Stochastic Modeling of T cell receptor gene rearrangement

RepSeq Data Representativeness and Robustness Assessment by Shannon Entropy

High-throughput sequencing (HTS) has the potential to decipher the diversity of T cell repertoires and their dynamics during immune responses. Applied to T cell subsets such as T effector and T regulatory cells, it should help identify novel biomarkers of diseases. However, given the extreme diversity of TCR repertoires, understanding how the sequencing conditions, including cell numbers, biological and technical sampling and sequencing depth, impact the experimental outcome is critical to proper use of these data. Here, we assessed the representativeness and robustness of TCR repertoire diversity assessment according to experimental conditions. By comparative analyses of experimental datasets and computer simulations, we found that (i) for small samples, the number of clonotypes recovered is often higher than the number of cells per sample, even after removing the singletons; (ii) high-sequencing depth for small samples alters the clonotype distributions, which can be corrected by filtering the datasets using Shannon entropy as a threshold; and (iii) a single sequencing run at high depth does not ensure a good coverage of the clonotype richness in highly polyclonal populations, which can be better covered using multiple sequencing. Altogether, our results warrant better understanding and awareness of the limitation of TCR diversity analyses by HTS and justify the development of novel computational tools for improved modeling of the highly complex nature of TCR repertoires.

Long-Range Control of V(D)J Recombination & Allelic Exclusion: Modeling Views

Allelic exclusion of immunoglobulin (Ig) and T-cell receptor (TCR) genes ensures the development of B and T lymphocytes operating under the mode of clonal selection. This phenomenon associates asynchronous V(D)J recombination events at Ig or TCR alleles and inhibitory feedback control. Despite years of intense research, however, the mechanisms that sustain asymmetric choice in random Ig/TCR dual allele usage and the production of Ig/TCR monoallelic expressing B and T lymphocytes remain unclear and open for debate. In this chapter, we first recapitulate the biological evidence that almost from the start appeared to link V(D)J recombination and allelic exclusion. We review the theoretical models previously proposed to explain this connection. Finally, we introduce our own mathematical modeling views based on how the developmental dynamics of individual lymphoid cells combine to sustain allelic exclusion.

Models and methods for analysis of lymphocyte repertoire generation, development, selection and evolution

T and B cell receptor repertoires are diversified by variable region gene rearrangement and selected based on functionality and lack of self-reactivity. Repertoires can also be defined based on phenotype and function rather than receptor specificity - such as the diversity of T helper cell subsets. Natural killer (NK) cell repertoires, in which each cell expresses a randomly chosen subset of its inhibitory receptor genes, and is educated based on self-MHC recognition by yet unknown mechanisms, are also phenotypic repertoires. Studying the generation, development and selection of lymphocyte repertoires, and their functions during immune responses, is essential for understanding the function of the immune system in healthy individuals and in immune deficient, autoimmune or cancer patients. The study of lymphocyte repertoires will enable clinical immunologists to develop better therapeutic monoclonal antibodies, vaccines, transplantation donor-recipient matching protocols, and other immune intervention strategies. The recent development of high-throughput methods for repertoire data collection - from multicolor flow cytometry through single-cell imaging to deep sequencing - presents us now, for the first time, with the ability to analyze and compare large samples of lymphocyte repertoires in health, aging and disease. The exponential growth of these datasets, however, challenges the theoretical immunology community to develop methods for data organization and analysis. Furthermore, the need to test hypotheses regarding immune function, and generate predictions regarding the outcomes of medical interventions, necessitates the development of complex mathematical and computational models, covering processes on multiple scales, from the genetic and molecular to the cellular and system scales.

Epigenetic control of Tcrb gene rearrangement

V(D)J recombination assembles antigen receptor genes from germline V, D and J segments during lymphocyte development. In αβT-cells, this leads to the subsequent expression of T-cell receptor (TCR) β and α chains. Generally, V(D)J recombination is closely controlled at various levels, including cell-type and cell-stage specificities, order of locus/gene segment recombination, and allele usage to mediate allelic exclusion. Many of these controls rely on the modulation of gene accessibility to the recombination machinery, involving not only biochemical changes in chromatin arrangement and structural modifications of chromosomal organization and positioning, but also the refined composition of the recombinase targets, the so-called recombination signal sequences. Here, we summarize current knowledge regarding the regulation of V(D)J recombination at the Tcrb gene locus, certainly one for which these various levels of control and regulatory components have been most extensively investigated.

TCR beta allelic exclusion in dynamical models of V(D)J recombination based on allele independence

Allelic exclusion represents a major aspect of TCRbeta gene assembly by V(D)J recombination in developing T lymphocytes. Despite recent progress, its comprehension remains problematic when confronted with experimental data. Existing models fall short in terms of incorporating into a unique distribution all the cell subsets emerging from the TCRbeta assembly process. To revise this issue, we propose dynamical, continuous-time Markov chain-based modeling whereby essential steps in the biological procedure (D-J and V-DJ rearrangements and feedback inhibition) evolve independently on the two TCRbeta alleles in every single cell while displaying random modes of initiation and duration. By selecting parameters via fitting procedures, we demonstrate the capacity of the model to offer accurate fractions of all distinct TCRbeta genotypes observed in studies using developing and mature T cells from wild-type or mutant mice. Selected parameters in turn afford relative duration for each given step, hence updating TCRbeta recombination distinctive timings. Overall, our dynamical modeling integrating allele independence and noise in recombination and feedback-inhibition events illustrates how the combination of these ingredients alone may enforce allelic exclusion at the TCRbeta locus.

Epigenetic regulation of antigen receptor gene rearrangement

V(D)J recombination assembles antigen-specific immunoglobulin and T-cell receptor variable region genes from germline V, D, and J segments during lymphocyte development. Regulation of this site-specific DNA rearrangement process occurs with respect to the cell type and stage of differentiation, order of locus recombination, and allele usage. Many of these controls are mediated via the modulation of gene accessibility to the V(D)J recombinase. Here, we summarise recent advances regarding the impact of nuclear organisation and epigenetic-based mechanisms on the regulation of V(D)J recombination.

Quantitative insights into stochastic monoallelic expression of cytokine genes

Gene expression from both parental alleles is beneficial by masking the effects of deleterious recessive mutations and by reducing the noise in gene expression in diploid organisms. However, a class of genes are expressed preferentially or strictly from a single allele. The selective advantage of avoiding biallelic expression is clear for allelic-excluded antigen receptor and odorant receptor genes, genes undergoing X-chromosome inactivation in females and parental genomic imprinted genes. In contrast, there is no clear biological rationale for the predominant and stochastic monoallelic expression of cytokine genes in the immune system, and the underlying mechanism is elusive and controversial. A clarification of the mechanism of predominant monoallelic expression would be instrumental in better understanding its eventual biological functional. This prompted the development of a quantitative framework that could describe the dynamics of the pattern of allele expression of the IL-10 gene, from which general quantitative insights could be gained. We report that the experimental observations on these patterns of allelic expression cannot be easily reconciled with a simple model of stochastic transcriptional activation, in which the two alleles are, at any time, equally competent for transcription. Instead, these observations call into action a general model of eukaryotic transcriptional regulation according to which the locus competence for transcription is dynamic, involving multiple, cooperative and stochastic modification steps. In this model, the probability that an allele becomes transcriptionally active is a function of the number of chromatin modifications that it accumulated. On the basis of the properties of this model, we argue that predominant monoallelic expression might have had no adaptive role, and may have evolved under indirect selection for low frequency of expressing cells.

Regulation of V(D)J recombination

Adaptive immunity is intimately linked to the expression of antigen-specific immunoglobulin and T cell receptor genes and their recombination assembly from germline V, D and J gene segments. This developmentally regulated process relies on the activity of the Rag1-Rag2 recombinase, on accessibility of target gene segments and on monoallelic gene activation. Recent studies have revealed new mechanisms that, along with recombinase activity and locus accessibility, are likely to contribute to the control of V(D)J recombination, including target-site bias by the recombinase, RNA processing and chromosome positioning.