrier (%) A somewhat important barrier (%) A very important barrier (%)
Factor 1: Personal barriers to physical activity (Eigenvalue = 4.21, 38% variance, Cronbach's alpha = 0.76)
Do not have the motivation to do physical activity, exercise or sport 0.58 26 34 40
Not enjoying physical activity, exercise or sport 0.80 57 25 18
Do not have the skills to do physical activity, exercise or sport 0.70 81 14 5
Factor 2: Social support barriers to physical activity (Eigenvalue = 1.13, 10% variance, Cronbach's alpha = 0.68)
No partner's support to be physically active 0.80 78 13 9
No children's support to be physically active 0.82 94 4 2
No friends' support to be physically active 0.57 84 11 5
Factor 3: Environmental barriers to physical activity (Eigenvalue = 1.22, 11% variance, Cronbach's alpha = 0.71)
Do not have enough information about how to increase physical activity 0.75 83 12 5
Not having access to places to do physical activity, exercise or sport 0.57 66 23 11
Not being able to find physical activity facilities that are inexpensive 0.70 49 29 22
Not having the time to be physically active because of job 0.76 42 29 29
Not having the time to be physically active because of family commitments 0.68 63 22 15
Table 2 Perceived barriers to healthy eating (N = 445)
Barriers to healthy eating Factor loadings Not a barrier (%) A somewhat important barrier (%) A very important barrier (%)
Factor 4: Personal and environmental barriers to healthy eating (Eigenvalue = 4.61, 42% variance, Cronbach's alpha = 0.83)
Do not have enough information about a healthy diet 0.70 72 17 11
Do not have the motivation to eat a healthy diet 0.70 34 41 25
Do not enjoy eating healthy foods 0.80 64 26 10
Do not have the skills to plan, shop for, prepare or cook healthy foods 0.70 73 19 8
Do not have access to healthy foods 0.65 80 16 4
Not able to buy healthy foods that are inexpensive 0.60 60 27 13
Factor 5: Social and environmental barriers to healthy eating (Eigenvalue = 1.23, 11% variance, Cronbach's alpha = 0.72)
No partner's support to eat a healthy diet 0.76 79 13 8
No children's support to eat a healthy diet 0.80 97 2 1
No friends' support to eat a healthy diet 0.57 83 12 5
Not having time to prepare or eat healthy foods because of job 0.47 57 23 20
Not having time to prepare or eat healthy foods because of family commitment 0.55 77 15 8
Most important perceived barriers
In order to ascertain women's perceptions of the single most important barrier to physical activity and healthy eating (which may not have been included in the list of barriers developed by the researchers), participants were asked the following two open-ended questions: 'What is the one thing that makes it hardest for you to be physically active?' and 'What is the one thing that makes it hardest for you to eat a healthy diet?'
Statistical Analyses
Analyses were conducted mid-2003, using SPSS version 11.0.0 statistical software. [37]. Initially, descriptive analyses were performed to describe the proportion of women rating each of the items as not a barrier, a somewhat important barrier or a very important barrier. Content analyses of the open-ended questions were undertaken to identify main recurring themes.
Two separate exploratory factor analyses using SPSS FACTOR were performed with the 11 barriers to physical activity and the 11 barriers to healthy eating, to identify underlying patterns of relationships among individual items, and to reduce and simplify the items in order to facilitate subsequent analyses. Principal components analysis with varimax rotation (since factors were not correlated) was used. For any cross-loading items (i.e. items that had loadings of greater than 0.4 on more than one factor), only the higher loading was taken into account when calculating final factor scores. Inter-item reliability for each factor was assessed by Cronbach's α coefficients. Kaiser's measure of sampling adequacy was used to confirm the appropriateness of factor analysis [38]. Standardized factor scores were computed for each factor, with a large positive score representing more important barriers and a large negative score, less important barriers. Analysis of variance or t-tests were performed separately for each of the standardized factor scores to investigate differences in perceived barriers to physical activity and healthy eating with regard to domestic situation, SES and overweight status.
Results
Perceived barriers to physical activity
Table 1 presents the proportions of women reporting each of the perceived barriers to physical activity. The main barriers reported by young women related to motivation, time and cost. Combining the response categories 'somewhat important' and 'very important', 74% of the sample reported lack of motivation – 'not having the motivation to do physical activity, exercise or sport', time (58%) – 'not having time to be physically active because of my job,' and cost (51%) – 'not being able to find physical activity facilities that are inexpensive' – as common barriers to physical activity. Lack of time due to work commitments (reported by 58%) was more commonly reported than lack of time due to family commitments (37%), perhaps due to the relatively small proportion (30%) of young women in this study with at least one child. Less common perceived barriers to physical activity included lack of information, skills, partners' and children's support, and friends' support.
Perceived barriers to healthy eating
Table 2 presents perceived barriers to healthy eating. As with physical activity, lack of motivation (66%), lack of time due to job commitments (43%), and cost (inability to buy healthy foods that are inexpensive: 40%) were common perceived barriers. Less commonly reported barriers included lack of information, skills and friends', partners' and children's support, and access. As with physical activity, lack of time related to job demands (reported by 43%) was more common than lack of time due to family commitment (23%).
The most important perceived barriers to physical activity and healthy eating
Consistent with women's responses to the closed-ended questions, the most important perceived barriers to physical activity reported in response to the open-ended questions were lack of time due to work, study or family commitments (78%), lack of motivation (37%) and childcare issues (25%). The most important perceived barriers to healthy eating related to taste (24%); lack of time (21%); lack of motivation (13%); and the perception that healthy foods are inconvenient or expensive (13%).
Factor analysis of perceived barriers to weight maintenance
The factor analysis of the perceived barriers to physical activity revealed three interpretable factors (Table 1) with eigenvalues greater than one. These factors together explained 60% of the total variance. Two items – 'not having access to places to do physical activity, exercise or sport' and 'not having friends' support to be physically active' – cross-loaded on two factors and these items were included only on factors on which each item showed the largest loading. The Cronbach's α coefficients for the three factors ranged from 0.68 to 0.76, indicating moderate internal reliability. Provisional names were assigned for these three factors: 'personal barriers', 'social support barriers' and 'environmental barriers'. The items included as personal barriers to physical activity were related to motivation, enjoyment, and skill. Social support barriers encompassed lack of support from family and friends; and environmental barriers related to information, access, cost, and time.
The principal components analysis of the 11 barriers to healthy eating resulted in two distinct interpretable factors with eigenvalues greater than one (Table 2). The Cronbach's α coefficients for the two factors were 0.72 and 0.83, indicating moderate to good internal reliability. Together the two factors explained 53% of the total variance. Provisional names were assigned to these factors: 'personal and environmental barriers' and 'social and environmental barriers'. Personal and environmental barriers to healthy eating included motivation, enjoyment, skills, information, cost, and access. Social and environmental barriers were related to lack of support from family and friends and time constraints.
Associations of domestic situation, education and overweight status with perceived barriers
Mean factor scores did not vary according to women's overweight status or SES. Mean factor scores did differ significantly by domestic situation for two factors: social support barriers to physical activity and social and environmental barriers to healthy eating (see Table 3). Compared with women living in other domestic situations, women with children had the lowest score on the social support for physical activity factor, suggesting that lack of support from partners, children and friends was a more important perceived barrier to physical activity for these women. This group also had the lowest score on social and environmental barriers to healthy eating factor, suggesting that lack of social support and insufficient time were more important perceived barriers to healthy eating among women with children than among other women. Conversely, young women who lived with their parents had the highest scores on these factors, indicating the relative lack of importance of social support for physical activity, and social and environmental barriers to healthy eating, for this group.
Table 3 Mean standardized factor scores on weight maintenance by domestic situationa
Factor Domestic situation
Parents Alone/ Share Partner Children p
Personal barriers to physical activity 0.08 0.22 -0.09 -0.07 0.12
Social support for physical activity -0.37 -0.14 -0.06 0.55 .000
Environmental barriers to physical activity 0.13 0.12 0.03 -0.18 0.11
Personal and environmental barriers to healthy eating -0.04 0.23 0.02 -0.04 0.25
Social and environmental barriers to healthy eating -0.30 -0.16 -0.06 0.49 .000
a. A large positive score represents more important barriers; a large negative score, less important barriers.
Discussion
This study suggests that a lack of motivation, time constraints due to work, and cost issues are the key perceived barriers to maintaining weight faced by young women. Overall these findings support other research that has examined barriers to physical activity and healthy eating [18,22,25,39]. However, the present study is unique in providing an insight into the relative importance of a range of personal, social and environmental factors as perceived barriers to weight maintenance among young women, a high risk group for weight gain. Findings showed that young women tended to rate personal factors as key perceived barriers to physical activity and healthy eating, followed by environmental factors, with social factors rated as less important. While the environment is likely to be an important source of influence on obesity-related behaviours [40], these findings highlight that efforts to prevent obesity should not ignore the central role of cognitive factors. Given the striking similarities in the types of barriers reported to impede physical activity, and the perceived barriers to healthy eating, findings also suggest that there may be potential economies of scale in health promotion programs aimed at preventing weight gain among young women. For example, strategies aimed at boosting motivation for healthy behaviour may help to promote both increased physical activity and healthy eating simultaneously. While motivating young healthy women to adopt healthy eating and physical activity behaviors is likely to be challenging, recent intervention research suggests that motivationally-tailored interventions may be more successful that other approaches (e.g. based on social-cognitive theory) in promoting physical activity and healthy eating [41,42].
It is noteworthy that perceived barriers to weight maintenance did not vary by socio-economic status or overweight status in this sample of women. In contrast, previous research has shown that overweight men and women face a number of perceived physical activity barriers [32]. Similarly, given that diet varies by socio-economic status [43,44] we expected that women of lower socio-economic status would be more likely to experience barriers to eating a healthy diet. Previous studies also suggest that persons of low SES often live in areas where the cost of food is greater, and access to healthy foods is poorer [30,31]. The reasons for the difference between the present results and earlier findings are unclear. It may be, however, that in this sample of relatively young women, many were still acquiring their education, and hence any SES differences in perceived barriers to healthy behaviours were not yet established.
Compared to other young women, those living with children were the most likely to report lack of social support for physical activity, and lack of support and time for healthy eating, as key perceived barriers to maintaining their weight. Young women who lived with their parents were the least likely to perceive these to be barriers to weight maintenance. These findings are consistent with those of previous studies showing that getting married and having children are associated with decreased physical activity and greater weight gain [21,26]. Any weight gain prevention program targeting women with children should incorporate a focus on enlisting social support for both physical activity, and shopping for and preparing healthy foods.
In a previous study with the same sample, we reported that while the majority of the women were in a healthy weight range (51%) or overweight/obese (31%), 18% of the women were underweight [21]. It should be acknowledged that some women in this sample, particularly those who were underweight, may have been trying to gain weight. One limitation of the present study was that the questions assessing perceived barriers to weight maintenance did not distinguish women trying to keep their weight down, from those trying to keep their weight up, and interpretation of the questions on perceived barriers may have been slightly different between these groups. However, attempts to gain weight are relatively uncommon among young women [45], and hence this is likely to have affected only a small proportion of the sample. A second limitation of this study is that the barriers were not assessed objectively, but rather through self-reports (ie perceived barriers). Nonetheless, it is important to consider women's perceptions of factors hindering their efforts to engage in healthy behaviours, since objective barriers may be perceived differently by different women (e.g., poor access to a gym may be viewed as less of a barrier to physical activity among a woman who walks for exercise than one who prefers aerobics). Finally, although the study achieved a somewhat modest response rate, the sample was selected from a nationally representative sampling frame and the socio-demographic profile of women was comparable to that of similarly-aged women in the wider population [35].
Conclusions
The findings of this study highlight the need for health promotion strategies that provide increased motivation, support and skills to enable young women to shop and prepare healthy, quick and inexpensive meals. Similarly, the findings suggest a need to promote more time-efficient physical activity alternatives. Additional strategies that recognize the perceived barriers to physical activity and healthy eating faced by young women with children are particularly required.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
SA conducted the literature review, final statistical analyses and early drafts of the results and conclusions sections. KB and DC conceived the study, design and measures, collected the data, coordinated the analyses and participated in the write-up of all sections. NW conducted preliminary analyses and drafting of early results. VI contributed to drafting the final manuscript.
Acknowledgements
Kylie Ball and David Crawford are each supported by Australian National Health and Medical Research Council/National Heart Foundation Career Development Awards.
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| 15462679 | PMC524367 | CC BY | 2021-01-04 16:37:47 | no | Int J Behav Nutr Phys Act. 2004 Oct 5; 1:15 | utf-8 | Int J Behav Nutr Phys Act | 2,004 | 10.1186/1479-5868-1-15 | oa_comm |
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RetrovirologyRetrovirology1742-4690BioMed Central London 1742-4690-1-321547655410.1186/1742-4690-1-32ResearchIdentification of endogenous retroviral reading frames in the human genome Villesen Palle 1palle@birc.au.dkAagaard Lars 1laa@birc.au.dkWiuf Carsten 1wiuf@birc.au.dkPedersen Finn Skou 23fsp@mb.au.dk1 Bioinformatics Research Center, University of Aarhus, Høegh-Guldbergs Gade 10, Bldg. 090, DK-8000 Aarhus, Denmark2 Department of Molecular Biology, University of Aarhus, C. F. Møllers Allé, Bldg. 130, DK-8000 Aarhus, Denmark3 Department of Medical Microbiology and Immunology, University of Aarhus, DK-8000 Aarhus, Denmark2004 11 10 2004 1 32 32 22 9 2004 11 10 2004 Copyright © 2004 Villesen et al; licensee BioMed Central Ltd.2004Villesen 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 endogenous retroviruses (HERVs) comprise a large class of repetitive retroelements. Most HERVs are ancient and invaded our genome at least 25 million years ago, except for the evolutionary young HERV-K group. The far majority of the encoded genes are degenerate due to mutational decay and only a few non-HERV-K loci are known to retain intact reading frames. Additional intact HERV genes may exist, since retroviral reading frames have not been systematically annotated on a genome-wide scale.
Results
By clustering of hits from multiple BLAST searches using known retroviral sequences we have mapped 1.1% of the human genome as retrovirus related. The coding potential of all identified HERV regions were analyzed by annotating viral open reading frames (vORFs) and we report 7836 loci as verified by protein homology criteria. Among 59 intact or almost-intact viral polyproteins scattered around the human genome we have found 29 envelope genes including two novel gammaretroviral types. One encodes a protein similar to a recently discovered zebrafish retrovirus (ZFERV) while another shows partial, C-terminal, homology to Syncytin (HERV-W/FRD).
Conclusions
This compilation of HERV sequences and their coding potential provide a useful tool for pursuing functional analysis such as RNA expression profiling and effects of viral proteins, which may, in turn, reveal a role for HERVs in human health and disease. All data are publicly available through a database at .
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Background
It has become evident that the human genome harbors a fairly small number of genes, and exons account for little over 1% of our DNA. This stands in stark contrast to various types of repetitive DNA, and it has been estimated that transposable elements alone take up almost half of our genome [1]. Among such multi-copy elements are human endogenous retroviruses (HERVs). These represent stably inherited copies of integrated retroviral genomes (so-called provirus structures) that have entered our ancestors' genome. It has been estimated that HERVs and related sequences such as solitary long terminal repeat structures (solo-LTRs) and retrotransposon-like (env-deficient) elements constitute approximately 8% of the human genome [1].
Phylogenetic analysis of the retroviral polymerase gene (pol) [2] and envelope genes (env) [3] have identified at least 26 distinct HERV groups. However, less well-defined sequence comparisons suggest that there may be well over 100 different HERV groups [4,5]. Within the family of Retroviridae most of the seven genera are represented by endogenous members, and HERVs are divided into class I, II and III depending on sequence relatedness to gammaretroviruses, betaretroviruses or spumaviruses, respectively. Many HERVs are named according to tRNA usage (i.e. HERV-K has a primer binding site that matches a lysine tRNA), while others have been more or less provisionally named by their discoverer. It seems increasingly clear that the nomenclature for endogenous retroviruses (ERVs) needs to be revised to accommodate such wide diversity. Furthermore, it is evident that many more ERVs are yet to be discovered as retroviral elements are present in most, if not all, vertebrates and even in some invertebrates [6,7].
With a single exception (HERV-K) all HERV groups are ancient (i.e. entered the genome prior to human speciation) and entered our genome at least 25 million years ago [6,8,9] presumably as an infection of the germ-line. Alternatively, it is possible that ERVs have evolved from pre-existing genomic elements such as LTR-retrotransposons [10]. After colonization most HERV groups have spread within the genome either by re-infection or intracellular transposition [11,12] and have reached copy numbers ranging from a few to several hundreds [13]. The vast majority of these provirus copies are non-functional due to the accumulation of debilitating mutations. Indeed, no replication-competent HERVs have yet been described, although fully intact members of the HERV-K group have been reported [14]. Other mammalian species such as mouse, cat and pig harbor modern replication-competent ERVs that to a large extent may interact with related exogenous viruses [15,16].
The presence of endogenous retroviral sequences in our genome has several possible implications: i) replication and (random) insertion of new proviral structures, ii) effect on adjacent cellular genes, iii) long range genomic effects and iv) expression of viral proteins (or RNA). Since the majority of HERVs are highly defective no de novo insertions have been observed and presumably HERV mobilization very rarely results in spontaneous genetic disorders or gene knock-outs as seen with other active retrotransposons such as L1 elements [17]. However, existing HERV loci have been shown to alter gene expression by providing alternative transcription initiation, new splice sites or premature polyadenylation sites [18]. Moreover, the presence of enhancers and hormone-responsive elements in the LTR structure of existing HERVs may up- or down-regulate the transcription of flanking cellular genes. It has been speculated that transcription initiation from HERVs/solo-LTRs into neighboring genes in the antisense orientation might interfere with gene expression. Alternatively, gene transcripts encompassing antisense viral sequences could down-regulate HERV expression. The human C4 gene may provide an example of the latter, where antisense HERV-K sequences are generated and display an effect on a heterologous target [19]. Such effects may possibly rely on formation of dsRNA and RNA interference. On a genome scale the presence of closely related sequences may trigger events of ectopic recombination and hence lead to chromosomal rearrangements. Sequence analysis of provirus flanking-DNA suggests that this has occurred during primate evolution [20]. The frequency and significance of such events in human disorders are not clear at present. Finally, HERVs may express viral proteins. The common retroviral genes, gag, (pro), pol and env lead to expression of 3 viral polyproteins (Gag, Gag-Pol and Env) that are processed by a viral or host protease into the active structural and enzymatic subunits. Although most HERV genes are no longer intact, a small fraction has escaped mutational decay. For a subgroup of HERV-K (HDTV) all proteins can apparently be expressed and particle formation has been detected in teratocarcinoma cell lines [13]. Furthermore, HERV-K (HDTV) also directs expression of a small accessory protein Rec (formerly cORF) that up-regulates nucleo-cytoplasmic transport of unspliced viral RNA [21,22]. Loci from other HERV groups have maintained a single intact open reading frame, such as the env genes from HERV-H [23], HERV-W [24] and HERV-R (ERV3) [25]. Conservation of an open reading frame during primate evolution clearly suggests some biological function. Animal studies have demonstrated that ERV proteins may in fact serve a useful role for the host either by preventing new retroviral infection or by adopting a physiological role. Syncytin, an Env-derived protein that mediates cell-cell fusion during human placenta formation, provides a striking example of the latter [26,27]. Recently, a second Env protein, dubbed Syncytin 2, proposed to have a similar cell-fusion role [28] was identified. Env proteins may also inhibit cell entry of related exogenous retroviruses that use a common surface receptor, and a Gag-derived protein restricts incoming retroviruses in mice [29].
In the literature, expression of HERVs has frequently been linked with human disease including various cancers and a number of autoimmune disorders [30]. While causal links between disease and HERV activity have yet to be established, it is clear from animal models that expression of endogenous retroviral proteins can affect cell proliferation and invoke or modulate immune responses. A few recent examples include i) the possible association of Rec (HERV-K) with germ-cell tumors [31], ii) the immunosuppressive abilities of HERV-H Env in a murine cancer model resulting in disturbed tumor clearance [32] and iii) the possible superantigenic (SAg) properties of envelopes from HERV-K and HERV-W [33,34] and the increased activity of such proviruses in multiple sclerosis [34], rheumatoid arthritis [35], schizophrenia [36] and type-1 diabetes [33]. SAg expression from the HERV-K18 locus may furthermore be induced by INF-α and thus viral infection such as Epstein-Barr virus [37,38]. One major problem in verifying putative disease association is the multi-copy nature of HERVs and the ambiguous assignment to individual provirus; a problem that can be solved by properly annotating the human genome.
Among Env-associated effects the mechanism of SAg-like activity is believed to involve true epitope-independent stimulation of T-cells, while the mechanism of action of the immunosuppressive CKS-17-like domain is still unknown. This immunosuppressive peptide region maps to the envelope gene [39] and may significantly alter the pathogenic properties of retrovirus and even enhance cancer development. Phylogenetic analysis suggests that a CKS17-like motif arose early in the evolution of retrovirus and is widespread in many current HERV lineages [3], thus identification of novel envelope genes attracts particular attention.
Computer-assisted identification of HERV loci has previously been reported. These include searching conserved amino-acid motifs within the pol gene [2,40] and env gene [3], detection of full-length env genes by nucleotide similarity [41] and compiling of LTR- or ERV-classified repeats as reported by RepeatMasker analysis [4,5,42]. Currently only Paces et al. [5,42] provide a searchable database where individual loci are mapped as chromosomal coordinates [43]. However, except for detection of 16 full-length env genes in a recent survey by de Parseval et al [41] and a detailed analysis of intactness of HERV-H- related proviruses [40], no one has systematically detected HERV regions and scanned them for content of viral open reading frames. In this paper we report mapping of 7836 regions in the human genome that show sequence resemblance to known retroviral genomes which cover the majority of large proviral structures or HERV loci, and, importantly, provide a detailed annotation of all viral open reading frames.
Results
In order to screen the human genome for HERV-related sequences we have performed multiple nucleotide BLAST searches and subsequently clustered neighboring hits into larger regions up to about 10 kb in size (Figure 1A/1B). The query sequences cover all known retroviral genera and include both endogenous and exogenous strains from various host organisms. To avoid detection of solo-LTR structures we used the coding regions as query (Figure 1A). The corresponding DNA sequences were scanned for the presence of all viral open reading frames (vORFs, here defined as a stop codon to stop codon fragment above 62 codons) with significant homology to known retroviral proteins (E<0.0005) and annotated as Gag, Pol or Env. From our initial BLAST-identified regions we detect 7836 genuine HERV-related regions in which at least one, mostly several vORF can be detected. The majority of these HERV regions correspond quite well to the internal parts of a provirus locus. However, the insertion of other repetitive elements inside a provirus will produce a mosaic structure that is less well-defined. In terms of our HERV regions this may lead to either "partition" of a provirus into two or more consecutive HERV regions (as illustrated by the "provirus into provirus" insertion depicted in Figure 1B) or enclosure of minor stretches of non-retroviral DNA (such as Alu elements or small microsatellites) within the sequences of some HERV regions. Hence, the precise boundaries of the retrovirus-related DNA (as often defined by nucleotide similarity alone) must be manually inspected and the flanking LTRs must be identified in order to deduce the exact proviral structure. To assist in LTR determination we have scanned for flanking direct repeats and included LTR elements as identified by RepeatMasker analysis [4]. Due to these exceptions we shall refer to our data as "HERV regions" although they in most cases correspond to individual HERV loci.
Figure 1 A: Genomic organization of simple retroviruses when present as a provirus (DNA) integrated in the host genome. The regulatory long terminal repeats (LTRs) flank the internal three major genes gag, pol and env. A fourth gene pro is present between gag and pol for some retroviruses, while part of either gag or pol in others. B: Individual BLAST hits (white and yellow boxes) on either strand of the human genome were clustered into HERV regions (blue boxes) or discarded by using a score function. Finally, only HERV regions with at least one retroviral ORF were kept (see Materials and Methods). In the example illustrated HERV ID 5715 was presumably inserted into an existing HERV locus with the opposite orientation. HERV ID 5715 is located in the first intron of the CD48 gene (antisense direction) and is also known as HERV-K18 or IDDMK1,222. C: HERV ID 5715 with graphical vORF annotation. Putative LTR structures are indicated and all ORFs (stop-codon to stop-codon fragments above 62 aa) are mapped and annotated by homology criteria
The average region size is 4300 nucleotides and the ~7800 HERV regions cover ~1.1% of the human genome. All data are publicly available as a searchable database at Our data include i) chromosomal coordinates and sequence information of the 7836 HERV regions, ii) annotation of ~38000 retroviral ORFs within these regions and iii) graphical visualization of individual HERV regions (Figure 1C) or larger chromosomal window. All DNA and predicted vORF sequences can be retrieved and is linked to external genome browsers for further analysis.
Skewed chromosomal distribution and few intragenic HERVs
The 7836 HERV regions (~2.7 per Mb) are not uniformly distributed among the 22+2 chromosomes (χ2 test, P~0). Table 1 summarizes the genome distribution statistics, from which it is clear that chromosomes 2, 7, 9, 10, 15, 16, 17, 20 and 22 are less densely populated, while chromosomes 4, 19, X and Y have higher density than expected from a random distribution. In particular, the Y chromosome stands out with more than 14 HERVs per Mb. The distribution of HERVs per Mb along each of the chromosomes is also not uniform, perhaps except at chromosome 21 (Table 1). Furthermore, we observe local "hotspots", most prominent for chromosomes 19, X and Y. For instance, a 5 Mb window in chromosome Y (position 18–23 Mb) encompasses 120 HERV regions. Moreover, there are a number of cases where HERVs have presumably been inserted right next to or even into an existing locus. HERV ID 5715 provides a nice example of the latter, where a HERV-K member presumably has integrated into an existing HERV-K (Figure 1B). We also detect the perfect HERV-K tandem repeat previously reported [44]. However, in contrast to Reus et al. [44] we find a single in-frame stop codon within both gag genes (HERV ID 26658–9. W). We also find other examples of closely situated HERV loci as for instance HERV ID 44313 that is composed of two proviruses of distinct origin (HERV-K and a γ-retrovirus-like sequence) both severely degenerated.
Table 1 Genomic distribution of HERV regions
Chr. Length (Mb) Windows analyzeda Observed HERVs Expected HERVs χ2 testb χ2 test within chr.c
1 246 228 654 614.7 0.0987 <0.0001
2 243 242 534 652.4 1.3E-06 <0.0001
3 199 197 581 531.1 0.0250 <0.0001
4 192 190 641 512.2 4.0E-09 <0.0001
5 181 180 446 485.3 0.0656 <0.0001
6 171 169 496 455.6 0.0513 <0.0001
7 159 157 342 423.3 4.9E-05 0.0003
8 146 145 396 390.9 0.7923 <0.0001
9 136 120 258 323.5 2.0E-04 <0.0001
10 135 135 304 364.0 1.3E-03 <0.0001
11 134 133 379 358.6 0.2695 <0.0001
12 132 132 393 355.9 0.0440 <0.0001
13 113 98 239 264.2 0.1146 <0.0001
14 105 88 205 237.3 0.0335 <0.0001
15 100 83 135 223.8 1.7E-09 <0.0001
16 90 82 101 221.1 2.6E-16 <0.0001
17 82 80 98 215.7 4.4E-16 <0.0001
18 76 77 167 207.6 0.0043 0.0001
19 64 57 259 153.7 9.4E-18 <0.0001
20 64 62 76 167.2 1.0E-12 <0.0001
21 47 36 85 97.1 0.2181 0.0588
22 49 36 55 97.1 1.7E-05 <0.0001
X 154 152 629 409.8 9.7E-29 <0.0001
Y 50 25 359 67.4 1.1E-278 <0.0001
TOTAL 3068 2905 7832 7832d
a Only windows overlapping with NCBI GoldenPath (release 34)
b Single chromosomes tested against group of other chromosomes. P-values below the significance level 0.00208 (0.05/24, Bonferroni corrected) are underlined.
c The genomic positions of HERVs were χ2 tested against a random distribution using 10000 simulations for each chromosome.
d Four additional HERV regions are located in the DR51 haplotype of the HLA region on chromosome 6 and not counted here.
The number of HERV regions that are located within (non-HERV) genes are significantly reduced as compared to a random distribution (χ2 test, P < 10-300), and only 13% of our 7836 HERV regions are situated inside a gene, despite that 33% of the genome is spanned by genes (Figure 2). In total 813 genes (see Additional file 1) carry one or more HERV regions within their predicted boundaries and as such provide a valuable set of genes that may show altered expression due to the presence of internally located proviruses. There is a strong bias (χ2 test, P < 10-52) for intragenic HERVs to be orientated antisense relative to the gene (Figure 2). HERV sequences located between genes are equally distributed between the two strands, and the orientation does not depend on the distance from the gene (data not shown).
Figure 2 Number of HERV regions located inside genes, and their orientation relative to the gene. The expected number assumes a random genomic distribution.
Limited number of intact viral open reading frames
Of the ~38000 retroviral ORFs 25% are classified as Gag, 7% as Pro, 55% as Pol and 13% as Env proteins. This correlates well with the expected size of the gag, pro, pol and env genes, although Pol may be slightly overrepresented. The far majority of the vORFs (stop to stop) are short (Table 2) and presumably do not encode any functional proteins, although a role in cellular processes cannot be excluded. Long vORFs on the other hand may still retain their original viral function. In total 42 HERV regions encompass either a Gag or an Env ORF above 500 codons or a Pol ORF above 700 codons (which approach the size of intact viral proteins) and together they count 17 Gag, 13 Pol and 29 Env proteins (Table 2 and Figure 3). Only two HERV-K related loci (HERV ID 13983 and 29013) carry long reading frames for all viral genes. However, none of them are completely intact. In fact, 41 of the above 59 long vORFs, are all betaretroviral and stem from the HERV-K group. Interestingly, 15 of the remaining 18 non-betaretroviral ORFs are envelope proteins (see below). Our method only detects a single non-betaretroviral Gag ORF above 500 codons (which is located in a gammaretroviral structure, HERV ID 44200–1), while two long Pol ORFs are both present in full-length HERV-Fc and HERV-H elements (HERV ID 1178 and 10816) that also harbour intact env genes [41,45].
Table 2 Distribution of vORF lengths (stop codon to stop codon)
vORF size (aa/codons) Gag Pro Pol Env HERV regions
63 – 100 4820 1322 10390 2354 6795
100 – 200 4015 1002 9110 2278 5803
200 – 300 643 165 1426 361 1894
300 – 400 160 54 286 81 527
400 – 500 33 3 70 24 123
500 – 600 1 20 12 33
600 – 700 4 10 9 22
700 – 800 10 4 7 15
800 – 900 1 1 2
900 – 1000 1 5 6
> 1000 1 3 4
Figure 3 Genomic distribution of all Gag (red) and Env (blue) ORFs above 500 aa and Pol (green) ORFs above 700 aa. Right-pointing triangles denote intact ORFs, while left-pointing triangles denote ORFs that are almost-intact besides a single stop codon or frame-shift mutation.
If one extends the search criteria and scans the human genome for retroviral genes where a single mutation (one nucleotide insertion, deletion or substitution) either removes premature termination or restores the correct reading frame, the number of long Gag, Pol and Env proteins increases two-fold to 27, 23 and 43, respectively (Figure 3).
Novel envelope genes identified
Our method detects 29 Env ORFs (stop to stop) above 500 codons (Table 3), which comprise a few seemingly intact or almost-intact env genes in the human genome not previously reported. One particularly interesting locus (HERV ID 40701) shows similarity to a recently reported full-length endogenous retrovirus from Zebrafish (Danio rerio), dubbed ZFERV [46]. A phylogenetic analysis of the Zebrafish ERV suggested that it is distinct from existing retrovirus genera being most similar to gammaretroviruses [46]. An analysis of a short Gag and Pol ORF upstream of the Env gene (HERV ID 40701) confirms the relatedness to gammaretroviruses (weak similarity to Feline leukemia virus). Also, two loci (HERV ID 44200–1 and 44204–5) harbor novel Env-like ORFs that C-terminally show homology to Env from HERV-W/syncytin-1 [26,27] and HERV-RFD/syncytin-2 [28], while the N-terminal sequences show no clear homology. The identified ORFs are highly similar (96% aa identities) except for a small C-terminal truncation and both genes are located within a narrow 40 kb region at chromosome 19 (Table 3). Interestingly, both these loci are positive in our EST mapping analysis (see below). Furthermore, among the 29 Env ORFs, five turned out to carry a specific 292 bp deletion (indicative for type 1 HERV-K-HML-2) that fuses the pol and env reading frames. The same deletion is present in the HERV-K18 Env locus that has been reported to have SAg-like activity [37].
Table 3 Previously and newly identified long Env ORFs in the human genome
Genea Bibliographic name Chromosomal position of locus (NCBI release 34) Lengthc ORF ID Comment EST matchesd
HERV H- like Env Chr. X 70307525–70316940 (+1) 474 4769 N-term unknown Minor C-term deletion
EnvF(c)1 Chr. X 95868842–95875915 (+1) 583 8944 Intacta
HERV-W Env Chr. X 105067535–105070015 (-1) 475 24413 Minor N-term deletion 3
HERV-K Env (type 1) Chr. 1 75266332–75270814 (+1) 586 42910 In frame pol-env fusion 3
HERV-K Env (type 1) K18-SAg IDDMK1,222 Chr. 1 157878336–157885675 (+1) 560 46511 In frame pol-env fusion
EnvH3 EnvH/p59 Chr. 2 155926784–155933168 (+1) 554 70149 Intacta
HERV-K Env (type 1) Chr. 2 130813720–130815944 (-1) 687 80419 In frame pol-env fusion
EnvH1 EnvH/p62 H19 Chr. 2 166767087–166774769 (-1) 583 82113 Intacta
EnvR(b) Chr. 3 16781208–16788508 (+1) 513 86185 Intacta
HERV-K Env (type 1) Chr. 3 114064939–114072223 (-1) 597 103885 In frame pol-env fusion C-term deletion
EnvH2 EnvH/p60 Chr. 3 167860265–167867997 (-1) 562 107739 Intacta
HERV-K-like Env Chr. 5 34507318–34513254 (-1) 475 153615 N- and C-term deletion
EnvFRD Syncytin 2 Chr. 6 11211667–11219905 (-1) 537 171089 Intacta 16
EnvK4 HERV-K109 Chr. 6 78422690–78431275 (-1) 697 174741 Intacta
EnvK2b HML-2.HOM HERV-K108 Chr. 7 4367317–4383401 (-1) 698 188263 188274 Intacta 4
EnvR Erv3 Chr. 7 63862984–63871411 (-1) 605 191393 Intacta 17
EnvW Syncytin (1) Chr. 7 91710047–91718755 (-1) 537 192333 Intacta 100
EnvF(c)2 Chr. 7 152498159–152502575 (-1) 545 195475 Intacta 1
EnvK6 HERV-K115 Chr. 8 7342682–7353583 (-1) 698 204173 Intacta
HERV-K Env Chr. 11 101104479–101112064 (+1) 661 240932 Minor C-term deletion 6
HERV-K-like Env Chr. 12 104204746–104209814 (+1) 658 255589 Minor C-term deletion
EnvK1 Chr. 12 57008431–57016689 (-1) 697 260042 Intacta
ZFERV-like Env Chr. 14 91072914–91085655 (-1) 664 285129
HERV-K Env (type 1) Chr. 16 35312483–35314318 (+1) 550 293143 In frame pol-env fusion
EnvT Chr. 19 20334642–20343232 (+1) 664 310016 Intacta
HERV-W/FRD-like Env Chr. 19 58210000–58211244 (+1) 477 312172 N-term unknown Minor C-term deletion 3
HERV-W/FRD-like Env Chr. 19 58244133–58246051 (+1) 535 312208 N-term unknown 3
EnvK3 HERV-K (C19) Chr. 19 32821287–32829201 (-1) 698 314652 Intacta
a Nomenclature for verified and complete env genes as in de Parseval et al. [41]. Note that EnvK5 (HERV-113) at Chr. 19 [14] is not present in the NCBI release 34 of the human genome.
b EnvK2 is organized as a tandem repeat.
c ORF length from start to stop codon.
d Number of ESTs that map to the same genomic region (see text).
EST matching to HERV regions with long ORFs
We mapped 265 ESTs to one of the 42 HERV regions that encode a long Gag, Pol or Env ORF (Figure 3). The EST GenBank accession number, the matching HERV ID and the source organ and tissue type are provided as supplementary material (see Additional file 2). Briefly, 20 of the 42 HERV regions were found to have matching ESTs suggesting transcriptional activity. For the long envelope genes we have included the number of EST matches in Table 3. Our analysis reveals that besides "activity" of members of the HERV-K group, only HERV-Fc(2), HERV-R (Erv3) and a few HERV-W/FRD members (including Syncytin-1 and -2) have unambiguous EST matches. By far, Syncytin-1, dominates with 100 EST matches, followed by Syncytin-2 and HERV-R. Syncytin-1 and Syncytin-2 were predominantly found in placental EST libraries (see Additional file 2), which is also true for 5 of 17 HERV-R ESTs. Interestingly, among the two (partial) HERV-W/FRD-like env genes four of 6 ESTs are also derived from placental tissues.
Discussion
We report a mapping of 7836 loci in the human genome that show nucleotide sequence similarity to retroviral genomes and importantly, we provide a detailed analysis of their coding potential by annotation of all viral ORFs (stop-codon to stop-codon fragments longer than 62). This compilation of HERV regions and their corresponding viral ORFs is available as a searchable database [47]. A graphical example is provided in Figure 1C. In total our HERV regions (which exclude flanking LTRs) amount to 1.1 % of the human genome, a number that agrees well with previous reports [1,42].
The vast majority of the mapped HERV regions contain several frame-shift mutations or in-frame stop codons that truncate the viral ORFs and thus testify to their old association with the human genome. In fact, we detect only 42 proviruses that have retained Gag, Pol or Env ORFs in the size range that approach full-length proteins (Figure 3 and Table 2). As expected the majority are part of the evolutionary young HERV-K (HML-2) group. Neither of these HERV-K loci are completely intact, although one potential replication-competent locus (HERV-K113, polymorphic for humans and not present in the NCBI34 genome) has been reported [14]. Alternatively, complementation among HERV-K loci may open up for infectious particle formation, and clearly defines interesting candidates to investigate experimentally. Moreover, assuming a high error-rate during transcription or retrotransposition, one cannot exclude that almost-intact loci may occasionally revert to their original functional state and become replication-competent. Based on our data about 34 gag, pol or env genes can be restored by a single point mutation or a single insertion-deletion event.
Within our list of intact or almost-intact viral ORFs in the human genome, we detect only a single gag gene and two pol genes that are not from the HERV-K group. However, among the 29 long envelope genes 15 are gammaretroviral (Table 3). The fragmented, pseudogene nature of the gag and pol genes (small ORFs) in several of these provirus loci strongly suggests that selection has preserved the env genes. In case of syncytin-1 and -2 (HERV-W and HERV-FRD members, respectively) evolutionary conservation can be understood in functional terms, since the encoded envelope proteins have been suggested to play an essential role in placental development by causing trophoblast syncytia formation [28,48]. Compelling evolutionary evidence for purifying selection in these genes has recently been gathered to support this hypothesis [28,49,50].
Concerning other ancient loci such as HERV-R (erv3) no evidence for a physiological role has yet been established despite a remarkable conservation and expression of the env gene. Potential cellular roles for envelope genes that may drive purifying selection include i) protection from infection by related retroviruses by receptor interference as demonstrated for the murine fv4 locus [51], ii) mediator of organized cell-cell fusion like the syncytin genes [26-28] and iii) a hypothesized role in preventing the immune response against the developing embryo by means of the immunosuppressive domain [52].
Two seemingly intact env genes not detected in the recent survey of intact human envelope genes [41] are equally interesting in terms of possible functional conservation. One is located on chromosome 14q32.12 and this novel gene shows low but significant similarity to a recently reported endogenous retrovirus from Zebrafish (ZFERV [46]). BLAST analysis of the protein coding regions suggests that this HERV group belong to the gammaretroviral genera. Whether this gene is still active or whether the encoded protein still maintains function and/or plays a cellular role is yet to be established. Although we were unable to detect any unambiguous EST matches to this gene (Table 3), RT-PCR analysis indicates low RNA abundance in a few human tissues including placenta (Kjeldbjerg AL, Aagaard L, Villesen P and Pedersen FS, unpublished). A second seemingly intact novel env gene is found on chromosome 19q13.41, and interestingly a C-terminal truncated "twin" gene is located just 40 kb away. Both genes appear to be active as judged by EST data (Table 3) mostly in placental tissue (see Additional file 2). We have been able to confirm this by RT-PCR analysis (unpublished), and ongoing expression analysis aims at clarifying the activity and function of these novel genes.
Among the long betaretroviral env genes five turned out to carry a specific 292 bp deletion that fuses the pol and env reading frames. This deletion variant of the HERV-K (HML-2) group is indicative of the type 1 genomes [53] that despite the lack of functional proteins have been mobilized quite efficiently. Alternatively, recombination or gene conversion may have conserved this HERV-K deletion variant [11,54]. It is noteworthy that the Env protein from one of these Ä292-genes, HERV-K18, is reported to have SAg-like activity [37], and a similar function of the other four K18 SAg-like genes is an open question.
Although our analysis is extensive it is most likely not exhaustive. The sensitivity is obviously limited by our query sequences, and some ancient HERVs may have suffered from the mutational decay to a degree which makes is impossible to detect them by homology. For instance, the ZFERV-related env gene reported by us was only detected due to inclusion of the ZFERV sequence [46], and although available data such as HERVd [43] also points to this region it is reported as a number of incomplete HERVs. Similarly, nucleotide based searches (as RepeatMasker and BLAST detection) only partially detect the novel HERV-W/RFD-like envelope genes and the intact envelope genes among HERV-Fc family even though these proviruses are fairly intact as suggested by a recent mobilization of HERV-Fc in the primate lineage [45]. Thus, inclusion of more retroviral query sequences as our vORF validated HERV data may likely improve detection methods in an iterative manner ("phylogenetic walking") as previously applied by Tristem [2]. Finally, screening the human genome in silico does not guarantee detection of polymorphic HERV loci in which the empty pre-integration site is still segregating in the human population. Indeed, an experimental survey has recently detected two such polymorphic loci in the human population (HERV-K113 and 115 [14]), and like HERV-K113 other recently acquired proviruses may escape our attention.
In general, our analysis of the genomic positions of our ~7800 HERV regions revealed three distinct patterns, which all confirm earlier reported results: i) there is an unequal distribution of HERVs between chromosomes and along the genome. In particular the Y chromosome stands out with a five-fold excess of our vORF positive (internal) HERV sequences (Table 1), and it has thus been dubbed "a chromosomal graveyard" [55]. This agrees well with previous genome surveys of LTR/ERV-related elements and the phenomenon may likely be associated with the high level of heterochromatin and low levels of recombination [55-58]. ii) HERVs are underrepresented within genes and iii) HERVs found in introns are predominantly orientated in the antisense direction (Figure 2). This pattern is well known [56,58] and expected due to selection against gene disruption or interference by retroviral regulatory elements such as promoters, splice sites and polyadenylation signals. This selection may have counteracted a preference for proviral integration (and retrotransposition) near or inside genes as suggested by recent studies for several retroviral genera [59,60].
Conclusion
Initially, HERV discovery was driven by the search for replication-competent viruses and their possible association with human cancers as established in other species. Recent research has demonstrated that the presence of endogenous retroviral sequences in our genome has a number of complex functional and evolutionary consequences and cannot simply be regarded as "junk" DNA. The increased complexity and diversity of HERVs as testified by the identification of two novel env genes in this survey make expression analysis and functional assessment a difficult task. To aid this process our genome-wide HERV data as well as predictions of Gag, Pol and Env reading frames in these loci are a useful resource and our data can be searched and visualized at Clearly, the 42 HERVs encompassing intact or near-intact gag, pol and env genes as described here are interesting experimental objects, although less intact viral proteins may also hold biological activity. In the near future use of comparative genomics and mapping of allele polymorphisms will most certainly enhance identification of endogenous retroviruses and reveal selection patterns that may eventually decipher a role for these genes in human health and/or disease.
Methods
In order to identify HERV regions in the human genome we performed BLAST searches using sensitive parameters. BLAST hits were saved in a database and subsequently clustered into putative HERV loci. These putative loci were then scanned for viral Open Reading Frames (vORFs) and the presence of flanking direct repeat sequences (putative LTRs). Subsequently, ORFs were categorized based on a library of known retroviral proteins and non-retroviral proteins.
Identifying HERV regions
In order to cover as many different HERV families as possible we compiled a query set of 237 publicly available sequences from Genbank, published papers and Repbase sequences [4]. These sequences cover all known retroviral genera and include both endogenous and exogenous strains from various host organisms (the query set is available upon request). Each query sequence was manually edited, removing LTR elements in order to avoid detection of solo LTRs. BLAST searches against contigs from the NCBI release 34 of the human genome were performed using WU-BLAST (Gish, W. (1996–2003) ), with default parameters except for W = 8, E = 0.001, V = 1000000, B = 1000000. Search results were stored in a MySql database and mapped to chromosomal positions using Ensembl Bioperl packages [61].
Overlapping BLAST hits were clustered into putative HERV regions allowing a gap of 500 nucleotides between hits. A region-score was calculated based on the sum of e-value weighted hitlengths divided by region length. Only regions longer than 300 nucleotides and a region-score > 3.0 (threshold based on empirical tests) were kept, resulting in 45658 putative HERV region.
Detection of direct flanking repeats (putative LTRs) were done by comparing a window before and after the HERV region.
ORF finding and categorization
For the 45658 putative HERV loci, we scanned the DNA sequence (including 1000 bases flanking the locus) for forward open reading frames (stop-codon to stop-codon) of lengths > 62 aminoacids (aa). Stop-codon-to-stop-codon fragments were chosen to accommodate the use of non-conventional translational initiation by retroviruses at the internal pro and pol genes (by means of ribosomal frame-shifting and terminations suppression). Therefore the predicted proteins in particular for gag and env genes may contain incorrect N-terminal regions that must be removed by looking for appropriate start codons. ORF lengths below 63 aa were discarded as the probability of finding ORFs less than 63 aa in a random sequence increases to more than 0.05 (assuming equal codon frequencies).
All ORFs were then assigned to a category by FASTA searching against a library of known retroviral proteins (RV) and known non-retroviral proteins (NON_RV). RV proteins were downloaded from NCBI and categorized into either GAG, POL, PRO, ENV, ACC (accessory protein) or UNWANTED (for unwanted or unknown proteins). NON_RV proteins consists of all human SwissProt proteins of length 400–700 aa not including the words "endogenous, virus, envelope, env-, env, gag-, gag, pol-, pol, reverse". The final library consisted of 6260 records (3454 RV proteins + 2806 NON_RV proteins). ORF was assigned to the same category as the highest scoring hit. All loci with a significant RV ORF (vORF) were flagged as HERVs (E < 0.0005) – this data set consists of 7836 loci. Manual inspection of long ORF above 400 codons revealed that two envelope ORFs (ORF ID 86185 and 312172) were (mis)categorized as non-significant (NonS) due to low sequence similarity to our retroviral protein library.
EST matching to individual proviruses
In order to match the human ESTs to the vORF positive HERV regions we first performed an all against all search using NCBI MegaBLAST [62]. The output was filtered so that only the best matching pairs (HERV-EST) were kept and put into a database. The ESTs that matched the HERV regions encompassing a long ORF were subsequently assigned to a human genomic region using EST mapping data from UCSC Genome Browser [63]. ESTs that unambiguously mapped to the same genomic region as the HERV regions of interest were counted as positive EST matches.
List of abbreviations used
ERV Endogenous retrovirus
EST Expressed sequence tag
HERV Human endogenous retrovirus
LTR Long terminal repeat
vORF Viral open reading frame
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
The study was conceived by LAA and FSP; PV and LAA participated in designing and coordinating the study; PV carried out all programming and compilation of , while LAA prepared query sequences, detailed analysis of the results and drafted the manuscript and PV and CW performed the statistical analysis. All authors read and approved the final manuscript.
Supplementary Material
Additional File 1
Table 1. Genes with one or more vORF HERVs inside. Genes were selected from Ensembl (Current Release 21.34d.1) and compared with all HERV regions containing a retroviral ORF. 813 genes (642 with descriptions) contained 1182 HERVs (969) overlapping the gene chromosomal coordinates (exons + introns). The HERV score is a measure of the density of retroviral blast hits in the region.
Click here for file
Additional File 2
Table 2. ESTs matching HERVs containing a long viral ORF. ESTs were compared to HERVs using megaBLAST. Only ESTs that best matched the target HERV were kept. Finally, ESTs mapping conclusively to the same genomic regions as the target HERV were kept. EST library information (organ and tissue) was parsed from Genbank. The positions are in NCBI35 coordinates due to overly stringent settings of EST mappings in the NCBI34 mapping at UCSC. HERV positions were lifted to NCBI35 coordinates using the "lift genome annotations" tool at
Click here for file
Acknowledgements
This work was supported by the Danish Medical and Technical Research Councils, The Karen Elise Jensen Foundation, The Danish Cancer Society and Aarhus University Research Foundation.
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| 15476554 | PMC524368 | CC BY | 2021-01-04 16:36:37 | no | Retrovirology. 2004 Oct 11; 1:32 | utf-8 | Retrovirology | 2,004 | 10.1186/1742-4690-1-32 | oa_comm |
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J Exp Clin Assist ReprodJournal of Experimental & Clinical Assisted Reproduction1743-1050BioMed Central London 1743-1050-1-21550712710.1186/1743-1050-1-2ResearchImpact of seasonal variation, age and smoking status on human semen parameters: The Massachusetts General Hospital experience Chen Zuying 1zchen1@partners.orgGodfrey-Bailey Linda 2lcbailey@hohp.harvard.eduSchiff Isaac 1ischiff@partners.orgHauser Russ 12rhauser@hohp.harvard.edu1 Vincent Memorial Obstetrics & Gynecology Service, Andrology Laboratory and In Vitro Fertilization Unit, Massachusetts General Hospital, Boston, Massachusetts USA2 Department of Environmental Health, Occupational Health Program, Harvard School of Public Health, Boston, Massachusetts USA2004 30 9 2004 1 2 2 23 9 2004 30 9 2004 Copyright © 2004 Chen et al; licensee BioMed Central Ltd.2004Chen 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 investigate the relationship of human semen parameters with season, age and smoking status.
Methods
The present study used data from subjects recruited into an ongoing cross-sectional study on the relationship between environmental agents and semen characteristics. Our population consisted of 306 patients who presented to the Vincent Memorial Andrology Laboratory of Massachusetts General Hospital for semen evaluation. Sperm concentration and motility were measured with computer aided sperm analysis (CASA). Sperm morphology was scored using Tygerberg Kruger strict criteria. Regression analyses were used to investigate the relationships between semen parameters and season, age and smoking status, adjusting for abstinence interval.
Results
Sperm concentration in the spring was significantly higher than in winter, fall and summer (p < 0.05). There was suggestive evidence of higher sperm motility and percent of sperm with normal morphology in the spring than in the other seasons. There were no statistically significant relationships between semen parameters and smoking status, though current smokers tended to have lower sperm concentration. We also did not find a statistically significant relationship between age and semen parameters.
Conclusions
We found seasonal variations in sperm concentration and suggestive evidence of seasonal variation in sperm motility and percent sperm with normal morphology. Although smoking status was not a significant predictor of semen parameters, this may have been due to the small number of current smokers in the study.
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Background
Male factor infertility has been identified as the main or secondary cause in >40% of infertile couples. The number of office visits each year for infertility in the United States has risen from 600,000 in 1968 to 2 million by the 1990's. Semen analysis is a central component in male infertility evaluation [1,2]. The present study was designed to evaluate the relationship of human semen parameters to season, age and smoking status.
Seasonal variations in semen parameters have been reported in both fertile and infertile men [3-6]. Saint Pol et al. found a significant seasonal variation in sperm count, with highest sperm counts in late winter and early spring and lowest concentration in late summer [5]. There are several studies that suggest that an increase in age is associated with a decline in semen parameters [6-8]. Paulson and coworkers identified an inverse association between age and total sperm count, but did not find an age related decrease in fertilization rate or a decrease in live birth rate in the oocyte donation model [9].
There is a consistent association between cigarette smoking and fertility in women [10-13]. However, the data on cigarette smoking and measures of male fertility are less clear. Künzle et al. found an association between smoking and reduced semen quality [14] while others found no strong relationship [15].
The present study explores the relationship of human semen parameters with season, age and smoking status, while controlling for abstinence interval. In an earlier publication, we reported on the relationship between semen parameters, season, and age using data from a retrospective review of an existing laboratory database at the Massachusetts General Hospital Vincent Memorial Andrology Laboratory [16]. The present study uses data from subjects recruited into an ongoing study exploring the relationship between environmental agents and semen parameters. There is no overlap with subjects from our earlier study.
Methods
Study participants
The Human Subject Internal Review Board committees of the Harvard School of Public Health and the Massachusetts General Hospital approved the study (IRB #96-7545). Informed consent was obtained from each participant before entering the study.
The study population consisted of patients (n = 306) presenting to the Vincent Memorial Andrology Laboratory of Massachusetts General Hospital (MGH) between January 2000 and January 2002 for semen analysis as a component of infertility evaluation. Of the 306 subjects, age was not available for five study subjects despite several attempts at follow up after the initial study visit. Sperm morphology was not performed on two subjects with azoospermia.
Men were approached only if the referring physician had previously received a brief description of the study. The Andrologist approached patients and asked if they were willing to meet the research nurse to learn about the research study, noting that it was optional and not part of their clinic appointment. All patients approached had the opportunity to decide for themselves if they wanted to participate in the research study. Inclusion criteria for this study were: 1) scheduled for a routine semen analysis as a patient at the Vincent Memorial Andrology Laboratory, 2) either English or Spanish speaking, 3) age 18–54 years, 4) had not had a vasectomy, and 5) was not currently receiving hormone therapy.
All subjects received an explanation of the study in a private setting prior to obtaining informed consent. Information on lifestyle, such as smoking history and medical history was obtained by nurse interview.
From the date that semen specimen was produced, samples were classified by season as follows: winter = December, January, February; Spring = March, April, May; Summer = June, July, August; and Fall = September, October, November.
Collection of samples
Semen was collected by masturbation in a private room in the hospital. The semen specimen was allowed to liquefy for at least 20 minutes in an incubator at 37°C and was analyzed within 60 minutes after collection. A routine semen analysis was performed which included the following parameters: semen volume, pH, sperm concentration, sperm motility, and sperm morphology.
Laboratory evaluation
Semen volume and pH
Volume was determined and sample color and viscosity were recorded. Semen pH was measured within one hour of ejaculation (Color pHast; EM Science, Gibbstown, NJ, USA).
Concentration and motility
All fresh semen samples were analyzed for sperm concentration and motion parameters by the HTM-IVOS Semen analyzer (Hamilton-Thorn 10HTM-IVOS, Beverly, MA, USA). Setting parameters and the definition of measured sperm motion parameters for CASA were established by the manufacturer: (frames acquired: 30; frame rate: 60 Hz; straightness (STR) threshold: 80.0%; medium VAP cutoff: 25.0 um/s; and duration of tracking time: 0.38 sec). To measure both sperm concentration and motility, aliquots of semen samples (5 μl) were placed into a pre-warmed (37°C) Makler counting chamber (Sefi – Medical Instruments, Haifa, Israel). A minimum of 200 sperm from at least four different fields was analyzed from each specimen. Percent motile sperm was defined as World Health Organization (WHO) grade "a" sperm (rapidly progressive with velocity ≥ 25 μm/s at 37°C) plus "b" grade sperm (slow/sluggish progressive with velocity ≥ 5 μm/s but < 25 μm/s) [17].
Morphology
Using the "feathering" method at least two slides were derived from each fresh semen sample [17]. The resulting thin-smear slide was allowed to air dry before staining which was carried out using a Diff-Quik staining kit, consisting of three solutions (Dade Behring AG, Düdingen, Switzerland). Slides were then mounted with a microscopy cover glass (Fisher Scientific, Pittsburgh, PA, USA).
Morphological assessment was performed at a magnification of 100X with an oil immersion using a Nikon microscope (Nikon Company, Tokyo, Japan). As the slide was scored, the normal and abnormal spermatozoa (head defects, midpiece defects and tail defects) were noted. Sperm morphology was determined using the strict criteria by Kruger et al. [18]. From each sample at least 200 spermatozoa was counted from two slides. Results were expressed as percentage of normal spermatozoa, head defects, midpiece defects and tail defects.
Statistical analysis
Multiple regression analyses (SAS version 8.2, SAS Institute, Cary, NC, USA) was performed to investigate whether there were differences in semen parameters with respect to season, age, and smoking status. Winter was used as the reference season. We also investigated month-to-month variation in semen parameters. For each semen parameter, a separate multiple regression was performed. Semen analysis parameters were entered into the models both untransformed and after square root transformation because of their skewed distribution. Since the square root transformed results were similar to the untransformed results, and are simpler to interpret, only the untransformed results are presented. To explore whether the semen parameters and age relationships were linear, age was used as both a continuous and categorical variable (less than 30 years, 30 to 40 years, and greater than 40 years old). Abstinence time was modeled as an ordinal five-category variable (2 or fewer days, 3, 4, 5, and 6 or more days).
Results
Subject's ages ranged from 18.2 to 54.3 years. The mean (± SD) age was 35.9 (± 5.6) years. The majority of the subjects (67%) were between 30 and 40 years old; only 11% were <30 years and 21% were >40 years old.
Mean sperm concentration was above the WHO reference values [17]. Average (± SD) sperm concentration was 103 (± 95.5) M/ml with range = 0 – 655.4 M/ml. Mean (± SD) percent motility and percent normal morphology were 47.6% (± 25.5) and 6.9% (± 4.7), respectively. Mean (± SD) semen volume was 3.0 ml (± 1.6), with a range = 0.1 – 11.0. The mean (± SD) semen pH was 8.4 (± 0.3), with range = 6.8 – 9.0. Mean (± SD) abstinence interval was 1.7 (± 1.4) days. Distributions of semen parameters for the study population are presented in Table 1.
Table 1 Distributon of semen parameters for study subjects referred for infertility evaluation at Massachusetts General Hospital (n = 306).
parameter mean ± SD range
age (yrs)a 35.9 5.6 18.2–54.3
volume (ml) 3.0 1.6 0.1–11.0
pH 8.4 0.3 6.8–9.0
concentration (M/ml) 103 95.5 0–655.4
motility (%) 47.6 25.5 0–89.0
morphology (%)b,c 6.9 4.7 0–24.0
Note: aage was not recorded for 5 patients bby Tygerberg-Kruger strict morphology cmorphology was not recorded for 2 patients
Seasonal variations in semen quality are shown in Table 2. The number of semen samples obtained in the Spring, Summer, Fall, and Winter were 62, 81, 82, 81, respectively. Mean sperm concentration in the spring (137.2 million/ml) was significantly higher than in the winter (99.2 million/ml), summer (93.1 million /ml) and fall (90.6 million/ ml), (p-value < 0.05). These seasonal differences remained after adjusting for age and abstinence times. Figure 1 shows the month-to-month median sperm concentration across the study. Median sperm concentration by month was higher in March, April, May and June than all other months (Figure 1). Mean sperm motility also was higher in the spring (52.3%) than in the summer (47.7%), fall (47.1%) and winter (44.3%). This was higher when compared to winter (p = 0.06).
Table 2 Seasonal variation in semen parameters observed among study patients referred for infertility evaluation at Massachusetts General Hospital (n = 306).
Spring Summer Fall Winter
Parameter mean ± SD mean ± SD mean ± SD mean ± SD
volume (ml) 3.0 1.5 2.9 1.6 2.9 1.5 3.1 1.9
PH 8.4 0.2 8.4 0.2 8.4 0.3 8.4 0.3
concentration (M/ml) 137.2a 122.1 93.1 80.1 90.6 81.5 99.2 95.3
motility (%) 52.3b 22.4 47.7 26.9 47.1 25.1 44.3 26.3
morphology (%)c 7.5 4.9 6.7 4.2 7.0 5.1 6.4 4.8
Note: Spring = March/April/May (n = 62); Summer = June/July/August (n = 81); Fall = Sept/Oct/Nov (n = 82), and Winter = Dec/Jan/Feb (n = 81). a p < 0.05 vs. Summer, Fall, and Winter by multiple regression analysis method bp = 0.06 vs. Winter cby Tygerberg-Kruger strict morphology
Figure 1 Median sperm concentration by month.
There were also seasonal variations in sperm morphology parameters. The mean percent normal morphology in Spring (7.5%) was greater than in Summer (6.7%), Fall (7.0%) or Winter (6.4%), though not statistically significant. These seasonal differences remained after adjusting for age and abstinence interval. Mean semen volume and pH were similar across season.
There were no statistically significant relationships between age with semen volume, sperm concentration, percent motility, and percent normal morphology. However, there was little variability in age since the majority of men (> 65%) were between 30 and 40 years old.
In the present study, only 22 men were current smokers and 57 were ex-smokers. After controlling for age and abstinence time, there was no statistically significant relationship between semen quality and smoking status, though current smokers tended to have lower mean sperm concentration (83 million/ml) than never smokers (104 million/ml).
Discussion
Although there are numerous previously published studies investigating the relationship among semen parameters and season, age and smoking status, the data are not entirely consistent. To determine if these associations are robust, replication is required. It is the accumulation of consistent observations from epidemiological studies that provides confidence in the findings. Therefore, we believe the present study adds to the literature since it provides replication of seasonal trends in semen parameters. In addition, the present study was conducted in men residing in the Northeast region of the United States, an area with distinct seasons and one that has not been well represented in the literature on this topic. Our study has several strengths. The center selected as the site of this study (the Vincent Memorial Andrology Laboratory of Massachusetts General Hospital) has a large and readily accessible population of men seeking infertility evaluation. Based in a large tertiary care facility, the Andrology Laboratory draws patients from diverse backgrounds throughout the New England region of the United States, receiving referrals from physicians in the community and the medical center.
Our study also had potential limitations. Since it is known that there is within-person variability in semen parameters, using a single sample to characterize an individual may introduce measurement error, likely to be random. Another potential limitation is that it is possible that if some men recently moved to the New England area this may introduce bias. However, of the men in the study, 96% of them lived in New England area for at least 3 months prior to their semen analysis, the period of sperm development. Therefore, the concern with recent immigration to the New England area would be minimal.
In the present study, we found higher sperm concentrations, motility and percent normal morphology in the spring than in other seasons. This may partially explain seasonal patterns of births in United States, where there is a deficit of spring births [19], conceived in the summer.
Our data are in agreement with previous reports of seasonal variation in sperm concentration with spring having the highest concentration. Gyllenborg et al. [20] found high sperm counts in the spring as compared to the summer. Two other retrospective studies found peak sperm concentrations in the spring and winter [4,21]. In our earlier publication, a retrospective review of semen analysis results from a different cohort of men, we found higher median sperm concentrations in the winter (111.6 million/mL) as compared to the fall (87.7 million/mL), with a median spring concentration of 90.0 million/mL [16]. In our earlier study we were unable to control for abstinence interval, thus if winter abstinence times were longer than spring this may partially account for the differences between studies.
Seasonal variations in sperm morphology were recently explored by Centola and Eberly in a large sample of California men [6]. Although they did not find statistical significant seasonal variations in percent normal morphology, there were significant seasonal differences in percent tail defects, percent tapered forms, and percent immature sperm. In our earlier study we found higher median percentage of sperm with normal morphology in the winter (9.0%) as compared to spring (6.5%) [16]. It is unclear why these results differed from the present study results. The literature on seasonal variations in sperm motility is largely inconsistent [5,6,22,23].
Effects of temperature and hours of daylight may partially explain seasonal variations in semen quality. Sperm production in humans is known to decrease when testicular temperature is raised by experimental techniques [24]. Normal spermatogenesis requires a temperature 2–3°C below rectal temperature [25]. We think temperature and photoperiod may play a role in seasonal variations in semen quality. To explore this further, we are presently conducting a study collecting information on lifestyle factors, such as alcohol and drug use, environmental and occupational exposures, and personal factors such as stress. The information will allow us to further explore risk factors for altered semen quality.
Spermatogenesis occurs over approximately three months and does not seem to vary in duration among men [25]. Chia et al. reported there were no significant month-to-month fluctuations in semen volume and sperm density among men who resided in the tropics [26], where there are minimal changes in temperature, unlike the seasonal variation of climate in the New England region. In our study, improved semen parameters in the spring may reflect spermatogenesis during the cold New England winter.
While we did not find a relationship between age and semen parameters, there was little variability in age in our study population. In our earlier study we found inverse associations between age and sperm concentration, motility and morphology [16]. However, the age range was larger in this earlier study. In another study, Schwartz and coworkers found an improvement in semen characteristics up to 25 years of age [27], followed by a leveling off and a subsequent decrease. However, the age relationships were not statistically significant for sperm count, semen volume, and the total number of spermatozoa. Statistically significant decreases in sperm concentration with advanced age were found among 29 'older' fathers (mean age 50.3 years) compared with those from 35 'younger' fathers (mean age 32.2 years) [7]. A recent review of the literature by Kidd et al. suggested that increased age was associated with a decline in semen volume, sperm motility, and sperm morphology but not with sperm concentration [8].
Studies have shown associations between cigarette smoking and infertility in women, time to conception, and risk of spontaneous abortion, as well as reduction in fecundity [11,12]. Data on associations between cigarette smoking and male fertility are unclear [11,15,28,29]. Hughes and Brennan [11] reported that there were no consistent effects on semen quality among male smokers. Similarly, a survey of more than 4,000 European couples attempting to become pregnant failed to find an effect of male smoking on fecundity [15].
However, in contrast, in a cross-sectional study of men with proven fertility (n = 243), cigarette smoking was associated with significantly lower semen volume (but not other semen parameters) after adjusting for age and alcohol consumption [29]. Results from a meta-analysis (including >1000 men) indicated that smokers' sperm density is on average 13–17% lower than that of nonsmokers [28]. The available data suggest that cigarette smoking was associated with a significant decrease in sperm density, total sperm count, total motile sperm, and the percentage of normal forms [14].
In our study, only 22 men were current smokers and 57 were ex-smokers. After controlling for age and abstinence time, there was no significant relationship between semen quality and smoking status, though current smokers tended to have lower sperm concentration. The present study is ongoing and we will reexamine these relationships in a larger dataset. In addition, we are also collecting information on other lifestyle and personal factors, such as physical exercise, stress, and alcohol intake. Their relationship with semen parameters will be investigated in the future when we have a larger number of subjects.
Conclusions
We found seasonal variations in sperm concentration and suggestive evidence of seasonal variation in sperm motility and percent sperm with normal morphology. Although smoking status was not a significant predictor of semen parameters, this may have been due to the small number of current smokers in the study.
Competeting interests
The authors declare that they have no competing interests.
Authors' contributions
ZC, LG-B, IS, and RH all contributed equally to this work and reviewed the manuscript.
Acknowledgements
This study was funded by support from the National Institute of Environmental Health Sciences (grant # ES09718 and ES00002).
The authors thank Lucille Pothier, Computer Programmer at the Harvard School of Public Health, for assistance with data analysis. We also thank Ana Trisini, (Research Assistant at Harvard School of Public Health, Department of Environmental Health) for assistance with manuscript editing and Nelta Mercedat Lozius (Clinical Laboratory Assistant at Massachusetts General Hospital, Obstetrics & Gynecology Services) for assistance with analysis the samples.
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| 15507127 | PMC524369 | CC BY | 2021-01-04 16:39:57 | no | J Exp Clin Assist Reprod. 2004 Sep 30; 1:2 | utf-8 | J Exp Clin Assist Reprod | 2,004 | 10.1186/1743-1050-1-2 | oa_comm |
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Epidemiol Perspect InnovEpidemiologic perspectives & innovations : EP+I1742-5573BioMed Central London 1742-5573-1-31550712810.1186/1742-5573-1-3Analytic PerspectiveThe missed lessons of Sir Austin Bradford Hill Phillips Carl V 123carl.v.phillips@cphps.orgGoodman Karen J 1kgoodman@sph.uth.tmc.edu1 Management, Policy and Community Health Division, University of Texas School of Public Health, 1200 Pressler, Houston, TX 77225, USA2 Center for Clinical Research and Evidence-Based Medicine, University of Texas Medical School, Houston, TX USA3 Center for Philosophy, Health, and Policy Sciences, Inc, Houston, USA2004 4 10 2004 1 3 3 18 8 2004 4 10 2004 Copyright © 2004 Phillips and Goodman; licensee BioMed Central Ltd.2004Phillips and Goodman; 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.
Austin Bradford Hill's landmark 1965 paper contains several important lessons for the current conduct of epidemiology. Unfortunately, it is almost exclusively cited as the source of the "Bradford-Hill criteria" for inferring causation when association is observed, despite Hill's explicit statement that cause-effect decisions cannot be based on a set of rules. Overlooked are Hill's important lessons about how to make decisions based on epidemiologic evidence. He advised epidemiologists to avoid over-emphasizing statistical significance testing, given the observation that systematic error is often greater than random error. His compelling and intuitive examples point out the need to consider costs and benefits when making decisions about health-promoting interventions. These lessons, which offer ways to dramatically increase the contribution of health science to decision making, are as needed today as they were when Hill presented them.
epidemiologic methodshealth policycausal inference
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Introduction
One of the most cited papers in health research is Austin Bradford Hill's "The Environment and Disease: Association or Causation?" [1], Hill's 1965 Presidential Address to the Section of Occupational Medicine of the Royal Society of Medicine, where he presented what are now commonly called the "Bradford-Hill criteria." This paper ironically gains its fame for providing a checklist for inferring causation, something Hill did not claim to be creating. Meanwhile, largely ignored are its great insights and potential contributions to critical methodological and policy issues.
Hill outlined a systematic approach for using scientific judgment to infer causation from statistical associations observed in epidemiologic data, listing nine issues to be considered when judging whether an observed association is a causal relationship. Despite widely distributed and clearly elaborated advice to the contrary [2], Hill's nine considerations are still frequently taught to students of epidemiology and referred to in the literature as "causal criteria." Typically presented as a checklist approach to assessing causation (though without a method for deciding whether to assign a particular checkmark, let alone how to make a final assessment), Hill's list is commonly taught in epidemiology courses and is probably invoked more often than any other method for assessing causation. At a time when the discussion of the nature of causation and methods for identifying causal effects are reaching new levels of sophistication in epidemiology [3-5], this is particularly unfortunate.
Hill never used the term "criteria" and he explicitly stated that he did not believe any hard-and-fast rules of evidence could be laid down, emphasizing that his nine "viewpoints" [1](p. 299) were neither necessary nor sufficient for causation. His suggestions about how to intuitively assess causation are almost completely lost when his address is distilled into a checklist (See endnote 1).
Causal criteria are an intriguing subject for the history of science, including the question of why Hill's list seems more popular than others [7-10] and whether causal conclusions that explicitly appealed to criteria are more likely to be borne out by subsequent evidence. (To our knowledge, there has been no such validation study of causal criteria.) But it is not the main purpose of this analysis to join the extensive discussion of the history and merits of causal criteria. We will say only that Hill's list seems to have been a useful contribution to a young science that surely needed systematic thinking, but it long since should have been relegated to part of the historical foundation, as an early rough cut. Yet it is still being recited by many as something like natural law. Appealing in our teaching and epistemology to the untested "criteria" of a great luminary from the past is reminiscent of the "scientific" methods of the Dark Ages. Hill's own caveats suggest a similar opinion (though such a claim requires some caution, given that Hill repeated his list in his medical statistics textbooks until the time of his death, adding neither an evolution in his perspective nor arguments to support the validity or usefulness of the list [11-14]).
This brief analysis of Hill's "criteria" and what has been made of them can add little new to that topic (though we will argue that Hill deserves more credit than he is usually given by critics of "criteria" for the nuances and examples he presented). Our purpose is to call attention to the seldom-cited last page and a half of the article, which presents lessons that remain overlooked today.
Analysis
Hill eloquently warned about overemphasis on statistical significance testing, writing "the glitter of the t table diverts attention from the inadequacies of the fare" [1](p. 299). The mistake of drawing conclusions from inadequate samples had been replaced with the mistake of treating statistical significance as necessary and sufficient for action. An intellectual generation passed after 1965 with almost no improvement [15], and little has changed in another generation after that. Researchers still frequently present results as if statistical significance and p-values are useful decision criteria, and decision makers are left with inadequate information.
One implication of Hill's advice is well understood. Emphasis on the p-value (let alone dichotomous statements of significance) has been soundly denounced for decades [16,17]. Estimation of effect sizes, presented as point estimates with confidence intervals, is the preferred method in current textbooks [18] and these are generally reported, though in practice confidence intervals tend to be interpreted as mere tests of statistical significance by ignoring their range except to note whether or not they include the null value (see endnote 2).
A further inadequacy of the fare is less well appreciated, stemming not from the question of p-values versus confidence intervals, but from systematic errors. No statistical test of random sampling error informs us about the possible impacts of measurement error, confounding, and selection bias. Methods for quantifying such errors (and perhaps more importantly, arguments for why we need to do so) have been developed in epidemiology, particularly over the last five years [19-25]. Hill hinted at this more than three decades before the recent spate of attention when he noted that one of his own studies [26], like many studies, had great potential for selection bias (though he does not use this term). In effect, he asks "why would I bother to do an exaggeratedly precise statistical test when I know that the other sources of error are likely so large?" Rather than emphasize low p-values, he concluded that simple cell counts made both random error and plausible systematic error unlikely to account for the observed association. While his solution was inadequate – indeed, it might even be called hubris (see endnote 3) – he did issue a clear warning about mistaking statistical precision for validity. Despite the influence of Hill's article, the fact that it contained this point is forgotten (and the point, while obviously true, remains widely ignored).
Even as modern epidemiologic analysts become less dazzled by the t-table, replacing significance testing with confidence intervals and introducing quantification of systematic errors, there is still a tendency to completely overlook Hill's other important insight. Hill sought to address the question how to decide whether to take action once causal inferences are made. In his last few paragraphs, he offers an important commentary on the policy recommendations that flow from decisions regarding cause and effect in epidemiology. Since "our object is usually to take action" [1](p. 300), policy considerations are central to the importance of the science. While epidemiology has its roots in specific policy questions ("can we do something to prevent cholera outbreaks?"), epidemiologists have ambivalent attitudes towards the policy decisions associated with their research [31]. In grant applications and introductions to research reports, it is typical for epidemiologists to justify expensive research based on immediate practical benefits. But in presenting the results, they often deny, implicitly or explicitly, the need to assess the policy contributions [32], defending the value of science for its own sake (sometimes even as they issue press releases calling for policy responses).
Even when policy implications are presented explicitly, they are seldom carefully analyzed. Analyzing the implications of a health research finding for decision making is often not terribly difficult, but making recommendations without such analysis can lead to absurd suggestions [33]. One epidemiology journal famously goes so far as to instruct authors to avoid the common practice of tacking on policy recommendations at the end of research reports. The argument is that policy analysis is too complicated and too serious to be an afterthought by researchers whose expertise lies elsewhere [34,35]. Judging from Hill's comments, he might have preferred more careful policy analysis be included in epidemiologic research reports, rather than none at all, though it is not clear he could solve the challenge of fitting it into the standard 3000-word, single-result health research paper. The present journal offers a solution by publishing policy analyses that are based on health research results, and allowing the articles to be whatever length they need be [36].
Hill, who was educated in economics, argued that in order to take policy action, we ought to pay attention to the absolute costs and benefits of potential actions. It would clearly be reading too much into the text to suggest that he had a prescient vision of modern probability-weighted cost and benefit based policy analyses and decision theory (those fields were in their early stages at the time of his writing and he never used any of those terms). But, in another memorable phrase, he did make the case for having "differential standards before we convict" [1](p. 300), based on costs and benefits. Moving another step beyond statistical significance testing, we need to consider more than the degree of certainty that there is some health hazard, and act based on the expected gains and losses, with or without statistical certainty.
Hill points this out (in an example sufficiently ill-chosen that it may have contributed to his important message being ignored): "On relatively slight evidence we might decide to restrict the use of a drug for early-morning sickness in pregnant women. If we are wrong in deducing causation from association no great harm will be done. The good lady and the pharmaceutical industry will doubtless survive [1](p. 300)."
Setting aside the impolitic dismissal of women's preferences and the unsupported assertion that there is no great harm at stake (as well as the irony of the popularity, withdrawl, and rehabilitation of the morning sickness drug, Bendectin) the underlying point might be his most important lesson: Policy actions that appear to create a net benefit (on average, considering all costs and benefits) should be taken, even without statistical "proof" of an association, while actions that entail great costs should only be taken with sufficient certainty of substantial benefit.
Hill goes on to strengthen his argument: "On fair evidence we might take action on what appears to be an occupational hazard, e.g. we might change from a probably carcinogenic oil to a noncarcinogenic oil in a limited environment and without too much injustice if we are wrong. But we should need very strong evidence before we made people burn a fuel in their homes that they do not like or stop smoking the cigarettes and eating the fats and sugar that they do like [1](p.300)."
Hill clearly stated that the science and data analysis should not be influenced by what is at stake. But health researchers should recognize that the stakes matter, and incorporate a consideration of them into their work. The alternative to carrying out the policy analysis is to leave the weighing of costs and benefits to an unreliable post-science political process.
The observation that the costs and benefits matter, despite being rather obvious, is frequently – indeed, typically – overlooked in public health discussions. The popular decongestant phenylpropanolamine was banned on weak evidence without regard to the high cost to consumers [37]; dietary recommendations are made without considering absolute benefits, let alone the cost to people of avoiding their favorite foods; and health and safety regulations are tremendously uneven in their cost effectiveness, to cite just three examples. The "policy recommendations" paragraph found in many health research papers sometimes quantifies medical costs, but typically ignores lifestyle, psychological, or productivity costs. It is even rare to find quantification of the absolute aggregate benefit that would result from a policy or behavioral change.
Making a good decision does not depend on having studies with confidence intervals that exclude the null. A best decision can be based on whatever information we have now, and indeed a decision will be made – after all, the decision to maintain the status quo is still a decision [20,38]. Hill offered his clearest condemnation of over-emphasizing statistical significance testing, not when he discussed p-values, but when he concluded by saying: "All scientific work is incomplete – whether it be observational or experimental. All scientific work is liable to be upset or modified by advancing knowledge. That does not confer upon us a freedom to ignore the knowledge we already have, or to postpone the action that it appears to demand at a given time [1](p. 300)."
The pursuit of the low p-value (or confidence interval that excludes the null) leaves our society postponing apparently useful policy choices while we do more research to try to show what we already believe to be true. It also creates the incentive to use dubious methods (e.g., unstated multiple hypothesis testing, choosing models or transforming data to maximize the effect size [39]) in order to squeeze out significant results. Those same methods can be used by those who would prefer to make real causal relationships disappear below the p = .05 horizon. Making the best of the knowledge we have would reduce such temptations. If epidemiologists help empower policy makers to ban an easily-replaced chemical when we believe there is, say, a 50-50 chance that it is a health hazard (based on an honest assessment of all uncertainty), then the payoff for fiddling with the data to show the certainty is a bit higher or a bit lower would be eliminated.
This would release us from the trap of letting ignorance trump knowledge. Regulators often fail to act because we have not yet statistically "proven" an association between an exposure and a disease, even when there is enough evidence to strongly suspect a causal relationship. There is a growing movement to escape this mistake by making a similar mistake in the other direction: adopting precautionary principles, which typically call for restrictions until we have "proven" lack of causal association – a decision based on ignorance that merely reverses the default. If we can escape from the false dichotomy of "proven vs. not proven," facilitated by the nonexistant bright line implied by statistical hypothesis testing and by the notion that causality can be definitively inferred from a list of criteria, then we can make decisions based on what we do know rather than what we don't.
Conclusions
The uncritical repetition of Hill's "causal criteria" is probably counterproductive in promoting sophisticated understanding of causal inference. But a different list of considerations that can be found in his address is worthy of repeating:
• Statistical significance should not be mistaken for evidence of a substantial association.
• Association does not prove causation (other evidence must be considered).
• Precision should not be mistaken for validity (non-random errors exist).
• Evidence (or belief) that there is a causal relationship is not sufficient to suggest action should be taken.
• Uncertainty about whether there is a causal relationship (or even an association) is not sufficient to suggest action should not be taken.
These points may seem obvious when stated so bluntly, but causal inference and health policy decision making would benefit tremendously if they were considered more carefully and more often. The last point may be the most important unlearned lesson in health decision making.
In fairness to those who do not appreciate these points even today, it overinterprets Hill's short paper to claim that he clearly laid out these considerations, or that he was calling for modern decision analysis and uncertainty quantification. But the fundamental concepts were clearly there (and the overinterpretation is not as great as that required to derive a checklist of criteria for determining causation). Several generations of advancement in epidemiology and policy analysis provide much deeper exposition of his points. But Hill still offers timeless insightful analysis about how to interpret our observations. Strangely, these forgotten lessons, which are only slowly and grudgingly being appreciated in modern epidemiology, are hidden in plain sight, in what is possibly the best known paper in the field.
Endnotes
1. Interestingly, there are more extreme cases of a scholar's name being immortalized for something contrary to his beliefs. The "Coase Theorem" in economics, from one of the most cited article in the economics and legal literatures [6] (often identified as the most cited article in one of those fields or in their intersection), is usually invoked to make worldly claims that certain beneficial transactions will occur (which, among other things, reduce the need for regulation). But much of Coase's work (including that paper) focuses on how the circumstances required for those transactions to take place are absent in the real world.
2. Reporting confidence intervals provides more information about the estimated association of an exposure and outcome. For example, a large measured effect with a wide confidence interval and a small measured effect with a narrow confidence interval may have the same p-value, but the confidence intervals suggests that a large association is likely in the former case, but not the latter. This has implications for both scientific conclusions and decision making. However, the reporting of confidence intervals addresses only this limitation, not others described subsequently.
3. In effect, Hill claimed that the association was so strong that neither the random nor the systematic error could explain it. In doing so, he failed to heed his own observation that systematic errors might explain an association no matter how low the p-value, and invoked the strength of the statistical association to rule out the possibility it was caused by systematic error. More important, Hill made the mistake of overestimating his ability to intuitively assess complicated quantitative relationships. In Hill's defense, his remark predated the research, primarily from the 1970s and 1980s, that demonstrated that both lay people and experts have poor quantitative intuition (most of the key papers from that literature can be found in a few collected volumes [27-30]). Current researchers who argue that their intuition obviates the need for modern methods for quantifying uncertainty have no such excuse.
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| 15507128 | PMC524370 | CC BY | 2021-01-04 16:36:33 | no | Epidemiol Perspect Innov. 2004 Oct 4; 1:3 | utf-8 | Epidemiol Perspect Innov | 2,004 | 10.1186/1742-5573-1-3 | oa_comm |
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BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-5-1371545391910.1186/1471-2105-5-137Research ArticleFew amino acid positions in rpoB are associated with most of the rifampin resistance in Mycobacterium tuberculosis Cummings Michael P 1mike@umiacs.umd.eduSegal Mark R 2mark@biostat.ucsf.edu1 Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742-3360, USA2 Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94143-0560, USA2004 28 9 2004 5 137 137 15 4 2004 28 9 2004 Copyright © 2004 Cummings and Segal; 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
Mutations in rpoB, the gene encoding the β subunit of DNA-dependent RNA polymerase, are associated with rifampin resistance in Mycobacterium tuberculosis. Several studies have been conducted where minimum inhibitory concentration (MIC, which is defined as the minimum concentration of the antibiotic in a given culture medium below which bacterial growth is not inhibited) of rifampin has been measured and partial DNA sequences have been determined for rpoB in different isolates of M. tuberculosis. However, no model has been constructed to predict rifampin resistance based on sequence information alone. Such a model might provide the basis for quantifying rifampin resistance status based exclusively on DNA sequence data and thus eliminate the requirements for time consuming culturing and antibiotic testing of clinical isolates.
Results
Sequence data for amino acid positions 511–533 of rpoB and associated MIC of rifampin for different isolates of M. tuberculosis were taken from studies examining rifampin resistance in clinical samples from New York City and throughout Japan. We used tree-based statistical methods and random forests to generate models of the relationships between rpoB amino acid sequence and rifampin resistance. The proportion of variance explained by a relatively simple tree-based cross-validated regression model involving two amino acid positions (526 and 531) is 0.679. The first partition in the data, based on position 531, results in groups that differ one hundredfold in mean MIC (1.596 μg/ml and 159.676 μg/ml). The subsequent partition based on position 526, the most variable in this region, results in a > 354-fold difference in MIC. When considered as a classification problem (susceptible or resistant), a cross-validated tree-based model correctly classified most (0.884) of the observations and was very similar to the regression model. Random forest analysis of the MIC data as a continuous variable, a regression problem, produced a model that explained 0.861 of the variance. The random forest analysis of the MIC data as discrete classes produced a model that correctly classified 0.942 of the observations with sensitivity of 0.958 and specificity of 0.885.
Conclusions
Highly accurate regression and classification models of rifampin resistance can be made based on this short sequence region. Models may be better with improved (and consistent) measurements of MIC and more sequence data.
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Background
Rifampin, one of the principal drugs used in tuberculosis treatment, is a semi-synthetic antibiotic that inhibits transcription by preventing RNA synthesis. Isolates of Mycobacterium tuberculosis resistant to rifampin occur at low to moderate frequencies in many regions of the world [1]. Mutations in rpoB, the gene encoding the β subunit of DNA-dependent RNA polymerase, are associated with rifampin resistance. In the laboratory, drug resistance is quantified in terms of minimum inhibitory concentration (MIC), which is defined as the minimum concentration of the antibiotic in a given culture medium below which bacterial growth is not inhibited.
Several studies have been conducted where MIC of rifampin has been measured and partial DNA sequences have been determined for rpoB in different isolates of M. tuberculosis [2-6]. However, no model has been constructed to predict rifampin resistance based on sequence information alone. Such a model might provide the basis for quantifying rifampin resistance status based exclusively on DNA sequence data and thus eliminate the requirements for time consuming culturing and antibiotic testing of clinical isolates. Tree-based statistical methods (see Methods) have generated very accurate models relating amino acid sequence of short (8-mer) peptides to their binding by major histocompatibility complex (MHC) class I molecules with higher accuracy than artificial neural networks [7]. Both tree-based models and aggregation of such models through random forests (see Methods) have proven to be quite successful in other problems involving sequence data as covariates such as HIV-1 replication capacity [8] and cytidine to uridine RNA editing in plant mitochondria [9]. The success of tree-based statistical models and random forests in these problems involving covariates derived from sequence data motivated our application of these models to the problem of rifampin resistance in M. tuberculosis.
The response variable is a set of continuously distributed values for MIC, which makes the problem one of regression. These data are used to answer the following questions: What proportion of the variance in MIC is attributable to sequence differences in positions 511–533 of the β subunit of RNA polymerase of M. tuberculosis? What particular positions, and what distribution of amino acids at those positions, are associated with most of the variance in MIC? Alternatively, the response variable could be cast in discrete terms: resistant or susceptible. This is possible by assuming a threshold value for MIC above which an isolate is considered resistant to rifampin. Among the specific questions we can answer with such a model are the following: What particular positions, and what distribution of amino acids at those positions, allow for distinguishing rifampin-susceptible and rifampin-resistant isolates of M. tuberculosis? What is the misclassification error rate associated with susceptibility prediction for these data? We address these questions and evaluate the ability to predict MIC from protein sequence data (inferred from DNA sequence data) using tree-based regression and classification methods. We find that these methods generate highly accurate models of rifampin resistance.
Results
The data set used in the study consists of 173 observations with 60 distinct genotype-phenotype combinations (Table 1). The most frequent combination has 47 occurrences, and there are 40 unique (singleton) combinations. MIC for rifampin varies from 0.0625 μg/ml to > 512 μg/ml. The 173 sequences are distributed among 24 genotypes, 11 of which occur uniquely in the data set. The plurality genotype is represented by 69 samples; 98 samples differ from the plurality by one amino acid; and the remaining 6 samples differ from the plurality by two amino acids. Some genotypes defined by the partial sequence of rpoB are associated with several different phenotypes (MIC values). Also, some genotypic states are associated with large effects, while some have little or no effect on MIC phenotype. Finally, some changes in MIC are not associated with changes in the sequence region examined. These genotype data are short (69 bp) partial sequences of a single gene, and thus they may not contain all phenotypically relevant genetic information. Indeed, there is evidence that amino acid changes outside of the examined region are associated with changes in MIC for rifampin [3]. Additionally, the sample size is small (also typical of most genotype-phenotype datasets), which will decrease power. Nonetheless these data are typical of studies surveying the genetic variation associated with antibiotic resistance and of genotype-phenotype data in general. Thus they make an appropriate subject of investigation.
Regression tree analysis
The regression tree for the relationship of rpoB amino acid sequence and MIC has two splits defining three terminal nodes (Fig. 1). At each node in the tree, the MIC prediction given (μg/ml) is the mean of all isolates at that node. The first split of the topmost node (root node) consists of the entire sample and is based on the amino acid at position 531, with those sequences having serine (S) going to the left child node, and those having leucine (L) or tryptophan (W) going to the right child node. The best split for each node is that which gives the largest decrease in the error. Here error is measured as the deviance, which for a continuous variable is a constant multiple of the residual sums-of-squares. Reported values were determined using 10-fold cross-validation. Moving down the tree the error decreases, as the sum of the deviance for each pair of child nodes is less than the deviance of the parent node. Given the hierarchical nature of trees and the criterion used to choose splits, the first split, that based on position 531, explains the highest proportion of the overall phenotypic variance. This bisection of the data results in groups that differ one hundredfold in mean MIC (1.596 μg/ml and 159.676 μg/ml). The subsequent partition based on position 526, the most variable in this region, results in a > 354-fold difference in MIC. The proportion of the variance in MIC explained across all splits involving the two amino acid positions (526 and 531) is 0.679. All proportions of variances explained by the model as reported here are those estimated through cross-validation and are not based on re-substitution, and thus represent appropriately conservative estimates.
Classification tree analysis
From a clinical perspective it may be most relevant to consider the level of drug resistance as a two-state categorical variable (susceptible or resistant) rather than as a continuously distributed variable. In clinical practice, if an isolate of M. tuberculosis is determined to be rifampin resistant then rifampin is replaced with another antibiotic. Although blood serum concentration of rifampin reaches levels of 6 – 7 μg/ml about 1.5 – 2 hours after ingestion [10], a clinically relevant MIC value for dichotomizing the MIC values would be lower than this peak. We conservatively define MIC values ≤ 1 μg/ml as susceptible and values > 1 μg/ml as resistant, a definition consistent with conventional standards [11]. With this dichotomization we can explore the use of tree-based statistical classification to predict rifampin resistance in a way that is more relevant to clinical practice.
The predictor variables are again the unordered categorical designations of amino acids at polymorphic positions. The classification tree for these data (Fig. 2) has two splits based on two of the 11 variable amino acid positions. At each node in the tree, the prediction of rifampin susceptibility status (susceptible or resistant) is given for all isolates at that node. The first split is based on position 531; those isolates with serine (S) are predicted to be susceptible, and those with leucine (L) or tryptophan (W) are predicted to be resistant. The class counts for the full data set are given at each node. For example, the root node (top most node in the figure) contains all 173 cases of which 103 are resistant are resistant to rifampin, and the remaining 70 isolates are susceptible to rifampin. The proportion of correctly classified observations across all splits as determined by re-substitution of the observations on the cross-validation pruned subtree is 0.884. Comparing this tree to the pruned regression subtree (Fig. 1) reveals that the two split definitions in each tree are identical. Both the regression and classification tree models are significant (P < 0.0001) based on permutation tests.
Random forest analyses
The random forest analysis, which aggregates results over many tree models, each constructed on subsamples of the data, produced markedly better models as compared to the single tree-based models. The random forest analysis of the MIC data as a continuous variable, a regression problem, produced a model that explained 0.861 of the variance. The random forest analysis of the MIC data as discrete classes (susceptible and resistant), a classification problem, produced a model that correctly classified 0.942 of the observations with corresponding sensitivity of 0.958 and specificity of 0.885.
Although both the regression and classification random forest results are markedly better than the single tree-based models, they do lack the ease of interpretation of a tree model. However, variable importance can be assessed in random forests by measuring the increase in group purity based individual models containing the variable. As might be expected, the results for both regression and classification are similar and identify the same amino acid positions as being most important in determining response to rifampin as did the single tree models: primarily 531 and 526, and much less so for 513 and 516 (Figure 3).
Discussion
Analysis of genotype and phenotype data poses several significant challenges. Data characteristics such as mixture of variable types, high dimensionality, interactions between variables, and preponderance of unordered categorical variables render many candidate analytical methods inappropriate or ineffective. Tree-based statistical models adeptly deal with these all these challenges and do so in a way that produces readily interpretable results.
Through the analyses described above, we have learned several things that were not previously apparent. We have distinguished phenotypically relevant from phenotypically irrelevant changes in genotype by establishing the relative importance of the polymorphic sequence positions, and amino acids at those positions, as they affect susceptibility to rifampin. For example, although they are polymorphic, changes at positions 511, 512, 515, 521 and 529 did not significantly affect MIC for rifampin. The hierarchical importance of changes, and their contextual/conditional relationships, are depicted in the resulting tree diagrams in a readily interpretable manner. Inherent in the tree structure is the fact that earlier splits explain more variation in phenotype then subsequent splits. For example, the first split, at position 531, explains more variation then does the split based on position 526.
The models can be used to predict MIC for rifampin where genotype is known, as well as provide the basis for hypothesis testing involving future empirical work. Furthermore models can be refined to yield improved predictions by incorporating additional data as they become available. Improved models may be possible with additional data: full length sequence of rpoB may include sequence features that are responsible for some variation in MIC values for rifampin, and sequence data from additional strains might lead to even more general models.
As demonstrated above, the relationship of genotype to phenotype can be quantified using tree-based statistical models and aggregations thereof. Our approach has been to use types of models in the analysis of genotype-phenotype relationships because they offer distinct advantages compared to other methods and allow for rigorous and ready interpretation of results. Tree-based and random forest analyses are readily applicable to other forms of genotypic information including data that take the general form of visualized fragments (bands on gels) such as microsatellites, restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs), and similar data. Tree-based and random forest analyses can also be applied directly to DNA sequence data including single nucleotide polymorphisms (SNPs). In general, tree-based statistical and random forest models are applicable to all cases where the goal is to examine the relationship between genotype and phenotype.
Conclusions
Relatively simple models provided accurate predictions of rifampin resistance in M. tuberculosis. These models demonstrated that only a few variable positions in the β subunit of DNA-dependent RNA polymerase were responsible for most of the variation in rifampin resistance. Such models might provide the basis for quantifying rifampin resistance status based exclusively on DNA sequence data and thus eliminate the requirements for time consuming culturing and antibiotic testing of clinical isolates. More generally, the results of this study demonstrate the usefulness of tree-based statistical models and random forests in genetic analysis.
Methods
Data sources
Sequence data for amino acid positions 511–533 of rpoB and associated MIC of rifampin for different isolates of M. tuberculosis were taken from studies examining rifampin resistance in clinical samples from New York City and throughout Japan [2-4]. Minimum inhibitory concentration (MIC) is defined as the minimum concentration of the antibiotic in a given culture medium below which bacterial growth is not inhibited.
Variables
The predictor variables are unordered categorical designations of amino acid at polymorphic positions, and the response variable are continuous values for MIC represented by their log2 transforms. Values given in the original sources as <x were set to log2(x - 0.5), and those values given as >x were set to log2(x + 0.5). The MIC values are converted back to μg/ml in figures to be consistent with Table 1 and to facilitate interpretation.
Tree-based statistical analyses
Analysis of the relationships between rpoB amino acid sequence and rifampin susceptibility was done through the use of tree-based statistical models [12], also known as classification and regression trees (CART) [13]. Analyses were done with rpart (recursive partitioning) [14] using the rpart library [15] for the open source statistical package R [16]. Tree-based models operate by recursively partitioning a data set in two (binary split) based on the value of a single predictor variable to best achieve homogeneous collections of a nominal or ordinal response variable (classification) or to best separate low and high values of a continuous response variable (regression). The split definition can be considered as a question, which has the following general form: Is the observation xi ∈ A? Here A is a region of the variable space. Thus answering the question for all observations produces two groups of observations; those for which the answer is yes (those in region A) and those for which the answer is no (xi ∉ A, those in the complement of A). The specific criteria for choosing among the possible partitions (questions) is based on the change in deviance, which for regression problems is equivalent to least squares. Subsequent binary partitioning continues until stopping criteria (variously defined) are met. The result is a classification or regression tree: a hierarchical series of data bifurcations, which depicts the partition definitions and describes the resulting data subsets defined by each partition.
For unordered categorical covariates, such as amino acid designation, the search through possible splits is exhaustive. For each variable amino acid position there are 2n-1 -1 possible partitions, where n is the number of different amino acids observed. For example, in the case of amino acid position 526 of rpoB analyzed here there are 9 observed amino acids resulting in 255 possible partitions to be evaluated. The preferred way to construct an appropriately sized tree is to first build a large tree and subsequently prune it [12,13]. Pruning is the process of removing branches from a tree to produce a subtree. To objectively choose the appropriate size for a pruned tree, it is useful to employ the concept of cost-complexity [13]. Embodied within the cost-complexity measure is a reward for tree (model) fit and a penalty for tree size (number of parameters). A tree can be pruned by using the cost-complexity measure to identify subtrees to be eliminated. A more formal definition and discussion of cost-complexity is given elsewhere [13].
Performance of tree-based models can be assessed in a number of ways depending on the goals of the analysis. One way is to evaluate the fit of the data used to generate the model, which is known as the re-substitution error. The use of re-substitution error may be justified when the principal goal of the analysis is to explain the observations in hand. However, the re-substitution error provides an underestimate of the error if the goal is to produce a model for future prediction. Another scheme to assess performance is to partition observations into a subset for model building, the training set, and a subset to evaluate the model, the test set. To remove biases this general scheme can be expanded in the form of cross-validation. Typically 10-fold cross-validation is used, where the data are randomly divided into 10 equal or near equal portions. Nine of these portions are used to generate the model and the remaining portion, the test set, is used to evaluate the model. This step is repeated until all test sets have been used in model evaluation.
We assessed the significance of our tree-based statistical models through permutation where the predictor variables are randomized with respect to the response variable [17]. The frequency of observing a result value equal to or better than the observed value in 1 × 104 permutations is the estimate of the probability associated with the observed result.
Random forest analyses
In a series of recent papers [18-21], Breiman has demonstrated that consequential gains in classification or prediction accuracy can be achieved by using an ensemble of trees, where each tree in the ensemble is grown in accordance with the realization of a random vector. Final predictions are obtained by aggregating (voting) over the ensemble, typically using equal weights. Bagging [18] represents an early example whereby each tree is constructed from a bootstrap [22] sample drawn with replacement from the training data. The simple mechanism whereby bagging reduces prediction error for unstable predictors, such as trees, is well understood in terms of variance reduction resulting from averaging [18,23]. Such variance gains can be enhanced by reducing the correlation between the quantities being averaged. It is this principle that motivates random forests.
Random forests seek to effect such correlation reduction by a further injection of randomness. Instead of determining the optimal split of a given node of a (constituent) tree by evaluating all allowable splits on all covariates, as is done with single tree methods or bagging, a subset of the covariates drawn at random is employed. Breiman [20,21] argues that random forests (a) enjoy exceptional prediction accuracy, (b) that this accuracy is attained for a wide range of settings of the single tuning parameter employed, and (c) that over-fitting does not arise due to the independent generation of ensemble members.
Here, our random forests comprised 1 × 104 individual trees constructed by sub-sampling eight predictor variables (regression) or two predictor variables (classification) at each node. Variable importance was assessed by measuring the increase in group purity when partitioning data based on a variable. We used the R package randomForest [24].
Authors' contributions
MPC conceived of the study, and participated in its coordination. Both authors participated in study design, carried out the statistical analyses, wrote and approved the final manuscript.
Acknowledgements
We thank AL Bazinet, DS Myers and MC Neel for assistance and comments on the manuscript.
Figures and Tables
Figure 1 Cross-validated pruned regression tree for minimum inhibitory concentration (MIC) of rifampin (μg/ml) based on amino acid sequence data from positions 511–533 of the β subunit of RNA polymerase of Mycobacterium tuberculosis. The number of observations (n) and the mean MIC values across observations () are given for each node. Split definitions are depicted with amino acid positions represented by numerals and amino acids represented by single letter code adjacent branches.
Figure 2 Cross-validated pruned classification tree for rifampin susceptibility and resistance based on amino acid sequence data from positions 511–533 of the β subunit of RNA polymerase of Mycobacterium tuberculosis. The numbers of observations in each class, susceptible or resistant, are given for each node.
Figure 3 Variable importance plot from random forest classification analysis. The plot includes all polymorphic positions in the region examined, and shows the importance of each position as the decrease in the Gini index (a measure of impurity) induced by splitting the data on that position averaged over all trees (higher values are more important). The plot for regression analysis is very similar (not shown).
Table 1 Minimum inhibitory concentration (MIC) of rifampin and associated variable amino acids in positions 511–533 of the β subunit of RNA polymerase of Mycobacterium tuberculosis [2–4].
MIC (μg/ml) No. of Isolates No. of Isolates
with Differences Amino Acid Differences from Consensus (No. of Isolates)
0.0625 48 1 515:V(1)
0.125 2 0
0.25 2 0
< 0.39 13 2 521:P(1), 533:P(1)
0.5 2 1 533:P(1)
1 3 1 533:P(1)
2 2 1 511:R and 512:T(1)
4 2 1 516:V(1)
8 6 5 516:V(1), 526:G(1), 526:L(2), 526:Q and 533:P(1)
12.5 3 3 514:L and 516:V(1), 533:P(2)
16 3 3 526:L(1), 526:N(1), 529:K(1)
32 1 0
> 32 15 15 511:R and 516:Y(1), 513:K(1), 513:L(1), 526:D(2), 526:Y(4), 531:L(4), 531:W(1), 533:P(1)
50 1 1 531:L(1)
64 7 7 531:L(7)
100 1 1 531:L(1)
128 19 19 513:L(1), 516:Y(1), 526Y(1), 531L(16)
200 1 1 526:D(1)
> 200 7 7 513:L(1), 516:A and 526:D(1), 526:P(1), 526:Y(2), 531:L(2)
256 13 13 513:K(1), 516:Y and 526:N(1), 526:P(1), 531:L(10)
512 18 18 526:P(4), 526:R(2), 526:Y(3), 531:L(7), 531:W(2)
> 512 4 4 516:Y(1), 526:D(1), 526:P(1), 531:W(1)
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| 15453919 | PMC524371 | CC BY | 2021-01-04 16:02:41 | no | BMC Bioinformatics. 2004 Sep 28; 5:137 | utf-8 | BMC Bioinformatics | 2,004 | 10.1186/1471-2105-5-137 | oa_comm |
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BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-5-1421546178910.1186/1471-2105-5-142SoftwareArrayD: A general purpose software for Microarray design Sharma Anu 1anusha77in@yahoo.comSrivastava Gyan Prakash 1gyanprakash@lycos.comSharma Vineet K 1vsharma@igib.res.inRamachandran Srinivasan 1ramu@igib.res.in1 Institute of Genomics and Integrative Biology (CSIR), Mall Road, Delhi 110 007, India2004 2 10 2004 5 142 142 3 6 2004 2 10 2004 Copyright © 2004 Sharma 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
Microarray is a high-throughput technology to study expression of thousands of genes in parallel. A critical aspect of microarray production is the design aimed at space optimization while maximizing the number of gene probes and their replicates to be spotted.
Results
We have developed a software called 'ArrayD' that offers various alternative design solutions for an array given a set of user requirements. The user feeds the following inputs: type of source plates to be used, number of gene probes to be printed, number of replicates and number of pins to be used for printing. The solutions are stored in a text file. The choice of a design solution to be used will be governed by the spotting chemistry to be used and the accuracy of the robot.
Conclusions
ArrayD is a software for standard cartesian robots. The software aids users in preparing a judicious and elegant design. ArrayD is universally applicable and is available at .
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Background
Microarray is a popularly used high-throughput technology to investigate gene expression of thousands of genes simultaneously at the level of mRNA. Ever since the development of this technology [1-3], transcriptional profiling at the genomic level has been employed to address numerous issues in biology and in medicine [4-8]. It is likely that microarrays will continue to be used to explore various biological phenomena. The basic underlying principle involves spotting DNA fragments either derived from polymerase chain reaction or preparation of plasmids or oligonucleotides at high density (~10,000–25,000 spots on a glass slide of 25 mm × 75 mm) representing the probes of the genes under study. The surface on which the DNA fragments or oligonucleotides are spotted is usually glass slides coated with poly-L-lysine or amino alkyl silane that serve to improve adherence of DNA to the surface. Uniform spotting at high density requires robotic operation and a variety of robots are now available for spotting [9]. The robots employed for the preparation of microarrays are of the cartesian type with movement in x-y-z direction.
A critical aspect of microarray production is the design considering space optimization to produce high-density arrays for a given set of samples and replicates. The softwares generally supplied with robotic spotters translate user input parameters into a set of instructions in robot language for printing arrays. These softwares do not offer design capabilities in which spotting parameters and grid configurations can be chosen for a given set of samples and replicates. Presently various solutions have to be derived manually in most academic laboratories. We have developed a user-friendly software 'ArrayD' that can be used by experts and novice alike to fill this gap to simplify and aid in rapid design. ArrayD offers a variety of design solutions given a set of requirements: Number of gene probes, number of replicates, and the source plate (384 well or 96 well). Because the algorithm implemented in ArrayD is inherently simple and uses fundamental principles of robot operation, the design solutions offered by ArrayD are universally applicable to any system. The choice of a design solution would be governed by the spotting chemistry and the humidity used in addition to elegant appearance. The hallmark of ArrayD is its overall simplicity and the variety of alternative designs it offers for users to decide on choosing the appropriate spotting parameters. The multiple design solutions offered by ArrayD provides a wide range of arrays from compact to loosely spaced spots as well as convenient grid patterning, which can be user selected for printing.
Implementation
ArrayD program is developed in C and can be compiled and operated on UNIX V5.1, IRIX 5.1 and Red Hat Linux 7.0 (or higher) operating systems. A companion computer program ArraySolution was developed in Perl (Practical Extraction Report Language) version 5.6.1 and can be implemented on any UNIX or Linux operating system.
Inputs to be defined for ArrayD
(a) Type of source plate to be used
The input parameter toggles between either 96 well or 384 well plate.
(b) Number of gene probes to be printed
The number of gene probes including positive and negative controls and blanks.
(c) Number of replicates
The number of replicates of each gene probe. Although the most common pattern chosen is duplicates, users can choose any number of replicates. Replicates are assumed to be printed in the Y axis.
(d) Number of pins to be used for printing
This parameter relates to time taken for printing the slides and the number of spots arrayed per slide. The number of pins in X-axis and Y-axis need to be specified. The type of pins used is assumed to be stealth pins, which are widely used. It is not necessary to specify pin type for ArrayD. Instead, this aspect is considered in the printing software according to the pin type used for implementing a particular design.
Results and discussion
A general microarray design layout is displayed in Figure 1. ArrayD accepts standard slide dimensions (25 mm × 75 mm), conceptualizes the spotting area to be 50 mm × 22 mm to provide space for barcode labeling and for appropriate placement of coverslip over the print area.
The reference direction of the robot for picking probes from source plate is left → right followed by top → down; the printing direction is top → down followed by left → right. Replicates are considered to be spotted in Y-axis (Figure 1). After the user has entered the parameters, the software generates a text file called 'solution.txt' that carries possible alternative array design parameters for the given input. The algorithm implemented in ArrayD is displayed in Figure 2.
The program first validates the input given by the user for appropriate number of pins in each direction and the plate type to be used. For a valid input, ArrayD calculates maximum possible number of super grids in X (or Y) direction based on the coverslip dimensions, pin number in X (or Y) direction and pin-to-pin distance (Figure 2). The coverslip dimensions have been set in the program as 50 mm × 22 mm for the longest size coverslip that can be effectively used during hybridization. The pin-to-pin distance is fixed at 4500 microns in the print head for 384 well plates and at 9000 microns for 96 well plates.
ArrayD uses a predefined inter-spot distance database. Design solutions of ArrayD encompass various inter-spot distances that would be compatible with different spotting chemistries and conditions of humidity. We have used inter-spot distances of 170 μm, 180 μm, 190 μm, 200 μm, 220 μm, 250 μm and 300 μm. This database can be expanded to incorporate even lower inter-spot distances for use with other spotting chemistries by simple modification. We chose 170 μm as least distance based on several trial experiments in our laboratory using 50% DMSO as spotting solution and SMP3 pin type. In our experience, a minimum inter-spot distance of 200 microns works best with 50% DMSO at 40% – 50% humidity at 25°C.
The options for the inter-spot distance currently offered by the software can work successfully for SMP2, SMP2B, SMP2XB, SMP2.5, SMP2.5B, SMP2.5XB, SMP3, SMP3B, SMP3XB, SMP4, SMP4B, SMP4XB, SMP5, SMP5B and SMP5XB stealth pins (See Table 1). For each possible super grid configuration, the number of grids in each direction is optimized based on the number of gene probes (samples) input by the user as shown in figure 2.
Design solutions offered by the program
Alternative array designs for a given set of input parameters are ranked on the basis of 'Distance area ratio' that describes the area covered by the array for each design. The array design spanning least area is ranked highest. This strategy allows for applying the labeled target sparingly. Subsequently, an easy report in tabular form can be generated by feeding the output data file from ArrayD into the companion Perl program 'ArraySolution.pl', which classifies array solutions into 'Square', 'Rectangle (Horizontal bar)', or 90° rotated 'Rectangle (Vertical column)' based on the geometry of a given design solution. If the number of grids are equal in both the direction we have a 'Square' design. In all other cases we obtain a 'Rectangle' design, which can be either of two types: the long side of the array is parallel to the length (Horizontal) or the width (Vertical) of the slide. The output of ArraySolution is a tab-delimited text file called 'filename.solution' where filename corresponds to the input name of the file carrying design solutions. The tabular report consist of Number of super grids in X – direction, Number of super grids in Y – direction, Number of spots per grid in X – direction, Number of spots per grid in Y – direction, Distance between two spots (in microns), Distance Area ratio and geometry of design (Square or Rectangle). This can aid users to decide on a particular design solution based on space optimization and elegant appearance.
An example of a sample run is provided in Figure 3. The number of gene probes (including controls and blanks) to be spotted using a 2 by 2 pin configuration in X-Y axis is fed as 2304 (Figure 3). The gene probes have to be spotted in duplicates so the total number of spots on the slide would be 4608. The program provides 67 different array designs for various inter-spot distances, number of grids and number of spots in each grid. Two examples of different solutions are presented in Figure 4. In this example, the first solution is ranked highest with inter-spot distance of 170 microns and a 24 × 24 grid pattern with 4 grids in Y axis and 2 grids in X axis. An alternative solution provides a design with a higher inter-spot distance of 200 microns and 18 × 16 grid pattern with 4 grids each in X axis and Y axis. The first solution can be used in conditions when humidity is low and the spotting solution does not absorb moisture and spread after printing. The second solution is more appropriate for printing samples in 50% DMSO. The classification of all design solutions based on the geometries obtained from ArraySolution is displayed in Table 2 [see Additional file 1].
Conclusion
We have developed a simple and rapid software ArrayD that offers various design solutions of designing microarrays for a specific set of user-defined requirements.
Availability and requirements
The source code and the executable file for ArrayD and ArraySolution programs are freely available and can be downloaded from our website [11]. The source code can be compiled and executed on Unix v 5.1, or IRIX v 5.1 or Red Hat Linux v 7.0 (or higher). The executable files can be downloaded for Windows platform (Windows 98/NT/XP/2000). Further information can be requested by sending e-mail to ramu@igib.res.in or ramucbt@yahoo.com.
Authors' contributions
AS explained the operational details to software expert, did the experimentation, maintenance and testing of the software. GPS did the basic software writing and implementation of 'ArrayD'. VKS prepared the code for the companion program 'ArraySolution' to classify the solutions on the basis of design geometry. SR is the Group Leader generating demand, sourcing and linking people, explaining the concepts, testing, critical examination, presentation of data, providing salary through grants.
Supplementary Material
Additional File 1
Report generated by ArraySolution. A total of 67 different design solutions were classified into three categories of Square, Rectangle (Horizontal) and Rectangle (Vertical) as mentioned in text. The detailed design parameters including number of supergrids in X and Y direction, number of spots per grid in X and Y direction, distance between the spots, distance area ratio and geometry of design are provided for preparing elegant microarrays.
Click here for file
Acknowledgements
AS, GPS and VKS thank Council of Scientific and Industrial Research (CSIR) for providing financial assistance. We thank Dipayan Dasgupta for his help in compilation of the software and Mamta Khandelwal for her help in uploading the software on the web site. We thank the assistance of Technosol.
Figures and Tables
Figure 1 A general layout of microarray. In this example, a 2 × 2 pin configuration for 192 samples and 384 spots (duplicate) were considered. The origin is marked. Each pin prints one grid. One Super grid comprises of 4 grids, two in each axis. The number of super grids in X-direction is 2 and the number of super grids in Y-direction is 1. The spot pattern of a portion of one grid is zoomed for clarity. Replicates are spotted adjacent to each other in Y-direction. The number of samples in each grid is 24 and the total number of spots is 48. Two spots are further zoomed to show the diameter of the spot and the inter-spot distance.
Figure 2 The flowchart of algorithm implemented in ArrayD to compute all possible design solutions for a given input parameters. The program first validates the given input parameters and then calculates the grid configuration. Note that in the case of 384 well plate type the pin-to-pin distance is 4500 microns on the print-head and therefore the max-grid-size is set at 4000 microns, which is 500 microns less than the upper limit (4500 microns). Similarly for 96 well plate type, the max-grid-size is set at 8500 microns (500 microns less than the upper limit 9000 microns). Maximum number of pins in the print head is taken as 48 and conforms to most printing robots. The spot distance database has inter-spot distances of 300, 250, 220, 200, 190, 180 and 170 microns. Users can expand this database. The variables used in the flowchart: pin_x: pin number in X-direction; pin_y: pin number in Y-direction; R: number of replicates; D: pin-to-pin distance; d: inter-spot distance; SGx (max): maximum possible number of super grids in X-direction; SGy (max): maximum possible number of super grids in Y-direction; GT: Total number of grids in the slide; Gx: Total Number of Grids in X-direction; Gy: Total Number of grids in Y-direction; ST: Maximum possible number of samples in each grid; Sx: Maximum possible number of samples in each grid in X-direction; Sy: Maximum possible number of samples in each grid in Y-direction; Xs: number of samples in each grid in X-direction for a solution; Ys: number of samples in each grid in Y-direction for a solution; Sg: Total number of samples per grid for a solution; A: Total area covered by the microarray on the slide.
Figure 3 Screenshot of input parameters to ArrayD. Five inputs (Plate type (384 or 96), total number of samples, total number of replicates, pin number in X-axis and pin number in Y-axis) are fed to the program sequentially.
Figure 4 A sample run of ArrayD. The inputs given to the program were: type of plate-384; number of samples-2304; number of replicates-2; number of pins in X-axis-2; number of pins in Y-axis-2. A total of 67 solutions were offered. Two solutions are shown: top ranking solution with inter-spot distance 170 μm and an alternative design solution with inter-spot distance 200 μm. The ArrayD output was subsequently fed to the companion program 'ArraySolution' to classify each design based on its geometry and the report generated is displayed in Table 2 [see Additional file 1].
Table 1 Stealth pins for implementing various design solutions offered by ArrayD
Stealth Pin Catalog Number a Spot Diameter b (μm) Minimum spot spacing c (μm)
SMP2 62.5 90
SMP2B 70 100
SMP2XB 80 110
SMP2.5 85 100
SMP2.5B 90 110
SMP2.5XB 110 130
SMP3 100 120
SMP3B 110 135
SMP3XB 125 150
SMP4 135 160
SMP4B 145 175
SMP4XB 160 190
SMP5 165 200
SMP5B 185 215
SMP5XB 200 240
a: The catalog numbers of pins according to Telechem Inc., USA.
b: The spot diameter (in microns) indicates the size of the spot after printing microarrays.
c: The minimum inter-spot distance that can be achieved for each of the respective pins to avoid overlapping or smudging of the spots. Data sourced from Arrayit web site [10].
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Arrayit Web site
ArrayD Web site
| 15461789 | PMC524372 | CC BY | 2021-01-04 16:02:45 | no | BMC Bioinformatics. 2004 Oct 2; 5:142 | utf-8 | BMC Bioinformatics | 2,004 | 10.1186/1471-2105-5-142 | oa_comm |
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BMC Med Res MethodolBMC Medical Research Methodology1471-2288BioMed Central London 1471-2288-4-241546182110.1186/1471-2288-4-24Research ArticleThe fallacy of enrolling only high-risk subjects in cancer prevention trials: Is there a "free lunch"? Baker Stuart G 1sb16i@nih.govKramer Barnett S 2KramerB@OD.NIH.GOVCorle Donald 1dc13a@nih.gov1 Biometry Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland, USA2 Office of Disease Prevention, National Institutes of Health, Bethesda, Maryland, USA2004 4 10 2004 4 24 24 16 3 2004 4 10 2004 Copyright © 2004 Baker et al; licensee BioMed Central Ltd.2004Baker 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
There is a common belief that most cancer prevention trials should be restricted to high-risk subjects in order to increase statistical power. This strategy is appropriate if the ultimate target population is subjects at the same high-risk. However if the target population is the general population, three assumptions may underlie the decision to enroll high-risk subject instead of average-risk subjects from the general population: higher statistical power for the same sample size, lower costs for the same power and type I error, and a correct ratio of benefits to harms. We critically investigate the plausibility of these assumptions.
Methods
We considered each assumption in the context of a simple example. We investigated statistical power for fixed sample size when the investigators assume that relative risk is invariant over risk group, but when, in reality, risk difference is invariant over risk groups. We investigated possible costs when a trial of high-risk subjects has the same power and type I error as a larger trial of average-risk subjects from the general population. We investigated the ratios of benefit to harms when extrapolating from high-risk to average-risk subjects.
Results
Appearances here are misleading. First, the increase in statistical power with a trial of high-risk subjects rather than the same number of average-risk subjects from the general population assumes that the relative risk is the same for high-risk and average-risk subjects. However, if the absolute risk difference rather than the relative risk were the same, the power can be less with the high-risk subjects. In the analysis of data from a cancer prevention trial, we found that invariance of absolute risk difference over risk groups was nearly as plausible as invariance of relative risk over risk groups. Therefore a priori assumptions of constant relative risk across risk groups are not robust, limiting extrapolation of estimates of benefit to the general population. Second, a trial of high-risk subjects may cost more than a larger trial of average risk subjects with the same power and type I error because of additional recruitment and diagnostic testing to identify high-risk subjects. Third, the ratio of benefits to harms may be more favorable in high-risk persons than in average-risk persons in the general population, which means that extrapolating this ratio to the general population would be misleading. Thus there is no free lunch when using a trial of high-risk subjects to extrapolate results to the general population.
Conclusion
Unless the intervention is targeted to only high-risk subjects, cancer prevention trials should be implemented in the general population.
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Background
Some prevention trials are restricted to high-risk subjects. If the investigators are only interested in the effects of the intervention on subjects at increased risk [1] or if the study is designed to be a preliminary investigation in preparation for a definitive study in the general population, we think this restriction is reasonable.
However some investigators who are interested in studying the effect of the intervention in the general population may be tempted to design a "definitive" study to estimate the effect of the intervention in a high-risk group. Some investigators may believe that a trial of high-risk subjects would have greater power than a trial of the same size among average-risk subjects. Some examples of this type of thinking can be found in papers on risk prediction models [2,3]. Some investigators may believe that a trial of high-risk subjects with the same power as a trial of average-risk subjects would have lower costs than a trial of average-risk subjects. Some investigators may believe the ratio of benefits to harms can be correctly extrapolated from high-risk to average-risk subjects. Although the rationales for these various beliefs are related, they involve some distinct underlying assumptions that are important to critically examine.
Methods and results
Possibly lower statistical power
To crystallize our thinking about statistical power, we consider the following simple hypothetical and realistic example. Investigators want to estimate the effect of intervention in the general population, so they first consider designing a randomized trial among the general at-risk population. Suppose they anticipate that the cumulative probability of incident cancer over the course of the study is pC = .02 in the control arm and pI = .01 in the study arm, and they believe that the difference in probabilities is clinically significant. Also suppose that due to the limited availability of the intervention, they can enroll at most n = 2000 study participants in each arm. The investigators compute power using the following standard formula [1] setting the two-sided type I error at .05,
where NormalCDF is the cumulative distribution function for a normal distribution with mean 0 and variance 1, Δ is the anticipated difference one wants to detect, n is the sample size per arm, seNull is the standard error under the null hypothesis, and seAlt is the standard error under the alternative hypothesis. Let p = (pC + pI)/2. As discussed in [1], for a study designed to estimate the absolute risk difference, the statistic of interest is , so
For a study designed to estimate the relative risk, the statistic of interest is , so
Applying these formulas to the above example and substituting either (2) or (3) into (1), the investigators obtain a power of .74 based on the absolute risk difference statistic and a power .76 based on a relative risk statistic [see Additional file 1].
Suppose the investigators think this power is too low. To increase power they propose to restrict the study to a high-risk group in which the probability of cancer is .04. Also suppose the investigators make the typical assumption that if the intervention yields a relative risk of .5 in the general population, it would also yield a relative risk of .5 in the high-risk group. Applying (1–3) with high risk subjects for whom pC = .04 and pI = .02 with n = 2000, the investigators compute a power of .96 using either the absolute risk difference or relative risk. Because the power is higher using high-risk subjects, the investigators plan the study for a high-risk population and will generalize the results to the general population.
Is there a free lunch? An underlying assumption in this example is that the relative risk is invariant between the general population and the high-risk group. There is no free lunch because the impact of violating this assumption could be substantial. For example, suppose instead that the absolute risk difference is invariant between the general population and the high risk group. Under this scenario the absolute risk difference in the general population is .01, so the absolute risk difference in the high-risk group is also .01. In this case for pC = .04, pI = .03, and n = 2000, the power (computed using either absolute risk difference or relative risk statistics) for the trial of high-risk subjects is only .41. The decreased power in a high risk group under a constant risk difference model is not surprising: if the risk difference pC - pI is the same, but pI is increasing, the variances, pC(1 - pC)/n and pI(1 - pI)/n, will increase as pC increases up to .5, which will reduce the power.
A crucial issue is whether or not the absolute risk difference or the relative risk is likely invariant between average-risk subjects in the general population and high-risk subjects. The answer depends on the cancer, the interventions, and the biology. To gain some appreciation of this issue, we analyzed published data (summarized in Table 1) from a prevention trial of particular interest to us, a study of tamoxifen for the prevention of breast cancer [5]. Rather than limit the analysis to one particular high-risk group, we investigated subjects at various levels of risk defined separately by three variables: age, predicted risk, (the five-year risk of cancer based on the Gail model [3]), and family risk. We fit four models separately to each variable:
Table 1 Data from a cancer prevention trial for investigating assumptions of constant risk difference and relative risk when risk groups change.
Placebo group Tamoxifen group
Variable risk group cancer at risk cancer at risk
age at entry 1 ≤ 49 68 10149 38 10045
2 50–59 50 7912 25 8040
3 >60 57 7719 26 7782
predicted risk 1 ≤ 2.00% 35 6318 13 6311
2 2.01–3.01% 42 8108 29 8262
3 3.01–5.00% 43 7313 27 6959
4 ≤ 5.01% 55 4142 20 4425
family risk 1 0 38 5891 17 5724
2 1 90 15000 46 15182
3 2 37 4263 20 4211
4 3 10 729 6 855
Cancer is invasive breast cancer. Predicted risk is the 5-year predicted risk. Family risk is number of first degree relatives with breast cancer. Data are from Table 5 of [5] with number at risk computed by dividing number of breast cancers by reported breast cancer rate.
constant risk difference,
where δ is the risk difference that is constant over groups;
varying risk difference,
where δi is the risk difference that varies over groups;
constant relative risk,
where β is the relative risk that is constant over groups;
varying relative risk,
where β is the relative risk that varies over groups.
We obtained maximum likelihood estimates of δ, δi, β, and βi using a Newton-Raphson procedure [see Additional file 2].
To investigate the plausibility of the constant relative risk and constant risk difference models in this example, we plotted the estimates of δ, δi, β, and βi along with confidence intervals (Figure 1). In the top row of Figure 1 we plotted points corresponding to with (100 - 5/k) % confidence intervals and horizontal lines for with 95% confidence intervals. We also presented the p-values corresponding to twice the difference in log-likelihoods for Varying RD versus Constant RD. Similarly, in the bottom row of Figure 1, we plotted points corresponding to with (100 - 5/k)% confidence intervals and horizontal lines for with 95% confidence intervals. We also presented the p-value corresponding to twice the difference in log-likelihoods for Varying RR versus Constant RR. Out of 6 p-values (3 risk factors × 2 statistics) only one, for absolute risk difference under the risk factor of predicted risk had a small p-value (and the p-value of .01 would not be significant at the .05 level under a Bonferroni adjustment of .05/6). Based on these p-values and inspection of Figure 1, the models Constant RD and Constant RR are both plausible, especially for age and family risk.
Figure 1 Data from the tamoxifen prevention trial. See text for a description of groups. Horizontal lines are estimates and 95% confidence intervals for model for constant absolute risk difference per 1000 (RD) or relative risk (RR). P-values correspond to likelihood ratio tests comparing the models with varying and constant risk difference or relative risks.
The trial designer does not know the true state of nature. If Constant RD is the true state of nature, the power will be lower in the high-risk group than the general population. However if Constant RR is the true state of nature, the power will be greater in the high-risk group than the general population. Thus there is high probability that the power could be reduced when studying high-risk subjects than when studying the general population. Therefore, there is no free lunch in terms of lowering statistical power.
Possibly increased costs
Even if the model is correct (namely pC and pI are correctly chosen), the smaller trial of high-risk subjects may be more expensive than the larger trial of average-risk subjects from the general population. Consider the following two trials with a power of .90 and a one-sided type I error of .05. In the trial of high-risk subjects pC = .04 and pI = .02, and in the trial of average-risk subjects, pC = .02 and pI = .01. Suppose the statistic of interest is the absolute risk difference. To obtain sample size for each randomization group we use the standard sample size formula [4],
where p = (pC + pI)/2, 1.644485 is the z-statistics corresponding to the 95th percentile of the normal distribution (for a one-sided type I error of .05) and 1.28155 is the z-statistics corresponding to the 90th percentile (for a power of .90). Based on (4), the sample size for a trial using average-risk subjects from the general population study is 2529 per group and the sample size for a trial of high-risk subjects is 1244 per group. Let CR denote the cost of recruitment per subject and CI denote the cost of intervention and follow-up per subject averaged over the two randomization groups. Suppose high risk subjects comprise a fraction f of the general population. The total cost of the trial for average-risk subjects from the general populations is
Cgeneral = 2(CR 2529 + CI 2529), (5)
and the total cost of the trial for high-risk subjects is
Chigh-risk = 2(CR 1244/f + CI 1244). (6)
where the factor of 2 is for the two randomization groups. The condition for the trial of high-risk subjects to cost more than the trial of average-risk subjects (namely Chigh-risk >Cgeneral) is
when 1244/f - 2529 > 0. If f = .20, the trial of high-risk subjects will cost more than the trial of average-risk subjects if CR/CI > .34. If f = .10, the trial of high-risk subjects will cost more than the trial of average-risk subjects if CR/CI > .13.
In many cancer prevention trials the above values of CR/CI are likely. For example, diagnostic testing to identify high-risk smokers can include expensive airway pulmonary function tests or bronchoscopy. In the future, more trials will likely involve expensive genetic testing of subjects [5] with costs ranging from $350 to almost $3,000 per test according to recent information from Myriad Genetic Laboratories. As part of a sensitivity analysis related to genetic testing of subjects prior to enrollment in a trial, Baker and Freedman [5] considered values of .1, .5, and 1 for ratios similar to CR/CI.
Even without diagnostic testing, the costs of obtaining high-risk subjects can be substantial. If f = .10, the initial recruitment will require ten times the number of people as for a trial of average-risk subjects from the general population. This increased recruitment would likely require higher advertising costs and increased overhead costs from the inclusion of additional institutions.
One additional consideration is how noncompliance and contamination affect the intent-to-treat analysis. If noncompliance and contamination can be anticipated, the investigator can correspondingly adjust the sample size and costs. Mathematically the effect of noncompliance and contamination is to change the values of pC and pI in (4), which would then affect (5) and (6). In some settings, investigators may anticipate that high-risk subjects are more likely to comply with the intervention than average-risk subjects. To compensate for the anticipated increased compliance, study designers could reduce the sample size which would lower costs. However, in other situations, investigators may anticipate that subjects found to be at high-risk on a diagnostic test would likely seek the best therapy outside of the trial rather than chance randomization to standard or experimental therapy. To compensate for the anticipated dilution in treatment effect, investigators would need to increase the sample size which would increase the costs.
For the above reasons even if the probabilities under the alternative hypothesis are correctly specified, some trials of high-risk subjects may be more expensive than larger trials of average-risk subjects with the same power and type I error.
Possibly misleading ratio of benefits to harms
When there is strong evidence prior to the trial of a high probability of harmful side effects due to the intervention, one would want to restrict the intervention to high-risk subjects. Otherwise, some investigators may be tempted to estimate the ratio of benefit to harms in the trial of high-risk subjects and extrapolate the ratio to average risk subjects. Unfortunately, even if the assumption of constant relative risk over risk categories were true, extrapolating the benefit-harm ratio from a high risk group to the general population could be misleading.
Suppose that in a randomized trial involving average-risk subjects from the general population the probability of cancer is .02 in the control arm and .01 in the study arm. Also suppose that relative risk is same in the general population as in the high-risk group, so that in a randomized trial involving a high-risk group, the probability of cancer is .04 in the control arm and .02 in the study arm. Furthermore, suppose that the probability of harmful side effects is the same for high-risk subjects as for average-risk subjects in the general population, namely .015 in the control arm and .025 in the study arm. Based on these results, for every 1000 high-risk persons who receive the intervention, (.04 - .02) 1000 = 20 will benefit from the intervention and (.025 - .015) 1000 = 10 will be harmed by side effects, yielding a benefit-harm ratio of 20:10 = 2:1. Similarly for every 1000 average-risk person who receive the intervention, (.02 - .01) 1000 = 10 will benefit from the intervention and (.025 - .015) 1000 = 10 will be harmed by side effects yielding a benefit-harm ratio of 10:10 = 1:1. In this example it would be incorrect to extrapolate the high benefit-harm ratio estimated from the high-risk group to the general population for whom the benefit-harm ratio is much lower. For many cancer prevention interventions, the ratio of life-threatening disease avoided to life threatening harms would be favorable in the high-risk group but not favorable when extrapolated to the general population.
Conclusion
There is no "free lunch" when using high-risk subjects in prevention trials design to make inference about the general population. Using high risk subjects instead of average-risk subjects from the general population may lower statistical power, increase costs, and yield a misleading ratio of benefit to harms than actually the case.
Given the substantial costs of definitive randomized trials in cancer prevention, and the importance of accurately assessing the balance of benefit and harm when treating healthy and asymptomatic people, it is therefore important to conduct trials in the actual target population rather than try to conduct them in high-risk populations with the plan to extrapolate results to the general population.
Competing Interests
The authors declare that they have no competing interests.
Authors' contributions
SGB wrote the initial draft, and BSK and DC made valuable improvements. 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
Appendix A, worked-out calculations of power.
Click here for file
Additional File 2
Appendix B, likelihood formulations
Click here for file
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Gail MH Brinton LA Byar DP Corle DK Green SB Schairer C Mulvihill JJ Projecting individualized probabilities of developing breast cancer for white females who are being examined annually Journal of the National Cancer Institute 1989 81 1879 1886 2593165 10.1093/jnci/81.24.1879
Frideman LM Furberg CD DeMets DL Fundamental of Clinical Trials 1981 John Wright: Boston
Baker SG Freedman LS Potential impact of genetic testing on cancer prevention trials, using breast cancer as an example Journal of the National Cancer Institute 1995 87 1137 1144 7674318
Fisher B Costantino JP Wickerham DL Redmond CK Kavanah M Cronin WM Vogel V Robidoux A Dimitrov N Atkins J Daly M Wieand S Tan-Chiu E Ford L Wolmark N Tamoxifen for Prevention of Breast Cancer: Report of the National Surgical Adjuvant Breast and Bowel Project P-l Study Journal of the National Cancer Institute 1998 90 1371 1388 9747868 10.1093/jnci/90.18.1371
| 15461821 | PMC524373 | CC BY | 2021-01-04 16:32:50 | no | BMC Med Res Methodol. 2004 Oct 4; 4:24 | utf-8 | BMC Med Res Methodol | 2,004 | 10.1186/1471-2288-4-24 | oa_comm |
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BMC Med EducBMC Medical Education1472-6920BioMed Central London 1472-6920-4-161538505110.1186/1472-6920-4-16Research ArticlePerceptions of first and third year medical students on self-study and reporting processes of problem-based learning Musal Berna 1berna.musal@deu.edu.trGursel Yucel 1yucel.gursel@deu.edu.trTaskiran H Cahit 1cahit.taskir@deu.edu.trOzan Sema 1sema.ozan@deu.edu.trTuna Arif 1ariftuna@hotmail.com1 Medical Education Department, Dokuz Eylul School of Medicine, Inciralti, Izmir, Turkey2004 22 9 2004 4 16 16 20 5 2004 22 9 2004 Copyright © 2004 Musal et al; licensee BioMed Central Ltd.2004Musal 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 objective of this study is to investigate the perceptions of first and third year medical students on self-study and reporting processes of Problem-based Learning (PBL) sessions and their usage of learning resources.
Methods
The questionnaire applied to the students consisted of; questions about students' perceptions on searching and preparing phases of the self-study process, the breadth and depth of discussion during reporting phase and the usage of learning resources.
Results
First-year students spent more time for self-study and more highly rated the depth of discussion compared to third-year students. The searching and preparing phases of the self-study process were considered as statistically important factors strongly influencing the breadth and depth of discussion during the reporting phase. The effect of extensiveness of searching on the depth of discussion was negative among the first-year students, and positive among third-year students.
Conclusions
The relative shortness of third-year students' self-study periods can be related to their mental weariness, decreased motivation or first-year students' slowness in accessing appropriate resources. The third-year students' more frequent use of textbooks may be due to the improvement of their abilities in reaching relevant learning resources. The findings implied that the increase in students' PBL experience paralleled the development of their discussion skills using different learning resources.
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Background
The institution of the present study, Dokuz Eylul University School of Medicine (DEUSM), has been implementing Problem-based Learning (PBL) in its undergraduate curriculum since the 1997–1998 academic year. The duration of undergraduate medical education is six years. PBL is the principal educational strategy in the first three years. Task-based learning strategy was adopted as an educational strategy for clerkships in the 2000–2001 academic year. During the first three years of undergraduate education, PBL sessions are the main focus of a modular structure.
The three objectives of PBL are; acquisition of essential knowledge, use of knowledge in clinical contexts and self-directed learning [1]. In a PBL programme, the students use a seven-step procedure to structure their activities. This procedure consists of clarifying vague phrases and concepts in the problem, defining the problem, analysing the problem on the basis of prior knowledge, arranging the proposed explanations, formulating learning objectives, trying to fill in the knowledge gaps by means of self study and reporting the findings in the group [2]. Individual study is an essential step of information processing approach to learning. The group members individually collect information with respect to the objectives [3].
PBL curriculum emphasises the development of self-regulating skills. Rather than being passive recipients of information, students are expected to be actively involved [4]. The diversification of learning resources and their access routes had a considerable impact on professional skills development. Due to the fact that medicine requires lifelong learning, it has become important for students to discover learning resources on their own and to interpret their findings. The use of a variety of resources necessitates the processing of information through critical self-directed inquiry. Important components of a PBL curriculum are self-directed learning and students' investigation of learning objectives. They support deep approaches to learning. Compared to traditional lecture-based curriculum, students in a PBL curriculum use a greater number and variety of resources [5].
In PBL, students are encouraged to take substantial responsibility for their learning. Small group discussions stimulate independent and active learning. They guide the students during their independent and self-directed learning. During a PBL group session, limited only by the boundaries of their prior knowledge, students try to clarify the issues being discussed. The issues that cannot be explained thoroughly are formulated as student-generated learning objectives which will guide the students during their independent and self-directed learning.
During the searching phase of individual study, students are expected to refer to different learning resources and search for literature relevant to their learning issues. The findings are evaluated and prepared for the group discussion. The extensiveness of different learning resources used is an indicator of students' self-directed learning skill. The consultation of diverse information sources influences the breadth and depth of discussion of the tutorial group during the reporting phase [6].
The iteration of self-directed learning periods leads the students to organise and review the learning resources critically. Through this critical approach, a major educational objective of PBL, the learning resources can be efficiently and effectively accessed and relevant information can be elaborated to form the theoretical basis leading to the solution of the problem [1]. Students learn most effectively when using a variety of information resources. Therefore, the provision of adequate resources meeting the needs of different learning styles is important. Students' accessibility to these learning resources may be limited if they are preserved at different locations under the management of different departments [7]. Since the beginning of the curriculum change process in Dokuz Eylul University School of Medicine (DEUSM), a special emphasis has been given to the diversification and improvement of learning resources, and facilities have been improved to meet the learning needs of PBL students. During the first three academic years of DEUSM, approximately 30–35% of the weekly schedule is allocated to students' self-study periods. Several types of learning resources such as the library, the Learning Resources Centre and a computer laboratory with Internet access are available to students. In addition, the staff teachers provide appointment-based scientific counselling upon request. The library, offering a wide variety of printed material like textbooks and periodicals is open on office days and weekends between 8:30 a.m.–11:00 p.m. The Learning Resources Centre, an interactive learning environment inaugurated in the 2001–2002 academic year, is open on office days between 8:30 a.m.–7:00 p.m. The learning resources of the centre are; CD-ROMs, video-tapes, microscopes, histology and pathology slides, models & mannequins, posters and computers with Internet access. The centre's exhibitions of learning material are synchronous with the PBL modules being implemented.
During the first week of their medical education, first-year students attend a PBL orientation course. This course consists of basic principles of PBL, student and tutor roles and presentation of available learning resources in DEUSM. All tutors are initially required to take a PBL course and regularly attend weekly tutor meetings [8]. The tutor profile of the first three years is similar. Faculty members from all existing preclinical and clinical departments fulfil tutor role in PBL groups for determined periods of time during an academic year. Some alterations observed by tutors in preparing and reporting processes between novice and experienced PBL students led us to plan the present study.
The research questions of this study are;
√ What were the differences between first and third-year students' perceptions with respect to self-study and reporting processes of PBL?
√ What were the length of students' self-study times and their usage of learning resources?
√ What was the overall and year-specific impact of self-study process on the breadth and depth of discussion during the reporting phase?
The objective of the present study is to investigate and compare the perceptions of first and third-year PBL students on self-study and reporting processes and their usage of learning resources.
Methods
The first-year students of DEUSM who were recently introduced to PBL programme and completed their first semester and the third-year students who had a two and a half year experience in the PBL programme were included in this study.
The questionnaire consisted of questions about students' perceptions on searching and preparing phases of the self-study process, the breadth and depth of discussion during reporting phase and the usage of learning resources. The questionnaire implemented and tested for validity and reliability in Maastricht University [6] was translated into Turkish, using expressions appropriate for our study group. Two questions, one on self-study time and the other on the usage of learning resources were added (Appendix 1).
The participants reflected their perceptions of 22 questionnaire items, grouped under the headings of searching and preparing phases of self-study process, breadth and depth of discussion during the reporting phase, on a five-point scale ranging from 1 = totally disagree to 5 = totally agree. The points attributed to the items of the scale were evaluated between 1 to 5 points (1 = minimum, 5 = maximum).
The pilot study of the questionnaire was applied to 10 medical students and favourable results were obtained. At the beginning of a PBL session in February 2002, the questionnaire was distributed to first and third-year students and collected 15 minutes later. Before the application of the questionnaire, the purpose of the study was briefly explained to the students and their oral consents were obtained.
The response rate was 78.8% (115/146) for first-year students and 85.5% (142/166) for third-year students.
SPSS 10.0 for Windows was used and the reliability coefficient was calculated (Cronbach alpha: 0.81). Chi-Square Test was used to investigate students' frequency of use of learning resources. Independent Samples T Test was used to compare the scores of self-study and reporting processes of both classes. The effects of independent variables on the breadth and depth of discussion were analysed with Multiple Regression Analysis Test.
Results
The weekly self-study times of the first and third-year students during a two-week module were 15.00 ± 8.83 and 11.57 ± 7.04 hours respectively (p = 0.001).
The first and third-year students' percentages of learning resources usage and statistical difference between them were respectively as follows; textbooks 24.3% and 44.4% (χ2 = 11.1, p = 0.01), educational CDs 14.8% and 6.3% (χ2 = 4.983, p = 0.026), lecture handouts 95.7% and 95.8% (χ2 = 0.002, p = 0.962) and medical journals 8.7% and 9.9% (χ2 = 0.102, p = 0.750). Lecture handouts were used very frequently. It was found that third-year students referred more frequently to textbooks than first-year students.
The scores reflecting students' perceptions of statements regarding learning issue driven searching and extensiveness of searching ranged between 3.4–3.7 out of five (Table 1). Third-year students' scores for the same statements were higher than those of first-year students' (p = 0.034, p = 0.009). First-year students' average scores on explanation-oriented preparing of learning issues were higher than those of third-year students' (p = 0.015).
Table 1 First and third-year students' average scores regarding self-study process
Titles First-year students average score* ± SD Third-year students average score* ± SD Statistical analysis**
Learning issue driven preparing 3.5 ± 0.8 3.7 ± 0.8 P = 0.034
Extensiveness of searching 3.4 ± 0.9 3.7 ± 0.9 P = 0.009
Explanation-oriented preparing 3.5 ± 0.6 3.3 ± 0.7 P = 0.015
* (1 = minimum, 5 = maximum)
** Independent samples T test.
The scores reflecting students' perceptions on statements regarding the discussion of learning objectives during the reporting phase of a PBL session, ranged between 3.2–3.7 out of five. First-year students' average scores on the depth of discussion were higher than those of third-year students' (p = 0. 000) (Table 2).
Table 2 First and third-year students' average scores on discussion during reporting phase
Titles First-year students' average score* ± SD Third-year students' average score* ± SD Statistical analysis**
Breadth of discussion 3.3 ± 0.8 3.2 ± 0.9 P = 0.345
Depth of discussion 3.7 ± 0.7 3.4 ± 0.8 P = 0.000
* (1 = minimum, 5 = maximum)
** Independent samples T test.
The effects of learning issue driven searching, extensiveness of searching and explanation oriented preparing on the breadth and depth of discussion were analysed with regression analysis (Table 3).
Table 3 The effects of the independent variables on the breadth and depth of discussion (Multiple Regression Analysis)
R2 β t F
Dependent variable: Breadth of discussion
Searching process
Learning issue driven searching 0.21 2.97*
Extensiveness of searching 0.07 0.96
Preparing process 0.09 6.976*
Explanation-oriented preparing 0.14 1.89*
Dependent variable: Depth of discussion
Searching process
Learning issue driven searching 0.26 3.87*
Extensiveness of searching -0.07 -1.08
Preparing process 0.15 12.377*
Explanation-oriented preparing 0.26 3.87*
*p < 0.05
The 9% change in the breadth of discussion was explained with searching and preparing phases. Learning issue driven searching with the highest β value was the most important and statistically significant factor influencing the breadth of discussion. The impact of explanation oriented preparing on the breadth of discussion was also statistically significant (Table 3).
The 15% change in the depth of discussion was explained with searching and preparing phases. It was found that learning issue driven searching and explanation oriented preparing were the most important and statistically significant factors influencing the depth of discussion. The extensiveness of searching had a statistically insignificant negative effect on the depth of discussion (Table 3).
Regression analysis was separately carried out for both classes. Excluding the extensiveness of searching, other findings were similar. Extensiveness of searching had a statistically negative effect on the depth of discussion among first-year students (β = -0.28, t = -2.680, p = 0.009), but a positive effect among third-year students (β = 136, t = 2.198, p = 0.030).
Discussion
A probable explanation for the relative shortness of third-year students' self-study times compared with those of first-year students' was third-year students' mental weariness due to continuous and intensive effort in reaching learning objectives. Another probable explanation was first-year students' slowness in accessing appropriate resources due to their lack of familiarity with self-directed learning.
It was found that first and third-year students frequently used lecture handouts. The reasons for the high frequency of use of handouts were considered as their wide availability due to their provision at the end of lectures that are limited to one hour a day. In order not to hinder the curiosity of students and their motivation for self-directed learning, handouts are designed as brief outlines prepared by lecturers and include topic titles, schemata, algorithms and tables.
Since the Learning Resources Centre was inaugurated in 2001, third year students could only use it during their second and third years, whereas first-year students started using it since the beginning of their medical education. More frequent use of Learning Resources Centre CDs by first-year students may be related to their early encounter with these learning facilities.
Third-year students' more frequent use of textbooks may reflect the development of their ability in reaching essential resources.
Third-year students' higher ratings for learning issue driven searching and extensiveness of searching are consistent with the general expectation stating that experienced students can search more learning resources [4]
The first-year students attributed higher scores to statements regarding explanation oriented preparing (Table 1). This finding may be explained with third-year students' mental weariness due to continuous and intensive efforts since the beginning of their medical education or first-year students' eagerness to adapt to a new educational system.
In the Maastricht study, first-year students' average scores for learning issue driven searching, extensiveness of searching and explanation oriented searching were 3.1 ± 0.3, 2.8 ± 0.4 and 3.2 ± 0.3 respectively [6].
The scores of the entire study group attributed to breadth and depth of discussion during the reporting phase varied between 3.2 ± 0.9 and 3.7 ± 0.7. Although third-year students were expected to become more competent in PBL discussions, third-year students' scores, especially the ones attributed to the depth of discussion, were lower than those of first-year students' (Table 2). This finding is consistent with Cohen's view that the students who gain experience in cooperative study are inclined to limit their efforts to share and explain the information they gather [9]. Higher scores of first-year students on the depth of discussion may also be interpreted as a reflection of their adaptation to the PBL system. In the Maastricht study, average scores attributed by first-year students to the breadth and depth of discussion were 3.0 ± 0.4 and 3.4 ± 0.5 respectively [6]
The results of this study showed that the breadth of discussion during reporting phase was affected by the searching and preparing phases of the self-study process. Similarly, it was understood that the depth of discussion during the reporting phase was affected by the searching and preparing phases of self-study process. Learning issue driven searching "using learning objectives as study references" and explanation oriented preparing "studying and summarising learning resources at an appropriate level to be shared with other students during PBL session", directly influenced the breadth and depth of discussion.
It was observed that students' searching of different resources (extensiveness of searching), though not statistically significant, negatively affected the depth of discussion. During a PBL session, in the presence of different resources, in-depth understanding of newly acquired information requires a well-structured discussion. This may be difficult for first-year students due to their lack of familiarity with PBL and self-directed learning. In the group session, first-year students may encounter difficulties while tutoring a discussion based on several resources [6]. When regression analysis was separately carried out for both classes, it was observed that extensiveness of searching had a statistically negative effect on the depth of discussion among first-year students, but a positive effect among third-year students. These findings imply that the increase in students' PBL experience paralleled the development of their discussion skills using different learning resources.
The design of the present study based on students' perceptions was its main limitation. The assumptions regarding the causes of differences between first and third-year students' perceptions were based on the PBL experience of authors.
Conclusions
First-year students' longer self-study times, higher explanation oriented preparing scores, and higher depth of discussion scores compared with the scores of third-year students were considered as research questions which need to be investigated in future studies.
Competing interests
None declared.
Authors' contributions
BM carried out research design, statistical data analysis, data evaluation, research report, YG carried out research design, data evaluation, research report, HCT carried out data evaluation and research report, SO carried out data evaluation and contributed to the research report, AT contributed to research design, data collection and data evaluation. All authors read and approved the final manuscript.
List of abbreviations
DEUSM: Dokuz Eylul School of Medicine
PBL: Problem-based Learning
Appendix
Self-study and Reporting Processes Questionnaire
Year: 1 □ 3 □
• What is your weekly average study time in a two-week module?
(..............) hours.
• What kind of resources do you use during your self-study process?
() Textbook () Lecture handouts () Others .....................
() Educational CDs () Medical journals
• Please indicate your level of agreement with the following statements about self-study process, by rating them between 1-to-5.
(1 = totally disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = totally agree)
1 2 3 4 5
Search Phase
Learning Issue Driven Searching
1. I use the learning issues as a starting point for my search and search the resources accordingly.
During studying
2. I always check the learning issues to decide whether I study deep enough.
3. I remain attached to the learning issues.
4. I check the learning issues to decide whether the resources I study fully cover the learning issues.
5. I use the learning issues as a guide while studying the resources step by step.
Extensiveness of searching
6. When searching the resources, I try to evaluate the relevancy of different books with the subject to be studied.
7. When searching the resources, I try to compare different resources about the same subject.
8. I spent a lot of time and effort on searching the resources before I start studying
Preparing phase
Explanation Oriented
9. I study the subjects such that I can explain them without looking at the resources.
10. I study the subjects such that I can comment about the theories being discussed
11. I study such that I can explain the content of the resource in my own words.
12. I study such that I know what needs to be discussed in each learning issue.
13. I study by making summaries of the selected resources.
14. I study by making notes and algorithms.
Reporting Phase
Breadth of Discussion
15. Many different issues/findings are discussed.
16. When a student from the group reaches an information not included in the learning issues explains it to others.
17. The members of the group question different aspects of the resources.
18. Different/contradicting resources are compared.
Depth of Discussion
19. During discussions new concepts are discussed and explained in detail.
20. The issues are discussed in depth.
21. The problems of the scenario are questioned and clarified using the newly learned knowledge.
22. The discussion in the reporting makes very useful contributions to newly learned knowledge in the self-study process.
Pre-publication history
The pre-publication history for this paper can be accessed here:
Acknowledgements
Linda Distlehorst, Chair of Medical Education Department, Southern Illinois School of Medicine, for her review and constructive comments.
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| 15385051 | PMC524374 | CC BY | 2021-01-04 16:30:53 | no | BMC Med Educ. 2004 Sep 22; 4:16 | utf-8 | BMC Med Educ | 2,004 | 10.1186/1472-6920-4-16 | oa_comm |
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RetrovirologyRetrovirology1742-4690BioMed Central London 1742-4690-1-301545390710.1186/1742-4690-1-30ResearchIsolation of suppressor genes that restore retrovirus susceptibility to a virus-resistant cell line Gao Guangxia 12gaogx@sun.im.ac.cnGoff Stephen P 1goff@cancercenter.columbia.edu1 Department of Biochemistry and Molecular Biophysics Howard Hughes Medical Institute Columbia University College of Physicians and Surgeons New York NY 10032, USA2 Institute of Microbiology, Chinese Academy of Sciences, Beijing 100080, China2004 28 9 2004 1 30 30 24 8 2004 28 9 2004 Copyright © 2004 Gao and Goff; licensee BioMed Central Ltd.2004Gao and Goff; 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
Genetic selections in mammalian cell lines have recently been developed for the isolation of mutant cells that are refractory to infection by retroviruses. These selections have been used to recover lines that block early postentry stages of infection, either before reverse transcription or before nuclear entry. The mechanisms of action of these blocks remain unknown.
Results
We have devised a method for the selection of genes from cDNA libraries that suppress the block to virus infection, and so restore virus susceptibility. The protocol involves the transformation of pools of resistant cells by cDNA expression libraries, followed by the selection for rare virus-sensitive cells, using multiple rounds of selection after infection by marked viral vector genomes. The suppressor genes were then recovered from these virus sensitive cells, and their ability to restore virus susceptibility was confirmed by reintroduction of these cDNAs into the resistant line.
Conclusions
The identities of these genes provide insights into the mechanism of virus resistance and will help to define new pathways used during retrovirus infection. The methods for gene isolation developed here will also permit the identification of similar suppressors that modify or override other recently identified virus resistance genes.
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Background
It is becoming increasingly apparent that mammalian cells harbor numerous genes that induce intracellular blocks to retrovirus infection [1,2]. These genes have presumably evolved and been maintained in the genome in response to the pathogenic and lethal consequences of infection, and are now thought to constitute an important part of the host defense against these viruses. Some of the genes and gene products responsible for this resistance have been recently identified, including the Fv1 locus in the mouse, which blocks infection after reverse transcription but before nuclear entry and establishment of the integrated provirus [3]; the APOBEC3G enzyme, which is incorporated into virion particles and catalyzes the destructive deamination of the viral cDNA during reverse transcription [4]; and the TRIM5a protein, which somehow blocks incoming virus soon after entry and prevents the activation of reverse transcription [5]. Others likely remain to be identified.
We have been involved in the development of screens and selections for virus resistance genes, and have isolated mutant cell lines after chemical mutagenesis that are profoundly resistant to retrovirus infection. Two such lines isolated from a parental fibroblast cell line, Rat2 cells, have been characterized in some detail [6]. Mutant line R3-2 exhibited a nearly 1000-fold resistance to infection by genetically marked Moloney murine leukemia virus genomes, and was resistant to pseudotyped viruses utilizing the ecotropic envelope, the amphotropic envelope, or even the VSV G envelope protein. Infection of R3-2 resulted in the normal synthesis of the linear viral DNA by reverse transcription, but circular viral DNAs and integrated proviruses were not generated. The viral DNA was apparently trapped in the cytoplasm in a form that was not readily extracted by conditions that allowed DNA recovery from wild-type infected cells. Mutant line R4-7 exhibited about a 100-fold resistance to infection by M-MuLV, also independent of the envelope mediating entry. Infection of this line was blocked earlier, before the initiation of reverse transcription. Both lines R3-2 and R4-7 were also resistant to infection by pseudotyped HIV-1 viral vectors.
To probe the nature of the blocks in these mutant cell lines, we have sought to identify and characterize suppressor genes that override the restriction exhibited by these cells. To identify such genes, we have developed methodologies that allow for the selection of rare virus-sensitive clones arising after transfer of gene libraries into populations of virus-resistant parents. We here report the isolation of two cDNA constructs that each restore virus sensitivity to the R4-7 mutant cell line. These DNAs constitute valuable tools in the characterization of this line's virus resistance.
Results
Selection for virus-sensitive clones from R4-7 mutant cells expressing cDNAs
The R4-7 mutant cell line is approximately 100-fold resistant to transduction by MuLV-based vectors as compared to wild-type Rat2 cells [6]. To identify genes that could suppress this phenotype and restore virus sensitivity, a protocol involving multiple rounds of selection for virus sensitivity was devised (Fig. 1). First, R4-7 cells were transformed by a library of rat kidney cDNAs expressed from the constitutive CMV promoter. Recipient cells were selected by cotransformation with a DNA expressing puromycin resistance. Five pools of the puromycin-resistant cells were generated and maintained separately, each pool containing more than 1000 independent transformed clones. The expectation was that multiple rounds of selection for virus-sensitive clones would be required to recover such cells, with each round providing at most a 100-fold enrichment.
Figure 1 Flowchart for isolation of cDNAs that suppress virus resistance and restore virus sensitivity to the R4-7 mutant cell line. See text for description.
Four of the pools of transformed cells, with each clone in the pools overexpressing a small number of cDNAs, were sequentially exposed to a series of three genetically marked ecotropic MuLV-based vectors, and the rare successfully infected cells were recovered after each infection by selection for the marker carried by the vector (see Methods). The cells were first exposed to N2 virus, an MuLV vector carrying the neor marker, and infected cells were selected in medium containing G418. These cultures were then expanded and exposed to Eco-TK virus, an MuLV vector carrying the Herpes virus TK gene, and infected cells were selected with HAT medium. These cultures were expanded and finally exposed to Eco-His virus, and infected cells were selected with medium containing histidinol. In all cases, the selecting viral vectors were applied at low multiplicities of infection (MOI) so as not to override the resistance of the parental R4-7 cells, as can happen at high MOI [6]. Individual colonies were recovered after the triple selection.
The number of colonies of infected cells recovered at each stage of the selection was determined for each of the four pools (Table 1). The number of colonies of wild-type Rat2 cells exposed to the virus in parallel was determined for comparison. In each of the first two rounds of selection, the pools of mutant cells yielded about 25-fold fewer transductants than the wild-type control, indicating retention of the resistance in the bulk of the population. In the third round, pools 3 and 4 yielded slightly higher numbers of colonies than the other pools, suggesting possible enrichment for virus sensitive clones, though still less than the wild-type cells. A total of 36 candidate colonies were isolated.
Table 1 Numbers of colonies recovered after each round of infection and selection
Initial Cell Population
Pool 1 Pool 2 Pool 3 Pool 4 Rat2
PuroR colonies after transfection >1000 >1000 >1000 >1000 -
NeoR colonies after N2 virus infection ~400 ~400 ~400 ~400 TMTC
HATR colonies after TK virus infection 100 60 40 30 2000
HisR colonies after His virus infection 3 2 12 19 ~200
VirusS lines by GFP virus susceptibility 0 0 2 4 -
To determine whether any of these candidate clones had become truly virus sensitive, all 36 colonies were individually picked and expanded into larger cultures. These cultures were then tested by infection with Eco-GFP, a virus vector expressing the green fluorescent protein, and the fraction of the cells expressing the marker was determined by inspection. While all the clones from pools 1 and 2 were as resistant as the parental R4-7 line, a total of 6 clones – 2 from pool 3 (dubbed A1, A2) and 4 from pool 4 (dubbed B1, B2, C1, C2) – were fully sensitive to infection. These cloned lines were thus candidates as potentially carrying cDNAs that could restore virus sensitivity to the R4-7 line.
Recovery of cDNAs from virus-sensitive cell lines capable of suppressing virus resistance
To recover the cDNAs present in the virus sensitive cell lines, total genomic DNA was isolated, and polymerase chain reactions were performed to amplify expression cassettes composed of the CMV promoter, the cDNA insert of the library and the poly(A) addition signal. The amplified DNA from each line was directly cloned into the TOPO plasmid DNA and used to transform bacteria. In this way cloned cDNAs were recovered from five of the six lines. Because the lines were expected to each carry a few different cDNAs, and because only one cDNA in each line would be expected to be responsible for the phenotype, a total of 50 bacterial colonies were isolated for each of the five lines. DNAs were prepared from these bacterial colonies and assigned to groups based on the pattern of restriction fragments after produced after digestion with MspI. The number of distinct cDNAs recovered from each of the five lines ranged from 1 to 11, and all together included 29 cDNAs (Table 2).
Table 2 Numbers of cDNAs recovered from VirusS cell lines
Origin of cell lines Total
Pool 3 Pool 3 Pool 4 Pool 4 Pool 4 Pool 4
VirusS cell line A1 A2 B1 B2 C1 C2
Total cDNAs examined 50 50 50 50 50 - 250
Distinct cDNAs 10 2 5 1 11 0 29
Active cDNAs 0 0 1 0 1 0 2
The cDNAs isolated from the virus sensitive lines were then tested directly for their ability to suppress the virus resistance of R4-7 cells. Each cDNA (20 ug) was mixed with pGK-puro DNA (2 ug) and used to transform naive R4-7 cells, and recipients stably expressing the DNAs were selected by growth in puromycin. The resulting puromycin-resistant colonies derived from a given cDNA were pooled and grown into large cultures, and the resulting populations were tested for sensitivity to Eco-neo virus infection. Two of the cDNAs, one from cell line B1 (designated pB1-11) and one from cell line C1 (designated pC1-2), dramatically suppressed the virus resistance of R4-7 cells (Fig. 2). An inactive cDNA retained as a negative control did not suppress the resistance. The susceptibility to infection of the pooled R4-7 transfectants for the two active clones was similar to that of the wild-type Rat2 cells, and roughly 100-fold higher than that of the R4-7 parents. To further document the sensitivity of induced by pC1-2, two individual clones were isolated from the R4-7 populations expressing pC1-2 and a control cDNA, and these clones were similarly tested by infection with Eco-neo virus. Like the pooled populations, the clones expressing pC1-2 were virus-sensitive and the controls were not (Fig. 3). Thus, these cDNAs were sufficient to suppress the resistance, and were likely responsible for the virus sensitivity of the two lines in which they were recovered after the triple selection. The remaining lines had presumably become sensitive to virus independently of any of the cDNAs they carried, or as a result of a cDNA that was not recovered from the PCR amplified DNA products.
Figure 2 Ability of the suppressor cDNAs to restore virus susceptibility to the R4-7 mutant cell line. R4-7 cells were cotransformed with the indicated cDNAs, and the transformants were pooled and grown into cell populations. These cultures were then exposed to equal amounts (approximately 10,000 cfu in NIH/3T3 cells) of an N2 virus preparation, and virus susceptibility was assessed by plating the infected cells in medium containing G418. While the mutant R4-7 control populations yielded only ~50 colonies, the populations expressing the active cDNAs produced nearly confluent lawns. Rat2: virus-sensitive subclone isolated after mutagenesis. R4-7: mutant line. No cDNA: pGKpuro marker DNA alone. Control cDNA: marker plus inactive cDNA. PB1-11, pC1-2: marker plus indicated cDNA.
Figure 3 Restoration of virus susceptibility by pC1-2 DNA in clonal cell lines. Single-cell clones were derived from R4-7 cell populations cotransformed with either inactive control cDNA or pC1-2 DNA. The resulting lines were exposed to N2 virus (approximately 300 cfu in NIH/3T3 cells) and plated in medium containing G418. While the control yielded no colonies, the clonal lines containing pC1-2 showed 100–200 colonies.
Characterization of biologically active suppressor cDNAs
The pB1-11 and pC1-2 DNAs could function as general enhancers of retrovirus infection, or alternatively as specific suppressors of the block in the R4-7 mutant cell line. To distinguish between these possibilities, the DNAs were introduced into the wild-type Rat2 cells, the distinct R3-2 mutant line, and the R4-7 line by cotransformation, and stable transformants were selected and expanded. The resulting transformed lines were then tested for their sensitivity to infection by Eco-Neo virus. The Rat 2 lines expressing pB1-11 showed no change in virus susceptibility, and the Rat2 lines expressing pC1-2 showed at most a 2-fold increase in sensitivity (Fig. 4). The corresponding R3-2 lines gave similar results (data not shown). Thus, both cDNAs were highly specific in enhancing the virus susceptibility of the R4-7 line.
Figure 4 Lack of effect of suppressor cDNAs in wild-type cells. Rat2 or a virus-sensitive subclone isolated after mutagenesis (RC-2) were cotransformed with the indicated DNAs, and the transformants were pooled and grown into cell populations. The resulting cultures were exposed to N2 virus (approximately 300 cfu in NIH/3T3 cells) and plated in medium containing G418. All the cultures yielded approximately equal numbers (~200) of colonies.
The DNA sequences of the two cDNAs were determined and compared with the nucleic acid sequences of the NCBI databases. Clone pB1-11 contained an insert of 855 bp with close sequence similarity to the central portion of a transcript originally termed HCC1.3/1.4, identified as encoding a prominent autoantigen expressed in a human hepatocarcinoma [7]. The similar mouse gene product, dubbed CAPER, was subsequently shown to interact with c-Jun, a subunit of the AP-1 activator, and the estrogen receptors ERa and ERß, and to exhibit transcriptional coactivator activity when expressed in concert with these transcription factors [8]. The cDNA insert of pB1-11 aligned well with both the human sequences (92% identity match to bp 910–1767 of HCC1.4 (Genbank accession no. L10911)) and the mouse sequences (94% identity match to bp 1153–2006 of CAPER (accession no. AY061882)). Remarkably, the cDNA fragment was inserted in reverse orientation relative to the CMV promoter of the pcDNAI plasmid vector [9], and thus the active DNA would produce an antisense mRNA transcript.
Clone pC1-2 proved to contain an insert of 1407 bp, with close sequence similarity to a central portion of the VL30 elements, a family of endogenous retrovirus-like elements widely expressed in many mouse [10-14] and Rat cell lines [15,16]. The pC1-2 sequences aligned best with particular Rat elements expressed in tumor cells (~88% identity to bp 5025–6151 of a 7.4-kb element [17]; Genbank accession no. D90005) and in the ovary (~90% identity to bp 3341–4677 of a 5.5-kb element [18]; Genbank accession no. U48828). There was weaker similarity to related retroviruses, such as the gibbon ape leukemia virus [19]. The insert was in the sense orientation relative to the CMV promoter, and if transcribed would result in formation of a plus strand RNA, corresponding to the central portion of the VL30 transcripts. Like most rat VL30 elements, the insert did not include any significant open reading frames, but rather contained numerous mutations that introduced frameshifts and stop codons that would preclude synthesis of any long protein products. These results suggest that both of the pB1-11 and pC1-2 DNAs might function by virtue of their RNA products rather than any encoded proteins. The sequences of the two inserts have been submitted to the NCBI database (pB1-11 accession number is AY769432; pC 1-2 accession number is AY769433; see figure 5).
Expression of CAPER and VL30 RNAs in R4-7 mutant line
The biological activity of the pB1-11 and pC1-2 DNAs in restoring virus susceptibility could be mediated through effects on their corresponding endogenous gene products expressed in the R4-7 mutant cell line, or could be indirect. If their activity was direct, then either one of the corresponding endogenous genes – the CAPER gene or a VL30 element – might be the locus that was originally mutated to give rise to the resistance of the R4-7 line. To examine this possibility, RNAs were prepared from R4-7 and wild-type cells, and analyzed by Northern blot. Hybridizing with the pB1-11 probe showed a single major RNA about 3 kb in length in both lines, with no significant change in level detected (Fig. 6). Hybridization with the pC1-2 probe showed an intense smear of RNAs in both lines as typically seen for VL30 RNAs (data not shown). No differences between the lines was apparent.
Figure 6 Northern blot analysis of mRNAs in parental Rat2 and mutant R4-7 cell lines. RNA preparations from the indicated cells were separated, blotted, and hybridized with a 32P-labeled pB1-11 probe. The major mRNA at ~3.0 kb is indicated. The position of the 28S and 18S rRNA markers are indicated on the left.
Although the levels of the CAPER mRNA was not detectably altered in the R4-7 line, it remained possible that the gene and its transcripts harbored point mutations that were responsible for the virus resistance. To test this possibility, CAPER cDNAs were isolated from the R4-7 and Rat2 cells by RT-PCR, and the amplified sequences were cloned into the TOPO vector. Ten cDNA clones from each line were recovered and sequenced. Clones of three distinct structures were recovered from each line, likely arising by alternative splicing, but the sequences of the corresponding clones from the two lines were identical (data not shown). These results suggest that the CAPER gene is likely not mutated in the R4-7 line. Nevertheless, to test whether any of these cDNAs could alter virus susceptibility, the cDNA inserts from both R4-7 and Rat2 cells were transferred into the expression vector pcDNA3.1/zeo (see Methods). Overexpression of the various CAPER cDNAs from the Rat2 cells in R4-7 cells did not restore virus susceptibility, and overexpression of the corresponding cDNAs from the R4-7 cells did not induce virus resistance. Thus, of the various CAPER expression constructs, only the original pB1-11 antisense DNA had biological activity.
Discussion
The results here document the development of an effective procedure for the isolation of cDNAs that allow virus infection of virus-resistant cells. The key feature is the repeated infection of the parental resistant line with viral vectors carrying distinct selectable markers, and has become possible only with the development of a multitude of such markers. In this way, rare susceptible cells in the R4-7 population are enriched by as much as 10 to 100 fold in each round of selection. The protocol should allow the recovery of DNAs that confer susceptibility from any large library, if present at an abundance of perhaps at least one in 106 clones. The system can only work if a single DNA is sufficient to enhance virus susceptibility. Once cell lines with restored virus sensitivity were isolated, the recovery of the cDNAs from genomic DNA and the screening for active clones were relatively straightforward.
The identities of the two sequences in the active cDNAs isolated here were surprising and the mechanisms of action of the two distinct clones remains mysterious. Both are highly potent, restoring virus susceptibility essentially to wild-type levels (figure 2). The time of the block to replication in the R4-7 line that is overcome by these two DNAs is very early after virus entry, before the initiation of reverse transcription by the incoming virus [6]. One possibility is that the mutant line fails to uncoat the virions sufficiently to allow deoxyribonucleotides into the core. In this scenario the cDNAs would somehow facilitate the uncoating process or inhibit a block to uncoating.
HCC1.3 and HCC1.4 are two closely related cDNAs first recovered from a patient with hepatocellular carcinoma [7]. The encoded protein was a prominent nuclear autoantigen. The deduced amino acid sequences contain an arginine/serine rich domain and three ribonucleoprotein consensus sequence domains, often found in RNA splicing factors; they show weak homology to S. pombe GAR2, a nuclear protein. A later report demonstrated that the gene product interacted with the transcriptional activators AP-1 and the estrogen receptors ERa and ERß, and had potent cotransactivation activity; the gene was renamed CAPER, for coactivator of AP-1 and ER [8]. The antisense orientation of the pB1-11 cDNA suggests that its mechanism of action might be to lower the level of the endogenous sense mRNAs and the encoded proteins produced from the CAPER gene. We were unable to directly assess the level of the mRNAs in the presence of the antisense cDNA by Northern blots because the level of expression of the antisense RNA was so much higher than the endogenous mRNA that these transcripts were obscured. However, it is possible that the reduction in levels of a protein factor involved in regulation of transcription could elicit profound changes in the patterns of gene expression in the cell. We cannot rule out the remote possibility that a cryptic promoter results in some production of sense mRNA, and a protein fragment with biological activity, from the pB1-11 cDNA.
Whatever the mechanism of action of the pB1-11 cDNA, it is unlikely that the endogenous CAPER gene is the locus of the original virus resistance mutation in the R4-7 line. The levels of the major mRNA are similar in the mutant and the wild-type parent (Fig. 6), and sequence analysis of a variety of cDNAs from parent and mutant lines did not uncover any mutations. Further, the overexpression of the CAPER cDNAs from R4-7 did not cause resistance, and the overexpression of the wild-type CAPER cDNA did not suppress the resistance. Rather, the antisense cDNA must correct the phenotype indirectly, likely through effects on gene expression. The localization of the HCC1.3/1.4 or CAPER protein in the nucleus [7] rather than at the site of virus arrest also suggests that its mechanism is indirect. Possibly CAPER acts to maintain a program of cytoplasmic protein expression that blocks virus infection in the R4-7 mutant line.
Figure 5 Sequence alignment of pB1-11 and pC1-2 DNA inserts with similar sequences from NCBI database. The insert of pB1-11 (855 bp) is an antisense sequence match to the central portion of the CAPER mRNA [8], and that of pC1-2 (1407 bp) is a sense sequence match to a portion of the VL30 endogenous retrovirus-like element [17].
The VL30 elements are a very large family of endogenous virus-like genes found in both mouse and rat genomes [10-14]. The various elements are dispersed and have significantly divergent sequences. Though gag- and pol-related sequences are often recognizable, nearly all the elements are grossly defective, with multiple frameshift and premature termination mutations interrupting the open reading frames. In addition, the majority of the elements have suffered deletions of various regions relative to the longer family members. Thus, while many of the elements are highly transcribed in rodent cell lines, very few of the transcripts code for protein products of significant length. However, the VL30 RNAs often contain recognition elements for packaging into virion particles encoded by murine leukemia viruses, signals for initiation of DNA synthesis and strong stop DNA translocation, and termini recognized by viral integrase proteins, and thus are competent for transfer by replication-competent viruses acting as helpers.
The sequence of the insert in pC1-2 corresponds to a portion of the retroviral pol gene, specifically the integrase coding region, but is typical of the VL30s in containing no long ORF; furthermore, known cis-acting regions needed for replication are absent. We suppose that the RNA itself may be responsible for the activity, perhaps by binding some cellular protein. The region of the VL30 genome present in pC1-2 – the 3' portion of the pol gene – is not known to contain a binding site for any particular protein. The corresponding region of replication-competent viruses, however, would normally contain the splice acceptor site for the envelope mRNA. Although many VL30 elements do not contain env genes, and although the splice acceptor sites are not readily apparent in the pC1-2 sequence, the transcript might be hypothesized to bind splicing machinery. In this scenario, a possible mechanism of action of the clone is for the overexpressed RNA to bind up a splicing factor or other RNA binding protein, titering out the free protein and removing it from solution. If this factor were responsible for the viral resistance of the R4-7, either directly or indirectly, the binding might relieve that block. The mechanism would be surprising only because the endogenous VL30 RNAs are already so abundant in Rat2 cells, and they are not able to suppress the block to infection. However, the pC1-2 sequence must be an unusual element, in that some distinctive aspect of its sequence must be responsible for its peculiar biological activity. Perhaps identifying proteins that bind to the pC1-2 transcript would be informative.
The mechanism of resistance exhibited by the R4-7 line remains uncertain. The block is early but likely not at virus entry: it occurs whether ecotropic envelope, amphotropic envelope, or even the VSV G protein is used for entry [6]. Further, the block is unlikely to involve VSV G function, since the cells are susceptible to infection by VSV itself (J.-W. Carroll and M. MacDonald, Rockefeller University, unpublished observation). The early block occurs at a similar stage of infection – before reverse transcription – as the dominant block induced by TRIM5a, a gene responsible for retrovirus resistance in primates [5]. There are no other indications, however, that the two blocks are related. We have observed that the R4-7 cells exhibit a slightly different morphology than the parental Rat2 cells, being somewhat more rounded and more easily detached from the substrate during trypsinization. This phenotype could in principle be unrelated to the virus resistance, since the cells were subjected to heavy chemical mutagenesis before their isolation [6]. However, the R4-7 cells expressing both pB1-11 and pC1-2 were restored to a flatter morphology, much closer to that of the parental line, suggesting that the two phenotypes may be causally linked. If this notion is correct, changes in the cytoskeleton may be involved in the resistance. Further analysis of the R4-7 cells by gene expression profiling may help reveal the basis for its behaviors.
Conclusions
The power of genetic selections in mammalian cells for alterations in virus susceptibility is increasing rapidly. We believe that selections like the one devised here will be applicable to the isolation of suppressors of other blocks to infection, including the prototypical Fv1 gene [3], the APOBEC3G cytosine deaminase [4], and the TRIM5a gene [5]. The identity of such suppressors may provide important clues into the mechanism of their action and regulation.
Methods
Cell lines, cell culture
The Rat2 cell line is a TK-negative fibroblast line that is highly sensitive to MuLV infection. RC-2 is a subclone isolated after mutagen exposure but also sensitive to virus, and was used in many experiments as a wild-type control line. Lines R3-2 and R4-7 are virus-resistant mutants of Rat2 isolated after exposure to ICR-191 [6]. 293T cells are human embryonic kidney cells transformed by adenovirus E1 and also expressing SV40 T antigen. All these lines were maintained in DMEM with 10% fetal calf serum.
DNA transformations
A rat kidney cDNA library in the pcDNAI vector [9] was purchased from Invitrogen (Carlsbad, CA). To increase the library transfection efficiency and maximize the integrity of the cDNAs, the library was digested in the vector sequence with the restriction enzyme SfiI and then religated. R4-7 cells in ten 10-cm dishes were cotransformed with 20 ug of the religated library DNA and 2 ug of pGK-puro plasmid by calcium phosphate-mediated transformation. Cells expressing transformed DNAs were selected by growth in culture medium containing 5 ug/ml puromycin. Each transformed cell was expected to receive about 2–10 different cDNAs. The cultures were expanded before the selections for virus susceptibility such that a pool of 105 cells contained about 2000 distinct puromycin resistant clones. Thus, there were about 50 sibling cells of each transformant in the pools at the time of selection for virus susceptibility.
Retrovirus preparations
Eco-neo or MuLV-N2 virus [20]; Eco-TK virus, and Eco-GFP virus [21] were as previously described [6]. To generate Eco-His virus, the Neo resistance gene in the N2 vector was replaced with His resistance gene, and GP+E86 packaging cells [22] were stably transformed with the resulting vector DNA. Recipients were selected with histidinol and the resistant cells were pooled to generate Eco-His producer cells. Typical titers of the virus preparations on Rat2 cells were 107 cfu/ml for N2 virus; 2 × 104 for TK virus; 2 × 106 for Eco-His virus; and 105 cfu/ml for Eco-GFP virus.
Viral transduction and selection
Selections for virus sensitive cells were performed by infecting approximately 105 R4-7 cells per 10-cm dish in each round, with virus titers determined by infection of Rat2 cells. In the first round approximately 104 cfu of N2 virus were applied, and transductants were selected with 800 ug/ml G418. In the second round, approximately 2 × 103 cfu of Eco-TK virus were used, and transductants were selected with HAT medium (Gibco). In the third round, approximately 200 cfu of Eco-His virus were applied, and transductants were selected with medium containing 1 mg/ml histidinol. The multiplicities of all these infections with the selecting viruses were kept low, at less than 0.1 These low MOIs were required because infection of R4-7 cells at high MOI can override the block, perhaps by saturation of a titratable factor. Even at this low MOI, the presence of many siblings of each transformant implied that most cDNAs in the pool were tested for inducing virus susceptibility.
Polymerase chain reactions
cDNA inserts from the expression library were recovered from cell lines by PCR as follows. Genomic DNA was extracted (DNAeasy kit, Qiagen) and subjected to PCR with primers hybridizing upstream from the CMV promoter (sequence 5'-GGGCCAGATATACGCGTT-3') and downstream from the poly(A) addition region (sequence 5'-AATTTGTGATGCTAT-3') of the pcDNAI vector. Conditions for the PCR were: ten cycles of 94°C for 10 sec, 55°C for 30 sec, and 68°C for 3 min, followed by 20 cycles of the same conditions but with an increase in the polymerase reaction time of 5 sec in each cycle. The amplified DNAs were cloned directly into the TOPO vector (Invitrogen) and used to transform DH10b bacteria to ampicillin resistance. DNAs were isolated from approximately fifty bacterial colonies for each original cell line.
CAPER cDNAs were prepared from RC-2 mRNA preparations by standard RT-PCR methods using primers spanning the entire ORF (sequences: 5'-ATATAGCTTAAGGCCACCATGGCAGACGATATTGATAT-3' and 5'-ATATAGGCGGCCGCTCATCGTCTACTTGGAAC-3'), and cloned into the pcDNA3.1/zeo expression plasmid using AflII and NotI restriction sites.
Authors' contributions
GG carried out all the experiments and participated in their design. SPG participated in the experimental design and drafted the manuscript. Both authors read and approved the final manuscript.
Acknowledgements
This work is supported in part by grants to GG from the Ministry of Science and Technology of China (2002AA222041) and CAS Knowledge Innovation Projects (KSCX2-SW-216); and to SPG from the NCI (R01 CA30488). SPG is an Investigator of the Howard Hughes Medical Institute.
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| 15453907 | PMC524375 | CC BY | 2021-01-04 16:36:37 | no | Retrovirology. 2004 Sep 28; 1:30 | utf-8 | Retrovirology | 2,004 | 10.1186/1742-4690-1-30 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1552605810.1371/journal.pmed.0010033Research ArticleInfectious DiseasesMalariaA Randomised, Double-Blind, Controlled Vaccine Efficacy Trial of DNA/MVA ME-TRAP Against Malaria Infection in Gambian Adults Efficacy of DNA/MVA ME-TRAP in GambiansMoorthy Vasee S
1
2
*Imoukhuede Egeruan B
1
Milligan Paul
1
Bojang Kalifa
1
Keating Sheila
2
Kaye Pauline
1
Pinder Margaret
1
Gilbert Sarah C
3
Walraven Gijs
1
Greenwood Brian M
4
Hill Adrian S. V
2
3
1Medical Research Council LaboratoriesBanjulGambia2Centre for Clinical Vaccinology and Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Churchill HospitalOxfordUnited Kingdom3Wellcome Trust Centre for Human Genetics, University of OxfordOxfordUnited Kingdom4London School of Hygiene and Tropical MedicineLondonUnited KingdomKoech Davy Academic EditorKenya Medical Research InstituteKenya
Competing Interests: VSM, EBI, PM, KB, SK, PK, MP, SCG, GW, and BMG have declared that no competing interests exist. AVSH is a co-founder and equity holder in Oxxon Therapeutics, a company developing prime-boost therapeutic vaccines.
Author Contributions: See Acknowledgments.
*To whom correspondence should be addressed. E-mail: vmoorthy@malariavaccine.org11 2004 26 10 2004 1 2 e3313 7 2004 31 8 2004 Copyright: © 2004 Moorthy 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.
Malaria Vaccine Trial Results Are Negative, but Important
Background
Many malaria vaccines are currently in development, although very few have been evaluated for efficacy in the field. Plasmodium falciparum multiple epitope (ME)– thrombospondin-related adhesion protein (TRAP) candidate vaccines are designed to potently induce effector T cells and so are a departure from earlier malaria vaccines evaluated in the field in terms of their mechanism of action. ME-TRAP vaccines encode a polyepitope string and the TRAP sporozoite antigen. Two vaccine vectors encoding ME-TRAP, plasmid DNA and modified vaccinia virus Ankara (MVA), when used sequentially in a prime-boost immunisation regime, induce high frequencies of effector T cells and partial protection, manifest as delay in time to parasitaemia, in a clinical challenge model.
Methods and Findings
A total of 372 Gambian men aged 15–45 y were randomised to receive either DNA ME-TRAP followed by MVA ME-TRAP or rabies vaccine (control). Of these men, 296 received three doses of vaccine timed to coincide with the beginning of the transmission season (141 in the DNA/MVA group and 155 in the rabies group) and were followed up. Volunteers were given sulphadoxine/pyrimethamine 2 wk before the final vaccination. Blood smears were collected weekly for 11 wk and whenever a volunteer developed symptoms compatible with malaria during the transmission season. The primary endpoint was time to first infection with asexual P. falciparum. Analysis was per protocol.
DNA ME-TRAP and MVA ME-TRAP were safe and well-tolerated. Effector T cell responses to a non-vaccine strain of TRAP were 50-fold higher postvaccination in the malaria vaccine group than in the rabies vaccine group. Vaccine efficacy, adjusted for confounding factors, was 10.3% (95% confidence interval, −22% to +34%; p = 0.49). Incidence of malaria infection decreased with increasing age and was associated with ethnicity.
Conclusions
DNA/MVA heterologous prime-boost vaccination is safe and highly immunogenic for effector T cell induction in a malaria-endemic area. But despite having produced a substantial reduction in liver-stage parasites in challenge studies of non-immune volunteers, this first generation T cell–inducing vaccine was ineffective at reducing the natural infection rate in semi-immune African adults.
Inducing an immune response is just one part of what a vaccine needs to do before it will protect against episodes of malaria.
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Introduction
The disease burden of malaria has increased in recent years partly because of the rise of drug-resistant Plasmodium falciparum parasites [1] and insecticide-resistant Anopheline spp. vectors [2]. There is an urgent need for effective malaria control methods to reduce mortality and morbidity from malaria in endemic countries. Detailed analysis of immunological mechanisms of immunity against malaria in humans and experimental animals has indicated a likely protective role for T cell responses against the liver stages of P. falciparum [3,4,5,6,7,8,9]. Comparison of a variety of means of immunisation to induce protective T cell responses in animal models has identified heterologous prime-boost immunisation, i.e., sequential immunisation with two different vaccines with the same recombinant DNA sequence, as a particularly effective approach [10,11]. DNA and viral vaccines recombinant for a malarial DNA sequence known as multiple epitope (ME)–thrombospondin-related adhesion protein (TRAP), which were designed to induce protective immunogenicity against liver-stage P. falciparum malaria, were manufactured to explore this approach [12]. γ-interferon T cell responses to ME and TRAP peptides were associated with protection from severe malarial anaemia in a prospective study of Kenyan children [13].
DNA and modified vaccinia virus Ankara (MVA)'s excellent safety profiles in malaria-naïve and semi-immune volunteers have been discussed previously [12]. In several studies, prime-boost immunisation (usually with DNA/MVA) has been highly immunogenic for CD4+ and CD8+ T cell induction against infectious pathogens and cancers in both murine and nonhuman primate studies [14,15,16,17,18,19]. DNA/MVA vaccination was protective 7 mo after vaccination in an HIV macaque model [20].
Priming with three 2-mg intramuscular DNA ME-TRAP vaccinations at 3-wk intervals, followed by boosting with one intradermal MVA ME-TRAP vaccination of 1.5 × 108 plaque-forming units, produced very strong vaccine-induced CD4+ and CD8+ T cell responses in previous phase I studies in the United Kingdom [21]. The immunogenicity of two DNA ME-TRAP primes followed by one MVA ME-TRAP boost at these doses is similarly high in both the United Kingdom (S. Dunachie and A. V. S. Hill, unpublished data) and Gambia [22]. DNA ME-TRAP/MVA ME-TRAP regimens led to a delay in time to parasitaemia compared to unvaccinated controls after high-dose heterologous sporozoite challenge of malaria-naïve individuals [21].
To follow up these encouraging findings in volunteers, we have conducted a randomised, controlled trial of DNA ME-TRAP/MVA ME-TRAP in a rural part of Gambia to explore whether this vaccine combination could provide protection against natural P. falciparum infection. We chose a two-DNA prime, one-MVA boost regimen with 3-wk between doses because this is a three-dose regimen that would be amenable to integration with the World Health Organization/United Nations Children's Fund Expanded Program on Immunization, with the necessary supporting safety and immunogenicity data both from adults in the United Kingdom and Gambia. We used 3-wk intervals because 4-wk intervals had not been evaluated in phase I trials previously, hence bridging studies would be necessary to bridge to the three-dose, 4-wk interval Expanded Program on Immunization schedule.
Methods
Vaccines
The malarial DNA sequence is known as ME-TRAP. The ME string contains 14 CD8+ T cell epitopes, one CD4+ T cell epitope, and two B cell epitopes from six pre-erythrocytic P. falciparum antigens. It also contains two non-malarial CD4+ T cell epitopes [23]. The ME string is fused in frame to the entire T9/96 strain of P. falciparum TRAP [10,24,25]. The individual epitopes making up the ME string are described in detail elsewhere [23]. The strain of P. falciparum used to produce the vaccine construct is T9/96. The candidate malaria vaccines were manufactured to Good Manufacturing Practice by contract manufacturers (DNA ME-TRAP by Qiagen, Hilden, Germany; MVA ME-TRAP by IDT, Rosslau, Germany). DNA ME-TRAP was supplied as a single dose of2 mg in 2-ml vials. MVA ME-TRAP was supplied as two-dose vials, each containing 3 × 108 plaque-forming units in 0.8 ml. The rabies vaccine (Chiron Behring, Marburg, Germany) was supplied as a lyophilised single-dose vial with accompanying diluent and syringe. This vaccine was chosen because of its public health benefit in Gambia.
Study Setting and Volunteers
Approval was obtained from the Joint Gambian Government/Medical Research Council Ethics Committee, the Oxford Tropical Research Ethics Committee, and the London School of Hygiene and Tropical Medicine Ethics Committee. An independent Data and Safety Monitoring Board provided oversight for the trial. In addition, independent clinical trial monitors monitored the trial for adherence to International Committee on Harmonisation Good Clinical Practice guidelines.
Malaria incidence is highly seasonal in Gambia. The climate is typical of sub-Sahelian Africa, with a long dry season followed by a relatively short rainy season from July to October. Rainfall averages about 600 mm per year. Morbidity and mortality from malaria both occur more frequently during the rainy season. However, in 2002, Gambia experienced a drought, and the malaria season was delayed, with few disease episodes before October. The entomological inoculation rate varies between less than 1 and greater than 100 in Gambia [26]. Based on previous years' data, we assumed that the average cumulative incidence over a number of years would be about 60% (interquartile range [IQR], 50%–70%), with very few years with incidence less than 40% or more than 90%. Allowing for 15% loss to follow-up, and using a significance level of 0.05, the median power of a study with 372 participants would be 90% (95% confidence interval [CI], 69%–98%) if the vaccine efficacy were 40%. Volunteers were recruited from 13 villages in the North Bank Division of Gambia in July 2002 with follow-up to December 2002 [26]. The villages were chosen for proximity to the alluvial flood plain. A strong association between proximity to the flood plain and entomological inoculation rate has been seen in this part of Gambia [27], and the entomological inoculation rate in the study area is likely to have been in the range of 10–20 infectious bites per year.
Before recruitment, meetings were held with village heads and elders, followed by general village meetings at which the study was explained. Volunteers received information sheets and consent forms translated into the three local languages in Arabic script, as well as in English. After written informed consent was obtained by a study physician, age and identity were checked, pre-test HIV counselling occurred, and potential volunteers underwent clinical evaluation, including a full medical history and clinical examination. They were screened for haematological (full blood count), renal (plasma creatinine), and hepatic (plasma alanine aminotransferase [ALT]) dysfunction, and duplicate malaria smears were made. Exclusion criteria included any chronic illness detected by clinical evaluation, ALT greater than 42 (international units/litre), creatinine greater than 130 (micromoles/litre), packed cell volume less than 30%, positive antibody ELISA to HIV-1 or HIV-2, simultaneous participation in another clinical trial, blood transfusion in the month prior to vaccination, previous experimental malaria vaccination, administration of another vaccine within 2 wk of vaccination, previous rabies vaccination, allergy to any previous vaccine or to sulphadoxine/pyrimethamine, history of splenectomy, and any treatment with immunosuppressive drugs. Eligible volunteers were given a unique study number and a photographic identity card. Parental written informed consent was obtained for volunteers aged 15–17 y.
Procedures
A member of the Data and Safety Monitoring Board generated and held the randomisation code that associated each study number with a specific vaccine. A blocking procedure was used, and whole villages were enrolled with sequential study numbers to ensure balanced numbers in each group. During the course of the study investigators and volunteers did not know the size of the blocks, nor were they aware of which vaccine preparation was administered to a particular volunteer. Opaque sealed envelopes were used for vaccine allocation. Study numbers were not preprinted on vials but were written on vials at vaccination. Used vials were checked for correct allocation off-site. Vaccination was performed by nurses who played no other part in the trial.
Volunteers were randomly assigned to receive either (1) two 2-mg doses of DNA ME-TRAP followed by a single 1.5 × 108-plaque-forming-units dose of MVA ME-TRAP or (2) three doses of rabies vaccine; injections were given on days 0, 21, and 42, timed to coincide with the start of the rainy season. The first two doses of vaccine consisted of two intramuscular injections, one into each deltoid muscle. DNA ME-TRAP was given as 1 ml and rabies vaccine as 0.5 ml into each arm. The third dose of vaccine was given as four intradermal injections into the skin overlying the deltoid muscle, with two injections into each arm. The malaria vaccine group received MVA ME-TRAP as four 0.1-ml injections, whereas the control group received four 0.05-ml injections of rabies vaccine. Two weeks before administration of the third dose, all volunteers received three tablets of sulphadoxine/pyrimethamine to clear blood-stage P. falciparum infections [23].
After each vaccination volunteers were observed for 1 h and visited at home on the first, second, and seventh day postvaccination for assessment of local adverse events (discolouration, induration, blister formation, pain, or limitation of arm motion), systemic adverse events (headache, nausea, malaise, or elevated axillary temperature), and unsolicited adverse events. One week and 13 wk after the third vaccination, venous blood was collected for repeated measurement of full blood count, ALT, and creatinine.
Since vaccination with MVA causes a characteristic local reactogenicity in some subjects, specific steps were taken to ensure that the participants were evaluated in a double-blinded manner. Field workers who assessed reactogenicity after the third dose were different from those who undertook surveillance during the parasitological follow-up period. During the surveillance period, starting 2 wk after the third dose of vaccine, volunteers were visited twice weekly and asked whether they had attended a health centre. At weekly visits blood smears and axillary temperatures were taken. At midweek visits, blood smears and temperature were taken if symptoms compatible with malaria were present. Investigators and field supervisors made random visits to ensure accurate data collection. This active case detection was supplemented by passive case detection by study nurses to whom volunteers had 24-h access at three of the study villages and by a clinic at Medical Research Council Farafenni (20 km from the study villages). Symptomatic malaria was defined as the presence of asexual P. falciparum parasites at any parasitaemia with either an axillary temperature of 37.5 °C or more or one or more of the following symptoms: headache, myalgia, arthralgia, malaise, nausea, dizziness, or abdominal pain.
When blood smears were obtained, two sets of duplicate blood smears (four smears in total) were made. A Field's stain was performed on films obtained from subjects with possible clinical malaria and the films read immediately. Two further smears (“A” and “B” slides) were stained with Giemsa after overnight drying; 100 high-power fields were read by two slide readers before a film was declared negative. The presence of P. falciparum parasites was confirmed by a supervisor before a slide was declared positive. The arithmetic mean of the A and B slides was used to determine parasite density. If parasite densities for A and B slides were markedly discrepant, a third read was performed by the supervisor and this read was used for analysis. Parasite density was expressed per microlitre (assuming one parasite per high power field equals 500 parasites/μl). Full blood counts were performed and packed cell volumes were measured in a CA620 cell analyser (Medonic, Stockholm, Sweden). ALT (international units/litre) and creatinine (micromoles/litre) were measured in a Visual analyser (bioMérieux, Craponne, France).
Effector T cell responses were assessed in ex vivo γ-interferon enzyme-linked immunospot (ELISPOT) assays for 98 volunteers randomly selected from a substudy list containing a 3:1 ratio of participants receiving malaria vaccines to participants receiving rabies (control) vaccines. For this assay, 4 × 105 peripheral blood mononuclear cells (PBMCs) were assayed as described [28], using Millipore (Billerica, Massachusetts, United States) MAIP S45 plates for 18–20 h before being developed. Mabtech (Stockholm, Sweden) antibodies were used, and counting of spots was performed blinded to vaccine allocation with the AutoImmun Diagnostika (Strassberg, Germany) computerised system. All peptides were at 25 μg/ml concentration. A single pool contained all ME peptides. Four pools each were used of 20-mer peptides, overlapping by ten amino acids, to span the entire TRAP antigen of the T9/96 and 3D7 strains of P. falciparum.
Statistical Analysis
An analysis plan, written before unblinding, specified exclusion criteria, statistical methods, and important covariates (age, village of residence, and bednet use [defined as sleeping nightly under an intact or impregnated bednet]). Ethnic group, though not specified as a covariate in the analysis plan, was found on analysis to be associated with the risk of infection, and was included as a covariate. The primary endpoint was time to first infection with asexual P. falciparum, defined as the number of days from the start of the surveillance period to the date of the first positive slide. Vaccine efficacy was calculated from the hazard ratio estimated by Cox's regression, adjusting for the effects of prognostic variables. Volunteers who received fewer than three doses or who were parasitaemic both prevaccination and at the beginning of surveillance without an intervening negative blood smear were excluded from the primary analysis but included in a secondary analysis. Observations on individuals who were lost to follow-up or were missing from trial data for 3 wk were censored. Analyses were done with Stata version 7 (Stata Corporation, College Station, Texas, United States). ELISPOT responses were analysed as follows. After subtraction of medium-alone values from each pooled peptide response, responses were summed across T9/96 and 3D7 pools. Geometric means were calculated for T9/96 TRAP, 3D7 TRAP, and ME string responses. Responses in the two groups were compared using the Mann-Whitney test.
Results
In total, 489 volunteers were screened (Figure 1), of whom 117 were excluded for the following reasons: 46 could not be found on the day of vaccination, 44 were not eligible (anaemia, ALT, creatinine, HIV, various medical conditions, too young or too old), and 27 withdrew consent. Thus, 372 volunteers aged 15–45 y were enrolled. Of these, 335 men (90%) received their second dose of vaccine, and 320 of these received the third dose. Some 52 volunteers who were randomised did not receive three doses (two men received the wrong vaccine at the second dose, 26 left the study area, 23 withdrew consent, and one was withdrawn because he developed pneumonia between the first and second doses). In total, 296 volunteers (141 in the malaria group and 155 in the rabies group) received three doses and were followed up, 277 of whom completed 11 wk of surveillance. Additional data were available for 14 volunteers who did not receive all three vaccine doses (all 14 received the first and third doses), for two volunteers in the malaria vaccine group who received the wrong vaccine at the second dose, and for 18 volunteers who were parasitaemic both before vaccination and at the start of surveillance. These individuals were included in a secondary analysis. Losses to follow-up were similar in the two groups. Prognostic variables were similarly distributed in the two groups at the start of surveillance (Table 1). This trial is reported in accordance with CONSORT guidelines (Table S1).
Figure 1 Trial Profile
Table 1 Characteristics of the Trial Cohorts at the Start of Surveillance
Table shows the 296 participants who received three doses of vaccine and were followed up
a Village group 2 consisted of nine closely situated villages
Vaccine Safety
No clinically significant differences in packed cell volume, ALT, or creatinine were seen in either vaccine group. One volunteer who received rabies vaccine had a history of breathlessness and chest pain several years prior to enrolment, experienced a relapse of symptoms, and deteriorated and died, probably from heart disease, 3 mo after he received the last dose of vaccine. This event was regarded as unrelated to vaccination. There were no other serious adverse events. Adverse events were rare after first and second doses and were not increased in the DNA ME-TRAP group compared to the rabies vaccine group (data not shown). Injection site pain, limited arm motion, headache, and malaise in the first 24 h after vaccination (mild to moderate in intensity, i.e., not preventing activities of daily living, in all but one volunteer) were more common after MVA ME-TRAP vaccination than rabies vaccination (Table 2). Some volunteers developed an injection site blister 1–2 d after MVA ME-TRAP vaccination, which healed over 1–3 wk without complications. Induration (for 1–2 d) and discolouration (faint, shiny macular appearance for several weeks) were common after MVA ME-TRAP vaccination. The frequency of short duration severe adverse events (i.e., preventing activities of daily living) of less than 2% seen with MVA ME-TRAP immunisations is less than that seen with some other licensed alum-formulated vaccines in widespread use.
Table 2 Frequency of Solicited Symptoms during the 7 d after the Third Dose of Vaccine
Table shows the number and percentage of participants who had at least one report of the symptom
Immunogenicity
In the study, 63 and 30 volunteers from the malaria and rabies vaccine groups, respectively, were assayed 7 d after final vaccination for T cell responses. In the rabies vaccine group, geometric mean effector T cell responses were 3.1, 3.9, and 1.4 spot-forming cells (SFCs) per million PBMCs for T9/96 and 3D7 strains of TRAP and the ME string, respectively. In the malaria vaccine group, the effector T cell frequency to the vaccine strain of the TRAP antigen, T9/96, was geometric mean 251.1 SFCs per million PBMCs (80-fold increase above control group, p <0.001, range 6.25–2148.75). A large cross-reactive T cell response to 3D7 TRAP, a strain with 6% amino acid variance to T9/96, and a weaker response to the ME string were also seen at this timepoint (Table 3).
Table 3 Effector T Cell Responses 1 wk after the Third Vaccination
Of the 98 individuals identified for testing T cell responses, 80 received three doses of vaccine according to protocol and gave analysable responses
Time to First P. falciparum Infection
By the end of the study, 171 participants developed parasitaemia, 80/141 (57%) in the malaria vaccine group and 91/155 (59%) in the rabies vaccine group. The distribution of time to first infection was similar in the two groups (Figure 2). Vaccine efficacy among participants who received three doses, adjusted for age, bednet use, ethnic group, and village of residence was 10.3% (95% CI, −22% to +34%; p = 0.49). Similar results were obtained when all participants who received at least one dose of vaccine were included in the analysis (efficacy, 1.0%; 95% CI, −32% to +25%; p = 0.95).
Figure 2 Kaplan-Meier Survival Curves Showing the Probability of Remaining Free of P. falciparum Infection during the 11 wk of Surveillance
Week 0 of surveillance began in October 2002, 14 d after the third dose of vaccine was administered.
Geometric mean P. falciparum densities in first infections were similar in the two groups (31 parasites/μl [IQR, 5–154] in the malaria vaccine group compared to 24 parasites/μl [IQR, 5–69] in the rabies group; Mann-Whitney test, p = 0.79).
During surveillance, there were ten episodes of symptomatic malaria in the malaria vaccine group and 13 in the rabies group. The risk of malaria-related symptoms during an episode of parasitaemia was similar in both vaccine groups. Percentage mean packed cell volume at the end of the trial was similar in both groups (41 [IQR, 37–44] for the malaria vaccine group and 40 [IQR, 37–43] for the rabies group).
Within the ELISPOT substudy group, the risk of developing parasitaemia was not associated with effector T cell response to the 3D7 strain of TRAP. The 80 men from the substudy group who received three doses of either malaria vaccine (55 men) or rabies vaccine (25 men), completed 11 wk of surveillance, and had complete ELISPOT data after dose three were divided into four quartiles. Men with the highest effector T cell responses had hazard ratios for infection similar to those with the lowest after adjustment for age, bednet use, and village of residence.
The incidence of parasitaemia decreased with increasing age, and was decreased in those of Fula ethnicity compared to those in the Mandinka and Wollof ethnic groups (Table 4). The use of bednets was not associated with a significantly reduced risk of malaria infection (Table 4).
Table 4 Results of Cox Proportional Hazards Regression Analysis for the Risk of Developing Parasitaemia after Three Doses of Vaccine
Discussion
This trial demonstrated that vaccination with two doses of DNA ME-TRAP followed by a single dose of MVA ME-TRAP is safe and highly immunogenic for effector T cell induction but that it did not reduce the P. falciparum infection rate in a semi-immune adult African population. This provides a second comparison between protection in malaria-naïve and malaria-experienced adults. RTS,S/AS02, a circumsporozoite protein malaria vaccine based on a hepatitis B surface antigen virus-like particle formulated in a proprietary adjuvant, provided about 40% sterile protection in the artificial challenge model [29] and 71% short-term protection against natural infection [30]. The lack of field efficacy found in the present study despite evidence of partial protection in United Kingdom volunteers supports the use of complete, not partial, protection in the sporozoite challenge model as a predictor of likely field efficacy against malaria infection when screening pre-erythrocytic vaccine candidates. However, some vaccines are known to prevent disease but not infection, as is also the case for naturally acquired immunity to malaria. There was no effect of bednet use on parasitaemia in either this study or an earlier malaria vaccine trial in adults [30], whereas bednet use has been found to substantially reduce the incidence of clinical malaria and childhood mortality in Gambian children [31]. The present study does not exclude the possibility that the vaccination regimen tested could provide significant anti-disease immunity. Paediatric study designs are necessary to evaluate this possibility. The present study highlights an issue related to use of surrogate efficacy endpoints; whereas positive results can spur development, negative results may incorrectly lead to the cessation of development of a candidate vaccine.
Another possible reason for the observed low efficacy is that the frequency of the effector T cell response declines from 7 d after boost, and so efficacy would be prevented if very high frequencies of circulating effectors are needed for protective efficacy. Alternatively, a suboptimal regional memory T cell pool in the liver may be responsible [32], or, less likely in view of the observed T cell strain cross-reactivity, TRAP polymorphisms may have impaired T cell recognition.
In previous studies in East and West Africa, summed T cell responses to TRAP in unvaccinated semi-immune adults by ex vivo γ-interferon ELISPOT were geometric mean less than 20 SFCs per million PBMCs. The candidate regimen represents a new method for induction of unprecedented effector T cell frequencies, which are about 50-fold higher than those induced by lifelong natural exposure. Estimates of the reduction in liver-stage parasite burden induced by these vaccines in the human challenge model are of the order of 80%–90% of infected hepatocytes [21,33]. It is unclear whether a similar level of anti-parasite activity could have been achieved in this study without any significant change in infection rate. Another candidate malaria vaccine that reduced liver parasite burden by an estimated 95% in challenge studies [29,33] did have a substantial, if short-lived, impact on infection rates in a similar Gambian field study [30]. This suggests that a moderate increase in the efficacy of this first-generation prime-boost vaccination strategy in reducing liver parasite burden might have an important impact on overall efficacy.
Second-generation prime-boost vaccine strategies for malaria currently in or near to clinical evaluation include the following: use of a different viral vector as the priming agent that may lead to proportionately greater CD8+ rather than CD4+ T cell induction (J. M. Vuola, S. Keating, D. P. Webster, T. Berthoud, S. Dunachie, et al., unpublished data), as is the case with fowlpox-MVA immunisation; the use of a different antigen, the circumsporozoite protein, or polyprotein constructs [34] to address the difficult issue of target antigen selection; and evaluation of regimes that seek to combine high-level T cell responses with strong anti-sporozoite antibody induction, e.g., protein/adjuvant and recombinant virus prime-boost immunisation. In the medium term, combination with protective blood-stage antigens is also desirable. Determining methods for the successful combination of different candidate vaccine regimens (whether within or between parasite stages) will be one of the important challenges of coming years.
We were unable to obtain a useful estimate of the likely efficacy of the DNA ME-TRAP/MVA ME-TRAP vaccination regime against clinical disease. Even for an adult population, the incidence of clinical disease was lower than expected. Sulphadoxine/pyrimethamine was administered 4 wk before the start of surveillance in this study and in an RTS,S field efficacy study [30]. There is some evidence that pretreatment with this antimalarial reduces the incidence of clinical malaria for longer than 4 wk [35,36]. However, there was also less clinical disease than in recent years in paediatric cohorts recruited for other studies in 2002 at the study site, probably for climatic reasons.
This study highlights North Bank Division in Gambia as an excellent malaria vaccine field trial site both for adults and, by extrapolation, for children. In a low-transmission year, cumulative incidence overall in men aged 15–45 y was 72% over 11 wk, which was higher than expected. Also, compliance was good despite a demanding study design, and migration from the study area was acceptably low.
This paper adds to the body of data detailing the very gradual acquisition of anti-infection immunity in adults resident in sub-Saharan Africa [30]. While substantial immunity to severe malaria is acquired after only a few infections and anti-disease immunity is acquired in childhood, we saw statistically significant decreases in incidence of infection with increasing age in the 15–45 age range (Table 4). The protection against infection for those with Fula ethnicity observed in this trial is consistent with a report from Burkina Faso [37]. The Fulani mostly reside in distinct villages in this part of Gambia.
Immunological analysis of the high level of protection inducible by immunisation of humans and animals with irradiated sporozoites has encouraged attempts to generate protective immunity by subunit vaccines that induce strong cellular immune responses. To date the induction of high-level protective T cell responses against malaria and some other infectious pathogens has generally required two-component prime-boost vaccination approaches [38]. We report the first field efficacy trial of a subunit vaccine designed to induce protective immunity through effector T cell rather than antibody induction. Effector T cell induction 50-fold greater than that generated by natural malaria infection is now possible through DNA-based heterologous prime-boost vaccination of humans. However, further development of T cell–inducing vaccines will be required to evaluate the effects of altering the characteristics, target antigen specificities, and durability of the induced T cells in order to generate higher levels of protective immunity against malaria.
Patient Summary
Background
Malaria kills 1–2 million people a year, mostly children under the age of five who live in sub-Saharan Africa. Scientists are trying to develop cheap, safe, and effective vaccines that could be given to people living in regions where malaria is very common to prevent them from developing the disease.
What Did the Researchers Find?
The researchers enrolled 372 Gambian men aged 15–45 years into the study. They injected half the men with two malaria vaccines, one after the other, and half the men with a rabies vaccine that does not protect against malaria (this vaccine was given so that “control” participants would have some benefit from being in the trial) just before the rainy season, when malaria is especially prevalent. The scientists took blood smears from the men once a week and checked to see if they had been infected with the parasite that causes malaria. They found that the men who had been vaccinated became infected just as quickly as those who had not. Although the two malaria vaccines in concert did not work, neither did they cause any serious side effects. The men given the malaria vaccines did produce an immune response to the vaccines, though not one that was clinically useful.
What Does This Mean for Patients?
It looks as though the combination of these two vaccines is not effective at preventing infection with Plasmodium falciparum, the parasite that causes malaria. However, there are other vaccines in development that have not been tested yet.
Resources on the Web.
Gates Malaria Partnership (which co-funded the study): http://www.lshtm.ac.uk/gmp/
Malaria Vaccine Initiative: http://www.malariavaccine.org/
Medicines for Malaria Venture: http://www.mmv.org/pages/page_main.htm
Roll Back Malaria Partnership: http://rbm.who.int/partnership
The Wellcome Trust (which co-funded the study): http://www.wellcome.ac.uk/en/malaria/
Supporting Information
Trial Registration
This trial has been submitted for registration in the International Standard Randomised Controlled Trial Number (ISRCTN) Register. The ISRCTN is ISRCTN05221133; Web site http://www.controlled-trials.com/isrctn/trial/1/0/05221133.html.
Table S1 Consort Checklist
(55 KB DOC).
Click here for additional data file.
We thank the volunteers who participated in this study; the Data Safety Monitoring Board (Chairman, Anthony Bryceson); the local safety monitor (Dr Ousman Nyan); the malaria field, laboratory, and data entry staff; and S. McConkey, S. Dunachie, T. Berthoud, and D. Webster for help and advice. VSM was a Wellcome Trust Training Fellow in Clinical Tropical Medicine when this study occurred. EBI is a Gates' Malaria Partnership Training Fellow. AVSH is a Wellcome Trust Principal Fellow. This trial was co-funded by the Gates' Malaria Partnership at the London School of Hygiene and Tropical Medicine and the Wellcome Trust. The funding sources had no role in study design, collection, analysis, and interpretation of data, in the writing of the report, or in the decision to submit the paper for publication.
Author contributions. VSM wrote the manuscript and clinical trial protocol, designed the case report form, and supervised recruitment, vaccination, laboratory work, and follow-up. EBI supervised recruitment, vaccination, and follow-up. PM analysed the data and helped plan the trial. KB helped plan the trial. SK conducted the immunology analysis. PK was the data manager. MP helped laboratory supervision and planning of the trial. SCG conducted preclinical development and some quality control of the vaccines. GW helped with recruitment and planning of the trial. BMG helped plan the trial. AVSH supervised development of the malaria vaccines and the immunology assays and helped plan and report the trial.
Citation: Moorthy VS, Imoukhuede EB, Milligan P, Bojang K, Keating S, et al. (2004) A randomised, controlled, double-blind efficacy trial of DNA/MVA ME-TRAP prime-boost immunisation against malaria infection in Gambian adults. PLoS Med 1(2): e33.
DOI: 10.1371/journal.pmed.0010033
Abbreviations
ALTalanine aminotransferase
CIconfidence interval
ELISPOTenzyme-linked immunospot
IQRinterquartile range
MEmultiple epitope
MVAmodified vaccinia virus Ankara
PBMCperipheral blood mononuclear cell
SFCspot-forming cell
TRAPthrombospondin-related adhesion protein
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| 15526058 | PMC524376 | CC BY | 2021-01-05 10:38:00 | no | PLoS Med. 2004 Nov 26; 1(2):e33 | utf-8 | PLoS Med | 2,004 | 10.1371/journal.pmed.0010033 | oa_comm |
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 1552605910.1371/journal.pmed.0010036Research ArticleImmunologyInfectious DiseasesHIV/AIDSInfectious DiseasesHIV Infection/AIDSImmunology and allergyLimited Durability of Viral Control following Treated Acute HIV Infection Viral Control in Treated Acute HIVKaufmann Daniel E
1
Lichterfeld Mathias
1
Altfeld Marcus
1
Addo Marylyn M
1
Johnston Mary N
1
Lee Paul K
1
Wagner Bradford S
1
Kalife Elizabeth T
1
Strick Daryld
1
Rosenberg Eric S
1
Walker Bruce D
1
2
Klenerman Paul Academic Editor1Partners AIDS Research Center, Infectious Disease UnitMassachusetts General Hospital and Division of AIDS, Harvard Medical School, Boston, MassachusettsUnited States of America2Howard Hughes Medical Institute, Massachusetts General Hospital and Division of AIDSHarvard Medical School, Boston, MassachusettsUnited States of AmericaKlenerman Paul Academic EditorUniversity of OxfordUnited Kingdom
Competing Interests: The authors have declared that no competing interests exist.
Author Contributions: ESR and BDW designed the study. DEK, ML, MMA, PKL, BSW, ETK, and DS performed the experiments. DEK, ML, MA, ESR, and BDW analyzed the data. MNJ enrolled patients. DEK and ML contributed to writing the paper.
*To whom correspondence should be addressed. E-mail: bwalker@partners.org11 2004 26 10 2004 1 2 e3615 6 2004 3 9 2004 Copyright: © 2004 Kaufmann 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.
Supervised Treatment Interruptions Fail to Control HIV-1 Viremia
Background
Early treatment of acute HIV infection with highly active antiretroviral therapy, followed by supervised treatment interruption (STI), has been associated with at least transient control of viremia. However, the durability of such control remains unclear. Here we present longitudinal follow-up of a single-arm, open-label study assessing the impact of STI in the setting of acute HIV-1 infection.
Methods and Findings
Fourteen patients were treated during acute HIV-1 infection and subsequently subjected to an STI protocol that required retreatment if viral load exceeded 50,000 RNA copies/ml plasma or remained above 5,000 copies/ml for more than three consecutive weeks. Eleven of 14 (79%) patients were able to achieve viral loads of less than 5,000 RNA copies/ml for at least 90 d following one, two, or three interruptions of treatment. However, a gradual increase in viremia and decline in CD4+ T cell counts was observed in most individuals. By an intention-to-treat analysis, eight (57%), six (43%), and three (21%) of 14 patients achieved a maximal period of control of 180, 360, and 720 d, respectively, despite augmentation of HIV-specific CD4+ and CD8+ T cell responses. The magnitude of HIV-1-specific cellular immune responses before treatment interruption did not predict duration of viremia control. The small sample size and lack of concurrent untreated controls preclude assessment of possible clinical benefit despite failure to control viremia by study criteria.
Conclusions
These data indicate that despite initial control of viremia, durable viral control to less than 5,000 RNA copies/ml plasma in patients following treated acute HIV-1 infection occurs infrequently. Determination of whether early treatment leads to overall clinical benefit will require a larger and randomized clinical trial. These data may be relevant to current efforts to develop an HIV-1 vaccine designed to retard disease progression rather than prevent infection since they indicate that durable maintenance of low-level viremia may be difficult to achieve.
Long-term follow-up of 14 patients on HAART during acute infection followed by supervised treatment interruptions shows that most failed to achieve lasting control of viremia.
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Introduction
The use of highly active antiretroviral therapy (HAART) can dramatically prolong the life of individuals infected by human immunodeficiency virus 1 (HIV-1) [1], but early hopes for virus eradication have not been realized [2]. The successful use of HAART is limited by drug-related toxicities, high costs, and drug resistance [3], factors which have led to the development of alternative therapeutic strategies, including the use of supervised, or structured, treatment interruption (STI). This approach, involving recurrent limited exposure to autologous virus, has not been successful in chronic infection [4,5], but has been shown to lead to at least transient containment of viremia after intervention in the acute phase of infection in humans and animals exposed to AIDS-associated retroviruses [6,7,8,9].
In the present study, we performed a detailed longitudinal assessment of the impact of early treatment followed by STIs in patients treated during acute or early HIV-1 infection. The main hypothesis of the study was that early treatment of acute HIV-1 infection followed by STI would lead to immune boosting and subsequent control of viremia without the need for drugs. The primary endpoint was the time to viral rebound above 50,000 copies/ml once or above 5,000 copies for three determinations separated by a week each. The early results of this trial were previously reported, showing that five of eight patients were able to achieve a plasma viral load of 500 copies/ml or less at a median of 6 mo off therapy [6]. The current study investigates the frequency and durability of control achieved with this intervention, with follow-up to a median of 5.3 y after infection, and with an increase in size of the cohort to 14 patients. Our results indicate that, although the majority of patients treated in the acute phase of infection go on to control HIV-1 to less than 5,000 RNA copies/ml plasma for at least 6 mo off therapy, the ability to contain viremia below this level over the long term is maintained in a minority of patients.
Methods
Objective
The hypothesis of the study was that early treatment of acute HIV-1 infection would confer immunologic maturation and subsequent control of HIV-1 without the need for ongoing drug therapy. Alternatively, if a breakthrough of virus replication was observed, this would provide a boost in HIV-1-specific immunity after reinstitution of antiviral therapy. The primary endpoint was the time to viral rebound to more than 50,000 copies/ml or viral loads above 5,000 copies/ml for three determinations separated by a week each. The secondary objective was to correlate immunologic and virologic parameters with any observed effects including evolution of HIV-1-specific T helper and cytotoxic T lymphocyte responses. The original study protocol, including the patient consent form and the institutional review board approval, can be found in Protocols S1–S4.
Study Population
Fourteen patients presenting with acute or early HIV-1 infection were enrolled in this study between July 1997 and January 2000 (Table 1). Acute HIV-1 infection was defined by the presence of HIV-1 RNA in the plasma, a negative or weakly positive HIV-1 antibody by HIV-1/2 ELISA, and the detection of no more than three bands in an HIV-1 Western blot; early HIV-1 infection was defined by a positive ELISA and confirmation of early infection by either detuned negative ELISA or previously known negative ELISA. All participants in the study had symptoms compatible with the acute retroviral syndrome and were treated with HAART (one protease inhibitor and two nucleoside reverse transcriptase inhibitors) within a median of 19 d (range, 9–33) from the onset of symptoms. Study participants were recruited from the Massachusetts General Hospital, the Brigham and Women's Hospital, and the Fenway Community Heath Care Center in Boston. All individuals gave written informed consent to participate, and the study was approved by the respective institutional review boards and conducted in accordance with the human experimentation guidelines of the Massachusetts General Hospital.
Table 1 Characteristics of the Study Participants
a All patients were males. All individuals were White Americans except AC-45, who was Hispanic
b ELISA and Western blot positive, but infection within 180 d from time therapy was initiated
Ind, indetermined; NA, not applicable; neg, negative; pos, positive
Six of the 14 individuals were investigated in an interim study [10]. These patients were AC-02 (AS2 in [10]), AC-05 (AS5), AC-14 (AS1), AC-15 (AS3), AC-25 (AS6), and AC-46 (AS4).
STIs
Entry criteria included treatment with HAART before or shortly after HIV-1 seroconversion, viral suppression on HAART to less than 400 RNA copies/ml for 2 mo, HIV-1 viral load at the time of entry into the study of less than 50 RNA copies/ml, and lack of significant mutations conferring drug resistance [11,12]. Lymphocyte proliferative response to recombinant HIV-1 p24 protein had to exceed a stimulation index of ten before treatment discontinuation, and net counts per minute had to be 800 or greater. All antiretroviral drugs were discontinued simultaneously. After a treatment interruption, patients were seen at least once a week for the first 24 wk, and then monthly, with a total of at least 30 visits for the first year after cessation of therapy. In the second year, visits continued monthly. Treatment was restarted if viral load remained above 5,000 RNA copies/ml plasma for greater than three consecutive weeks, or was in excess of 50,000 copies/ml on any single occasion.
Human Leukocyte Antigen Typing
High- and intermediate-resolution human leukocyte antigen class I typing was performed at a commercial laboratory (Dynal Biotech, Oxford, United Kingdom) by sequence-specific PCR as described [13].
Detection of GB Virus C RNA
GB virus C (GBV-C) RNA was detected using a two-step nested PCR amplification reaction from whole plasma RNA. Briefly, GBV-C RNA was extracted from plasma using the Qiagen Viral RNA Mini Kit (Qiagen, Valencia, California, United States) according to the manufacturer's instructions. Extracted RNA was reverse transcribed using the Qiagen OneStep RT-PCR Kit and amplified by nested PCR; in both steps primers specific for the 5′ UTR of GBV-C were used, as described previously [14].
Chemokine Receptor Genotyping
In order to analyze the chemokine receptor (CCR) 5Δ32 deletion polymorphism, the region spanning the 32-nt deletion was amplified by PCR, and the two alleles were separated by gel electrophoresis [15]. The CCR2–64I polymorphism was detected by PCR–restriction fragment length polymorphism analysis as described previously [16].
Synthetic HIV-1 Peptides
We synthesized 410 synthetic peptides 15–20 amino acids long at the Massachusetts General Hospital Peptide Core Facility on an automated peptide synthesizer using Fmoc technology, as described [17]. Peptides overlapped by 10 amino acids and spanned the entire HIV-1 clade B 2001 consensus sequence.
ELISPOT Assays
ELISPOT assays were carried out as described previously [18]. Peripheral blood mononuclear cells (PBMCs) were incubated overnight at 50,000 to 100,000 cells/well in 96-well polyvinylidene plates that had been precoated with 0.5 μg/ml anti-human interferon-γ monoclonal antibody (Mabtech, Stockholm, Sweden). The final concentration of the peptide per well was 14 μg/ml. The numbers of spots per well were counted using an automated ELISPOT plate reader (AID EliSpot reader system, Autoimmune Diagnostika, Strassberg, Germany). A response was considered positive if there were more than 50 spot-forming cells (SFCs)/106 PBMCs and if the well had at least three times the mean number of SFCs in the three control wells. The dependence of responses on CD8+ T cells was determined by measuring the depletion of CD4+ T cells using the Minimacs cell depletion system (Miltenyi Biotec, Bergisch-Gladbach, Germany). When HIV-1-specific CD8+ T cell responses were detected against adjacent peptides, and therefore might represent targeting of the overlap region, responses to the weaker peptide were excluded for calculations of magnitude and breadth, as previously described [19].
Proliferation Assays
Freshly isolated PBMCs (105 cells) were incubated with baculovirus-derived recombinant p24 protein (Protein Sciences, Meriden, Connecticut, United States) at 5 μg/ml for 6 d and then pulsed with 3H thymidine at 1.0 μCi for 6 h before harvesting as previously described [20]. A stimulation index of five or greater was considered significant.
Statistical Analysis
Time to failure during the different treatment interruptions was assessed by Kaplan-Meier analysis. Patients who were still controlling viremia at the time of last visit, who failed because they restarted therapy without meeting the criteria of virologic failure, or who were lost in follow-up were included in the analyses, but the data were censored at the last evaluable time point. Equality of survival distributions for the first and second treatment discontinuations was evaluated using the Wilcoxon matched-pairs signed-ranks test. CD4+ T cell losses were calculated on regression lines based on least squares fit. A Cox proportional hazards regression model was used for the analysis of continuous variables such as days following onset of symptoms, CD4+ T cell count, HIV viral load, and time to rebound of viremia, as well as for the estimation of hazard ratios for the categorical variables of ELISA, Western Blot, coreceptor polymorphism, and GBV-C status. Statistical analyses of CD8+ and CD4+ T cell responses were based on a Student's t test, a multiparametric ANOVA test, a Wilcoxon matched-pairs signed-ranks test, or a Mann-Whitney U test, as indicated. p-values lower than 0.05 were considered to indicate statistical significance, and all reported p-values are two-sided. Statistical analysis and graphical presentation were performed using SPSS, SAS, and Prism software packages.
Results
Longitudinal Assessment of Control of Viremia following Treated Acute or Early Infection
Fourteen patients identified at the time of acute or early infection (Table 1; Figure 1) were entered into this protocol, and they were followed for a median of 5.3 y from the time of infection (range, 494–2,475 d). Patients underwent successive treatment interruptions after an initial treatment period of at least 8 mo (median, 508 d; range, 245–1,096 d) and were required to restart therapy when viral load exceeded 50,000 RNA copies/ml plasma on a single occasion, or 5,000 copies/ml for three consecutive weeks. For purposes of analysis, patients who dropped out of the study or who reinitiated therapy without meeting criteria were considered to have lost the ability to contain viremia.
Figure 1 HIV-1 Viral Loads and CD4+ T Cell Counts in the 14 Study Participants
Time zero corresponds to first institution of highly active antiretroviral therapy (HAART). Closed squares, HIV-1 plasma viral loads; open circles, CD4+ T cell counts; shaded areas, treatment with HAART according to protocol; diagonally shaded areas, patient restarted therapy without meeting criteria of virological failure; vertical dotted lines, virological failure without reinstitution of HAART. Patients are ordered by increasing number of supervised treatment interruptions.
Using these criteria for reinitiation of therapy and to define failure, 11 of 14 patients (79%) were able to achieve virologic control to less than 5,000 RNA copies/ml plasma for at least 90 d after one, two, or three treatment interruptions (Table 2). The period of longest containment was after one interruption for five patients, after two interruptions for eight patients, and after three interruptions for one patient (Table 3).
Table 2 Period of Viral Control Achieved Off Therapy
Table 3 Time to Failure during the STIs
a Numbers correspond to time until virological failure, unless otherwise specified
Red indicates the longest time off therapy until failure or last follow-up
b Last follow-up visit; patients still meeting criteria of virological control
c Failure because patient restarted antiviral therapy without meeting criteria of virological failure
d Virological failure due to HIV-1 superinfection
Once control was achieved, the majority of the patients experienced a subsequent rise in viremia. The median time between cessation of therapy and rebound of viremia (having a viral load greater than 50 copies/ml) was 17 d (range, 7–169 d).
Six of 14 patients (43%) achieved a period of control after stopping therapy for 1 y, but only three of 14 (21%) were able to control viremia off therapy at less than 5,000 RNA copies/ml plasma for more than 2 y. Duration of viremia control during successive treatment interruptions was highly variable, and there was no increase in the sustainability of viral containment during successive STI cycles. The three patients achieving control of viremia for more than 2 y did so during the first (AC-10), the second (AC-02), and the third (AC-14) treatment interruption, respectively (Figure 2A). A paired comparison (Wilcoxon matched-pairs signed-ranks test) showed no significant difference in the length of viremia control with subsequent treatment interruptions. Although patients experienced rebound viremia with discontinuation of therapy, none of the patients experienced recurrence of symptoms associated with acute HIV-1 infection.
Figure 2 Evolution of Viral Load and CD4+ T Cell Counts during STI
(A) Survival curves of time to virologic failure during the first three supervised treatment interruptions. Virologic failure was defined as having a viral load of greater than 5,000 copies RNA/ml plasma for 3 wk or greater than 50,000 copies once. Patients still achieving viral control at the last visit and individuals restarting therapy without meeting criteria or lost in follow-up are censored at the last evaluable time point. The horizontal axis represents the time off therapy since the beginning of the treatment interruption, the vertical axis corresponds to the number of patients maintaining control of viremia. The curves for first, second, and third STIs do not differ significantly from each other (log-rank test, p > 0.05).
(B) Evolution of CD4+ T cell counts during the longest treatment interruption. Slopes of CD4+ T cell counts during the first year of the longest treatment interruption are shown for patients who experienced a cessation of therapy of at least 12 mo (all except AC13, AC25, and AC45), compared to the natural decline of CD4+ T cell counts in untreated patients of the MACS cohort with early chronic HIV-1 infection (CD4+ counts of >350 cells/mm3). CD4+ T cell losses were calculated on a regression line based on least squares fit. The two groups differed significantly from each other (Mann-Whitney U test, p = 0.02).
(C) CD4+ T cell count at intercept and CD4+ T cell slopes during the longest treatment interruption. The CD4+ T cell slopes of the same 11 patients shown in (B) and of untreated patients of the MACS cohort are represented according to the CD4+ T cell count at the intercept of the regression line based on least squares fit with the vertical axis (day 0 of treatment interruption).
These data show that at least transient control of viremia to less than 5,000 RNA copies/ml plasma was achieved in the majority of study participants during at least one of the treatment interruptions, but that durable viral control in participants following treated acute infection occurred infrequently. Moreover, the data do not show a consistent pattern of augmentation of viral control with sequential treatment interruptions.
Effect of Treatment Interruptions on CD4+ T Cell Counts
Although viral load is a strong predictor of disease progression, CD4+ T cell loss is an additional, independent predictor [21]. Early treatment of acute HIV-1 infection led to normalization of CD4+ T cell counts in most patients (median, 753 cells/mm3; range, 492–986), but the effect of treatment interruption was variable, even in those doing well, as defined by sustained low viral loads. Overall, 11 of 14 patients interrupted therapy for at least 12 mo, and these individuals were evaluated regarding the effect of treatment interruption on CD4+ T cell loss (Figure 2B and 2C). The rate of change in CD4+ T cell counts during the first year of the longest period off treatment ranged from +157 to −438 cells/mm3/y (median, −192). Of the three patients who did not meet viral load criteria for restarting therapy for more than 2 y, one (AC-02) had an increasing CD4+ T cell count of 157 cells/mm3/y, one (AC-10) had a stable CD4+ T cell count (−9 cells/mm3/y) , and one (AC-14) experienced a decline of 344 cells/mm3/y. Comparison with data from the Multicenter AIDS Cohort Study (MACS) showed that the kinetics of CD4+ T cell loss was faster (Mann-Whitney U test , p = 0.02) than in untreated patients with early chronic HIV-1 infection (average loss of −67 cells/mm3/y in patients with a CD4+ T cell count of more than 350 cells/mm3 at baseline). However, CD4+ T cell loss rate was in the same range as what has been described after treatment interruption in chronic HIV-1 infection [22,23]. Analysis of CD4+ T cell decline during the second year for the three individuals who controlled viremia for more than 2 y revealed similar trends in CD4+ T cell slopes, although they were less steep: AC-02, +88 cells/mm3/y; AC-10, +44 cells/mm3/y; and AC-14, −110 cells/mm3/y. When the first 3 mo off therapy were excluded in order to minimize the potential effects of recent treatment on CD4+ T cell number, the rate of change in CD4+ T cell counts during the first year off therapy no longer differed statistically from the MACS data (median, −207 cell/mm3/y; range, +119 to −699; Mann-Whitney U test, p = 0.07). A possible reason for steep CD4+ T cell slopes may be high CD4+ T cell counts at time of treatment interruption. Comparison with MACS data (Figure 2C) showed that several of the study participants still behaved as outliers when this factor was considered. These results indicate that periods of relative control of viremia were associated with declining CD4+ T cell counts in most patients.
Correlation of Clinical and Genetic Markers with Duration of Viremia Control
Although the study was small, we evaluated clinical and laboratory parameters to see if any was predictive of duration of viral control. Analyses included clinical and laboratory parameters at time of presentation with acute HIV-1 infection, genetic markers associated with different rates of disease progression, and the presence or absence of GBV-C coinfection. All patients presented with symptomatic acute infection. Time between onset of symptoms and institution of therapy did not affect duration of control following STI (Cox proportional hazards regression model, p > 0.05). The individuals who controlled viremia for a longer time either during the first STI or during any of the treatment interruptions were not different from those who experienced earlier breakthrough as measured by ELISA and Western blot status at initiation of HAART, coreceptor polymorphisms (CCR5delta32, CCR2 V64I), or the presence or absence of GBV-C coinfection (Cox proportional hazards model, p > 0.05 in all comparisons; data not shown). The only parameter that was predictive of prolonged viral control during the first treatment interruption was a low viremia at time of institution of therapy (p = 0.01): there was a 2.8-fold increase in hazard per order of magnitude increase in viral load. This factor was no longer predictive when the period of longest control of viremia was considered. The time to rebound of viremia (>50 copies/ml or >400 copies/ml) did not correlate with the duration of viral control. Although 11 out of 14 individuals achieved at least transient control of viremia, and three experienced prolonged control, none of these patients possessed the HLA alleles B27 or B57 associated with better disease outcome [24,25].
Relationship of Magnitude and Breadth of HIV-1-Specific CD8+ T Cells to Duration of Viremia Control
To assess the relationship between the clinical outcome and evolution of HIV-1-specific CD8+ T cells, we longitudinally analyzed the breadth and magnitude of CD8+ T cell responses using an interferon-γ ELISPOT and a panel of 410 overlapping peptides spanning the entire HIV-1 clade B consensus sequence. At the beginning of the first STI, HIV-1-specific CD8+ T cells were weak (median of 590 SFCs/106 PBMCs) (Figure 3A) and narrowly directed at a median of two epitopes (Figure 3B). CD8+ T cell responses increased significantly (p < 0.05) during the first off-treatment period, reaching a median total magnitude of 2,725 SFCs/106 PBMCs and targeting a median of eight epitopes, and then were sustained when therapy was reintroduced. A further increase in the magnitude and breadth of HIV-1-specific CD8+ T cells was observed in the subsequent off-treatment periods, although these augmentations failed to reach statistical significance. The CD8+ T cell–mediated immune responses emerging during these consecutive cycles of treatment interruption were broadly directed, targeting all structural and most accessory and regulatory HIV-1 gene products (data not shown). However, the magnitude of HIV-1-specific CD8+ T cell responses at the beginning of the first (r = 0.01, p = 0.76), second (r = 0.16, p = 0.54), or third (r = 0.1, p = 0.55) treatment interruptions was not predictive of the time the study participants were subsequently able to stay off therapy according to study criteria.
Figure 3 Evolution of HIV-1-Specific CD4+ and CD8+ T Cell Responses during STI
(A–D) Magnitude and breadth of increase of HIV-specific CD8+ T cells during supervised treatment interruptions.
(A and B) Magnitude (A) and breadth (B) of HIV-specific CD8+ responses at the first day of treatment interruption (black bars) and at the last day off therapy (white bars). Data represent the mean and standard deviation.
(C and D) Correlation between the increase of the magnitude (C) or breadth (D) of CD8+ T cell responses and the time off therapy during the first treatment interruption.
(E and F) Evolution of CD4+ T helper cell responses during supervised treatment interruptions.
(E) Magnitude of CD4 T helper cell responses at baseline and at the first day of treatment interruption (closed circles) and last day off therapy (open circles). Horizontal bars correspond to median values. An stimulation index greater than five was considered significant.
(F) Correlation between the magnitude of p24-specific lymphocyte proliferative responses at the beginning of the first treatment interruption and the time patients were able to remain off therapy during the subsequent STI.
The periods off treatment allowed for assessment of the relationship between exposure to virus and evolution of immune responses. There was a highly significant positive association between time until virologic failure during the first treatment interruption and change in the magnitude of HIV-1-specific CD8+ T cell responses (r = 0.92, p < 0.001) (Figure 3C). Similarly, the longer a patient remained off therapy during the second and third interruptions, the greater the augmentation of the total magnitude of HIV-1-specific CD8+ T cell responses (r = 0.83, p < 0.016; r = 0.74, p = 0.05, respectively). The increase in CD8+ T cell epitopes targeted during the first treatment interruption was also linearly correlated to the duration until virological failure (r = 0.81, p < 0.001) (Figure 3D). However, no significant relationship was observed between the augmentation of epitopes targeted during the second and third treatment pauses and the time the study participants were able to remain off therapy in the respective treatment interruption. These data suggest that the duration of a treatment interruption, and therefore the duration of exposure to plasma virus, correlates positively with the magnitude and breadth of HIV-1-specific CD8+ T cell responses that emerge during off-therapy time periods. Yet, CD8+ T cell responses prior to treatment interruptions were not significantly predictive of the duration of time that patients are able to spontaneously control HIV-1 replication, as defined by the study criteria.
Relationship of Magnitude of Lymphocyte Proliferative Responses to p24 Antigen to Duration of Viremia Control
We next analyzed evolution of lymphoproliferative responses to recombinant HIV-1 p24 Gag protein in order to assess HIV-1-specific CD4+ T cell function. Most individuals had no detectable response at baseline prior to treatment, consistent with prior reports of patients with acute HIV-1 infection [20]. After initiation of therapy, all individuals generated HIV-1-specific lymphoproliferative responses (Figure 3E), which was a criterion for inclusion in the study. During treatment interruptions, there was a variable decline in magnitude, and comparisons between responses on the first day of treatment interruption and last day off therapy did not reach statistical significance (first STI, p = 0.72; second, p = 0.12; and third, p = 0.60, respectively). These HIV-1-specific CD4+ T cell responses also tended to rise with reinitiation of therapy, and some of them were very robust, with stimulation indices over 50 detected in several individuals (Figure 3E). Similar to CD8+ T cell responses, the magnitude of HIV-1-specific CD4+ T helper cell responses at the beginning of the first (r = 0.05, p = 0.43) (Figure 3F), second (r = 0.16, p = 0.54), or third (r = 0.1, p = 0.55) treatment interruption was not statistically predictive of the time the study participants were subsequently able to stay off therapy according to study criteria.
Discussion
Although early treatment of acute HIV-1 infection followed by treatment interruptions may enhance control of viremia [6,8], the durability of this control remains unclear. Here we analyzed the long-term impact of initiation of antiviral therapy during acute HIV-1 infection followed by STIs in a cohort of 14 patients. Although initial control of viremia to less than 5,000 RNA copies/ml plasma was achieved in the majority of the individuals studied, a gradual increase in viremia and decline in CD4+ T cell counts was observed in most patients, even after a year or more of viral containment. Durable virologic control occurred infrequently, despite the presence of robust HIV-1-specific CD4+ and CD8+ T cell responses detected by standard assays. Moreover, even during periods of successful control of viremia, progressive loss of CD4+ T cells was frequently observed. These data indicate that although early treatment of acute and early infection is frequently associated with transient control of viremia after STI, ongoing low-level viral replication is associated with ultimate virologic breakthrough in most patients.
The standard immunologic assays and virologic assessments in this cohort revealed considerable heterogeneity among the study participants, and did not show a consistent pattern in duration of viremia control during successive treatment interruptions. Eleven of 14 patients (79%) were able to maintain a viral load of less than 5,000 copies/ml for at least 90 d, but progressive loss of control ensued in the majority of patients and only three patients (21%) were able to maintain control for more than 2 y. These three patients did so during the first (AC-10), the second (AC-02), and the third (AC-14) STI. Clinical, genetic, and immunological parameters did not distinguish these three individuals from the other 11 patients, nor did they predict the duration of control following treatment interruption. Indeed, the longer a patient was off therapy, the stronger and more broadly directed the CD8+ T cell responses became, but these were still not sufficient to maintain prolonged control in most patients. Although three patients did not complete the study as initially intended (patient AC-45 withdrew from the study after viral breakthrough on the first STI, AC-13 restarted therapy despite a viral load of less than 5,000 copies/ml during both the first and second STIs and then withdrew, and AC-05 restarted therapy prematurely during the second STI but then failed to control during the third STI), the results are not substantially different if these three are censored rather than considered to have failed to control.
Loss of viral control in this cohort occurred not only in the presence of strong CD8+ T cell responses, but in most cases also in the presence of virus-specific CD4+ T cell responses, although the CD4+ T cell responses often declined during periods of viremia. In addition, total CD4+ T cell numbers were also monitored and declined in most patients over time, including one of the three patients who were able to maintain low viral loads for at least 2 y. Mechanisms leading to rapid CD4+ T cell loss need to be further studied in future STI trials. Other parameters including chemokine receptor polymorphisms [26] and GBV-C coinfection [27,28] similarly failed to explain the different courses following treatment interruption. The only parameter found to be associated with longer control of viremia during the first treatment interruption was a lower viral load at time of institution of antiviral therapy. Given the multiplicity of comparisons made, the true significance of this finding is uncertain.
The reasons for progressive loss of control despite augmentation of virus-specific CD4+ and CD8+ T cell responses remain to be defined. In one individual (AC-06), HIV-1 superinfection in the setting of strong and broadly directed HIV-specific cellular immune responses was associated with the loss of viral control, as previously reported [29]. No other cases of superinfection have been identified in these patients (data not shown). The immunologic studies performed failed to show an association between increases in viral load and loss of immune responses, but this may be due to the use of the current standard IFN-γ assays to quantify immune function. Numerous studies now indicate that IFN-γ production alone is not associated with viral load [19,30,31] but rather that functional characteristics of CD4+ and CD8+ T cells may be better associated with viral control [32,33,34,35]. Such studies will be important to pursue. In particular, even a low level of viremia correlates with a low or undetectable frequency of interleukin-2-producing HIV-1-specific memory CD4+ T cells endowed with proliferative capacity in vitro [36,37,38,39], thus abrogating CD4+ T cell help crucial to maintain efficacy of CD8+ T cell functions. In an interim study of a subset of six of the 14 patients presented here (patients AC-02, AC-05, AC-14, AC-15, AC-25, and AC-46), a fully differentiated effector phenotype of HIV-1-specific CD8+ T cells for selected epitopes was found to be associated with better control of viremia [10]. Other factors that may contribute include functional defects in antigen-specific cell-mediated immunity [35,37,40,41,42], and progressive immune escape [43,44,45]. HIV-1-specific humoral immunity can also affect viral control after treatment interruption [46], and viral factors including viral fitness [47,48] and infection with multiple viral variants [49] can influence viral set point and the rate of disease progression. Virus sequencing studies currently in progress in this cohort indicate that viral breakthrough is associated with sequence changes within and outside known CTL epitopes (data not shown). Full evaluation of the relationship between immune escape and viral breakthrough will require extensive additional analyses, including detailed analysis of responses to autologous virus [50,51]. Assessing the changes in CD4+ and CD8+ T cell functions over time as well as viral evolution under immune selection pressure will be important to evaluate immune correlates in this cohort.
These data are important in light of other recent data on treatment interruption in both acute and chronic infection. In chronic HIV-1 infection, STI studies showed only marginal, if any, improvements of HIV-1 viremia control following a number of treatment interruptions cycles, despite at least transient increases in HIV-1-specific CD8+ and CD4+ T cell responses [4,5,52,53,54,55]. In the setting of infection with a multidrug-resistant virus, this strategy may even be deleterious [56]. Other studies of STI after treated acute HIV-1 infection have shown limited benefits [9], including recent trials such as the PrimSTOP trial [57] and the QUEST study [58]. However, little is known about the relationship between scheduling of HAART and treatment interruptions and the characteristics of viral rebound after therapy has been discontinued.
Although durable control of viremia was not achieved, it is noteworthy that the majority of patients were able to achieve transient relative containment of viremia, providing rationale for future studies aimed at further enhancing immune control. Early treatment alone should still be considered an important therapeutic option. Therapeutic vaccinations administered after treated acute HIV-1 infection and before cessation of therapy have given disappointing results thus far [9], but the availability of new and more potent immunogens requires reassessment of this approach. Indeed, the ability to enhance CD4+ T helper cell responses in the chronic phase of infection has been demonstrated [59], but whether this will enhance CD8+ T cell function requires additional studies. Some promising results have been obtained using immunomodulatory drugs, including cyclosporine [60] and hydroxyurea [61], in combination with antiviral therapy, presumably because of the limitation of T cell activation. Administration of granulocyte-macrophage colony-stimulating factor blunted the viral rebound following interruption of HAART, and largely prevented a decrease of CD4+ T cell counts in an STI trial in chronic HIV-1 infection [62]. These additional therapeutic interventions deserve further investigation in future STI studies.
Although the present study shows progressive viral breakthrough, it was not designed to address whether there might be a change in set point viremia achieved or overall clinical benefit through transient early treatment of acute HIV infection. The definition of failure chosen for this study was a viral load of greater than 5,000 RNA copies/ml plasma, which at the time the study was initiated corresponded to the level of viremia at which treatment was recommended. Larger randomized trials will be needed to determine the potential clinical and virologic benefit of approaches based on STIs. In studies of untreated infection, there is only a 5-fold difference in viremia separating the quartile with the slowest disease progression from the quartile with the most rapid progression [63], suggesting that small differences in steady-state viremia may influence clinical outcome. In the meantime, STI probably should be avoided outside the setting of controlled clinical trials. The data in this study may also be relevant to current efforts to develop a therapeutic AIDS vaccine designed to retard disease progression rather than prevent infection, since they suggest that durable maintenance of low-level viremia may be difficult to achieve.
Supporting Information
Protocol S1 Study Protocol
(68 KB DOC).
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Protocol S2 Protocol Amendment
(47 KB PDF).
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Protocol S3 Patient Consent Form
(187 KB PDF).
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Protocol S4 Institutional Review Board Approval
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Patient Summary
Background
Highly active antiretroviral therapy (HAART), which is used to treat patients with HIV, can have nasty side effects and is expensive. As a result, for the last five years scientists have been trying to determine if it is possible to give patients breaks from taking antiretroviral drugs, without patients' health suffering. It is likely that such a treatment strategy (called “supervised treatment interruption,” or STI) will not work in patients who have been infected with HIV for a long time. However, until now, the jury was out about whether STI could be of benefit to patients who had only recently been infected with HIV. Some research suggested that if newly infected patients had short “holidays” from taking HAART, it might help to boost their immune system—which in turn might help to keep HIV at bay.
What Did the Researchers Do and Find?
The researchers studied 14 patients who had recently been infected with HIV. Patients were treated until their viral load was below the limit of detection by using a very sensitive method. As they were then watched after treatment interruption, most of them were able to maintain a low, though detectable, viral load for some time. The researchers then stopped the treatment and carefully watched the patients over a period of up to five years. If the number of viruses in the patients' blood rose too high, the researchers gave the patients HAART again until the number of viruses fell again. In about half the patients, treatment needed to be restarted within a year because the viruses had started becoming more numerous in the blood. The doctors had hoped that it would take much longer for the number of viruses to reach this level. In other words, giving patients “drug holidays” did not help to keep the virus at bay for long periods of time.
What Are the Limitations of the Study?
It is relatively rare for doctors to be able to diagnose HIV shortly after an individual becomes infected with the virus. Many people have HIV for a long time before they see a doctor. Therefore, even if the STI strategy had worked, it would only have been relevant to a few patients. In addition, the study was small and preliminary, so we have to be careful about reading too much into the results. A limitation in the study is that it did not address whether there might be a long-term clinical benefit despite a gradual increase in viral load.
What Does This Study Mean for Patients?
It is important to remember that this was an experimental trial—patients with HIV should not stop taking antiretroviral drugs unless their doctor specifically tells them to do so. Although it looks as though STI may not work in the way everyone had hoped, these results may help scientists develop an HIV vaccine that is designed to keep the disease at bay. Whether early treatment of acute infection has an overall benefit in terms of time-to-development of AIDS or need for long-term treatment after drug discontinuation will need to be answered in larger clinical trials designed to answer these important questions.
Resources on the Web.
AIDSinfo: http://www.aidsinfo.nih.gov/
AIDSmap: http://www.aidsmap.com/
Medline Plus AIDS Information: http://www.nlm.nih.gov/medlineplus/aids.html
We thank all study participants for their invaluable help and Roche Molecular Systems for generous support in providing HIV-1 Amplicor viral load testing kits. We also thank V. DeGruttola and K. Maghsouti for useful comments on the manuscript and valuable help with statistical analyses.
This study was supported by the Howard Hughes Medical Institute (BDW), the Doris Duke Charitable Foundation (BDW, MA, and ESR), the National Institutes of Health (BDW, ESR, and MA.), the Swiss Foundation for Grants in Biology and Medicine (DEK), and the Deutsche Forschungsgemeinschaft (ML).
Comparative data on CD4+ T cell counts in untreated chronic HIV-1 infection were collected by the MACS and analyzed and prepared by Alvaro Muñoz. MACS centers (principal investigators) are located at the Johns Hopkins Bloomberg School of Public Health (Joseph Margolick), Howard Brown Health Center and Northwestern University Medical School (John Phair), University of California at Los Angeles (Roger Detels), University of Pittsburgh (Charles Rinaldo), and Data Analysis Center (Lisa Jacobson). The MACS is funded by the National Institute of Allergy and Infectious Diseases, with additional supplemental funding from the National Cancer Institute and the National Heart, Lung, and Blood Institute, grants UO1-AI-35042, 5-M01-RR-00052 (General Clinical Research Center), UO1-AI-35043, UO1-AI-37984, UO1-AI-35039, UO1-AI-35040, UO1-AI-37613, and UO1-AI-35041.
This work was supported by the following: the Harvard Medical School Center for AIDS Research, the Acute Infection Early Disease Research Program (grants RO1 AI 29568, RO1 AI050429, and RO1 AI 44656), and the Doris Duke Charitable Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Citation: Kaufmann DE, Lichterfeld M, Altfeld M, Addo MM, Johnston MN, et al. (2004) Limited durability of viral control following treated acute HIV infection. PLoS Med 2(2): e36.
Note Added in Proof
Recent studies in persons with chronic HIV infection treated with HAART have now shown that immunization with whole inactivated HIV can enhance HIV-specific CD8+ T cell function as measured by the ability to proliferate in response to viral antigens in vitro [64].
Abbreviations
CCRchemokine receptor
GBV-CGB virus C
HAARThighly active antiretroviral therapy
HIV-1human immunodeficiency virus 1
MACSMulticenter AIDS Cohort Study
PBMCperipheral blood mononuclear cell
SFCspot-forming cell
STIsupervised treatment interruption
==== Refs
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 10.1371/journal.pmed.0010047SynopsisInfectious DiseasesMalariaMalaria Vaccine Trial Results Are Negative, but Important Synopsis11 2004 26 10 2004 1 2 e47Copyright: © 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 Randomised, Double-Blind, Controlled Vaccine Efficacy Trial of DNA/MVA ME-TRAP Against Malaria Infection in Gambian Adults
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A malaria vaccine called ME-TRAP, which targets the pre-erythrocytic stage of the disease, was not effective at reducing natural infection rates in semi-immune African adults, according to the report of a randomized controlled trial published this month in PLoS Medicine. “This first field efficacy trial was an important milestone in the progression of new recombinant vectored vaccines to deployable products,” says Adrian Hill (University of Oxford, United Kingdom), the lead investigator of the study. “The safety profile was excellent and the efficacy data provide a first indication of the levels of cellular immunogenicity that will be required for preventing infection,” he says.
Hill and his co-workers used a heterologous prime–boost vaccination technique. They gave the volunteers two vaccines—a DNA priming vaccine followed by a modified vaccinia virus Ankara (MVA) that acted as a booster. The DNA and MVA vaccines both had the same insert coding for thrombospondin-related adhesion protein (TRAP; a pre-erythrocytic antigen) and a string of T cell epitopes (called ME for “multiple epitopes”).
Hill's team had previously shown that ME-TRAP vaccines given in prime–boost sequence could induce large T cell responses in healthy volunteers from the UK and could delay parasitemia in a sporozoite challenge test (Nat Med 9: 729–735). The next step was to do a randomized controlled trial in Gambia to determine whether this vaccination strategy could provide protection against natural Plasmodium falciparum infection.
The researchers recruited volunteers from 13 Gambian villages that were close to the alluvial flood plain and so were at high risk of developing malaria. They randomly assigned the 372 volunteers to receive either two doses of the DNA ME-TRAP vaccine followed by a single dose of MVA ME-TRAP, or three doses of rabies vaccine. This three-dose schedule is similar to the one used by the World Health Organization/United Nations Children's Fund Expanded Program on Immunization. Two weeks before the third dose was given, all the volunteers received antimalarial drugs to clear blood-stage P. falciparum infections.
The time to first infection, the primary end point of the study, was similar in the two groups, with an estimated vaccine efficacy of only 10%. However, the effector T cell response to the TRAP antigen T9/96, measured one week after the third vaccination, was 80 times higher in the DNA/MVA vaccine group than in the rabies vaccine group.
“It is absolutely crucial that results like these are published, since the failures, as well as the successes, need to be documented if we are to move towards rational strategies for optimizing malaria vaccines,” says Tom Smith from the Swiss Tropical Institute, who was not involved in the study. “At the same time, it makes sense to move on quickly without shedding too many tears, in a field that is moving much faster than it was before the recent injections of money from the Gates Foundation, but where it is still impossible to second-guess the results of field trials. This is partly because we do not have any good proxy measures of effective immunity in P. falciparum, and partly because this is a fertile area for trying out new techniques, such as DNA vaccines, where there is still a lot to learn.”
Hill is planning to do further trials that address the important question of whether this type of vaccine can prevent the symptoms of malaria. “The next step,” says Hill, “is to assess newer vaccine regimes that employ two viral vectors rather than DNA and to study prevention of malaria rather than infection.”
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PLoS MedPLoS MedpmedplosmedPLoS Medicine1549-12771549-1676Public Library of Science San Francisco, USA 10.1371/journal.pmed.0010048SynopsisImmunologyInfectious DiseasesHIV/AIDSInfectious DiseasesHIV Infection/AIDSImmunology and allergySupervised Treatment Interruptions Fail to Control HIV-1 Viremia Synopsis11 2004 26 10 2004 1 2 e48Copyright: © 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.
Limited Durability of Viral Control following Treated Acute HIV Infection
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Highly active antiretroviral therapy (HAART) for the treatment of individuals infected by HIV-1 is limited by high costs, drug resistance, and drug-related toxicities. This has led researchers to investigate new treatment options, including ways to boost immune responses to better control HIV. One such approach has been termed supervised treatment interruption (STI)—in which HAART is intermittently stopped once viral load has been reduced to a low level, in order to boost natural immunity by brief exposure to virus. The goal is to allow for the eventual discontinuation of drug treatment.
ELISPOT assays detect HIV-specific cytotoxic T lymphocyte responses
Preliminary evidence, published by Bruce Walker and his colleagues from Harvard Medical School in Nature in 2000, suggested that this approach worked in persons treated in the earliest stages of acute HIV infection. HIV-1 viral loads in newly infected patients remained suppressed for a median of six months after therapy had been stopped. However, a follow up paper, published this month in PLoS Medicine by the same research group, shows that the viral load rebounded in eight of the 14 patients by one year.
“The findings are very straightforward and very important,” comments Danny Douek from the Vaccine Research Center, National Institutes of Health, United States, who was not involved in the study. “In almost every case, virus rebounded and no clinical benefit from the interruption could be determined.”
Walker's team first considered the possibility of STI in 1997 after they demonstrated that HAART given to patients recently infected with HIV could protect T helper cells, which are normally destroyed in the earliest stages of infection. They hypothesized that early treatment of acute HIV-1 infection with HAART might boost the immune response, allowing it to control the HIV-1 infection without the need for continuous therapy. “We did not know at that time whether the T helper cells would be functional,” explains Walker. “The only way to tell this was to stop medications and see if the immune response could control the virus.”
To test this hypothesis the researchers did an open-label trial of STIs; they published data from six months follow-up in the Nature paper. “The key finding was that we were able to get at least transient control of virus in all eight persons studied, and in five of eight the viral load was less than 500 copies (very low!) at the time of publication,” explains Walker. However, at that point they did not know how long the protective effects would last.
The first evidence that protection was not complete came two years later when Walker's team reported a case of superinfection; one of the patients in the original experiment was infected with a second strain of HIV, even though the first virus was still well controlled. “This paper was important because it indicated that the amount of immunity might be enough for the person's own virus, but might not protect against closely related viruses circulating in the population,” says Walker.
The PLoS Medicine study adds more concern since it shows that although most persons can indeed transiently control their own virus, they do so for only a limited amount of time. “We expanded the study to 14 persons, and now have about five years of follow-up on some of the patients,” says Walker. “Although we were able to use early treatment and structured treatment interruption to boost immunity and have 11 of 14 patients control their virus, most of the persons ultimately ‘broke through,’ meaning that they had a recurrence of viremia.” At the present time the researchers do not know what causes the loss of viral control.
Walker and colleagues conclude that treatment interruptions should probably be avoided outside the setting of controlled clinical trials, whereas Douek goes a step further: “The study shows that even early short-term treatment and structured treatment interruptions, using current strategies, impart only transient benefit and are unlikely to serve as a reasonable therapeutic option in the future.”
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1552355810.1371/journal.pbio.0020377Research ArticleAnimal BehaviorPhysiologyMus (Mouse)BMAL1 and CLOCK, Two Essential Components of the Circadian Clock, Are Involved in Glucose Homeostasis Metabolism and Peripheral ClocksRudic R. Daniel
1
McNamara Peter
2
Curtis Anne-Maria
1
Boston Raymond C
3
Panda Satchidananda
4
Hogenesch John B
4
FitzGerald Garret A garret@spirit.gcrc.upenn.edu
1
1Center for Experimental Therapeutics, University of PennsylvaniaPhiladelphia, PennsylvaniaUnited States of America2Phenomix Corporation, La Jolla, CaliforniaUnited States of America3School of Veterinary Medicine, University of PennsylvaniaKennett Square, PennsylvaniaUnited States of America4The Genomics Institute of the Novartis Research FoundationLa Jolla, CaliforniaUnited States of America11 2004 2 11 2004 2 11 2004 2 11 e37711 2 2004 31 8 2004 Copyright: © 2004 Rudic 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.
Sleeping, Waking, ... and Glucose Homeostasis
Circadian timing is generated through a unique series of autoregulatory interactions termed the molecular clock. Behavioral rhythms subject to the molecular clock are well characterized. We demonstrate a role for Bmal1 and Clock in the regulation of glucose homeostasis. Inactivation of the known clock components Bmal1 (Mop3) and Clock suppress the diurnal variation in glucose and triglycerides. Gluconeogenesis is abolished by deletion of Bmal1 and is depressed in Clock mutants, but the counterregulatory response of corticosterone and glucagon to insulin-induced hypoglycaemia is retained. Furthermore, a high-fat diet modulates carbohydrate metabolism by amplifying circadian variation in glucose tolerance and insulin sensitivity, and mutation of Clock restores the chow-fed phenotype. Bmal1 and Clock, genes that function in the core molecular clock, exert profound control over recovery from insulin-induced hypoglycaemia. Furthermore, asynchronous dietary cues may modify glucose homeostasis via their interactions with peripheral molecular clocks.
Besides regulating various behavioral rhythms, the molecular clock plays a role in the control of glucose homeostasis
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Introduction
The master clock, which, in mammals, resides in the hypothalamic suprachiasmatic nucleus (SCN), is thought to synchronize multiple peripheral oscillators to ensure temporal coordination of behavior and metabolism. Peripheral clocks amplify or dampen central rhythms or exhibit autonomous behavior to facilitate local adaptive responses (Hastings et al. 2003). The central clock may communicate to modulate or entrain rhythms in the periphery via hormones (McNamara et al. 2001) or hemodynamic cues. Asynchronous environmental cues, such as eating, also influence the autonomous behavior of peripheral clocks (Damiola et al. 2000; Stokkan et al. 2001).
The variation in sleep and wakefulness (activity) is perhaps the most well-known circadian rhythm. Surgical ablation of the SCN in mice (Ibuka et al. 1980; Welsh et al. 1988) and rats (Ibuka et al. 1977; Mosko and Moore 1979) abolishes the nocturnal burst in locomotor activity. Similarly, disruption and/or mutation of Bmal1 (Bunger et al. 2000) or Clock (Vitaterna et al. 1994), transcription factors that compose the positive limb of an autoregulatory feedback loop in the core molecular clock (Young and Kay 2001; Reppert and Weaver 2002), also impairs circadian behavior. Bmal1 and Clock may influence behavioral rhythms by regulating the firing rate of SCN neurons (Herzog et al. 1998; Deboer et al. 2003).
Genes relevant to the molecular clock are also expressed in peripheral tissues (Akhtar et al. 2002; Kita et al. 2002; Panda et al. 2002; Storch et al. 2002; Oishi et al. 2003) where approximately 5%–10% of the transcriptome is subject to circadian oscillation (Albrecht and Eichele 2003). Although the precise role of peripheral clocks and the mechanisms that link them to the SCN remain largely obscure, genetic mutation or deletion has implicated peripheral clocks in the regulation of some aspects of cellular function, including division (Matsuo et al. 2003), estrous cyclicity (Miller et al. 2004), and phospholipid metabolism (Marquez et al. 2004). Glucose and lipid homeostasis are also known to exhibit circadian variation (Seaman et al. 1965; Malherbe et al. 1969; Gagliardino and Hernandez 1971; Schlierf and Dorow 1973). Surgical ablation of the SCN impairs the control of glucose homeostasis (la Fleur et al. 2001). However, the proximity of satiety centres to the SCN has potentially confounded interpretation of these results. Indeed, there is no direct evidence implicating the molecular clock in the regulation of glycaemia or insulin sensitivity (Si).
Our studies revealed a profound role for core clock genes—Bmal1 and Clock—in regulating recovery from insulin-induced hypoglycaemia. Furthermore, the impact of a high-fat diet (HF) was to amplify the diurnal variation in glucose tolerance and Si in a manner dependent on the Clock gene. These studies suggest that the temporal distribution of a caloric load may influence the response to insulin and that circadian variability in glucose homeostasis may be subject to modulation by asynchronous dietary cues.
Results
We examined the role of the molecular clock in glucose homeostasis by using mice in which core clock genes are impaired (Clockmut) or deficient (Bmal1−/−). Both plasma glucose and triglycerides were subject to circadian variation in wild-type (WT) mice, peaking at approximately circadian time point 4 (CT4) and CT28 (where CT0 is subjective day beginning at 7 AM, and CT12 is subjective night beginning at 7 PM) (Figure 1A and 1B), as reported previously (Seaman et al. 1965; Schlierf and Dorow 1973). We also observed that corticosterone (Figure 1C), which stimulates gluconeogenesis during hypoglycaemia (Cryer 1993), and adiponectin (Figure 1D), which has been associated with insulin resistance (Yamauchi et al. 2001; Maeda et al. 2002), oscillated significantly, but out of phase with the glucose and triglyceride rhythms. Diurnal variation in glucose and triglycerides, but not in corticosterone, was disrupted in the mutant mice (Table 1).
Figure 1 Circadian Variation of Glucose, Triglyceride, and Hormone Levels in Circulating Blood
Plasma from whole blood isolated from unchallenged WT mice at different CTs was analyzed for glucose (A), triglyceride (B), corticosterone (C), and adiponectin levels (D) (n = 12 per time point). Results for Bmal1
−/− and Clockmut mice are shown in Table 1.
Table 1 Clock-Controlled Metabolic Rhythms
Utilizing peak and trough CTs described in Figure 2A, WT mice showed circadian variation in glucose and triglycerides at CT5 and CT17 that was absent in Bmal1−/− mice, though corticosterone rhythms were preserved in the mice with disrupted circadian rhythms. Values are presented as mean ± SEM; n = 7–12
*p < 0.05 versus corresponding time point (one-way ANOVA with the Kruskal-Wallis test)
ND, no data
Although there was no clear rhythm in the hypoglyacemic response to insulin, recovery of blood glucose exhibited a robust circadian variation (Figure 2A), with an excessive rebound from the effects of insulin evident at subjective dawn (CT19 and CT25) (Figure 2A). Insulin caused a profound hypoglyacemic response, independent of clock time, in both Bmal1
−/− and Clockmut mice (Figure 2B). This response was more pronounced in the former, consistent with the comparative severity of the molecular and behavioral phenotypes between the Bmal1−/− and Clockmut animals (King et al. 1997; Bunger et al. 2000). Despite exacerbation of the hypoglycaemic response to insulin in the mutants, the counterregulatory responses of both corticosterone and glucagon were retained (Figure 2C and 2D).
Figure 2 Disruption of Genes in the Core Molecular Clock Alters the Response to Insulin
(A) Insulin tolerance (IT) was examined in WT mice on CT7, CT13, CT19, and CT25 at 30 min, 60 min, and 90 min after insulin injection (n = 12 per time point, *p < 0.01).
(B) IT was examined in WT (black line), Bmal1
−/− (blue line), and Clockmut mice (green line) at CT1 (i) and CT13 (ii) (n = 6–10, *p < 0.05, †p < 0.01, ††p < 0.001).
(C and D) Plasma levels of the counterregulatory hormones corticosterone (C) and glucagon (D) were assessed 60 min after insulin injection in Bmal1
−/− and Clockmut mice (n = 7, corticosterone assay; samples were pooled for glucagon assay, *p < 0.05).
Gluconeogenesis also contributes to restoration of blood glucose after insulin-induced hypoglycaemia. Consistent with this observation, conversion of exogenously administered pyruvate to glucose, which reflects gluconeogenesis (Miyake et al. 2002), was impaired in the Clockmut animals. This impairment was most marked in Bmal1−/− mice, while Bmal1+/− and Clockmut mice exhibited an intermediate phenotype when compared with WT littermate controls (Figure 3A). Furthermore, activity of the key rate-limiting enzyme of gluconeogenesis, phosphoenolpyruvate carboxykinase (PEPCK), exhibited diurnal variation in the liver and aorta that was blunted in Clockmut mice (Figure 3B). PEPCK activity in kidney was antiphasic to the rhythm in aorta and liver and was unimpaired in Clockmut mice (Figure 3B), suggesting tissue-specific regulation of enzyme activity.
Figure 3 Impaired Gluconeogenesis in Mice with a Disrupted Circadian Clock
(A) Pyruvate tolerance was compared among WT (black line), Bmal1+/− (blue line), and Bmal1−/− (purple line), and Clockmut (green line) mice at CT7 (n = 6–10).
(B) Relative PEPCK activity (units are expressed as luciferase activity × 103) was measured in liver (i), aorta (ii), and kidney (iii) from WT (white bars) and Clockmut mice (green bars).
The frequent sampling intravenous glucose tolerance test (FSIGT) was performed to assess more precisely the impact of the molecular clock on sensitivity to insulin. This test provides an estimate of Si, consistent with that obtained by the euglycaemic clamp (Pacini et al. 2001). Additionally, data modeling provides estimates of glucose-mediated glucose disposal (Sg), insulin secretion, and Si. Si and insulin secretion, but not Sg, exhibited a diurnal variation in WT mice fed a regular chow diet (RC) (Table 2). Circadian variation of glucose and lipid homeostasis might condition the metabolic response to asynchronous environmental cues, such as diet, that impinge on Si. Dyslipidemia coincides with insulin resistance in the metabolic syndrome (Brotman and Girod 2002), and a diet high in fat impairs Si (Grundleger and Thenen 1982; Coulston et al. 1983). Both HF-fed WT and HF-fed Clockmut mice increased body weight significantly and to a similar degree in comparison to their age-matched, RC-fed controls (Table 3). Body fat composition averaged 17.6% of lean body mass in RC-fed WT mice, rising to 27.7% (p < 0.002) on high-fat feeding. Again, fat composition was not significantly altered by the presence of the Clock mutation (Table 3).
Table 2 Indices of Noninsulin- and Insulin-Mediated Parameters of Glucose Disposal Derived from Modelling of FSIGT Data at CT1 and CT13
Values are presented as mean ± fractional standard deviation (n = 6–7 per group)
a
p < 0.001 versus HF group (two-tailed, Student's t-test)
b
p < 0.001 versus respective group at CT1
G0, blood glucose concentration at 1 minute post-glucose bolus; ND, valid Si value could not be determined
Table 3 Body Mass Index Was Assessed in Mice Feeding on RC and HF
Values are presented as mean ± SEM; n = 13 per group for WT; n = 7 per group for subsequent parameters
*p < 0.05 compared to RC (two-tailed Student's t-test); **p < 0.01 (two tailed Student's t-test)
BMC, bone mineral content
Glucose tolerance on an RC trended towards an intolerant phenotype at CT1 versus CT13, but this difference did not attain significance (Figure 4A). This is consistent with the temporal variation in insulin secretion observed in RC-fed WT mice in the FSIGT experiment (Table 2). However, when the mice were fed HF for 2 mo, this glycaemic excursion at CT1 evoked by the environmental challenge was amplified and significant (two way analysis of variance [ANOVA]; F = 63.2, p < 0.001) (Figure 4A). Similarly, although the hypoglycaemic response to insulin was not different in mice fed regular chow at CT1 and CT13 (Figure 4B), the HF induced a significant temporal variation (Figure 4B). Thus, the impact of a high fat intake on carbohydrate metabolism in WTs includes an amplification of the diurnal variation in the response to both glucose and insulin. This coincides with a modest impairment in the ability to restore euglycaemia after insulin. A similar impairment resulting from a defect in gluconeogenesis has been observed in rats (Oakes et al. 1997). The mutants failed to exhibit a significant time-dependent variation in their response to glucose or insulin, again reminiscent of the RC-fed, WT phenotype (Figure 4).
Figure 4 The Molecular Clock Conditions HF-Induced Circadian Variation in Glucose Homeostasis
(A) Glucose tolerance (GT) in RC-fed WT mice (i), HF-fed WT mice (ii), and HF-fed Clockmut mice (iii).
(B) IT in RC-fed WT mice (i), HF-fed WT mice (ii), and HF-fed Clockmut mice (iii) at respective times (n = 6–8; *p < 0.05, †p < 0.01).
Mice were also subjected to extended high-fat feeding (11 mo versus 2 mo). Long-term hyperlipidemia is known to induce frank diabetes with impaired release of insulin (Johnson et al. 1990), in contrast to short-term, high-fat feeding, which increases release of insulin, but impairs the response to it (Linn et al. 1999). The extended HF impaired insulin secretion, reflected by its marked reduction to negative values in HF-fed WT mice (Table 2). The lack of insulin secretion resulted in calculated values of Si that were imperceptibly low (see Material and Methods). However, Sg, insulin secretion, and Si were restored to a WT phenotype in Clockmut mice that were also HF-fed for 11 mo (Table 2). This is, again, consistent with a role for the molecular clock in conditioning the response of glucose metabolism to the intake of dietary fat. Remarkably, mutation of the molecular clock protected against the development of frank diabetes caused by chronic high-fat feeding.
Discussion
Maintenance of blood glucose levels within a narrow range is critical to mammalian survival, and environmental cues can trigger appropriate tissue disposition of glucose through adaptive behaviors such as in hibernation (Castex and Hoo-Paris 1987) or the “fight-or-flight” response (Surwit et al. 1992). In this sense, glucose regulation is a fundamental and ancestral defence mechanism. Our studies suggest that Bmal1 and Clock, core components of the molecular clock, contribute substantially to regulation of recovery from the hypoglycaemic response to insulin. However, other mechanisms also impinge on this ancient adaptive response. Thus, impaired recovery from insulin-induced hypoglycaemia is observed in mice lacking proopiomelanocortin. These animals lack adrenal glands and melanocortins and exhibit a defective glucagon response to insulin-induced hypoglycaemia (Hochgeschwender et al. 2003). They contrast with the Bmal1
−/− and Clockmut mice, where the counterregulatory hormone response is unimpaired. Thus, steroids, epinephrine, and glucagon appear to facilitate recovery from insulin-induced hypoglycaemia in a manner distinct from, but complementary to, the molecular clock.
An assumption intrinsic to our studies is that the phenotypes revealed in the mutant mice are attributable to their function as core elements of the molecular clock. However, as trans-activators, both Clock and Bmal1 may have pleiotropic effects independent of the circadian clock that could impinge on metabolism. Several lines of evidence argue against this hypothesis. First, genes relevant to these metabolic phenotypes display circadian oscillations in their steady-state mRNA levels (Young et al. 2001; Oishi et al. 2003). In addition, the mRNA levels of many of these key proteins are phase-aligned with Per1 (e.g., Enolase 3, Pgam, Transketolase, Lipase, Lpl, Dgat1, Ppar alpha) or Per2 (e.g., Mod1, Lpl, Pepck, lipin 1) (unpublished data). In addition, many of their mRNAs are at lower levels in Bmal1
−/− (e.g., Mod1, Pepck, Enolase3, Pgam) (unpublished data), consistent with a direct role of Bmal1 in their transcription. Thirdly, these metabolic parameters are disrupted in both circadian mutants with the same rank order of potency as the locomotor activity phenotypes (Bmal1−/− > Clockmut). Thus, the most parsimonious interpretation is that the observed metabolic deficiencies in the Bmal1
−/− and Clockmut mice are due to their roles in the circadian clock, rather than to “off-clock” effects.
We observed that the impact of HF on glucose homeostasis was apparently to emphasize the role of the molecular clock. Diet has previously been shown to interact with peripheral clocks. Changes in feeding shift the circadian pattern of gene expression in the liver, but not in the master clock in the SCN (Damiola et al. 2000), demonstrating the importance of food as a cue to circadian control. Individual constituents of food could also provide discrete stimuli. For example, glucose alone can induce rhythmic gene expression in isolated fibroblasts (Hirota et al. 2002). Thus, dietary composition, the size and timing of a feed might all be expected to interact differentially with an underlying circadian regulation of metabolic control.
Alterations in dietary content, the availability of “fast food,” inactivity, and sociocultural factors have all been implicated in the emergence of the metabolic syndrome as a major challenge to the public health (Zimmet et al. 2001). However, while mechanistic integration of the diverse elements of the syndrome has proven elusive, our studies suggest that timing may influence the functional consequences of ingesting a caloric load.
Materials and Methods
Animals
Mice were acclimatized for 2 wk in 12 h light–12 h dark cycles before being subjected to a 36-h period of constant darkness followed by experimentation in darkness. Experimental chronology is measured in CT, subjective day beginning at 7 AM (CT0), and subjective night beginning at 7 PM (CT12).
Diet
WT and Clockmut mice were placed on an HF (Teklad, TD02435) and compared to age-matched WT mice on a regular chow diet (RC). Mice were on RC for 8 wk except for those subjected to FSIGT where they received RC for 11 mo. Body mass composition was measured by dual energy X-ray absorptiometry at 10 mo.
Intraperitoneal tolerance
Tests were performed as described (Klaman et al. 2000) with a diminution in the glucose bolus (0.1 g/kg).
Intravenous glucose tolerance test and minimal modeling
The tolerance test was performed as described (Pacini et al. 2001) in unanesthetized mice, and the minimal model of Bergman et al. (1979) was applied to the data using MINMOD software (Boston et al. 2003). The derived values were Si, Sg, and acute insulin response to glucose, which measures insulin secretion. Si is the ratio of insulin delivery rate to the interstitium to insulin extraction rate from the interstitium. Long-term feeding of HF to WT mice resulted in imperceptibly small insulin sensitivity values. This could be the consequence of impaired delivery of insulin to the interstitium, exacerbated extraction rate, or a combination of both factors. Insulin secretion is derived from area under the insulin curve, above basal, from 0 to 10 min after glucose infusion; and disposition index, which equals the product of insulin sensitivity multiplied by insulin secretion and measures the degree to which insulin sensitivity can be compensated for by elevated insulin secretion (Pacini et al. 2001).
Assay methods
Insulin, leptin, corticosterone, and glucagon levels were measured by immunoassays from Crystalchem (Downers Grove, Illinois, United States), ICN Biochemicals (Costa Mesa, California, United States), and Linco Research (St. Charles, Missouri, United States). Plasma glucose was measured by the glucose oxidase method using a glucose analyzer machine for FSIGT and by glucometer for the intraperitoneal tolerance test. PEPCK activity was quantitated by a bioluminescent method (Wimmer 1988).
Statistical analysis
The significance of differences amongst the tolerance test curves was assessed by distribution-free two-way ANOVA with a Bonferroni correction. FSIGT data were tested by one-way ANOVA with the Kruskal-Wallis test. Paired Student's t-tests were used to perform comparisons of corticosterone levels before and after insulin injection in Bmal−/− mice and between WT and Clockmut mice. Plasma samples for glucagon analysis were pooled and were thus not compared by a formal statistical analysis. Results are presented as mean ± standard error of the mean (SEM), except for the FSIGT data (Table 2), presented as mean ± fractional standard deviation. Differences were considered significant when p < 0.05.
We wish to thank Christopher A. Bradfield and Celeste Simon for graciously providing MOP3 knockout mice and Joseph S. Takahashi and Amita Sehgal for providing Clock mutant mice. We also thank the Penn Diabetes Center/Mouse Phenotyping, Physiology, and Metabolism Core (NIH P30DK19525). We are indebted to Daniel J. Rader, Karen Teff, and Mitch Lazar for their helpful suggestions. Finally, we wish to thank Darko Stefanovski, Margaret Lucitt, and Eileen Clark for technical assistance. Supported in part by grants from the National Institutes of Health (HL 62250 and HL 54500) and fellowship grants from the American Heart Association to RDR (0225478U) and to PM (0160504U). GAF is the Robinette Foundation Professor of Cardiovascular Medicine and the Elmer Bobst Professor of Pharmacology.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Author contributions. RDR, PM, and GAF conceived and designed the experiments. RDR, PM, AMC, and SP performed the experiments. RDR, RB, and JH analyzed the data. RB and JH contributed reagents/materials/analysis tools. RDR wrote the paper.
Academic Editor: Steve O'Rahilly, University of Cambridge
Citation: Rudic RD, McNamara P, Curtis AM, Boston RC, Panda S, et al. (2004) BMAL1 and CLOCK, two essential components of the circadian clock, are involved in glucose homeostasis. PLoS Biol 2(11): e377.
Abbreviations
Bmal1−/−
Bmal knockout mice
Clockmut
Clock mutant mice
CT[number]circadian time [designated time point]
FSIGTfrequent sampling intravenous glucose tolerance test
GTglucose tolerance
HFhigh-fat diet
ITinsulin tolerance
PEPCKphosphoenolpyruvate carboxykinase
RCregular chow diet
SCNsuprachiasmatic nucleus
Sgglucose-mediated glucose disposal
Siinsulin sensitivity
WTwild-type
==== Refs
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| 15523558 | PMC524471 | CC BY | 2021-01-05 08:21:16 | no | PLoS Biol. 2004 Nov 2; 2(11):e377 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020377 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 1552355910.1371/journal.pbio.0020380Research ArticleBioinformatics/Computational BiologyCell BiologyEvolutionMolecular Biology/Structural BiologyEukaryotesEubacteriaComponents of Coated Vesicles and Nuclear Pore Complexes Share a Common Molecular Architecture Nuclear Pore Complexes and Coated VesiclesDevos Damien
1
Dokudovskaya Svetlana
2
Alber Frank
1
Williams Rosemary
2
Chait Brian T
3
Sali Andrej sali@salilab.org
1
Rout Michael P rout@rockefeller.edu
2
1Departments of Biopharmaceutical Sciences and Pharmaceutical Chemistry and California Institute for Quantitative Biomedical Research, University of CaliforniaSan Francisco, CaliforniaUnited States of America2Laboratory of Cellular and Structural Biology, Rockefeller UniversityNew York, New YorkUnited States of America3Laboratory of Mass Spectrometry and Gaseous Ion Chemistry, Rockefeller UniversityNew York, New YorkUnited States of America12 2004 2 11 2004 2 11 2004 2 12 e38013 7 2004 7 8 2004 Copyright: © 2004 Devos 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 Structural Analysis of Eukaryotic Membrane Evolution
Numerous features distinguish prokaryotes from eukaryotes, chief among which are the distinctive internal membrane systems of eukaryotic cells. These membrane systems form elaborate compartments and vesicular trafficking pathways, and sequester the chromatin within the nuclear envelope. The nuclear pore complex is the portal that specifically mediates macromolecular trafficking across the nuclear envelope. Although it is generally understood that these internal membrane systems evolved from specialized invaginations of the prokaryotic plasma membrane, it is not clear how the nuclear pore complex could have evolved from organisms with no analogous transport system. Here we use computational and biochemical methods to perform a structural analysis of the seven proteins comprising the yNup84/vNup107–160 subcomplex, a core building block of the nuclear pore complex. Our analysis indicates that all seven proteins contain either a β-propeller fold, an α-solenoid fold, or a distinctive arrangement of both, revealing close similarities between the structures comprising the yNup84/vNup107–160 subcomplex and those comprising the major types of vesicle coating complexes that maintain vesicular trafficking pathways. These similarities suggest a common evolutionary origin for nuclear pore complexes and coated vesicles in an early membrane-curving module that led to the formation of the internal membrane systems in modern eukaryotes.
Structural similarities between the proteins of a nuclear pore subcomplex and proteins comprising vesicle coating complexes indicate a common origin for nuclear pore complexes and coated vesicles
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Introduction
The ability to sharply curve membranes was a defining event in the evolution of early eukaryotes, allowing the formation of endomembrane systems (Blobel 1980). In modern eukaryotes, these systems have become elaborate internal membranes, such as the Golgi apparatus, the endoplasmic reticulum (ER), and the nuclear envelope (NE). To date three major kinds of transport vesicles, distinguished by the compositions of their protein coat complexes, have been shown to traffic between these internal membranes and the plasma membrane: First, the clathrin/adaptin complexes are responsible for endocytosis and vesicular trafficking between the Golgi, lysosomes, and endosomes; second, the COPI complex mediates intra-Golgi and Golgi-to-ER trafficking; and lastly, the COPII complex supports vesicle movement from the ER to the Golgi (reviewed in Kirchhausen 2000a, 2000b; Boehm and Bonifacino 2001; Bonifacino and Lippincott-Schwartz 2003; Lippincott-Schwartz and Liu 2003).
The NE is contiguous with the ER and delineates the nucleus. It is made of an inner and outer membrane that together form a barrier between the nucleoplasm and the cytoplasm. This barrier is perforated by nuclear pore complexes (NPCs), which form pores between the inner and outer NE membranes by stabilizing a sharply curved section of connecting pore membrane. NPCs are approximately 50-MDa octagonally symmetric cylinders that function as the only known mediators of nucleocytoplasmic exchange; while permitting the free flow of small molecules, they restrict macromolecular trafficking to selected cargoes that are recognized by cognate transport factors. NPCs are found in all eukaryotic cells and are composed of a broadly conserved set of proteins, termed nups (reviewed in Rout and Aitchison 2001; Bednenko et al. 2003; Rout et al. 2003; Suntharalingam and Wente 2003; Fahrenkrog et al. 2004). Although the nups have been fully cataloged for both yeast (Saccharomyces) (Rout et al. 2000) and vertebrates (Cronshaw et al. 2002), there is currently little information concerning their origin and evolution. To this end, protein structures are helpful because it is easier to recognize similarities in structure than in sequence, especially for distantly related proteins. Thus, we have characterized the structures of seven proteins forming a core building block of the NPC, termed the yNup84 subcomplex in Saccharomyces and the vNup107–160 subcomplex in vertebrates. These structures reveal how the nuclear pore complex could have evolved from organisms with no analogous transport system.
Results
The yNup84/vNup107–160 subcomplex has a molecular weight of approximately 600 kDa and has been shown in yeast to be flexible (Siniossoglou et al. 1996; Siniossoglou et al. 2000; Lutzmann et al. 2002), presenting a considerable challenge to conventional experimental methods for structure determination; thus, we used a computational approach that relies on a database of experimentally determined structures (Marti-Renom et al. 2000). We first focused on the component nups of the yNup84 subcomplex: ySeh1, ySec13, yNup84, yNup85, yNup120, yNup133, and yNup145C, whose corresponding vertebrate homologs are, respectively, vSec13 l, vSec13R, vNup107, vNup75, vNup160, vNup133, and vNup96 (Siniossoglou et al. 1996; Fontoura et al. 1999; Siniossoglou et al. 2000; Cronshaw et al. 2002; Lutzmann et al. 2002; Boehmer et al. 2003; Harel et al. 2003; Walther et al. 2003; Loiodice et al. 2004). For putative domains in each of these nups, we first applied two threading programs to assign structure folds based on similarity to known protein structures (templates) (Marti-Renom et al. 2000) (see Materials and Methods). The corresponding sequence-structure alignments were refined and used to generate three-dimensional models of the nup domains, followed by evaluation of the models. Our analyses predicted that every nup in the yNup84/vNup107–160 subcomplex consists of a β-propeller domain, an α-solenoid domain, or both (Figure 1; Table 1). β-propellers contain several blades arranged radially around a central axis, each blade consisting of a four-stranded antiparallel β-sheet; α-solenoid domains are composed of numerous pairs of antiparallel α-helices stacked to form a solenoid (Figure 1) (Neer et al. 1994; Andrade et al. 2001a; Andrade et al. 2001b). While we have not defined the precise details of each domain, such as the exact shapes and numbers of propeller blades and solenoid repeats, the overall fold assignments for each nup are clear. These predictions indicate that yNup84, yNup85, and yNup145C all mainly consist of an α-solenoid domain, whereas yNup120 and yNup133 contain both an amino-terminal β-propeller and a large carboxyl-terminal α-solenoid region. Both ySec13 and ySeh1 are predicted to be almost entirely single-domain β-propellers of six and seven blades, respectively. These latter two proteins fall into the well-conserved class of tryptophan/aspartic acid (WD) repeat-containing β-propeller proteins. For both proteins, homology with the WD-repeat β-propellers has been reported previously (Saxena et al. 1996; Siniossoglou et al. 1996; Yu et al. 2000) and is confirmed here.
Figure 1 Ribbon Representation of Nup Models
β-sheets (β-propellers) are colored cyan and α-helices (α-solenoids) are colored magenta. Gray dashed lines indicate regions that were not modeled. Arrowheads indicate the positions of high proteolytic susceptibility (see Figures 2 and 3).
Table 1 Nup84 Subcomplex Proteins are Composed of Two Fold Types
A list of the best scoring models for domains in the proteins of the Nup84 subcomplex in yeast. For Nup84, Nup85 and Nup145C, about 200 amino-terminal residues were not modeled. However, secondary structure predictions, hydropathy profiles, and threading of the yeast proteins and their homologs suggest that most of the unmodeled portion of these proteins also adopt the solenoid fold. For Nup120 and Nup133, we were unable to model, respectively, 133 and 299 amino-terminal residues. Secondary structure predictions suggest extensions or variations to the typical β-propeller and the α-solenoid folds
aPercentage identity between the aligned sequence of the nup and its template
bZ-score of the comparative model based on the alignment indicated by percentage identity (number of residues) (Melo et al. 2002) (Tables S1–S6)
We support our fold assignments using four considerations (Figure 2; Tables 1 and S1–S7). First, both fold assignment programs returned their predictions with highly significant scores (Tables S1–S7), and they predominantly assigned only the two predicted folds out of the approximately 1,000 different known fold types (Tables S1–S7) (Orengo et al. 1997). Moreover, while there are numerous variations corresponding to different proteins within each predicted fold type, the two different methods used for fold recognition often selected the same template proteins (Tables S1–S7). Second, the evaluation of the atomic model for each nup was statistically significant when compared against the best models generated for random sequences of identical amino acid composition and length; all the nup models were at least six standard deviations away from the mean score of the random models (Figure S1; Tables 1 and S1–S7) (Melo et al. 2002). Third, secondary structure predictions from amino acid sequences alone indicate that all seven nups consist mainly of repetitive structures that largely match the secondary structures observed in their corresponding three-dimensional models (Figure 3 and Figure S2). The agreement ranges from 58% to 87% of the residues for a three-state assignment (helix, strand, other). This agreement is the maximum possible level of consistency, given the approximately 75% accuracy of the secondary structure prediction methods (Koh et al. 2003).
Figure 2 Proteolytic Domain Map of the Yeast Nup84 Subcomplex Proteins
Immunoblots of limited proteolysis digests for Protein A-tagged versions of each of the seven nups in the yNup84 subcomplex. Each protein is detected via its carboxyl-terminal tag; thus, all the fragments visualized are amino-terminal truncations (except for the full length proteins, which are indicated by arrowheads). The fragments of the Asp-N and Lys-C protease digests depicted in Figure 2 are labeled with letters (A, B, C…) that correspond to those in Table 2, and the terminal Protein A fragments are labeled with an X (the Protein A tag is resistant to proteolysis). The sizes of marker proteins are indicated in kilodaltons (kDa) to the right of the gel.
Figure 3 Predicted Secondary Structure Maps of the Nup84 Subcomplex Proteins
Thin horizontal lines represent the primary sequence of each protein; secondary structure predictions are shown as columns above each line for β-strands (β-propellers; cyan) and α-helices (α-solenoids; magenta). The height of the columns is proportional to the confidence of the secondary structure prediction (McGuffin et al. 2000). The modeled regions are indicated above each sequence by horizontal dark bars, corresponding to the models in Figure 1. Proteolytic cleavage sites are identified by small, medium, and large arrows for weak, medium, and strong susceptibility sites, respectively. Where necessary, uncertainties in the precise cleavage positions are indicated above the arrows by horizontal bars.
Table 2 Proteolytically Sensitive Sites of yNup84 Subcomplex Proteins
Listed are the sites in each of the yNup84 complex proteins most sensitive to the two proteases, as shown in Figure 2A
aFragments labeled as in Figure 2A
bMolecular weight of carboxyl-terminal fragments, containing 26-kDa Protein A tag, was calculated on gel scans using NIH Image
cThe amino acid residues adjacent to the cleavage site are indicated, where “D” designates an aspartic acid and “K” designates a lysine
dAmino acid residue positions indicated for full-length Nup145
Finally, we provide direct biochemical evidence in support of our fold assignments, using proteolytic mapping of domain boundaries and loop locations in the seven nups (see Figure 2). Tagged nups were purified from yeast extracts and incubated with the endoproteinases Asp-N (which hydrolyzes peptide bonds at the amino side of aspartic acid) or Lys-C (which hydrolyzes peptide bonds at the carboxylic side of lysines) while still attached to the magnetic beads via their proteolytically resistant tags. After digestion, proteolytic fragments that remained attached to the beads were separated by SDS-PAGE, and cleavage sites were determined either by molecular weight estimation of the fragments or by amino-terminal Edman sequencing (Table 2). The regions predicted to form β-propellers were, as expected, extremely resistant to proteolysis (see Figure 2) (Kirchhausen and Harrison 1984; Saxena et al. 1996). On the whole, the predicted α-solenoid regions were also resistant to proteolysis, although less so than the β-propellers. However, the major cleavages were found toward the end of the predicted α-solenoid domains, even in the most susceptible nup (yNup133). Strikingly, the strongest cleavages generally occurred in the border regions between the predicted domains, as is particularly evident for yNup133 and yNup120 (Figure 3). Hence, in every case, the regions that we predicted to form compact folded structures were proteolytically resistant, and the predicted linkers between these domains were proteolytically sensitive. This correlation provides support for all seven of our structural models. In addition, circular dichroism and Fourier transform infrared spectra reported for Nup85 are in agreement with our predictions, indicating a composition characteristic of α-solenoids (approximately 50% α-helical, 23% loops, 5% turns, and 10% β-sheet) (Hirano et al. 1990; Denning et al. 2003). We expect our findings will spur efforts to determine the detailed atomic structures of nups; the rapid proteolytic domain mapping and molecular modeling techniques we have utilized here should aid these efforts.
Having established the domain folds for the yNup84 subcomplex, we also assigned domain folds in its vertebrate (i.e., human) and plant (i.e., Arabidopsis) homologs. All seven nups from both human and Arabidopsis yielded identical domain fold assignments to their yeast counterparts (Table S7), despite low primary sequence conservation among them (Suntharalingam and Wente 2003). These findings indicate that the overall architecture of the yNup84/vNup107–160 subcomplex has been preserved throughout the eukaryotes. Hence, the yNup84/vNup107–160 subcomplex, which contributes nearly one-quarter of the mass of the NPC, is composed in the main of repetitive β-propellers and α-solenoids; taken together with other repetitive domain nups (such as the FG repeat nups), this suggests that a significant percentage of the NPC's bulk is composed of protein repeats (Rout and Aitchison 2001; Suntharalingam and Wente 2003).
To gain insight into the function and origin of the yNup84/vNup107–160 subcomplex, we asked whether there are other known subcomplexes that share similar compositions and fold arrangements. A search of the entire SwissProt/TrEMBL database for entries that contain an amino-terminal β-propeller followed by an α-solenoid revealed that this specific architectural combination is absent from both bacteria and archaebacteria, and is found only in eukaryotic proteins, whose role (where known) is as components either of coated vesicles or of the yNup84/vNup107–160 subcomplex. Thus, the clathrin heavy chain, a major component of clathrin-coated vesicles, appears remarkably similar in domain architecture (ter Haar et al. 1998; Kirchhausen 2000b) to both yNup120/vNup160 and yNup133/vNup133. All three proteins are composed of an amino-terminal β-propeller followed by an extended α-solenoid. Proteolysis of assembled clathrin cages leads to the release of an amino-terminal fragment of 52–59 kDa (Kirchhausen and Harrison 1984). This result is similar to our domain mapping results, where the proteolysis of yNup120 and yNup133 resulted in amino-terminal fragments of 45 kDa and 60 kDa, respectively. Strikingly, one component of the yNup84/vNup107–160 subcomplex, ySec13/vSec13R, is also a known vesicle-coating protein. Similarly, ySeh1/vSec13L, a close homolog of ySec13/vSec13R, is also associated with both the yNup84/vNup107–160 subcomplex and the vesicle-coating proteins (Siniossoglou et al. 1996; Kirchhausen 2000b; Cronshaw et al. 2002; Gavin et al. 2002; Harel et al. 2003). Together, these results point to an intimate connection between vesicle-coating complexes and the yNup84/vNup107–160 subcomplex.
In clathrin-coated vesicles, clathrin is attached via its amino-terminal domain to an adaptin complex. There are four types of adaptin complexes, all made of two large subunits that wrap around two small subunits. The bulk of each large subunit is made of an α-solenoid trunk (Figure 4) (Collins et al. 2002; Evans and Owen 2002). Similarly, the bulk of yNup84/vNup107, yNup85/vNup75, and yNup145C/vNup96 are also composed of α-solenoid trunks. Hence, the yNup84/vNup107–160 subcomplex resembles the clathrin/adaptin complex, in that the clathrin-like yNup120/vNup160 and yNup133/vNup133 are attached to the adaptin-like proteins yNup84/vNup107, yNup85/vNup75, and yNup145C/vNup96. This resemblance is further strengthened by our observation that the preferred templates for modeling the α-solenoid domains in the yNup84/vNup107–160 subcomplex were derived from proteins in vesicle coating complexes (Figure S1; Tables S1–S7).
Figure 4 The Nup84 Complex and Coated Vesicles Share a Common Architecture
A diagram showing the organization of the clathrin/AP-2 coated vesicle complex is shown at left; the positions of clathrin and the adaptin AP-2 large subunits (α, β2 plus “ear” domains) and small subunits (σ, μ) are indicated. β-propeller regions are colored cyan, α-solenoid regions are colored magenta, and sample ribbon models for each fold are shown in the center. The variants of each fold that are found as domains in major components of the three kinds of vesicle-coating complexes and the yNup84 subcomplex are listed on the right. The -N and -C indicate amino-terminal and carboxyl-terminal domains, respectively. The classification of these domains is based on X-ray crystallography data (clathrin, α-adaptin, β2-adaptin [PDB codes 1gw5, 1bpo, 1b89 (ter Haar et al. 1998; Collins et al. 2002)]), by the detailed homology modeling presented here (yNup84 complex proteins; ySec13 also in Saxena et al. [1996]), or by sequence homology or unpublished secondary structure prediction and preliminary analyses (COPI I (sec31) complex proteins [Schledzewski et al. 1999], Sec31).
Our analyses showed that the yNup84/vNup107–160 subcomplex and all three major classes of vesicle coating complexes can be linked together through their common architecture. As summarized in Figure 4, these similarities include both previously reported relationships (e.g., between the clathrin/adaptin complexes and the COPI complexes) (Schledzewski et al. 1999), and previously unsuspected relationships (e.g., between the COPII component Sec31 [Salama et al. 1997; Shugrue et al. 1999; Belden and Barlowe 2001; Boehm and Bonifacino 2001; Lederkremer et al. 2001] and clathrin).
The common architecture of the yNup84/vNup107–160 subcomplex and all three major classes of vesicle-coating complexes suggests that all of these complexes have common function in curving membranes. There is, in fact, circumstantial evidence for a role of the yNup84/vNup107–160 subcomplex in the establishment and maintenance of pore membrane curvature. Members of this complex, when disrupted in yeast, cause the uniformly distributed NPCs to cluster into patches in the plane of the NE (Siniossoglou et al. 1996; Siniossoglou et al. 2000; Ryan and Wente 2002; Teixeira et al. 2002), suggesting that impairment of yNup84 subcomplex function results in a suboptimal interaction of the NPC with its surrounding nuclear membranes.
Discussion
As shown here, protein structure modeling is particularly useful in uncovering potential evolutionary and functional relationships that are refractory to classical approaches based on comparison of protein sequences alone. Our results show that clathrin/adaptin complexes, COPI complexes, COPII complexes, and the yNup84/vNup107–160 subcomplex all share a common molecular architecture. This commonality could have arisen by either convergent or divergent evolutionary pathways.
In a convergent pathway, β-propeller and α-solenoid folds could have been independently utilized by both NPCs and vesicle-coating complexes at different stages of eukaryotic evolution. This possibility is supported by the high abundance of both fold types in eukaryotic genomes (which could potentially make their fusion in proteins or complexes relatively frequent) (Yanai et al. 2002) and the low sequence similarities between proteins of the NPC and vesicle coating complexes (which may suggest that they are not related).
In a divergent pathway, NPCs and vesicle-coating complexes share these folds because both complex types could have originated from a common ancestor. In this scenario, a single “protocoatomer” would have been the progenitor for numerous vesicle coating complexes, as well as the yNup84/vNup107–160 subcomplex. Several lines of evidence support this latter hypothesis. First, the most confident models of the yNup84/vNup107–160 subcomplex proteins are based on structures of coated vesicle proteins (Figure S1; Tables S1–S7). Second, the particular arrangement of an amino-terminal β-propeller followed by an α-solenoid appears to be unique to components of either vesicle coating complexes or of the yNup84/vNup107–160 subcomplex (Protocol S1). Third, the overall composition of both complex types is similar, being mainly composed of proteins containing comparable distributions of β-propellers and α-solenoids (Figure 4). Fourth, both vesicle coating complexes and NPCs apparently share a common function: the bending and stabilizing of curved membranes. Fifth, the yNup84/vNup107–160 subcomplex actually contains bona fide vesicle coat components, Sec13 and Seh1. In light of these considerations, we favor the “protocoatomer” hypothesis, in which the NPCs and vesicle-coating complexes arose by a process of divergent evolution.
The lack of detectable sequence similarity between the proteins in the yNup84/vNup107–160 subcomplex and the coated vesicles is not surprising. Sequence comparisons of α-solenoid- and β-propeller-containing proteins suggest that these folds arose just before or around the time of the origin of eukaryotes, then rapidly duplicated and diversified (Cingolani et al. 1999; Smith et al. 1999; Andrade et al. 2001b). Both folds consist of repetitive structures, so the functional constraints on an individual repeat are weak, compared with the whole fold domain. It has been proposed that the robustness of these folds with respect to changes in their sequences permits their component repeats to individually lose their sequence similarity, eventually allowing the proteins they comprise to drift into new functions (Malik et al. 1997; Smith et al. 1999; Andrade et al. 2001a; Andrade et al. 2001b). Moreover, the lack of detectable sequence similarity for members of the same fold family is not necessarily an indicator of convergent evolution; obvious sequence similarities are often lost during long periods of evolution (e.g., FtsZ and tubulin or MreB and actin [Amos et al. 2004]). The divergent pathway is also consistent with the conservation among members of the syntaxin family (key components of the vesicular transport machinery), which points to a similar early origin and rapid diversification of the eukaryotic endomembrane system (Dacks and Doolittle 2002; Dacks and Field 2004). Based on these observations, we propose a single evolutionary origin for the structures maintaining both the endomembrane systems and the nucleus (Figure 5) over models suggesting separate or even endosymbiotic origins for these structures.
Figure 5 Proposed Model for the Evolution of Coated Vesicles and Nuclear Pore Complexes
Early eukaryotes (left) acquired a membrane-curving protein module (purple) that allowed them to mold their plasma membrane into internal compartments and structures. Modern eukaryotes have diversified this membrane-curving module into many specialized functions (right), such as endocytosis (orange), ER and Golgi transport (green and brown), and NPC formation (blue). This module (pink) has been retained in both NPCs (right bottom) and coated vesicles (left bottom), as it is needed to stabilize curved membranes in both cases.
The current protocoatomer hypothesis posits that a simple coating module containing minimal copies of the two conserved folds evolved in protoeukaryotes as a mechanism to bend membranes into sharply curved sheets and invaginated tubules (Figure 5). The ability to so manipulate cell membranes represented a major evolutionary innovation that allowed, among other possibilities, the elaboration of internal membranes, phagotrophy, and endosymbiosis (Maynard Smith and Szathmâary 1997); the importance of this ability is underscored by the presence of numerous types of membrane-curving devices in modern eukaryotes. As with clathrin, the flexibility of the α-solenoid in this simple module enabled the formation of curved membranes of various sizes. In addition, the α-solenoid repeat structure, together with the repeats in the β-propeller fold, provided the coating module with a large binding area. These features allowed the membrane-curving module to polymerize and form a coat, as well as to interact with other membrane-associated proteins. The endomembranes and their membrane-coating modules subsequently evolved to become more elaborate and specialized, with the partitioning of different functions into separate, interconnected compartments such as the ER, the Golgi, and the nucleus (Figure 5), each with their own specialized set of coating modules.
In conclusion, we suggest that the progenitor of the NPC arose from a membrane-coating module that wrapped extensions of an early ER around the cell's chromatin. In this primitive NE, the coating modules would have originally formed the sharply curved membrane, creating large and freely permeable pores (Figure 5). These pores then closed to form the selectively permeable NPCs of modern eukaryotes (Rout et al. 2003). In doing so, they retained at their core a coating module as a relic of their evolutionary origins. This module, the yNup84/vNup107–160 subcomplex, may still serve to curve and stabilize the nuclear pore membrane in modern eukaryotes; as such, it would function as a key scaffold to form the NPCs, the portals of the nucleus. Our findings could thus provide an explanation for the origin of the nuclear pore complex (which until now has been a mystery) and may fill a significant gap in our understanding of the evolution of eukaryotes.
Materials and Methods
Only two domains in the seven nups have their folds assigned by sequence comparison to proteins of known structure (Saxena et al. 1996; Siniossoglou et al. 1996). Therefore, to assign folds for as many target domains comprising the yNup84/vNup107–160 subcomplex as possible, we applied a structure-based approach consisting of iterative detection of potential template structures, their alignment to the target sequence, model building, and model assessment (Marti-Renom et al. 2000). Secondary structure was predicted from sequence by the PredictProtein (Rost 1996) and PSI-Pred (McGuffin et al. 2000) servers.
Detection of potential template structures
For each of the seven yeast nups and representative homologs, potentially related known structures were detected by the mGenThreader (McGuffin and Jones 2003) and FUGUE (Shi et al. 2001) web servers (Tables S1–S7). Several other servers gave similar results (unpublished data). To find out whether or not mGenThreader frequently identifies the β-propeller and α-solenoid folds as false positives, we randomly selected 20 sequences of known structure from each one of the structural classes and submitted them to mGenThreader. Using the same parameters as in our analysis of the nups, only two of these 140 sequences were incorrectly predicted to contain β-propeller or α-solenoid folds (unpublished data). Thus, we estimate the false positives rate for the nup fold assignments based on mGenThreader alone to be approximately 1%–2%.
Alignment of the matched target-template pairs
The matches obtained in the previous step provided an operational definition of a domain. They were either accepted or refined by manual and automated alignment. Manual realignment relied on sequence conservation and secondary structure predictions by PROF (Rost 1996) and PSI-PRED (McGuffin et al. 2000). The automatic realignments were obtained by SALIGN (Marti-Renom et al. 2004) and T-Coffee (Notredame et al. 2000). In the last iteration, the alignments and the models were refined by MOULDER, a genetic algorithm method for iterative alignment, model building, and model assessment (John and Sali 2003).
Model building
For each alignment, an all-atom model was built by comparative modeling based on satisfaction of spatial restraints as implemented in MODELLER (Sali and Blundell 1993).
Model assessment.
The fold assignment, alignment, and model building were repeated by varying the domain boundaries, target sequences for modeling, template structures, and their alignments. The aim was to improve model assessment by statistical potentials of ProsaII (Sippl 1993) and DFIRE (Zhou and Zhou 2002), and by a composite model evaluation criterion (Melo et al. 2002; John and Sali 2003). The only importance of explicit model building in this analysis was to provide another semi-independent way to validate the fold assignments: If a model was assessed to have the correct fold, the initial fold assignment must have been correct. Beyond that, the models were not used.
Domain combination search.
To search for proteins that resemble the domain architecture of clathrin, we queried MODBASE (Pieper et al. 2004), our relational database of annotated comparative protein structure models, and Superfamily (Gough et al. 2001), a database of HMM-based structural assignments. Both databases assign folds to all available protein sequences that match at least one known protein structure. We first searched for any protein sequences that were matched to both β-propeller and α-solenoid structures. We used the broadest definitions of the β-propeller folds (b.66, b.67, b.68, b.69, b.70, for 4-, 5-, 6-, 7- and 8-bladed β-propellers, respectively) and α-solenoid folds (a.118) from the SCOP database (v1.65) (Lo Conte et al. 2002). In MODBASE, we found 95 proteins predicted to contain both β-propeller and α-solenoid domains (Protocol S1). Of these 95 proteins, 37 passed the following filters, ensuring clathrin-like characteristics: they had to be 800–2,000 residues long, the amino-terminal β-propeller domain had to be followed by a carboxyl-terminal α-solenoid domain, the β-propeller and α-solenoid domains each had to span at least 35% of the total length, and no other domain could be more than 25% of the total length. All of the 37 proteins were from eukaryotes. Their functions were assigned either as clathrin or unknown in the Swiss-Prot/TrEMBL database (O'Donovan et al. 2002). Similar results were obtained by querying the Superfamily database (Gough et al. 2001).
Proteolytic domain laddering.
Magnetic beads (2.8 μm Dynabeads M-270 Epoxy [#143.02; Dynal, Oslo, Norway]) were conjugated to rabbit IgG (#55944; ICN Biochemicals, Costa Mesa, California, United States) according to the manufacturer's instructions. Yeast cells carrying PrA-tagged versions of nups were grown and harvested as described previously (Rout et al. 2000). Cell pellets were frozen in liquid nitrogen and homogenized to a fine powder in a motorized grinder (#RM100; Retsch, Haan, Germany) continuously cooled with liquid nitrogen. The cell powder was thawed on ice and ten volumes of extraction buffer (20 mM HEPES [pH 7.4], 1.0% Triton X-100, 0.5% sodium deoxycholate, 0.3% sodium N-lauroyl-sarcosine, 0.1 mM MgCl2, 1 mM DTT, 1:500 protease inhibitor cocktail [#P-8340; Sigma, St. Louis, Missouri, United States]) were added to cells and homogenized at 4 °C with a Polytron (Kinematica, Littau-Luzerne, Switzerland). The cell lysate was clarified by centrifugation (2,000 g for 5 min at 4 °C). The magnetic beads were added to the extract to a ratio of about 8 × 109 beads per g of cells. After incubation for 1 h at 4 °C, the beads were magnetically recovered. The beads were washed, resuspended in 50 μl of reaction buffer (according to the manufacturer's specifications), and Asp-N (#1420488; Roche, Basel, Switzerland) or Lys-C (#1420429; Roche) proteinase was added to give a weight ratio of 1:200 of proteinase to the tagged nup. After incubation at different time points at 37 °C, bead aliquots were removed and washed, and tagged fragments were eluted with 0.5 M NH4OH containing 0.5 mM EDTA. The eluant was vacuum-dried, resuspended in SDS-PAGE sample buffer, and separated on a 4%–12% bis-Tris gel (Invitrogen, Carlsbad, California, United States). Proteins were then either transferred electrophoretically to nitrocellulose or PVDF and probed with HRP-rabbit IgG (#011–0303-003; Jackson ImmunoResearch, West Grove, Pennsylvania, United States), or analyzed by amino-terminal Edman sequencing (Fernandez et al. 1994).
Supporting Information
Figure S1 Model Score Versus Length
The graphs plot the assessment score of the model (Melo Z-score) (Melo et al. 2002) versus the model size, for the "non-MOULDER" models in Tables S2–S6. The red circles indicate the entries in Table 1 in the main text of the paper. Because the Z-score depends on the number of residues in the model, the smallest model with the highest Z-score was considered most significant.
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Figure S2 Agreement between Predicted and Modeled Secondary Structure
The secondary structure predicted from sequence by PROF (Rost and Liu 2003) and PSI-Pred (McGuffin et al. 2003) is compared to the secondary structure observed in the three-dimensional models presented in Table S1 (“…” represents regions that are not modeled). The numbers above the predicted secondary structures correspond to the confidence score returned by the servers. Current secondary structure prediction methods based on multiple alignments correctly predict the secondary structure state for 70%–80% of residues (in a three-state prediction) (Eyrich et al. 2001). Since the random prediction would predict only about 30% of the residues correctly, the fact that our predictions match the assignments at 58%–87% level is highly suggestive, supporting our fold assignments. A representative example, Nup85, is shown here. For the visualization of all the Nups, see the additional information web page (http://salilab.org/damien/NPC/).
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Protocol S1 List of Proteins Modeled as β-Propeller and α-Solenoid Domains in ModBase
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Table S1 Modeling Results for Yeast Nup84 Complex Proteins I (yNup133)
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Table S2 Modeling Results for Yeast Nup84 Complex Proteins II (yNup133)
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Table S3 Modeling Results for Yeast Nup84 Complex Proteins III (yNup133)
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Table S4 Modeling Results for Yeast Nup84 Complex Proteins IV (yNup133)
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Table S5 Modeling Results for Yeast Nup84 Complex Proteins V (yNup133)
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Table S6 Modeling Results for Yeast Nup84 Complex Proteins (yNup133)
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Table S7 Modeling Results for Human and Plant Nup84 Complex Proteins (yNup133)
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Accession Numbers
Uniprot (Apweiler et al. 2004) accession numbers (http://www.pir.uniprot.org) for proteins discussed in this paper are as follows. Yeast: ySeh1 (P53011), ySec13 (Q04491), yNup84 (P52891), yNup85 (P46673), yNup120 (P35729), yNup133 (P36161), and yNup145C (P49687). Human: vSec13 l (Q96EE3), vSec13R (P55735), vNup107 (P57740), vNup75 (Q9BW27), vNup160 (Q12769), vNup133 (Q8WUM0), and vNup96 (P52948).
We thank the following colleagues for their helpful contributions and discussions: Joe Fernandez and the Proteomics Resource Center of the Rockefeller University, Marc Marti-Renom, Joseph Mancias, Martine Cadene, Mark Field, Günter Blobel, John Aitchison, Kelli Mullin, John Kilmartin, Margaret Robinson, Chris Akey, Mallur Madhusudhan, Miklós Müller, Miguel Andrade, Fred Davis, and Robert Fletterick. We also acknowledge the support of the Rockefeller University, NIH GM062427, NIH/NCRR RR00862, NIH/NCI R33 CA89810, SUN, IBM, Intel, The Rita Allen and Sinsheimer Foundations, the Irma T. Hirschl Trust, and The Sandler Family Supporting Foundation.
Conflicts of interest. The authors have declared that no conflicts of interest exist.
Academic Editor: Greg Petsko, Brandeis University
Citation: Devos D, Dokudovskaya S, Alber F, Williams R, Chait BT, et al. (2004) Components of coated vesicles and nuclear pore complexes share a common molecular architecture. PLoS Biol 2(12): e380.
Abbreviations
COPcoat protein
ERendoplasmic reticulum
NEnuclear envelope
NPCnuclear pore complex
nupnucleoporin
WDtryptophan/aspartic acid
==== Refs
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| 15523559 | PMC524472 | CC BY | 2021-01-05 08:21:16 | no | PLoS Biol. 2004 Dec 2; 2(12):e380 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020380 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020415SynopsisAnimal BehaviorPhysiologyMus (Mouse)Sleeping, Waking, … and Glucose Homeostasis Synopsis11 2004 2 11 2004 2 11 2004 2 11 e415Copyright: © 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.
BMAL1 and CLOCK, Two Essential Components of the Circadian Clock, Are Involved in Glucose Homeostasis
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We often think of ourselves as either a day person or a night person—one who rises with the sun, raring to go, or one who prefers to stay up through the night to get things done. Regardless, we each have our regular waking and sleeping cycles. It's been known for some time that variations in sleep and wakefulness are part of our circadian rhythm, or molecular clock. A portion of the brain called the hypothalamic suprachiasmatic nucleus (SCN) regulates this biorhythm. When this area of the hypothalamus is destroyed in animal models, the circadian rhythm is disrupted. Two transcription factors (proteins that regulate gene expression) called Bmal1 and Clock regulate aspects of circadian rhythm, possibly by regulating neurons in the SCN.
Other aspects of human physiology are also regulated in a circadian manner. Besides altering sleep and wakefulness patterns, ablation of the SCN alters the ability to regulate sugar levels. Sugar (glucose) levels must be maintained within fairly narrow limits for survival. This regulation is controlled in part by a balance between blood sugar level and insulin production (insulin lowers the blood sugar level). In people and in mouse models, both glucose level and insulin level are subject to circadian rhythms. It isn't clear, however, if this is a behavioral effect, whereby the disruption of the SCN might alter our feeling of being well fed—that is, being sated—as eating has a profound effect on blood sugar levels.
Metabolic clock regulation of glucose homeostasis
Garret FitzGerald and colleagues tested the effect of the molecular clock genes in glucose regulation (homeostasis) by examining mice in which Clock and Bmal1 were impaired. In normal mice they observed a peak in glucose levels early in the day. This diurnal regulation was lost in the mutant mice. Furthermore, whereas the normal mice could fairly easily return their glucose levels to normal when they were artificially treated with insulin, this ability was severely impaired in the mutant mice. What's more, a high-fat diet amplified this circadian variation in the normal animals, but the rhythm was abolished in the mutants on a high-fat diet. Thus, the authors demonstrated that circadian control of blood glucose levels is due directly to the presence of these transcriptional factors rather than due to some other behavioral effect that ablation of the hypothalamus might have caused. It's possible, therefore, that besides what we eat, our internal circadian clock could also be an important regulator of blood sugar levels.
What is still left to be explored is whether the change in glucose that results from disruption of the Clock and Bmal1 genes is due to the transcription factors' effect as circadian regulators or to an activity of these transcription factors that is unrelated to circadian rhythm generation. But the study does raise the possibility that when you eat may be as important to your health as what you are eating.
| 0 | PMC524473 | CC BY | 2021-01-05 08:21:16 | no | PLoS Biol. 2004 Nov 2; 2(11):e415 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020415 | oa_comm |
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PLoS BiolPLoS BiolpbioplosbiolPLoS Biology1544-91731545-7885Public Library of Science San Francisco, USA 10.1371/journal.pbio.0020428SynopsisBioinformatics/Computational BiologyCell BiologyEvolutionMolecular Biology/Structural BiologyEukaryotesEubacteriaA Structural Analysis of Eukaryotic Membrane Evolution Synopsis12 2004 2 11 2004 2 11 2004 2 12 e428Copyright: © 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.
Components of Coated Vesicles and Nuclear Pore Complexes Share a Common Molecular Architecture
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It took nearly 200 years for biologists to redefine the plant/animal dichotomy set up by Linnaeus in 1758. Among the defining traits used in the new five kingdom model of the 20th century was the presence of a nucleus. Possession of a nucleus is one of the chief characteristics that earns an organism, even a single-celled organism, the name of eukaryote. Those not similarly blessed are prokaryotes. Biologists today classify life into three domains (of which microbes lay claim to two), yet the evolution of many fundamental features of eukaryotic biology remains a mystery.
A pivotal moment in the evolution of early eukaryotes was the emergence of elaborate, interconnected membrane-bound compartments that make up the Golgi apparatus, endoplasmic reticulum, and nuclear envelope. The nuclear envelope, with its inner and outer membrane, forms a barrier between the cytoplasm and nucleus. Embedded in this envelope are nuclear pore complexes (NPCs), massive (over 400 subunits), cylindrically shaped protein assemblies that connect the outer and inner nuclear membranes via sharply curved sections of pore membranes. The NPC's central ring-like structure is sandwiched between a cytoplasmic ring, with fibrils extending into the cytoplasm, and a nuclear ring, with a “basket” extending into the nucleoplasm. NPCs police traffic flow between the nucleus and cytoplasm, routinely allowing entry to small molecules while providing only selective passage to macromolecules.
Early eukaryote?
How eukaryotes evolved complex membrane-mediated trafficking systems from their stripped down prokaryotic contemporaries is a fundamental question in biology. Michael Rout's team investigates one aspect of eukaryotic evolution—the origin and evolution of NPC proteins (nups)—by examining the structure of nups. In a new study, Rout and colleagues report the structure of a core building block of the NPC in yeast, and propose how the complex could have evolved from organisms with no such system.
The researchers first tackled the structures of the seven protein components of a core NPC subcomplex, called the yNup84 subcomplex in yeast (and the vNup107-160 subcomplex in vertebrates). Rout and colleagues used algorithms that predict secondary structures to generate three-dimensional models of the component nups. Each nup, they found, consists mostly of either repeating alpha helixes (in an alpha-solenoid fold), zigzagging beta sheets (in a beta-propeller fold), or a distinctive arrangement of an amino-terminal beta-propeller followed by a long stretch of alpha-solenoid. Next, the authors compared the structural conformations of the homologous nups found in humans and plants, and showed that the overall architecture of the subcomplex has been conserved throughout eukaryotic evolution.
A search for evidence of the distinctive propeller/solenoid arrangement in other organisms shed light on the function and origin of the yNup87/vNup107-160 subcomplex. Neither bacterial nor archaebacterial proteins contain such an arrangement; it appears to exist only in eukaryotes. Moreover, proteins containing this arrangement function only as components of the coated vesicle complexes that operate in intracellular vesicular transport systems or as part of the NPC. That these complexes are linked by common architecture, the authors argue, suggests an “intimate connection between vesicle coating complexes and the yNup87/vNup107-160 subcomplex.” It's likely that both complexes function in curving membranes: when components of this subcomplex are disrupted in yeast, NPCs form abnormal clusters that impair nuclear membrane interactions.
How did this shared molecular architecture evolve? Rout and colleagues propose that both nups and vesicle coating complexes developed from a common early eukaryotic ancestor—a primitive coating component with a simplified version of the repetitive folds described here. This molecular carpenter specialized in carving and remodeling membranes, and was repurposed to support the many specialized functions that facilitate molecular transport through the elaborately connected, highly specialized internal membrane systems of the modern eukaryote.
| 0 | PMC524474 | CC BY | 2021-01-05 08:21:17 | no | PLoS Biol. 2004 Dec 2; 2(12):e428 | utf-8 | PLoS Biol | 2,004 | 10.1371/journal.pbio.0020428 | oa_comm |
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BMC BiochemBMC Biochemistry1471-2091BioMed Central London 1471-2091-5-141546178210.1186/1471-2091-5-14Methodology ArticleRNA integrity as a quality indicator during the first steps of RNP purifications : A comparison of yeast lysis methods López de Heredia Miguel 1lopez@lmb.uni-muenchen.deJansen Ralf-Peter 1rjansen@lmb.uni-muenchen.de1 Gene Centre and Institute for Biochemistry, University of Munich, Feodor Lynen Str. 25, D-81377 Munich, Germany2004 1 10 2004 5 14 14 22 6 2004 1 10 2004 Copyright © 2004 de Heredia and Jansen; licensee BioMed Central Ltd.2004de Heredia and Jansen; 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 completion of several genome-sequencing projects has increased our need to assign functions to newly identified genes. The presence of a specific protein domain has been used as the determinant for suggesting a function for these new genes. In the case of proteins that are predicted to interact with mRNA, most RNAs bound by these proteins are still unknown. In yeast, several protocols for the identification of protein-protein interactions in high-throughput analyses have been developed during the last years leading to an increased understanding of cellular proteomics. If any of these protocols or similar approaches shall be used for the identification of mRNA-protein complexes, the integrity of mRNA is a critical factor.
Results
We compared the effect of different lysis protocols on RNA integrity. We report dramatic differences in RNA stability depending on the method used for yeast cell lysis. Glass bead milling and French Press lead to degraded mRNAs even in the presence of RNase inhibitors. Thus, they are not suitable to purify intact mRNP complexes or to identify specific mRNAs bound to proteins.
Conclusion
We suggest a novel protocol, grinding deep-frozen cells, for the preparation of protein extracts that contain intact RNAs, as lysis method for the purification of mRNA-protein complexes from yeast cells.
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Background
Genome analyses of a range of organisms have lead to the identification of an increasing number of putative RNA-binding proteins (RBPs) whose function is still unknown. RBPs have been found to act as integral part of ribonucleoparticles (RNPs) controlling gene expression at different levels [1]. RNPs are involved in controlling RNA export, RNA stability, RNA subcellular localization and mRNA translation [2]. It has been proposed that in this context RBPs could act as central coordinators in regulating the expression and fate of specific subsets of RNAs. This model is reminiscent of bacterial operons, where the expression of genes that act in the same pathway is regulated as one unit [3].
Recently, research has mainly been focused on identifying protein-protein interactions using two-hybrid interactions [4,5], immunopurification [6] or affinity purification [7]. So far, only few examples have been reported that were aimed at the identification of mRNA-protein interactions. In yeast, immunopurification has, for example, been used to enrich RNP complexes leading to the identification of 22 mRNAs localized to the bud tip [8], to the identification of Lhp1p associated mRNAs [9] and to the identification of mRNA export factor associated transcripts [10]. There are many examples for affinity purification methods in yeast, but perhaps the one that has been used most extensively is the Tandem Affinity Purification (TAP). TAP consists of two serial affinity purification steps of a protein tagged with a double epitope tag, without affecting the expression level of the protein. It was first described for identifying new protein components of the yeast U1 snRNP [11] and later used to identify protein-protein interactions in yeast [6], bacteria [12], Trypanosoma brucei [13], Drosophila [14] and mammals [15]. It has also been used to describe the set of mRNAs associated with the Puf family of RNA-binding proteins in yeast [16].
Besides the purification method, the way to lyse cells is also crucial. In yeast, different lysis methods are in use. Glass bead milling has been applied to identify RNAs from immunoprecipitated RNPs [9]. Both French Press and glass bead milling have been successfully used to characterize protein-protein [6,11] and protein-RNAs interactions [16]. However, the integrity of the mRNA has not been determined under the conditions used. Here, we show that existing lysis methods lead to extensive mRNA degradation even in the presence of RNase inhibitors. We also present evidence that a third method, grinding deep-frozen cells at ultra-low temperature, can be used to obtain intact mRNAs.
Results
Glass bead mill lysis leads to degraded RNAs
Breaking yeast with a glass bead mill is a common method to produce cell lysates. The principle is based on the physical rupture of the yeast's cell wall and cell due to the friction produced by glass beads rapidly moving through the cell suspension. One of the advantages of this method is the high lysis efficiency.
We lysed two different yeast strains using a "bead-beater" bead mill in the presence of RNase inhibitors (100 U/ml SuperaseIn and 20 mM Ribonucleoside Vanadyl Complex, RVC) as described in Methods. We used a strain where Nrp1p, a putative RNA-binding protein that contains one RRM (RNA Recognition Motif) [17], has been tagged and a wild type strain. As shown in Figure 1A we could enrich the bait protein, Nrp1p, in the TEV eluate as compared to a purification from a control wild type strain performed in parallel. We then analyzed the RNA extracted from the input material at the IgG immunopurification step from both strains by agarose gel electrophoresis. The absence of 25S and 18S rRNAs in the extracts as compared to total RNA extracted by phenol [18] indicates that RNA was degraded (Figure 1B).
Figure 1 TAP Purification of RNA-binding protein complexes leads to RNA degradation when cells are lysed in a glass bead mill. A, 2 μl (corresponding to ~25 μg protein) of the input material for the IgG immunopurification (input) and the TCA-precipitated material from 200 μl of the TEV eluate from RJY358 (wt, untagged strain) and RJY929 (Nrp1p-TAP) were separated on a precast 4–12% gradient SDS polyacrylamide gel (Invitrogen) and stained with Coomassie. The molecular weight of the protein markers is indicated on the left. The band corresponding to the bait protein (Nrp1p-TAP) is labelled with an asterisk. B, 1 ml (corresponding to ~14 mg protein) of the input material for the IgG immunopurification (input) was phenol:chloroform extracted and 12 μg of the extracted RNA were separated on a 1.2% agarose-formaldehyde gel in the presence of ethidium bromide. As control for intact RNAs, 2 μg of total RNA (P/C lysis RNA) from the same strains prepared with a phenol method [18] were loaded in parallel as control. The position of the 18S and 25S ribosomal RNAs is indicated. C, crude lysate from strains RJY358 (wt, untagged) and RJY933 (Pbp2p-TAP) from two independent experiments were phenol extracted and 8 μg of the RNA were separated on a 1.2% agarose-formaldehyde gel and blotted onto a nylon membrane. 8 μg of total RNA (P/C lysis RNA) from the same strains prepared with a phenol extraction method [18] were loaded in parallel as control for intact RNAs. After methylene blue staining, the membrane was hybridized with a probe against PDA1 mRNA. The positions of the 18S and 25S ribosomal RNAs and the PDA1 mRNA hybridization signal are indicated.
The chosen purification method involves several steps: lysis, extract preparation and IgG immunopurification. To rule out in which step RNA degradation takes place, we analysed mRNA integrity in samples taken at different purification steps (Figure 1C and data not shown). Therefore, we used a strain where Pbp2p, a putative RNA-binding protein that contains two KH-type 1 domains (hnRNP K homology domain) [19], has been tagged and a wild type strain. We found that extensive degradation already occurs during cell lysis (Figure 1C) as shown by Northern blot against a specific abundant mRNA (PDA1) or by direct staining of ribosomal RNAs after blotting with methylene blue (unbalanced ratio of 25S and 18S ribosomal RNAs in Figure 1C).
Lysis by French Press leads to degraded RNAs
A second major lysis method for yeast cells is the French Press. Lysis occurs when the cell suspension is pressed through a small capillary. The pressure difference between the chamber and the capillary ruptures the cell.
We lysed cells as described [11] in the presence of RNase inhibitors (100 U/ml SuperaseIn and 20 mM RVC), and spun the crude lysate at 1200, 20000 and 200000 × g as indicated in Methods. We then analyzed the RNA extracted from the different fractions by Northern blot. As shown in Figure 2, when analyzing RNA quality by methylen blue staining, RNA degradation is not as obvious as with bead mill lysis (compare the ratio between 25S and 18S ribosomal RNAs in Figure 2 with that in Figure 1C). However, all different strains tested (wild type, Nrp1p-TAP and Pbp2p-TAP) show a high degree of PDA1 mRNA degradation during cell lysis (crude lysate in Figure 2), although subsequent centrifugation steps do not further enhance degradation of this mRNA (S1, S20, S200 or P200 in Figure 2). We also tested, if the RNA becomes degraded during the first step of the TAP protocol. We took samples before and after the IgG immunopurification step and checked RNA integrity by Northern blot. As shown in Figure 3, no further degradation of the RNAs during this step can be detected. Taken together these results lead to the conclusion that most of the RNA degradation observed during French Press or glass bead mill lysis happens during cell rupture despite the presence of RNase inhibitors in the lysis buffer.
Figure 2 RNA of cells lysed by French press is degraded. Strains RJY358 (wt, untagged), RJY933 (Pbp2p-TAP) and RJY929 (Nrp1p-TAP) were lysed in a French Press and samples from crude lysate, supernatant of 1200 × g (S1), 20000 × g (S20), 200000 × g (S200) spins and pellet of 200000 × g (P200) spin were phenol extracted. 8 μg of the extracted RNA were loaded onto 1.2% agarose-formaldehyde gels and blotted onto nylon membranes. 8 μg of total RNA (P/C lysis RNA) from the same strains prepared with a phenol extraction method [18] were loaded in parallel as control for intact RNAs. After methylene blue staining, the membranes were hybridized with a probe against PDA1 mRNA. The positions of the 18S and 25S ribosomal RNAs in the methylene blue staining and the PDA1 mRNA hybridization signal are indicated. The nature of the third band that appears in the methylene blue staining on top of the 25S rRNA is unknown.
Figure 3 RNA degradation is restricted to the lysis step prior to TAP purification. Strains RJY933 (Pbp2p-TAP), RJY358 (wt, untagged strain) and RJY929 (Nrp1p-TAP) were lysed in a French Press and processed up to the IgG immunopurification as indicated in Methods. Samples from supernatant of 20000 × g (S20) spin and pellet of 200000 × g (P200) spin, as well as input material (IgG input) and flow through (IgG FT) from the IgG immunopurification step were phenol extracted. 8 μg of the extracted RNA were loaded onto 1.2% agarose-formaldehyde gels and blotted onto nylon membranes. 8 μg of total RNA (P/C lysis RNA) from strain RJY933 (Pbp2p-TAP) prepared with a phenol extraction method [18] were loaded in parallel as control for intact RNAs. The positions of the 18S and 25S ribosomal RNAs in the methylene blue staining and the PDA1 mRNA hybridization signal are indicated.
Intact RNAs after lysis by mortar grinding
We also tested a third described method for cell lysis, which is grinding deep-frozen cells with a mortar [20-22]. This method breaks cells mechanically while keeping proteins and nucleic acids intact due to the lack of enzymatic activity at ultra-low breaking temperatures. After grinding, the extract is thawed in lysis buffer in the presence of RNase inhibitors (10 mM RVC and 100 U/ml SuperaseIn), immediately inactivating deleterious enzymatic activities.
First, we checked the integrity of the RNA after cells were lysed by manual grinding in liquid nitrogen. As shown in Figure 4A, RNA in crude lysate from the three strains tested (wild type, Nrp1p-TAP, Pbp2p-TAP) shows little difference from RNA isolated by direct phenol:chloroform extraction as indicated by the 25S/18S ribosomal RNA ratio and hybridization against PDA1 mRNA. We also tested RNA integrity during subsequent centrifugation steps after cell lysis with a motor-driven mortar. As shown in Figure 4B, the RNA from the different samples analyzed show only little degradation as judged by the PDA1 mRNA hybridization signal.
Figure 4 RNA degradation is reduced during lysis by grinding. A, Strains RJY358 (wt, untagged strain), RJY929 (Nrp1p-TAP) and RJY933 (Pbp2p-TAP) were manually ground in liquid nitrogen. Samples from crude lysate were phenol extracted and 8 μg of the extracted RNA were loaded onto 1.2% agarose-formaldehyde gels and blotted onto nylon membranes. 8 μg of total RNA (P/C lysis RNA) from strains RJY358 (wt, untagged strain), RJY929 (Nrp1p-TAP) and RJY933 (Pbp2p-TAP) prepared with a phenol extraction method [18] were loaded in parallel as control for intact RNAs. B, Strains RJY358 (wt, untagged strain), RJY929 (Nrp1p-TAP) and RJY933 (Pbp2p-TAP) were ground in a motor-driven mortar in the presence of dry ice. Samples from crude lysate, supernatant of 20000 × g (S20) spin, and pellet of 200000 × g (P200) spin were phenol extracted and 8 μg of the extracted RNA were loaded onto 1.2% agarose-formaldehyde gels and blotted onto nylon membranes. As control for RNA quality, RNA samples from independently lysed cells were loaded on the same gel. The positions of the 18S and 25S ribosomal RNAs in the methylene blue staining and the PDA1 mRNA hybridization signal are indicated.
Both RNase inhibitors are needed to keep mRNA intact
To optimize the lysis protocol, we also tested if both RNase inhibitors are needed to keep the RNA intact. For this purpose we first used a strain where She2p, an RNA-binding protein required for ASH1 mRNA localization, has been tagged [23]. She2p is known to bind to specific regions of ASH1 mRNA, which could help to protect the target mRNA. We lysed cells by mortar grinding and thawed them in lysis buffer with a final concentration of 170 U/ml of SuperaseIn as only RNase inhibitor. We took samples from crude lysate, different steps from the differential centrifugation and from the IgG immunopurification steps (input and flow through) and extracted the RNA. As shown in Figure 5A degradation of both PDA1 and ASH1 mRNAs is already detected in the crude lysate. Whereas no further degradation of PDA1 mRNA is detected during subsequent centrifugation, ASH1 mRNA is heavily degraded, indicating that there might not be a protective effect of RNA-binding proteins like She2p. In addition, when the extract was incubated with the IgG-coupled beads for 2 hours degradation becomes evident also for PDA1 mRNA (compare the last two lines in Figure 5A).
Figure 5 Both RNase inhibitors are needed to keep the RNA intact when cells are lysed by mortar grinding. A, Strain RJY1885 (She2p-TAP) was ground in a motor-driven mortar in the presence of dry ice. Samples from crude lysate and supernatants of 1200 × g (S1) and 7400 × g (S7) spins and pellet from 7400 × g spin (P7), as well as input material (IgG input) and flow through (IgG FT) from the IgG immunopurification, were phenol:chloroform extracted as indicated in Methods. 8 μg from the extracted RNA were loaded onto 1.2% agarose-formaldehyde gels. As RNA quality control, 8 μg of total RNA (P/C lysis RNA) extracted from the same strain with a phenol extraction method [18] were loaded in parallel. Membranes were first probed against ASH1 mRNA, stripped and then probed against PDA1 mRNA. The positions of the 25S and 18S ribosomal RNAs are shown, as well as the PDA1 and ASH1 mRNA hybridization signals. B, Sub2p-TAP strain [24] was ground in a motor-driven mortar in the presence of dry ice and thawed in lysis buffer supplemented with 50 U/ml of SuperaseIn and/or 5 mM RVC. Samples from crude lysate and supernatants of 100000 × g (S100) spin and flow through (IgG FT) from the IgG immunopurification, were phenol:chloroform extracted as indicated in Methods. 8 μg from the extracted RNA were loaded onto 1.2% agarose-formaldehyde gels. As RNA quality control, 8 μg of total RNA (P/C lysis RNA) extracted from the same strain with a phenol extraction method [18] were loaded in parallel. The positions of the 25S and 18S ribosomal RNAs are shown, as well as the PDA1 mRNA hybridization signal.
We then checked the effect of a reduced concentration of both RNase inhibitors, SuperaseIn and RVC, on RNA integrity. For this purpose we used a strain where Sub2p, an RNA-binding protein required for splicing and mRNA export, is tagged [24]. Sub2p is more abundant than She2p and believed to bind to mRNAs competent for export [25]. Like She2p, it could also have a protective function against mRNA degradation that could be more prominent due to its higher abundance. We lysed cells by mortar grinding and thawed them in lysis buffer containing either 5 mM RVC and 50 U/ml SuperaseIn, or 5 mM RVC, or 50 U/ml SuperaseIn. We took samples from crude lysate, supernatant of a 100000 × g spin, as well as input and flow through from the IgG immunopurification. As shown in Figure 5B, no degradation can be observed when RNA is stained with methylen blue and the signals from the 25S and 18S ribosomal RNAs are compared. In contrast, degradation of PDA1 mRNA is visible in crude lysates from samples that have been thawed in lysis buffers supplemented only with SuperaseIn as inhibitor (compare signal of RNA from lines 8 and 1 in Figure 5B), in concordance with previous results (Figure 5A). When RVC is present as sole RNase inhibitor (lines 5–7 in Figure 5B and compare with line 1), degradation is reduced. Only when both inhibitors are present in the lysis buffer (lines 2–4 in Figure 5B and compare with line 1) intact RNAs are detected.
Discussion
Since most RNA-binding proteins fulfil their function in the context of RNA-protein complexes, knowledge of RNAs associated with specific RBPs is essential to elucidate their functions. In order to identify these transcripts, new methods must be developed or existing successful protocols for the identification of protein-protein interactions must be adapted. Although several recent publications have identified RNA partners from RNP-complexes [9,16], there are so far no reports on the quality of the RNAs purified from these complexes. Here we demonstrate that the method used for cell lysis of yeast cells is of great importance for isolation of intact complexes. Whereas standard lysis methods like disruption by French Press or glass bead mill lead to massive RNA degradation (Figures 1, 2, 3), grinding yeast cells at ultra-low temperatures leaves cellular RNA intact (Figures 4, 5).
The major difference between the lysis methods compared in this study is the timing between addition of the RNase inhibitor and target inactivation. In French Press and glass bead milling, a lag between addition and target inactivation occurs because inhibitors require cells to be broken in order to inactivate RNases as the yeast's cell wall acts as a barrier for large molecules. Since RNases are highly active enzymes, this could result in RNA degradation prior to their inactivation by the inhibitor. This lag could explain the degradation observed in samples from crude lysates produced by these lysis methods even in the presence of RNase inhibitors (Figures 1, 2, 3). This idea is supported by the lack of further degradation during subsequent steps (Figures 2, 3). Although we have only analyzed the first step of the TAP protocol, the IgG immunopurification, the conclusion from this experiment can be extrapolated to immunoprecipitated RNPs as the molecular interactions in both methods are equivalent.
In contrast to bead milling or disruption by French Press, the temperature during grinding is kept close to -80°C and enzymatic activities are essentially absent. The results from Figure 4 show only little RNA degradation after thawing ground extracts in buffer supplemented with RNase inhibitors, which supports cell grinding as an RNA integrity conserving method. Our data demonstrating enhanced stability of mRNAs using the grinding method are supported by previous successful purifications of snRNPs with intact snRNAs using grinding as lysis method [21,22].
RNA degradation can severely bias identification of RNA from purified RNPs because only RNA fragments that are protected from degradation would remain in the purified extract. Under these circumstances, the choice of the primer for retrotranscribing the pool of purified RNAs is critical since it is likely that only primers annealing close to or inside the protected sites would result in a cDNA product.
Furthermore, when such protected RNA fragments are used to probe micro-arrays, the type of the DNA-array also becomes crucial. Since many RBPs bind to the UTRs of mRNAs and many DNA-microarrays contain only DNA corresponding to the ORF of the genes, detection of bound RNAs by such microarrays could be biased against RBPs binding outside the ORF. This problem would be enhanced using arrays composed of long oligonucleotides since only RNAs whose protected regions overlap with the oligo sequence would be identified.
Another point to consider is the low abundance of several RNPs. As many RNA-binding proteins are expressed at low levels, purification of complexes using RNPs as bait might result in low yield of bait protein plus associated RNAs. Under these circumstances, it is mandatory to keep RNA intact at early stages (in the crude lysate), since the following purification steps might become an additional source of RNA degradation. This idea is also supported by our results (Figure 5A) where, even under optimised lysis conditions, mRNAs become sensitive to degradation during longer incubation times.
Conclusions
Our data suggest that mechanical breakage of frozen yeast cells at ultra-low temperatures is the lysis method of choice for purification of intact mRNP complexes. Since in recent approaches [9,16] different lysis conditions have been used, a substantial number of protein-associated mRNAs might have been missed.
Methods
Yeast strains
Strains used in this work are isogenic with W303. The relevant genotypes are listed in Table 1.
Table 1 Strains used for this study. Strains used in this study and its relevant genotype. Modified gene is indicated in bold letters.
Strain Genotype
RJY358 MATa, ade2-1, trp1-1, can1-100, leu2-3, 112, his3-11, 15, ura3
RJY929 MATa, ade2-1, trp1-1, can1-100, leu2-3, 112, his3-11, 15, ura3, NRP1-TAP::k.l.TRP1
RJY933 MATa, ade2-1, trp1-1, can1-100, leu2-3, 112, his3-11, 15, ura3, PBP2-TAP::k.l.TRP1
RJY1885 MATalpha, ade2-1, trp1::hisG, can1-100, leu2-3, 112, his3-11, 15, ura3, pep4::LEU2, bar1::hisG, SHE2-TAP::k.l.TRP1
TAP-tagged strains were generated by transformation with PCR products using the lithium acetate method [26]. The primers used for generating the PCR products from plasmid pBS1479 [11] are listed on Table 2.
Table 2 Oligonucleotides used in this study. Oligonucleotides used in this study for generating the tagged strains.
Oligo name Sequence (5'-3')
Pbp2p-TAP forward AATTGATAGATCAAATGCTGAACGTAAAAGAAGGTCGCCCCTCTCCATGGAAAAGAGAAG
Pbp2p-TAP reverse GTAGTTTCTGTATTTTTATTTTCTATGTGTTTTTATTGACTAGTACGACTCACTATAGGG
Nrp1p-TAP forward TAATAGCGCTTTCGGTAATGGTTTTAATAGTTCAATACGTTGGTCCATGGAAAAGAGAAG
Nrp1p-TAP reverse AAATAAAAAATACAATGTGGTTGTGTGAAATTTATTGACCTCGTACGACTCACTATAGGG
She2p-TAP forward GTTGTCGCTACTAAATGGCATGACAAATTTGGTAAATTGAAAAACTCCATGGAAAAGAGAAG
She2p-TAP reverse GCTATTCATGTATATATATATGTTCTATTAACTAGTGGTACTTATTACGACTCACTATAGGG
Lysis methods
Yeast cultures were grown at 30°C in YPD media [27] up to an OD600 nm/ml of 2–3. Cultures were harvested at 4°C and washed with ice-cold sterile water.
Glass bead mill
Cell pellets from 10000 OD600 nm (5 l cultures with an OD600 nm/ml of 2) were harvested, washed with cold sterile water and immediately lysed or the wet pellet snap-frozen in liquid nitrogen. For lysis, harvested cells were resuspended in 30 ml lysis buffer (10 mM K-Hepes pH 7.9, 10 mM KCl, 1.5 mM MgCl2, 0.5 mM DTT, 1 μg/ml aprotinin, 0.8 μg/ml bestatin, 1 μg/ml leupeptin, 0.05 mg/ml pefabloc (Biomol, Germany), 0.7 μg/ml pepstatinA, 100 U/ml SuperaseIn (Ambion, UK), 20 mM Ribonucleoside Vanadyl Complex (RVC, NEB, UK)) and immediately broken. Frozen cells were stored at -80°C until used. Then, they were thawed in 30 ml lysis buffer and immediately lysed. Cells were lysed in a glass bead mill (Bead-beater, Biospec) in 3 cycles (3 min breaking and 5 min cooling). During lysis, cells were kept cold by a water-ice bath.
French Press
Cell pellets from 5000 OD600 nm (2.5 l cultures with an OD600 nm/ml of 2) were harvested, washed with cold sterile water and immediately lysed or the wet pellet snap-frozen in liquid nitrogen. For lysis, harvested cells were resuspended in 15 ml lysis buffer (10 mM K-Hepes pH 7.9, 10 mM KCl, 1.5 mM MgCl2, 0.5 mM DTT, 1 μg/ml aprotinin, 0.8 μg/ml bestatin, 1 μg/ml leupeptin, 0.05 mg/ml pefabloc, 0.7 μg/ml pepstatinA, 100 U/ml SuperaseIn, 20 mM RVC) and immediately broken. Frozen cells were stored at -80°C until used. Then, they were thawed in 25 ml lysis buffer and immediately broken. Lysis was performed as described [11] with a cold chamber.
Mortar grinding
Cell pellets corresponding to 3–15 l cultures, with an OD600 nm/ml of 2–3, were frozen by pressing the cell pellet through a 50 ml syringe directly into liquid nitrogen [20] and stored at -80°C until used. Up to 3 g frozen cells were ground manually in liquid nitrogen. Larger amounts were ground in a motor-driven mortar (Mortar Grinder RM 100, Retsch, Germany) for 15 min at pressure setting 5–7. Mortar and pestle were precooled twice with liquid nitrogen. Crushed dry ice was added continuously during grinding for keeping the mortar cold. Ground material was stored at -80°C until used. Typically, 25 g of ground cells were used for experiments running up to the first TAP immunopurification step, and 1–5 g of ground cells were used for experiments including only differential centrifugation steps. Ground cells were thawed in 1 ml of lysis buffer (40 mM K-Hepes pH 8, 1 mM MgCl2, 0.30% Igepal CA-630, 120 mM NaCl, 80 mM KCl, 2 mM EDTA, 1 mM DTT, 1 μg/ml aprotinin, 0.8 μg/ml bestatin, 1 μg/ml leupeptin, 0.05 mg/ml pefabloc, 0.7 μg/ml pepstatinA, 200 U/ml SuperaseIn, 40 mM RVC) per gram.
Sample preparation
Glass bead mill and French Press
After cell lysis, cell extracts were subjected to serial centrifugations at 4°C. First, the crude lysate (CL) was spun 3 min at 1200 × g to pellet cell debris. The total extract (S1) was further spun for 20 min at 7500 × g and the supernatant collected (S7). Salt and buffer concentration were adjusted to IgG binding conditions (20 mM K-Hepes pH 7.4, 5 mM KCl, 0.75 mM MgCl2, 100 mM K-acetate, 10 mM Tris-HCl pH 8, 100 mM NaCl, 10 mM Mg-acetate, 1 mM EGTA, 0.1% Igepal CA-630, 0.5 mM DTT, 100 U/ml SuperaseIn, 10 mM RVC, 1 μg/ml aprotinin, 0.8 μg/ml bestatin, 1 μg/ml leupeptin, 0.05 mg/ml pefabloc, 0.7 μg/ml pepstatinA) with the addition of adjusting buffer (50 mM K-Hepes pH 7.4, 140 mM K-acetate, 30 mM Tris-HCl pH 8, 300 mM NaCl, 3 mM EGTA, 0.3% Igepal CA-630, 1 mM DTT, 100 U/ml SuperaseIn, 10 mM RVC, 2 μg/ml aprotinin, 1.6 μg/ml bestatin, 2 μg/ml leupeptin, 0.1 mg/ml pefabloc, 1.4 μg/ml pepstatinA). The resulting sample was again spun for 20 min at 20000 × g and the supernatant (S20) finally spun at 200000 × g for 20 min. The supernatant was collected (S200) and the resulting pellet (P200) was resuspended in 10 ml IgG binding buffer (20 mM K-Hepes pH 7.4, 5 mM KCl, 0.75 mM MgCl2, 100 mM K-acetate, 10 mM Tris-HCl pH 8, 100 mM NaCl, 10 mM Mg-acetate, 1 mM EGTA, 0.1% Igepal CA-630, 0.5 mM DTT, 100 U/ml SuperaseIn, 10 mM RVC, 1 μg/ml aprotinin, 0.8 μg/ml bestatin, 1 μg/ml leupeptin, 0.05 mg/ml pefabloc, 0.7 μg/ml pepstatinA).
Mortar grinding
After thawing the ground cells in lysis buffer, the sample was subjected to serial centrifugation at 4°C. First, the crude lysate (CL) was spun 3 min at 1200 × g to pellet cell debris. Total extract (S1) was further spun for 20 min at 7500 × g and the supernatant (S7) was collected. The resulting pellet (P7) was resuspended in 10 ml 0.5 × lysis buffer. Supernatant (S7) was again spun for 20 min at 20000 × g and the supernatant (S20) finally spun at 200000 × g for 20 min. The supernatant was collected (S200) and the resulting pellet (P200) was resuspended in 10 ml 0.5 × lysis buffer.
For TAP purifications of Sub2p, total extract (S1) was directly centrifuged at 100000 × g for 1 h (S100).
The lipid phase was discarded from all fractions.
100–300 μl aliquots from the different fractions were extracted immediately 3–4 times with phenol:chloroform:isoamylalcohol (pH 4), precipitated with sodium acetate and ethanol and stored at -80°C until analyzed.
Glycerol (5% final concentration) was then added to those samples used for further TAP purification steps. These samples were snap-frozen in liquid nitrogen and stored at -80°C for a maximum of 2–3 days. Aliquots were taken before freezing and immediately after thawing to control for degradation during freeze-thawing. These aliquots were extracted, precipitated and stored as described above. TAP purification was performed up to the IgG immunopurification step (first step of the TAP protocol) as described [11], using as IgG binding buffer 20 mM K-Hepes pH 7.4, 5 mM KCl, 0.75 mM MgCl2, 100 mM K-acetate, 10 mM Tris-HCl pH 8, 100 mM NaCl, 10 mM Mg-acetate, 1 mM EGTA, 0.1% Igepal CA-630, 0.5 mM DTT, 100 U/ml SuperaseIn, 10 mM RVC, 1 μg/ml aprotinin, 0.8 μg/ml bestatin, 1 μg/ml leupeptin, 0.05 mg/ml pefabloc, 0.7 μg/ml pepstatinA. Samples were taken before (IgG input) and after IgG immunopurification (flow through, IgG FT) and immediately extracted, precipitated and stored at -80°C as described above.
Northern blot
Total RNA was isolated by direct phenol:chloroform extraction from the same strains used in the study as described [18], precipitated with sodium acetate and ethanol and kept at -80°C in ethanol until used as quality control. RNA pellets from the different samples were resuspended in DEPC-treated water, ratio A260 nm/A280 nm measured and equivalent amounts of RNA were loaded onto 1.2% agarose-formaldehyde gels. Samples loaded on gels for direct visualization were supplemented with 0.2 μg/μl of ethidium bromide in loading buffer. For Northern blot analysis gels were blotted onto nylon membranes, the membrane stained with methylene blue for determining transfer efficiency and probed against ASH1 and/or PDA1 mRNA (see Figure legend for details).
List of abbreviations
The abbreviations used are: RNP, ribonucleoprotein; RBP, RNA-binding protein; TAP, tandem affinity purification; RVC, ribonucleoside vanadyl complex; RRM, RNA recognition motif; UTR, untranslated region; ORF, open reading frame; DEPC, diethylpyrocarbonate; TCA, trichloroacetic acid; TEV, tobacco etch virus protease.
Authors' contributions
MLdH carried out the studies and drafted the manuscript. RPJ conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.
Acknowledgements
This work was supported partially by an individual fellowship to MLdH by Fundación Ramón Areces (Spain) and by research grants to RPJ by the Deutsche Forschungsgemeinschaft (Germany). We want to thank Anja Moraru and Dr. Coral del Val for critical reading of the manuscript and Dr. Katja Strässer (Gene Centre, Munich, Germany) for the Sub2p-TAP strain and for critical reading of the manuscript.
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| 15461782 | PMC524479 | CC BY | 2021-01-04 16:26:23 | no | BMC Biochem. 2004 Oct 1; 5:14 | utf-8 | BMC Biochem | 2,004 | 10.1186/1471-2091-5-14 | oa_comm |
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BMC BioinformaticsBMC Bioinformatics1471-2105BioMed Central London 1471-2105-5-1461547154110.1186/1471-2105-5-146SoftwareTools for loading MEDLINE into a local relational database Oliver Diane E 1oliver@SMI.Stanford.EDUBhalotia Gaurav 2bhalotia@sims.berkeley.eduSchwartz Ariel S 2sariel@cs.berkeley.eduAltman Russ B 1russ.altman@stanford.eduHearst Marti A 3hearst@sims.berkeley.edu1 Department of Genetics, Stanford University, Stanford, CA, USA2 Computer Science Division, University of California, Berkeley, CA, USA3 School of Information Management & Systems, University of California, Berkeley, CA, USA2004 7 10 2004 5 146 146 31 3 2004 7 10 2004 Copyright © 2004 Oliver 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
Researchers who use MEDLINE for text mining, information extraction, or natural language processing may benefit from having a copy of MEDLINE that they can manage locally. The National Library of Medicine (NLM) distributes MEDLINE in eXtensible Markup Language (XML)-formatted text files, but it is difficult to query MEDLINE in that format. We have developed software tools to parse the MEDLINE data files and load their contents into a relational database. Although the task is conceptually straightforward, the size and scope of MEDLINE make the task nontrivial. Given the increasing importance of text analysis in biology and medicine, we believe a local installation of MEDLINE will provide helpful computing infrastructure for researchers.
Results
We developed three software packages that parse and load MEDLINE, and ran each package to install separate instances of the MEDLINE database. For each installation, we collected data on loading time and disk-space utilization to provide examples of the process in different settings. Settings differed in terms of commercial database-management system (IBM DB2 or Oracle 9i), processor (Intel or Sun), programming language of installation software (Java or Perl), and methods employed in different versions of the software. The loading times for the three installations were 76 hours, 196 hours, and 132 hours, and disk-space utilization was 46.3 GB, 37.7 GB, and 31.6 GB, respectively. Loading times varied due to a variety of differences among the systems. Loading time also depended on whether data were written to intermediate files or not, and on whether input files were processed in sequence or in parallel. Disk-space utilization depended on the number of MEDLINE files processed, amount of indexing, and whether abstracts were stored as character large objects or truncated.
Conclusions
Relational database (RDBMS) technology supports indexing and querying of very large datasets, and can accommodate a locally stored version of MEDLINE. RDBMS systems support a wide range of queries and facilitate certain tasks that are not directly supported by the application programming interface to PubMed. Because there is variation in hardware, software, and network infrastructures across sites, we cannot predict the exact time required for a user to load MEDLINE, but our results suggest that performance of the software is reasonable. Our database schemas and conversion software are publicly available at .
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Background
MEDLINE is a large biomedical bibliographic database that is well known to users around the globe. It contains over 12 million citations from over 4,600 journals. MEDLINE is a rich source of biomedical text that lends itself well to research on text mining, information extraction, and natural language processing in biomedical domains. The usual way in which users query MEDLINE is through PubMed, the web-based interface and search engine provided by the National Library of Medicine (NLM) [1]. PubMed allows individuals to conduct searches directly by entering search terms on web pages and viewing results, and supports software-based queries across the Internet with programming utilities offered by the NLM [2]. Because we were interested in developing custom-made programs that query MEDLINE, the programming utilities offered by the NLM were an obvious choice to consider. However, due to risks of server overload, the NLM places limits on the number of queries that a user can send in a given time interval, and requests that large-volume queries be done on nights or weekends [3]. By contrast, a local version of MEDLINE gives software developers greater control over how they use the data, and facilitates the development of customizable interfaces. In this report, we describe the design and implementation of the database schema and database loading tools we have built to enable others to produce similar systems at their sites.
The entire content of MEDLINE is available as a set of text files formatted in XML (eXtensible Markup Language) [4]. The NLM distributes these files at no cost to the licensee, but the files are large and not easily searched without additional indexing and search tools. For example, in the 2003 release of MEDLINE, there are 396 files (which cover citations through 2002), and the total uncompressed size of these files is 40.8 gigabytes (GB). Although it is relatively inexpensive to store 40.8 GB of data, it is not easy to manipulate data of that magnitude without good software support. Relational databases are a natural choice for storing MEDLINE because they are able to handle large amounts of data, offer built-in approaches to query optimization, and enable the developer to create indexes. Additionally, the standard query language for relational databases, SQL (Structured Query Language), enjoys widespread familiarity and can be integrated with text-database queries in some commercial systems.
Alternatives to relational databases are XML-based databases, which have recently emerged as another option for storing information transmitted in XML format.XML databases may exist as standalone databases or as add-ons to relational systems. The MEDLINE data set would be an excellent test of the capabilities of these databases because of its size and complexity. We focused on relational databases because they are currently more ubiquitous and standardized, and interested users are more likely to be comfortable with relational database technology.
In the remainder of this report, we describe the software tools we developed for converting MEDLINE in XML files to MEDLINE in a relational database, and provide a few sample queries that demonstrate the flexibility of the resulting system.
Implementation
Database schema
The NLM provides a DTD (Document Type Definition) that defines the structure of data in the MEDLINE XML files [5-7]. From this DTD, we designed a relational database schema. Although developers of MEDLINE at the NLM maintain their own version of MEDLINE in a relational database, the schema they use is not directly applicable to our purposes, because their implementation contains tables and data that are used for maintenance and that are not relevant to external users. Thus, it was appropriate for us to design our own schema based on the specific content of the XML files, as defined by the DTD. Other groups currently license the same MEDLINE XML files and may have implemented all of MEDLINE in a relational database, but if so, their database schemas are not well publicized and were not available.
There are multiple ways in which one can design a schema from the same DTD, because DTD elements and attributes can be mapped to tables and fields in different ways. Certain design decisions may favor speed at loading time, and others may favor speed and ease of use at query time. Loading records associated with 12 million citations into a database is very time consuming, and the time can be minimized if lookups to the database are minimized during loading. In general, we aimed to minimize lookups even if that meant repeating information in the database. As developers often do in the design of data warehouses, we chose to de-normalize the schema in order to improve read-only query performance, which is the typical data access pattern in our workload.
The typical table contains a PubMed identifier (PMID) in one column, and data related to that PMID in the remaining columns. Figures 1 and 2 show original representation of content from a portion of the DTD and a corresponding table that follows the typical table structure.
Our development team included a group of researchers from the University of California at Berkeley and another group from Stanford University. We shared similar goals in that we all wanted to load MEDLINE into a relational database, but because we were in two different departments at two different institutions, we had different project constraints and timelines. Thus, our groups were loosely associated in the software development process, but not closely integrated, and therefore, the original schema that we shared diverged.
The result was three MEDLINE schemas and three software variants: One schema was used with Java code developed at Berkeley, another schema was used with Berkeley's code modified to run at Stanford, and the third schema was used with Perl code developed at Stanford. Here we describe the underlying design that influenced all three of the schemas. (The schema used for the Java program did not include information from DTD elements DataBankList and AccessionNumberList. This has been corrected in the most recent version of the software available on the Berkeley website.)
The main table in the schema is medline_citation. The medline_citation table contains the PMID as the primary key and has additional columns that correspond to single-valued elements in the DTD, where the values of those elements depend on the PMID. The medline_abstract table is similar in that it has a PMID as the primary key and columns of data that depend on the PMID. Since document abstracts are larger than the other data types, we placed them in a separate table. However, since abstracts are stored as CLOBs (Character Large Objects), they are not stored in the same pages as the rest of the fields in the medline_abstract table. Therefore, in a more recent implementation, we removed the medline_abstract table from the schema, and added the abstract_text field as a CLOB in the medline_citation table. This change reduces the number of tables by one, and eliminates the need for a join between the medline_citation and medline_abstract tables.
Some tables in the schema have more than one row corresponding to the same PMID. Columns in these tables map to multi-valued elements in the DTD. Examples are the table medline_keyword_list, which stores multiple values of keyword for a given PMID, and medline_gene_symbol_list, which stores multiple values of gene_symbol for a given PMID.
The element Article in the DTD has a one-to-one relationship between an article and a PubMed identifier. Rather than giving Article its own table, we put single-valued data from Article into the table medline_citation.
To keep track of the name of the file from which data are read for a given citation, we added the field xml_file_name to the medline_citation table. This field does not correspond to any element in the DTD structure, but allows the database administrator to go back to the original XML file if necessary to find the original source of the data.
We could have stored each author only once in a table of its own, and assigned each author a unique integer primary key to serve as an author identifier. An author is represented by a combination of values in fields for last name, forename, first name, middle name, initials, suffix, affiliation, and collective name. Another table would have stored the set of author identifiers associated with each PMID, and because integer joins are fast, this design would have facilitated rapid search for all PMIDs associated with a given author, by joining the author table with the table of author identifiers and citations. However, there are several drawbacks to this approach. Generating integer primary keys during loading requires that either a lookup be done to see if each author of each citation already exists or not (35 million lookups), or all authors and primary keys must be kept in memory. The former approach is very time consuming during loading; the latter approach strains memory resources. In addition, regardless of how primary keys are managed during loading, it is not possible to determine algorithmically if two different representations of one author are actually the same author, or if one representation is actually two different authors. We therefore avoided generating unique primary keys and repeated all eight fields representing the author for every citation occurrence of that author.
Figure 3 shows relationships among the tables. The table medline_journal is a parent of thirteen other tables (it contains the primary key pmid, which is used as a foreign key by the other tables). One of the other tables, medline_mesh_heading, is a parent of medline_mesh_heading_qualifier. Multiple qualifiers can be associated with each MeSH heading for a given citation.
Parsing and loading software
We implemented three versions of software that parses and loads MEDLINE. The first was Java MedlineParser, which was developed at Berkeley [see additional file 1]. The second was the same Java code, modified to run at Stanford. The third was Perl ParseMedline, which was developed at Stanford.
All versions of the software perform two basic tasks: (1) they parse the XML files to collect data, and (2) they load the data into the database. Figure 4 shows the steps involved. Data can be loaded as they are collected, or can be written out to disk initially, and loaded later. All three versions offer these two options to the user. Document parsing is processor intensive, data insertion is disk intensive, and if needed, the two tasks can be executed at different times to accommodate other demands on the server.
There are two types of application programming interfaces (APIs) for parsing XML files – the tree-based DOM (Document Object Model) and the event-based SAX (Simple API to XML) [8]. We chose the latter. A DOM parser organizes data from the XML file into a tree of nodes, and requires that the entire document be read in and stored in memory prior to writing out any data. Thus, the DOM parser is impractical for large documents whose data do not fit in memory. The SAX parser, however, receives data through a stream, and recognizes the beginning or end of a document, element, or attribute in an event-driven manner. It writes out data as it proceeds through the parsing process, and there is no need for the entire document to fit into memory. In XML MEDLINE, one document is a single XML-formatted MEDLINE file, and in the 2003 release, the majority of files range in size from 60 to 142 megabytes (MB). Using the DOM parser would put great demand on resources. In addition, the SAX parser is faster because it does not need to create an entire XML tree structure, map that structure to the program's data structures, and then throw out the original tree. Instead, it creates its own data structures as events are handled.
The Java version uses the Java SAX parser to parse the XML files, and JDBC (Java Database Connectivity) to communicate with the database. The Perl version uses the Perl SAX parser, and Perl DBI (Database Interface) to communicate with the database. We provide additional detail about the Java implementation here.
The SAX parser requires the developer to write code that specifies the data model for objects in the domain. The data model is an object model that represents tables in the schema. The SAX parser also requires code that listens for SAX events and that maps elements – or nodes in the XML tree – to the object model. We created two main classes upon which our code is based: GenericXMLParser and NodeHandler. GenericXMLParser is responsible for generating events when nodes that correspond to objects in the object model are encountered in the document, and NodeHandler provides the event listener. Together, these two classes form a generic approach to reading in XML data and writing out those data to tables; they are independent of the DTD or table structure.
As the parser processes the document, it decides how to handle the semantics of data at each node and determines whether to store parsed data at that node or to delegate the event to a child handler. For each node that corresponds to a table, there is a handler class that extends NodeHandler. A handler defines metadata for the node, and encodes any non-standard behavior at that node. An example of metadata is shown in Table 1. Metadata include column names for the table and an XML element associated with each column name. An XML element is represented by a concatenation of the name of the element that holds the data value, and elements higher up in the element stack up to the node that corresponds to the object, or table. This concatenated name gives a unique representation of the element that holds the data. Finally, the data type is given for each column. The column names and data types match those specified in the database schema.
Since NodeHandler and GenericXMLParser are generic, they can be used to write similar parsers for other XML documents. We have, for example, used these classes to write a parser for MeSH (Medical Subject Headings) XML files, which are also distributed by the NLM. The MeSH files are small compared to MEDLINE. MeSH 2003 comes in three XML files that total less than 600 MB.
An optional feature is validation. XML files provided by the NLM are validly formatted, but we provide additional checks to ensure that all element tags in the XML data file have been handled by the parser and that all data have been inserted into the database. A developer who is extending the software to cover new tables can use this feature to ensure that metadata definitions are correct in classes that extend NodeHandler.
Choice of Relational Database Management Systems
In the course of our work, we applied the software tools we were developing to three different relational database products. Our Berkeley team initially experimented with PostgreSQL, since PostgreSQL is an open-source relational database and is freely available and modifiable. For the final implementation, however, we chose IBM's DB2 8.1 over PostgreSQL because we found that it could load our data more efficiently and because DB2 has a text-search extender. Our Stanford team used Oracle 9i, which like DB2, offers word-based indexing of text fields. Word-based indexing is essential to support keyword search of MEDLINE titles and abstracts.
Hardware configurations
At Berkeley, we used a Pentium IV Intel Xeon 2.00-GHz dual-processor system, with 1 GB of random access memory (RAM). It had an Integrated Drive Electronics (IDE) hard disk with a rotational speed of 7200 revolutions per minute (RPM). At Stanford, we used a Sun Fire V880 server configured with four 750-MHz processors, 8 GB of RAM, and storage-area-network (SAN) storage for the relational database. We also used a Sun Enterprise 3500 server with eight 400-MHz processors and 4 GB of RAM for reading input files and writing intermediate output files in the Perl version.
Results and discussion
In this section, we describe loading time and disk-space utilization for the three implementations, followed by examples of queries, emphasizing differences between our system and PubMed.
The first implementation used the Java software, run on an Intel system (Linux), using IBM's DB2 database management system. The second implementation also used the Java software, run on a Sun server (SunOS), using Oracle's 9i database-management system. The third implementation used the Perl program, run on networked Sun servers, also using Oracle 9i. Table 2 summarizes our results.
Loading time and disk space utilization
It took 76 hours (3 days and 4 hours) for the Berkeley group to run Java MedlineParser to load MEDLINE, and 196 hours (8 days and 4 hours) for the Stanford group to do so in Oracle. There were numerous differences between the two systems, and it was not possible to test each variable independently. Therefore, we present our data as a range of possibilities, and recognize that other users will have systems that are not the same as either of ours. We believe that differences in processor speed, memory, disk read-write efficiency, and optimization methods employed in commercial database-management systems may have affected loading times. In addition, the code diverged slightly after the initial transfer of code from Berkeley to Stanford, with the main difference being that the Berkeley version used CLOBs for abstracts, whereas the Stanford version used text fields truncated to 4000 characters (size limit imposed on VARCHAR datatype). The Stanford run was also slower because a log file was generated, whereas this feature was turned off in the Berkeley run.
The space requirement for the DB2 instance of MEDLINE at Berkeley was 46.3 GB, of which 10.4 GB are consumed by the abstract text CLOBs, 18.1 GB by the other tables, and 17.8 GB by indexes. The space requirement for the Oracle instance of MEDLINE at Stanford was 37.7 GB. The difference in size is primarily due to differences in the number of records that were loaded. The Berkeley group loaded data from XML files that included all of 2002 (early 2003 release) but also included additional files through April 2003. The Stanford group loaded data from 2002 XML files only. Berkeley parsed and loaded 500 input files (44.4 GB); Stanford parsed and loaded 396 input files (40.8 GB).
The Stanford group used Perl ParseMedline to load an additional instance of MEDLINE. Parsing and loading of this instance of the database took place in a two-stage process. In the first stage, Perl ParseMedline parsed the XML files and wrote the data to disk in comma-separated-value files. To reduce processing time, the 396 XML input files were divided into 8 sets of about 50 files each, and sets were processed in parallel. The maximum time required for processing one set was 31 hours (1 day and 7 hours). The output comma-separated-value files required 25.6 GB of disk space. In the second stage, the Stanford team loaded data from the comma-separated-value files into the Oracle database using SQL*Loader, a data loading tool provided by Oracle. This stage took 33 hours (1 day and 9 hours) and used 31.6 GB of space in the Oracle database. This version used less space than the other two primarily because it had less indexing and fewer key constraints. Relaxation of constraints is reasonable because the data are well curated by the NLM, and we can count on data in the XML files released by the NLM to be of high quality.
The total time required to parse and load the files in this two-stage process is the sum of the time required to parse the largest file if all files are processed in parallel (first stage) and the time required to load the resulting comma-separated-value files into the database (second stage). Alternatively, if the input files are parsed in series, the time for the first stage would be the sum of the input-file processing times. In our case, we overlapped the runs in a way that was convenient for us, given space and user constraints, and therefore mixed the parallel and serial approach. The overall time for our first stage was 99 hours (4 days and 3 hours); adding this time to the second stage gave a total time of 132 hours (5 days and 12 hours). Given the length of time to process each of our eight batches, we can estimate a lower limit of 64 hours (2 days and 16 hours), and an upper limit of 253 hours (10 days and 13 hours), if we had run the files completely in parallel or in series, respectively.
Sample queries
Certain queries that cannot be done easily through the PubMed application programming interface (API) can be done in a single SQL query to our relational database. In this section, we show the results of a several sample queries, run on a version of MEDLINE that contains citations through April 2003.
Timing data is presented in terms of "cold" caches and "warm" cache. The cold cache represents the worst case for timing, assuming the database server has just been restarted and the buffer pool is empty. The warm cache represents the best possible performance: running the same query a second time. A typical timing number should fall somewhere between the two; hence these times represent the range of expected times to run the sample queries.
A very simple query is one that retrieves all PMIDs in MEDLINE, where pmid is a column in table medline_citation (Table 3).
Although typical users of PubMed would not be interested in such a query, we are managing MEDLINE as a complete database, and need to have access to all PMIDs. Running this query on the Berkeley implementation took 12 minutes and 26 seconds.
Many articles in MEDLINE are assigned terms from MeSH. Another capability of this system that distinguishes it from PubMed is the ability to rank order journals according to how many articles those journals have published that have been assigned a particular MeSH term. In the query shown below (Table 4), the number of publications indexed with the MeSH term (or descriptor_name) "Leukemia" is shown for each journal (where medline_ta is the title abbreviation of a journal).
The result of this query is a table consisting of journals paired with number of publications (Table 5); note that the query does not normalize for the fact that some journals have been publishing for more years than others, and publish more articles than others. This query ran in 4 minutes with a cold cache, and in 20 seconds with a warm cache.
SQL includes the "LIKE" operator which allows for partial matches. By modifying the query above to change the fifth line to read "WHERE msh.descriptor_name LIKE 'Leukemia%'," we change the query to match all MeSH terms that begin with "Leukemia". The query would thus include terms such as "Leukemia, Subleukemic" and "Leukemia, Feline." This results in dramatically more results, although the rank ordering is not all that different (Table 6). This query ran in 4 minutes with a cold cache, and in 46 seconds with a warm cache.
MeSH terms are organized into a hierarchy, and each MeSH term has associated with it one or more descriptor tree numbers that indicate its place in the hierarchy. The Berkeley group developed additional code to parse MeSH XML data files (which can be downloaded from the NLM website [9]), and added MeSH tree data to the MEDLINE database. Using the additional functionality provided by the MeSH hierarchy, we can modify the query above to rank order journals according to how often they have articles that have been assigned the MeSH term under a certain tree number, thus eliminating the sensitivity to different spellings of related concepts that was shown in the queries above. In MeSH, a child tree number shares its leftmost digits with its parent tree number, and differs in its three rightmost digits Therefore, the SQL "LIKE" operator can be used to find a MeSH term and its descendants, as shown in the query below (Table 7). The MeSH tree number for "Leukemia" is "C04.557.337".
The results of this query are shown in Table 8.
This query ran in 4 minutes with a cold cache, and in 41 seconds with a warm cache.
The DB2 version of the system implementation makes use of the text index that is incorporated into the RDBMS system, using the operator "CONTAINS" which is not part of standard SQL. The following query asks how many papers in the last three years of MEDLINE have been published by authors with affiliations at Berkeley or Stanford (Table 9).
This yields the results in Table 10.
This query ran in 2.5 minutes with a cold cache, and in 7 seconds with a warm cache.
When we ran a similar query to determine the number of articles published by Berkeley, Stanford, MIT, Yale, and Harvard, the increase in time to run the query was minimal. This modified query ran in 3 minutes and 35 seconds with cold cache, and in 15 seconds with warm cache.
Thus, SQL makes it easy to quantify and rank order results, and does not require a post-processing step as would be necessary with queries to the PubMed API. Similarly, results retrieved from previous queries can be stored directly in the same database, and reused in later queries by simply joining MEDLINE tables with user-created tables. Again, the power of SQL may alleviate the need for a post-processing step. Instead of writing custom code to integrate results from the current query to PubMed with results from previous queries, the user could use SQL joins to integrate current and previous results.
Although our system offers capabilities that the PubMed API does not, we point out that PubMed offers functionality that is not available in our system. For example, the "Related Articles" feature found in PubMed is not available, and links to full text are not available. Also, PubMed provides a user interface that is more intuitive than SQL for an end user who is not a database expert, and will be preferred by users who simply want to look up an article.
The value of our system is that it offers greater flexibility for innovative software developers who want to experiment with novel techniques for searching biomedical text, and for system developers who want to build systems of which MEDLINE is a component. If such developers want to offer their systems to end users (e.g., biologists, clinicians, or the lay public), they will need to create more intuitive user interfaces. With direct access to the underlying database, developers can create interfaces that are specifically designed to serve the needs of their particular users.
Conclusions
In this work, we developed highly customizable Java parsing code and a relational database schema that others may be interested in using or modifying. We developed software that uses the Java programming language and the SAX parser to parse XML-formatted MEDLINE files and load the data into a relational database. We loaded one copy into DB2 and another into Oracle, using our Java tool.
We also created a similar tool in Perl. The Perl code is less flexible and not as readily extensible as the object-oriented code of our Java software, but the functionality offered by the resulting database implementations is very similar.
Differences in loading time among the three installations of MEDLINE were due to a multiple factors, including differences in processors, disk storage devices, memory, operating systems, database-management systems, methods implemented in the software, and choices made by the user. Factors that affected disk-space utilization included the fact that one group loaded more data than the other, abstracts were stored as CLOBs at one site and as truncated text at the other, and indexes differed. Other groups will have system setups that differ from ours, and may make their own modifications to the code that affect their loading times. By presenting data on three examples, we have demonstrated a range of performance results as a guide to what other users might expect at their sites.
Future work includes adding functionality to update the system to new versions of MEDLINE, and to accommodate MEDLINE update files. The Stanford group has begun to use MEDLINE to extract drug-gene relationships from the literature, and the Berkeley group used the system, augmented with data from MeSH and LocusLink, to compete in the TREC 2003 genomics track competition [10]. As we continue to use these systems for research purposes, we are likely to identify alternative approaches that offer enhancements and improvements over the current design. We encourage others who work in similar areas to contribute to the open-source effort.
An updated version of our Java code accepts MEDLINE XML input files released in early 2004 that conform to the latest DTD (November 2003). The open-source code for this most current version of MedlineParser is available at .
Availability and requirements
Project name: Java MedlineParser
Project web page:
Operating system: Platform independent
Programming language: Java
Other requirements: Java 1.4.1 or higher, JAXP, relational database, and JDBC driver appropriate for the particular target database
License: None
Any restrictions on use by non-academics: None
Project name: Perl ParseMEDLINE
Project web page:
Operating system: Platform independent
Programming language: Perl
Other requirements: Perl 5.8 or higher to handle MEDLINE Unicode data (if writing directly to database), or earlier version of Perl (if writing to comma-separated-value files first), Perl modules DBI and XML::Parser::PerlSAX, relational database, and Perl database driver appropriate for the particular database (e.g., DBD::Oracle)
License: None
Any restrictions on use by non-academics: None
Authors' contributions
DO, GB, and AS, developed the MEDLINE database schemas. GB and AS designed and implemented the Java MedlineParser. GB and AS ran MedlineParser to install MEDLINE in DB2 at Berkeley. DO ran MedlineParser to install MEDLINE in Oracle 9i at Stanford. DO developed Perl ParseMedline and ran it to install the second version of MEDLINE at Stanford. DO and GB were primary authors of the article, and the remaining authors added their contributions to the manuscript. MH supervised the work at Berkeley; RB supervised the work at Stanford.
Acknowledgements
We thank Jane Rosov, John Butler, Tina Zhou, Leonard Brzezinski, Madhura Sharangpani, and John Conroy for useful discussions and assistance. Mark Musen and Teri Klein provided resources to support this work. Part of the research at Stanford was supported by NIH GM61374. The Berkeley portion of this research was supported by NSF DBI-0317510, an ARDA AQUAINT contract, and a gift from Genentech Corp.
Figures and Tables
Figure 1 Representation of information related to authors in the DTD. Selected portions of the DTD are shown. Database schema designers determine how entities and elements are converted to table names or field names in the database schema. See Figure 2 for the author table.
Figure 2 Representation of author information in the database schema. The typical table has a PubMed identifier (pmid) associated with other fields.
Figure 3 Dependencies in the database schema. Parent tables contain primary keys that child tables reference as foreign keys. The main table medline_citation, is a parent of thirteen other tables. The table medline_mesh_heading is a parent of medline_mesh_heading_qualifier.
Figure 4 MEDLINE database development process. In Step 1, the user loads the schema, creating empty tables in the database. In Step 2, the conversion software parses the XML files and either loads the data directly into the database (2a), or writes the data out to intermediate text files (2b). If intermediate text files are generated, data from those files are loaded into the database as a separate step in Step 3.
Table 1 Metadata for medline_author table.
columnNameDef xmlElementNameDef columnTypeDef
pmid PMID Types.INTEGER
last_name Author.LastName Types.VARCHAR
fore_name Author.ForeName Types.VARCHAR
first_name Author.FirstName Types.VARCHAR
middle_name Author.MiddleName Types.VARCHAR
initials Author.Initials Types.VARCHAR
suffix Author.Suffix Types.VARCHAR
affiliation Author.Affiliation Types.VARCHAR
collective_name Author.CollectiveName Types.VARCHAR
columnNameDef: column names for the table,
xmlElementNameDef: XML element names that correspond to column names,
columnTypeDef: data type of each column
Table 2 Loading time and disk-space utilization.
Site Language Processor Database Input Size Loading Time Disk Space
Berkeley Java Intel DB2 44.4 GB (500 files) 76 hours 46.3 GB
Stanford Java Sun Oracle 40.8 GB (396 files) 196 hours 37.7 GB
Stanford Perl Sun Oracle 40.8 GB (396 files) 132 hours 31.6 GB
Table 3 SELECT pmid
FROM medline_citation
Table 4 SELECT mc.medline_ta, count(mc.pmid) as num_of_publications
FROM medline_citation mc
JOIN medline_mesh_heading msh ON
mc.pmid = msh.pmid
WHERE msh.descriptor_name = 'Leukemia'
GROUP BY mc.medline_ta
ORDER BY count(mc.pmid) desc
FETCH first 10 rows only;
Table 5 Blood 940
Cancer 619
Rinsho Ketsueki 610
Cancer Res 588
Br J Haematol 524
Bone Marrow Transplant 520
Lancet 515
Leuk Res 476
Leukemia 463
The N Engl J Med 342
Table 6 Blood 6721
Cancer Res 4653
Leukemia 4640
Br J Haematol 3918
Leuk Res 3061
Cancer 2772
Rinsho Ketsueki 2628
Cancer Genet Cytogenet 2192
Bone Marrow Transplant 2123
Lancet 1931
Table 7 SELECT mc.medline_ta, count(mc.pmid) as num_of_publications
FROM medline_citation mc
JOIN medline_mesh_heading msh ON
mc.pmid = msh.pmid
JOIN mesh_descriptor md ON
md.descriptor_name = msh.descriptor_name
JOIN mesh_desc_tree_number mdtn ON
md.descriptor_ui = mdtn.descriptor_ui
WHERE mdtn.tree_number LIKE 'C04.557.337%'
GROUP BY mc.medline_ta
ORDER BY count(mc.pmid) desc
FETCH first 10 rows only;
Table 8 Blood 7361
Leukemia 5168
Cancer Res 4595
Br J Haematol 4249
Leuk Res 3274
Cancer 2856
Rinsho Ketsueki 2789
Cancer Genet Cytogenet 2362
Leuk Lymph 2226
Bone Marrow Transplant 2183
Table 9 SELECT 'Berkeley' as institution, count(pmid) as num_of_publications
FROM medline_citation
WHERE CONTAINS(article_affiliation,'"Berkeley"') = 1
AND date_created > current date – 3 years
UNION
SELECT 'Stanford' as institution, count(pmid) as num_of_publications
FROM medline_citation
WHERE CONTAINS(article_affiliation,'"Stanford"') = 1
AND date_created > current date – 3 years;
Table 10 Berkeley 2623
Stanford 4226
==== Refs
NCBI PubMed Overview.
NCBI Entrez Programming Utilities
NLM PubMed programming utilities user requirements
NLM Leasing data from the National Library of Medicine
NLM NLM Medline DTD (Nov. 1, 2002)
NLM Medline Citation DTD (Nov. 1, 2002)
NLM NLMCommon DTD (Nov. 1, 2002)
Events vs. Trees
NLM Medical Subject Headings - Files Available to Download
Bhalotia G Nakov PI, Schwartz AS, Hearst MA BioText team report for the TREK 2003 Genomics Track TREC Proceedings 2003
| 15471541 | PMC524480 | CC BY | 2021-01-04 16:02:41 | no | BMC Bioinformatics. 2004 Oct 7; 5:146 | utf-8 | BMC Bioinformatics | 2,004 | 10.1186/1471-2105-5-146 | oa_comm |
==== Front
BMC Cell BiolBMC Cell Biology1471-2121BioMed Central London 1471-2121-5-351545651210.1186/1471-2121-5-35DebateControl and maintenance of mammalian cell size Cooper Stephen 1cooper@umich.edu1 Department of Microbiology and Immunology, University of Michigan Medical School, Ann Arbor MI 48109-0620, USA2004 29 9 2004 5 35 35 25 5 2004 29 9 2004 Copyright © 2004 Cooper; licensee BioMed Central Ltd.2004Cooper; 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
Conlon and Raff propose that mammalian cells grow linearly during the division cycle. According to Conlon and Raff, cells growing linearly do not need a size checkpoint to maintain a constant distribution of cell sizes. If there is no cell-size-control system, then exponential growth is not allowed, as exponential growth, according to Conlon and Raff, would require a cell-size-control system.
Discussion
A reexamination of the model and experiments of Conlon and Raff indicates that exponential growth is fully compatible with cell size maintenance, and that mammalian cells have a system to regulate and maintain cell size that is related to the process of S-phase initiation. Mammalian cell size control and its relationship to growth rate–faster growing cells are larger than slower growing cells–is explained by the initiation of S phase occurring at a relatively constant cell size coupled with relatively invariant S- and G2-phase times as interdivision time varies.
Summary
This view of the mammalian cell cycle, the continuum model, explains the mass growth pattern during the division cycle, size maintenance, size determination, and the kinetics of cell-size change following a shift-up from slow to rapid growth.
cell cyclecell sizeexponential growthlinear growthshift-upcontinuum model
==== Body
Background
Conlon and Raff have described experiments that they claim casts doubt on a basic assumption regarding the way mammalian cell size is maintained during proliferation [1]. The key question studied by Conlon and Raff asks, "How do cells maintain a constant cell size and cell size distribution during extended cell growth?" In a cell culture growing over many generations, the cell size distribution neither varies nor broadens. Cells do not get progressively larger nor do they get progressively smaller. One formulation of this result is that cell mass increase is regulated during the cell cycle so that there is no disparity between the rate of cell mass increase and the rate of cell number increase. Total cell number and total cell mass increase in parallel during unlimited exponential growth. If there were any disparity or disproportion in the rate of mass and cell number increase, cells would get either larger or smaller during extended growth.
In an article accompanying the work by Conlon and Raff [2], a quote by Robert Brooks (Kings College, London) sums up the problem: "If [cell] growth is exponential, then cells must have a size control over division, since otherwise random differences in size at division would increase continuously from generation to generation. This does not happen. Conversely, if growth is not exponential, then such a size control is not necessary." This quote from Brooks may be thought of in this way. Consider two newborn cells of slightly different size. Exponential growth means that cell mass would be made in proportion to the extant cell mass. The larger cell would increase its mass at a more rapid rate than the smaller cell. When the cells divide, the dividing cell produced by the initially larger cell would be even larger compared to the dividing cell produced by the initially smaller cell. Given equipartition of cell mass at division, the new daughter cells would have an even more disparate size difference. Exponential growth in the next cycle would again lead to larger differences in cell size than in the previous cycle. According to this reasoning, the cell size distribution would grow increasingly broader. Since this is not observed, Conlon and Raff propose that either a cell must grow "linearly," or if a cell grows exponentially the cell must have a cell size control system. This reasoning implies that if cells grow linearly, then no cell size control system is required.
The experiments of Conlon and Raff [1] are presented as supporting linear cell growth. Linear cell growth postulates that there is a constant mass increase during each time interval of the cell cycle. Furthermore, comparing their results on mammalian cells to what is referred to as the "yeast" model of cell size control, Conlon and Raff [1] conclude that mammalian cells have a different mechanism for cell size control. As Conlon and Raff summarize their experimental conclusion:
"We show that proliferating rat Schwann cells do not require a cell-size checkpoint to maintain a constant cell size distribution, as, unlike yeasts, large and small Schwann cells grow at the same rate, which depends on the concentration of extracellular growth factors."
A reanalysis of the experiments and reasoning of Conlon and Raff, presented here, leads to a very different view of cell size control and cell size maintenance. It is first shown that there is no problem with either linear or exponential mass increase for size maintenance. Size maintenance does not depend on which pattern of cell mass increase occurs within a cell cycle. The preferred–and experimentally and theoretically supported–pattern of mass increase during the division cycle is exponential growth or exponential mass increase. An exponential growth pattern poses no problem for size maintenance. Constancy of cell size is fully compatible with an exponential pattern of mass increase as well as the hypothetical linear pattern of mass increase. No major difference between the size control systems of yeast, mammalian, or bacterial cells need be postulated to account for the constancy of cell size during the growth of cell cultures. In contrast to the proposed absence of a cell size control system in mammalian cells, it is shown that mammalian cells do have a very simple size control system. The formal elements of this system are similar to that found in the control of the bacterial cell cycle.
Discussion
Cell size maintenance with exponential and linear mass increase
Can cells grow exponentially during the division cycle and maintain a constant cell size? Consider two possible cases of exponential growth for cells with variable cell sizes. For the first case (Fig. 1a), three cells of the same newborn size have slightly different rates of mass increase. If all three of the cells in Fig. 1a were to have the same interdivision time, the dividing cells would have disparate sizes. But if the interdivision times vary so that cells divide at the same cell size, then cell size is maintained even with exponential growth during the division cycle. A newborn cell that makes mass at a rate slightly faster than average will divide earlier than cells with an average or below average rate of mass increase (Fig. 1a; arrows indicate division times). Conversely, a newborn cell producing mass at a rate slightly slower than average will divide later than cells with an average or above average rate of mass increase (Fig. 1a). Variation in interdivision times allows maintenance of constant average cell size even with exponential mass increase. A second case (Fig. 1b) starts with different sized newborn cells that synthesize mass at the same rate. As in Fig. 1a, the earlier a cell reaches the division size, the earlier the cell will divide and the cell will have a shorter interdivision time. Size constancy is maintained even though mass increases at a constant rate for the three cells with different-sized newborn cells (Fig. 1b). Mixtures of initial size variation and variation of rates of mass synthesis can be analyzed in the same manner; the analysis is strongly supported by a reanalysis of published experimental data on the variation of mammalian cell interdivision times as determined by time-lapse cinematography [3].
Figure 1 Exponential and linear growth patterns are both compatible with cell size maintenance. In panel (a) newborn cells of identical size increase mass at slightly different rates with an exponential pattern of mass increase. If cells divide at a constant cell size, here size 2.0, size will be maintained even though the rate of mass increase varies. This occurs as the cells divide at different times (division indicated by the downward arrows) as they reach the same size. In panel (b), exponential growth at identical rates from initial cells of different cell sizes also gives size maintenance as cells divide at the same size because there are different interdivision times for each cell; the larger initial cells have a shorter interdivision time and the smaller initial cells have a longer interdivision time. As shown in panels (c) and (d), linear cell increase (note the different ordinate scale compared to panels (a) and (b)) can also lead to cell size maintenance as cells divide at the same size, 2.0.
Linear cell growth during the division cycle (Figs. 1c and 1d) can also produce size maintenance. Whether cells reach the division size earlier due to a larger initial cell size or due to a more rapid rate of mass increase, the cell size at division can be the same for all cells. Thus size maintenance is also consistent with linear growth.
The patterns shown in Figs. 1a,1b,1c,1d show that there is no impediment to size maintenance as long as interdivision times are not invariant. In all four panels in Fig. 1 the interdivision time varies depending on the time required for a newborn cell to reach a particular cell size.
To be precise, it is not proposed that cells always divide at "exactly" the same size. There is a statistical variation in mass increase and interdivision times that can lead to variations in cell size at division [3]. The important point is that when cells deviate from the mean size there is a return to the mean size through compensating interdivision times during the next cell cycle. Large cells will have a relatively shorter interdivision time, leading to a return to the average cell size.
Further, it is not proposed that a large, newborn cell "controls" its mass increase to have a slower rate of mass increase (compared to smaller cells) thus compensating for the initial larger cell size. Nor do small cells increase their rate of mass synthesis to compensate for their initial mass deficit. Mass increase variation is postulated to have some inherent statistical variation [3] but with all cells, no matter what their extant size, having the same relative rate of mass increase.
There can be variability in cell mass increase with the rate of mass increase being independent of cell size. A large newborn cell could have a faster than average rate of mass increase. In this case, the interdivision time would be even shorter to compensate for both the larger initial newborn cell size and the greater than average rate of mass increase.
The size maintenance pattern is illustrated in Fig. 2, where the production of large and small cells can arise either by variation in interdivision times or deviations from equipartition. Newborn or baby cells (b) that have a relatively short interdivision time produce small (s) cells while newborn cells that have a relatively long interdivision time produce large (l) cells. Large and small cells may also be produced by deviation from equipartition at division so that an average-sized dividing cell produces one large (l) and one small (s) cell. The return of small and large cells to the average cell size occurs in the next generation by variation in interdivision times so that small cells (s) have a longer (on average) interdivision time than larger (l) cells (on average).
Figure 2 Interdivision time variation allows a return of slightly deviant sizes to a constant cell size. In panel (a) newborn "baby" cells (b) grow for slightly different times, producing either large (l) or small (s) newborn cells from large or small dividing cells. Deviation from equipartition for an average sized dividing cell can also produce large and small cells. The resolution of size differences is illustrated in (b) and (c) where the larger cell (l) has a shorter interdivision time dividing at average (a) cell size and the smaller cell (s) has a longer interdivision time also dividing at average cell size. The dividing average sized cells (a) produce newborn baby cells (b) of the original newborn size.
It may appear that this simple analysis is merely begging the question by not indicating how the cell "knows" to divide at a particular size. This question will be answered below. But first, two issues should be dealt with. An initial discussion will clarify the relationship of cell mass increase to cell size. This will be followed by a discussion of problems with the proposal of linear growth during the division cycle.
What is meant by the proposal that large cells grow faster than small cells?
What is meant by the Conlon and Raff proposal that, in yeast culture, large cells grow faster than small cells? And conversely, that in mammalian cells, large and small cells grow at the same rate? There are four different meanings that can be given the notion of the rate of mass increase and its relationship to cell size. These different meanings lead to some verbal confusion that requires clarification.
One meaning of the proposal that large cells make mass faster than small cells is that given two cells of disparate sizes, the absolute rate of increase in cell mass is greater in the larger cells. A cell of size 2.0 might add, in some time interval, 0.2 units of cell mass, while a cell of size 1.0, in that same time interval might add only 0.05 units of cell mass. This pattern is a clear and unambiguous difference in the rate of mass increase that is related to cell size.
A second meaning of cell size affecting the rate of mass increase considers that a cell of size 2.0 adds 0.2 unit of mass and a cell of size 1.0 adds 0.1 unit of cell mass over the same time interval. Of course, this case could arguably be said to be a constant rate of mass increase, as the rate of mass increase is proportional to the amount of extant mass. This second proposal is equivalent to mass increasing exponentially. This is because as extant mass changes during the cell cycle the absolute rate of mass increase also changes to reflect the newly added cell mass. After the cell of size 1.0 grows to size 1.1, in the next time interval, rather than 0.1 units of mass being added, there are 0.11 units of mass added to the cell mass. Just as interest is compounded in a bank account, and the funds grow exponentially, so mass in this second example increases exponentially.
A third meaning of the variation in mass increase with cell size is that the rate of mass increase is determined at birth and continues throughout the cell cycle, unaffected by continued cell size increase. A relatively small newborn cell could have a rate of addition of "X" units per time interval, and this rate would remain constant even as the cell increases its cell mass. The larger cell would add more than "X" units each time interval and not change this rate during the cell cycle. This pattern of increase would be called linear synthesis during the cell cycle.
It is interesting to think about these different meaning when considering the theoretical graph drawn by Conlon and Raff [1] to illustrate the return of cells of disparate sizes to the same cell size. As shown in Fig. 3 (redrawn from Fig. 1 of Conlon and Raff [1]), consider two cells, one of size 1.0 and one of size 10.0. During one generation of growth 5.5 units of mass are added by the smaller cell to produce a dividing cell of size 6.5, and 5.5 units of mass are also added to the larger cell to produce a dividing cell of size 15.5. As discussed by Conlon and Raff, upon cell division the daughter cells produced by this pattern of growth would be sizes 3.25 and 7.75. Repeating this each generation (5.5 units added to each cell independent of the extant newborn cell mass) leads, according to Conlon and Raff, to a convergence of cell size as shown in Fig 3.
Figure 3 Hypothetical model of Conlon and Raff where constant size increase independent of cell size allows return of deviant cell sizes to a constant cell size over time (This figure is drawn directly from Conlon and Raff (Conlon and Raff, 2003)). The assumption made for this figure is that both large and small cells increase their mass equally over time. Thus, a cell of size 10 and a cell of size 1 increase their mass over one doubling time by 11 units (the sum of the starting masses, 10 and 1). To the large and small cell an increase of 5.5 units of mass is proposed to occur as cells grow. Thus, the large cell grows to size 15.5 and the small cell grows to size 6.5, and at division the daughter cells now have sizes of 7.75 and 3.25 respectively. This continues for a number of generations as the founder cells, originally of disparate sizes, now converge to the same size.
But no indication of the length of the division cycles is given in Fig 3. If the interdivision times are the same for the large and small cells, which is implicit in, and not excluded by, the analysis in Fig 3 (Conlon and Raff's Fig 1), the relative rate of mass increase for the larger cell is 5.5/10.0 or 0.55 and the relative rate of mass increase for the smaller cell is 5.5/1.0 or 5.5. From this point of view, the ratio of the rates of mass increase is a factor of 10, with the smaller cell making mass from its mass at 10 times the rate (relative to extant mass) compared to the larger cell.
But if the absolute rates of mass increase were the same, then the smaller cell would have a much longer interdivision time than the larger cell. If, over a unit time, 1.0 unit of cell mass were added to the larger newborn cell, and that cell divided at size 11.0, then the interdivision time would be that unit time. The smaller cell, however, would require 10 time units for its interdivision time, because that is the time required to reach size 11.0 as 1.0 unit of material is added to each small cell during each unit of time. The smaller cell grows for a longer time before division. After this first division the new daughter cells produced by each of the initial cells would be the same size. By allowing interdivision time variation, cell size uniformity is restored in one generation.
A similar analysis can be made for exponential mass increase (i.e., mass added proportional to extant mass). If the cell of size 10.0 added 1.0 unit of mass in a unit of time, then the small cell would add 0.1 unit of mass in that same time interval. In this case, there would be even more time required for the small cell to reach the division size of 11.0. In any case, exponential growth coupled with interdivision time variation can allow size maintenance because both the large and the small newborn cells will divide at the same size, as described in Fig. 1.
Of course, the example given by Conlon and Raff (Fig 3) as discussed here is unrealistic. Cell sizes do not vary over a factor of 10 in exponential culture. But this re-analysis of Fig. 3 illustrates the power of considering different interdivision times as a factor in maintaining constant cell size.
Robert Brooks (personal communication) notes that in some of his experiments cell size is observed as very variable. He states that in experiments with Shields they found that size varied over a range of at least 6-fold. In response it can be pointed out that recent careful measurements of the size variation during the division cycle of cells grown under ideal conditions indicates that size variation is not broad [4-7]. Helmstetter (personal communication) points out that when cells are not grown under optimal conditions there are always some cells of odd or abnormal size. But these cells are cells that are dying or in some way impaired. These abnormally sized cells should not be considered as typical of the cells in a well-maintained, exponentially-growing cell culture.
The fourth part of our verbal analysis of mass increase as a function of cell size relates to bacterial cells. As will be seen below, one of the most important results in bacterial physiology is that as growth rate speeds up, cells get larger. As the growth rate of a cell is continuously varied by increasing the richness of the medium, there is a continuous variation in bacterial cell size with the faster growing cells being larger than slower growing cells [8]. Bacterial cells with an interdivision time of 20 minutes are larger than cells with an interdivision time of 60 minutes. Although it could be said that larger cells make mass faster leading to the shorter interdivision time for larger cells, it is equally possible, and in fact preferred, to reformulate or verbalize this result by saying that faster growth produces larger cells. For a given medium the rate of mass increase is determined for the bacterial cells, and the cell size results from the growth rate. This idea, the fourth way of looking at the relationship of cell size and mass increase, will be illustrated below in the analysis of bacterial patterns of DNA replication and cell size maintenance.
As we shall see, in bacterial cells a constant period for DNA replication and a constant time between termination of replication and cell division explains the variation in bacterial cell size as a function of growth rate. This same explanation also applies to mammalian cells: the rate of growth determined by external conditions determines cell size. Rather than taking the results of Conlon and Raff and concluding that larger cells when placed in medium with more serum now grow faster, it is better, as with bacteria, to say that when cells are placed in a condition that provides faster growth (i.e., a shorter interdivision time), the cells grow larger. While this may appear, at first sight, to be a trivial and semantic difference, this distinction actually lies at the heart of the problem and is the key to the solution of size determination and size maintenance. Rather than thinking that cell size produces cells with a particular growth rate (e.g., large cells grow fast), it is preferable to think that a particular growth rate produces cells of a particular size (e.g, fast growing cells are made larger than slower growing cells).
What is wrong with linear growth?
There are problems inherent and unavoidable in any proposal of linear cell growth during the division cycle. Linear growth means that during the division cycle, as a cell proceeds from size 1.0 to size 2.0, cell mass is added at a constant amount per unit time. If a cell grows linearly, over tenths of a cell-cycle time, a cell increases its size from size 1.0, to 1.1, to 1.2, and so forth.
The main problem with linear growth (i.e., constant amounts of cell mass are added at constant time intervals) is that as the cell gets larger, the cytoplasm becomes inefficient. Inefficiency is defined here as producing less mass per extant mass compared to more efficient use of the extant mass. Efficient mass increase would exist when extant cell mass makes new mass as fast as possible. As a cell grows, more cytoplasm is present. With linear growth the extra cytoplasm does not increase the absolute rate of cell mass synthesis. In essence, the new cytoplasm does not work to make new mass. There is a decrease in the relative rate of mass increase (i.e., mass synthesis per extant mass) which means that the ribosomes, after some growth, are not working as efficiently as before there was growth.
One mechanistic model explaining the postulated absence of a change in the absolute rate of mass increase to produce linear growth is to propose that the new mass does not enter into active participation in mass synthesis until a cell division; new mass will not be "activated" to enter into mass synthesis until the next division. From this viewpoint, there is a constant rate of mass increase based on the original mass. As a cell approaches division, the efficiency of mass making new mass tends toward half that of the efficiency of the initial, newborn cell mass. An alternative mechanistic proposal to explain linear growth is that during a cell cycle the amount of material able to be taken up by a cell is constant, and only upon cell division is there an "activation" of the new cell surface so that there is an increase in the ability of the cell to take in material.
Even more important and troublesome is the result that if a cell grows linearly, at the instant of cell division there must be a sudden saltation or jump in the synthetic activity of the cytoplasm. Toward the end of the cell cycle, 1.9 units of cell mass make 0.1 unit of cell mass to achieve a cell mass of 2.0. Given linear growth, at the instant of division the 2.0 units of cell mass, now apportioned into two daughter cells, must now make, during the next time interval, 0.2 units of cell mass or twice as much as in the previous time interval. When the cell of size 2.0 divides, linear growth implies that the two new daughter cells now immediately activate the "quiescent" cytoplasmic material (or activate the previously inert cell surface uptake capabilities). Irrespective of mechanism, considering the two daughter cells together, linear growth during the division cycle inevitably implies that at division there is a sudden doubling in the rate of mass increase.
There is no known biochemical mechanism for these proposals to produce linear cell growth, or the sudden jump in the rate of mass increase. As currently understood, the new cytoplasm joins right in to make new mass. And there is no mechanism known to allow new cell surface to remain inert until a cell division. While the absence of any identification of these mechanisms does not mean that these mechanisms do not exist, there is no need to propose the existence of these mechanisms if cells grow exponentially.
The experimental evidence favors exponential mass increase during the cell cycle. In bacteria the evidence for exponential growth is extremely strong [9,10]. Analysis of data on eukaryotic cell size increase also supports exponential growth during the division cycle [11].
What of the experiments presented by Conlon and Raff [1] that cell mass increases linearly? Conlon and Raff studied cells cultured in 1% fetal calf serum, forskolin, and aphidicolin. Aphidicolin is an inhibitor of DNA synthesis. While mass increased, there was no concomitant increase in DNA. The cells were incubated for 216 hours (9 days). The cell volume was measured using a Coulter Counter, although in one experiment total protein content was measured.
Conlon and Raff realized that it is extremely difficult to distinguish linear from exponential growth over one doubling time. Therefore they measured mass increase over a longer period of time (approximately 3 or more normal interdivision times). The problem with this experiment is that the inhibited cells do not allow an exponential increase in cell number as DNA synthesis is inhibited. Therefore the experiment is subject to the critique that aphidicolin inhibition produced the observed results. The results may not, and very likely do not, reflect the situation in normal, uninhibited, and unperturbed cells. For example, there could have been exponential growth during the first "virtual cell cycle". Then the limitations of DNA content would lead to the observed linearity of growth as measured over the extended period of analysis. But this linearity should not be taken as an indication that during the normal cell cycle the cell mass increases linearly.
Even if cells grow linearly during the division cycle, if the rate of mass increase is measured over a number of cell cycles with uninhibited cells, then a priori there should be evidence of an approach to exponential mass increase. If the rate of mass increase during the first cycle is 1.0, during the second cycle it should be 2.0, during the third cycle 4.0, and so on. Thus, even on its own terms, with linear mass increase during the division cycle, the experiments of Conlon and Raff [1] on the pattern of mass increase are flawed by the presence of an inhibitor of DNA synthesis. An analysis of this idea is presented schematically in Fig. 4.
Figure 4 Approach of cell mass to exponential even if cells had linear synthesis within cell cycle. Panel (a) illustrates cells dividing to produce two, four or eight times the original number of cells (thick line is cell number). The mass (thin line) increases linearly. It is clear that the cell size will not be maintained. In panel (b), even with linear mass growth within the cell cycle (thin line), as cells divide the rate of mass synthesis doubles and then quadruples as cell numbers increase. It is not proposed that mass increases linearly, but merely that even linear synthesis should exhibit, in an uninhibited situation, exponential mass growth.
Raff (personal communication) disputes this interpretation of the aphidicolin experiments, proposing that "while the aphidicolin-arrest strategy is certainly artificial, it is not unrealistic...as many cells, including Schwann cells, grow a great deal after they have stopped dividing. Moreover...hepatocytes grow linearly, independent of their size, if a mouse is re-fed after it has been starved for a couple of days." As noted in Fig. 4, without inhibition, growing cells that grow and divide must, a priori, approach an exponential pattern (i.e., rate of 1, to 2, to 4, to 8 as cells multiply), and therefore the only meaningful discussion of the linear vs. exponential growth pattern relates to growth within the cell cycle. Regarding application of liver growth following starvation and refeeding, this complex situation seems particularly inapplicable to discussions of cell growth in cell culture as there are so many complicating factors. A detailed analysis of the proper systems for cell-cycle analysis has been presented [4].
The experiments of Conlon and Raff also show some internal inconsistencies that weaken the actual data. A comparison of cell volume increase and protein per cell increase in the same cells over a 96 hour period (Fig.3 of Conlon and Raff) shows that the volume increase was 4.75-fold (~2,000 μm3/cell increasing to ~9,500 μm3/cell) but the protein increase was only 2.93-fold (~0.16 ng/cell increasing to ~0.47 ng/cell). Until these differences are resolved, it is difficult to accept these experiments as supporting linear cell growth–or any other pattern of cell growth–during the normal division cycle. The discrepancies pointed out here suggest that the quantitative measures of cell size by Coulter Counter may not be able to distinguish different growth patterns.
Another problem arises in Conlon and Raff's [1] analysis of the pulse-chase experiments where cells starved for different times are pulsed and chased to measure protein turnover. They concluded: "...the rate of decrease in radiolabeled protein increased as the cells increased in size." That is, there was a greater release of labeled amino acids from cells that were inhibited with aphidicolin for longer periods of time and which were therefore larger [1]. But the release data were plotted on rectangular coordinates. This led to the observation that the slope between the 0 hour and 2 hour points in their Fig.4 is steeper for the cells arrested for 72 hours compared to the cells arrested for 48 hours. The 72 hour cells were larger than the 48 hour cells. But considering the actual values, and reading the results from the published graph, the counts for the 72 hour arrested cells went from ~179 to ~121 in two hours, or a ratio of 0.67 for the two hour chase. The 48 hour arrested cells went from ~138 to ~94 for a ratio of 0.68 for the two hour chase. Thus, in contrast to the conclusion of Conlon and Raff [1] there is no apparent difference in the turnover of proteins as a function of cell size.
Robert Brooks (personal communication) has argued against this analysis, noting that the cells starved for 24 hours appeared to show "no turnover" as the line for this graph (Conlon and Raff's Fig.4) was flat. But in the text in the legend to their Fig.4(b) Conlon and Raff state, "The shallowness of the curve for the 24-hour-arrested cells is likely to be the result of the lower than expected value at 0 hours." This explanation comes from the initial counts in Fig.4(a) where it can be seen that there is some apparent error in the zero time value for the 24 hour starved cells in their Fig.4(b).
But an even more egregious error in analysis precedes even these technical problems. The cells studied by Conlon and Raff were not synchronized. The cells were not aligned and were in all phases of the cell cycle. Theoretically, it is impossible to determine the pattern of mass synthesis during the cell cycle on cells that are not synchronized. (For complete details see [12]). This is because of the age distribution of cells in a growing culture. The age distribution for growing cells in culture is given by 21-X, where X is the cell age during the cell cycle; X varies between 0.0 and 1.0 (newborn cells are age 0.0 and dividing cells are age 1.0). At age 0.0 the relative number of newborn cells is 2.0 (21-0 = 21 = 2) while the relative cell number of dividing cells is 1.0 at age 1.0 (21-1 = 20 = 1). This distribution of cell ages means that any incorporation measurement on asynchronous cells must, and will, yield an exponential pattern of uptake. This is illustrated in Fig. 5 for an idealized case where we imagine cells making all of their cytoplasm only at age 0.5. Because of the age distribution an exponential pattern of incorporation is observed when the entire culture is analyzed (Fig. 5a,5b). The details of the analysis are presented in the legend to Fig. 5. If the cells had been synchronized then one would have measured a peaked pattern as illustrated in Fig. 5c.
Figure 5 Unsynchronized cells cannot be used to determine cell-cycle pattern of synthesis. Panel (a) shows a series of age distributions starting with the initial age distribution reflecting the pattern Age Distribution = 21-X, where X is the cell age going from 0.0 to 1.0. In this Gedanken analysis, it is assumed that cells of age 0.5 (i.e., cells in mid-cycle) are the only cells incorporating amino acid (cross-hatched bars). The asterisk (*) on a bar in each pattern indicates the newborn cells. One reads the cell ages by going from the asterisked bar to the right and then back to the left to finish off the age distribution. The number to the right of each pattern is the relative number of cells incorporating amino acid. Thus, in the uppermost pattern in Panel (a) the relative number is 1.46. After one-tenth of a generation we see that the oldest cells in the first pattern have divided to give double the number of cells and these cells are now the youngest cells in the culture. All of the other cells move up one-tenth of an age so that the cells that were age 0.4 are now age 0.5 (cross-hatched bar) and the rate of synthesis increases to 1.57. This is because there are more cells in the original culture of age 0.4 than there were of age 0.5. Continuing down the patterns in Panel (a) we see that as cells move to age 0.5 there is a continuous, and exponential, increase in the radioactivity. The cells above age 0.5 (in the original topmost diagram) divide and produce two cells each tenth of a cell cycle, so that over one total cell cycle there is an exponential increase in the rate of amino acid incorporation (a measure of cytoplasm increase). The total pattern of incorporation is plotted in panel (b) where the exponential incorporation during one cell cycle is indicated. Panels (a) and (b) thus show that even with a non-exponential pattern of incorporation, if a total culture is studied, the measured incorporation pattern will be exponential. If, however, cells are truly synchronized, as illustrated in Panel (c), a peaked incorporation pattern is observed, accurately reflecting the mid-cycle incorporation of amino acids into the cells at a particular cell-cycle age. Starting with newborn cells at age 0.0 and moving through the cell cycle at one-tenth of an age each pattern in (panel c) the incorporation (noted by the numbers to the right of the diagrams (panel c) shows a peaked pattern.
Robert Brooks (personal communication) argues that this critique is incorrect because "they [1] started with quiescent (G0/G1) cells." Quiescent cells with a G1-phase amount of DNA are not synchronized [13-15]. The reader is referred to these papers for a detailed analysis. Despite the widespread belief and acceptance that cells can be synchronized by growth arrest (i.e., by whole-culture synchronization methods), this idea is incorrect. Cells can only be synchronized by selective methods [15].
How can one determine whether mass increases exponentially or linearly during a normal, unperturbed, division cycle? To illustrate one approach to determining the pattern of mass increase during the division cycle, consider the following experiment. Grow cells for many generations in a radioactive amino acid (e.g., C-14 labeled amino acid) so that cell protein is totally labeled. Then add a pulse of a counter-labeled amino acid (e.g., H-3 labeled). As shown in Table 1, if cells grow linearly, the ratio of tritium (H-3) to C-14 should decrease as the cells become larger. With exponential growth the ratio of tritium to C-14 should be constant over the cell cycle. If one now one took such double-labeled cells, fixed them, and spread the cells out on a gradient such that the larger cells were preferentially at the bottom and the smaller cells at the top, if cells grew linearly there would be a decrease in the H-3/C-14 ratio as the larger and larger cells were assayed. If cells grew exponentially there would be a constant radioactivity ratio over the entire set of cell size fractions. The idealized results from Table 1 are illustrated in Fig. 6.
Table 1 Analysis of linear and exponential growth by comparing long-term and short-term isotope incorporation.
LINEAR GROWTH EXPONENTIAL GROWTH
Cell size Size increase Inc/size Cell age Cell size Size increase Inc/size
1 0.1 0.100 0 1.00 0.07 0.072
1.1 0.1 0.091 0.1 1.07 0.08 0.072
1.2 0.1 0.083 0.2 1.15 0.08 0.072
1.3 0.1 0.077 0.3 1.23 0.09 0.072
1.4 0.1 0.071 0.4 1.32 0.09 0.072
1.5 0.1 0.067 0.5 1.41 0.10 0.072
1.6 0.1 0.063 0.6 1.52 0.11 0.072
1.7 0.1 0.059 0.7 1.62 0.12 0.072
1.8 0.1 0.056 0.8 1.74 0.12 0.072
1.9 0.1 0.053 0.9 1.87 0.13 0.072
2 1 2.00
The center, bold-faced, column lists the cell ages from 0 to 1.0. At the left the linear increase of mass is related to the absolute increase in mass per interval (0.1 each interval for linear increase in mass during division cycle), and the ratio of incorporation per extant cell mass is given in the third column (0.1 to 0.053). Similar results for exponential growth except the mass increase per interval goes from 0.07 at the start of the division cycle to 0.13 at the end. The ratio of incorporation per extant mass in the right-most column is thus constant.
Figure 6 Comparison of the ratio of pulse label to total label for exponential and linear patterns of mass increase as described in Table 1.
To summarize this critique of the aphidicolin-inhibition results, the experiments of Conlon and Raff do not measure the mass increase during the cell cycle. The experiments using inhibition of DNA replication merely measure the pattern of mass increase in a perturbed experimental situation on cells that are not synchronized. This experiment is not supportive of any particular pattern of mass increase during the normal division cycle. More important, as shown in Fig. 5, without synchronization of cells, it is impossible to determine the pattern of mass increase during the division cycle.
The bacterial cell cycle: Rules, patterns, and regulation
This analysis presented here explicitly deals with animal or eukaryotic cells. However, it is relevant to bring to bear on this problem the experience and results obtained regarding cell-size determination in bacteria. In 1968 the rules for the replication of DNA in a simple bacterium (Escherichia coli) as well as the relationship of cell size to control of DNA replication were worked out [16-20]. The pattern of DNA replication and cell size are determined by three rules:
1. A round of DNA replication is invariant (40 minutes) over a wide range of growth rates [16-19,21].
2. The time between termination of replication and cell division is invariant (20 minutes) over a wide range of growth rates [16-19,21,22].
3. At the time of initiation of replication, the cell mass per origin is a constant [16,20,23].
These rules are illustrated in Figs. 7 and 8. These three rules predict (Fig. 8c), that cell size should be a logarithmic function of growth rate. Cell size plotted on semi-logarithmic coordinates against the reciprocal of the interdivision time (i.e., the growth rate) gives a straight line. Faster growing cells are larger than slower growing cells. Ten years earlier, in 1958, before the rules predicting the size-growth rate relationship were determined, this experimental result [8] was clearly obtained in what has been called "the Fundamental Experiment of Bacterial Physiology" (Cooper, 1991)[12]. An analysis of the history, origins, and meaning of this experiment has been published (Cooper, 1993)[40].
Figure 7 Diagram of patterns of DNA replication during the division cycle in bacteria. The different patterns go from an infinite interdivision time (i.e., essentially no or extremely slow growth) to cells with 90, 60, 50, 40, 35, 30, 25, and 20 minute interdivision times. In all cases, the rate of replication fork movement is 40 minutes for a round of replication or one-quarter of the genome every 10 minutes. All rounds of replication end 20 minutes before the end of the cell cycle. This is most clearly seen in the 60-minute cells where a newborn cell has one genome, which replicates for 40 minutes ending replication 20 minutes before cell division. The same rules are drawn here for a 90-minute and a very slow growing cell (infinite interdivision time). The large numbers in each pattern at the left indicate the number of origins to be initiated at each time of initiation of replication. Thus, in the 60-minute cells there is one origin in the newborn cell. Consider that the cell mass is given a unit value for each origin to be initiated. Thus, the newborn cell in the 60-minute case is given a size of 1.0 unit of mass. This means that the dividing cell in the 60-minute cells is size 2.0. Mass increases, in the 60-minute case, from 1 to 2. In the 90-minute cells the cell of size 1 is one third of the way through the cell cycle. Since mass increases continuously during the division cycle it is clear that the newborn cell in the 90-minute culture is less than 1.0 in size. Let us say it was something like size 0.7. In this case the newborn cell in the 90-minute cells would be size 0.7 and the dividing cell would be size 1.4. It is clear that the 90-minute cells are, on average, smaller than the 60 minute cells. Similarly, if we consider the very slow cells, the cell of size 1.0 is very near the end of the cell cycle, and the newborn cell is slightly above size 0.5. Since the very slow growing cells (top panel) go from sizes 0.5 to 1.0 and the 60 minutes cells go from size 1.0 to 2.0, the 60 minute cells are twice as large as the very slow growing cells. The 30-minute cells have two origins in the newborn cell and thus the newborn cells can be considered size 2.0 with the dividing cells 4.0. The 20-minute cells have a newborn cell of size 4.0 (four origins in the newborn cell) and a dividing size of 8.0. As one goes from extremely long interdivision time, to 60, to 30 to 20, the relative sizes go from 0.5, to 1, to 2 to 4, with the growth rates expressed as doublings per hour, or 0 (infinite interdivision time), 1 (60 minute interdivision time), 2 (30 minute interdivision time), and 3 (20 minute interdivision time). Cells that initiate DNA replication in the middle of the cycle may be considered as follows. The 40-minute cell has two origins in the middle of the cell cycle so the mid-aged cell is size 2.0. The newborn cell might be some size like 1.5 and the dividing cell something like 3.0. Thus, the 40-minute cell has an average size intermediate between the 60 and the 30-minute cell. Similarly, the 25-minute cell also initiates mid-cycle, but there are 4 origins at the time of initiation. Thus, the mid-aged cell in this case is size 4.0 and the newborn cell may be considered something like size 3.0. The cell sizes go from 3.0 to 6.0, and these cells are larger than the 30-minute cells and smaller than the 20 minute cells.
Figure 8 Size determination in bacteria. In panel (a) the rates of growth of cells from infinitely slow (very long interdivision time) minutes to 20 minutes (as illustrated in Fig. 6) are plotted with the relative sizes shown. Thus, the 60 minute cell goes from size 1.0 to 2.0 over 60 minutes. The 30-minute cell (third angled line from top) goes from size 2 to 4 over 30 minutes. And the 20-minute cell (top angled line) goes from size 4 to 8 over 20 minutes. Other rates of growth for 25, 35, 40, 50, 90 and "infinite" interdivision times are also shown. In panel (b) the same results are plotted over relative cell ages from age 0 (newborn) to 1.0 (dividing cell). The open circles indicate when initiation occurs, and corresponds to the numbers in the individual panels. Thus, in Fig. 6 the cells with a 60, 30, and 20 minute interdivision time initiation DNA replication in the newborn cell (age 0.0) at sizes 1, 2 and 4. Besides the cell age at initiation, the open circle also indicates the relative size of the cell at initiation (see numbers in Fig. 7). The cell sizes at age 0.0 for all cells is a measure of the average cell size in the culture. (Given an identical pattern of cell growth during the division cycle the relative cell size of the cells in a culture is precisely proportional to the newborn cell size). These size values are then plotted against the rate of cell growth (the inverse of the interdivision time or doublings per hour) as shown in panel (c). The log of the cell sizes are a straight line when plotted as a function of the rate of cell growth (the inverse of the interdivision time).
The important consequence of Figs. 7 and 8 is that we understand how cell size is controlled in bacteria. Cells initiate DNA replication at a certain cell size. This cell size (sometimes referred to as the "initiation mass") is a constant size within experimental limits (Cooper, 1997)[23]. The cell size at initiation is constant per origin present in the cell. A cell with two origins being initiated is twice as large as a cell with only one origin. The number of origins present at initiation and the cell age during the division cycle at which initiation occurs determines the average cell size of a cells growing in culture.
Analysis of size maintenance in animal cells
The ideas of the bacterial cycle can be directly applied to animal cells. Cells of different growth rates are shown in Fig. 9a. The different lines, a-g, identify cells of different sizes because they pass through size 1.0 at different cell ages during a cell cycle span. Cell "g" is a faster growing cell than cell "a" with the others of intermediate growth rates. The earlier a cell reaches size 1.0, the larger the cells will be. Thus, in Fig. 9a, the cell "g" is larger than the cell "a" because the cell "g" reaches size 1.0 earlier than the cell "a". As drawn in Fig. 9a, the newborn "g" cell is size 1.0. The mother or dividing cell is size 2.0. We can imagine that the mean size of cells growing at this rate is approximately 1.5. In contrast, the "a" cell varies between newborn size of approximately 0.6 and dividing size of 1.2. The average size of the "a" cells is smaller than the "g" cell, approximately size 0.9. (The precise calculation of the average cell size requires consideration of the age distribution and the actual pattern of mass increase during the division cycle; for purposes of this analysis, these complications are omitted.) Other cells (b-f) may be similarly analyzed to see that faster growing cells are larger than slower growing cells.
Figure 9 Mammalian cell size variation as growth rate varies. Panel (a) shows a given mammalian cell growing at different rates and with different sizes. The lines are parallel because the interdivision times are normalized to a relative cell age as cells are born at age 0.0 and divide at age 1.0. All lines are exponentially increasing cell sizes from smallest to largest. Where the lines cross the thick horizontal line indicates a cell of size 1.0. Since the fastest cell (cell g) has a size 1.0 at the start of the cell cycle these cells must go from a newborn sizes of 1.0 to a size at division of 2.0. The slowest cell (cell a) has size 1.0 toward the end of the cell cycle, so the newborn cell is slightly larger than size 0.5 at age 0.0. The size ranges of these cells goes over a factor of 2. In panel (b) the size patterns are re-interpreted in terms of initiation at a particular time during the cell cycle. In this figure the thick, short line on each pattern is the S phase, the thinner line to the right is the G2 phase and the thinner line to the left is the G1 phase. Given that S and G2 are relatively constant in length then the slower cells (e.g., cell "a") have a longer G1 phase than the faster growing cells (e.g., cell "g", which has no measurable G1 phase). This is because the interdivision time is the sum of S+G2+G1. If S and G2 are relatively constant as the interdivision time decreases (i.e., as cells grow at faster growth rates), the G1 phase gets smaller. When the interdivision time equals the sum of S and G2 as in cell "g", there is no G1 phase. Such a situation has been analyzed previously (Cooper, 1979). It is clear from panel (b) that as cells grow faster, the time during the division cycle at which initiation of S phase starts is earlier and earlier. This is illustrated even more directly in panel (c) where the phases are normalized to a unit length. The slowest cell (cell "a") has the shortest fraction of cells with an S or G2 phase and the fastest growing cell (cell "g") has the entire division cycle occupied by S and G2 phases. The topmost line in panel (c) is the fastest cell and it starts S phase early in the cell cycle. Thus we see that the faster a cell grows the earlier in the cell cycle the cell achieves a size of 1.0. This accounts for the result that the slower cell has a smaller cell size than the faster growing cell.
As will now be seen, this variation in size is related to, and determined by, the growth rate.
It is proposed that mammalian cells initiate DNA replication at some relatively constant cell size. The time for S and G2 phases are relatively constant as the interdivision time varies [24], so the cell cycle age at initiation of S phase occurs earlier and earlier within the cell cycle as the growth rate increases (or as the interdivision time decreases). This is shown in Fig. 9b, where the interdivision time is varied but S- and G2-phase lengths are constant. In Fig. 9c the cell cycle patterns in Fig. 9b are normalized to a constant length. In Fig. 9c it is clear that the faster cells initiate S phase earlier in the cell cycle. This is because faster growing cells have a relatively short G1 phase. These faster growing cells achieve the initiation mass earlier in the cell cycle and thus these cells will be larger. As in bacteria, faster growth leads to larger average cell sizes. (For a discussion of the case of cells growing so fast as to not have a G1-phase as in cell "g" in Fig. 9b, see [24]).
The rate of cell growth is determined by medium composition. For example, as more and more nutrients are added to a minimal medium, bacterial cells grow at faster and faster rates. The interdivision time shortens as the medium becomes richer. For bacteria the mechanism for growth rate variation with medium composition is, in outline, well understood [25]. The addition of nutrients to a medium represses the synthesis of enzymes that are not now needed (e.g., addition of leucine stops the synthesis of leucine synthesizing enzymes). This leads to a shift in the synthetic capacity of the cell to the protein synthesizing system (RNA polymerase, ribosomes, related materials, etc.) as these functions are not repressible by external components [25]. This leads to a more rapid rate of mass increase and thus a shorter mass doubling time [24,26].
Although the details may vary, it is proposed here (and in fact supported by the experiments of Conlon and Raff) that the richer a medium is (e.g., more serum rather than less serum), the faster the cells will grow. The faster a cell grows, the larger it will be (Fig. 9). The variation of G1-phase length with interdivision time variation has been analyzed in detail [24,26].
Conlon and Raff [1] supply evidence for the relationship of cell size and growth rate in their Fig. 7. Cells that have become overcrowded by not being diluted back (their Fig. 7b) decrease their volume (their Fig. 7a).
The analysis presented above explains the variation of cell size as function of growth rate as observed by Conlon and Raff (slower growing cells are smaller than faster growing cells). Furthermore, the analysis can also explain the maintenance of cell size, even with exponential mass increase during the division cycle, as shown in Fig. 9. Larger than average cells will divide sooner as they reach the initiation mass earlier and smaller than average cells will delay initiation until the initiation mass is achieved. Cell division will follow after relatively constant S- and G2/M-phases. This is the underlying and fundamental explanation for the patterns described in Figs. 1 and 2.
Thus, we now have an answer to the question (raised in discussion of Fig. 2) "How does the cell 'know' when to divide so that size homeostasis is maintained?" The answer is that initiation of S phase is determined by the cell mass. A relatively large cell initiates S phase earlier than a relatively small cell. This earlier initiation is played out in an earlier cell division after a period equal to the S and G2/M phases. Since the S and G2/M phases are relatively invariant, an earlier initiation produces an earlier cell division. While the analysis in Fig. 1 discussed the size maintenance problem in terms of the cell dividing earlier if a newborn cell was larger and later if a newborn cell was smaller (or if the rate of mass increase was high or low), the deeper analysis presented now proposes that the decision to divide is determined not at the moment of cell division but earlier at the start of S phase. The initiation of S phase is determined by cell size and the faster a cell reaches the S-phase initiation size the earlier the cell will initiate S phase and the earlier it will divide. For reasons not yet understood, there is a relationship between initiation of S phase and cell division such that once S phase is initiated the cell will ineluctably proceed to division.
We now see the answer to the problem of cell size at division. Cell size at division is merely a surrogate indicator of cell size at initiation. Further, the time of cell division is a surrogate measure of the time of initiation of S phase. A cell that initiates S phase earlier in the cell cycle will have more time to increase its total mass prior to division. The larger newborn cell, having initiated S phase relatively early compared to its relatively smaller sister and cousin cells, will divide earlier as described in Fig. 1. Conversely, smaller cells will delay initiation of S phase; that delay will allow more mass increase before the actual cell division because S phase is somewhat delayed and thus division is postponed allowing mass to increase before the ultimate cell division. In this way, the cell size distribution is maintained.
Size variation during a shift from slow to fast growth
Immediately following the discovery of bacterial cell size variation with growth rate [8] shift-up experiments of cells from slow growth (relatively small size) to faster growth (relatively large size) were performed [27]. The phenomenon of "rate maintenance" was discovered in this shift-up experiment. Rate maintenance is the continuation of the rate of cell division for a constant period after the shift-up [19]. The rate of mass increase changes immediately to the new rate at the instant of shift-up, while the rate of cell division continues for a period of time before abruptly changing to the new rate. The rate maintenance phenomenon occurs over a wide range of shift-ups [19]. The continuation of the original, slower rate of cell number increase, combined with an immediate transition to the new rate of mass increase, leads to an increase in cell size over the period of rate maintenance (Fig. 10a). Rate maintenance is now understood to result from the constant S and G2 periods (C and D periods in bacteria) that do not allow new divisions to occur until the newly inserted replication forks pass through the S (i.e., C) period and the G2 (i.e., D) period. Without going into details here (see [12] for a complete analysis and explanation), suffice it to say that the rate maintenance phenomenon leads to the observed variation in bacterial cell sizes as the rate of cell growth varies over a wide range.
Figure 10 Comparison of shift-up of bacterial cells and mammalian cells. In the panel (a), after a shift of bacterial cells from slow-growth medium to fast growth medium there is an immediate change in the rate of mass synthesis to the new rate while the rate of cell division continues at the old rate for a fixed period of time (rate maintenance). At the end of this "rate maintenance" period, there is a sudden shift in the rate of cell number increase to the new rate. The thick line in panel (a) shows the change in cell size following the shift-up. In contrast, in panel (b) a slower and more gradual change in the rate of mass synthesis, concomitant with the cell number pattern also changing slowly over a period of time, will give a longer period of change in cell size. Conlon and Raff observed this slow pattern of mammalian cell size change.
Conlon and Raff [1] studied mammalian cells during a shift-up from slow to rapid growth and small to large cell size. Upon shifting slow cells to faster medium (e.g., shifting cells from low serum to high serum) there is a concomitant increase in cell size (Fig. 6e of Conlon and Raff [1]). One major difference from the bacterial shift-up result is that with animal cells the time for cell size to increase took a much longer time, between 6 and 9 days. To explain the difference between the bacterial shift-up result (Fig. 10a) and the mammalian cell shift-up result (Fig. 10b) one can postulate that for reasons unrelated to the cell cycle but merely related to cellular metabolism occurring continuously throughout the cell cycle, the change in external conditions does not immediately lead to the new rate of mass increase (Fig. 10b). The rate of mass increase is predicted to change relatively slowly as mammalian cells are shifted from serum-free (slow growth) medium to serum-containing (fast growth) medium. Of course, this is just the result reported by Conlon and Raff (their Fig. 6e).
This view of the change in cell size following a shift from slow to rapid growth is quite different from the description Conlon and Raff present for the case of yeast cells switched from a nutrient-poor to a nutrient-rich medium. They write [1], "When switched from a nutrient poor medium to a nutrient-rich medium, the cell cycle arrests and resumes only when the cells have reached the appropriate size for the new condition, which occurs within one cell cycle...Thus, the cells can adjust their size threshold rapidly in response to changing external conditions." The bacterial model of the shift-up allows a rapid change in cell size within one cell cycle without postulating any "arrest" of passage through the cell cycle.
Rather than postulate a mechanism that slows or actively shuts down the cell cycle, it is proposed that no change in cell division occurs until the increased initiations of S phases pass through the S and G2/M phases, as in the bacterial model. No additional mechanism need be proposed to "stop" some event of the cell cycle until cell size has increased.
The age-size distribution summarizes size control
One way to consider a growing culture is to see that every cell in a growing culture has an age and a size. The age/size structure of a population is a representation of each of the cells in the culture and its age and size. If there is no statistical variation, and cells move through the cell cycle with a perfectly precise exponential growth pattern, then the age/size distribution is seen in Fig. 11a. The projections of the dots in this panel to the age axis (bottom, abscissa) and the size axis (left, ordinate) indicate that when cells are growing exponentially, there are a greater number of smaller cells relative to the population than there are younger cells. This reflects the age distribution discussed above.
Figure 11 Age-size structure of a growing culture. Panel (a) is the age-size structure for a perfectly deterministic population growing exponentially in mass during the division cycle. The dots on the exponentially increasing line are placed at equal age intervals shown by their representation at the bottom of the panel. The representation of the dots at the left of panel (a) indicates that there is a greater concentration of smaller cells than younger cells. In panel (b) the age-size structure for a population with variation in size and interdivision times is illustrated. The cloud of points (indicated by a few points as representative of the population) is one possible age-size structure. In panel (c) the newborn cells are indicated by the filled circles, the dividing cells by open circles, and the cells in the act of initiation of DNA synthesis by + signs. It can be seen that the larger cells at birth will, on average, reach the size required for initiation of DNA replication more quickly than smaller cells. This is because the larger cells are closer to the initiation size (represented by I on the right side of panel (c)). The B and D distributions at the right of panel (c) indicate the size distributions of newborn (B) cells and dividing (D) cells. The B, D, and I distributions at the top of panel (c) illustrate the age distributions for newborn, dividing, and initiating cells. The size distribution of initiating cells is drawn with a narrower distribution. Variations in mass increase during the period after initiation lead to the widening of the size distribution at division. Panel (d) is a replotting of the pattern in panel (c) with the bottom time scale defined by setting the time of initiation of DNA synthesisas age 0.0. Cells before initiation have a negative age value, and cells after initiation have a positive age value. Initiation takes place, by definition in this panel, at age 0.0. There is some variation in the size of cells at initiation, but it is proposed that this variation is less than the variation at other events of the cell cycle. The narrowing of the age-size structure at the time of initiation is a graphic representation of the size-homeostasis mechanism. No matter what size cells are present at birth or division, these cells are returned to their proper age-size relationship at the instant of initiation of DNA synthesis. Larger cells at division produce larger newborn cells which then reach initiation size earlier than smaller cells which were produced by the division of smaller dividing cells. This is a restatement of the idea that larger cells get to initiation earlier because larger cells have less of a negative age value at cell birth. At the top and right panels of (c) and (d) are representation of the presumed variation of the sizes and ages of cells at particular events. The size at birth is always a little more widely distributed than the size at division due to a slight inequality of partition of mass at division. The size at initiation of DNA replication is drawn with a relatively small variability.
There are, however, statistical variations in cell sizes at a given age and cells of a given age may have different sizes. The precise statistical distribution is not known, but one view of the possible result is shown in Fig. 11b. The shaded area indicates a cloud of points preferentially collected around the middle of the shaded area, with fewer cells at the outer edges. If this were a three-dimensional graph, there would be a peaked "ridge" up the center of the shaded area indicating that more cells reside with a particular age/size distribution than those at the edges of the age/size distribution.
It is possible to indicate the cells at particular times during the division cycle such as birth, division and initiation of DNA synthesis, as shown in Fig. 11c. There is no distribution in age at birth, since by definition age at birth is 0.0. The graphs at the upper and right sides of Fig. 11c are representations of the spread of the various distributions. There is variability in the age at initiation of DNA replication (I) and the age at division (D). The age at cell birth (B) is defined as constant (i.e., 0.0) but the size at birth (B) is not constant. It is expected that the size at division will be slightly less variable than the size at birth. This is attributable to the probability that any deviation from equipartition of dividing cells leads to a broadening of the size distribution in newborn cells. From Fig. 11c it can also be seen that larger newborn cells (distribution B) will reach the size at initiation (I) earlier than smaller newborn cells. This explains the size maintenance pattern drawn in Fig. 2. Note that in Fig. 11c the size at initiation is relatively narrow. It is this narrowing of size at initiation that leads to the slightly narrower size at division relative to the wider size distribution at birth.
An instructive way of looking at the age/size distribution is to replot cell ages using the age at initiation of DNA synthesis (I) as a starting point (Fig. 11d). By defining age at initiation as 0.0 one gets negative ages for cells before initiation and positive ages for cells after initiation. Fig. 11d shows that there is no distribution in the age at initiation (since by definition the age at initiation is 0.0 for all cells) but there is now a variation in the "age" of newborn cells. Smaller cells have a more negative age and take longer to reach initiation size than larger newborn cells; that is why there is a distribution of cell ages of newborn cells with respect to the time until initiation. The "bottleneck" at initiation of DNA synthesis enables cells born of different sizes to retain size homeostasis. Since all cells to the left of initiation must pass through the bottleneck of initiation on the way to division, all cells, of any newborn size, are realigned and assigned a new age and a new size as they pass through the act of initiation.
Summary
Understanding mammalian cell size control
This analysis explains how cell size is maintained through a combination of interdivision time variation and cell growth rate variation. Exponential growth is possible and allowed during the division cycle, in contrast to the proposal of Conlon and Raff [1]. The ideas presented here are a fresh way to look at the cell cycle and cell growth in eukaryotic cells, even though the ideas have been around for over three decades due to work on size determination in bacteria (Cooper, 1979; Helmstetter, 1969). The model of the cell cycle presented here explains many experimental results without postulating checkpoints, G1-phase events, restriction points, or similar phenomena. Experimental support for these ideas [28,29] and the application of these ideas to other problems of cell growth and differentiation [3,13-15,26,28-35] have been published. These ideas have also been reviewed [36-39].
It may be best to summarize these two contrasting views of size maintenance by looking at cell growth in a simple manner, and asking how the rate of mass increase is related to the passage of the cell through the cell cycle. The model of Conlon and Raff looks at the events of passage through the cell cycle as occurring independently of mass increase. The problem then remains as to how mass increase fits into, or coordinates with, the pattern or timing of passage through the cell cycle. It is as though the cell moves through the cell cycle without considering the mass problem, and then the mass of the cell looks at the cell cycle and says "I must grow at some rate so that I do not get too big or too small." In the Conlon/Raff model, a control exists that coordinates mass increase with the rate of cell division.
The model presented here–in contrast to the model of Conlon and Raff–situates mass as the driving force of the cell cycle. Mass increases at some rate that is determined by external conditions (medium, growth factors, pH, etc.). As the mass increases, the accumulation of mass starts or regulates passage through the cell cycle. A cell cannot grow to an abnormal larger size because at a certain cell size or cell mass the S phase is initiated and this event starts a sequence of events leading to mitosis and cytokinesis. A cell cannot get too small because if mass grows slowly (or even stops growing) then the later events of the cell cycle (S-, G2-, and M-phases) are delayed (or do not occur) until mass increases sufficiently to start S phase. A cell cannot get too large because at a certain size the cell initiates S phase leading to the relatively early cell division. A cell cannot get too small because if mass accumulation is inhibited then S phase initiations are also inhibited.
Thus, there is no problem relating mass increase and the cell cycle. Cell mass growth and cell cycle passage cannot be dissociated because one (mass increase) is the determinant of the other (S-phase initiation). For this reason one needs neither checkpoints nor control elements outside of mass increase.
The time for mass to double in a particular situation determines the doubling time of a culture. This is because initiations of S phase occur every mass doubling time, and cell divisions similarly occur every mass doubling time. Thus total mass increases at the same rate as total cell number.
The model presented here explains size determination, size maintenance, and the relationship of mass increase and cell number increase in a growing, exponential, unperturbed, mammalian cell cultures.
Acknowledgements
This paper is dedicated to Moselio Schaechter, who has supported and encouraged me over the years, who was a participant in what has been called "the Fundamental Experiment of Bacterial Physiology", the experiment that is the basis for the eukaryotic ideas presented here, and who has been a model scientist, person, and mentor.
Additional material on the ideas presented here may be viewed at .
I thank Charles Helmstetter, Robert Brooks, Arthur Koch, Martin Raff, Ian Conlon, and Sanjav Grewal for their comments and suggestions. Further comments, thoughts, critiques, suggestions, or ideas from readers of this article are most welcome
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| 15456512 | PMC524481 | CC BY | 2021-01-04 16:31:37 | no | BMC Cell Biol. 2004 Sep 29; 5:35 | utf-8 | BMC Cell Biol | 2,004 | 10.1186/1471-2121-5-35 | oa_comm |
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BMC Cell BiolBMC Cell Biology1471-2121BioMed Central London 1471-2121-5-361545857810.1186/1471-2121-5-36DebateControl and maintenance of mammalian cell size: Response Conlon Ian 12Ian.Conlon@dft.gsi.gov.ukRaff Martin 12m.raff@ucl.ac.uk1 MRC Laboratory for Molecular Cell Biology and Cell Biology Unit, University College London, London WC1E 6BT, UK2 Great Minster House, 77 Marsham Street, London SW1P 4DR, UK2004 30 9 2004 5 36 36 19 8 2004 30 9 2004 Copyright © 2004 Conlon and Raff; licensee BioMed Central Ltd.2004Conlon and Raff; 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.
A response to Cooper S: Control and maintenance of mammalian cell size. BMC Cell Biol 2004, 5:35
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Stephen Cooper was kind enough to send to us an original draft of his paper that now appears in BMC Cell Biology [1]. Although we have exchanged a number of e-mails with him in attempt to clarify points of confusion and disagreement, he continues to tilt at windmills and attack straw men. This is discouraging.
His paper claims to be an analysis of our paper that was published in Journal of Biology last year [2]. Unfortunately, in much of his paper, he challenges our answers to questions that we did not address, conclusions that we did not draw, and arguments that we did not make. There are too many examples of this to deal with them all.
One problem is semantic. He uses the term "cell growth" ambiguously, to mean both cell enlargement and cell number increase, which is confusing when discussing both cell growth and cell proliferation. In the Background, for example, he writes "How do cells maintain a constant cell size and cell size distribution during extended cell growth?".
There is more important confusion in the phrase "linear growth". He uses it to mean the addition of an equal amount of mass at each stage of the cell cycle, and he claims that we use it in our paper in the same way. In our paper, however, we clearly defined linear growth to describe our observation that Schwann cells, blocked in S phase with aphidicolin, added a constant amount of volume and mass per cell over time, independent of their size. This confusion leads him to claim erroneously, in his Abstract and elsewhere, that we proposed that mammalian cells grow linearly during the division cycle; we do not believe this, and we did not test it or discuss it in our paper. Much of his paper is based on the premise that we were trying to understand how cell growth changes through the cell cycle. In fact, we have never addressed this question, in the paper or elsewhere. For this reason, much of Cooper's paper is not relevant to ours.
Cooper criticizes individual experiments in our paper, but this too is almost always based on unnecessary misunderstanding. He accuses us, for example, of "an egregious error" in studying protein synthesis in Schwann cells that were not synchronized and therefore in all phases of the cell cycle. In fact, however, the cells were all arrested at the start of S phase with aphidicolin, as pointed out in both the text and figure legend.
Despite its length, Cooper's paper never comes to grips with either the two main findings in our paper or the points of the experiments described in it. Unlike yeast cells (S. pombe) blocked in S phase by a mutation, which grow faster as they enlarge [3], we found that Schwann cells blocked in S phase with aphidicolin continue to grow at the same rate as they enlarge, adding a constant amount of volume and protein each day, independent of their size, We argued, as have others [4], that if big and little cells grow at the same rate (at the same point in the cell cycle), they do not need a cell-size checkpoint to maintain a constant distribution of sizes as they proliferate, unlike the situation for yeast cells. A second important difference from yeast cells that we found was that Schwann cells shifted from serum-free medium to serum-containing medium took 5–6 divisions and more than a week to attain the larger size of cells continuously proliferating in serum. This is what one would predict for cells that do not have a cell-size checkpoint and where little cells grow at the same rate as big cells at the same point in the cell cycle [2,4]. By contrast, when similar shift-up experiments are performed with yeast cells, the cells attain their new larger size within one cell cycle when shifted from a nutrient-poor culture medium to a richer medium [5]. We concluded that, if Schwann cells have cell-size checkpoints, they are very different form those that operate in yeast cells.
Cooper also ignores our earlier findings that Schwann cell size at division depends simply on how fast the cells are growing and how fast they progress through the cell cycle and that both of these rates depend on the concentrations of extracellular signals that can regulate the two rates independently [6]. We found that GGF, for example, stimulated cell-cycle progression in these cells but not cell growth, whereas IGF-1 stimulated cell growth and synergized with GGF to stimulate cell-cycle progression. When IGF-1 concentration (and therefore cell growth) was held constant, an increase in the concentration of GGF drove the cells through the cycle faster; with less time to grow, the cells were smaller in high GGF compared to low GGF, at all stages of the cycle. These findings do not fit easily with Cooper's model that cell mass is the driving force of the cell cycle in all cells.
Cooper's model for how cell growth and cell division can be coordinated is one version of a cell-size checkpoint model, in which progression through the cell cycle is somehow linked to cell size. Such models have been widely accepted in the cell-cycle field to explain how proliferating cells maintain their appropriate size over time [7]. Whereas the evidence for cell-size checkpoints in single-cell organisms is strong, the evidence for them in animal cells is weak, despite Cooper's arguments to the contrary. Our studies suggest that cultured Schwann cells (and we suspect many other animal cells) do not need, and probably do not have, such cell-size checkpoints to coordinate their growth and division. This difference between single-cell organisms and animal cells is not surprising given their very different life styles: in bacteria and yeasts, cell growth and proliferation are controlled mainly by nutrients, whereas in animals, they are controlled mainly by signals from other cells.
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Cooper S Control and maintenance of mammalian cell size BMC Cell Biol 2004 5 35 15456512 10.1186/1471-2121-5-35
Conlon I Raff M Differences in the way a mammalian cell and yeast cells coordinate cell growth and cell-cycle progression J Biol 2003 2
Nurse P Thuriaux P Nasmyth K Genetic control of the cell division cycle in the fission yeast Schizosaccharomyces pombe Mol Gen Genet 1976 146 167 178 958201 10.1007/BF00268085
Brooks RF John PCL Variability in the cell cycle and the control of proliferation In The Cell Cycle 1981 Cambridge: Cambridge University Press
Fantes P Nurse P Control of cell size at division in fission yeast by a growth-modulated size control over nuclear division Exp Cell Res 1977 107 377 386 872891
Conlon I Dunn GA Mudge AW Raff MC Extracellular control of cell size Nature Cell Biol 2002 3 918 921 11584274 10.1038/ncb1001-918
Polymenis M Schmidt EV Coordination of cell growth with cell division Curr Opin Genet Dev 1999 9 76 80 10072360 10.1016/S0959-437X(99)80011-2
| 15458578 | PMC524482 | CC BY | 2021-01-04 16:31:36 | no | BMC Cell Biol. 2004 Sep 30; 5:36 | utf-8 | BMC Cell Biol | 2,004 | 10.1186/1471-2121-5-36 | oa_comm |
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BMC Evol BiolBMC Evolutionary Biology1471-2148BioMed Central London 1471-2148-4-371546181910.1186/1471-2148-4-37Research ArticleEvolution and distribution of RNA polymerase II regulatory sites from RNA polymerase III dependant mobile Alu elements Shankar Ravi 1ravis@igib.res.inGrover Deepak 1grover@igib.res.inBrahmachari Samir K 1skb@igib.res.inMukerji Mitali 1mitali@igib.res.in1 Functional Genomics Unit, Institute of Genomics and Integrative Biology (IGIB), CSIR, Mall Road, Delhi 110007, India2004 4 10 2004 4 37 37 1 7 2004 4 10 2004 Copyright © 2004 Shankar et al; licensee BioMed Central Ltd.2004Shankar 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 primate-specific Alu elements, which originated 65 million years ago, exist in over a million copies in the human genome. These elements have been involved in genome shuffling and various diseases not only through retrotransposition but also through large scale Alu-Alu mediated recombination. Only a few subfamilies of Alus are currently retropositionally active and show insertion/deletion polymorphisms with associated phenotypes. Retroposition occurs by means of RNA intermediates synthesised by a RNA polymerase III promoter residing in the A-Box and B-Box in these elements. Alus have also been shown to harbour a number of transcription factor binding sites, as well as hormone responsive elements. The distribution of Alus has been shown to be non-random in the human genome and these elements are increasingly being implicated in diverse functions such as transcription, translation, response to stress, nucleosome positioning and imprinting.
Results
We conducted a retrospective analysis of putative functional sites, such as the RNA pol III promoter elements, pol II regulatory elements like hormone responsive elements and ligand-activated receptor binding sites, in Alus of various evolutionary ages. We observe a progressive loss of the RNA pol III transcriptional potential with concomitant accumulation of RNA pol II regulatory sites. We also observe a significant over-representation of Alus harboring these sites in promoter regions of signaling and metabolism genes of chromosome 22, when compared to genes of information pathway components, structural and transport proteins. This difference is not so significant between functional categories in the intronic regions of the same genes.
Conclusions
Our study clearly suggests that Alu elements, through retrotransposition, could distribute functional and regulatable promoter elements, which in the course of subsequent selection might be stabilized in the genome. Exaptation of regulatory elements in the preexisting genes through Alus could thus have contributed to evolution of novel regulatory networks in the primate genomes. With such a wide spectrum of regulatory sites present in Alus, it also becomes imperative to screen for variations in these sites in candidate genes, which are otherwise repeat-masked in studies pertaining to identification of predisposition markers.
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Background
In the post genome sequence era, repetitive sequences, erstwhile considered junk and devoid of function, are increasingly being implicated in many cellular functions, genome organization and diseases [1-8]. Alu repeats, which belong to SINE (short interspersed nucleotide elements) family of repetitive sequences, are present exclusively in the primate genomes. These elements which are ~300 bps in length have originated from the 7SL RNA gene and comprise of two similar, but not identical subunits [9-12]. Each element contains a bipartite promoter for RNA polymerase III, a poly (A) tract located between the monomers, a 3'-terminal poly(A) tract, a number of CpG dinucleotides, and is flanked by short direct repeats [13,14]. Based on certain diagnostic site mutations, they have been broadly classified into three subfamilies: Old (Alu Js), Middle (Alu S) and the Youngest (Alu Ys) [15,16]. Further, some of the Alu Y sequences are very new and exhibit polymorphisms, indicating that they have recently undergone retropositioning process [17].
Alus have been shown to harbor a number of regulatory sites like hormone response element (HRE), and a couple of ligand activated transcription factor binding sites [18-24]. These sites regulate the expression of downstream genes, in some cases in a temporal or tissue specific manner. Most of the regulatory sites in Alus have been reported during the course of characterization of specific genes [25-32]. Besides, the intrinsic A-Box and B-Box RNA polymerase III (RNA pol III) sequences and the recombinogenic sites present in these elements are involved in retrotranspositional and recombination process [10].
Alus originally demonstrated to have non uniform distribution on the chromosomes through banding studies [33,34] have been recently substantiated by genome sequence analysis [35]. It has been observed that that Alus not only show a non- random pattern of distribution in the human chromosomes but also varying densities within genes. Additionally, in a genome wide expression analysis, co-variation of expression of gene pairs has been attributed to sequence similarity metric in the upstream region of promoter predominantly contributed by Alu repeats present in these regions [36]. These effects of Alu have been shown to be completely independent of the effects of isochoric (GC) composition on Alu density as well as gene expression [34-36].
Identification and analysis of various permutations and combinations of these regulatory elements in otherwise conserved repetitive Alus are mostly excluded from genetic analysis. Since, Alus occupy a tenth of the human genome, it is imperative to identify those, which might assume function in the proper context. Our primary aim in this analysis is to find out if any bias exists in the distribution of transcriptional regulatory sites in Alus of various evolutionary ages and their distribution with respect to the functional classes of genes.
Results and Discussion
Distribution of functional sites in Alus is position specific
As a first step toward examining the role of these regulatory sites, we mapped their most probable positions on Alus, using in house developed algorithms (Figure 1). This was carried out on 500 Alus, each of Alu Jo, Alu Jb, Alu Sx, Alu Sc, Alu Yb8 and Alu Y subfamilies. The classification of these evolutionarily distinct subfamilies are based on diagnostic sites [15,16,37,38]. Besides, members of the most recent and retropositionally active and polymorphic Alus were also included in the analysis [39,40]. Though the polymorphic Alus belong to Alu Y subfamily, these were treated as a separate category since insertion/deletion of these Alus have been associated with many phenotypes/diseases [2]. The regulatory sites show positional conservation across all subfamilies in which they are represented (Table 1). However, these sites are distinct from the diagnostic sites, which are used for classifying Alus, which suggests that they have not arisen randomly in different subfamilies.
Table 1 Position of sites analysed in Alu repeats in various subfamilies.
Family A-box B-box AML MPO CETP Rec AP1 ERE RARE TRE nCaRE LXR
Jb 5 76 48 48 47 22 13/221 80 57–76 -67 289
Jo 5 76 48 48 47 22 13/221 80 66 -67 289 224–240
Sx 5 76 48 48 47 22 13 80 60 -67 289 237–250
Sc 5 76 48 48 47 22 13/267 80 68 -67 289
Y 5 76 48 48 47 22 80 -67 289
Yb8 5 76 48 48 47 22 13/270 80 60–66 -67 289 230–240
POLY 5 76 48 48 47 22 13/267 80 60 -67 289
Figure 1 Representation of regulatory sites on Alu elements. 500 representative Alu sequences each of distinct evolutionary ages were selected for identification of most probable regulatory sites. 126 polymorphic Alus (POLY) from younger subfamilies which show insertion – deletion polymorphisms were also analysed. Sites were identified using local alignment based program as well as by probabilistic modelling approach. These sites are positionally conserved in all subfamilies.
Evolution of regulatory sites is biased and clustered in Alus
Nearly all the analyzed regulatory sites for RNA polymerase II (RNA pol II) are distributed in the region between A- Box and B-Box with more clustering near the B-Box region (Figure 1). There is an evolutionary age specific loss / gain of these sites in various subfamilies leading to a bias in their distribution (Figure 2). Newly transposing Alus have methylated CpG sites, which are prone to transition. Many sites seem to have evolved as a consequence of these transitions. The regulatory elements are most abundant in the middle subfamilies and least represented in the younger Alus. Some sites like AP1, ERE, nCARE are present in older and middle Alus but rarely so in the younger as well as polymorphic Alus. An opposite trend is observed for CETP, wherein the highest density is observed in the younger active and polymorphic Alus. RARE and TRE sites are retained in all subfamilies whereas LXR is specific to only middle Alu subfamilies (Figure 2). It is curious, nCARE which is also present in the 7sl RNA, the progenitor of Alus, is not equally represented in all Alus and has higher density in the older Alus and middle and is very poorly represented in the younger subfamilies.
Figure 2 Distribution of regulatory sites in various Alu subfamilies as well as polymorphic Alus. On the X-axis Alus of different evolutionary ages as well as polymorphic Alus (POLY) are represented. On the Y-axis the percentage of elements carrying these sites in various subfamilies is indicated.
Evolution from retropositionally active to transcriptionally active Alu elements
Majority of Alu retroposition has ceased at least 30 million years ago and only a few Alu subfamilies are still active [15,17,41]. Transcription of Alus is a prerequisite for retrotransposition and there is regulation not only during transcription initiation but also at the level of stability of transcripts [42]. Alu elements are transcribed by RNA pol III which are composed of two properly spaced conserved sequence motifs, an upstream element named the A-Box and a downstream element called the B Box which are essential for efficient transcription. Deletion of the Box B sequences within the Alu repeat completely abolishes the transcriptional activity. In the absence of box A sequences even though there is a reduction in efficiency of transcription by 10 to 20 fold, B-Box sequence is still capable of initiating transcription 70 bps upstream [43,44]. An intact A Box is therefore a critical determinant for RNA pol III retropositional activity. Besides, it has been shown by in vitro as well as in vivo studies in the 'B' Box that 'G' and 'T' residues at the 1st and 3rd positions respectively are very critical for it's functioning [45]. Our analysis on the distribution of these promoter elements show that the polymorphic Alu sequences have the highest density of A Box (70%) and is almost absent in older subfamilies (Figure 2). Since the younger Alus are considered to be transcriptionally more active, this fits in well with the loss of this site in the course of evolution due to accumulation of mutations. The B Box motif with the sequence G(A/T)T(C/T)RANNC shows a similar trend as the A Box. Interestingly, a fraction of older Alu subfamily still retains the B-Box sequence. However, 'A' residue at the second position which has not been shown to be critical for transcription is a diagnostic nucleotide [39] for the younger subfamilies. This could result in the increased proportion for B-Box in the younger families. We observe a very curious distribution of the B Box motif if we consider the sequence GTT(C/T)GAGAC (B'Box in Figure 2) wherein we restrict the pattern to the experimentally validated sequence. Alu Sx and Alu Sc have the highest density match with this pattern, followed by the older subfamilies and it is present in only < 2% frequency in AluY and polymorphic Alus. The "C" at the 4th position in this case is mutated to "T" in the older families. The Yb8 family that has been reported to be transcriptionally and retropositionally active amongst the younger subfamilies, retains the B'-Box element in a significant fraction. This suggests that even though retropositionally competent younger Alus are hypothesized to be transcriptionally active, only a minority retains consensus B'-Box. It is possible that the enhancing activity of the A Box is sufficient to drive transcription from the weaker B'- Box in the younger subfamilies. Our findings corroborates well with an earlier study in which presence of all subfamilies in the RNA polymerase III driven Alu transcript pool was reported [46]. Additionally, it was also observed that though there was a quantitative bias towards younger subfamilies and younger members of these subfamilies (based on their relative presence in the transcript compared to their abundance in the genome), there was a preferential expression of the middle subfamilies relative to the most active subfamilies. Our observations, therefore, further rules out the hypothesis that transcription may be biased only towards retropositionally active subfamilies of Alu elements. This could be the reason why only a fraction of younger Alus is currently retrotranspositionally active. The presence and retention of B-Box coupled with near absence of A Box in the Alu Sx and AluSc families suggests basal level of transcription from these elements which could be enhanced through binding of other regulatory proteins under certain conditions such as stress [47]. Additionally, with evidence of presence of naturally occurring Alu antisense as well as edited Alu transcripts [48,49], transcribing Alus could play a major role in yet unknown biological processes.
Exaptation of Alus in the transcriptional regulatory repertoire
Alus have been demonstrated to exert effects at transcription, post-transcription as well as at the translation level. In an earlier study on complete chromosomes 21 and 22, we have demonstrated that the Alu elements are clustered in genes of signaling, metabolic and transport proteins and rarely present in the structural and information proteins [50]. This clustering bias was found to be irrespective of genomic location, GC content, length of genes or intronic content. To further address whether the Alus harboring transcriptional regulatory sites also show a selective distribution and thereby exert effects on transcription, we analyzed their distribution in the genes of various functional categories of chromosome 22. Two different datasets 1) Promoter region Alus and 2) Intronic region Alus, harboring regulatory sites were analyzed. The promoter region Alus of genes involved in metabolism, signaling were significantly rich in regulatory sites compared to those of information, structure and transport (F value = 4.86, df = 4, 40, p-value < 0.0027). In the intronic regions, distinction in their distribution with respect to functional categories was not so significant though the intronic regions also harboured Alus containing regulatory sites (F value = 2.92, df = 4,40, p-value = 0.032). Since the genes of the signaling and metabolic pathway are more subject to regulation by cellular cues like hormonal triggers, this observation is significant. Most of the Alus in the promoters belong to the middle Alu S families and rarely Younger Alus are present. Since younger Alus also harbour few regulatory sites and actively retropose, it is possible that there is a negative selection against their insertion in the promoter sites of genes of information pathways and structural proteins [see the supplementary data].
Alu movements and aberrant gene expression
Gene inversions, duplications and formation of pseudogenes have been extensively reported to be mediated both through retrotransposition as well as recombination of Alus. This, in many cases, has also been associated with aberrant gene expression. For instance, presence of AML sites in an Alu upstream of MPO gene, has been first demonstrated to be associated with Acute Myelocytic Leukemia [20]. This is due to the presence of a strong SP1 site within AML which leads to over expression of MPO gene. AML sites are most abundant in younger and polymorphic Alus and a single base pair transition results in MPO site, present predominantly in the members of older subfamilies. In the case of polymorphic Alus, many sequences that do not show 100% conservation of AML site still retain the SP1 site. Interestingly, the core recombinogenic site is also most predominant in younger and polymorphic Alus. The presence of recombinogenic sites in polymorphic Alus, could therefore not only contribute to genome shuffling but also serve to distribute ectopic sites such as AML through retrotransposition and recombination (Figure 2).
Regulatory region distribution through Alu expansion
Analysis of regulatory sites within Alus suggests that a polymorphic Alu has the potential to transpose and recombine which allows it to integrate at random sites in the genome. They also harbour potential regulatory sites, which could evolve to become accessory sites for RNA pol II transcription as revealed by their clustering in older subfamilies. Further, the Alu sequence due to acquisition of novel functions could form a part of the transcription repertoire involved in the regulation of the downstream /associated genes and create novel regulatory networks (Figure 3). These results also corroborate with the hypothesis of evolution of transposable elements of Kidwell [51] wherein they had proposed a 3 stage life cycle of class II Transposable elements:- invasion and amplification followed by mutations and maturity and finally senescence and fading. In the case of Alu, instead of fading, they could also evolve to become members of host regulatory machinery.
Figure 3 Alu expansion and evolution of regulatory sites. With the help of LINEs, Alu may keep on retro-transposing or may get inactive/negatively selected. Alternatively, it may integrate upstream of a gene, accumulate mutations, evolve RNA pol II regulatory sites, get stabilized and control gene expression. This is supported by the presence of sparse regulatory sites, unhindered A box, recombinogenic sites initially in the younger and active Alus and its accumulation in older Alu subfamilies as well as significant presence of Alus harbouring regulatory sites in the promoter encompassing regions of the genes of signaling and metabolic pathways.
Conclusions
Comparison of sequences in the regulatory regions of many homologous genes in human have shown accumulation of Alus, not only post divergence from non-human primates but also during primate evolution [52]. Perhaps, recruitment of cis regulatory elements responsive to cellular cues through Alu elements could result in altered spatial and temporal transcription of genes as well as create novel metabolic and signaling networks. These might contribute to the observable physiological complexity in human and primates [53]. Additionally, the underlying events which would be defining event of speciation of human from chimpanzee (with which it shares nearly 99% homology at coding level) still eludes identification and might to some extent reside in such genomic elements. These issues can now be addressed through comparison of these sites in human and chimpanzee.
Currently, Alus are repeat-masked in all studies pertaining to identification of predisposition markers in complex disorders. With such wide spectrum of nuclear receptors, which play a major role in maintaining normal physiological state and affect as diverse processes as development, reproduction, general metabolism, residing in Alus, it therefore becomes imperative to screen for variations in these sites. This might have important consequences in the candidate genes for those complex diseases that are triggered in response to hormonal imbalances as well as other environmental cues.
Methods
126 polymorphic Alu sequences cited in literature [39,40] were retrieved using NCBI BLAST and Repeat Masker software[54,55]. The analysis was carried out on Alu repeats of human chromosome 22. A randomly selected representative set of approximately 500 Alu sequences, each of distinct evolutionary ages, Alu Jb, Alu Jo, Alu Sx, Alu Sc, Alu Yb8 and Alu Y were used for the analysis. Sequences were retrieved from Sanger Institute Home Page, June 2001 release [56]. Besides, Alus were also analyzed within 5000 base pairs upstream of genes of chromosome 22 in the regulatory regions encompassing promoter sequences as well as inside their intronic regions.
Collection of biologically active sites
Information about the regulatory sites and their sequences was collected from various literature sources (Table 2). Characteristic features of the sites are given below. We selected those regulatory sites, which have been shown to have function in the Alu elements. The A Box and B Box sequences define the bipartite internal promoters, which bind RNA polymerase III. MPO and AML sites, which are 14 nucleotides differ by an A / G at 5th position of the sequence and transition from G to A at this site converts the MPO allele to AML, resulting in the formation of a strong SP-1 binding site and over expression of the following gene. AP1 sites bind AP-1 transcription factor, which is a dimeric complex that contains members of the JUN, FOS, ATF and MAF protein families. Hormone responsive elements (HRE) are super family of binding sites for ligand activated nuclear hormone receptors for thyroid hormone (TRE), retinoic acid (RARE) and vitamin D, which regulate gene transcription. Estrogen response elements (EREs) are sites for binding of estrogen receptor (ER), a ligand-activated enhancer protein that is a member of the steroid/nuclear receptor super family and transactivates gene expression in response to estradiol. The negative calcium response element type 2 (nCARE) is a regulatory DNA sequence, which inhibits transcription in response to raised extra cellular calcium levels. The nuclear receptors liver X (LXR) is involved in different cell-signaling pathways. CETP site is an orphan receptor site in the Alu in promoter of cholesteryl ester transfer protein (CETP) which plays a key role in reverse cholesterol transport in mediating the transfer of cholesteryl ester from HDL to atherogenic apolipoprotein B-containing lipoproteins.
Table 2 Sequences of regulatory elements analysed in Alu repeats.
Site Sequence
Retinoic acid response element (RARE) 5'(AG)G(GT)TCA 3'
Estrogen Response Element (ERE) 5'(GA)(GA)TCA(CG)(AC)(CG)TGACC 3'
Negative calcium response element (nCARE) 5' TGAGACNNNGTCTCAAAAA 3'
Liver X receptor 5' GACCTNNNNTGATCC 3'
Cholestryl esterase transferase response element (CETP) 5'CCGNGGCGGGC 3'
AP1 site 5' T(GTA)A(GC)TCA 3'
Acute Myelocytic Leukemia (AML) site 5' AGGCGGGTGGATCA 3'
Myelo Peroxidase (MPO) site 5' AGGCAGGTGGATCA 3'
Recombinogenic site 5'CCCTGTAATCCTAGCACTTTGGAGGC 3'
A-Box 5' GGGCGCGGTGGC 3'
B-Box 5' G(A/T)T(C/T)RANNC 3'
B'Box 5' G TT(C/T)GAGAC 3'
Nucleotide sequences in parenthesis indicate alternate nucleotides and have been written in increasing order of their preference.
Computational methods
Two different programs were written in order to locate the most probable biologically significant regions. A local alignment based program, Xalign, was implemented in C++, Red Hat 7.3 based Linux. This program finds the probable sites by aligning the consensus of regulatory site with the query sequence. Multiple queries with a size upto 600 nucleotides can be taken at a time. Another program, Promotif, was implemented in C++, Red Hat 7.3 based Linux, using the probabilistic modeling approach. It uses the position weight matrix, normalization of the positions with conservation index (Ci Value), and inter-nucleotide dependence in terms of transition matrix to find out the sites. Position weight matrices were generated using Gibbs Motif Sampler, for every site included in the program. The sequences for position weight matrix generation were carefully selected based on the sequence and length reported for each binding site. The final length for search was fixed at the lowest length observed. This provides element specific matrix with lesser chance for the selection on non-RE regions. For the sites analyzed, it had an in built transition matrix, position weight matrix and conservation index. Batch analysis of over a thousand Alu sequences can be performed with this program.
Using the annotated sequences from literature as well as from NCBI web page, training set for the probabilistic model was created. Training was done for approximately 70% sequences and rest of the sequences were taken as test set. Details of the program along with the equations used are available on request.
Mapping of recently integrated and younger Alus
About 126 recently integrated Alus from younger subfamilies were searched in the human genome using BLASTn at NCBI server and regulatory sites were mapped in these regions using the programs discussed above.
Association analysis
Alus in the promoter regions and intronic regions of functionally classified genes [50] of chromosome 22 were mapped and pattern of distribution of biologically significant sites were analyzed by ANOVA.
Authors' contributions
RS developed the algorithms and programs for identifying regulatory and significant regions, carried out the analysis of distribution of these sites in Alu subfamilies, association analysis and drafted the manuscript. DG was involved in chromosome 22 analyses. SKB participated in the design of the study. MM conceived of the study, participated in its design, analysis, coordination and manuscript preparation. All authors read and approved the final manuscript.
Supplementary Material
Supplementary data
The analysis over the promoter and intronic regions has been performed through the data given in the supplementary table file, supplementary table 3_ravishankar et al. Format: .xls. For human chromosome 22, the data contains the accession number, associated Alu family, the respective positions, functional class of the region and further details, for each associated regulatory element found within the Alu repeats in the 5' flanking promoter and intronic regions. The zipped file name is supplementary 1.zip. Details about programs used are on request for academic users.
Click here for file
Acknowledgements
We thank Krishna Kumar and S Suganya for computational support. Financial support from Council of Scientific and Industrial Research (CSIR) projects (CMM0016) to MM and (CMM0017) to SKB is duly acknowledged.
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| 15461819 | PMC524483 | CC BY | 2021-01-04 16:29:01 | no | BMC Evol Biol. 2004 Oct 4; 4:37 | utf-8 | BMC Evol Biol | 2,004 | 10.1186/1471-2148-4-37 | oa_comm |
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BMC Evol BiolBMC Evolutionary Biology1471-2148BioMed Central London 1471-2148-4-371546181910.1186/1471-2148-4-37Research ArticleEvolution and distribution of RNA polymerase II regulatory sites from RNA polymerase III dependant mobile Alu elements Shankar Ravi 1ravis@igib.res.inGrover Deepak 1grover@igib.res.inBrahmachari Samir K 1skb@igib.res.inMukerji Mitali 1mitali@igib.res.in1 Functional Genomics Unit, Institute of Genomics and Integrative Biology (IGIB), CSIR, Mall Road, Delhi 110007, India2004 4 10 2004 4 37 37 1 7 2004 4 10 2004 Copyright © 2004 Shankar et al; licensee BioMed Central Ltd.2004Shankar 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 primate-specific Alu elements, which originated 65 million years ago, exist in over a million copies in the human genome. These elements have been involved in genome shuffling and various diseases not only through retrotransposition but also through large scale Alu-Alu mediated recombination. Only a few subfamilies of Alus are currently retropositionally active and show insertion/deletion polymorphisms with associated phenotypes. Retroposition occurs by means of RNA intermediates synthesised by a RNA polymerase III promoter residing in the A-Box and B-Box in these elements. Alus have also been shown to harbour a number of transcription factor binding sites, as well as hormone responsive elements. The distribution of Alus has been shown to be non-random in the human genome and these elements are increasingly being implicated in diverse functions such as transcription, translation, response to stress, nucleosome positioning and imprinting.
Results
We conducted a retrospective analysis of putative functional sites, such as the RNA pol III promoter elements, pol II regulatory elements like hormone responsive elements and ligand-activated receptor binding sites, in Alus of various evolutionary ages. We observe a progressive loss of the RNA pol III transcriptional potential with concomitant accumulation of RNA pol II regulatory sites. We also observe a significant over-representation of Alus harboring these sites in promoter regions of signaling and metabolism genes of chromosome 22, when compared to genes of information pathway components, structural and transport proteins. This difference is not so significant between functional categories in the intronic regions of the same genes.
Conclusions
Our study clearly suggests that Alu elements, through retrotransposition, could distribute functional and regulatable promoter elements, which in the course of subsequent selection might be stabilized in the genome. Exaptation of regulatory elements in the preexisting genes through Alus could thus have contributed to evolution of novel regulatory networks in the primate genomes. With such a wide spectrum of regulatory sites present in Alus, it also becomes imperative to screen for variations in these sites in candidate genes, which are otherwise repeat-masked in studies pertaining to identification of predisposition markers.
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Background
In the post genome sequence era, repetitive sequences, erstwhile considered junk and devoid of function, are increasingly being implicated in many cellular functions, genome organization and diseases [1-8]. Alu repeats, which belong to SINE (short interspersed nucleotide elements) family of repetitive sequences, are present exclusively in the primate genomes. These elements which are ~300 bps in length have originated from the 7SL RNA gene and comprise of two similar, but not identical subunits [9-12]. Each element contains a bipartite promoter for RNA polymerase III, a poly (A) tract located between the monomers, a 3'-terminal poly(A) tract, a number of CpG dinucleotides, and is flanked by short direct repeats [13,14]. Based on certain diagnostic site mutations, they have been broadly classified into three subfamilies: Old (Alu Js), Middle (Alu S) and the Youngest (Alu Ys) [15,16]. Further, some of the Alu Y sequences are very new and exhibit polymorphisms, indicating that they have recently undergone retropositioning process [17].
Alus have been shown to harbor a number of regulatory sites like hormone response element (HRE), and a couple of ligand activated transcription factor binding sites [18-24]. These sites regulate the expression of downstream genes, in some cases in a temporal or tissue specific manner. Most of the regulatory sites in Alus have been reported during the course of characterization of specific genes [25-32]. Besides, the intrinsic A-Box and B-Box RNA polymerase III (RNA pol III) sequences and the recombinogenic sites present in these elements are involved in retrotranspositional and recombination process [10].
Alus originally demonstrated to have non uniform distribution on the chromosomes through banding studies [33,34] have been recently substantiated by genome sequence analysis [35]. It has been observed that that Alus not only show a non- random pattern of distribution in the human chromosomes but also varying densities within genes. Additionally, in a genome wide expression analysis, co-variation of expression of gene pairs has been attributed to sequence similarity metric in the upstream region of promoter predominantly contributed by Alu repeats present in these regions [36]. These effects of Alu have been shown to be completely independent of the effects of isochoric (GC) composition on Alu density as well as gene expression [34-36].
Identification and analysis of various permutations and combinations of these regulatory elements in otherwise conserved repetitive Alus are mostly excluded from genetic analysis. Since, Alus occupy a tenth of the human genome, it is imperative to identify those, which might assume function in the proper context. Our primary aim in this analysis is to find out if any bias exists in the distribution of transcriptional regulatory sites in Alus of various evolutionary ages and their distribution with respect to the functional classes of genes.
Results and Discussion
Distribution of functional sites in Alus is position specific
As a first step toward examining the role of these regulatory sites, we mapped their most probable positions on Alus, using in house developed algorithms (Figure 1). This was carried out on 500 Alus, each of Alu Jo, Alu Jb, Alu Sx, Alu Sc, Alu Yb8 and Alu Y subfamilies. The classification of these evolutionarily distinct subfamilies are based on diagnostic sites [15,16,37,38]. Besides, members of the most recent and retropositionally active and polymorphic Alus were also included in the analysis [39,40]. Though the polymorphic Alus belong to Alu Y subfamily, these were treated as a separate category since insertion/deletion of these Alus have been associated with many phenotypes/diseases [2]. The regulatory sites show positional conservation across all subfamilies in which they are represented (Table 1). However, these sites are distinct from the diagnostic sites, which are used for classifying Alus, which suggests that they have not arisen randomly in different subfamilies.
Table 1 Position of sites analysed in Alu repeats in various subfamilies.
Family A-box B-box AML MPO CETP Rec AP1 ERE RARE TRE nCaRE LXR
Jb 5 76 48 48 47 22 13/221 80 57–76 -67 289
Jo 5 76 48 48 47 22 13/221 80 66 -67 289 224–240
Sx 5 76 48 48 47 22 13 80 60 -67 289 237–250
Sc 5 76 48 48 47 22 13/267 80 68 -67 289
Y 5 76 48 48 47 22 80 -67 289
Yb8 5 76 48 48 47 22 13/270 80 60–66 -67 289 230–240
POLY 5 76 48 48 47 22 13/267 80 60 -67 289
Figure 1 Representation of regulatory sites on Alu elements. 500 representative Alu sequences each of distinct evolutionary ages were selected for identification of most probable regulatory sites. 126 polymorphic Alus (POLY) from younger subfamilies which show insertion – deletion polymorphisms were also analysed. Sites were identified using local alignment based program as well as by probabilistic modelling approach. These sites are positionally conserved in all subfamilies.
Evolution of regulatory sites is biased and clustered in Alus
Nearly all the analyzed regulatory sites for RNA polymerase II (RNA pol II) are distributed in the region between A- Box and B-Box with more clustering near the B-Box region (Figure 1). There is an evolutionary age specific loss / gain of these sites in various subfamilies leading to a bias in their distribution (Figure 2). Newly transposing Alus have methylated CpG sites, which are prone to transition. Many sites seem to have evolved as a consequence of these transitions. The regulatory elements are most abundant in the middle subfamilies and least represented in the younger Alus. Some sites like AP1, ERE, nCARE are present in older and middle Alus but rarely so in the younger as well as polymorphic Alus. An opposite trend is observed for CETP, wherein the highest density is observed in the younger active and polymorphic Alus. RARE and TRE sites are retained in all subfamilies whereas LXR is specific to only middle Alu subfamilies (Figure 2). It is curious, nCARE which is also present in the 7sl RNA, the progenitor of Alus, is not equally represented in all Alus and has higher density in the older Alus and middle and is very poorly represented in the younger subfamilies.
Figure 2 Distribution of regulatory sites in various Alu subfamilies as well as polymorphic Alus. On the X-axis Alus of different evolutionary ages as well as polymorphic Alus (POLY) are represented. On the Y-axis the percentage of elements carrying these sites in various subfamilies is indicated.
Evolution from retropositionally active to transcriptionally active Alu elements
Majority of Alu retroposition has ceased at least 30 million years ago and only a few Alu subfamilies are still active [15,17,41]. Transcription of Alus is a prerequisite for retrotransposition and there is regulation not only during transcription initiation but also at the level of stability of transcripts [42]. Alu elements are transcribed by RNA pol III which are composed of two properly spaced conserved sequence motifs, an upstream element named the A-Box and a downstream element called the B Box which are essential for efficient transcription. Deletion of the Box B sequences within the Alu repeat completely abolishes the transcriptional activity. In the absence of box A sequences even though there is a reduction in efficiency of transcription by 10 to 20 fold, B-Box sequence is still capable of initiating transcription 70 bps upstream [43,44]. An intact A Box is therefore a critical determinant for RNA pol III retropositional activity. Besides, it has been shown by in vitro as well as in vivo studies in the 'B' Box that 'G' and 'T' residues at the 1st and 3rd positions respectively are very critical for it's functioning [45]. Our analysis on the distribution of these promoter elements show that the polymorphic Alu sequences have the highest density of A Box (70%) and is almost absent in older subfamilies (Figure 2). Since the younger Alus are considered to be transcriptionally more active, this fits in well with the loss of this site in the course of evolution due to accumulation of mutations. The B Box motif with the sequence G(A/T)T(C/T)RANNC shows a similar trend as the A Box. Interestingly, a fraction of older Alu subfamily still retains the B-Box sequence. However, 'A' residue at the second position which has not been shown to be critical for transcription is a diagnostic nucleotide [39] for the younger subfamilies. This could result in the increased proportion for B-Box in the younger families. We observe a very curious distribution of the B Box motif if we consider the sequence GTT(C/T)GAGAC (B'Box in Figure 2) wherein we restrict the pattern to the experimentally validated sequence. Alu Sx and Alu Sc have the highest density match with this pattern, followed by the older subfamilies and it is present in only < 2% frequency in AluY and polymorphic Alus. The "C" at the 4th position in this case is mutated to "T" in the older families. The Yb8 family that has been reported to be transcriptionally and retropositionally active amongst the younger subfamilies, retains the B'-Box element in a significant fraction. This suggests that even though retropositionally competent younger Alus are hypothesized to be transcriptionally active, only a minority retains consensus B'-Box. It is possible that the enhancing activity of the A Box is sufficient to drive transcription from the weaker B'- Box in the younger subfamilies. Our findings corroborates well with an earlier study in which presence of all subfamilies in the RNA polymerase III driven Alu transcript pool was reported [46]. Additionally, it was also observed that though there was a quantitative bias towards younger subfamilies and younger members of these subfamilies (based on their relative presence in the transcript compared to their abundance in the genome), there was a preferential expression of the middle subfamilies relative to the most active subfamilies. Our observations, therefore, further rules out the hypothesis that transcription may be biased only towards retropositionally active subfamilies of Alu elements. This could be the reason why only a fraction of younger Alus is currently retrotranspositionally active. The presence and retention of B-Box coupled with near absence of A Box in the Alu Sx and AluSc families suggests basal level of transcription from these elements which could be enhanced through binding of other regulatory proteins under certain conditions such as stress [47]. Additionally, with evidence of presence of naturally occurring Alu antisense as well as edited Alu transcripts [48,49], transcribing Alus could play a major role in yet unknown biological processes.
Exaptation of Alus in the transcriptional regulatory repertoire
Alus have been demonstrated to exert effects at transcription, post-transcription as well as at the translation level. In an earlier study on complete chromosomes 21 and 22, we have demonstrated that the Alu elements are clustered in genes of signaling, metabolic and transport proteins and rarely present in the structural and information proteins [50]. This clustering bias was found to be irrespective of genomic location, GC content, length of genes or intronic content. To further address whether the Alus harboring transcriptional regulatory sites also show a selective distribution and thereby exert effects on transcription, we analyzed their distribution in the genes of various functional categories of chromosome 22. Two different datasets 1) Promoter region Alus and 2) Intronic region Alus, harboring regulatory sites were analyzed. The promoter region Alus of genes involved in metabolism, signaling were significantly rich in regulatory sites compared to those of information, structure and transport (F value = 4.86, df = 4, 40, p-value < 0.0027). In the intronic regions, distinction in their distribution with respect to functional categories was not so significant though the intronic regions also harboured Alus containing regulatory sites (F value = 2.92, df = 4,40, p-value = 0.032). Since the genes of the signaling and metabolic pathway are more subject to regulation by cellular cues like hormonal triggers, this observation is significant. Most of the Alus in the promoters belong to the middle Alu S families and rarely Younger Alus are present. Since younger Alus also harbour few regulatory sites and actively retropose, it is possible that there is a negative selection against their insertion in the promoter sites of genes of information pathways and structural proteins [see the supplementary data].
Alu movements and aberrant gene expression
Gene inversions, duplications and formation of pseudogenes have been extensively reported to be mediated both through retrotransposition as well as recombination of Alus. This, in many cases, has also been associated with aberrant gene expression. For instance, presence of AML sites in an Alu upstream of MPO gene, has been first demonstrated to be associated with Acute Myelocytic Leukemia [20]. This is due to the presence of a strong SP1 site within AML which leads to over expression of MPO gene. AML sites are most abundant in younger and polymorphic Alus and a single base pair transition results in MPO site, present predominantly in the members of older subfamilies. In the case of polymorphic Alus, many sequences that do not show 100% conservation of AML site still retain the SP1 site. Interestingly, the core recombinogenic site is also most predominant in younger and polymorphic Alus. The presence of recombinogenic sites in polymorphic Alus, could therefore not only contribute to genome shuffling but also serve to distribute ectopic sites such as AML through retrotransposition and recombination (Figure 2).
Regulatory region distribution through Alu expansion
Analysis of regulatory sites within Alus suggests that a polymorphic Alu has the potential to transpose and recombine which allows it to integrate at random sites in the genome. They also harbour potential regulatory sites, which could evolve to become accessory sites for RNA pol II transcription as revealed by their clustering in older subfamilies. Further, the Alu sequence due to acquisition of novel functions could form a part of the transcription repertoire involved in the regulation of the downstream /associated genes and create novel regulatory networks (Figure 3). These results also corroborate with the hypothesis of evolution of transposable elements of Kidwell [51] wherein they had proposed a 3 stage life cycle of class II Transposable elements:- invasion and amplification followed by mutations and maturity and finally senescence and fading. In the case of Alu, instead of fading, they could also evolve to become members of host regulatory machinery.
Figure 3 Alu expansion and evolution of regulatory sites. With the help of LINEs, Alu may keep on retro-transposing or may get inactive/negatively selected. Alternatively, it may integrate upstream of a gene, accumulate mutations, evolve RNA pol II regulatory sites, get stabilized and control gene expression. This is supported by the presence of sparse regulatory sites, unhindered A box, recombinogenic sites initially in the younger and active Alus and its accumulation in older Alu subfamilies as well as significant presence of Alus harbouring regulatory sites in the promoter encompassing regions of the genes of signaling and metabolic pathways.
Conclusions
Comparison of sequences in the regulatory regions of many homologous genes in human have shown accumulation of Alus, not only post divergence from non-human primates but also during primate evolution [52]. Perhaps, recruitment of cis regulatory elements responsive to cellular cues through Alu elements could result in altered spatial and temporal transcription of genes as well as create novel metabolic and signaling networks. These might contribute to the observable physiological complexity in human and primates [53]. Additionally, the underlying events which would be defining event of speciation of human from chimpanzee (with which it shares nearly 99% homology at coding level) still eludes identification and might to some extent reside in such genomic elements. These issues can now be addressed through comparison of these sites in human and chimpanzee.
Currently, Alus are repeat-masked in all studies pertaining to identification of predisposition markers in complex disorders. With such wide spectrum of nuclear receptors, which play a major role in maintaining normal physiological state and affect as diverse processes as development, reproduction, general metabolism, residing in Alus, it therefore becomes imperative to screen for variations in these sites. This might have important consequences in the candidate genes for those complex diseases that are triggered in response to hormonal imbalances as well as other environmental cues.
Methods
126 polymorphic Alu sequences cited in literature [39,40] were retrieved using NCBI BLAST and Repeat Masker software[54,55]. The analysis was carried out on Alu repeats of human chromosome 22. A randomly selected representative set of approximately 500 Alu sequences, each of distinct evolutionary ages, Alu Jb, Alu Jo, Alu Sx, Alu Sc, Alu Yb8 and Alu Y were used for the analysis. Sequences were retrieved from Sanger Institute Home Page, June 2001 release [56]. Besides, Alus were also analyzed within 5000 base pairs upstream of genes of chromosome 22 in the regulatory regions encompassing promoter sequences as well as inside their intronic regions.
Collection of biologically active sites
Information about the regulatory sites and their sequences was collected from various literature sources (Table 2). Characteristic features of the sites are given below. We selected those regulatory sites, which have been shown to have function in the Alu elements. The A Box and B Box sequences define the bipartite internal promoters, which bind RNA polymerase III. MPO and AML sites, which are 14 nucleotides differ by an A / G at 5th position of the sequence and transition from G to A at this site converts the MPO allele to AML, resulting in the formation of a strong SP-1 binding site and over expression of the following gene. AP1 sites bind AP-1 transcription factor, which is a dimeric complex that contains members of the JUN, FOS, ATF and MAF protein families. Hormone responsive elements (HRE) are super family of binding sites for ligand activated nuclear hormone receptors for thyroid hormone (TRE), retinoic acid (RARE) and vitamin D, which regulate gene transcription. Estrogen response elements (EREs) are sites for binding of estrogen receptor (ER), a ligand-activated enhancer protein that is a member of the steroid/nuclear receptor super family and transactivates gene expression in response to estradiol. The negative calcium response element type 2 (nCARE) is a regulatory DNA sequence, which inhibits transcription in response to raised extra cellular calcium levels. The nuclear receptors liver X (LXR) is involved in different cell-signaling pathways. CETP site is an orphan receptor site in the Alu in promoter of cholesteryl ester transfer protein (CETP) which plays a key role in reverse cholesterol transport in mediating the transfer of cholesteryl ester from HDL to atherogenic apolipoprotein B-containing lipoproteins.
Table 2 Sequences of regulatory elements analysed in Alu repeats.
Site Sequence
Retinoic acid response element (RARE) 5'(AG)G(GT)TCA 3'
Estrogen Response Element (ERE) 5'(GA)(GA)TCA(CG)(AC)(CG)TGACC 3'
Negative calcium response element (nCARE) 5' TGAGACNNNGTCTCAAAAA 3'
Liver X receptor 5' GACCTNNNNTGATCC 3'
Cholestryl esterase transferase response element (CETP) 5'CCGNGGCGGGC 3'
AP1 site 5' T(GTA)A(GC)TCA 3'
Acute Myelocytic Leukemia (AML) site 5' AGGCGGGTGGATCA 3'
Myelo Peroxidase (MPO) site 5' AGGCAGGTGGATCA 3'
Recombinogenic site 5'CCCTGTAATCCTAGCACTTTGGAGGC 3'
A-Box 5' GGGCGCGGTGGC 3'
B-Box 5' G(A/T)T(C/T)RANNC 3'
B'Box 5' G TT(C/T)GAGAC 3'
Nucleotide sequences in parenthesis indicate alternate nucleotides and have been written in increasing order of their preference.
Computational methods
Two different programs were written in order to locate the most probable biologically significant regions. A local alignment based program, Xalign, was implemented in C++, Red Hat 7.3 based Linux. This program finds the probable sites by aligning the consensus of regulatory site with the query sequence. Multiple queries with a size upto 600 nucleotides can be taken at a time. Another program, Promotif, was implemented in C++, Red Hat 7.3 based Linux, using the probabilistic modeling approach. It uses the position weight matrix, normalization of the positions with conservation index (Ci Value), and inter-nucleotide dependence in terms of transition matrix to find out the sites. Position weight matrices were generated using Gibbs Motif Sampler, for every site included in the program. The sequences for position weight matrix generation were carefully selected based on the sequence and length reported for each binding site. The final length for search was fixed at the lowest length observed. This provides element specific matrix with lesser chance for the selection on non-RE regions. For the sites analyzed, it had an in built transition matrix, position weight matrix and conservation index. Batch analysis of over a thousand Alu sequences can be performed with this program.
Using the annotated sequences from literature as well as from NCBI web page, training set for the probabilistic model was created. Training was done for approximately 70% sequences and rest of the sequences were taken as test set. Details of the program along with the equations used are available on request.
Mapping of recently integrated and younger Alus
About 126 recently integrated Alus from younger subfamilies were searched in the human genome using BLASTn at NCBI server and regulatory sites were mapped in these regions using the programs discussed above.
Association analysis
Alus in the promoter regions and intronic regions of functionally classified genes [50] of chromosome 22 were mapped and pattern of distribution of biologically significant sites were analyzed by ANOVA.
Authors' contributions
RS developed the algorithms and programs for identifying regulatory and significant regions, carried out the analysis of distribution of these sites in Alu subfamilies, association analysis and drafted the manuscript. DG was involved in chromosome 22 analyses. SKB participated in the design of the study. MM conceived of the study, participated in its design, analysis, coordination and manuscript preparation. All authors read and approved the final manuscript.
Supplementary Material
Supplementary data
The analysis over the promoter and intronic regions has been performed through the data given in the supplementary table file, supplementary table 3_ravishankar et al. Format: .xls. For human chromosome 22, the data contains the accession number, associated Alu family, the respective positions, functional class of the region and further details, for each associated regulatory element found within the Alu repeats in the 5' flanking promoter and intronic regions. The zipped file name is supplementary 1.zip. Details about programs used are on request for academic users.
Click here for file
Acknowledgements
We thank Krishna Kumar and S Suganya for computational support. Financial support from Council of Scientific and Industrial Research (CSIR) projects (CMM0016) to MM and (CMM0017) to SKB is duly acknowledged.
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| 15476560 | PMC524484 | CC BY | 2021-01-04 16:29:01 | no | BMC Evol Biol. 2004 Oct 12; 4:39 | latin-1 | BMC Evol Biol | 2,004 | 10.1186/1471-2148-4-39 | oa_comm |
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BMC GenomicsBMC Genomics1471-2164BioMed Central London 1471-2164-5-761546960710.1186/1471-2164-5-76Methodology ArticleEvaluation of sense-strand mRNA amplification by comparative quantitative PCR Goff Loyal A 1lgoff@eden.rutgers.eduBowers Jessica 2jessica_bowers@datascope.comSchwalm Jaime 2jaime_schwalm@datascope.comHowerton Kevin 2kevin_howerton@datascope.comGetts Robert C 2bob_getts@datascope.comHart Ronald P 1rhart@rci.rutgers.edu1 W.M. Keck Center for Collaborative Neuroscience, Rutgers University, Piscataway, NJ 08854 USA2 Genisphere, Inc., Hatfield, PA 19440 USA2004 6 10 2004 5 76 76 15 7 2004 6 10 2004 Copyright © 2004 Goff et al; licensee BioMed Central Ltd.2004Goff 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
RNA amplification is required for incorporating laser-capture microdissection techniques into microarray assays. However, standard oligonucleotide microarrays contain sense-strand probes, so traditional T7 amplification schemes producing anti-sense RNA are not appropriate for hybridization when combined with conventional reverse transcription labeling methods. We wished to assess the accuracy of a new sense-strand RNA amplification method by comparing ratios between two samples using quantitative real-time PCR (qPCR), mimicking a two-color microarray assay.
Results
We performed our validation using qPCR. Three samples of rat brain RNA and three samples of rat liver RNA were amplified using several kits (Ambion messageAmp, NuGen Ovation, and several versions of Genisphere SenseAmp). Results were assessed by comparing the liver/brain ratio for 192 mRNAs before and after amplification. In general, all kits produced strong correlations with unamplified RNAs. The SenseAmp kit produced the highest correlation, and was also able to amplify a partially degraded sample accurately.
Conclusion
We have validated an optimized sense-strand RNA amplification method for use in comparative studies such as two-color microarrays.
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Background
One of the principal complications in microarray analysis of gene expression is the relatively large amount of input RNA required for each assay. On average, 1–20 μg of total RNA are required per study using glass microarrays [1-4]. This is easily obtained from standard tissue samples, but is more difficult to obtain from smaller samples, such as laser capture microdissections [5,6]. The primary impediment to the use of laser capture microscopy (LCM) in gene expression analysis is that microdissections yield insufficient mRNA due to low total RNA recovered from small sample sizes. With samples such as these, the ability to conduct a linear amplification of the target mRNA becomes imperative, to ensure that enough material is available for gene expression analysis. There are several methods for amplifying RNA including the arithmetic transcription methods [7,8], PCR based exponential amplification, or a combination of both arithmetic and exponential amplification [9]. Each method has proven effective in generating large amounts of amplified RNA from small starting samples. Each method is not without its drawbacks however. PCR based amplification has been shown to amplify sequence-dependent biases geometrically, and hybridization kinetics during the thermal cycles can create sequence-dependent and abundance-dependant biases [10]. New methods must be carefully validated with large numbers of mRNAs before they may be accepted for general use.
Most RNA amplification methods are based on the T7-based antisense RNA amplification technique first described by Van Gelder and Eberwine in 1990 [7]. In this technique poly(A)+ mRNA is reverse-transcribed and converted into double stranded cDNA using an oligo(dT) primer containing a promoter for T7 RNA polymerase. The second strand cDNA serves as a transcription template for amplified antisense RNA (aRNA) production. cDNA microarray studies using T7 amplified RNA have shown that the technique yields reproducible results that correlate with the results obtained from using total RNA [2,9,11]. This method is incompatible, however, with standard spotted oligonucleotide microarrays when combined with conventional reverse transcription based labeling methods.
Spotted oligo microarrays consist of 'long' 50–80 mer sense-strand oligonucleotide probes arrayed onto a suitable substrate. Each probe sequence is designed to hybridize to a specific antisense cDNA reverse transcribed from a given mRNA species. The advantage of spotted oligo microarrays over cDNA microarrays is that the oligos can be designed to be more specific, with similar hybridization kinetics, lower homology among related transcript probes, and selection among different splice variants of the same gene. However, aRNA prepared from Eberwine-amplified mRNA would produce a sense-strand cDNA target that would not hybridize with sense-strand oligo probes on the microarray.
The Genisphere SenseAmp linear mRNA amplification method produces sense-strand amplified mRNA by incorporating a double stranded T7 promoter into the 3' end of the first strand cDNA, driving transcription of an amplified RNA with the same strandedness as mRNA. SenseAmp linear amplification also allows for the use of dT and random primers in the synthesis of cDNA. This variation on the amplification protocol may be as effective on partially degraded mRNA or, using random primers in a first-strand reaction, on RNAs lacking a poly(A) tail. Further, the use of random primers combined with dT priming may help to reduce the 3' bias associated with Eberwine-based amplification methods [12,13] by improving the access of reverse transcription to the 5' end of mRNA.
Most studies evaluating amplification validity compare unamplified to amplified material [3,14-17]. However, this is not a good model of experiments normally performed with spotted oligo microarrays. In most two-color microarray experiments, an experimental sample is compared with a reference sample on the same microarray, so it is the ratio between two samples that becomes the most important parameter. RNA amplification may have some sequence bias, but as long as the bias is consistent between reactions, the effect of the bias may be canceled. We chose, therefore, to evaluate amplification strategies by comparing two RNA samples both before and after amplification, and correlating the ratios obtained before and after amplification. This key difference allows us to identify the best amplification method for use with two-color microarrays.
Throughout the course of this study, several pre-production versions of SenseAmp were evaluated with the aim of judging the optimal method. Total RNA from replicate rat brain and liver samples was amplified using one of several different techniques including three versions of the SenseAmp method, MessageAmp from Ambion, Nugen's Ovation RNA-based single primer isothermal amplification (Ribo-SPIA) method, and as an additional study, SenseAmp amplification of partially degraded RNA samples. The ratio of amplified RNAs obtained from each method was compared via relative qPCR to that of unamplified mRNAs from the same pool to determine how accurately the relative abundances were preserved. The use of qPCR provides a much broader range of results than possible with microarrays [18]. Relative qPCR analysis also allowed for the quantification of amplified RNA regardless of which strand was amplified, thus a direct comparison could be made between the various amplification techniques.
The fidelity of the amplification methods was determined using the ΔΔCt relative quantification method for qPCR. This method is used to compare the expression of a given gene in one sample relative to a second, and is based on the amplification efficiency of the PCR primer pairs used [19]. Quantitative PCR was selected because of its universal use as a microarray validation method [10,11,18-21], enhanced dynamic range [18-20], and ease of use with limited sample sizes for evaluating expression changes for several hundred genes. The basis of this method is the assumption that the exponential amplification of the starting product, and therefore the amount of PCR products produced with each round of amplification, is dependent upon the efficiency of each PCR primer pair. This efficiency is determined either experimentally or is calculated from the raw fluorescence data obtained during the qPCR amplification [22]. Equation (1) was used to compare the expression of 192 different genes in rat liver and rat brain samples. Triplicate total RNA samples from rat brain and liver were analyzed for each pair of primers targeting the mRNA concentrations of a given gene.
Ratio of gene expression = E-ΔΔCt (1)
Through comparison of the relative gene expression across the various different amplification techniques, we were able to determine that each amplification method produces amplified RNA in quantities that accurately reflect the original mRNA proportions. The SenseAmp kit exhibited the best correlation to the unamplified control, and was effective in amplifying degraded RNA samples as well. In addition, we inadvertently identified a potential bias that can arise with the use of the oligo dT in reverse transcription priming.
Results
We compared liver/brain expression ratios for a broad collection (n = 192) of mRNAs before and after amplification. Rat brain and liver RNAs were chosen since we needed to begin with large quantities of unamplified materials in order to test several amplification reactions on the same starting material, and to reliably assay the unamplified RNA. Several variations on the amplification method were tested to determine which method best replicated the distribution of liver/brain ratios found in unamplified RNAs. As anticipated, each of the amplification techniques produced amplified RNA that reproduced the full range of relative quantities (RQ) between liver and brain RNAs (Figure 1) and correlated well with the initial mRNA pool (Table 1, Figure 2). The SenseAmp version 1–2, which was designed to incorporate aspects of both version 1 and version 2, was shown to be most similar to the unamplified control results with a correlation coefficient of 0.90. As indicated by the lack of overlap in the 95% confidence intervals, SenseAmp version 1–2 produced amplified RNA with greater fidelity than either the MessageAmp or Ovation methods. Furthermore, each successive version of the SenseAmp protocol appeared to enhance the fidelity of the result. A series of two rounds of amplification with SenseAmp version 1–2 was indistinguishable in correlation to the unamplified control from a single round. These results suggest that each amplification technique is capable of producing linearly-amplified RNA that represents the relationships of the two original tissues. The SenseAmp kit (version 1–2) produced the most accurate reproduction of the original liver/brain ratios while also providing a sense-strand amplified RNA appropriate for use with oligonucleotide microarrays.
Figure 1 Distributions of liver/brain RQ ratios for all amplification methods. Box and whiskers plot showing the distribution of log2 RQ ratios for each amplification method. The blue diamond is centered on the mean and shows the 95% CI of the mean. The blue lines depict the percentile range. The center of the notched box is the median, with the notches showing the 95% CI of the median. The boxes show the inter-quartile range (IQR). Dashed lines are 1.5 times the IQR. Outliers are shown as red crosses (1.5–3.0 times the IQR) or red circles (>3.0 times the IQR).
Table 1 Correlations between liver/brain RQ ratios of amplified vs. unamplified RNAs. For each correlation, n is the number of PCR results retained after filtering the amplification efficiency [22]. The correlation coefficient (r) is shown along with its 95% confidence interval (CI). Each correlation was significant at p < 0.0001. A cross-correlation matrix showing all relationships between samples is available at
n* r‡ 95% CI p
MessageAmp™ 121 0.80 0.74 To 0.85 <0.0001
Ovation™ 112 0.82 0.76 To 0.86 <0.0001
SenseAmp™ Version 1 118 0.87 0.83 To 0.90 <0.0001
SenseAmp™ Version 2 121 0.88 0.85 To 0.91 <0.0001
SenseAmp™ Version 1–2 121 0.90 0.87 To 0.93 <0.0001
2 Rounds Version 1–2 121 0.89 0.85 To 0.92 <0.0001
SenseAmp™ on degraded RNA 121 0.94 0.92 To 0.96 <0.0001
* number of valid samples shared with unamplified control
‡Pearson correlation coefficient
Figure 2 Scatterplots comparing liver/brain log2 RQ ratios of amplified RNAs with unamplified RNA. For each amplification method, a scatter plot shows the correlation of the liver/brain ratio to that of unamplified RNA. A linear regression fit is plotted as a line with the equation shown. The coefficient of determination (R2) corresponds to the square of the correlation coefficient (r) in Table 1.
Amplification of partially-degraded RNA samples using the SenseAmp version 1–2 method also produced a high correlation of liver/brain ratios to those from unamplified RNAs (r = 0.94). This high correlation using degraded RNA appeared to be due to the presence of random primer in the amplification reaction. Comparing the rank order of mRNA abundances in liver (Table 2), we found that reactions using oligo dT primers generally produced higher correlations between amplified RNAs indicating that a similar offset to the rank order was occurring for all dT based methods. However comparing the dT primer rank order to that of random primed samples demonstrates greater dissimilarity, although this effect was variable. We interpret these results as supporting the hypothesis that the addition of a random primer to the amplification assay inadvertently enhances the correlation to random-primed, unamplified RNA, partially offsetting the negative effect of RNA degradation.
Table 2 Rank correlations of liver Ct values identifies effects of oligo d(T) primers vs. random hexamer primers.
Unamplified MessageAmp NuGen Version 1 Version 2 Version 1–2 2 Rounds V 1–2
MessageAmp 0.75 1
NuGen 0.65 0.83 1
Version 1 0.61 0.68 0.61 1
Version 2 0.84 0.92 0.78 0.71 1
Version 1–2 0.84 0.90 0.84 0.67 0.95 1
2 Rounds V1–2 0.79 0.89 0.81 0.67 0.93 0.92 1
Degraded V1–2 0.85 0.85 0.77 0.71 0.89 0.91 0.85
Rank cross-correlation matrix for liver Ct values. The mean cycle threshold (Ct) values obtained with liver RNA samples were rank-ordered and correlated. Results indicate the faithful reproduction of an ordered list of mRNA concentrations in liver RNA before and after amplification. Results were filtered for acceptable PCR efficiencies (see Methods), producing 138 primer pairs for this analysis. Methods using random primer (including unamplified RNA) are bold, those using oligo d(T) are italicized. Scatter plots of each rank Ct correlation are available at:
Discussion
Most studies of the fidelity of amplified RNA have compared the amplified sample to the original total RNA sample exclusively [2-4,10,14]. While this is valid, the approach described here more accurately reproduces the standard experimental conditions for two-color microarray expression analysis by comparing the ratio of gene expression between two different samples. The ratios obtained for amplified brain RNA vs. amplified liver RNA are then compared to the ratios from the unamplified control comparison (Table 1, Figure 2). Any reproducible biases within the techniques are represented in both the brain and liver samples and therefore cancelled out in the comparison. This approach models a two-color gene expression comparison experiment and demonstrates the differences in expression profiles obtained from different amplification techniques.
Using this approach, all three amplification kits tested had correlation coefficients of 0.80 or greater, indicating a great deal of fidelity in amplifying paired samples of RNA. The SenseAmp kit performed relatively better among the three, with a correlation coefficient of 0.90, with the 95% confidence interval lying above the means and intervals produced with MessageAmp or Ovation methods. Other researchers have shown that additional rounds of amplification yield reproducible results for a single RNA sample with only modest biases [6,10]. The fidelity of amplification was maintained in the course of our experiments with the SenseAmp production kit, through a second round of amplification. The similar correlations between the SenseAmp version 1–2 and the two rounds of version 1–2 amplification indicate that a second round of amplification does not significantly affect the relative abundance of mRNA. Of the three SenseAmp versions tested, version 1–2 had the highest correlation to unamplified RNA using this approach. In order to confirm that qPCR was an appropriate choice for validating RNA amplification procedures, we compared the brain vs. liver expression ratios on oligonucleotide arrays of SenseAmp version 1–2 amplified to unamplified RNA (not shown). As we observed with qPCR, a high correlation of about 0.93 was observed after comparing about 2700 differentially expressed genes, indicating that our qPCR experimental design was appropriate.
Variations in correlation among the versions of the SenseAmp method may be due to modifications to the structure of the T7 promoter/cDNA template. The version 1 template consisted of a completely double stranded linear DNA molecule, with one strand of the promoter synthesized enzymatically. For version 2, the T7 promoter was composed of two prehybridized, synthetic DNA strands ligated to a single stranded cDNA template. For version 1–2, a double stranded T7 promoter was synthesized onto the end of a single stranded cDNA template from a T7 template oligo by a 3' recessed end "fill-in" reaction using the Klenow fragment of DNA polymerase I. Like version 1, the promoter contains one enzymatically-synthesized strand and like version 2 the cDNA portion is single stranded. The incorporation of an enzymatically-synthesized strand appears be a more effective initiation site for the T7 polymerase (unpublished results). Furthermore, single stranded DNA templates downstream of the ds T7 promoter have been shown to be very efficient T7 polymerase templates [23,24] demonstrating a 2 fold improvement in kinetics [24]. The combined increase in T7 amplification efficiency in version 1–2 may preserve the distribution of mRNA concentrations in the amplified product.
Previous studies have cautioned against comparing samples using different reverse transcription primers [2]. Priming with oligo dT reduced PCR yields and created 3' and sequence-specific biases compared with the use of random primer [13,14,25]. These biases arise from the specificity shown by oligo dT primer for the 3' poly(A) tail and low processivity of T7 polymerase, as well as the presence of internal poly(A) sequences which may act as additional priming sites for the oligo dT. Random primer has also been shown to create a better 3'/5' ratio than the oligo dT primer [14].
Our experimental design called for the use of oligo dT primer in most of the RNA amplification reactions but random primer in the cDNA synthesis phase of qPCR. This design was used for each of the comparison experiments and therefore any bias introduced by the oligo dT primed reaction would be repeated for each of the amplification techniques. The effect of the oligo dT priming in the RNA amplification was identified when the degraded RNA sample was amplified using a mixture of oligo dT primer and random primer. The result showed that the degraded sample amplification resulted in a higher correlation to the unamplified control than any of the amplification techniques including the SenseAmp amplification of intact RNA. It is our interpretation that this high correlation of the amplified, degraded samples to the unamplified qPCR samples may be due to the common use of random primers for both data sets.
Conclusions
Overcoming the problem of tissue heterogeneity with LCM and other, similar techniques will allow the research community to focus its efforts on the biologically relevant cell types. The use of RNA amplification with these small, cell-type specific techniques provides reliable and reproducible quantities of mRNA suitable for high-throughput gene expression profiling. Amplification from small amounts of LCM-selected samples provides stronger hybridization signal and reduced biological noise attributed to the presence of other cell types.
RNA amplification has been shown here, and elsewhere, to be both a useful and consistent technique for production of practical amounts of RNA when limited starting material is available. While there are several reliable amplification methods available, most amplify an antisense RNA which is suitable for cDNA microarray analysis. The most apparent benefit of the SenseAmp method is the amplification of the sense mRNA strand. This allows for the direct use of cDNA reverse-transcribed from amplified RNA as a hybridization target for oligo microarrays, and any other analysis that requires a sense-strand orientation. In addition, we observed similar liver/brain ratios between amplified RNAs and unamplified RNAs. This comparison models the relative expression ratios observed with two-color microarrays. While each of the methods tested produced acceptable results, the SenseAmp methods provided optimal correlation between unamplified samples and sense-strand amplified RNA.
Methods
Primer design
A subset of 192 sequence targets was chosen from the Compugen/Sigma-Genosys Rat 8 K oligo library for qPCR analysis. Using previously-analyzed microarray results as a guide (not shown), we selected targets with a broad range of expression ratios from brain-specific, through common, to liver-specific mRNAs. GAPDH mRNA was also selected for normalization. Primers were designed for all 193 sequences using Applied Biosystems Primer Express software v2.0 (Applied Biosystems, Foster City, CA). Primers were designed to have a Tm between 58°C and 60°C and with an optimal length of 20 nt. The %GC content was held between 20% and 80% with no 3' GC clamp. The target amplicon for each sequence was designed to be between 50 and 150 nt with an optimal Tm of 85°C. The target mRNAs represented a broad range of sizes (as measured by cDNA lengths; range 110–8074; mean 1876 nt; 190 nt 95% CI) and base composition (range 38–68% GC; mean 52% GC; 0.85% 95% CI). Amplicons were distributed between 5'UTR (8.7%), coding sequence (82.0%), and 3'UTR (9.2%). Primers were purchased from Sigma-Genosys (The Woodlands, TX). The final working concentration for each of the primer pairs was 50 nM. A table of target sequences and primers is available in the supplemental materials .
Preparation of total RNA
Samples of rat brain (n = 3) and rat liver (n = 3) were frozen in liquid nitrogen and ground to a coarse powder. RNA was isolated from each sample using TRIzol (Invitrogen, Carlsbad CA). After isolation, samples of the prepared RNA were further purified using a Qiagen RNeasy column (Qiagen, Valencia CA). Total RNA was quantified by UV spectrophotometry and the integrity was assessed using a Bioanalyzer model 2100 (Agilent, Palo Alto CA). Identical total RNA samples were divided among the 8 different experiments (including unamplified control).
Degraded RNA was prepared by treatment at 65°C for 15 minutes in fragmentation buffer (40 mM Tris acetate, pH 8.1, 100 mM potassium acetate, 30 mM magnesium acetate). Samples of RNA degraded under these conditions were analyzed on an Agilent Bioanalyzer using RNA Nano chips and 2100 Expert software. Degraded samples typically had little or no 28S rRNA peak remaining and a broad smear below a weaker 18S rRNA peak, corresponding to an RNA Integrity Number (RIN) of 4.9 (using baseline correction) out of a score of 10 for RNA of ideal quality.
RNA amplification
Each of the three replicates for each tissue was amplified using the Ambion messageAmp (Ambion, Austin TX), NuGen Ovation AminoAllyl amplification (NuGen Technologies, San Carlos CA), or SenseAmp version 1, version2, or version 1–2 kits. SenseAmp, version 1–2, is the commercial version of the Genisphere SenseAmp kit. Amplification with each method was done according to the protocol outlined for each method. For each of the MessageAmp and SenseAmp amplifications, 0.75 μg of input total RNA was used. For SenseAmp with random priming, 250 ng of input total RNA was used. The final yield of amplified RNA for each method was ~36 μg. For the NuGen Ovation amplification, 70 ng of input total RNA was used to yield ~10 μg of amplified cDNA.
For all versions of SenseAmp, total RNA was reverse transcribed using 100 ng of an anchored dT primer [d(T)24V] as described in the SenseAmp manual . For the degraded RNA samples, random 9 mers were added to the reverse transcription reaction at twice the mass of the input total RNA (e.g. 500 ng random primers per 250 ng of total RNA). Superscript II (Invitrogen) was used for all reverse transcriptions. The cDNA was purified using a MinElute PCR Purification Kit (Qiagen).
SenseAmp version 1
The purified cDNA was 3' tailed with dATP. A T7-promoter/oligo d(T) primer was used to initiate second strand cDNA synthesis using E. coli DNA polymerase I (Invitrogen) at 16°C for 2 hours as described by the manufacturer. Double-stranded cDNA was purified using the MinElute PCR Purification Kit and used for in vitro transcription using the MegaScript kit (Ambion). Amplified sense RNA was purified using the RNeasy Kit (Qiagen) and the manufacturer's recommendation for RNA clean up.
SenseAmp version 2
The purified cDNA was poly d(T) tailed as described in the SenseAmp (Genisphere) product manual. Excess double-stranded T7-promoter was ligated to the 3' poly d(T) tail on the cDNA in 1X ligation buffer (Roche) at room temperature for 30 minutes. The double stranded (ds)T7 promoter consisted of equal molar amounts of a T7 promoter oligo hybridized to a complementary oligo have a 10 base d(A)10 overhang on the 3' end prehybridized in 6X ligation buffer (Roche Applied Science, Indianapolis IN). Excess unligated ds T7 promoter was removed using the MinElute PCR Purification Kit. The purified cDNA, which contained a double-stranded T7 promoter linked to a single stranded cDNA template [23,24], was used for in vitro transcription using the MegaScript kit (Ambion). Amplified sense RNA was purified using the RNeasy Kit (Qiagen).
SenseAmp version 1–2
The complete process is described in the Gensiphere SenseAmp product manual. Briefly, the purified cDNA was poly d(T) tailed. A T7-promoter/oligo dA template strand with a 3' blocking group was hybridized to the poly d(T) tail of the purified cDNA. Double-stranded T7-promoter was synthesized at room temperature for 30 minutes using Klenow fragment of DNA Polymerase I (Invitrogen). The 3' blocker was used to prevent the synthesis of complete second strand cDNA during the T7 promoter "fill-in" reaction. Excess T7 promoter template was removed using the MinElute PCR Purification Kit. The purified cDNA, which contained a double-stranded T7 promoter linked to a single stranded cDNA template, was used for in vitro transcription using the MegaScript kit (Ambion). Amplified sense RNA was purified using the RNeasy Kit (Qiagen) and the manufacturer's recommendation for RNA clean up.
cDNA synthesis
Five μg of each amplified RNA sample and unamplified control (with the exception of the NuGen Ovation amplification which yielded cDNA directly) was reverse transcribed into cDNA. RNA was added to 1 μl of 50 ng/μl random hexamer primer, 1 μl 10 mM dNTP mix (Sigma, St. Louis MO), and RNase-free water to make 12 μl. The mixture was denatured at 65°C for 5 min and immediately chilled. Reaction buffer and SuperScript II (Invitrogen) was then added and the volume was adjusted to 20 μl. The mixture was then incubated at 25°C for 10 minutes, 42°C for 50 minutes, and finally 70°C for 15 minutes to stop the reaction.
Quantitative real-time PCR (qPCR)
Each treatment assay was conducted across a total of four 384-well plates per assay. Each plate targeted 48 different genes for PCR amplification, each with 3 brain and 3 liver samples as well as 6 GAPDH wells for normalization across plates. A calibrator plate was used for each treatment to determine the concentration of cDNA required from each amplification technique to produce a GAPDH Ct comparable to that derived from the 1:10 dilution in the unamplified control. cDNAs for the NuGen, 2 rounds of SenseAmp version 1–2, and SenseAmp version 1–2 on degraded RNA were all diluted 100X. cDNAs from SenseAmp version 1 were diluted 120X. The remaining version 2, version 1–2, and messageAmp cDNA samples were diluted 200X. 2 μl of diluted cDNA was added to the primer pair mix and SYBR Green Master Mix (Applied Biosystems) in each well. qPCR was conducted on the Prism 7900HT Sequence Detection System (Applied Biosystems). Plates were run for 40 cycles and fluorescence intensity measured after every cycle. For each target sequence the average cycle number at which fluorescence was detected above background in the exponential phase of amplification was obtained for the brain and liver samples. This value, Ct, or cycle number at threshold, was used for calculations of relative abundance of mRNA molecules in the liver samples compared to the brain samples for each of the amplification methods.
PCR primer efficiency
The efficiency of each of the 192 target gene PCR primer pairs was calculated using the LinRegPCR software [22]. Normalized fluorescence values for each well were recorded for each cycle of RT-PCR. LinRegPCR used the log of these data to calculate the linear regression of a "window of linearity" in the exponential phase of amplification. The efficiency of the primer pairs corresponds to 10slope of the linear regression of the normalized log fluorescence values within the "window of linearity" for each well. As per the recommendations for this calculation, PCR primer pairs with strongly deviating PCR efficiencies or correlation coefficients below 0.999 were discarded [22] Average efficiency values for each primer pair were determined and used in equation (1) to reveal the relative abundance of mRNA in each sample.
Data analysis
The following algorithm was applied to the results from each amplification method as well as the unamplified control. As per the ΔΔCt qPCR analysis method, an average cycle number was determined at which fluorescence crossed a threshold above background. The resulting Ct value was recorded for each tissue type and target gene. This Ct value was normalized across plates by subtraction of the Ct value from the housekeeping gene GAPDH. This value represents the ΔCt. The ΔCt from the reference brain samples was subtracted from the ΔCt obtained from the liver samples. This gave the change in ΔCt between the two tissues or ΔΔCt. With the addition of calculated primer pair efficiencies, the ratio of gene expression for each target mRNA sequence between the two tissues was determined using equation (1). Ratios of expression values for liver tissues relative to brain (RQ) for each amplification technique were plotted in Excel (Microsoft, Redmond WA) and Pearson correlations to the unamplified control were determined using Analyze-It (Analyse-It Software, ), an Excel Statistics Add-on.
Authors' contributions
LAG performed all qPCR assays, selected and designed primer pairs, developed databases holding all data, and prepared the first draft of the manuscript. JB, JS, KH and RCG participated in the design of the study, developed the SenseAmp reactions, and modified the reactions in response to qPCR validation results. RCG supervised SenseAmp development. RPH conceived the study, supervised the qPCR assays, and coordinated work. All authors read and approved the final manuscript.
Acknowledgements
RPH is supported by grants from the New Jersey Commission on Spinal Cord Research. Donna Wilson provided technical assistance. Dr. Sophie Parmentier-Batteur performed the NuGen Ovation amplification reactions.
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