B cells have been found to play a critical role in the pathogenesis of several autoimmune (AI) diseases. A common feature amongst many AI diseases is the formation of ectopic germinal centers (GC) within the afflicted tissue or organ, in which activated B cells expand and undergo somatic hypermutation (SHM) and antigen-driven selection on their immunoglobulin variable region (IgV) genes. However, it is not yet clear whether these processes occurring in ectopic GCs are identical to those in normal GCs. The analysis of IgV mutations has aided in revealing many aspects concerning B cell expansion, mutation and selection in GC reactions. We have applied several mutation analysis methods, based on lineage tree construction, to a large set of data, containing IgV productive and non-productive heavy and light chain sequences from several different tissues, to examine three of the most profoundly studied AI diseases - Rheumatoid Arthritis (RA), Multiple Sclerosis (MS) and Sjögren's Syndrome (SS). We have found that RA and MS sequences exhibited normal mutation spectra and targeting motifs, but a stricter selection compared to normal controls, which was more apparent in RA. SS sequence analysis results deviated from normal controls in both mutation spectra and indications of selection, also showing differences between light and heavy chain IgV and between different tissues. The differences revealed between AI diseases and normal control mutation patterns may result from the different microenvironmental influences to which ectopic GCs are exposed, relative to those in normal secondary lymphoid tissues.

BACKGROUND: B lymphocytes are subject to elimination following strong BCR ligation in the absence of appropriate second signals, and this mechanism mediates substantial cell losses during late differentiation steps in the bone marrow and periphery. Mature B cells may also be eliminated through this mechanism as well as through normal turnover, but the population containing mature cells destined for elimination has not been identified. Herein, we asked whether the transitional 3 (T3) subset, which contains most newly formed cells undergoing anergic death, could also include mature B cells destined for elimination. METHODOLOGY/PRINCIPAL FINDINGS: To interrogate this hypothesis and its implications, we applied mathematical models to previously generated in vivo labeling data. Our analyses reveal that the death rate of T3 B cells is far higher than the death rates of all other splenic B cell subpopulations. Further, the model, in which the T3 pool includes both newly formed and mature primary B cells destined for apoptotic death, shows that this cell loss may account for nearly all mature B cell turnover. CONCLUSIONS/SIGNIFICANCE: This finding has implications for the mechanism of normal mature B cell turnover.

Young patients with Myasthenia Gravis (MG) frequently have ectopic GCs in their thymus. We investigated these ectopic GCs by microdissection of GC B cells and analysis of their Ig gene characteristics, in comparison to normal GCs. CDR3 length distribution, a measure of clonal variability, and Ig gene family usage, were similar in MG and normal tonsil samples. Lineage tree analysis demonstrated similar diversification and mutations per cell compared to normal control trees. Mutations were observed in the framework regions, responsible for the structural integrity of the BCR; however, these mutations were mostly conservative or neutral, confirming that a functional BCR is conserved in MG. In the CDRs, responsible for antigen binding, selection against replacement mutations was revealed. This may indicate that the MG clones analyzed are already highly antigen-specific, and therefore potential affinity-reducing replacement mutations in the CDR3 are not propagated, due to antigen-driven selection. Somatic hypermutation targeting motifs and aa substitution preferences in MG were similar to those of normal controls. Overall, these results suggest that B cells in the ectopic GCs in MG appear to undergo normal diversification and selection, in spite of the chronic nature and different environment of the response.

Regulated gene expression assembles an extracellular proteinaceous matrix to control biomineralization and the resultant biomechanical function of tooth enamel. The importance of the dominant enamel matrix protein, amelogenin (Amel); a minor transiently expressed protein, dentin sialoprotein (Dsp); an electrogenic sodium bicarbonate cotransporter (NBCe1); the timely removal of the proteinaceous matrix by a serine protease, Kallikrein-4 (Klk4); and the late-stage expression of Amelotin (Amtn) on enamel biomechanical function were demonstrated and measured using mouse models.

Microarray technology which enables large scale analysis of gene expression and thus comparison between transcriptomes of different cell types, cells undergoing different treatments or cells at different developmental stages has also been used to study the transcriptome involved with spermatogenesis. Many new germ cell-specific genes were determined, and the resulting genes were classified according to different criteria. However, the biological significance of these classifications and their clustering according to developmental transcriptional patterns during spermatogenesis have not yet been addressed. In this study we utilized mouse testicular transcriptome analysis at five distinct post-natal ages (Days 7, 10, 12, 14, and 17), representing distinct meiotic stages, in an attempt to better understand the biological significance of genes clustered into similar expression patterns during this process. Among 790 sequences that showed an expression level change of twofold or more in any of the five key stages that were monitored, relative to the geometric average of all stages, about 40% peaked and about 30% were specifically suppressed at post-natal day 14 (representing the early pachytene stage of spermatocytes), reflecting tight transcriptional regulation at this stage. We also found that each of the six main transcription clusters that were determined was characterized by statistically significant representation of genes related to specific biological processes. Finally, our results indicated that genes important for meiosis are not randomly distributed along the mouse genome but rather preferentially located on specific chromosomes, suggesting for the first time that chromosomal location might be a regulating factor of meiotic gene expression.

Adenosine-to-inosine (A-to-I) RNA editing alters the original genomic content of the human transcriptome and is essential for maintenance of normal life in mammals. A-to-I editing in Alu repeats is abundant in the human genome, with many thousands of expressed Alu sequences undergoing editing. Little is known so far about the contribution of Alu editing to transcriptome complexity. Transcripts derived from a single edited Alu sequence can be edited in multiple sites, and thus could theoretically generate a large number of different transcripts. Here we explored whether the combinatorial potential nature of edited Alu sequences is actually fulfilled in the human transcriptome. We analyzed datasets of editing sites and performed an analysis of a detailed transcript set of one edited Alu sequence. We found that editing appears at many more sites than detected by earlier genomic screens. To a large extent, editing of different sites within the same transcript is only weakly correlated. Thus, rather than finding a few versions of each transcript, a large number of edited variants arise, resulting in immense transcript diversity that eclipses alternative splicing as mechanism of transcriptome diversity, although with less impact on the proteome.

Murine natural killer (NK) cells express inhibitory Ly49 receptors for MHC class I molecules, which allows for "missing self" recognition of cells that downregulate MHC class I expression. During murine NK cell development, host MHC class I molecules impose an "educating impact" on the NK cell pool. As a result, mice with different MHC class I expression display different frequency distributions of Ly49 receptor combinations on NK cells. Two models have been put forward to explain this impact. The two-step selection model proposes a stochastic Ly49 receptor expression followed by selection for NK cells expressing appropriate receptor combinations. The sequential model, on the other hand, proposes that each NK cell sequentially expresses Ly49 receptors until an interaction of sufficient magnitude with self-class I MHC is reached for the NK cell to mature. With the aim to clarify which one of these models is most likely to reflect the actual biological process, we simulated the two educational schemes by mathematical modelling, and fitted the results to Ly49 expression patterns, which were analyzed in mice expressing single MHC class I molecules. Our results favour the two-step selection model over the sequential model. Furthermore, the MHC class I environment favoured maturation of NK cells expressing one or a few self receptors, suggesting a possible step of positive selection in NK cell education. Based on the predicted Ly49 binding preferences revealed by the model, we also propose, that Ly49 receptors are more promiscuous than previously thought in their interactions with MHC class I molecules, which was supported by functional studies of NK cell subsets expressing individual Ly49 receptors.

In studies of inflammatory bowel diseases (IBD), research has so far focused mainly on the role of T cells. Despite evidence suggesting that B cells and the production of autoantibodies may play a significant role in IBD pathogenesis, the role of B cells in gut inflammation has not yet been thoroughly investigated. In the present study we used the new approach of lineage tree analysis for studying immunoglobulin variable region gene diversification in B cells found in the inflamed intestinal tissue of two ulcerative colitis patients as well as B cells from mucosa-associated lymph nodes (LN) in the same patients. Healthy intestinal tissue of three patients with carcinoma of the colon was used as normal control. Lineage tree shapes revealed active immune clonal diversification processes occurring in ulcerative colitis patients, which were quantitatively similar to those in healthy controls. B cells from intestinal tissues and the associated LN are shown here to be clonally related, thus supplying the first direct evidence supporting B-cell trafficking between gut and associated LN in IBD and control tissues.

During the immune response, the generation of memory B lymphocytes in germinal centers involves affinity maturation of the cells' antigen receptors, based on somatic hypermutation of receptor genes and antigen-driven selection of the resulting mutants. Affinity maturation is vital for immune protection, and is the basis of humoral immune learning and memory. Lineage trees of somatically hypermutated immunoglobulin genes often serve to qualitatively illustrate claims concerning the dynamics of affinity maturation in germinal centers. Here, we derive the quantitative relationships between parameters characterizing affinity maturation dynamics (proliferation, differentiation and mutation rates, initial affinity of the Ig to the antigen, and selection thresholds) and the mathematical properties of lineage trees, using a computer simulation which combines mathematical models for all mature B cell populations, stochastic models of hypermutation and selection, lineage tree generation and measurement of graphical tree characteristics. We identified seven key lineage tree properties, and found correlations of these with initial clone affinity and with the selection threshold. These two parameters were found to be the main factors affecting lineage tree shapes in both primary and secondary response trees. The results also confirm that recycling from centrocytes back to centroblasts is highly likely.

Lineage trees describe the microevolution of cells within an organism. They have been useful in the study of B cell affinity maturation, which is based on somatic hypermutation of immunoglobulin genes in germinal centers and selection of the resulting mutants. Our aim was to create and implement an algorithm that can generate lineage trees from immunoglobulin variable region gene sequences. The IgTree program implements the algorithm we developed, and generates lineage trees. Original sequences found in experiments are assigned to either leaves or internal nodes of the tree. Each tree node represents a single mutation separating the sequences. The mutations that separate the sequences from each other can be point mutations, deletions or insertions. The program can deal with gaps and find potential reversion mutations. The program also enumerates mutation frequencies and sequence motifs around each mutation, on a per-tree basis. The algorithm has proven useful in several studies of immunoglobulin variable region gene mutations.

Autoimmune diseases show high diversity in the affected organs, clinical manifestations and disease dynamics. Yet they all share common features, such as the ectopic germinal centers found in many affected tissues. Lineage trees depict the diversification, via somatic hypermutation (SHM), of immunoglobulin variable-region (IGV) genes. We previously developed an algorithm for quantifying the graphical properties of IGV gene lineage trees, allowing evaluation of the dynamical interplay between SHM and antigen-driven selection in different lymphoid tissues, species, and disease situations. Here, we apply this method to ectopic GC B cell clones from patients with Myasthenia Gravis, Rheumatoid Arthritis, and Sjögren's Syndrome, using data scaling to minimize the effects of the large variability due to methodological differences between groups. Autoimmune trees were found to be significantly larger relative to normal controls. In contrast, comparison of the measurements for tree branching indicated that similar selection pressure operates on autoimmune and normal control clones.

Despite the various processing steps involved in V(D)J recombination, which could potentially introduce many biases in the length distribution of complementarity determining region 3 (CDR3) segments, the observed CDR3 length distributions for complete repertoires are very close to a normal-like distribution. This raises the question of whether this distribution is simply a result of the random steps included in the process of gene rearrangement, or has been optimized during evolution. We have addressed this issue by constructing a simulation of gene rearrangement, which takes into account the DNA modification steps included in the process, namely hairpin opening, nucleotide additions, and nucleotide deletions. We found that the near-Gaussian- shape of CDR3 length distribution can only be obtained under a relatively narrow set of parameter values, and thus our model suggests that specific biases govern the rearrangement process. In both B-cell receptor (BCR) heavy chain and T-cell receptor beta chain, we obtained a Gaussian distribution using identical parameters, despite the difference in the number and the lengths of the D segments. Hence our results suggest that these parameters most likely reflect the optimal conditions under which the rearrangement process occurs. We have subsequently used the insights gained in this study to estimate the probability of occurrence of two exactly identical BCRs over the course of a human lifetime. Whereas identical rearrangements of the heavy chain are highly unlikely to occur within one human lifetime, for the light chain we found that this probability is not negligible, and hence the light chain CDR3 alone cannot serve as an indicator of B-cell clonality.

Immunoglobulin light chain amyloidosis (AL) is characterized by a limited clonal expansion of plasma cells and amyloid formation. Here, we report restriction in the diversity of VL gene usage with a dominance of clonally related B cells in the peripheral blood (PB) isotype-specific repertoire of AL patients. A rigorous quantification of lineage trees reveals presence of intraclonal variations in the PB clones compared to the bone marrow (BM) clones, which suggests a common precursor that is still subject to somatic mutation. When compared to normal BM and PB B cells, AL clones showed significant but incomplete impairment of antigenic selection, which could not be detected by conventional R and S mutation analysis. Therefore, graphical analysis of B cell lineage trees and mathematical quantification of tree properties provide novel insights into the process of B cell clonal evolution in AL.

Tree structures are useful for describing and analyzing biological objects and processes. Consequently, there is a need to design metrics and algorithms to compare trees. A natural comparison metric is the "Tree Edit Distance," the number of simple edit (insert/delete) operations needed to transform one tree into the other. Rooted-ordered trees, where the order between the siblings is significant, can be compared in polynomial time. Rooted-unordered trees are used to describe processes or objects where the topology, rather than the order or the identity of each node, is important. For example, in immunology, rooted-unordered trees describe the process of immunoglobulin (antibody) gene diversification in the germinal center over time. Comparing such trees has been proven to be a difficult computational problem that belongs to the set of NP-Complete problems. Comparing two trees can be viewed as a search problem in graphs. A* is a search algorithm that explores the search space in an efficient order. Using a good lower bound estimation of the degree of difference between the two trees, A* can reduce search time dramatically. We have designed and implemented a variant of the A* search algorithm suitable for calculating tree edit distance. We show here that A* is able to perform an edit distance measurement in reasonable time for trees with dozens of nodes.

Systems of differentiating cells are often regarded by experimental biologists as unidirectional processes, in which cells spend a fixed time at each successive developmental stage. However, mathematical modeling has in several cases revealed that differentiating cell systems are more complex than previously believed. For example, non-linear transitions, feedback effects, and even apparent reversals have been suggested by our studies on models for the development of lymphocytes and their receptor repertoires, and are reviewed in this paper. These studies have shown that cell population growth in developing lymphocyte subsets is usually nonlinear, as it depends on the density of cells in each compartment. Additionally, T cell development has been shown to be subject to feedback regulation by mature T cell subsets, and B cell development has been shown to include a phenotypic reflux from an advanced to an earlier developmental stage. The challenges we face in our efforts to understand how the repertoires of these cells are generated and regulated are also discussed here.

Lineage trees have frequently been drawn to illustrate diversification, via somatic hypermutation (SHM), of immunoglobulin variable-region (IGV) genes. In order to extract more information from IGV sequences, we developed a novel mathematical method for analyzing the graphical properties of IgV gene lineage trees, allowing quantification of the differences between the dynamics of SHM and antigen-driven selection in different lymphoid tissues, species, and disease situations. Here, we investigated trees generated from published IGV sequence data from B cell clones participating in autoimmune responses in patients with Myasthenia Gravis (MG), Rheumatoid Arthritis (RA), and Sjögren's Syndrome (SS). At present, as no standards exist for cell sampling and sequence extraction methods, data obtained by different research groups from two studies of the same disease often vary considerably. Nevertheless, based on comparisons of data groups within individual studies, we show here that lineage trees from different individual patients are often similar and can be grouped together, as can trees from two different tissues in the same patient, and even from IgG- and IgA-expressing B cell clones. Additionally, lineage trees from most studies reflect the chronic character of autoimmune diseases.

Light chain amyloidosis (AL) is a bone marrow (BM) plasma cell neoplasia with systemic deposition of Ig light chain amyloid fibrils. Here, we report the identification of clonal CD19 B cells in the BM and the use of a novel mathematical algorithm to generate B cell lineage trees of the clonal CD19 B cells and CD138 plasma cells from the BM of AL patients to delineate the relationship between these two clonal populations. The CD19+ clonal B cells in the BM of AL patients related to the clonal plasma cells represent a pre-plasma cell precursor population. The B cell lineage trees from AL patients also show significant differences in clonal diversification and antigenic selection compared to clones from normal, healthy controls. These data provide a robust example of the use of graphical quantification methods in delineating the role of neoplastic precursors in the pathogenesis of hematopoietic malignancies.

Previous studies have not completely clarified the precise defect that characterizes B cell development in aged animals. The question of which developmental mechanism is actually deficient in aging remains controversial. The goal of this study was to elucidate the effects of aging on bone marrow B cell population dynamics. We used mathematical modeling to predict the outcome of the different possible effects, and then compared these predictions to experimental data, to find the most plausible effects. Our model shows that the three main differences between B cell development in young and old mice are a decrease in the maximum number of cells in the pre-B compartment and increases in the rate of transition from cycling pre-B cells to resting pre-B cells and in the fractions of static cells included in the immature B cell subset.

The ability of murine NK cells to reject cells lacking self MHC class I expression results from an in vivo education process. To study the impact of individual MHC class I alleles on this process, we generated mice expressing single MHC class I alleles (K(b), D(b), D(d), or L(d)) or combinations of two or more alleles. All single MHC class I mice rejected MHC class I-deficient cells in an NK cell-dependent way. Expression of K(b) or D(d) conveyed strong rejection of MHC class I-deficient cells, whereas the expression of D(b) or L(d) resulted in weaker responses. The educating impact of weak ligands (D(b) and L(d)) was further attenuated by the introduction of additional MHC class I alleles, whereas strong ligands (K(b) and D(d)) maintained their educating impact under such conditions. An analysis of activating and inhibitory receptors in single MHC class I mice suggested that the educating impact of a given MHC class I molecule was controlled both by the number of NK cells affected and by the strength of each MHC class I-Ly49 receptor interaction, indicating that NK cell education may be regulated by a combination of qualitative and quantitative events.