Quantifying selection in immune receptor repertoires

Origin of Public Memory B Cell Clones in Fish After Antiviral Vaccination

Vaccination induces “public” antibody clonotypes common to all individuals of a species, that may mediate universal protection against pathogens. Only few studies tried to trace back the origin of these public B-cell clones. Here we used Illumina sequencing and computational modeling to unveil the mechanisms shaping the structure of the fish memory antibody response against an attenuated Viral Hemorrhagic Septicemia rhabdovirus. After vaccination, a persistent memory response with a public VH5JH5 IgM component was composed of dominant antibodies shared among all individuals. The rearrangement model showed that these public junctions occurred with high probability indicating that they were already favored before vaccination due to the recombination process, as shown in mammals. In addition, these clonotypes were in the naïve repertoire associated with larger similarity classes, composed of junctions differing only at one or two positions by amino acids with comparable properties. The model showed that this property was due to selective processes exerted between the recombination and the naive repertoire. Finally, our results showed that public clonotypes greatly expanded after vaccination displayed several VDJ junctions differing only by one or two amino acids with similar properties, highlighting a convergent response. The fish public memory antibody response to a virus is therefore shaped at three levels: by recombination biases, by selection acting on the formation of the pre-vaccination repertoire, and by convergent selection of functionally similar clonotypes during the response. We also show that naive repertoires of IgM and IgT have different structures and sharing between individuals, due to selection biases. In sum, our comparative approach identifies three conserved features of the antibody repertoire associated with public memory responses. These features were already present in the last common ancestors of fish and mammals, while other characteristics may represent species-specific solutions.

The expanding role of systems immunology in decoding the T cell receptor repertoire

T cells play a crucial role in the immune system's defense against many infectious diseases, including persistent infections for which no effective vaccines currently exist. The T cell component of the adaptive immune system is highly complex involving a constantly evolving landscape of various inter-related T cell populations. These T cell populations are characterized by their phenotypic and functional properties as well as the collection, or repertoire, of T cell receptors (TCR) that mediate T cell recognition of antigenic peptides derived from pathogens. Understanding the various processes and factors that impact the development and evolution of the broader T cell repertoire available to recognize and respond to pathogens and the characteristics of antigen-experienced T cell repertoires associated with effective immune control of pathogens is critical to the rational design of T cell-based vaccines and therapies. In this article we discuss, using examples of recent research, the promise that systems immunology approaches, involving quantitative analysis and mathematical and computational modeling of immunological data, hold for decoding the complex TCR repertoire system in the current era of advancing technologies.

High-throughput sequencing of the T-cell receptor repertoire: pitfalls and opportunities

T-cell specificity is determined by the T-cell receptor, a heterodimeric protein coded for by an extremely diverse set of genes produced by imprecise somatic gene recombination. Massively parallel high-throughput sequencing allows millions of different T-cell receptor genes to be characterized from a single sample of blood or tissue. However, the extraordinary heterogeneity of the immune repertoire poses significant challenges for subsequent analysis of the data. We outline the major steps in processing of repertoire data, considering low-level processing of raw sequence files and high-level algorithms, which seek to extract biological or pathological information. The latest generation of bioinformatics tools allows millions of DNA sequences to be accurately and rapidly assigned to their respective variable V and J gene segments, and to reconstruct an almost error-free representation of the non-templated additions and deletions that occur. High-level processing can measure the diversity of the repertoire in different samples, quantify V and J usage and identify private and public T-cell receptors. Finally, we discuss the major challenge of linking T-cell receptor sequence to function, and specifically to antigen recognition. Sophisticated machine learning algorithms are being developed that can combine the paradoxical degeneracy and cross-reactivity of individual T-cell receptors with the specificity of the overall T-cell immune response. Computational analysis will provide the key to unlock the potential of the T-cell receptor repertoire to give insight into the fundamental biology of the adaptive immune system and to provide powerful biomarkers of disease.

Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination

Despite the extreme diversity of T-cell repertoires, many identical T-cell receptor (TCR) sequences are found in a large number of individual mice and humans. These widely shared sequences, often referred to as "public," have been suggested to be over-represented due to their potential immune functionality or their ease of generation by V(D)J recombination. Here, we show that even for large cohorts, the observed degree of sharing of TCR sequences between individuals is well predicted by a model accounting for the known quantitative statistical biases in the generation process, together with a simple model of thymic selection. Whether a sequence is shared by many individuals is predicted to depend on the number of queried individuals and the sampling depth, as well as on the sequence itself, in agreement with the data. We introduce the degree of publicness conditional on the queried cohort size and the size of the sampled repertoires. Based on these observations, we propose a public/private sequence classifier, "PUBLIC" (Public Universal Binary Likelihood Inference Classifier), based on the generation probability, which performs very well even for small cohort sizes.

The Bayesian optimist's guide to adaptive immune receptor repertoire analysis

Probabilistic modeling is fundamental to the statistical analysis of complex data. In addition to forming a coherent description of the data-generating process, probabilistic models enable parameter inference about given datasets. This procedure is well developed in the Bayesian perspective, in which one infers probability distributions describing to what extent various possible parameters agree with the data. In this paper, we motivate and review probabilistic modeling for adaptive immune receptor repertoire data then describe progress and prospects for future work, from germline haplotyping to adaptive immune system deployment across tissues. The relevant quantities in immune sequence analysis include not only continuous parameters such as gene use frequency but also discrete objects such as B-cell clusters and lineages. Throughout this review, we unravel the many opportunities for probabilistic modeling in adaptive immune receptor analysis, including settings for which the Bayesian approach holds substantial promise (especially if one is optimistic about new computational methods). From our perspective, the greatest prospects for progress in probabilistic modeling for repertoires concern ancestral sequence estimation for B-cell receptor lineages, including uncertainty from germline genotype, rearrangement, and lineage development.

Evidence for Shaping of Light Chain Repertoire by Structural Selection

The naïve immunoglobulin (IG) repertoire in the blood differs from the direct output of the rearrangement process. These differences stem from selection that affects the germline gene usage and the junctional nucleotides. A major complication obscuring the details of the selection mechanism in the heavy chain is the failure to properly identify the D germline and determine the nucleotide addition and deletion in the junction region. The selection affecting junctional diversity can, however, be studied in the light chain that has no D gene. We use probabilistic and deterministic models to infer and disentangle generation and selection of the light chain, using large samples of light chains sequenced from healthy donors and transgenic mice. We have previously used similar models for the beta chain of T-cell receptors and the heavy chain of IGs. Selection is observed mainly in the CDR3. The CDR3 length and mass distributions are narrower after selection than before, indicating stabilizing selection for mid-range values. Within the CDR3, proline and cysteine undergo negative selection, while glycine undergoes positive selection. The results presented here suggest structural selection maintaining the size of the CDR3 within a limited range, and preventing turns in the CDR3 region.

Deep Sequencing Reveals Transient Segregation of T Cell Repertoires in Splenic T Cell Zones during an Immune Response

Immunological differences between hosts, such as diverse TCR repertoires, are widely credited for reducing the risk of pathogen spread and adaptation in a population. Within-host immunological diversity might likewise be important for robust pathogen control, but to what extent naive TCR repertoires differ across different locations in the same host is unclear. T cell zones (TCZs) in secondary lymphoid organs provide secluded microenvironmental niches. By harboring distinct TCRs, such niches could enhance within-host immunological diversity. In contrast, rapid T cell migration is expected to dilute such diversity. In this study, we combined tissue microdissection and deep sequencing of the TCR β-chain to examine the extent to which TCR repertoires differ between TCZs in murine spleens. In the absence of Ag, we found little evidence for differences between TCZs of the same spleen. Yet, 3 d after immunization with sheep RBCs, we observed a >10-fold rise in the number of clones that appeared to localize to individual zones. Remarkably, these differences largely disappeared at 4 d after immunization, when hallmarks of an ongoing immune response were still observed. These data suggest that in the absence of Ag, any repertoire differences observed between TCZs of the same host can largely be attributed to random clone distribution. Upon Ag challenge, TCR repertoires in TCZs first segregate and then homogenize within days. Such "transient mosaic" dynamics could be an important barrier for pathogen adaptation and spread during an immune response.

Unique glandular ex-vivo Th1 and Th17 receptor motifs in Sjögren's syndrome patients using single-cell analysis

Primary Sjögren's syndrome (pSS) is an autoimmune disease in which the underlying cause has yet to be elucidated. The main objective of this study was to determine the T cell receptor (TCR) repertoires of individual infiltrating T helper (Th)-1 and 17 cells of pSS patients using single-cell analysis. Single-cell analysis of ex-vivo infiltrating T cells demonstrated that pSS patients had higher frequencies of activated Th17 cells. Single-cell TCR sequencing revealed that TCRβ variable (TRBV)3-1/joint (J)1-2 (CLFLSMSACVW) and TRBV20-1/J1-1 (SVGSTAIPP*T) were expressed by activated Th1 and Th17 cells in both cohorts. Uniquely, TCRα variable (TRAV)8-2/J5 (VVSDTVLETAGE) was expressed by Th1 cells present only in patients and complementarity-determining region (CDR)3α-specific motif (LSTD*E) present in both Th1/Th17 cells. The study demonstrates that both activated Th1 and Th17 cells of pSS patients showed restricted clonal diversities of which two CDR3 motifs were present in controls and patients, with another two motifs unique to pSS.

Compositional characteristics of human peripheral TRBV pseudogene rearrangements

The diversity of the T cell receptor (TCR) complementarity determining region 3 (CDR3) repertoire is the result of random combinations, insertions and deletions during recombination of the germline V, D and J gene fragments. During evolution, some human TCR beta chain variable (TRBV) pseudogenes have been retained. Many previous studies have focused on functional TRBV genes, while little attention has been given to TRBV pseudogenes. To describe the compositional characteristics of TRBV pseudogene rearrangements, we compared and analysed TRBV pseudogenes, TRBV open reading frames (ORFs) and functional TRBV genes via high-throughput sequencing of DNA obtained from the peripheral blood of 4 healthy volunteers and 4 patients. Our results revealed several differences in J and D gene usage. The V deletion distribution profile of the pseudogenes was significantly different from that of the ORFs and functional genes. In addition, arginine, lysine and cysteine were more frequently used in putative CDR3 pseudogene rearrangements, while functional rearrangements used more leucine. This study presents a comprehensive description of the compositional characteristics of peripheral TRBV pseudogene rearrangements, which will provide a reference for further research on TRBV pseudogenes.

Method for identification of condition-associated public antigen receptor sequences

Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type one diabetes responsive TCRβ sequences .

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic, and (iv) machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.

High-throughput immune repertoire analysis with IGoR

High-throughput immune repertoire sequencing is promising to lead to new statistical diagnostic tools for medicine and biology. Successful implementations of these methods require a correct characterization, analysis, and interpretation of these data sets. We present IGoR (Inference and Generation Of Repertoires)-a comprehensive tool that takes B or T cell receptor sequence reads and quantitatively characterizes the statistics of receptor generation from both cDNA and gDNA. It probabilistically annotates sequences and its modular structure can be used to investigate models of increasing biological complexity for different organisms. For B cells, IGoR returns the hypermutation statistics, which we use to reveal co-localization of hypermutations along the sequence. We demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization.

[IGoR: a tool for learning and simulating the random generation of antigen receptors]

Antigen receptors, which form the base of the adaptive immune system, are created stochastically by a DNA editing process called V(D)J recombination. As high-throughput sequencing enables to study the repertoire of these receptors, it is now possible to learn the probabilistic laws of this random process, and to use them to analyse receptors of interest, generate synthetic repertoires to create controls, or aid the identification of receptors that are specific to diseases, with possible applications for medical diagnostics. This article describes how these tasks can be performed using the IGoR software, which can learn statistical models from data, annotate existing sequences, or generate new synthetic ones with the same laws as the recombination process.

Deep sequencing of blood and gut T-cell receptor β-chains reveals gluten-induced immune signatures in celiac disease

Celiac disease (CD) patients mount an abnormal immune response to gluten. T-cell receptor (TCR) repertoires directed to some immunodominant gluten peptides have previously been described, but the global immune response to in vivo gluten exposure in CD has not been systematically investigated yet. Here, we characterized signatures associated with gluten directed immune activity and identified gluten-induced T-cell clonotypes from total blood and gut TCR repertoires in an unbiased manner using immunosequencing. CD patient total TCR repertoires showed increased overlap and substantially altered TRBV-gene usage in both blood and gut samples, and increased diversity in the gut during gluten exposure. Using differential abundance analysis, we identified gluten-induced clonotypes in each patient that were composed of a large private and an important public component. Hierarchical clustering of public clonotypes associated with dietary gluten exposure identified subsets of highly similar clonotypes, the most proliferative of which showing significant enrichment for the motif ASS[LF]R[SW][TD][DT][TE][QA][YF] in PBMC repertoires. These results show that CD-associated clonotypes can be identified and that common gluten associated immune response features can be characterized in vivo from total repertoires, with potential use in disease stratification and monitoring.

Comparative analysis of murine T-cell receptor repertoires

For understanding the rules and laws of adaptive immunity, high-throughput profiling of T-cell receptor (TCR) repertoires becomes a powerful tool. The structure of TCR repertoires is instructive even before the antigen specificity of each particular receptor becomes available. It embodies information about the thymic and peripheral selection of T cells; the readiness of an adaptive immunity to withstand new challenges; the character, magnitude and memory of immune responses; and the aetiological and functional proximity of T-cell subsets. Here, we describe our current analytical approaches for the comparative analysis of murine TCR repertoires, and show several examples of how these approaches can be applied for particular experimental settings. We analyse the efficiency of different metrics used for estimation of repertoire diversity, repertoire overlap, V-gene and J-gene segments usage similarity, and amino acid composition of CDR3. We discuss basic differences of these metrics and their advantages and limitations in different experimental models, and we provide guidelines for choosing an efficient way to lead a comparative analysis of TCR repertoires. Applied to the various known and newly developed mouse models, such analysis should allow us to disentangle multiple sophisticated puzzles in adaptive immunity.

T cell receptor β-chains display abnormal shortening and repertoire sharing in type 1 diabetes

Defects in T cell receptor (TCR) repertoire are proposed to predispose to autoimmunity. Here we show, by analyzing >2 × 10⁸TCRB sequences of circulating naive, central memory, regulatory and stem cell-like memory CD4⁺ T cell subsets from patients with type 1 diabetes and healthy donors, that patients have shorter TCRB complementarity-determining region 3s (CDR3), in all cell subsets, introduced by increased deletions/reduced insertions during VDJ rearrangement. High frequency of short CDR3s is also observed in unproductive TCRB sequences, which are not subjected to thymic culling, suggesting that the shorter CDR3s arise independently of positive/negative selection. Moreover, TCRB CDR3 clonotypes expressed by autoantigen-specific CD4⁺ T cells are shorter compared with anti-viral T cells, and with those from healthy donors. Thus, early events in thymic T cell development and repertoire generation are abnormal in type 1 diabetes, which suggest that short CDR3s increase the potential for self-recognition, conferring heightened risk of autoimmune disease.

T cell receptors are generated by somatic gene recombination, and are normally selected against autoreactivity. Here the authors show that CD4 T cells from patients with autoimmune type 1 diabetes have shorter TCRβ sequences, broader repertoire diversity, and more repertoire sharing than those from healthy individuals.

Identification of unique neoantigen qualities in long-term survivors of pancreatic cancer

Pancreatic ductal adenocarcinoma is a lethal cancer with fewer than 7% of patients surviving past 5 years. T-cell immunity has been linked to the exceptional outcome of the few long-term survivors, yet the relevant antigens remain unknown. Here we use genetic, immunohistochemical and transcriptional immunoprofiling, computational biophysics, and functional assays to identify T-cell antigens in long-term survivors of pancreatic cancer. Using whole-exome sequencing and in silico neoantigen prediction, we found that tumours with both the highest neoantigen number and the most abundant CD8+ T-cell infiltrates, but neither alone, stratified patients with the longest survival. Investigating the specific neoantigen qualities promoting T-cell activation in long-term survivors, we discovered that these individuals were enriched in neoantigen qualities defined by a fitness model, and neoantigens in the tumour antigen MUC16 (also known as CA125). A neoantigen quality fitness model conferring greater immunogenicity to neoantigens with differential presentation and homology to infectious disease-derived peptides identified long-term survivors in two independent datasets, whereas a neoantigen quantity model ascribing greater immunogenicity to increasing neoantigen number alone did not. We detected intratumoural and lasting circulating T-cell reactivity to both high-quality and MUC16 neoantigens in long-term survivors of pancreatic cancer, including clones with specificity to both high-quality neoantigens and predicted cross-reactive microbial epitopes, consistent with neoantigen molecular mimicry. Notably, we observed selective loss of high-quality and MUC16 neoantigenic clones on metastatic progression, suggesting neoantigen immunoediting. Our results identify neoantigens with unique qualities as T-cell targets in pancreatic ductal adenocarcinoma. More broadly, we identify neoantigen quality as a biomarker for immunogenic tumours that may guide the application of immunotherapies.

Quantification of Inter-Sample Differences in T-Cell Receptor Repertoires Using Sequence-Based Information

Inter-sample comparisons of T-cell receptor (TCR) repertoires are crucial for gaining a better understanding of the immunological states determined by different collections of T cells from different donor sites, cell types, and genetic and pathological backgrounds. For quantitative comparison, most previous studies utilized conventional methods in ecology, which focus on TCR sequences that overlap between pairwise samples. Some recent studies attempted another approach that is categorized into Poisson abundance models using the abundance distribution of observed TCR sequences. However, these methods ignore the details of the measured sequences and are consequently unable to identify sub-repertoires that might have important contributions to the observed inter-sample differences. Moreover, the sparsity of sequence data due to the huge diversity of repertoires hampers the performance of these methods, especially when few overlapping sequences exist. In this paper, we propose a new approach for REpertoire COmparison in Low Dimensions (RECOLD) based on TCR sequence information, which can estimate the low-dimensional structure by embedding the pairwise sequence dissimilarities in high-dimensional sequence space. The inter-sample differences between repertoires are then quantified by information-theoretic measures among the distributions of data estimated in the embedded space. Using datasets of mouse and human TCR repertoires, we demonstrate that RECOLD can accurately identify the inter-sample hierarchical structures, which have a good correspondence with our intuitive understanding about sample conditions. Moreover, for the dataset of transgenic mice that have strong restrictions on the diversity of their repertoires, our estimated inter-sample structure was consistent with the structure estimated by previous methods based on abundance or overlapping sequence information. For the dataset of human healthy donors and Sézary syndrome patients, our method also showed robust estimation performance even under the condition of high sparsity in TCR sequences, while previous studies failed to estimate the structure. In addition, we identified the sequences that contribute to the pairwise-sample differences between the repertoires with the different genetic backgrounds of mice. Such identification of the sequences contributing to variation in immune cell repertoires may provide substantial insight for the development of new immunotherapies and vaccines.

Interpreting T-Cell Cross-reactivity through Structure: Implications for TCR-Based Cancer Immunotherapy

Immunotherapy has become one of the most promising avenues for cancer treatment, making use of the patient’s own immune system to eliminate cancer cells. Clinical trials with T-cell-based immunotherapies have shown dramatic tumor regressions, being effective in multiple cancer types and for many different patients. Unfortunately, this progress was tempered by reports of serious (even fatal) side effects. Such therapies rely on the use of cytotoxic T-cell lymphocytes, an essential part of the adaptive immune system. Cytotoxic T-cells are regularly involved in surveillance and are capable of both eliminating diseased cells and generating protective immunological memory. The specificity of a given T-cell is determined through the structural interaction between the T-cell receptor (TCR) and a peptide-loaded major histocompatibility complex (MHC); i.e., an intracellular peptide–ligand displayed at the cell surface by an MHC molecule. However, a given TCR can recognize different peptide–MHC (pMHC) complexes, which can sometimes trigger an unwanted response that is referred to as T-cell cross-reactivity. This has become a major safety issue in TCR-based immunotherapies, following reports of melanoma-specific T-cells causing cytotoxic damage to healthy tissues (e.g., heart and nervous system). T-cell cross-reactivity has been extensively studied in the context of viral immunology and tissue transplantation. Growing evidence suggests that it is largely driven by structural similarities of seemingly unrelated pMHC complexes. Here, we review recent reports about the existence of pMHC “hot-spots” for cross-reactivity and propose the existence of a TCR interaction profile (i.e., a refinement of a more general TCR footprint in which some amino acid residues are more important than others in triggering T-cell cross-reactivity). We also make use of available structural data and pMHC models to interpret previously reported cross-reactivity patterns among virus-derived peptides. Our study provides further evidence that structural analyses of pMHC complexes can be used to assess the intrinsic likelihood of cross-reactivity among peptide-targets. Furthermore, we hypothesize that some apparent inconsistencies in reported cross-reactivities, such as a preferential directionality, might also be driven by particular structural features of the targeted pMHC complex. Finally, we explain why TCR-based immunotherapy provides a special context in which meaningful T-cell cross-reactivity predictions can be made.

An evolutionary perspective on the systems of adaptive immunity

We propose an evolutionary perspective to classify and characterize the diverse systems of adaptive immunity that have been discovered across all major domains of life. We put forward a new function-based classification according to the way information is acquired by the immune systems: Darwinian immunity (currently known from, but not necessarily limited to, vertebrates) relies on the Darwinian process of clonal selection to 'learn' by cumulative trial-and-error feedback; Lamarckian immunity uses templated targeting (guided adaptation) to internalize heritable information on potential threats; finally, shotgun immunity operates through somatic mechanisms of variable targeting without feedback. We argue that the origin of Darwinian (but not Lamarckian or shotgun) immunity represents a radical innovation in the evolution of individuality and complexity, and propose to add it to the list of major evolutionary transitions. While transitions to higher-level units entail the suppression of selection at lower levels, Darwinian immunity re-opens cell-level selection within the multicellular organism, under the control of mechanisms that direct, rather than suppress, cell-level evolution for the benefit of the individual. From a conceptual point of view, the origin of Darwinian immunity can be regarded as the most radical transition in the history of life, in which evolution by natural selection has literally re-invented itself. Furthermore, the combination of clonal selection and somatic receptor diversity enabled a transition from limited to practically unlimited capacity to store information about the antigenic environment. The origin of Darwinian immunity therefore comprises both a transition in individuality and the emergence of a new information system - the two hallmarks of major evolutionary transitions. Finally, we present an evolutionary scenario for the origin of Darwinian immunity in vertebrates. We propose a revival of the concept of the 'Big Bang' of vertebrate immunity, arguing that its origin involved a 'difficult' (i.e. low-probability) evolutionary transition that might have occurred only once, in a common ancestor of all vertebrates. In contrast to the original concept, we argue that the limiting innovation was not the generation of somatic diversity, but the regulatory circuitry needed for the safe operation of amplifiable immune responses with somatically acquired targeting. Regulatory complexity increased abruptly by genomic duplications at the root of the vertebrate lineage, creating a rare opportunity to establish such circuitry. We discuss the selection forces that might have acted at the origin of the transition, and in the subsequent stepwise evolution leading to the modern immune systems of extant vertebrates.

T cell receptor repertoires of mice and humans are clustered in similarity networks around conserved public CDR3 sequences

Diversity of T cell receptor (TCR) repertoires, generated by somatic DNA rearrangements, is central to immune system function. However, the level of sequence similarity of TCR repertoires within and between species has not been characterized. Using network analysis of high-throughput TCR sequencing data, we found that abundant CDR3-TCRβ sequences were clustered within networks generated by sequence similarity. We discovered a substantial number of public CDR3-TCRβ segments that were identical in mice and humans. These conserved public sequences were central within TCR sequence-similarity networks. Annotated TCR sequences, previously associated with self-specificities such as autoimmunity and cancer, were linked to network clusters. Mechanistically, CDR3 networks were promoted by MHC-mediated selection, and were reduced following immunization, immune checkpoint blockade or aging. Our findings provide a new view of T cell repertoire organization and physiology, and suggest that the immune system distributes its TCR sequences unevenly, attending to specific foci of reactivity.

DOI:http://dx.doi.org/10.7554/eLife.22057.001

Persisting fetal clonotypes influence the structure and overlap of adult human T cell receptor repertoires

The diversity of T-cell receptors recognizing foreign pathogens is generated through a highly stochastic recombination process, making the independent production of the same sequence rare. Yet unrelated individuals do share receptors, which together constitute a "public" repertoire of abundant clonotypes. The TCR repertoire is initially formed prenatally, when the enzyme inserting random nucleotides is downregulated, producing a limited diversity subset. By statistically analyzing deep sequencing T-cell repertoire data from twins, unrelated individuals of various ages, and cord blood, we show that T-cell clones generated before birth persist and maintain high abundances in adult organisms for decades, slowly decaying with age. Our results suggest that large, low-diversity public clones are created during pre-natal life, and survive over long periods, providing the basis of the public repertoire.

Converging evolution leads to near maximal junction diversity through parallel mechanisms in B and T cell receptors

T and B cell receptor (TCR and BCR) complementarity determining region 3 (CDR3) genetic diversity is produced through multiple diversification and selection stages. Potential holes in the CDR3 repertoire were argued to be linked to immunodeficiencies and diseases. In contrast with BCRs, TCRs have practically no Dβ germline genetic diversity, and the question emerges as to whether they can produce a diverse CDR3 repertoire. In order to address the genetic diversity of the adaptive immune system, appropriate quantitative measures for diversity and large-scale sequencing are required. Such a diversity method should incorporate the complex diversification mechanisms of the adaptive immune response and the BCR and TCR loci structure. We combined large-scale sequencing and diversity measures to show that TCRs have a near maximal CDR3 genetic diversity. Specifically, TCR have a larger junctional and V germline diversity, which starts more 5' in Vβ than BCRs. Selection decreases the TCR repertoire diversity, but does not affect BCR repertoire. As a result, TCR is as diverse as BCR repertoire, with a biased CDR3 length toward short TCRs and long BCRs. These differences suggest parallel converging evolutionary tracks to reach the required diversity to avoid holes in the CDR3 repertoire.

Specificity, Privacy, and Degeneracy in the CD4 T Cell Receptor Repertoire Following Immunization

T cells recognize antigen using a large and diverse set of antigen-specific receptors created by a complex process of imprecise somatic cell gene rearrangements. In response to antigen-/receptor-binding-specific T cells then divide to form memory and effector populations. We apply high-throughput sequencing to investigate the global changes in T cell receptor sequences following immunization with ovalbumin (OVA) and adjuvant, to understand how adaptive immunity achieves specificity. Each immunized mouse contained a predominantly private but related set of expanded CDR3β sequences. We used machine learning to identify common patterns which distinguished repertoires from mice immunized with adjuvant with and without OVA. The CDR3β sequences were deconstructed into sets of overlapping contiguous amino acid triplets. The frequencies of these motifs were used to train the linear programming boosting (LPBoost) algorithm LPBoost to classify between TCR repertoires. LPBoost could distinguish between the two classes of repertoire with accuracies above 80%, using a small subset of triplet sequences present at defined positions along the CDR3. The results suggest a model in which such motifs confer degenerate antigen specificity in the context of a highly diverse and largely private set of T cell receptors.

Insights into immune system development and function from mouse T-cell repertoires

The ability of the adaptive immune system to respond to arbitrary pathogens stems from the broad diversity of immune cell surface receptors. This diversity originates in a stochastic DNA editing process (VDJ recombination) that acts on the surface receptor gene each time a new immune cell is created from a stem cell. By analyzing T-cell receptor (TCR) sequence repertoires taken from the blood and thymus of mice of different ages, we quantify the changes in the VDJ recombination process that occur from embryo to young adult. We find a rapid increase with age in the number of random insertions and a dramatic increase in diversity. Because the blood accumulates thymic output over time, blood repertoires are mixtures of different statistical recombination processes, and we unravel the mixture statistics to obtain a picture of the time evolution of the early immune system. Sequence repertoire analysis also allows us to detect the statistical impact of selection on the output of the VDJ recombination process. The effects we find are nearly identical between thymus and blood, suggesting that our analysis mainly detects selection for proper folding of the TCR receptor protein. We further find that selection is weaker in laboratory mice than in humans and it does not affect the diversity of the repertoire.

A Perspective on the Role of Computational Models in Immunology

This is an exciting time for immunology because the future promises to be replete with exciting new discoveries that can be translated to improve health and treat disease in novel ways. Immunologists are attempting to answer increasingly complex questions concerning phenomena that range from the genetic, molecular, and cellular scales to that of organs, whole animals or humans, and populations of humans and pathogens. An important goal is to understand how the many different components involved interact with each other within and across these scales for immune responses to emerge, and how aberrant regulation of these processes causes disease. To aid this quest, large amounts of data can be collected using high-throughput instrumentation. The nonlinear, cooperative, and stochastic character of the interactions between components of the immune system as well as the overwhelming amounts of data can make it difficult to intuit patterns in the data or a mechanistic understanding of the phenomena being studied. Computational models are increasingly important in confronting and overcoming these challenges. I first describe an iterative paradigm of research that integrates laboratory experiments, clinical data, computational inference, and mechanistic computational models. I then illustrate this paradigm with a few examples from the recent literature that make vivid the power of bringing together diverse types of computational models with experimental and clinical studies to fruitfully interrogate the immune system.

BRILIA: Integrated Tool for High-Throughput Annotation and Lineage Tree Assembly of B-Cell Repertoires

The somatic diversity of antigen-recognizing B-cell receptors (BCRs) arises from Variable (V), Diversity (D), and Joining (J) (VDJ) recombination and somatic hypermutation (SHM) during B-cell development and affinity maturation. The VDJ junction of the BCR heavy chain forms the highly variable complementarity determining region 3 (CDR3), which plays a critical role in antigen specificity and binding affinity. Tracking the selection and mutation of the CDR3 can be useful in characterizing humoral responses to infection and vaccination. Although tens to hundreds of thousands of unique BCR genes within an expressed B-cell repertoire can now be resolved with high-throughput sequencing, tracking SHMs is still challenging because existing annotation methods are often limited by poor annotation coverage, inconsistent SHM identification across the VDJ junction, or lack of B-cell lineage data. Here, we present B-cell repertoire inductive lineage and immunosequence annotator (BRILIA), an algorithm that leverages repertoire-wide sequencing data to globally improve the VDJ annotation coverage, lineage tree assembly, and SHM identification. On benchmark tests against simulated human and mouse BCR repertoires, BRILIA correctly annotated germline and clonally expanded sequences with 94 and 70% accuracy, respectively, and it has a 90% SHM-positive prediction rate in the CDR3 of heavily mutated sequences; these are substantial improvements over existing methods. We used BRILIA to process BCR sequences obtained from splenic germinal center B cells extracted from C57BL/6 mice. BRILIA returned robust B-cell lineage trees and yielded SHM patterns that are consistent across the VDJ junction and agree with known biological mechanisms of SHM. By contrast, existing BCR annotation tools, which do not account for repertoire-wide clonal relationships, systematically underestimated both the size of clonally related B-cell clusters and yielded inconsistent SHM frequencies. We demonstrate BRILIA’s utility in B-cell repertoire studies related to VDJ gene usage, mechanisms for adenosine mutations, and SHM hot spot motifs. Furthermore, we show that the complete gene usage annotation and SHM identification across the entire CDR3 are essential for studying the B-cell affinity maturation process through immunosequencing methods.

Measuring the sequence-affinity landscape of antibodies with massively parallel titration curves

Despite the central role that antibodies play in the adaptive immune system and in biotechnology, much remains unknown about the quantitative relationship between an antibody’s amino acid sequence and its antigen binding affinity. Here we describe a new experimental approach, called Tite-Seq, that is capable of measuring binding titration curves and corresponding affinities for thousands of variant antibodies in parallel. The measurement of titration curves eliminates the confounding effects of antibody expression and stability that arise in standard deep mutational scanning assays. We demonstrate Tite-Seq on the CDR1H and CDR3H regions of a well-studied scFv antibody. Our data shed light on the structural basis for antigen binding affinity and suggests a role for secondary CDR loops in establishing antibody stability. Tite-Seq fills a large gap in the ability to measure critical aspects of the adaptive immune system, and can be readily used for studying sequence-affinity landscapes in other protein systems.

DOI:http://dx.doi.org/10.7554/eLife.23156.001

Antibodies are proteins produced by cells of the immune system to tag or neutralize potential threats to the body, such as foreign substances and disease-causing microbes. Antibodies do this by binding to target molecules called antigens. An antibody’s ability to bind to an antigen depends on the sequence of amino acids – the building blocks of proteins – that make up the antibody. Through a process that randomizes this sequence of amino acids, the immune system generates a vast pool of antibodies that are able to target almost any foreign antigen that exists in nature.

Currently, little is understood about how the sequence of amino acids in an antibody determines how strongly that antibody binds to its antigen target – a property referred to as the antibody’s binding affinity. Answering this fundamental question requires techniques that can measure the affinities of many different antibodies at the same time. However, previous high-throughput methods have been unable to provide quantitative measurements of binding affinities. These kinds of measurements are difficult because an antibody’s amino acid sequence governs more than just binding affinity: it also affects how easy it is to produce that antibody, and what fraction of antibody molecules work properly.

Adams et al. now describe a new method, named “Tite-Seq”, that overcomes these issues. First, thousands of different antibodies are displayed on the surface of yeast cells, with each cell carrying a single kind of antibody. These cells are then incubated with fluorescently labeled antigen at a wide range of different concentrations. Next, the yeast cells are sorted based on how brightly they glow; brighter cells have more antigen bound to them, and so it is possible to calculate how much of the antigen is bound to each kind of antibody at each concentration. Plotting these data provides a “binding curve” for each antibody, which is then used to read off the antibody’s binding affinity in a way that is not affected by the factors that have plagued other high-throughput methods.

Tite-Seq is thus able to measure the binding affinities for thousands of different antibodies at the same time. This will potentially allow researchers to address many fundamental and yet unanswered questions about how the immune system works. Tite-Seq can also be used to measure how amino acid sequence affects the binding affinity of proteins other than antibodies.

DOI:http://dx.doi.org/10.7554/eLife.23156.002

A Public Database of Memory and Naive B-Cell Receptor Sequences

The vast diversity of B-cell receptors (BCR) and secreted antibodies enables the recognition of, and response to, a wide range of epitopes, but this diversity has also limited our understanding of humoral immunity. We present a public database of more than 37 million unique BCR sequences from three healthy adult donors that is many fold deeper than any existing resource, together with a set of online tools designed to facilitate the visualization and analysis of the annotated data. We estimate the clonal diversity of the naive and memory B-cell repertoires of healthy individuals, and provide a set of examples that illustrate the utility of the database, including several views of the basic properties of immunoglobulin heavy chain sequences, such as rearrangement length, subunit usage, and somatic hypermutation positions and dynamics.

Structural Basis for a New Templated Activity by Terminal Deoxynucleotidyl Transferase: Implications for V(D)J Recombination

Eukaryotic DNA polymerase of the polX family, such as pol μ and terminal deoxynucleotidyl transferase (TdT), are key components of the non-homologous end-joining or V(D)J recombination machinery, respectively. The established role of TdT is to add random nucleotides during V(D)J recombination. Here we show that TdT also has a templated-polymerase activity, similar to pol μ, in the presence of higher concentrations of a downstream DNA duplex, and performs a micro-homology single base-pair search to align the DNA synapsis. To understand the molecular basis of this alignment, we solve crystal structures of TdT with four DNA strands and study the influence of the 3' protruding end. Two mutations in TdT inspired by sequence alignments with pol μ further improve the templated activity. We propose that both templated and untemplated activities of TdT are needed to explain the distributions of lengths of N regions observed experimentally in T cell receptors and antibodies.

Diversity and divergence of the glioma-infiltrating T-cell receptor repertoire

Although immune signaling has emerged as a defining feature of the glioma microenvironment, how the underlying structure of the glioma-infiltrating T-cell population differs from that of the blood from which it originates has been difficult to measure directly in patients. High-throughput sequencing of T-cell receptor (TCR) repertoires (TCRseq) provides a population-wide statistical description of how T cells respond to disease. We have defined immunophenotypes of whole repertoires based on TCRseq of the α- and β-chains from glioma tissue, nonneoplastic brain tissue, and peripheral blood from patients. Using information theory, we partitioned the diversity of these TCR repertoires into that from the distribution of VJ cassette combinations and diversity due to VJ-independent factors, such as selection due to antigen binding. Tumor-infiltrating lymphocytes (TILs) possessed higher VJ-independent diversity than nonneoplastic tissue, stratifying patients according to tumor grade. We found that the VJ-independent components of tumor-associated repertoires diverge more from their corresponding peripheral repertoires than T-cell populations in nonneoplastic brain tissue, particularly for low-grade gliomas. Finally, we identified a "signature" set of TCRs whose use in peripheral blood is associated with patients exhibiting low TIL divergence and is depleted in patients with highly divergent TIL repertoires. This signature is detectable in peripheral blood, and therefore accessible noninvasively. We anticipate that these immunophenotypes will be foundational to monitoring and predicting response to antiglioma vaccines and immunotherapy.

Dynamics of Individual T Cell Repertoires: From Cord Blood to Centenarians

The diversity, architecture, and dynamics of the TCR repertoire largely determine our ability to effectively withstand infections and malignancies with minimal mistargeting of immune responses. In this study, we have employed deep TCRβ repertoire sequencing with normalization based on unique molecular identifiers to explore the long-term dynamics of T cell immunity. We demonstrate remarkable stability of repertoire, where approximately half of all T cells in peripheral blood are represented by clones that persist and generally preserve their frequencies for 3 y. We further characterize the extremes of lifelong TCR repertoire evolution, analyzing samples ranging from umbilical cord blood to centenarian peripheral blood. We show that the fetal TCR repertoire, albeit structurally maintained within regulated borders due to the lower numbers of randomly added nucleotides, is not limited with respect to observed functional diversity. We reveal decreased efficiency of nonsense-mediated mRNA decay in umbilical cord blood, which may reflect specific regulatory mechanisms in development. Furthermore, we demonstrate that human TCR repertoires are functionally more similar at birth but diverge during life, and we track the lifelong behavior of CMV- and EBV-specific T cell clonotypes. Finally, we reveal gender differences in dynamics of TCR diversity constriction, which come to naught in the oldest age. Based on our data, we propose a more general explanation for the previous observations on the relationships between longevity and immunity.

Inferring processes underlying B-cell repertoire diversity

We quantify the VDJ recombination and somatic hypermutation processes in human B cells using probabilistic inference methods on high-throughput DNA sequence repertoires of human B-cell receptor heavy chains. Our analysis captures the statistical properties of the naive repertoire, first after its initial generation via VDJ recombination and then after selection for functionality. We also infer statistical properties of the somatic hypermutation machinery (exclusive of subsequent effects of selection). Our main results are the following: the B-cell repertoire is substantially more diverse than T-cell repertoires, owing to longer junctional insertions; sequences that pass initial selection are distinguished by having a higher probability of being generated in a VDJ recombination event; somatic hypermutations have a non-uniform distribution along the V gene that is well explained by an independent site model for the sequence context around the hypermutation site.

Mathematics in modern immunology

Mathematical and statistical methods enable multidisciplinary approaches that catalyse discovery. Together with experimental methods, they identify key hypotheses, define measurable observables and reconcile disparate results. We collect a representative sample of studies in T-cell biology that illustrate the benefits of modelling–experimental collaborations and that have proven valuable or even groundbreaking. We conclude that it is possible to find excellent examples of synergy between mathematical modelling and experiment in immunology, which have brought significant insight that would not be available without these collaborations, but that much remains to be discovered.

Maximum-Entropy Models of Sequenced Immune Repertoires Predict Antigen-Antibody Affinity

The immune system has developed a number of distinct complex mechanisms to shape and control the antibody repertoire. One of these mechanisms, the affinity maturation process, works in an evolutionary-like fashion: after binding to a foreign molecule, the antibody-producing B-cells exhibit a high-frequency mutation rate in the genome region that codes for the antibody active site. Eventually, cells that produce antibodies with higher affinity for their cognate antigen are selected and clonally expanded. Here, we propose a new statistical approach based on maximum entropy modeling in which a scoring function related to the binding affinity of antibodies against a specific antigen is inferred from a sample of sequences of the immune repertoire of an individual. We use our inference strategy to infer a statistical model on a data set obtained by sequencing a fairly large portion of the immune repertoire of an HIV-1 infected patient. The Pearson correlation coefficient between our scoring function and the IC50 neutralization titer measured on 30 different antibodies of known sequence is as high as 0.77 (p-value 10-6), outperforming other sequence- and structure-based models.

Individual heritable differences result in unique cell lymphocyte receptor repertoires of naïve and antigen-experienced cells

The adaptive immune system's capability to protect the body requires a highly diverse lymphocyte antigen receptor repertoire. However, the influence of individual genetic and epigenetic differences on these repertoires is not typically measured. By leveraging the unique characteristics of B, CD4⁺ T and CD8⁺ T-lymphocyte subsets from monozygotic twins, we quantify the impact of heritable factors on both the V(D)J recombination process and on thymic selection. We show that the resulting biases in both V(D)J usage and N/P addition lengths, which are found in naïve and antigen experienced cells, contribute to significant variation in the CDR3 region. Moreover, we show that the relative usage of V and J gene segments is chromosomally biased, with ∼1.5 times as many rearrangements originating from a single chromosome. These data refine our understanding of the heritable mechanisms affecting the repertoire, and show that biases are evident on a chromosome-wide level.

The diversity of antigen receptor specificities is largely generated by random recombination of its segments. Here the authors show, by genetic comparison of monozygotic twin lymphocyte subsets, that individual genetic and epigenetic biases also contribute to the shape of the B and T cell repertoires.

Dynamic Perturbations of the T-Cell Receptor Repertoire in Chronic HIV Infection and following Antiretroviral Therapy

HIV infection profoundly affects many parameters of the immune system and ultimately leads to AIDS, yet which factors are most important for determining resistance, pathology, and response to antiretroviral treatment – and how best to monitor them – remain unclear. We develop a quantitative high-throughput sequencing pipeline to characterize the TCR repertoires of HIV-infected individuals before and after antiretroviral therapy, working from small, unfractionated samples of peripheral blood. This reveals the TCR repertoires of HIV⁺ individuals to be highly perturbed, with considerably reduced diversity as a small proportion of sequences are highly overrepresented. HIV also causes specific qualitative changes to the repertoire including an altered distribution of V gene usage, depletion of public TCR sequences, and disruption of TCR networks. Short-term antiretroviral therapy has little impact on most of the global damage to repertoire structure, but is accompanied by rapid changes in the abundance of many individual TCR sequences, decreases in abundance of the most common sequences, and decreases in the majority of HIV-associated CDR3 sequences. Thus, high-throughput repertoire sequencing of small blood samples that are easy to take, store, and process can shed light on various aspects of the T-cell immune compartment and stands to offer insights into patient stratification and immune reconstitution.

How many TCR clonotypes does a body maintain?

We consider the lifetime of a T cell clonotype, the set of T cells with the same T cell receptor, from its thymic origin to its extinction in a multiclonal repertoire. Using published estimates of total cell numbers and thymic production rates, we calculate the mean number of cells per TCR clonotype, and the total number of clonotypes, in mice and humans. When there is little peripheral division, as in a mouse, the number of cells per clonotype is small and governed by the number of cells with identical TCR that exit the thymus. In humans, peripheral division is important and a clonotype may survive for decades, during which it expands to comprise many cells. We therefore devise and analyse a computational model of homeostasis of a multiclonal population. Each T cell in the model competes for self pMHC stimuli, cells of any one clonotype only recognising a small fraction of the many subsets of stimuli. A constant mean total number of cells is maintained by a balance between cell division and death, and a stable number of clonotypes by a balance between thymic production of new clonotypes and extinction of existing ones. The number of distinct clonotypes in a human body may be smaller than the total number of naive T cells by only one order of magnitude.

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The number of T cells of one clonotype is an integer.

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The history of a clonotype starts with release from the thymus, and ends with extinction.

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Competition and cross-reactivity are included in a natural way.

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The average number of cells per clonotype, in a human body, is only of order 10.

A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status

BACKGROUND

Lymphocyte receptor repertoires are continually shaped throughout the lifetime of an individual in response to environmental and pathogenic exposure. Thus, they may serve as a fingerprint of an individual's ongoing immunological status (e.g., healthy, infected, vaccinated), with far-reaching implications for immunodiagnostics applications. The advent of high-throughput immune repertoire sequencing now enables the interrogation of immune repertoire diversity in an unprecedented and quantitative manner. However, steadily increasing sequencing depth has revealed that immune repertoires vary greatly among individuals in their composition; correspondingly, it has been reported that there are few shared sequences indicative of immunological status ('public clones'). Disconcertingly, this means that the wealth of information gained from repertoire sequencing remains largely unused for determining the current status of immune responses, thereby hampering the implementation of immune-repertoire-based diagnostics.

METHODS

Here, we introduce a bioinformatics repertoire-profiling framework that possesses the advantage of capturing the diversity and distribution of entire immune repertoires, as opposed to singular public clones. The framework relies on Hill-based diversity profiles composed of a continuum of single diversity indices, which enable the quantification of the extent of immunological information contained in immune repertoires.

RESULTS

We coupled diversity profiles with unsupervised (hierarchical clustering) and supervised (support vector machine and feature selection) machine learning approaches in order to correlate patients' immunological statuses with their B- and T-cell repertoire data. We could predict with high accuracy (greater than or equal to 80 %) a wide range of immunological statuses such as healthy, transplantation recipient, and lymphoid cancer, suggesting as a proof of principle that diversity profiling can recover a large amount of immunodiagnostic fingerprints from immune repertoire data. Our framework is highly scalable as it easily allowed for the analysis of 1000 simulated immune repertoires; this exceeds the size of published immune repertoire datasets by one to two orders of magnitude.

CONCLUSIONS

Our framework offers the possibility to advance immune-repertoire-based fingerprinting, which may in the future enable a systems immunogenomics approach for vaccine profiling and the accurate and early detection of disease and infection.