How the thymus designs antigen-specific and self-tolerant T cell receptor sequences

Structure-based prediction of T cell receptor recognition of unseen epitopes using TCRen

T cell receptor (TCR) recognition of foreign peptides presented by major histocompatibility complex protein is a major event in triggering the adaptive immune response to pathogens or cancer. The prediction of TCR-peptide interactions has great importance for therapy of cancer as well as infectious and autoimmune diseases but remains a major challenge, particularly for novel (unseen) peptide epitopes. Here we present TCRen, a structure-based method for ranking candidate unseen epitopes for a given TCR. The first stage of the TCRen pipeline is modeling of the TCR-peptide-major histocompatibility complex structure. Then a TCR-peptide residue contact map is extracted from this structure and used to rank all candidate epitopes on the basis of an interaction score with the target TCR. Scoring is performed using an energy potential derived from the statistics of TCR-peptide contact preferences in existing crystal structures. We show that TCRen has high performance in discriminating cognate versus unrelated peptides and can facilitate the identification of cancer neoepitopes recognized by tumor-infiltrating lymphocytes.

The role of promiscuous molecular recognition in the evolution of RNase-based self-incompatibility in plants

How do biological networks evolve and expand? We study these questions in the context of the plant collaborative-non-self recognition self-incompatibility system. Self-incompatibility evolved to avoid self-fertilization among hermaphroditic plants. It relies on specific molecular recognition between highly diverse proteins of two families: female and male determinants, such that the combination of genes an individual possesses determines its mating partners. Though highly polymorphic, previous models struggled to pinpoint the evolutionary trajectories by which new specificities evolved. Here, we construct a novel theoretical framework, that crucially affords interaction promiscuity and multiple distinct partners per protein, as is seen in empirical findings disregarded by previous models. We demonstrate spontaneous self-organization of the population into distinct "classes" with full between-class compatibility and a dynamic long-term balance between class emergence and decay. Our work highlights the importance of molecular recognition promiscuity to network evolvability. Promiscuity was found in additional systems suggesting that our framework could be more broadly applicable.

RACER-m leverages structural features for sparse T cell specificity prediction

Reliable prediction of T cell specificity against antigenic signatures is a formidable task, complicated by the immense diversity of T cell receptor and antigen sequence space and the resulting limited availability of training sets for inferential models. Recent modeling efforts have demonstrated the advantage of incorporating structural information to overcome the need for extensive training sequence data, yet disentangling the heterogeneous TCR-antigen interface to accurately predict MHC-allele-restricted TCR-peptide interactions has remained challenging. Here, we present RACER-m, a coarse-grained structural model leveraging key biophysical information from the diversity of publicly available TCR-antigen crystal structures. Explicit inclusion of structural content substantially reduces the required number of training examples and maintains reliable predictions of TCR-recognition specificity and sensitivity across diverse biological contexts. Our model capably identifies biophysically meaningful point-mutant peptides that affect binding affinity, distinguishing its ability in predicting TCR specificity of point-mutants from alternative sequence-based methods. Its application is broadly applicable to studies involving both closely related and structurally diverse TCR-peptide pairs.

Is the exquisite specificity of lymphocytes generated by thymic selection or due to evolution?

We have previously argued that the antigen receptors of T and B lymphocytes evolved to be sufficiently specific to avoid massive deletion of clonotypes by negative selection. Their optimal 'specificity' level, i.e., probability of binding any particular epitope, was shown to be inversely related to the number of self-antigens that the cells have to be tolerant to. Experiments have demonstrated that T lymphocytes also become more specific during negative selection in the thymus, because cells expressing the most crossreactive receptors have the highest likelihood of binding a self-antigen, and hence to be tolerized (i.e., deleted, anergized, or diverted into a regulatory T cell phenotype). Thus, there are two -not mutually exclusive- explanations for the exquisite specificity of T cells, one involving evolution and the other thymic selection. To better understand the impact of both, we extend a previously developed mathematical model by allowing for T cells with very different binding probabilities in the pre-selection repertoire. We confirm that negative selection tends to tolerize the most crossreactive clonotypes. As a result, the average level of specificity in the functional post-selection repertoire depends on the number of self-antigens, even if there is no evolutionary optimization of binding probabilities. However, the evolutionary optimal range of binding probabilities in the pre-selection repertoire also depends on the number of self-antigens. Species with more self antigens need more specific pre-selection repertoires to avoid excessive loss of T cells during thymic selection, and hence mount protective immune responses. We conclude that both evolution and negative selection are responsible for the high level of specificity of lymphocytes.

How persistent infection overcomes peripheral tolerance mechanisms to cause T cell-mediated autoimmune disease

T cells help orchestrate immune responses to pathogens, and their aberrant regulation can trigger autoimmunity. Recent studies highlight that a threshold number of T cells (a quorum) must be activated in a tissue to mount a functional immune response. These collective effects allow the T cell repertoire to respond to pathogens while suppressing autoimmunity due to circulating autoreactive T cells. Our computational studies show that increasing numbers of pathogenic peptides targeted by T cells during persistent or severe viral infections increase the probability of activating T cells that are weakly reactive to self-antigens (molecular mimicry). These T cells are easily re-activated by the self-antigens and contribute to exceeding the quorum threshold required to mount autoimmune responses. Rare peptides that activate many T cells are sampled more readily during severe/persistent infections than in acute infections, which amplifies these effects. Experiments in mice to test predictions from these mechanistic insights are suggested.

Investigation into Cardiac Myhc-α 334-352-Specific TCR Transgenic Mice Reveals a Role for Cytotoxic CD4 T Cells in the Development of Cardiac Autoimmunity

Myocarditis is one of the major causes of heart failure in children and young adults and can lead to dilated cardiomyopathy. Lymphocytic myocarditis could result from autoreactive CD4+ and CD8+ T cells, but defining antigen specificity in disease pathogenesis is challenging. To address this issue, we generated T cell receptor (TCR) transgenic (Tg) C57BL/6J mice specific to cardiac myosin heavy chain (Myhc)-α 334-352 and found that Myhc-α-specific TCRs were expressed in both CD4+ and CD8+ T cells. To investigate if the phenotype is more pronounced in a myocarditis-susceptible genetic background, we backcrossed with A/J mice. At the fourth generation of backcrossing, we observed that Tg T cells from naïve mice responded to Myhc-α 334-352, as evaluated by proliferation assay and carboxyfluorescein succinimidyl ester staining. The T cell responses included significant production of mainly pro-inflammatory cytokines, namely interferon (IFN)-γ, interleukin-17, and granulocyte macrophage-colony stimulating factor. While the naïve Tg mice had isolated myocardial lesions, immunization with Myhc-α 334-352 led to mild myocarditis, suggesting that further backcrossing to increase the percentage of A/J genome close to 99.99% might show a more severe disease phenotype. Further investigations led us to note that CD4+ T cells displayed the phenotype of cytotoxic T cells (CTLs) akin to those of conventional CD8+ CTLs, as determined by the expression of CD107a, IFN-γ, granzyme B natural killer cell receptor (NKG)2A, NKG2D, cytotoxic and regulatory T cell molecules, and eomesodermin. Taken together, the transgenic system described in this report may be a helpful tool to distinguish the roles of cytotoxic cardiac antigen-specific CD4+ T cells vs. those of CD8+ T cells in the pathogenesis of myocarditis.

Tracking DNA-based antigen-specific T cell receptors during progression to type 1 diabetes

T cells targeting self-proteins are important mediators in autoimmune diseases. T cells express unique cell-surface receptors (TCRs) that recognize peptides presented by major histocompatibility molecules. TCRs have been identified from blood and pancreatic islets of individuals with type 1 diabetes (T1D). Here, we tracked ~1700 known antigen-specific TCR sequences, islet antigen or viral reactive, in bulk TCRβ sequencing from longitudinal blood DNA samples in at-risk cases who progressed to T1D, age/sex/human leukocyte antigen-matched controls, and a new-onset T1D cohort. Shared and frequent antigen-specific TCRβ sequences were identified in all three cohorts, and viral sequences were present across all ages. Islet sequences had different patterns of accumulation based upon antigen specificity in the at-risk cases. Furthermore, 73 islet-antigen TCRβ sequences were present in higher frequencies and numbers in T1D samples relative to controls. The total number of these disease-associated TCRβ sequences inversely correlated with age at clinical diagnosis, indicating the potential to use disease-relevant TCR sequences as biomarkers in autoimmune disorders.

Quantitative approaches for decoding the specificity of the human T cell repertoire

T cell receptor (TCR)-peptide-major histocompatibility complex (pMHC) interactions play a vital role in initiating immune responses against pathogens, and the specificity of TCRpMHC interactions is crucial for developing optimized therapeutic strategies. The advent of high-throughput immunological and structural evaluation of TCR and pMHC has provided an abundance of data for computational approaches that aim to predict favorable TCR-pMHC interactions. Current models are constructed using information on protein sequence, structures, or a combination of both, and utilize a variety of statistical learning-based approaches for identifying the rules governing specificity. This review examines the current theoretical, computational, and deep learning approaches for identifying TCR-pMHC recognition pairs, placing emphasis on each method's mathematical approach, predictive performance, and limitations.

Defining and Studying B Cell Receptor and TCR Interactions

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

Towards a quantitative theory of tolerance

A cornerstone of the classical view of tolerance is the elimination of self-reactive T cells via negative selection in the thymus. However, high-throughput T cell receptor (TCR) sequencing data have so far failed to detect substantial signatures of negative selection in the observed repertoires. In addition, quantitative estimates as well as recent experiments suggest that the elimination of self-reactive T cells is at best incomplete. We discuss several recent theoretical ideas that might explain tolerance while being consistent with these observations, including collective decision-making through quorum sensing, and sensitivity to change through dynamic tuning and adaptation. We propose that a unified quantitative theory of tolerance should combine these elements to help to explain the plasticity of the immune system and its robustness to autoimmunity.

Single-cell profiling identifies a novel human polyclonal unconventional T cell lineage

In the human thymus, a CD10+ PD-1+ TCRαβ+ differentiation pathway diverges from the conventional single positive T cell lineages at the early double-positive stage. Here, we identify the progeny of this unconventional lineage in antigen-inexperienced blood. These unconventional T cells (UTCs) in thymus and blood share a transcriptomic profile, characterized by hallmark transcription factors (i.e., ZNF683 and IKZF2), and a polyclonal TCR repertoire with autoreactive features, exhibiting a bias toward early TCRα chain rearrangements. Single-cell RNA sequencing confirms a common developmental trajectory between the thymic and blood UTCs and clearly delineates this unconventional lineage in blood. Besides MME+ recent thymic emigrants, effector-like clusters are identified in this heterogeneous lineage. Expression of Helios and KIR and a decreased CD8β expression are characteristics of this lineage. This UTC lineage could be identified in adult blood and intestinal tissues. In summary, our data provide a comprehensive characterization of the polyclonal unconventional lineage in antigen-inexperienced blood and identify the adult progeny.

Unique features of the TCR repertoire of reactivated memory T cells in the experimental mouse tumor model

T cell engineering with T cell receptors (TCR) specific to tumor antigens has become a breakthrough towards personalized cancer adoptive cell immunotherapy. However, the search for therapeutic TCRs is often challenging, and effective strategies are strongly required for the identification and enrichment of tumor-specific T cells that express TCRs with superior functional characteristics. Using an experimental mouse tumor model, we studied sequential changes in TCR repertoire features of T cells involved in the primary and secondary immune responses to allogeneic tumor antigens. In-depth bioinformatics analysis of TCR repertoires showed differences in reactivated memory T cells compared to primarily activated effectors. After cognate antigen re-encounter, memory cells were enriched with clonotypes that express α-chain TCR with high potential cross-reactivity and enhanced strength of interaction with both MHC and docked peptides. Our findings suggest that functionally true memory T cells could be a better source of therapeutic TCRs for adoptive cell therapy. No marked changes were observed in the physicochemical characteristics of TCRβ in reactivated memory clonotypes, indicative of the dominant role of TCRα in the secondary allogeneic immune response. The results of this study could further contribute to the development of TCR-modified T cell products based on the phenomenon of TCR chain centricity.

Defective peripheral B cell selection in common variable immune deficiency patients with autoimmune manifestations

Common variable immune deficiency (CVID) is a heterogeneous disorder characterized by recurrent infections, low levels of serum immunoglobulins, and impaired vaccine responses. Autoimmune manifestations are common, but B cell central and peripheral selection mechanisms in CVID are incompletely understood. Here, we find that receptor editing, a measure of central tolerance, is increased in transitional B cells from CVID patients and that these cells have a higher immunoglobulin κ:λ ratio in CVID patients with autoimmune manifestations than in those with infection only. Contrariwise, the selection pressure in the germinal center on CD27^bright memory B cells is decreased in CVID patients with autoimmune manifestations. Finally, functionally, T cell-dependent activation showed that naive B cells in CVID patients are badly equipped for activation and induction of mismatch repair genes. We conclude that central tolerance is functional whereas peripheral selection is defective in CVID patients with autoimmune manifestations, which could underpin the development of autoimmunity.

Surface patches induce nonspecific binding and phase separation of antibodies

Nonspecific interactions are a key challenge in the successful development of therapeutic antibodies. The tendency for nonspecific binding of antibodies is often difficult to reduce by rational design, and instead, it is necessary to rely on comprehensive screening campaigns. To address this issue, we performed a systematic analysis of the impact of surface patch properties on antibody nonspecificity using a designer antibody library as a model system and single-stranded DNA as a nonspecificity ligand. Using an in-solution microfluidic approach, we find that the antibodies tested bind to single-stranded DNA with affinities as high as KD = 1 µM. We show that DNA binding is driven primarily by a hydrophobic patch in the complementarity-determining regions. By quantifying the surface patches across the library, the nonspecific binding affinity is shown to correlate with a trade-off between the hydrophobic and total charged patch areas. Moreover, we show that a change in formulation conditions at low ionic strengths leads to DNA-induced antibody phase separation as a manifestation of nonspecific binding at low micromolar antibody concentrations. We highlight that phase separation is driven by a cooperative electrostatic network assembly mechanism of antibodies with DNA, which correlates with a balance between positive and negative charged patches. Importantly, our study demonstrates that both nonspecific binding and phase separation are controlled by the size of the surface patches. Taken together, these findings highlight the importance of surface patches and their role in conferring antibody nonspecificity and its macroscopic manifestation in phase separation.

Measures of epitope binding degeneracy from T cell receptor repertoires

Adaptive immunity is driven by specific binding of hypervariable receptors to diverse molecular targets. The sequence diversity of receptors and targets are both individually known but because multiple receptors can recognize the same target, a measure of the effective "functional" diversity of the human immune system has remained elusive. Here, we show that sequence near-coincidences within T cell receptors that bind specific epitopes provide a new window into this problem and allow the quantification of how binding probability covaries with sequence. We find that near-coincidence statistics within epitope-specific repertoires imply a measure of binding degeneracy to amino acid changes in receptor sequence that is consistent across disparate experiments. Paired data on both chains of the heterodimeric receptor are particularly revealing since simultaneous near-coincidences are rare and we show how they can be exploited to estimate the number of epitope responses that created the memory compartment. In addition, we find that paired-chain coincidences are strongly suppressed across donors with different human leukocyte antigens, evidence for a central role of antigen-driven selection in making paired chain receptors public. These results demonstrate the power of coincidence analysis to reveal the sequence determinants of epitope binding in receptor repertoires.

Contact map dependence of a T-cell receptor binding repertoire

The T-cell arm of the adaptive immune system provides the host protection against unknown pathogens by discriminating between host and foreign material. This discriminatory capability is achieved by the creation of a repertoire of cells each carrying a T-cell receptor (TCR) specific to non-self-antigens displayed as peptides bound to the major histocompatibility complex (pMHC). The understanding of the dynamics of the adaptive immune system at a repertoire level is complex, due to both the nuanced interaction of a TCR-pMHC pair and to the number of different possible TCR-pMHC pairings, making computationally exact solutions currently unfeasible. To gain some insight into this problem, we study an affinity-based model for TCR-pMHC binding in which a crystal structure is used to generate a distance-based contact map that weights the pairwise amino acid interactions. We find that the TCR-pMHC binding energy distribution strongly depends both on the number of contacts and the repeat structure allowed by the topology of the contact map of choice; this in turn influences T-cell recognition probability during negative selection, with higher variances leading to higher survival probabilities. In addition, we quantify the degree to which neoantigens with mutations in sites with higher contacts are recognized at a higher rate.

Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate

T cells acquire a regulatory phenotype when their T cell receptors (TCRs) experience an intermediate-to-high affinity interaction with a self-peptide presented via the major histocompatibility complex (MHC). Using TCRβ sequences from flow-sorted human cells, we identified TCR features that promote regulatory T cell (T_reg) fate. From these results, we developed a scoring system to quantify TCR-intrinsic regulatory potential (TiRP). When applied to the tumor microenvironment, TiRP scoring helped to explain why only some T cell clones maintained the T_conv phenotype through expansion. To elucidate drivers of these predictive TCR features, we then examined the two elements of the T_reg TCR ligand separately: the self-peptide, and the human MHC II molecule. These analyses revealed that hydrophobicity in the third complementarity determining region (CDR3β) of the TCR promotes reactivity to self-peptides, while TCR variable gene (TRBV gene) usage shapes the TCR’s general propensity for human MHC II-restricted activation.

Integrating T cell receptor sequences and transcriptional profiles by clonotype neighbor graph analysis (CoNGA)

Links between T cell clonotypes, as defined by T cell receptor (TCR) sequences, and phenotype, as reflected in gene expression (GEX) profiles, surface protein expression and peptide:major histocompatibility complex binding, can reveal functional relationships beyond the features shared by clonally related cells. Here we present clonotype neighbor graph analysis (CoNGA), a graph theoretic approach that identifies correlations between GEX profile and TCR sequence through statistical analysis of GEX and TCR similarity graphs. Using CoNGA, we uncovered associations between TCR sequence and GEX profiles that include a previously undescribed 'natural lymphocyte' population of human circulating CD8⁺ T cells and a set of TCR sequence determinants of differentiation in thymocytes. These examples show that CoNGA might help elucidate complex relationships between TCR sequence and T cell phenotype in large, heterogeneous, single-cell datasets.

Naïve Regulatory T Cell Subset Is Altered in X-Linked Agammaglobulinemia

The interplay between T- and B-cell compartments during naïve, effector and memory T cell maturation is critical for a balanced immune response. Primary B-cell immunodeficiency arising from X-linked agammaglobulinemia (XLA) offers a model to explore B cell impact on T cell subsets, starting from the thymic selection. Here we investigated characteristics of naïve and effector T cell subsets in XLA patients, revealing prominent alterations in the corresponding T-cell receptor (TCR) repertoires. We observed immunosenescence in terms of decreased diversity of naïve CD4⁺ and CD8⁺ TCR repertoires in XLA donors. The most substantial alterations were found within naïve CD4⁺ subsets, and we have investigated these in greater detail. In particular, increased clonality and convergence, along with shorter CDR3 regions, suggested narrower focused antigen-specific maturation of thymus-derived naïve T_reg (CD4⁺CD45RA⁺CD27⁺CD25⁺) in the absence of B cells - normally presenting diverse self and commensal antigens. The naïve T_reg proportion among naïve CD4 T cells was decreased in XLA patients, supporting the concept of impaired thymic naïve T_reg selection. Furthermore, the naïve T_reg subset showed prominent differences at the transcriptome level, including increased expression of genes specific for antigen-presenting and myeloid cells. Altogether, our findings suggest active B cell involvement in CD4 T cell subsets maturation, including B cell-dependent expansion of the naïve Treg TCR repertoire that enables better control of self-reactive T cells.

Tregs self-organize into a computing ecosystem and implement a sophisticated optimization algorithm for mediating immune response

Regulatory T cells (Tregs) play a crucial role in mediating immune response. Yet an algorithmic understanding of the role of Tregs in adaptive immunity remains lacking. Here, we present a biophysically realistic model of Treg-mediated self-tolerance in which Tregs bind to self-antigens and locally inhibit the proliferation of nearby activated T cells. By exploiting a duality between ecological dynamics and constrained optimization, we show that Tregs tile the potential antigen space while simultaneously minimizing the overlap between Treg activation profiles. We find that for sufficiently high Treg diversity, Treg-mediated self-tolerance is robust to fluctuations in self-antigen concentrations but lowering the Treg diversity results in a sharp transition-related to the Gardner transition in perceptrons-to a regime where changes in self-antigen concentrations can result in an autoimmune response. We propose an experimental test of this transition in immune-deficient mice and discuss potential implications for autoimmune diseases.

Rapid Assessment of T-Cell Receptor Specificity of the Immune Repertoire

Accurate assessment of TCR-antigen specificity at the whole immune repertoire level lies at the heart of improved cancer immunotherapy, but predictive models capable of high-throughput assessment of TCR-peptide pairs are lacking. Recent advances in deep sequencing and crystallography have enriched the data available for studying TCR-p-MHC systems. Here, we introduce a pairwise energy model, RACER, for rapid assessment of TCR-peptide affinity at the immune repertoire level. RACER applies supervised machine learning to efficiently and accurately resolve strong TCR-peptide binding pairs from weak ones. The trained parameters further enable a physical interpretation of interacting patterns encoded in each specific TCR-p-MHC system. When applied to simulate thymic selection of an MHC-restricted T-cell repertoire, RACER accurately estimates recognition rates for tumor-associated neoantigens and foreign peptides, thus demonstrating its utility in helping address the large computational challenge of reliably identifying the properties of tumor antigen-specific T-cells at the level of an individual patient's immune repertoire.

Learning from HIV-1 to predict the immunogenicity of T cell epitopes in SARS-CoV-2

We describe a physics-based learning model for predicting the immunogenicity of cytotoxic T lymphocyte (CTL) epitopes derived from diverse pathogens including SARS-CoV-2. The model was trained and optimized on the relative immunodominance of CTL epitopes in human immunodeficiency virus infection. Its accuracy was tested against experimental data from patients with COVID-19. Our model predicts that only some SARS-CoV-2 epitopes predicted to bind to HLA molecules are immunogenic. The immunogenic CTL epitopes across all SARS-CoV-2 proteins are predicted to provide broad population coverage, but those from the SARS-CoV-2 spike protein alone are unlikely to do so. Our model also predicts that several immunogenic SARS-CoV-2 CTL epitopes are identical to seasonal coronaviruses circulating in the population and such cross-reactive CD8+ T cells can indeed be detected in prepandemic blood donors, suggesting that some level of CTL immunity against COVID-19 may be present in some individuals before SARS-CoV-2 infection.

The Interplay between CD27dull and CD27bright B Cells Ensures the Flexibility, Stability, and Resilience of Human B Cell Memory

Memory B cells (MBCs) epitomize the adaptation of the immune system to the environment. We identify two MBC subsets in peripheral blood, CD27^dull and CD27^bright MBCs, whose frequency changes with age. Heavy chain variable region (VH) usage, somatic mutation frequency replacement-to-silent ratio, and CDR3 property changes, reflecting consecutive selection of highly antigen-specific, low cross-reactive antibody variants, all demonstrate that CD27^dull and CD27^bright MBCs represent sequential MBC developmental stages, and stringent antigen-driven pressure selects CD27^dull into the CD27^bright MBC pool. Dynamics of human MBCs are exploited in pregnancy, when 50% of maternal MBCs are lost and CD27^dull MBCs transit to the more differentiated CD27^bright stage. In the postpartum period, the maternal MBC pool is replenished by the expansion of persistent CD27^dull clones. Thus, the stability and flexibility of human B cell memory is ensured by CD27^dull MBCs that expand and differentiate in response to change.

Distinct organization of adaptive immunity in the long-lived rodent Spalax galili

A balanced immune response is a cornerstone of healthy aging. Here, we uncover distinctive features of the long-lived blind mole-rat (Spalax spp.) adaptive immune system, relative to humans and mice. The T-cell repertoire remains diverse throughout the Spalax lifespan, suggesting a paucity of large long-lived clones of effector-memory T cells. Expression of master transcription factors of T-cell differentiation, as well as checkpoint and cytotoxicity genes, remains low as Spalax ages. The thymus shrinks as in mice and humans, while interleukin-7 and interleukin-7 receptor expression remains high, potentially reflecting the sustained homeostasis of naive T cells. With aging, immunoglobulin hypermutation level does not increase and the immunoglobulin-M repertoire remains diverse, suggesting shorter B-cell memory and sustained homeostasis of innate-like B cells. The Spalax adaptive immune system thus appears biased towards sustained functional and receptor diversity over specialized, long-lived effector-memory clones-a unique organizational strategy that potentially underlies this animal's extraordinary longevity and healthy aging.

Implications of Tumor-Immune Coevolution on Cancer Evasion and Optimized Immunotherapy

Cancer represents a diverse collection of diseases characterized by heterogeneous cell populations that dynamically evolve in their environment. As painfully evident in cases of treatment failure and recurrence, this general feature makes identifying long-term successful therapies difficult. It is now well-established that the adaptive immune system recognizes and eliminates cancer cells, and various immunotherapeutic strategies have emerged to augment this effect. These therapies, while promising, often fail as a result of immune-specific cancer evasion. Increasingly available empirical evidence details both cancer and immune system populations pre- and post-treatment, providing rich opportunity for mathematical models of the tumor-immune interaction and subsequent co-evolution. Integrated mathematical and experimental efforts bear immediate relevance for optimized therapies and will undoubtedly accelerate our understanding of this emergent field.

Functionally specialized human CD4+ T-cell subsets express physicochemically distinct TCRs

The organizational integrity of the adaptive immune system is determined by functionally discrete subsets of CD4⁺ T cells, but it has remained unclear to what extent lineage choice is influenced by clonotypically expressed T-cell receptors (TCRs). To address this issue, we used a high-throughput approach to profile the αβ TCR repertoires of human naive and effector/memory CD4⁺ T-cell subsets, irrespective of antigen specificity. Highly conserved physicochemical and recombinatorial features were encoded on a subset-specific basis in the effector/memory compartment. Clonal tracking further identified forbidden and permitted transition pathways, mapping effector/memory subsets related by interconversion or ontogeny. Public sequences were largely confined to particular effector/memory subsets, including regulatory T cells (Tregs), which also displayed hardwired repertoire features in the naive compartment. Accordingly, these cumulative repertoire portraits establish a link between clonotype fate decisions in the complex world of CD4⁺ T cells and the intrinsic properties of somatically rearranged TCRs.

Genetic and environmental determinants of human TCR repertoire diversity

T cell discrimination of self and non-self is the foundation of the adaptive immune response, and is orchestrated by the interaction between T cell receptors (TCRs) and their cognate ligands presented by major histocompatibility (MHC) molecules. However, the impact of host immunogenetic variation on the diversity of the TCR repertoire remains unclear. Here, we analyzed a cohort of 666 individuals with TCR repertoire sequencing. We show that TCR repertoire diversity is positively associated with polymorphism at the human leukocyte antigen class I (HLA-I) loci, and diminishes with age and cytomegalovirus (CMV) infection. Moreover, our analysis revealed that HLA-I polymorphism and age independently shape the repertoire in healthy individuals. Our data elucidate key determinants of human TCR repertoire diversity, and suggest a mechanism underlying the evolutionary fitness advantage of HLA-I heterozygosity.

MHC-II alleles shape the CDR3 repertoires of conventional and regulatory naïve CD4+ T cells

T cell maturation and activation depend upon T cell receptor (TCR) interactions with a wide variety of antigenic peptides displayed in a given major histocompatibility complex (MHC) context. Complementarity-determining region 3 (CDR3) is the most variable part of the TCRα and -β chains, which govern interactions with peptide-MHC complexes. However, it remains unclear how the CDR3 landscape is shaped by individual MHC context during thymic selection of naïve T cells. We established two mouse strains carrying distinct allelic variants of H2-A and analyzed thymic and peripheral production and TCR repertoires of naïve conventional CD4⁺ T (T_conv) and naïve regulatory CD4⁺ T (T_reg) cells. Compared with tuberculosis-resistant C57BL/6 (H2-A^b) mice, the tuberculosis-susceptible H2-A^j mice had fewer CD4⁺ T cells of both subsets in the thymus. In the periphery, this deficiency was only apparent for T_conv and was compensated for by peripheral reconstitution for T_reg We show that H2-A^j favors selection of a narrower and more convergent repertoire with more hydrophobic and strongly interacting amino acid residues in the middle of CDR3α and CDR3β, suggesting more stringent selection against a narrower peptide-MHC-II context. H2-A^j and H2-A^b mice have prominent reciprocal differences in CDR3α and CDR3β features, probably reflecting distinct modes of TCR fitting to MHC-II variants. These data reveal the mechanics and extent of how MHC-II shapes the naïve CD4⁺ T cell CDR3 landscape, which essentially defines adaptive response to infections and self-antigens.

Predicting the Immunogenicity of T cell epitopes: From HIV to SARS-CoV-2

We describe a physics-based learning model for predicting the immunogenicity of Cytotoxic T Lymphocyte (CTL) epitopes derived from diverse pathogens, given a Human Leukocyte Antigen (HLA) genotype. The model was trained and tested on experimental data on the relative immunodominance of CTL epitopes in Human Immunodeficiency Virus infection. The method is more accurate than publicly available models. Our model predicts that only a fraction of SARS-CoV-2 epitopes that have been predicted to bind to HLA molecules is immunogenic. The immunogenic CTL epitopes across all SARS-CoV-2 proteins are predicted to provide broad population coverage, but the immunogenic epitopes in the SARS-CoV-2 spike protein alone are unlikely to do so. Our model predicts that several immunogenic SARS-CoV-2 CTL epitopes are identical to those contained in low-pathogenicity coronaviruses circulating in the population. Thus, we suggest that some level of CTL immunity against COVID-19 may be present in some individuals prior to SARS-CoV-2 infection.

Is T Cell Negative Selection a Learning Algorithm?

Our immune system can destroy most cells in our body, an ability that needs to be tightly controlled. To prevent autoimmunity, the thymic medulla exposes developing T cells to normal “self” peptides and prevents any responders from entering the bloodstream. However, a substantial number of self-reactive T cells nevertheless reaches the periphery, implying that T cells do not encounter all self peptides during this negative selection process. It is unclear if T cells can still discriminate foreign peptides from self peptides they haven’t encountered during negative selection. We use an “artificial immune system”—a machine learning model of the T cell repertoire—to investigate how negative selection could alter the recognition of self peptides that are absent from the thymus. Our model reveals a surprising new role for T cell cross-reactivity in this context: moderate T cell cross-reactivity should skew the post-selection repertoire towards peptides that differ systematically from self. Moreover, even some self-like foreign peptides can be distinguished provided that the peptides presented in the thymus are not too similar to each other. Thus, our model predicts that negative selection on a well-chosen subset of self peptides would generate a repertoire that tolerates even “unseen” self peptides better than foreign peptides. This effect would resemble a “generalization” process as it is found in learning systems. We discuss potential experimental approaches to test our theory.

Dissection of the Human T-Cell Receptor γ Gene Repertoire in the Brain and Peripheral Blood Identifies Age- and Alzheimer's Disease-Associated Clonotype Profiles

The immune system contributes to neurodegenerative pathologies. However, the roles of γδ T cells in Alzheimer's disease (AD) are poorly understood. Here, we evaluated somatic variability of T-cell receptor γ genes (TRGs) in patients with AD. We performed deep sequencing of the CDR3 region of TRGs in patients with AD and control patients without dementia. TRG clones were clearly detectable in peripheral blood (PB) and non-neuronal cell populations in human brains. TRG repertoire diversity was reduced during aging. Compared with the PB, the brain showed reduced TRGV9 clonotypes but was enriched in TRGV2/4/8 clonotypes. AD-associated TRG profiles were found in both the PB and brain. Moreover, some groups of clonotypes were more specific for the brain or blood in patients with AD compared to those in controls. Our pilot deep analysis of T-cell receptor diversities in AD revealed putative brain and AD-associated immunogenic markers.

CXCR3 Identifies Human Naive CD8+ T Cells with Enhanced Effector Differentiation Potential

In mice, the ability of naive T (TN) cells to mount an effector response correlates with TCR sensitivity for self-derived Ags, which can be quantified indirectly by measuring surface expression levels of CD5. Equivalent findings have not been reported previously in humans. We identified two discrete subsets of human CD8+ TN cells, defined by the absence or presence of the chemokine receptor CXCR3. The more abundant CXCR3+ TN cell subset displayed an effector-like transcriptional profile and expressed TCRs with physicochemical characteristics indicative of enhanced interactions with peptide-HLA class I Ags. Moreover, CXCR3+ TN cells frequently produced IL-2 and TNF in response to nonspecific activation directly ex vivo and differentiated readily into Ag-specific effector cells in vitro. Comparative analyses further revealed that human CXCR3+ TN cells were transcriptionally equivalent to murine CXCR3+ TN cells, which expressed high levels of CD5. These findings provide support for the notion that effector differentiation is shaped by heterogeneity in the preimmune repertoire of human CD8+ T cells.

Inherent reactivity of unselected TCR repertoires to peptide-MHC molecules

The repertoire of αβ T cell antigen receptors (TCRs) on mature T cells is selected in the thymus where it is rendered both self-tolerant and restricted to the recognition of major histocompatibility complex molecules presenting peptide antigens (pMHC). It remains unclear whether germline TCR sequences exhibit an inherent bias to interact with pMHC prior to selection. Here, we isolated TCR libraries from unselected thymocytes and upon reexpression of these random TCR repertoires in recipient T cell hybridomas, interrogated their reactivities to antigen-presenting cell lines. While these random TCR combinations could potentially have reacted with any surface molecule on the cell lines, the hybridomas were stimulated most frequently by pMHC ligands. The nature and CDR3 loop composition of the TCRβ chain played a dominant role in determining pMHC-reactivity. Replacing the germline regions of mouse TCRβ chains with those of other jawed vertebrates preserved reactivity to mouse pMHC. Finally, introducing the CD4 coreceptor into the hybridomas increased the proportion of cells that could respond to pMHC ligands. Thus, αβ TCRs display an intrinsic and evolutionary conserved bias for pMHC molecules in the absence of any selective pressure, which is further strengthened in the presence of coreceptors.

Inducible Gene Switches with Memory in Human T Cells for Cellular Immunotherapy

Cell-based therapies that employ engineered T cells—including those modified to express chimeric antigen receptors (CARs)—to target cancer cells have demonstrated promising responses in clinical trials. However, engineered T cell responses must be regulated to prevent severe side effects such as cytokine storms and off-target responses. Here we present a class of recombinase-based gene circuits that will enable inducible, one-time state switching in adoptive T cell therapy using an FDA-approved drug, creating a generalizable platform that can be used to control when and how strongly a gene is expressed. These circuits exhibit memory such that induced T cells will maintain any changes made even when the drug inducer is removed. This memory feature avoids prolonged drug inducer exposure, thus reducing the complexity and potential side effect associated with the drug inducer. We have utilized these circuits to control the expression of an anti-Her2-CAR, demonstrating the ability of these circuits to regulate CAR expression and T cell activity. We envision this platform can be extended to regulate other genes involved in T cell behavior for applications in various adoptive T cell therapies.

Broad cross-reactivity of the T-cell repertoire achieves specific and sufficiently rapid target searching

The molecular recognition of T-cell receptors is the hallmark of the adaptive immunity. Given the finiteness of the T-cell repertoire, individual T-cell receptors are necessary to be cross-reactive to multiple antigenic peptides. In this study, we quantify the variability of the cross-reactivity by using a string model that estimates the binding affinity between two sequences of amino acids. We examine sequences of 10,000 human T-cell receptors and 10,000 antigenic peptides, and obtain a full spectrum of cross-reactivity of the receptor-peptide binding. Then, we find that the cross-reactivity spectrum is broad. Some T-cells are reactive to 1000 peptides, but some T-cells are reactive to only one or two peptides. Since the degree of cross-reactivity has a correlation with the (un)binding affinity of receptors, we further investigate how the broad cross-reactivity affects the target searching of T-cells. High cross-reactive T-cells may not require many trials for searching correct targets, but they may spend long time to unbind from incorrect targets. In contrast, low cross-reactive T-cells may not spend long time to ignore incorrect targets, but they require many trials for screening correct targets. We evaluate this hypothesis, and show that the broad cross-reactivity of the natural T-cell repertoire can balance the trade-off between the rapid screening and unbinding penalty.

Specificity from nonspecific interaction: regulation of tumor necrosis factor-α activity by DNA

As anionic biopolymers, oligonucleotides can have biological functions independent from their roles as the medium for the storage and flow of genetic information. In this paper, we investigated the interaction between DNA and the pro-inflammatory cytokine tumor necrosis factor-α (TNFα). Although various forms of DNA bind to TNFα with low μm dissociation constants, the interaction stabilizes the trimeric form of TNFα and enhances its cytotoxic effect. Based on this mechanism, a photoswitchable TNFα (TNFα-2-nitroveratryloxycarbonyl) has been designed whose sensitivity to DNA-mediated up-regulation of TNFα activity can be tuned by light irradiation. The mechanism described in this study represents a general model to understand the involvement of nonspecific interactions among biomolecules in regulating their biological functions. Because the interaction is not DNA sequence-specific, the resulting effect should be considered for oligonucleotide-based therapeutics in general.

Towards multiscale modeling of the CD8+ T cell response to viral infections

The CD8⁺ T cell response is critical to the control of viral infections. Yet, defining the CD8⁺ T cell response to viral infections quantitatively has been a challenge. Following antigen recognition, which triggers an intracellular signaling cascade, CD8⁺ T cells can differentiate into effector cells, which proliferate rapidly and destroy infected cells. When the infection is cleared, they leave behind memory cells for quick recall following a second challenge. If the infection persists, the cells may become exhausted, retaining minimal control of the infection while preventing severe immunopathology. These activation, proliferation and differentiation processes as well as the mounting of the effector response are intrinsically multiscale and collective phenomena. Remarkable experimental advances in the recent years, especially at the single cell level, have enabled a quantitative characterization of several underlying processes. Simultaneously, sophisticated mathematical models have begun to be constructed that describe these multiscale phenomena, bringing us closer to a comprehensive description of the CD8⁺ T cell response to viral infections. Here, we review the advances made and summarize the challenges and opportunities ahead. This article is categorized under: Analytical and Computational Methods > Computational Methods Biological Mechanisms > Cell Fates Biological Mechanisms > Cell Signaling Models of Systems Properties and Processes > Mechanistic Models.

Influence of correlated antigen presentation on T-cell negative selection in the thymus

The thymus is the primary organ for the generation of naive T cells, a key component of the immune system. Tolerance of T cells to self is achieved primarily in the thymic medulla, where immature T cells (thymocytes) sample self-peptides presented by medullary thymic epithelial cells (mTECs). A sufficiently strong interaction activates the thymocytes leading to negative selection. A key question of current interest is whether there is any structure in the manner in which mTECs present peptides: can any mTEC present any peptide at any time, or are there particular patterns of correlated peptide presentation? We investigate this question using a mathematical model of negative selection. We find that correlated patterns of peptide presentation may be advantageous in negatively selecting low-degeneracy thymocytes (that is, those thymocytes which respond to relatively few peptides). We also quantify the probability that an auto-reactive thymocyte exits the thymus before it encounters a cognate antigen. The results suggest that heterogeneity of gene co-expression in mTECs has an effect on the probability of escape of autoreactive thymocytes.

Evolution of weak cooperative interactions for biological specificity

Functional specificity in biology is mediated by two classes of mechanisms, “lock–key” interactions and multivalent weak cooperative interactions (WCI). Despite growing evidence that WCI are widely prevalent in higher organisms, little is known about the selection forces that drove its evolution and repeated positive selection for mediating biological specificity in metazoa. We report that multivalent WCI for mediating biological specificity evolved as the number of tasks that organisms had to perform with functional specificity became large (e.g., multicellular organisms). We find that the evolution of multivalent WCI confer enhanced and robust evolvability to organisms, and thus it has been repeatedly positively selected. Thus, we provide insights on the evolution of WCI and, more broadly, on the evolution of evolvability.

A hallmark of biological systems is that particular functions and outcomes are realized in specific contexts, such as when particular signals are received. One mechanism for mediating specificity is described by Fisher’s “lock and key” metaphor, exemplified by enzymes that bind selectively to a particular substrate via specific finely tuned interactions. Another mechanism, more prevalent in multicellular organisms, relies on multivalent weak cooperative interactions. Its importance has recently been illustrated by the recognition that liquid-liquid phase transitions underlie the formation of membraneless condensates that perform specific cellular functions. Based on computer simulations of an evolutionary model, we report that the latter mechanism likely became evolutionarily prominent when a large number of tasks had to be performed specifically for organisms to function properly. We find that the emergence of weak cooperative interactions for mediating specificity results in organisms that can evolve to accomplish new tasks with fewer, and likely less lethal, mutations. We argue that this makes the system more capable of undergoing evolutionary changes robustly, and thus this mechanism has been repeatedly positively selected in increasingly complex organisms. Specificity mediated by weak cooperative interactions results in some useful cross-reactivity for related tasks, but at the same time increases susceptibility to misregulation that might lead to pathologies.

How nonuniform contact profiles of T cell receptors modulate thymic selection outcomes

T cell receptors (TCRs) bind foreign or self-peptides attached to major histocompatibility complex (MHC) molecules, and the strength of this interaction determines T cell activation. Optimizing the ability of T cells to recognize a diversity of foreign peptides yet be tolerant of self-peptides is crucial for the adaptive immune system to properly function. This is achieved by selection of T cells in the thymus, where immature T cells expressing unique, stochastically generated TCRs interact with a large number of self-peptide-MHC; if a TCR does not bind strongly enough to any self-peptide-MHC, or too strongly with at least one self-peptide-MHC, the T cell dies. Past theoretical work cast thymic selection as an extreme value problem and characterized the statistical enrichment or depletion of amino acids in the postselection TCR repertoire, showing how T cells are selected to be able to specifically recognize peptides derived from diverse pathogens yet have limited self-reactivity. Here, we investigate how the diversity of the postselection TCR repertoire is modified when TCRs make nonuniform contacts with peptide-MHC. Specifically, we were motivated by recent experiments showing that amino acids at certain positions of a TCR sequence have large effects on thymic selection outcomes, and crystal structure data that reveal a nonuniform contact profile between a TCR and its peptide-MHC ligand. Using a representative TCR contact profile as an illustration, we show via simulations that the statistical enrichment or depletion of amino acids now varies by position according to the contact profile, and, importantly, it depends on the implementation of nonuniform contacts during thymic selection. We explain these nontrivial results analytically. Our study has implications for understanding the selection forces that shape the functionality of the postselection TCR repertoire.

The Changing Landscape of Naive T Cell Receptor Repertoire With Human Aging

Human aging is associated with a profound loss of thymus productivity, yet naïve T lymphocytes still maintain their numbers by division in the periphery for many years. The extent of such proliferation may depend on the cytokine environment, including IL-7 and T-cell receptor (TCR) “tonic” signaling mediated by self pMHCs recognition. Additionally, intrinsic properties of distinct subpopulations of naïve T cells could influence the overall dynamics of aging-related changes within the naïve T cell compartment. Here, we investigated the differences in the architecture of TCR beta repertoires for naïve CD4, naïve CD8, naïve CD4⁺CD25⁻CD31⁺ (enriched with recent thymic emigrants, RTE), and mature naïve CD4⁺CD25⁻CD31⁻ peripheral blood subsets between young and middle-age/old healthy individuals. In addition to observing the accumulation of clonal expansions (as was shown previously), we reveal several notable changes in the characteristics of T cell repertoire. We observed significant decrease of CDR3 length, NDN insert, and number of non-template added N nucleotides within TCR beta CDR3 with aging, together with a prominent change of physicochemical properties of the central part of CDR3 loop. These changes were similar across CD4, CD8, RTE-enriched, and mature CD4 subsets of naïve T cells, with minimal or no difference observed between the latter two subsets for individuals of the same age group. We also observed an increase in “publicity” (fraction of shared clonotypes) of CD4, but not CD8 naïve T cell repertoires. We propose several explanations for these phenomena built upon previous studies of naïve T-cell homeostasis, and call for further studies of the mechanisms causing the observed changes and of consequences of these changes in respect of the possible holes formed in the landscape of naïve T cell TCR repertoire.

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.

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.

Computational prediction of vaccine potential epitopes and 3-dimensional structure of XAGE-1b for non-small cell lung cancer immunotherapy

BACKGROUND

XAGE-1b is shown to be overexpressed in lung adenocarcinoma and to be a strong immunogenic antigen among non-small cell lung cancer (NSCLC) patients. However, 3D structure of XAGE-1b is not available and its confirmation has not been solved yet.

METHODS

Multiple sequence alignment was run to select the most reliable templates. Homology modeling technique was performed using computer-based tool to generate 3-dimensional structure models, eight models were generated and assessed on basis of local and global quality. Immune Epitope Database (IEDB) tools were then used to determine potential B-Cell epitopes while NetMHCpan algorithms were used to enhance the determination for potential epitopes of both Cytotoxic T-lymphocytes and T-helper cells.

RESULTS

Computational prediction was performed for B-Cell epitopes, prediction results generated; 3 linear epitopes where XAGE-1b (13-21) possessed the best score of 0.67, 5 discontinuous epitopes where XAGE-1b (40-52) possessed the best score of 0.67 based on the predicted model of the finest quality. For a potential vaccine design, computational prediction yielded potential Human Leukocyte Antigen (HLA) class I epitopes including HLA-B*08:01-restricted XAGE-1b (3-11) epitope which was the best with 0.2 percentile rank. Regarding HLA Class II epitopes, HLA-DRB1*12:01-restricted XAGE-1b (25-33) was the most antigenic epitope with 5.91 IC50 value. IC50 values were compared with experimental values and population coverage percentages of epitopes were computed.

CONCLUSIONS

This study predicted a model of XAGE-1b tertiary structure which could explain its antigenic function and facilitate usage of predicted peptides for experimental validation towards designing immunotherapies against NSCLC.

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.

Organs on chip approach: a tool to evaluate cancer -immune cells interactions

In this paper we discuss the applicability of numerical descriptors and statistical physics concepts to characterize complex biological systems observed at microscopic level through organ on chip approach. To this end, we employ data collected on a microfluidic platform in which leukocytes can move through suitably built channels toward their target. Leukocyte behavior is recorded by standard time lapse imaging. In particular, we analyze three groups of human peripheral blood mononuclear cells (PBMC): heterozygous mutants (in which only one copy of the FPR1 gene is normal), homozygous mutants (in which both alleles encoding FPR1 are loss-of-function variants) and cells from 'wild type' donors (with normal expression of FPR1). We characterize the migration of these cells providing a quantitative confirmation of the essential role of FPR1 in cancer chemotherapy response. Indeed wild type PBMC perform biased random walks toward chemotherapy-treated cancer cells establishing persistent interactions with them. Conversely, heterozygous mutants present a weaker bias in their motion and homozygous mutants perform rather uncorrelated random walks, both failing to engage with their targets. We next focus on wild type cells and study the interactions of leukocytes with cancerous cells developing a novel heuristic procedure, inspired by Lyapunov stability in dynamical systems.

Effects of thymic selection on T cell recognition of foreign and tumor antigenic peptides

The advent of cancer immunotherapy has generated renewed hope for the treatment of many malignancies by introducing a number of novel strategies that exploit various properties of the immune system. These therapies are based on the idea that cytotoxic T lymphocytes (CTLs) directly recognize and respond to tumor-associated neoantigens (TANs) in much the same way as they would to foreign peptides presented on cell surfaces. To date, however, nearly all attempts to optimize immunotherapeutic strategies have been empirical. Here, we develop a model of T cell selection based on the assumption of random interaction strengths between a self-peptide and the various T cell receptors. The model enables the analytical study of the effects of selection on the CTL recognition of TANs and completely foreign peptides and can estimate the number of CTLs that can detect donor-matched transplants. We show that negative selection thresholds chosen to reflect experimentally observed thymic survival rates result in near-optimal production of T cells that are capable of surviving selection and recognizing foreign antigen. These analytical results are confirmed by simulation.

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.