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On the other hand, the window size must be large enough to provide significant word counts, a requirement that strengthens with the size of the words under consideration and the intrinsic variability of the genomic signature along the genome. All together, the trade-off that has been implemented in this paper allows detecting atypical regions as small as 1 kb. In fact, rRNA regions sharing this characteristic were consistently detected. It must be pointed out that smaller fragments can be eventually detected if their signatures are radically atypical. G+C% atypicality has often been considered as criterion for detecting HTs (8, 24) , but this approach suffered several drawbacks (28) (29) (30) . It is to be noted that our signature-based method detects regions for which the G+C% lies within one standard deviation from the mean G+C% of the species (for instance, regions 2675251-2676250 in B.subtilis or 534751-535250 in H.Influenzae, see also Supplementary Materials 2 and 4). |
As already observed by Nicolas et al. (12) for B.subtilis, rRNA has definitely an atypical signature. It is systematically classified as outlier, whatever the species (Table 1) . Although transfer of rRNA from one species to another is unlikely (11, 57) , it cannot be firmly ruled out. However, it is clear that the atypical signature of rRNA does not imply that they are horizontally transferred. |
The signature approach has an interesting property (that it shares with HMM) (7, 12, 28) : detection is not bound to any specific function in the genome. In contrast with most other methods, the signature approach not only detects genes, but whole transferred regions as well, in agreement with the described mechanisms of DNA exchange between species. It is to be noticed that the method allows detecting several atypical non-coding regions (Supplementary Materials 3, 5 and 7). One major difference between HMM and signature method lies beyond the time required for the learning process, in the few resources that HMM can mobilize to deal with a short 'one of its kind' HT. On the other hand, HTs shorter than 1 kb can hardly be detected by a signature-based approach. An innovative HT detector is likely to result from an adequate fusion of both methods. |
Several factors contribute to the efficiency of the search for donors. Of course, distance between putative HT and donor signatures is essential. Accuracy of signatures, linked to the length of available sequences, density of signatures in the 'vicinity' of HT, amount of amelioration sustained by HT during its presence in the host are also of importance [P. Deschavanne, S. Lespinats and B. Fertil, unpublished results; (25, 27, 31) ]. Distance between the signature of a putative HT and the closest species varies to a large extent, but usually the shortest ones fall within the intra-genomic range ( Table 1 , Supplementary Materials 1, 2, 4 and 6) . In some cases, the distance between the closest donor signature and the atypical segment signature is so great that no potential donor can be proposed (Supplementary Materials 1, 2, 4 and 6) . |
When strong similarities between a given DNA sequence and a foreign species are observed, the hypothesis for an underlying transfer is highly strengthen. However, the 'true' donor has to be previously sequenced and included in our bank of signatures to allow such a situation to occur. Moreover, we must take into account the intrinsic variability of short DNA segment signature (which is a function of their size, but also species-specific) when compared with the signature of a complete genome or any other large species sample (25, 27, 31) . In the present state, our signature database is in no way representative of the diversity and richness of life. However, it must be noticed that there is already an obvious structure (in terms of distances between signatures) expressing taxonomy relationships between species in our signature database (31, (58) (59) (60) (61) . Related species are often found close to one another. Clusters of potential donors may consequently provide pertinent information about the origin of HTs. |
The diversity of signatures of putative HTs that can be observed for most of the species analyzed in this paper reveals the multiplicity of transfer events and donors (Supplementary Materials 2, 4 and 6). However, several outliers, not necessarily neighbors in the genome, are given the same set of potential donors (Table 1 , Supplementary Materials 1, 2, 4 and 6). In general, the potential donors belong to few sets of taxonomically close species (Table 1 ) and share the biotope of the host (Supplementary Materials 1, 2, 4 and 6). For instance, B.subtilis, H.Influenzae and E.coli live in distinct biotopes; their potential donors do so as well. It is particularly encouraging to find that most of the potential donors that our approach has pointed out have had the opportunity to exchange DNA material with the recipient species. |
Numerous viruses and plasmids qualify as potential donors (Tables 1 and 5 , Supplementary Materials 1, 2, 4 and 6 ). It is not really surprising since they are known as HT vectors. They are often totally or partially inserted together with transferred genes in the host genome (14) . |
Some atypical DNA segments are particularly peculiar. They are isolated, have a specific signature (distances from neighbors are great), so that they cannot be given a credible set of donors (Supplementary Materials 1, 2, 4 and 6) . Lack of data in the search domain, shift of signature features after a substantial amelioration process, structural constraints serving special functions or roles (14,62) (as it is for rRNA coding regions) are some of the tracks that remain to explore in these circumstances. |
It would be interesting to localize the region the transfer may come from when the complete genome of the donor is available. However, homology (at the DNA level) is not a pertinent criterion for the comparison of sequences as soon as amelioration has taken place (8, 14) . In fact, homology is sometimes weak, e.g. between genes of Escherichia and Salmonella although these species have 'recently' diverged (34) . It is clear that a more powerful search for the origin of putative HTs would have to embody models of amelioration [such as the one designed by Lawrence and Ochman (8) ]. |
When searching for very recent horizontally transferred genes, in different strains of a species for instance, it was possible to find a great homology between detected genes and some genes from other species (Table 5 ). In numerous cases, the selection of donors is consistent with FASTA results ( Table 5 ). This confirms the pertinence, beyond the similarity of signature between putative HTs and donors, of the proposed method to retrieve the species of origin of a transferred region. It seems that the search for origin of HTs on the basis of genomic signature is a powerful approach to understand some of the mechanisms of evolution (13, 63) . |
Oligonucleotide usage is known to be species-specific and to suffer only minor variations along the genome (25, 27) . Considered together, these properties allow searching for atypical local signatures that may point out DNA transfers. Results obtained with the 22 genomes analyzed in this paper are found in good agreement with literature (Tables 2-4 , Supplementary Materials 3, 5 and 7) (12, (14) (15) (16) 24, 34, 35) . |
The species specificity of signature allows searching for donor species. Quite often, sets of donor species with common taxonomic features are obtained. With the help of environmental considerations, it is subsequently possible to identify (or collect clues about) potential donors. The search for donor makes use of non-homologous sequences. Partially sequenced species become consequently eligible, inasmuch 1.5 kb of the genome is available (25, 27) . Thanks to the exponentially growing rate of nucleotide databanks, the search for donor species by means of the sequence signature will turn more and more pertinent and fruitful in the future. In this context, it is worth noticing that computational power is clearly not an issue since the CGR algorithm described in this paper is fast and of 0 order (calculation time is proportional to the number of nucleotides). |
Several methods are proposed to look for HTs. The signature method, based on different hypotheses, is complementary to those already described. It seems that each method detects preferentially certain types of HTs (49, 50) . In agreement with many authors (1, 16, 49, 50, 64) , it appears that the conjunction of several methods is required to obtain an overview of HT extent in a genome. |
The signature method described in this paper generalized many approaches that ground the detection of outliers on the basis of the bias in oligonucleodides. The strong species specificity of the signature not only allows detecting various kinds of outliers but also provides clues about their possible origin. Obviously, the detection of HTs remains an open question; a consensus has still to emerge. |
Additional materials and experimentation with the genomic signature are available from the GENSTYLE site (http:// genstyle.imed.jussieu.fr). Comparisons of substitution, insertion and deletion probes for resequencing and mutational analysis using oligonucleotide microarrays Although oligonucleotide probes complementary to single nucleotide substitutions are commonly used in microarray-based screens for genetic variation, little is known about the hybridization properties of probes complementary to small insertions and deletions. It is necessary to define the hybridization properties of these latter probes in order to improve the specificity and sensitivity of oligonucleotide microarray-based mutational analysis of disease-related genes. Here, we compare and contrast the hybridization properties of oligonucleotide microarrays consisting of 25mer probes complementary to all possible single nucleotide substitutions and insertions, and one and two base deletions in the 9168 bp coding region of the ATM (ataxia telangiectasia mutated) gene. Over 68 different dye-labeled single-stranded nucleic acid targets representing all ATM coding exons were applied to these microarrays. We assess hybridization specificity by comparing the relative hybridization signals from probes perfectly matched to ATM sequences to those containing mismatches. Probes complementary to two base substitutions displayed the highest average specificity followed by those complementary to single base substitutions, single base deletions and single base insertions. In all the cases, hybridization specificity was strongly influenced by sequence context and possible intra- and intermolecular probe and/or target structure. Furthermore, single nucleotide substitution probes displayed the most consistent hybridization specificity data followed by single base deletions, two base deletions and single nucleotide insertions. Overall, these studies provide valuable empirical data that can be used to more accurately model the hybridization properties of insertion and deletion probes and improve the design and interpretation of oligonucleotide microarray-based resequencing and mutational analysis. Oligonucleotide microarrays are a powerful technological platform for large-scale screens of common genetic variation and disease-causing mutations (1) (2) (3) (4) (5) . In most published studies (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) (16) (17) (18) (19) (20) (21) , oligonucleotide microarrays are designed to screen specific sequence tracts, up to megabases in length (11, 15, 22, 23) , for all possible single nucleotide substitutions. With some exceptions (24) (25) (26) (27) (28) (29) (30) (31) , the same emphasis was not placed on identifying all possible small insertions and deletions in the heterozygous state. Nevertheless, it is crucial to detect such small insertions and deletions since they can play a major role in inactivating or altering gene function by disrupting functional elements (e.g. splice junctions, cis-acting elements and open reading frames) and also represent another class of common genetic variation. |
Two fundamental approaches are commonly used to analyze data sets from oligonucleotide microarrays tailored to identify genetic variation in specific DNA segments purely by hybridization (1, (3) (4) (5) 9) . One approach involves identifying statistically significant gains of target hybridization signal to oligonucleotide probes complementary to specific sequence variants (9) . In theory, the gain of signal approach has the advantage of both detecting the presence of genetic variation and identifying the nature of the sequence change in the target. However, it is not feasible to screen for virtually all possible insertions and deletions due to the overwhelming The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oupjournals.org number of mutation-specific probes needed for this analysis. Furthermore, little effort has been made to systematically access the hybridization properties of probes complementary to these small insertions and deletions. The second approach involves identifying losses of hybridization signal to perfect match (PM) probes that are fully complementary to the DNA segment of interest (8, 25, 27, 30, 31) . In theory, the loss of signal approach allows one to screen for all possible sequence changes, including insertions and deletions, that cause a given target nucleic acid sequence to contain mismatches with specific PM probes. However, this necessitates the sequencing of specific DNA regions to identify the nature of the sequence changes (8, 25, 27, 30, 31) . Thus, a combination of the gain and loss of hybridization signal analysis could provide the most robust means of identifying and characterizing mutations using non-enzymatic oligonucleotide microarray assays. |
Here, we analyze the specificity and reproducibility of nucleic acid hybridization to oligonucleotide microarrays used in the large-scale mutational analysis of the ATM (ataxia telangiectasia mutated) gene that is responsible for autosomal recessive disorder involving cerebellar degeneration, immunodeficiency, radiation sensitivity and cancer predisposition and is also commonly mutated in certain lymphoid malignancies (32, 33) . These microarrays include 25mer oligonucleotide probes complementary to all possible single base substitutions and insertions as well as one and two base deletions on both strands of the ATM coding region. This provides the first comparative analysis of the hybridization properties of substitution, insertion and deletion probes in an oligonucleotide microarray-based mutational analysis of a large gene. |
A series of 120 DNA samples derived from biopsies of lymphoma patients were previously screened for all possible ATM mutations using oligonucleotide microarrays (30) . Here, we have selected a total of 68 samples that showed robust amplification signals in all 62 coding exons for further analysis (30) . A total of 17 unique mutations, each in a one-to-one mixture with wild-type sequence, occurred once in these samples. The impact of any given mutation in a single sample is minimal given that 67 other samples with wild-type sequences in the region encompassing a given mutation are included in this analysis. Several single nucleotide polymorphisms (SNPs) were present multiple times: 735 C/T, 2572 T/C and 4258 C/T in two samples; 3161 C/G in four samples; and 5557 G/A in five samples. Likewise, these SNPs have a minimal effect on our global analyses given the large number of samples and bases interrogated in this study. |
As previously described (30) , individual ATM coding exons were amplified from genomic DNA using primers containing T3 and T7 RNA polymerase tails, pooled, and then in vitro transcribed using T3 or T7 RNA polymerase to create biotinlabeled sense and antisense strand targets, respectively. Fluorescein-labeled reference target was made using genomic DNA from an unaffected individual. Reference and test sample targets were fragmented, diluted in hybridization buffer [3 M TMA-Cl (tetramethylammonium chloride), 1· TE, pH 7.4, 0.001% Triton X-100] and hybridized to the ATM microarrays as described previously (30) . Afterwards, the microarray was stained with a phycoerythrinstreptavidin conjugate and digitized hybridization images from both reference and test targets were acquired using the Gene Array Scanner (Hewlett Packard, Palo Alto, CA) equipped with the appropriate emission filters. |
Custom software was used to quantify hybridization signals for each probe and subtract background hybridization signals. We exclusively focused on raw data from the biotin-labeled test targets since they provide approximately seven times the hybridization signal of the fluorescein-labeled wild-type reference target in this system (28) . This enhanced signal provides greater sensitivity toward detecting weak hybridization. |
For each sample, for each base and for each potential type of mutation (i.e. substitution, one or two base deletion or one base insertion), the specificity was calculated as the ratio of the PM probe hybridization signal of the wild-type target to their cognate insertion, deletion or single base substitution probes on each strand. The logarithm of these ratios was plotted as a function of the position within the gene. To illustrate the special patterns and to smooth out random variation, running averages of data from 10 bases were used. To capture the variability, at each base, the sample-to-sample standard deviation was again calculated using data derived from a running average of 10 bases for each sample. |
To estimate the mean hybridization specificity for each type of mutation, the geometric mean (i.e. the antilog of the average of the logged ratios) over all bases and over all specimens was calculated (Table 1) . To further examine the variability of the specificity ratios, the coefficient of variation (cv) was calculated in two ways. The cv is the ratio of the standard deviation divided by the mean; it is useful for understanding the amount of variability relative to the magnitude of the mean or typical value. For the intra-sample cv, the cv was calculated for each of the 68 samples (using the running average of 10 at each ATM base) and the average of the 68 coefficient of variations was taken. For the inter-sample cv, at each of the bases, the cv a Hybridization specificity ratio is defined as the ratio of PM probe hybridization signal to that of the brightest mismatch probe within a given category. The global average of all hybridization specificity ratios for each base in all samples for a given probe type is provided. b Determined for hybridization specificity ratios averaged across windows of 10 bases either within (intra) or across (inter) samples. |
was calculated using the 68 samples, and the average of the coefficient of variations was taken. For both calculations, the moving average of 10 was used, instead of the original value, since the goal was to understand how the specificity varied over bases and across samples, rather than to estimate the experimental (or measurement) error. |
In order to determine the relative specificity of the hybridization of complex nucleic acid targets to oligonucleotide probes complementary to single base substitutions, insertions and deletions, we analyzed data generated from oligonucleotide microarray-based mutational analysis of the 9168 bp ATM coding region (30) . These studies used a pair of oligonucleotide microarrays (Affymetrix, Santa Clara, CA) containing over 250 000 probes (25 nt in length) specifically designed to screen the sense and antisense strands of the ATM coding region for genetic variation (27, 30) . Collectively, the ATM sense and antisense microarrays contain 55 008 probes complementary to all possible single base substitutions, 73 344 probes complementary to all possible one base insertions, and 18 336 probes complementary to all possible one base deletions and 18 336 probes complementary to all possible two base deletions in the ATM coding sequence (Figures 1 and 2 ). These microarrays have been used to screen for sequence variation in the ATM gene in over 100 DNA samples (30) . SNPs and gene inactivating mutations were uncovered by screening for localized losses of hybridization signal to PM probes complementary to every 25 nt segment of the ATM coding region (8, 25, 27, 30) . However, hybridization data from deletion and insertion probes were not relied upon in this analysis. Therefore, this data set provides a unique opportunity to examine the relative hybridization specificity of nucleic acid targets to each of these classes of mismatch probes. |
In order to gain a global overview of hybridization specificity, we determined the average ratio of PM probe hybridization signal of wild-type target (see Materials and Methods) to their cognate insertion, deletion and single base substitution probes on each strand (Table 1 ). In these calculations, we considered data for all 9168 interrogated bases in all 68 DNA samples (see Materials and Methods). For example, we report the ratio of the PM probe signal to the signal from its cognate 1 or 2 bp deletion probe. However, for single base substitutions, we report the ratio of the PM probe signal to that of the cognate substitution probe with the highest hybridization signal. This provides the most rigorous assessment of cross-hybridization to single base substitution probes. Likewise, for single base insertion probes, we report the ratio of the PM probe signal to that of the cognate insertion probe with the highest hybridization signal. |
For both sense and antisense strands, we found that the two base deletion probes had the highest average PM to cognate MM hybridization specificity ratio (3.26-fold sense and (Table 1) . |
To provide a finer-scale analysis of hybridization specificity, we determined the relative frequencies of hybridization specificity ratios in defined bins. There was a similar distribution of specificity ratios for single base substitution and two base deletion probes on both strands ( Figure 3 ). The overall lower hybridization specificities of single base deletion and insertion probes are reflected by the increased frequencies of probes within the lower specificity bins (i.e. <2-fold ratio) and decreased frequencies of probes within higher specificity bins (i.e. >3-fold ratio) on both strands. |
Next, we sought to uncover underlying trends in the hybridization specificity of different classes of mismatch probes across the entire ATM coding region within a given sample (intra-sample variation). This provides insights into sequence context effects that may influence the hybridization specificity of each class of mismatch probe. To approach this problem, we plotted the average hybridization specificity ratios of substitution, deletion and insertion probes for all 1168 bases across the 68 samples (Figure 4 and Supplementary Figure 1) . We analyzed data determined over running averages of 10 bases in order to maximize our ability to detect trends and minimize the effect of randomly dispersed confounding factors (e.g. intra-or intermolecular secondary structure) that may skew data for any given base. |
As expected from Table 1 and Figure 3 , the two base deletion probes consistently showed a higher average hybridization specificity ratio followed by single base substitution, single base deletion and single base insertion probes on both strands of exon 50 ( Figure 4) . Nevertheless, the hybridization specificity ratios for all classes of mismatch probes fluctuate across the exon 50 sequence (Figure 4 ). For example, two base deletion probes showed a peak value of 6.76 (unlogged) centered at base 7071 and a trough value of 1.90 (unlogged) centered at base 7002 on the sense strand. We also found similar fluctuations in specificity ratios for all mismatch probe types in the remaining 61 ATM coding exons (Supplementary Figure 1 ). |
To assess intra-sample variability in hybridization specificity by a different means, we determined the average cv for substitution, deletion and insertion probes within a given experiment (Table 1) . Again, we analyzed data from running average of 10 bases in order to maximize our ability to detect trends and maintain consistency in our data analysis. Substitution probes had the lowest average intra-sample cv, 0.31 and 0.23 for sense and antisense strands, respectively. One base deletion, two base deletion and insertion probes showed comparable intra-sample coefficients of variation on the sense strand, 0.37, 0.39, and 0.38, respectively. However, insertion probes showed relatively higher variability than the deletion probes on the antisense strand. Coupled with plots shown in Supplementary Figure 1 , it is evident that of all the mismatch probe types, the hybridization specificities of base substitution probes were least affected by target sequence context. Intrigued by the above observations, we next searched for specific target sequence tracts that produced the lowest hybridization specificity among and between the different classes of mismatch probes. To approach this problem, we determined how many mismatch probes within running windows of 10 bases gave poor hybridization specificity, previously defined as a hybridization specificity ratio <1.2 (26). In Table 2 , we report nucleotide tracts where at least 8 probes within a given 10 base window showed poor hybridization specificity ratios. A comprehensive listing of probes with poor hybridization specificity is provided in Supplementary Table 1 . |
Repetitive sequence tracts, including homopolymer, homopurine and homopyrimidine, are highly represented in Table 2 . Upon closer inspection, it became apparent why the cross-hybridization is strong for probes in homopolymeric regions. In these sequence contexts, substitution and deletion probes can form duplexes with wild-type target that are longer than 12 bp in length. For example, the probe designed to detect a single base deletion at position 633 is designed to form one 12 bp and one 13 bp duplex with wild-type target. However, this probe can form duplexes that range from 12 to 18 bp in length with wild-type sense strand target due to slippage ( Figure 5 ). This type of ambiguity leads to increased stability of these DNA-RNA heteroduplexes (34) . |
In principle, the homopurine and homopyrimidine tracts uncovered have the capacity to form higher order structures, such as triple helices (35) . These tracts are known to alter the conformation and stabilities of RNA-DNA heteroduplexes (36, 37) , such as those formed between RNA targets and DNA probes in our system. Finally, we expect the ATM target to be especially rich in such sequence tracts given that both strands of the 3 0 -splice acceptor sequences, typically containing homopyrimidine tracts, for all 62 coding exons are included in the ATM target. This increases the likelihood that highly related sequence tracts in the ATM target can cross-hybridize to probes interrogating a particular homopurine or homopyrimidine sequence tract and reduce the overall hybridization specificity in this region. |
Next, we screened for potential structures that can form in the PM probes listed in Table 2 or their targets that could explain their poor hybridization specificity. To do this, we used Mfold (38) to calculate Gibbs free energies for intramolecular structures that can form in these PM probes and targets. Based on these Gibbs free energy values, we classified the probes and targets as having strong (S) [DG < (À3 kcal/mmol)], medium (M) [(À1 kcal/mmol) > DG > (À3 kcal/mmol)] and weak (W) [G > (À1 kcal/mmol)] potential for secondary structure. We found that several target and probe sequences could form substantial secondary structures, as displayed in Figure 6 . This could artificially lower the affinity of target to PM probes and thus lower the hybridization specificity. It is more difficult to model intermolecular structure in the solution-phase complex target and in the solidphase oligonucleotide probes. However, it appears likely that such structures could also have a similar negative impact on hybridization specificity. |
The relative variability in hybridization specificity ratios across samples (inter-sample variability) represents another important issue that should be considered in resequencing analysis (9) . To uncover general trends in inter-sample variability for each type of mismatch probe, we calculated an average cv for mismatch probe hybridization specificity ratios determined over running windows of 10 bases (Table 1) . Interestingly, on both strands, the single base substitution probes showed the lowest inter-sample cv. The one and two base deletion probes showed at least 2-fold higher coefficients of variation on both strands, relative to the substitution probes. Surprisingly, the one base insertion probes showed significantly higher coefficient of variations than any of the other classes of mismatch probes across samples. In fact, they are 3.5-fold higher than the corresponding substitution probes on each strand. |
The relative levels of inter-sample variation for all mismatch probes across exon 50 are displayed graphically in Figure 4 . The error bars represent one standard deviation from the mean of the hybridization specificity ratio determined over a running window of 10 bases in each of the 68 samples. Note that the substitution probes show lower inter-sample variability than one base deletion, two base deletion and . Hybridization specificities of mismatch probes. A 10-base running window of the log 10 hybridization specificity ratios of substitution (red), one base deletion (green), two base deletion (blue) and one base insertion (black) was plotted for the sense (A) and antisense (B) strands of ATM exon 50. The light red, light green, light blue and gray shaded areas represent -1 SD of the log 10 hybridization specificity ratios for the substitution, one base deletion, two base deletion and one base insertion probes, respectively. one base insertion probes, in agreement with Table 1 . The variability in hybridization specificity measurements is consistent across all 62 ATM coding exons (Supplementary Figure 1) . |
Overall, our analyses indicate that, on average, single base insertion probes show substantially lower reproducibility across experiments than base substitution, one base deletion and two base deletion probes. The increased inter-and intrasample variability in hybridization specificity of single base insertion and deletion probes relative to single base substitution and two base deletion probes should be considered when designing and interpreting microarray-based screens for genetic variation. For a given microarray design, substantially more control hybridization experiments may be needed to determine baseline fluctuations in the hybridization specificities of insertion and deletion probes relative to those of substitution probes. |
In contrast to single nucleotide mismatches, detailed thermodynamic analyses of double helical nucleic acids with bulged nucleotides have only recently been conducted (34, (39) (40) (41) . In such cases, the bulged nucleotide is unpaired on only one of the nucleic acid strands. These studies are relevant to understanding the properties of the deletion and insertion probes since they can form duplexes containing bulges with target nucleic acid. For deletion probes, the bulged nucleotide is located on the target strand ( Figure 7) . Conversely, the insertion probes contain the bulged nucleotide in duplexes with wild-type target (Figure 7) . |
Although subject to sequence context effects, duplexes containing a single base bulge are predicted to be more stable than those containing single nucleotide mismatches (34, (39) (40) (41) . This is reflected in the lower average hybridization specificity of single base deletion and insertion probes relative to that of substitution probes (Table 1 and Figure 4) . Conversely, duplexes containing two base bulges are predicted to be generally less stable than those containing a single base mismatch (40, 41) . In part, this is due to the assumption that helical stacking is interrupted by bulges of two or greater bases in length while it is preserved for one base bulges (40, 41) . The higher average hybridization specificity ratios of two base (38) was used to predict the intramolecular structures with the lowest Gibbs free energy (DG) for either the 25-30 base stretches that encompass each listed sequence tract in the target or for the PM probes complementary to each sequence tract. We use these DG values to predict the stability of these structures. DG > (À1 kcal/mmol) = weak (W); (À1 kcal/mmol) > DG > (À3 kcal/mmol) = medium (M); and DG < (À3 kcal/mmol) = strong (S). c Type of mismatch probe that provided poor hybridization specificity ratios. d Low hybridization specificity found on both sense and antisense strands. e Immediately following the 3 0 end of this segment is a (T) 5 sequence tract. |
deletion probes relative to substitution probes are in agreement with the predicted properties of these probes ( Table 1) . The considerably lower average inter-sample variability of substitution probes relative to deletion and insertion probes was unexpected given that the same target was hybridized to all mismatch probes simultaneously in the same experiment. The sources of inter-sample variation include sample preparation, hybridization conditions and the microarrays themselves. It is reasonable to assume that the microarrays themselves are not the major source of variability since the combinatorial manufacturing processes should lead to roughly equivalent synthesis quality for all the arrayed probes (42, 43) . It seems more likely that the insertion and deletion probes are more sensitive to subtle changes in target preparation (e.g. amount of fragmentation and dye incorporation) and hybridization conditions (e.g. target concentration, temperature and wash conditions) than the substitution probes. However, a definitive explanation for our observations will require further investigations (44) (45) (46) (47) (48) (49) (50) (51) (52) . |
In addition to their potential value, it is important to note some of the caveats when relying upon mismatch probes for mutation detection. For example, it is important to screen for all possible sequence changes, including multiple base insertions and deletions, in mutational analyses of disease-related loci, such as the ATM, BRCA1 and BRCA2 genes. Given that 4 N probes per base per strand are needed to screen for insertions of length N in a mixed sequence, it is unlikely that oligonucleotides complementary to insertions of two or more base pairs will be represented on microarrays screening large sequence tracts for mutations in the near future. Deletions represent a more tenable situation since only one probe per base per strand is needed to screen for a deletion of a given length in a mixed sequence. Nevertheless, there will still be limitations as to the number of deletion probes that can be realistically represented in a given microarray. |
Finally, it is often critical to precisely determine the nature of a sequence change within a given sample in order to properly assess its functional significance. Thus, it is important to consider error rates when assigning the identity of a mutation based on mismatch probe data. When dealing with clinical samples, it will be especially important to confirm the identity A Gene Encoding Sialic-Acid-Specific 9-O-Acetylesterase Found in Human Adult Testis Using differential display RT-PCR, we identified a gene of 2750 bp from human adult testis, named H-Lse, which encoded a putative protein of 523 amino acids and molecular weight of 58 kd with structural characteristics similar to that of mouse lysosome sialic-acid-specific 9-O-acetylesterase. Northern blot analysis showed a widespread distribution of H-Lse in various human tissues with high expression in the testis, prostate, and colon. In situ hybridization results showed that while H-Lse was not detected in embryonic testis, positive signals were found in spermatocytes but not spermatogonia in adult testis of human. The subcellular localization of H-Lse was visualized by green fluorescent protein (GFP) fused to the amino terminus of H-Lse, showing compartmentalization of H-Lse in large dense-core vesicles, presumably lysosomes, in the cytoplasm. The developmentally regulated and spermatogenic stage-specific expression of H-Lse suggests its possible involvement in the development of the testis and/or differentiation of germ cells. Sialic acids are a diverse family of acidic nine-carbon sugars that are frequently found as terminal units of oligosaccharide chains on different glycoconjugates in higher invertebrates and vertebrates [1, 2] . As a part of determinants in many glycoproteins [3, 4] , sialic acids play an important role in intercellular and/or intermolecular recognition [5] . The 9-O-acetylation and de-Oacetylation are the most common modifications of sialic acids found in mammalian cell surface sialoglycoconjugates, which can alter its size, hydrophobicity, net charge, and antigenicity [2, 6, 7] . These modifications can regulate a variety of biological phenomena, including endogenous lectin recognition, tumor antigenicity, virus binding, and complement activation [8, 9] . |
Enzymes specifically capable of removing O-acetyl esters from the 9-position of sialic acids are sialic-acidspecific 9-O-acetylesterase. The enzymes in mammals have two forms, one is cytosolic sialic-acid-specific 9-O-acetylesterase (Cse) in the cytosolic fraction and another is lysosome sialic-acid-specific 9-O-acetylesterase (Lse) in the lysosomal/endosomal compartment [10] . Lse is likely to participate in the terminal lysosomal degradation of 9-O-acetylated sialoglycoconjugates, while Cse is likely to salvage any 9-O-acetylated molecules that escape the initial action of the Lse enzyme. The process of de-O-acetylation of sialic acid, which is catalyzed by sialicacid-specific 9-O-acetylesterase, has been implicated in organogenesis and cellular differentiation [2, 5] . |
Spermatogenesis is a complicated process of germ cell differentiation in adult testis, which is established during testicular development. There are five types of germ cells, each at a specific developmental stage, found in the seminiferous tubules: spermatogonia, primary spermatocytes, secondary spermatocytes, spermatids and sperms. They can be divided into three groups according to their DNA content: 4N DNA content cells (4C cells), 2N DNA content cells (2C cells), and 1N DNA content cells (1C cells). The separation of these cells enables researchers to investigate the molecular mechanisms underlying testicular development and/or spermatogenesis. In the present study, we separated the 2C and 4C cells of seminiferous tubules in human adult testis by flow cytometry, and identified human H-Lse by differential display RT-PCR. The expression pattern of H-Lse was found to be developmentally regulated and stage-specific, indicating its possible role in testicular development and/or germ cell differentiation. |
Human testes were obtained from Donation Center of Nanjing Medical University with consent of relatives. The seminiferous tubules were collected in DMEM/F12, which contained collagenase, and washed to remove the Leydig cells as well as interstitial cells. Trypsin treatment and a brief treatment with DNase I were used to release the spermatogenic cells from seminiferous tubules. The suspension of cells was filtered with nylon mesh. |
Disaggregated spermatogenic cells were suspended at 1 × 10 6 cells/mL in 0.5 M sodium citrate solution (PH 2.35) with fresh 0.1% DEPC overnight at room temperature and at 4 • C for two days; they were centrifuged and resuspended in 0.5 M sodium citrate solution (PH 4.5) with fresh 0.1% DEPC for at least 1 day. The day before use, the cells were centrifuged and resuspended in PBS with 10 mM HEPES (PH 7.0), 0.1% BSA, and fresh 0.1% DEPC. Then the cells were spun down and resuspended in PBS with 100 µg/mL PI (propidium iodide) and fresh 0.1% DEPC. The cells were stained overnight at 4 • C [11] . |
The flow cytometry (FCM) used in this research was FACSVantage SE (Becton Dickinson, Calif) equipped with argon laser (power: 200 mW, wavelength: 488 nm); a 585 nm/42 nm filter set was used before the FL2 detector. Cellquest (Becton Dickinson) was used for sorting and the sorting mode was Normal-R. Drops per sort were 3 and drop delay was 13.6. The density of cells for sorting was about 1 × 10 6 cells/mL. |
Isolation of total RNA from 2C cells and 4C cells was performed with Trizol Reagent (Gibco BRL, Ontario). One hundred nanograms of total RNA was used for differential display RT-PCR [12] . The first chain cDNA was synthesized by using T12G, T12C, and T12A oligo (dT) primers, and then was used as template in PCR. PCR was performed as follows: 94 • C, 1 minute; 37 • C, 1 minute; 72 • C, 2 minutes for 40 cycles. Ten microlitres of the PCR products from the two cells were run on a 1.5% agarose gel. The fragments highly or specifically displayed in 4C cells were excised and purified. This DNA was reamplified with the same combination of primers and then subcloned into Pinpoint Xa1-T vector (Promega, USA). |
The colonies of full-length cDNA were screened by PCR. Human Testis Large-Insert cDNA Library (Clontech, Calif) was first converted into plasmid cDNA Library, and then an arrayed cDNA library in 96-well plates was made according to the method of Munroe [13, 14] . In this arrayed cDNA library 1.54 × 10 6 colonies were screened by PCR. |
Multiple tissue northern (MTN) blots (Clontech) were hybridized with the 32 P-labeled probes. The probe corresponding to 1378-1634 bp of H-Lse was used for hybridization. After stringent wash, the blot was placed on the storage phosphor screen (Packard, USA) and exposed for 3 hours in the dark. The signal was detected at the Cyclone storage phosphor system (Packard). |
The Stanford TNG Radiation Hybrid Panel (Research Genetics, Huntsville, Ala) was used to map the chromosomal localization of HSE with primers HSEmapF (5 -ATGAACACCGTCTCCACC-3 ) and HSEmapR (5 -AAATCTGAAGGACCCATC-3 ), according to the manufacturer's instructions. After 35 cycles of amplification, the reaction products were separated on a 1.5% agarose gel. The positive amplification was labeled as 1 and the negative one was labeled as 0. The results were analyzed through the Stanford genome center web server to determine the probable chromosomal location. |
RNA DIG-labeled probes were made by in vitro transcription. T7 and SP6 promoter sequences were incorporated into the two sides of the templates (195-553 bp of H-Lse) by PCR, sense and antisense probes were made using DIG-RNA labeling mix (Roche, USA) according to the manufacturer's instructions. After fixation, paraffin embedding, mounting, and sectioning, sections of human embryonic and adult testes were prehybridized in hybridization buffer (DIG Easy Hyb, Roche, Germany) at 42 • C for 2 hours. Hybridization was carried in hybridization buffer containing appropriate probes at 65 • C for 16 hours in humidity chamber. |
Subcellular localization of HSEI and HSEII was performed by the method of green fluorescent protein. pEGFP-C2-HSEI AND pEGFP-C2-HSEII were constructed using two sets of primers (HSEI: 5 -GGGGAATT CAATGATATGGTGCTGCAG-3 and 5 -GGGGTCGACAT TTAGCAACATTGCTCTG-3 ; HSEII: 5 -GGGGAATTCA TGGTCGCGCCGGGGCTTG-3 and 5 -GGGGTCGACA TTTAGCAACATTGCTCTG-3 ) and EcoRI/SalI restriction sites of pEGFP-C2. Recombinant vectors were transfected into BxPC-3 cells (BxPC-3 cell is a cell lineage of adenocarcinoma from pancreas) by Lipofectin reagent (Gibco BRL). Cells were imaged 40 hours after transfection on the fluorescence microscope. |
After being stained with PI and measured by the FCM, three groups of cells in seminiferous tubules of human adult testis were detected (Figure 1 ), 2C and 4C cells were subsequently sorted. A clone was identified by differential display RT-PCR, which was highly expressed in the 4C cells ( Figure 2 ) and with high homology (86%) to a mouse lysosome sialic acid 9-O-acetylesterase. The clone was named H-Lse. |
In the two rounds of screening in the arrayed cDNA library, the plasmid containing full-length H-Lse (GenBank accession number: AF303378) was found. H-Lse is 2750 bp in length, encoding a putative protein of 523 amino acids with a molecular weight of 58 kd. Its isoelectric point is 7.19. The N terminus (1-18 aa) of the protein is a region containing hydrophobic amino acid residues, which may be a signal peptide. By comparison of the protein sequences (Figure 3 ), we hypothesized that H-Lse is the human counterpart of mouse lysosome sialic acid 9-O-acetylesterase. |
After PCR amplification, the results can be shown as a pattern (00000000100010100000011000001000000011 000001000001000001001000000010000000000100100100 0001). Retrieving results from the Stanford genome center web server shows that HSE is localized in the human 11q24 ( Figure 4) . |
The distribution of H-Lse in various human tissues was analyzed by Northern blot ( Figure 5 ) and the results showed the presence of three distinct mRNA species at approximately 2.7 kb, 6.0 kb, and 7.5 kb. The expected transcript of H-Lse was approximately 2.7 kb and it was consistently expressed in all the tissues examined with high expression found in the testis, prostate, and colon. The transcript of approximately 7.5 kb was exclusively expressed in the colon. The transcript of approximately 6.0 kb was distributed in the testis, colon, small intestine, prostate, and thymus, with the highest level of expression found in the testis. |
To examine a possible role of H-Lse in testicular development and/or spermatogenesis, in situ hybridization experiments were conducted to compare H-Lse expression in human embryonic and adult testes since spermatogenesis is not initiated in the embryo and there is no meiosis in embryonic seminiferous tubules. The results showed that no signal was detected in the embryonic testis, while positive signals were detected in spermatocytes but not spermatogonia in the seminiferous tubules of adult testis. Signals were associated with germ cells but not other somatic cells in the testis, that is, Sertoli and Leydig cells. Negative control of sense probes confirmed the specificity of the results ( Figure 6 ). |
The subcellular localization of H-Lse fusion proteins was visualized by transiently transfecting H-Lse gene fused with GFP into BXPC-3 cells. As shown in Figure 7 , the control cells transfected with GFP protein alone exhibited fluorescence evenly distributed throughout the cytoplasm, while GFP-H-Lse fusion protein was compartmentalized in numerous large dense-core vesicles in the cytoplasm. |
Spermatogenesis is a developmental program that occurs in mitotic, meiotic, and postmeiotic phases. In the mitotic phase, spermatogonia proliferate to expand the quantity of germ cells; in the meiotic phase, spermatocytes accomplish chromosomal synapsis and genetic recombination before two meiotic divisions; and in the postmeiotic phase, haploid spermatids are remodeled into spermatozoa by the processes of acrosome formation, nuclear condensation, flagellar development, and loss of the majority of cytoplasm. Under the control of intrinsic and extrinsic factors, spermatogenesis is characterized by the expression of a spectrum of genes that are celltype-specific or stage-specific. They are thought to play an essential role in spermatogenesis at particular stages. For example, MutS homologue 5 is required for chromosome pairing, CPEB and SCP3 are required for synaptonemal complex assembly and chromosome synapsis in primary spermatocytes [15, 16, 17] . |
In the present study, we have identified a gene, H-Lse, from human adult testis with high homology to m-Cse 1 [19] . Similarly, it can inhibit binding of sialoadhesin, a macrophage-restricted and sialic-acid-dependent adhesion molecule [20] . On the other hand, 9-O-acetylation of sialic acids can form novel epitopes. Influenza virus C haemagglutinin specifically requires 9-O-acetylated sialic acids for binding to host cells [21] . Incubation of red blood cells with sialate 9-Oacetylesterase rendered the erythrocytes resistant against agglutination by influenza C virus [22] . O-acetylation of disialoganglioside GD3 by human melanoma cells has been reported to create a unique antigenic determinant [23] . Modifications of sialic acids may be an important mechanism underlying the interaction/cross-talk between different types of cells. The essential role of sialic acids modification in cellular communications may explain the presently observed wide distribution of H-Lse in all examined tissues. The present study suggests that the expression of H-Lse is developmentally regulated and spermatogenic stage-specific. The evidence for this includes: (1) lack of expression in embryonic testis; (2) association of high level of mRNA detected by DD-RT-PCR with the 4C but not 2C cells in adult testes; and (3) detection of in situ hybridization signal in spermatocytes but not spermatogonia or other somatic cells. In the absence of spermatogenesis, embryonic testis contains only two distinct cell types, spermatogonia and Sertoli cells, while the seminiferous epithelium of adult testis consists of germ cells at different stages of spermatogensis. The 4C cells found in adult testis include the primary spermatocytes and spermatogonia of G 2 /M stage, while 2C cells include spermatogonia of G0/G1 stage, secondary spermatocytes, and Sertoli cells. The absence of H-Lse mRNA in embryonic testis and the high level of its mRNA in the 4C cells of adult testis suggest that its expression is restricted to spermatocytes, particularly the primary spermatocytes. Together with the in situ hybridization results showing mRNA of H-Lse restricted to spermatocytes, but not spermatogonia, Sertoli cells or interstitial cells, these data suggest that H-Lse is likely to be involved in the process of spermatogenesis, although its role in testicular development cannot be entirely ruled out. Unfortunately, due to the deformation of the available human testes, we were not able to make further distinction between primary and secondary spermatocytes. What has been clearly shown by the present data is that H-Lse is only present at a stage beyond spermatogonia, suggesting its possible role in the differentiation of germ cells. |
G N F T Y M S A V C W L F G R Y L Y D T L Q Y P I G L V S S S W G G T Y I E V W S S R R T L K A C G V P N T 143 m-Lse 181 A G N L G H G N F T Y M S A V C W L F G R Y L Y D T L Q Y P I G L V S S S W G G T Y I E V W S S R R T L K A C G V P N T 240 h-Lse 181 S E N L G H G Y F K Y M S A V C W L F G R H L Y D T L Q Y P I G L I A S S W G G T P I E A W S S G R S L K A C G V P K Q 240 m-Cse 144 R D E R V G Q P E I K P M R N E C N S E E S S C P F R V V P S V R V T G P T R H S V L W N A M I H P L Q N M T L K G V V 203 m-Lse 241 R D E R V G Q P E I K P M R N E C N S E E S S C P F R V V P S V R V T G P T R H S V L W N A M I H P L Q N M T L K G V V 300 h-Lse 241 G S _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ I P Y D S V T G P S K H S V L W N A M I H P L O N M T L K G V V 274 m-Cse 204 W Y Q G E S N A D Y N R D L Y T C M F P E L I E D W R Q T F H Y G S Q G Q T D R F F P F G F V Q L S S Y M L K N S S D Y 263 m-Lse 301 W Y Q G E S N A D Y N R D L Y T C M F P E L I E D W R Q T F H Y G S Q G Q T D R F F P F G F V Q L S S Y M L K N S S D Y 360 h-Lse 275 W Y Q G E S N I N Y N T D |
Interestingly, the processes of 9-O-acetylation and de-O-acetylation of sialic acid have been implicated in organogenesis and cellular differentiation, since alteration of these processes could lead to interruption of cellular development such as embryogenesis. Transgenic mice constitutively overexpressed the 9-O-acetyl-sialicacid-specific esterase of influenza C that has been found to arrest embryo development at the two-cells stage. It has also been reported that in vitro development of embryonic stem cells shows that the expression level of Lse is low at the initiation of the development, and followed by an increase at later stages [24] . In transgenic mice with selective expression of 9-O-acetyl-sialic-acid-specific esterase in retina and the adrenal gland, these organs showed various abnormalities in organization, while all other tissues appeared normal [25] . Lse has also been considered to play a key role in the differentiation of B lymphocyte [2] , since it is expressed in late but not early B lymphocyte. The presently observed developmentdependent pattern of H-Lse expression is consistent with that found in other cell types: absence or low expression at early stage of differentiation but high at later stages. Taken together, 9-O-acetyl esters in sialic acids appear to be important for development or cellular differentiation. |
Spermatogenesis is a multiple-staged continuous progress of cellular differentiation. It has been reported that some cell surface glycoconjugates are modified during the early steps of spermatogenesis, and influence the differentiation of spermatogenic cells [26] . As ninecarbon sugars commonly found in many glycoproteins of spermatogenic cells, sialic acids represent a target for cell surface modification, that is, removal of 9-O-acetyl esters by enzymes such as Lse. Modification of sialic acids may result in alteration in cell-cell communication, that is, Sertoli cells and germ cells interaction, thereby influencing the differentiation of spermatogenic cells. Thus, future studies on the presently identified H-Lse may provide insight into molecular mechanisms underlying testicular development and/or germ cell differentiation during spermatogenesis in humans. The role of mast cells in the pathogenesis of pain in chronic pancreatitis BACKGROUND: The biological basis of pain in chronic pancreatitis is poorly understood. Mast cells have been implicated in the pathogenesis of pain in other conditions. We hypothesized that mast cells play a role in the pain of chronic pancreatitis. We examined the association of pain with mast cells in autopsy specimens of patients with painful chronic pancreatitis. We explored our hypothesis further using an experimental model of trinitrobenzene sulfonic acid (TNBS) -induced chronic pancreatitis in both wild type (WT) and mast cell deficient mice (MCDM). METHODS: Archival tissues with histological diagnoses of chronic pancreatitis were identified and clinical records reviewed for presence or absence of reported pain in humans. Mast cells were counted. The presence of pain was assessed using von Frey Filaments (VFF) to measure abdominal withdrawal responses in both WT and MCDM mice with and without chronic pancreatitis. RESULTS: Humans with painful chronic pancreatitis demonstrated a 3.5-fold increase in pancreatic mast cells as compared with those with painless chronic pancreatitis. WT mice with chronic pancreatitis were significantly more sensitive as assessed by VFF pain testing of the abdomen when compared with MCDM. CONCLUSION: Humans with painful chronic pancreatitis have an increased number of pancreatic mast cells as compared with those with painless chronic pancreatitis. MCDM are less sensitive to mechanical stimulation of the abdomen after induction of chronic pancreatitis as compared with WT. Mast cells may play an important role in the pathogenesis of pain in chronic pancreatitis. Although pain is the presenting symptom of most patients with chronic pancreatitis, its neurobiological basis remains poorly understood [1] . In the past, investigators have focused on the role of anatomical abnormalities such as a strictured pancreatic duct or narrowed intraparenchymal ducts. However, mechanical decompression techniques such as endoscopic stent placement or even surgical pancreatojejunostomy frequently do not provide a permanent solution to the pain [1] . More recently, investigators have begun focusing on the role of neurotransmitters and neurotrophins such as substance P and nerve growth factor with known or suspected roles in nociceptive signaling and/or sensitization and have reported an increased expression of several of them in the pancreas of patients with painful chronic pancreatitis [2] . Mast cells are also increased in both acute and chronic pancreatitis [3, 4] but their role in the generation of pain in pancreatitis has not been investigated. |
We hypothesized that mast cells are involved in the pathogenesis of pain in chronic pancreatitis. This hypothesis is based on the following observations. First, mast cells have been associated with human conditions in which pain is a predominant symptom. Interstitial cystitis and irritable bowel syndrome are both conditions in which pain is out of proportion to the objective pathological findings [5, 6] . In both conditions, an increase in the number of mast cells has been described in the bladder and the colon, respectively [5, 6] . Further, mast cells are frequently found in close proximity to nerves in the intestinal mucosa and the bladder [7] [8] [9] . This has also been observed in the pancreas -the total number of mast cells was significantly higher in pancreatic tissue from patients with chronic pancreatitis than in the normal pancreatic controls [3] . One of the preferential locations of mast cells was around and within the perineurium of nerve fibers in tissue samples of patients with chronic pancreatitis, suggesting the potential for interactions between mast cells and the nervous system. Lastly, there is evidence for bi-directional functional communication between mast cells and nerves [10] [11] [12] . Mast cells can not only release mediators that increase excitability of neurons but in turn, neurotransmitters such as substance P can trigger mast cell degranulation [10] . Mast cells may therefore contribute to the pathogenesis of pain in pancreatitis through degranulation products that can sensitize pancreatic afferent neurons in an ongoing vicious circle of neuronally mediated mast cell degranulation. |
Our first aim was to analyze the presence and distribution of mast cells in autopsy specimens of chronic pancreatitis and study the correlation, if any, with historical documentation of pain. We then explored our hypothesis further using an experimental model of trinitrobenzene sulfonic acid (TNBS)-induced chronic pancreatitis in both wild type and Kit W /Kit W-v mice, a strain deficient in mast cells (MCDM). |
Autopsy records from the University of Texas Medical Branch from the years 1993 to 2000 were searched electronically for the term "pancreatitis." One-hundred sixtysix patients were identified of which 26 patients carried an autopsy diagnosis of chronic pancreatitis and 140 patients carried a diagnosis of acute pancreatitis. The medical charts from patients with an autopsy diagnosis of chronic pancreatitis were reviewed for documentation of a medical history of chronic pancreatitis. If no such documentation was present in the chart, patients were excluded from the study (12/26) . Thus, 14/26 patients with both a documented history and an autopsy based diagnosis of chronic pancreatitis, were included in the study. Patients were categorized as painful chronic pancreatitis (8/26) when they fulfilled one of the following criteria: a documented history of chronic abdominal pain clinically attributed to chronic pancreatitis that required the use of narcotics, and/or frequent admissions for recurrent abdominal pain clinically attributed to chronic pancreatitis, and/or a surgical or endoscopic procedure for refractory abdominal pain clinically attributed to chronic pancreatitis. Patients were categorized as non-painful chronic pancreatitis (6/ 26) if patients did not fit any of the criteria listed under painful chronic pancreatitis. In addition, the following data were collected: demographic factors (age and race), cause of death, comorbidities, clinical history of pancreatitis, etiology of pancreatitis, diagnostic studies supporting a diagnosis of pancreatitis (amylase, lipase, calcifications on abdominal plain film, CT-scan, ultrasound or ERCP). Human pancreatic control tissue was obtained from 8 arbitrarily chosen patients of whom the autopsy records recorded acute myocardial infarction as the cause of death. Their medical records were reviewed to ensure that they did not have a clinical history of pancreatitis. Therefore there were three categories of patients: one with painful chronic pancreatitis, one with non-painful chronic pancreatitis and non-pancreatitis controls. A pathologist, blinded to the group assignment, verified all histological diagnoses and counted mast cells on a Giemsa stained tissue section (average of 10 high-power randomly chosen (40X) fields per specimen). The protocol was approved by the Institutional Review Board of the University of Texas Medical Branch. |
All mice were purchased from the Jackson Laboratory (Bar Harbor, ME). Male mice were used from the following strain: WBB6F1/j-Kit W /Kit W-v (MCDM) and the respective littermate control mouse strain, Kit W-v -+/+ (WT). The mice were 3 months of age at the onset of the experiment with body weights of 25-30 gram. |
Experimental protocols involving mice were approved by our Institutional Animal Care and Use Committee (IACUC) in accordance with the guidelines provided by the National Institutes of Health. |
Mice were anesthetized with sodium Nembutal (50 mg/kg body weigh, i.p.) Following a midabdominal laparotomy, a canula was introduced into the common pancreato-biliary duct; the duct was ligated proximally and distally to ensure perfusion into the pancreas and prevent entry of the injected substance into the liver or duodenum. 0.1 ml of 1% TNBS in phosphate buffered saline (PBS)-10% ethanol, pH 8, was infused into the pancreas (modified after Puig-Divi [13] ). The canula was removed and the abdomen closed. Control mice were treated in the exact same fashion but were perfused with saline instead (Figure 1 ). Mice were sacrificed 8 weeks after surgery. |
VFF hairs consist of a series of filaments of increasing diameter that produce increasing sensations of touch when applied to the skin. When the tip of a fiber of given length and diameter is pressed against the skin, the force of application increases until the fiber bends. After the fiber bends, continued advance creates more bend, but not more force of application. This principle makes it possible to apply a reproducible force to the skin surface. VFF testing is an established behavioral pain assay used to determine mechanical pain thresholds in somatic pain. |
More recently, VFF testing has been used as a surrogate marker for visceral pain [14, 15] . |
Mice were placed in a cage with a mesh floor and habituated to the environment for 30-60 minutes. Measurements were taken from the abdomen and the plantar surface of both hindpaws over a period of three weeks prior to the surgery and for a total of three weeks after the surgery ( Figure 1 ). VFF filaments of various caliber were applied to the mid-abdomen in ascending order 10 times, each for 1-2 seconds with a 10 second interval. A response was defined as: a) sharp retraction of the abdomen; b) immediate licking or scratching of site of application of hair; or c) jumping. The response frequency was defined as the total number of responses out of 10 applications (expressed as a percentage) to the skin per filament. An investigator blinded to the different treatment groups performed the behavioral testing. |
Fresh specimens of the mouse pancreas were fixed in 10% formaldehyde in PBS pH 7.4 containing 1 mM MgCl 2 at 4°C overnight. Sections from paraffin-embedded specimens were stained with hematoxyline and eosin and observed under a light microscope. Pathological changes were scored based on a scale described by Tito et al. by a pathologist blinded to the different treatment groups [16] . |
Comparisons of the number of mast cells in autopsy specimen were analyzed using the Mann-Whitney U test. |
For each behavioral experiment (see figure 1), the average response frequency was calculated as the mean of the mean response frequencies for each mouse (across four measures). The "post-pre response frequency" was calculated by subtracting the pre-surgical average response frequency from the post-surgical average response frequency. To assess the independent effect of TNBS on VFF response (ie. to control for the effect of the surgery itself), the postpre response frequency for TNBS infusion was compared with the post-pre response frequency for saline infusion. This comparison was performed using analysis of variance for a two-factor experiment with repeated measures on time at each level of force for each type of mice (WT and MCDM). The two factors were induction of pancreatitis or not (TNBS or saline, respectively) and time (pre-surgical or post-surgical). TNBS infusion was considered to have had an independent effect on the VFF response if the postpre response frequency was greater for TNBS than for saline infusion. |
Fisher's least significant difference procedure was used for multiple comparisons of least squares means with Experimental design Figure 1 Experimental design All mice underwent pre and post surgical VFF testing. For the VFF testing, 4 measures were taken for each mouse. WT and MCDM were randomized to either saline or TNBS perfusion into the pancreatic duct. |
Patient demographics are summarized in Table 1 . Alcohol abuse was the most common cause for pancreatitis in both groups. Analysis of our results, using the Mann-Whitney U test, revealed significantly more mast cells in patients with a history of painful chronic pancreatitis (n = 8) when compared to patients with either non-painful chronic pancreatitis (n = 6) (33.8 vs 9.4 average mast cell count/10 high power fields; p < 0.01) or controls (n = 8), |
(33.8 vs 6.1 average mast cell count/10 high power fields; p < 0.01) ( Figure 2 ). The increased number of mast cells in patients with painful pancreatitis was noted predominantly in interstitial areas and, to a lesser degree, in the periacinar space. Figure 3 shows the post-pre surgical response frequency for both WT and MCDM. TNBS had a significant independent effect on abdominal VFF response in WT mice at the force levels 4 and 8 mN (p = 0.007 and 0.037, respectively) ( Figure 3A ). There was a trend towards a significant effect at the force level of 16 mN (p = 0.066). In contrast, for MCDM, TNBS had no significant effect on abdominal VFF response at any force level ( Figure 3B ). There was no significant TNBS effect on VFF response in the left A g e |
Pancreatic histology confirmed the presence of chronic pancreatitis in both WT and MCDM with marked fibrosis, inflammatory infiltrates and ductular proliferation mimicking changes seen in human chronic pancreatitis ( Figure 5A ). The pancreas of saline treated controls was normal. There was no significant difference in the overall inflammatory scores between the WT and MCDM ( Figure 5B ). An increased number of mast cells were counted in WT mice with chronic pancreatitis compared to saline Histology (Giemsa) of mice with chronic pancreatitis (Figure 6 ). As to be expected, no mast cells were present in pancreas of MCDM. |
Chronic pancreatitis has been defined as a continuing inflammatory disease of the pancreas characterized by irreversible morphologic changes that typically cause pain and/or permanent loss of function [17] . The pathogenesis of pain in this condition remains to be satisfactorily established. We examined the association, if any, of pain with mast cells as quantified in autopsy specimens of patients with a history of painful and non-painful chronic pancreatitis and normal controls. Significantly more mast cells were present in pancreatic tissue from patients with a history of painful chronic pancreatitis, indicating an association with this condition and a potential role for these cells in the pathogenesis of pain in painful chronic pancreatitis. |
There are clearly limitations to a retrospective, autopsybased study such as the one we report here. For instance, we do not know whether pain was present at the time of death and there was incomplete information on the different patterns of pain. Also, our findings pertain mainly to patients with a history of alcoholic pancreatitis. Nevertheless, our findings do suggest an association of painful chronic pancreatitis with an increased number of mast cells. This observation provided the rationale for further experimental testing, which we performed in mice. We first developed a model of chronic pancreatitis in mice following a modified protocol first described by Puig-Divi et al. [13] . Histological changes consisted of periductal and lobular fibrosis, duct stenosis, chronic inflammatory cell infiltrates, and gland atrophy, mimicking features of chronic pancreatitis in humans. Significantly more mast cells were present in WT mice with chronic pancreatitis, adding to the validity of this model for use in studies on the role of mast cells in pancreatitis. Both WT and MCDM developed histological changes consistent with chronic pancreatitis, indicating that the elimination of mast cells did not modulate the animals' ability to mount an inflammatory response. Therefore, any changes observed in pain behavior are unlikely to stem from differences in underlying inflammation. |
Next we determined whether this mouse model could be used to study behavioral differences associated with chronic pancreatitis. The assessment of spontaneous pain in a visceral organ presents significant difficulties. We have used a behavioral method to assess this, which relies on the association of visceral pain with sensitization of somatic regions of the body that share segmental innervation at the level of the spinal cord (referred pain). This somatic sensitization can be quantified using VFF to stim-ulate the somatotopically appropriate abdominal region and measuring the abdominal withdrawal response. Thus, VFF testing of the anterior abdominal wall can be used as a surrogate marker for visceral pain. Although this is the first time that this technique has been used for the measurement of referred visceral hyperalgesia in a mouse model of chronic pancreatitis, this method has previously been described and validated to assess the severity of referred visceral pain for models of colonic hypersensitivity [14] as well as rat models of acute necrotizing pancreatitis [15] and chronic pancreatitis [18] . The abdominal VFF response was compared to the hind paw response to assess the specificity of the interventions to the pancreas. TNBS treated mice, but not the saline control, developed increased abdominal wall withdrawal responses to VFF testing when compared to baseline, suggesting the development of force-dependent referred hyperalgesia of the abdominal wall in WT mice. There was no evidence of referred hyperalgesia in the hindpaws, suggesting that the measured effect on abdominal withdrawal is specific for an intra-abdominal origin of the pain. Vera-Portocarrero et al. previously described similar findings, increased withdrawal frequency after VFF stimulation to the abdominal area, in a rat model of chronic pancreatitis [18] . These behavioral changes were abrogated by morphine. Rats that demonstrated behavioral changes also expressed increased substance P expression in the nociceptive layers of the spinal cord, suggestive of central nociceptive changes. |
Mast cells produce a variety of degranulation products in the setting of inflammation that may activate and/or sensitize primary nociceptive neurons. The neurotrophin growth factor (NGF) is one such product [19] [20] [21] [22] . NGF is released in the setting of inflammation and can not only function as a chemoattractant for other mast cells, but it can also trigger mast cell degranulation [23] . We are speculating that NGF production in the inflamed pancreas is responsible for plastic changes in the sensory neurons by activating proalgesic receptors and channels such as the NGF receptor tyrosine kinase A (TrkA) and Transient Receptor Potential Family V receptor 1 (TRPV1; previously known as VR1) thereby contributing to the generation of pain [24] [25] [26] . Similarly, other mast cell degranulation products such as tryptase and histamine are capable of modulating neuronal function [27] [28] [29] [30] [31] [32] . Tryptase may directly activate the proteinase-activated receptor-2 (PAR-2), a G-protein coupled receptor expressed by pancreatic nerves, important in the pathogenesis of pain in pancreatitis [33, 34] . Although the role for mast cells in the mediation of visceral nociceptive signaling needs to be explored further, we speculate that mast cell products released in pancreatitis, contribute to the development of pain by direct effects on nociceptors located on pancreatic afferent neurons (Figure 7 ). |
However, before concluding a definite role for mast cells from our experimental data, it should be noted that MCDM carry a spontaneous mutation for tyrosine kinase receptor c-kit which not only produces a deficiency of mast cells but may have an independent effect on the function of sensory neurons, which are known to express it [35] . Therefore, it remains to be determined whether the detected differences in nociceptive responses is due to the absence of mast cells per se or a yet unknown change in the responsiveness of sensory neurons due to a congenital lack of the c-kit receptor. Reconstitution of mast cells into the MCDM mice should restore their nociceptive responses close to the wild type phenotype. |
Our data should increase awareness of the importance of mast cells in the pathogenesis of painful inflammatory |
Proposed involvement of mast cells in nociceptive signaling in pancreatitis Figure 7 Proposed involvement of mast cells in nociceptive signaling in pancreatitis In pancreatitis, mast cells may migrate to sites of inflammation, in response to release of mast cell chemoattractants. Mast cell degranulation products may modulate neurotransmission directly by activating proalgesic receptors and channels such as trka (NGF), TRPV1 (NGF) and PAR-2 (tryptase and trypsin). |
The pre-publication history for this paper can be accessed here: |
http://www.biomedcentral.com/1471-230X/5/8/prepub Recombination Every Day: Abundant Recombination in a Virus during a Single Multi-Cellular Host Infection Viral recombination can dramatically impact evolution and epidemiology. In viruses, the recombination rate depends on the frequency of genetic exchange between different viral genomes within an infected host cell and on the frequency at which such co-infections occur. While the recombination rate has been recently evaluated in experimentally co-infected cell cultures for several viruses, direct quantification at the most biologically significant level, that of a host infection, is still lacking. This study fills this gap using the cauliflower mosaic virus as a model. We distributed four neutral markers along the viral genome, and co-inoculated host plants with marker-containing and wild-type viruses. The frequency of recombinant genomes was evaluated 21 d post-inoculation. On average, over 50% of viral genomes recovered after a single host infection were recombinants, clearly indicating that recombination is very frequent in this virus. Estimates of the recombination rate show that all regions of the genome are equally affected by this process. Assuming that ten viral replication cycles occurred during our experiment—based on data on the timing of coat protein detection—the per base and replication cycle recombination rate was on the order of 2 × 10(−5) to 4 × 10(−5). This first determination of a virus recombination rate during a single multi-cellular host infection indicates that recombination is very frequent in the everyday life of this virus. As increasing numbers of full-length viral sequences become available, recombinant or mosaic viruses are being recognized more frequently [1, 2, 3] . Recombination events have been demonstrated to be associated with viruses expanding their host range [4, 5, 6, 7] or increasing their virulence [8, 9] , thus accompanying, or perhaps even being at the origin of, major changes during virus adaptation. It remains unclear, however, whether recombination events represent a highly frequent and significant phenomenon in the everyday life of these viruses. |
Viruses can exchange genetic material when at least two different viral genomes co-infect the same host cell. Progeny can then become hybrid through different mechanisms, such as reassortment of segments when the parental genomes are fragmented [10] , intra-molecular recombination when polymerases switch templates (in RNA viruses) [11] , or homologous or non-homologous recombination (in both RNA and DNA viruses). Quantification of viral recombination in multicellular organisms has been attempted under two distinct experimental approaches: in vitro (in cell cultures) [12, 13, 14, 15] , and in vivo (in live hosts) [16, 17, 18] . The in vitro approach, which has so far been applied only to animal viruses, allows the establishment of the ''intrinsic'' recombination rate in experimentally co-infected cells in cell cultures [14, 15, 19] . However, it does not necessarily reflect the situation in entire, living hosts, where the frequency of coinfected cells is poorly known and depends on many factors such as the size of the pathogen population, the relative frequency and distribution of the different variants, and host defense mechanisms preventing secondary infection of cells. The in vivo experimental approach is closer to biological conditions and may thus be more informative of what actually happens in ''the real world.'' However, as discussed below, numerous experimental constraints have so far precluded an actual quantification of the baseline rate of recombination. First, many experimental designs have used extreme positive selection, where only recombinant genomes were viable (e.g., [13, 20, 21] ). Other studies did not use complementation techniques but detected recombinants by PCR within infected hosts or tissues [18, 22, 23, 24, 25] , which provides information on their presence but not on their frequency in the viral population. So far, no quantitative PCR or other quantitative method has been applied to evaluate the number of recombinants appearing in an experimentally infected live host. Finally, recent methods based on sequence analysis inferred the population recombination rate, rather than the individual recombination rate [1, 26, 27] . While results from these methods certainly take in vivo recombination into account, there are other caveats: isolates have often been collected in different hosts-sometimes in different geographical regions-and sometimes the selective neutrality of sequence variation on which these estimates are based is not clearly established. Estimates from such studies by essence address the estimation of the recombination rate at a different evolutionary scale. |
Taken together, the currently available information indicates that no viral recombination rate has ever been estimated directly at time and space scales corresponding to a single multi-cellular host infection, although this level is most significant for the biology and evolution of viruses. This study intends to fill this gap by evaluating the recombination frequency of the cauliflower mosaic virus (CaMV) during a single passage in one of its host plants (the turnip Brassica rapa). |
CaMV is a pararetrovirus, which is a major grouping containing hepadnaviruses (e.g., hepatitis B virus), badnaviruses (e.g., banana streak virus), and caulimoviruses (e.g., CaMV). Pararetroviruses are characterized by a non-segmented double-stranded DNA genome. After entering the host cell nucleus, the viral DNA accumulates as a minichromosome [28] whose transcription is ensured by the host RNA polymerase II [29] . The CaMV genome consists in approximately 8,000 bp and encodes six viral gene products that have been detected in planta ( Figure 1 ) [30] . Viral proteins P1 to P6 are expressed from two major transcripts, namely a 19S RNA, encoding P6, and a 35S RNA corresponding to the entire genome and serving as mRNA for proteins P1-P5 [31] . Using the pre-genomic 35S RNA as a matrix, the protein P5 (product of gene V) reverse-transcribes the genome into genomic DNA that is concomitantly encapsidated [30] . |
The detection of CaMV recombinants in turnip hosts has been reported numerous times. Some studies have demonstrated the appearance of infectious recombinant viral genomes after inoculation (i) of a host plant with two infectious or non-infectious parental clones [21, 32, 33, 34, 35] or (ii) of a transgenic plant containing one CaMV transgene with a CaMV genome missing the corresponding genomic region [36] . While the former revealed inter-genomic viral recombination, the latter demonstrated that CaMV can also recombine with transgenes within the host's genome. Another study based on phylogenetic analyses of various CaMV strains has clearly suggested different origins for different genomic regions and, hence, multiple recombination events during the evolution of this virus [37] . Indirect experimental evidence has indicated that, in some cases, CaMV recombination could occur within the host nucleus, between different viral minichromosomes, presumably through the action of the DNA repair cellular machinery [21, 35] . Nevertheless, the mechanism of ''template switching'' during reverse transcription, predominant in all retroviruses, most certainly also applies to pararetroviruses. For this reason, and on the basis of numerous experimental data, CaMV is generally believed to recombine mostly in the cytoplasm of the host cell, by ''legal'' template switching between two pre-genomic RNA molecules [21, 35, 36, 38, 39] , or ''illegal'' template switching between the 19S and the 35S RNA [36, 40] . Under this hypothesis, recombination in CaMV could therefore be considered as operating on a linear template during reverse transcription, with the 59 and 39 extremities later ligated to circularize the genomic DNA (position 0 in Figure 1 ). The above cited studies clearly demonstrate that CaMV is able to recombine. However, since these studies are based on complementation techniques, non-quantitative detection, or phylogenetically based inferences of recombination, they do not inform us on whether recombination is an exceptional event or an ''everyday'' process shaping the genetic composition of CaMV populations. |
In the present work, we aimed at answering this question. To this end, we have constructed a CaMV genome with four genetic markers, demonstrated to be neutral in competition experiments. By co-inoculating host plants with equal amounts of wild-type and marker-containing CaMV particles, we have generated mixed populations in which impressive proportions of recombinants-distributed in several different classes corresponding to exchange of different genomic regions-have been detected and quantified. Altogether, the recombinant genomes averaged over 50% of the population. Further analysis of these data, assuming a number of viral replications during the infection period ranging from five to 20, indicates that the per nucleotide per replication cycle [44] ) indicates the origin of replication via reverse transcription, which occurs in the direction indicated by the dotted outermost circle-like arrow. Reverse transcription is accomplished by the viral reverse transcriptase, using the 35S RNA as template [49] . DOI: 10.1371/journal.pbio.0030089.g001 recombination rate of CaMV is of the same order of magnitude, i.e., on the order of a few 10 À5 , across the entire genome. We thereby provide the first quantification, to our knowledge, of the recombination rate in a virus population during a single passage in a single host. |
From Figure 1 , and supposing that all marker-containing genomic regions can recombine, we could predict the detection and quantification of seven classes of recombinant genotypes: þbcd/aþþþ, aþcd/þbþþ, abþd/þþcþ, abcþ/þþþd, þþcd/abþþ, aþþd/þbcþ, and aþcþ/þbþd. Indeed, all classes were detected, and their frequencies in the ten CaMV populations analyzed are summarized in Table 1 . |
Altogether, the proportion of recombinant genomes found in the mixed viral populations was astonishingly high and very similar in the ten co-infected plants analyzed (Table 1 , last column), ranging between 44% (plant 5) to 60% (plants 7, 12, and 20), with a mean frequency (6 standard error) of 53.8% 6 2.0%. This result indicates that recombination events are very frequent during the invasion of the host plant by CaMV and represents, to our knowledge, the first direct quantification of viral recombination during the infection of a live multi-cellular host. |
The inferred per generation recombination and interference rates, assuming that CaMV undergoes ten replication cycles during the 21 d between infection and sampling, are given for each of the ten plants in Table 2 . Recombination rates between adjacent markers are large, on the order of 0.05 to 0.1. Taking the distance in nucleotides between markers into account yields an average recombination rate per nucleotide and generation on the order of 4 3 10 À5 . |
Interestingly, this recombination rate does not vary throughout the genome (Kruskal-Wallis test, p = 0.16). |
To relax the assumption of the number of replications during the 21 d, we calculated the recombination parameters assuming five or 20 generations. The effect of the number of generations on the estimates is linear: doubling the number of generations results in a halving of the recombination rate (detailed results not shown). For example, the average recombination rates r 1 , r 2 , and r 3 assuming 20 generations were equal to 0.05, 0.04, and 0.025, respectively (compare with values in Table 2 ), yielding per nucleotide per generation recombination rates of 1.9 3 10 À5 , 2.2 3 10 À5 and 1.6 3 10 À5 . |
Inspection of Table 2 also shows that first-order interference coefficients were in general negative, indicating that a crossing over in one genomic segment increases the probability that a crossing over will occur in another genomic segment, while the second-order coefficient parameter had an average value close to zero with a large variance. The mechanism leading to these results will be discussed in the following section. |
One major breakthrough in the work presented here lies in the space and time scales at which the experiments were performed. Indeed, the processes occurring within the course of a single infection of one multi-cellular host are of obvious biological relevance for any disease. Previous studies on viral recombination suffered from major drawbacks in this respect, basing their conclusions on experiments relying on complementation among non-infectious viruses or between viruses with undetermined relative fitness, on phylogenetically based analyses, or on experiments in cell cultures. For reasons detailed in the Introduction, the first two methods either do not provide information on the frequency of recombination, but only its occurrence, or address the question at a different temporal, and often spatial, scale. Results from cell cultures, on the other hand, impose cell coinfection by different viral variants, potentially overestimat- ing the frequency of recombination events. Our study circumvents these limitations by analyzing viral genotypes sampled from infected plants after the course of a single infection, and therefore the invasion and co-infection of cells in various organs and tissues is very close to natural. More than half of the genomes (53.8% 6 2.0%; see Table 1 ) present in a CaMV population after a single passage in its host plant were identified as recombinants, and these data allowed us to infer a per nucleotide per generation recombination rate on the order of 2 3 10 À5 to 4 3 10 À5 . The time length of one generation, i.e., the time required for a given genome to go from one replication to the next, is totally unknown in plant viruses. The only experimental data available on CaMV are based on the kinetics of gene expression in infected protoplasts, where the capsid protein is produced between 48 and 72 h [40] . The reverse transcription and the encapsidation of genomic DNA being two coupled phenomena [30] , we judged it reasonable to assume a generation time of 2 d and, thus, an average of ten generations during our experiments. In case this estimate is mistaken, we have verified a linear relationship between r and the number of generations, thereby allowing an immediate adjustment of r if the CaMV generation time is more precisely established. At this point, we must consider that all cloned genomes may not have been through all the successive replication events potentially allowed by the timing of our experiments. It was previously shown that about 95% of CaMV mature virus particles accumulate in compact inclusion bodies [41] , where they may be sequestered for a long time, as such inclusions are very frequent in all infected cells, including those in leaves that have been invaded by the virus population for several weeks. The viral population may thus present an age structure that could bias the estimation of the recombination rate. In order to minimize this bias, the clones we analyzed were collected in one young newly formed leaf, where the chances of finding genomes from ''unsequestered lines'' were assumed to be higher. In any case, our data analysis is conservative, since this age structure can only lead to an underestimation of the recombination rate. |
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