Single T Cell Sequencing Demonstrates the Functional Role of αβ TCR Pairing in Cell Lineage and Antigen Specificity

Germline-like TCR-α chains shared between autoreactive T cells in blood and pancreas

Human type 1 diabetes (T1D) is caused by autoimmune attack on the insulin-producing pancreatic beta cells by islet antigen-reactive T cells. How human islet antigen-reactive (IAR) CD4+ memory T cells from peripheral blood affect T1D progression in the pancreas is poorly understood. Here, we aim to determine if IAR T cells in blood could be detected in pancreas. We identify paired αβ (TRA/TRB) T cell receptors (TCRs) in IAR T cells from the blood of healthy, at-risk, new-onset, and established T1D donors, and measured sequence overlap with TCRs in pancreata from healthy, at risk and T1D organ donors. We report extensive TRA junction sharing between IAR T cells and pancreas-infiltrating T cells (PIT), with perfect-match or single-mismatch TRA junction amino acid sequences comprising ~29% total unique IAR TRA junctions (942/3,264). PIT-matched TRA junctions were largely public and enriched for TRAV41 usage, showing significant nucleotide sequence convergence, increased use of germline-encoded versus non-templated residues in epitope engagement, and a potential for cross-reactivity. Our findings thus link T cells with distinctive germline-like TRA chains in the peripheral blood with T cells in the pancreas.

Autoimmune CD8+ T cells in type 1 diabetes: from single-cell RNA sequencing to T-cell receptor redirection

Type 1 diabetes (T1D) is an organ-specific autoimmune disease caused by pancreatic β cell destruction and mediated primarily by autoreactive CD8+ T cells. It has been shown that only a small number of stem cell-like β cell-specific CD8+ T cells are needed to convert normal mice into T1D mice; thus, it is likely that T1D can be cured or significantly improved by modulating or altering self-reactive CD8+ T cells. However, stem cell-type, effector and exhausted CD8+ T cells play intricate and important roles in T1D. The highly diverse T-cell receptors (TCRs) also make precise and stable targeted therapy more difficult. Therefore, this review will investigate the mechanisms of autoimmune CD8+ T cells and TCRs in T1D, as well as the related single-cell RNA sequencing (ScRNA-Seq), CRISPR/Cas9, chimeric antigen receptor T-cell (CAR-T) and T-cell receptor-gene engineered T cells (TCR-T), for a detailed and clear overview. This review highlights that targeting CD8+ T cells and their TCRs may be a potential strategy for predicting or treating T1D.

Helper T cell immunity in humans with inherited CD4 deficiency

CD4+ T cells are vital for host defense and immune regulation. However, the fundamental role of CD4 itself remains enigmatic. We report seven patients aged 5-61 years from five families of four ancestries with autosomal recessive CD4 deficiency and a range of infections, including recalcitrant warts and Whipple's disease. All patients are homozygous for rare deleterious CD4 variants impacting expression of the canonical CD4 isoform. A shorter expressed isoform that interacts with LCK, but not HLA class II, is affected by only one variant. All patients lack CD4+ T cells and have increased numbers of TCRαβ+CD4-CD8- T cells, which phenotypically and transcriptionally resemble conventional Th cells. Finally, patient CD4-CD8- αβ T cells exhibit intact responses to HLA class II-restricted antigens and promote B cell differentiation in vitro. Thus, compensatory development of Th cells enables patients with inherited CD4 deficiency to acquire effective cellular and humoral immunity against an unexpectedly large range of pathogens. Nevertheless, CD4 is indispensable for protective immunity against at least human papillomaviruses and Trophyrema whipplei.

Stereotypic T cell receptor clonotypes in the thymus and peripheral blood of Myasthenia gravis patients

Myasthenia Gravis (MG) patients with anti-acetylcholine receptor (AChR) antibodies frequently show hyperplastic thymi with ectopic germinal centers, where autoreactive B cells proliferate with the aid of T cells. In this study, thymus and peripheral blood (PB) samples were collected from ten AChR antibody-positive MG patients. T cell receptor (TCR) repertoires were analyzed using next-generation sequencing (NGS), and compared with that of an age and sex matched control group generated from a public database. Certain V genes and VJ gene recombination pairs were significantly upregulated in the TCR chains of αβ-T cells in the PB of MG patients compared to the control group. Furthermore, the TCR chains found in the thymi of MG patients had a weighted distribution to longer CDR3 lengths when compared to the PB of MG patients, and the TCR beta chains (TRB) in the MG group's PB showed increased clonality encoded by one upregulated V gene. When TRB sequences were sub-divided into groups based on their CDR3 lengths, certain groups showed decreased clonality in the MG group's PB compared to the control group's PB. Finally, we demonstrated that stereotypic MG patient-specific TCR clonotypes co-exist in both the PB and thymi at a much higher frequency than that of the clonotypes confined to the PB. These results strongly suggest the existence of a biased T cell-mediated immune response in MG patients, as observed in other autoimmune diseases.

A mass cytometry approach to track the evolution of T cell responses during infection and immunotherapy by paired T cell receptor repertoire and T cell differentiation state analysis

T cell receptor (TCR) recognition followed by clonal expansion is a fundamental feature of adaptive immune responses. Here, we developed a mass cytometric (CyTOF) approach combining antibodies specific for different TCR Vα- and Vβ-chains with antibodies against T cell activation and differentiation proteins to identify antigen-specific expansions of T cell subsets and assess aspects of cellular function. This strategy allowed for the identification of expansions of specific Vβ and Vα chain expressing CD8+ and CD4+ T cells with varying differentiation states in response to Listeria monocytogenes, tumors, and respiratory influenza infection. Expanded Vβ chain expressing T cells could be directly linked to the recognition of specific antigens from Listeria, tumor cells, or influenza. In the setting of influenza infection, we showed that the common therapeutic approaches of intramuscular vaccination or convalescent serum transfer altered the clonal diversity and differentiation state of responding T cells. Thus, we present a new method to monitor broad changes in TCR specificity paired with T cell differentiation during adaptive immune responses.

High Epstein-Barr virus capsid antigen IgG level associates with the carriership of CD8+ T cell somatic mutations in the STAT3 SH2 domain

High carrier prevalence of STAT3 SH2 domain somatic mutations was recently discovered in CD8+ T cells. We found these low-allele-fraction clones in 26% of donors, without difference between multiple sclerosis (MS) patients and controls. Here we tested whether anti-viral antibodies associate with the carriership of these mutant clones. We compared antibody responses against common viruses in mutation carriers vs. non-carriers. Plasma samples of 152 donors (92 MS patients, 60 controls) were analyzed for antibodies against cytomegalovirus (CMV), Epstein-Barr virus (EBV), human herpesvirus-6A and parvovirus B19. The mutation carrier status associated with EBV VCA IgG level (p = 0.005) and remained significant after logistic regression (p = 0.036). This association was contributed similarly by MS patients and controls. These results suggest that EBV contributes to the generation or growth of these clones. The pathogenic role of the STAT3 mutant clones in MS is presently unclear, but their detailed characterization warrants further study.

A transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity

Antigen immunogenicity and the specificity of binding of T-cell receptors to antigens are key properties underlying effective immune responses. Here we propose diffRBM, an approach based on transfer learning and Restricted Boltzmann Machines, to build sequence-based predictive models of these properties. DiffRBM is designed to learn the distinctive patterns in amino-acid composition that, on the one hand, underlie the antigen's probability of triggering a response, and on the other hand the T-cell receptor's ability to bind to a given antigen. We show that the patterns learnt by diffRBM allow us to predict putative contact sites of the antigen-receptor complex. We also discriminate immunogenic and non-immunogenic antigens, antigen-specific and generic receptors, reaching performances that compare favorably to existing sequence-based predictors of antigen immunogenicity and T-cell receptor specificity.

Numbers and odds: TCR repertoire size and its age changes impacting on T cell functions

A vast array of αβ T cell receptors (TCRs) is generated during T cell development in the thymus through V(D)J recombination, which involves the rearrangement of multiple V, D, and J genes and the pairing of α and β chains. These diverse TCRs provide protection to the human body against a multitude of foreign pathogens and internal cancer cells. The entirety of TCRs present in an individual's T cells is referred to as the TCR repertoire. Despite an estimated 4 × 1011 T cells in the adult human body, the lower bound estimate for the TCR repertoire is 3.8 × 108. While the number of circulating T cells may slightly decrease with age, the changes in the diversity of the TCR repertoire is more apparent. Here, I review recent advancements in TCR repertoire studies, the methods used to measure it, how richness and diversity change as humans age, and some of the known consequences associated with these changes.

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

The T cell receptor sequence influences the likelihood of T cell memory formation

T cell differentiation depends on activation through the T cell receptor (TCR), whose amino acid sequence varies cell to cell. Particular TCR amino acid sequences nearly guarantee Mucosal-Associated Invariant T (MAIT) and Natural Killer T (NKT) cell fates. To comprehensively define how TCR amino acids affects all T cell fates, we analyze the paired αβTCR sequence and transcriptome of 819,772 single cells. We find that hydrophobic CDR3 residues promote regulatory T cell transcriptional states in both the CD8 and CD4 lineages. Most strikingly, we find a set of TCR sequence features, concentrated in CDR2α, that promotes positive selection in the thymus as well as transition from naïve to memory in the periphery. Even among T cells that recognize the same antigen, these TCR sequence features help to explain which T cells form immunological memory, which is essential for effective pathogen response.

Analysis of thymic generation of shared T-cell receptor α repertoire associated with recognition of tumor antigens shows no preference for neoantigens over wild-type antigens

BACKGROUND

The number of mutations in cancer cells is an important predictor of a positive response to cancer immunotherapy. It has been suggested that the neoantigens produced by these mutations are more immunogenic than nonmutated tumor antigens, which are likely to be protected by immunological tolerance. However, the mechanisms of tolerance as regards tumor antigens are incompletely understood.

METHODS

Here, we have analyzed the impact of thymic negative selection on shared T-cell receptor (TCR) repertoire associated with the recognition of either mutated or nonmutated tumor antigens by comparing previously known TCR-antigen-pairs to TCR repertoires of 21 immunologically healthy individuals.

RESULTS

Our results show that TCRα chains associated with either type of tumor antigens are readily generated in the thymus, at a frequency similar to TCRα chains associated with nonself. In the peripheral repertoire, the relative clone size of nonself-associated chains is higher than that of the tumor antigens, but importantly, there is no difference between TCRα chains associated with mutated or nonmutated tumor antigens.

CONCLUSION

This suggests that the tolerance mechanisms protecting nonmutated tumor antigens are non-deletional and therefore potentially reversible. As unmutated antigens are, unlike mutations, shared by a large number of patients, they may offer advantages in designing immunological approaches to cancer treatment.

Emerging interleukin targets in the tumour microenvironment: implications for the treatment of gastrointestinal tumours

The effectiveness of antitumour immunity is dependent on intricate cytokine networks. Interleukins (ILs) are important mediators of complex interactions within the tumour microenvironment, including regulation of tumour-infiltrating lymphocyte proliferation, differentiation, migration and activation. Our evolving and increasingly nuanced understanding of the cell type-specific and heterogeneous effects of IL signalling has presented unique opportunities to fine-tune elaborate IL networks and engineer new targeted immunotherapeutics. In this review, we provide a primer for clinicians on the challenges and potential of IL-based treatment. We specifically detail the roles of IL-2, IL-10, IL-12 and IL-15 in shaping the tumour-immune landscape of gastrointestinal malignancies, paying particular attention to promising preclinical findings, early-stage clinical research and innovative therapeutic approaches that may properly place ILs to the forefront of immunotherapy regimens.

TPBTE: A model based on convolutional Transformer for predicting the binding of TCR to epitope

T cell receptors (TCRs) selectively bind to antigens to fight pathogens with specific immunity. Current tools focus on the nature of amino acids within sequences and take less into account the nature of amino acids far apart and the relationship between sequences, leading to significant differences in the results from different datasets. We propose TPBTE, a model based on convolutional Transformer for Predicting the Binding of TCR to Epitope. It takes epitope sequences and the complementary decision region 3 (CDR3) sequences of TCRβ chain as inputs. And it uses a convolutional attention mechanism to learn amino acid representations between different positions of the sequences based on learning local features of the sequences. At the same time, it uses cross attention to learn the interaction information between TCR sequences and epitope sequences. A comprehensive evaluation of the TCR-epitope data shows that the average area under the curve of TPBTE outperforms the baseline model, and demonstrate an intentional performance. In addition, TPBTE can give the probability of binding TCR to epitopes, which can be used as the first step of epitope screening, narrowing the scope of epitope search and reducing the time of epitope search.

Entropic analysis of antigen-specific CDR3 domains identifies essential binding motifs shared by CDR3s with different antigen specificities

Antigen-specific T cell receptor (TCR) sequences can have prognostic, predictive, and therapeutic value, but decoding the specificity of TCR recognition remains challenging. Unlike DNA strands that base pair, TCRs bind to their targets with different orientations and different lengths, which complicates comparisons. We present scanning parametrized by normalized TCR length (SPAN-TCR) to analyze antigen-specific TCR CDR3 sequences and identify patterns driving TCR-pMHC specificity. Using entropic analysis, SPAN-TCR identifies 2-mer motifs that decrease the diversity (entropy) of CDR3s. These motifs are the most common patterns that can predict CDR3 composition, and we identify "essential" motifs that decrease entropy in the same CDR3 α or β chain containing the 2-mer, and "super-essential" motifs that decrease entropy in both chains. Molecular dynamics analysis further suggests that these motifs may play important roles in binding. We then employ SPAN-TCR to resolve similarities in TCR repertoires against different antigens using public databases of TCR sequences.

Deep autoregressive generative models capture the intrinsics embedded in T-cell receptor repertoires

T-cell receptors (TCRs) play an essential role in the adaptive immune system. Probabilistic models for TCR repertoires can help decipher the underlying complex sequence patterns and provide novel insights into understanding the adaptive immune system. In this work, we develop TCRpeg, a deep autoregressive generative model to unravel the sequence patterns of TCR repertoires. TCRpeg largely outperforms state-of-the-art methods in estimating the probability distribution of a TCR repertoire, boosting the average accuracy from 0.672 to 0.906 measured by the Pearson correlation coefficient. Furthermore, with promising performance in probability inference, TCRpeg improves on a range of TCR-related tasks: profiling TCR repertoire probabilistically, classifying antigen-specific TCRs, validating previously discovered TCR motifs, generating novel TCRs and augmenting TCR data. Our results and analysis highlight the flexibility and capacity of TCRpeg to extract TCR sequence information, providing a novel approach for deciphering complex immunogenomic repertoires.

Adoptive cellular immunotherapy for solid neoplasms beyond CAR-T

In recent decades, immune checkpoint blockade and chimeric antigen receptor T cell (CAR-T) therapy are two milestone achievements in clinical immunotherapy. However, both show limited efficacies in most solid neoplasms, which necessitates the exploration of new immunotherapeutic modalities. The failure of CAR-T and immune checkpoint blockade in several solid neoplasms is attributed to multiple factors, including low antigenicity of tumor cells, low infiltration of effector T cells, and diverse mechanisms of immunosuppression in the tumor microenvironment. New adoptive cell therapies have been attempted for solid neoplasms, including TCR-T, CAR-natural killer cells (CAR-NK), and CAR-macrophages (CAR-M). Compared to CAR-T, these new adoptive cell therapies have certain advantages in treating solid neoplasms. In this review, we summarized the 40-year evolution of adoptive cell therapies, then focused on the advances of TCR-T, CAR-NK, and CAR-M in solid neoplasms and discussed their potential clinical applications.

Quantifying changes in the T cell receptor repertoire during thymic development

One of the feats of adaptive immunity is its ability to recognize foreign pathogens while sparing the self. During maturation in the thymus, T cells are selected through the binding properties of their antigen-specific T-cell receptor (TCR), through the elimination of both weakly (positive selection) and strongly (negative selection) self-reactive receptors. However, the impact of thymic selection on the TCR repertoire is poorly understood. Here, we use transgenic Nur77-mice expressing a T-cell activation reporter to study the repertoires of thymic T cells at various stages of their development, including cells that do not pass selection. We combine high-throughput repertoire sequencing with statistical inference techniques to characterize the selection of the TCR in these distinct subsets. We find small but significant differences in the TCR repertoire parameters between the maturation stages, which recapitulate known differentiation pathways leading to the CD4⁺ and CD8⁺ subtypes. These differences can be simulated by simple models of selection acting linearly on the sequence features. We find no evidence of specific sequences or sequence motifs or features that are suppressed by negative selection. These results favour a collective or statistical model for T-cell self non-self discrimination, where negative selection biases the repertoire away from self recognition, rather than ensuring lack of self-reactivity at the single-cell level.

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity

Introduction

The success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance.

Methods

We report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls.

Results

In contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients.

Discussion

These features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges.

Clonal dynamics underlying the skewed CD4/CD8 ratio of mouse thymocytes revealed by TCR-independent barcoding

T cell differentiation in the thymus generates CD4⁺ helper and cytotoxic CD8⁺ cells as the two principal T cell lineages. Curiously, at the end of this complex selection process, CD4⁺ cells invariably outnumber CD8⁺ cells. Here, we examine the dynamics of repertoire formation and the emergence of the skewed CD4/CD8 ratio using high-resolution endogenous CRISPR/Cas9 barcoding that indelibly marks immature T cells at the DN2/DN3 pre-TCR stage. In wild-type mice, greater clone size of CD4⁺ cells and an intrinsically greater probability of Tcr β clonotypes for pMHCII interactions are major contributors to the skewed CD4/CD8 ratio. Clonal perturbations of thymocyte differentiation following the precocious expression of a rearranged iNKT invariant TCR α chain are due to loss of Tcr β clonotypes from the CD4 lineage-committed pre-selection repertoire. The present barcoding scheme offers a novel means to examine the clonal dynamics of lymphocyte differentiation orthogonal to that using TCR clonotypes.

CRSIPR-mediated barcoding of pre-TCR-expressing T cells is used to investigate the clonal dynamics of thymic T cells and reveals new fundamental understanding of how the skewed CD4/CD8 ratio arises during thymic selection.

Single-cell sequencing unveils distinct immune microenvironments with CCR6-CCL20 crosstalk in human chronic pancreatitis

OBJECTIVE

Chronic pancreatitis (CP) is a potentially fatal disease of the exocrine pancreas, with no specific or effective approved therapies. Due to difficulty in accessing pancreas tissues, little is known about local immune responses or pathogenesis in human CP. We sought to characterise pancreatic immune responses using tissues derived from patients with different aetiologies of CP and non-CP organ donors in order to identify key signalling molecules associated with human CP.

DESIGN

We performed single-cell level cellular indexing of transcriptomes and epitopes by sequencing and T-cell receptor (TCR) sequencing of pancreatic immune cells isolated from organ donors, hereditary and idiopathic patients with CP who underwent total pancreatectomy. We validated gene expression data by performing flow cytometry and functional assays in a second patient with CP cohort.

RESULTS

Deep single-cell sequencing revealed distinct immune characteristics and significantly enriched CCR6⁺ CD4⁺ T cells in hereditary compared with idiopathic CP. In hereditary CP, a reduction in T-cell clonality was observed due to the increased CD4⁺ T (Th) cells that replaced tissue-resident CD8⁺ T cells. Shared TCR clonotype analysis among T-cell lineages also unveiled unique interactions between CCR6⁺ Th and Th1 subsets, and TCR clustering analysis showed unique common antigen binding motifs in hereditary CP. In addition, we observed a significant upregulation of the CCR6 ligand (CCL20) expression among monocytes in hereditary CP as compared with those in idiopathic CP. The functional significance of CCR6 expression in CD4⁺ T cells was confirmed by flow cytometry and chemotaxis assay.

CONCLUSION

Single-cell sequencing with pancreatic immune cells in human CP highlights pancreas-specific immune crosstalk through the CCR6-CCL20 axis, a signalling pathway that might be leveraged as a potential future target in human hereditary CP.

Circulating biomarkers of response to immunotherapy and immune-related adverse events

INTRODUCTION

Immune checkpoint blockade has revolutionized cancer treatment. However, response rates vary, and these treatments have a high rate of immune-related side effects, which can be limiting. Thus, tests to predict who will respond and who may experience side effects are of critical importance toward realizing the ultimate goal of precision oncology.

AREAS COVERED

We review several of the most recent advances in circulating biomarkers that have been reported to be useful in predicting response and immune-related adverse events (irAE) to checkpoint blockade immunotherapies (CBI). We focus on high-quality studies published within the last few years. We highlight significant findings, identify areas for improvement, and provide recommendations on how these biomarkers may be translated into clinical utility.

EXPERT OPINION

As newer immunotherapies are developed, there is a pressing need to identify circulating biomarkers that can help predict responses and side effects. Current studies are mostly small-scale and retrospective; there is a need for larger-scale and prospective studies to help validate several of the biomarkers detailed here. As oncology focuses more on precision-based approaches, it is likely that a combination of biomarkers, including circulating ones as detailed here, will have critical utility in guiding clinical decisions.

Transcriptomic diversity in human medullary thymic epithelial cells

The induction of central T cell tolerance in the thymus depends on the presentation of peripheral self-epitopes by medullary thymic epithelial cells (mTECs). This promiscuous gene expression (pGE) drives mTEC transcriptomic diversity, with non-canonical transcript initiation, alternative splicing, and expression of endogenous retroelements (EREs) representing important but incompletely understood contributors. Here we map the expression of genome-wide transcripts in immature and mature human mTECs using high-throughput 5' cap and RNA sequencing. Both mTEC populations show high splicing entropy, potentially driven by the expression of peripheral splicing factors. During mTEC maturation, rates of global transcript mis-initiation increase and EREs enriched in long terminal repeat retrotransposons are up-regulated, the latter often found in proximity to differentially expressed genes. As a resource, we provide an interactive public interface for exploring mTEC transcriptomic diversity. Our findings therefore help construct a map of transcriptomic diversity in the healthy human thymus and may ultimately facilitate the identification of those epitopes which contribute to autoimmunity and immune recognition of tumor antigens.

Analysis of Gene Expression and TCR/B Cell Receptor Profiling of Immune Cells in Primary Sjögren's Syndrome by Single-Cell Sequencing

Primary Sjögren's syndrome (pSS) is a chronic autoimmune disease that is estimated to affect 35 million people worldwide and is characterized by lymphocytic infiltration, elevated circulating autoantibodies, and proinflammatory cytokines. The key immune cell subset changes and the TCR/BCR repertoire alterations in pSS patients remain unclear. In this study, we sought to comprehensively characterize the transcriptional changes in PBMCs of pSS patients by single-cell RNA sequencing and single-cell V(D)J sequencing. Naive CD8⁺ T cells and mucosal-associated invariant T cells were markedly decreased but regulatory T cells were increased in pSS patients. There were a large number of differentially expressed genes shared by multiple subpopulations of T cells and B cells. Abnormal signaling pathways, including Ag processing and presentation, the BCR signaling pathway, the TCR signaling pathway, and Epstein-Barr virus infection, were highly enriched in pSS patients. Moreover, there were obvious differences in the CD30, FLT3, IFN-II, IL-1, IL-2, IL-6, IL-10, RESISTIN, TGF-β, TNF, and VEGF signaling networks between pSS patients and healthy controls. Single-cell TCR and BCR repertoire analysis showed that there was a lower diversity of T cells in pSS patients than in healthy controls; however, there was no significant difference in the degree of clonal expansion, CDR3 length distribution, or degree of sequence sharing. Notably, our results further emphasize the functional importance of αβ pairing in determining Ag specificity. In conclusion, our analysis provides a comprehensive single-cell map of gene expression and TCR/BCR profiles in pSS patients for a better understanding of the pathogenesis, diagnosis, and treatment of pSS.

Longitudinal analysis reveals age-related changes in the T cell receptor repertoire of human T cell subsets

A diverse T cell receptor (TCR) repertoire is essential for protection against a variety of pathogens, and TCR repertoire size is believed to decline with age. However, the precise size of human TCR repertoires, in both total and subsets of T cells, as well as their changes with age, are not fully characterized. We conducted a longitudinal analysis of the human blood TCRα and TCRβ repertoire of CD4⁺ and CD8⁺ T cell subsets using a unique molecular identifier–based (UMI-based) RNA-seq method. Thorough analysis of 1.9 × 10⁸ T cells yielded the lower estimate of TCR repertoire richness in an adult at 3.8 × 10⁸. Alterations of the TCR repertoire with age were observed in all 4 subsets of T cells. The greatest reduction was observed in naive CD8⁺ T cells, while the greatest clonal expansion was in memory CD8⁺ T cells, and the highest increased retention of TCR sequences was in memory CD8⁺ T cells. Our results demonstrated that age-related TCR repertoire attrition is subset specific and more profound for CD8⁺ than CD4⁺ T cells, suggesting that aging has a more profound effect on cytotoxic as opposed to helper T cell functions. This may explain the increased susceptibility of older adults to novel infections.

BFF and cellhashR: analysis tools for accurate demultiplexing of cell hashing data

MOTIVATION

Single-cell sequencing methods provide previously impossible resolution into the transcriptome of individual cells. Cell hashing reduces single-cell sequencing costs by increasing capacity on droplet-based platforms. Cell hashing methods rely on demultiplexing algorithms to accurately classify droplets; however, assumptions underlying these algorithms limit accuracy of demultiplexing, ultimately impacting the quality of single-cell sequencing analyses.

RESULTS

We present Bimodal Flexible Fitting (BFF) demultiplexing algorithms BFFcluster and BFFraw, a novel class of algorithms that rely on the single inviolable assumption that barcode count distributions are bimodal. We integrated these and other algorithms into cellhashR, a new R package that provides integrated QC and a single command to execute and compare multiple demultiplexing algorithms. We demonstrate that BFFcluster demultiplexing is both tunable and insensitive to issues with poorly behaved data that can confound other algorithms. Using two well-characterized reference datasets, we demonstrate that demultiplexing with BFF algorithms is accurate and consistent for both well-behaved and poorly behaved input data.

AVAILABILITY AND IMPLEMENTATION

cellhashR is available as an R package at https://github.com/BimberLab/cellhashR. cellhashR version 1.0.3 was used for the analyses in this manuscript and is archived on Zenodo at https://www.doi.org/10.5281/zenodo.6402477.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Serial Analysis of the T-Cell Receptor β-Chain Repertoire in People Living With HIV Reveals Incomplete Recovery After Long-Term Antiretroviral Therapy

Long-term antiretroviral therapy (ART) in people living with HIV (PLHIV) is associated with sustained increases in CD4+ T-cell count, but its effect on the peripheral blood T-cell repertoire has not been comprehensively evaluated. In this study, we performed serial profiling of the composition and diversity of the T-cell receptor β-chain (TRB) repertoire in 30 adults with HIV infection before and after the initiation of ART to define its long-term impact on the TRB repertoire. Serially acquired blood samples from 30 adults with HIV infection collected over a mean of 6 years (range, 1-12) years, with 1-4 samples collected before and 2-8 samples collected after the initiation of ART, were available for analysis. TRB repertoires were characterized via high-throughput sequencing of the TRB variable region performed on genomic DNA extracted from unsorted peripheral blood mononuclear cells. Additional laboratory and clinical metadata including serial measurements of HIV viral load and CD4+ T-cell count were available for all individuals in the cohort. A previously published control group of 189 TRB repertoires from peripheral blood samples of adult bone marrow transplant donors was evaluated for comparison. ART initiation in PLHIV was associated with a sustained reduction in viral load and a significant increase in TRB repertoire diversity. However, repertoire diversity in PLHIV remained significantly lower than in the control group even after long-term ART. The composition of TRB repertoires of PLHIV after ART also remained perturbed compared to the control cohort, as evidenced by large persistent private clonal expansions, reduced efficiency in the generation of TRB CDR3 amino acid sequences, and a narrower range of CDR3 lengths. Network analysis revealed an antigen-experienced structure in the TRB repertoire of PLHIV both before and after ART initiation that was quite distinct from the structure of control repertoires, with a slight shift toward a more naïve structure observed after ART initiation. Though we observe significant improvement in TRB repertoire diversity with durable viral suppression in PLHIV on long-term ART, the composition and structure of these repertoires remain significantly perturbed compared to the control cohort of adult bone marrow transplant donors.

Targeting the tumor mutanome for personalized vaccination in a TMB low non-small cell lung cancer

BACKGROUND

Cancer is characterized by an accumulation of somatic mutations, of which a significant subset can generate cancer-specific neoepitopes that are recognized by autologous T cells. Such neoepitopes are emerging as important targets for cancer immunotherapy, including personalized cancer vaccination strategies.

METHODS

We used whole-exome and RNA sequencing analysis to identify potential neoantigens for a patient with non-small cell lung cancer. Thereafter, we assessed the autologous T-cell reactivity to the candidate neoantigens using a long peptide approach in a cultured interferon gamma ELISpot and tracked the neoantigen-specific T-cells in the tumor by T-cell receptor (TCR) sequencing. In parallel, identified gene variants were incorporated into a Modified Vaccinia Ankara-based vaccine, which was evaluated in the human leucocyte antigen A*0201 transgenic mouse model (HHD).

RESULTS

Sequencing revealed a tumor with a low mutational burden: 2219 sequence variants were identified from the primary tumor, of which 23 were expressed in the transcriptome, involving 18 gene products. We could demonstrate spontaneous T-cell responses to 5/18 (28%) mutated gene variants, and further analysis of the TCR repertoire of neoantigen-specific CD4+ and CD8+ T cells revealed TCR clonotypes that were expanded in both blood and tumor tissue. Following vaccination of HHD mice, de novo T-cell responses were generated to 4/18 (22%) mutated gene variants; T cells reactive against two variants were also evident in the autologous setting. Subsequently, we determined the major histocompatibility complex restriction of the T-cell responses and used in silico prediction tools to determine the likely neoepitopes.

CONCLUSIONS

Our study demonstrates the feasibility of efficiently identifying tumor-specific neoantigens that can be targeted by vaccination in tumors with a low mutational burden, promising successful clinical exploitation, with trials currently underway.

Identification of T cell antigens in the 21st century, as difficult as ever

Identifying antigens recognized by T cells is still challenging, particularly for innate like T cells that do not recognize peptides but small metabolites or lipids in the context of MHC-like molecules or see non-MHC restricted antigens. The fundamental reason for this situation is the low affinity of T cell receptors for their ligands coupled with a level of degeneracy that makes them bind to similar surfaces on antigen presenting cells. Herein we will describe non-exhaustively some of the methods that were used to identify peptide antigens and briefly mention the high throughput methods more recently proposed for that purpose. We will then present how the molecules recognized by innate like T cells (NKT, MAIT and γδ T cells) were discovered. We will show that serendipity was instrumental in many cases.

Identification and Tracking of Alloreactive T Cell Clones in Rhesus Macaques Through the RM-scTCR-Seq Platform

T cell receptor (TCR) clonotype tracking is a powerful tool for interrogating T cell mediated immune processes. New methods to pair a single cell's transcriptional program with its TCR identity allow monitoring of T cell clonotype-specific transcriptional dynamics. While these technologies have been available for human and mouse T cells studies, they have not been developed for Rhesus Macaques (RM), a critical translational organism for autoimmune diseases, vaccine development and transplantation. We describe a new pipeline, 'RM-scTCR-Seq', which, for the first time, enables RM specific single cell TCR amplification, reconstruction and pairing of RM TCR's with their transcriptional profiles. We apply this method to a RM model of GVHD, and identify and track in vitro detected alloreactive clonotypes in GVHD target organs and explore their GVHD driven cytotoxic T cell signature. This novel, state-of-the-art platform fundamentally advances the utility of RM to study protective and pathogenic T cell responses.

Single-Cell-Based High-Throughput Ig and TCR Repertoire Sequencing Analysis in Rhesus Macaques

Recent advancements in microfluidics and high-throughput sequencing technologies have enabled recovery of paired H and L chains of Igs and VDJ and VJ chains of TCRs from thousands of single cells simultaneously in humans and mice. Despite rhesus macaques being one of the most well-studied model organisms for the human adaptive immune response, high-throughput single-cell immune repertoire sequencing assays are not yet available due to the complexity of these polyclonal receptors. We used custom primers that capture all known rhesus macaque Ig and TCR isotypes and chains that are fully compatible with a commercial solution for single-cell immune repertoire profiling. Using these rhesus-specific assays, we sequenced Ig and TCR repertoires in >60,000 cells from cryopreserved rhesus PBMCs, splenocytes, and FACS-sorted B and T cells. We were able to recover every Ig isotype and TCR chain, measure clonal expansion in proliferating T cells, and pair Ig and TCR repertoires with gene expression profiles of the same single cells. Our results establish the ability to perform high-throughput immune repertoire analysis in rhesus macaques at the single-cell level.

Adoptive T-cell Immunotherapy: Perfecting Self-Defenses

As an important part of the immune system, T lymphocytes exhibit undoubtedly an important role in targeting and eradicating cancer. However, despite these characteristics, their natural antitumor response may be insufficient. Numerous clinical trials in terminally ill cancer patients testing the design of novel and efficient immunotherapeutic approaches based on the adoptive transfer of autologous tumor-specific T lymphocytes have shown encouraging results. Moreover, this also led to the approval of engineered T-cell therapies in patients. Herein, we will expand on the development and the use of such strategies using tumor-infiltrating lymphocytes or genetically engineered T-cells. We will also comment on the requirements and potential hurdles encountered when elaborating and implementing such treatments as well as the exciting prospects for this kind of emerging personalized medicine therapy.

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.

Multimodal T Cell Analysis with CoNGA

Advances in single-cell technologies have made it possible to simultaneously quantify gene expression and immune receptor sequence across thousands of individual T or B cells in a single experiment. Data from such experiments are advancing our understanding of the relationship between adaptive immune receptor sequence and transcriptional profile. We recently reported a software tool, CoNGA, specifically developed to detect correlation between receptor sequence and transcriptional profile. Here we describe in detail how CoNGA can be applied to analyze a large and diverse T cell dataset featuring multiple donors and batch annotations. Our workflow illustrates new analysis modes for the detection of TCR sequence convergence into similarity clusters and of matches to literature-derived TCR databases, as well as processing of gamma-delta T cells.

Heterologous Immunity of Virus-Specific T Cells Leading to Alloreactivity: Possible Implications for Solid Organ Transplantation

Exposure of the adaptive immune system to a pathogen can result in the activation and expansion of T cells capable of recognizing not only the specific antigen but also different unrelated antigens, a process which is commonly referred to as heterologous immunity. While such cross-reactivity is favourable in amplifying protective immune responses to pathogens, induction of T cell-mediated heterologous immune responses to allo-antigens in the setting of solid organ transplantation can potentially lead to allograft rejection. In this review, we provide an overview of murine and human studies investigating the incidence and functional properties of virus-specific memory T cells cross-reacting with allo-antigens and discuss their potential relevance in the context of solid organ transplantation.

High Throughput Human T Cell Receptor Sequencing: A New Window Into Repertoire Establishment and Alloreactivity

Recent advances in high throughput sequencing (HTS) of T cell receptors (TCRs) and in transcriptomic analysis, particularly at the single cell level, have opened the door to a new level of understanding of human immunology and immune-related diseases. In this article, we discuss the use of HTS of TCRs to discern the factors controlling human T cell repertoire development and how this approach can be used in combination with human immune system (HIS) mouse models to understand human repertoire selection in an unprecedented manner. An exceptionally high proportion of human T cells has alloreactive potential, which can best be understood as a consequence of the processes governing thymic selection. High throughput TCR sequencing has allowed assessment of the development, magnitude and nature of the human alloresponse at a new level and has provided a tool for tracking the fate of pre-transplant-defined donor- and host-reactive TCRs following transplantation. New insights into human allograft rejection and tolerance obtained with this method in combination with single cell transcriptional analyses are reviewed here.

Insights From Single Cell RNA Sequencing Into the Immunology of Type 1 Diabetes- Cell Phenotypes and Antigen Specificity

In the past few years, huge advances have been made in techniques to analyse cells at an individual level using RNA sequencing, and many of these have precipitated exciting discoveries in the immunology of type 1 diabetes (T1D). This review will cover the first papers to use scRNAseq to characterise human lymphocyte phenotypes in T1D in the peripheral blood, pancreatic lymph nodes and islets. These have revealed specific genes such as IL-32 that are differentially expressed in islet -specific T cells in T1D. scRNAseq has also revealed wider gene expression patterns that are involved in T1D and can predict its development even predating autoantibody production. Single cell sequencing of TCRs has revealed V genes and CDR3 motifs that are commonly used to target islet autoantigens, although truly public TCRs remain elusive. Little is known about BCR repertoires in T1D, but scRNAseq approaches have revealed that insulin binding BCRs commonly use specific J genes, share motifs between donors and frequently demonstrate poly-reactivity. This review will also summarise new developments in scRNAseq technology, the insights they have given into other diseases and how they could be leveraged to advance research in the type 1 diabetes field to identify novel biomarkers and targets for immunotherapy.

Predicting T Cell Receptor Antigen Specificity From Structural Features Derived From Homology Models of Receptor-Peptide-Major Histocompatibility Complexes

The physical interaction between the T cell receptor (TCR) and its cognate antigen causes T cells to activate and participate in the immune response. Understanding this physical interaction is important in predicting TCR binding to a target epitope, as well as potential cross-reactivity. Here, we propose a way of collecting informative features of the binding interface from homology models of T cell receptor-peptide-major histocompatibility complex (TCR-pMHC) complexes. The information collected from these structures is sufficient to discriminate binding from non-binding TCR-pMHC pairs in multiple independent datasets. The classifier is limited by the number of crystal structures available for the homology modelling and by the size of the training set. However, the classifier shows comparable performance to sequence-based classifiers requiring much larger training sets.

Single-Cell RNA Sequencing Approaches for Tracing T Cell Development

T cell development occurs in the thymus, where uncommitted progenitors are directed into a range of sublineages with distinct functions. The goal is to generate a TCR repertoire diverse enough to recognize potential pathogens while remaining tolerant of self. Decades of intensive research have characterized the transcriptional programs controlling critical differentiation checkpoints at the population level. However, greater precision regarding how and when these programs orchestrate differentiation at the single-cell level is required. Single-cell RNA sequencing approaches are now being brought to bear on this question, to track the identity of cells and analyze their gene expression programs at a resolution not previously possible. In this review, we discuss recent advances in the application of these technologies that have the potential to yield unprecedented insight to T cell development.

Single-cell sequencing links multiregional immune landscapes and tissue-resident T cells in ccRCC to tumor topology and therapy efficacy

Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrated, but the effect of immune heterogeneity on clinical outcome in ccRCC has not been fully characterized. Here we perform paired single-cell RNA (scRNA) and T cell receptor (TCR) sequencing of 167,283 cells from multiple tumor regions, lymph node, normal kidney, and peripheral blood of two immune checkpoint blockade (ICB)-naïve and four ICB-treated patients to map the ccRCC immune landscape. We detect extensive heterogeneity within and between patients, with enrichment of CD8A+ tissue-resident T cells in a patient responsive to ICB and tumor-associated macrophages (TAMs) in a resistant patient. A TCR trajectory framework suggests distinct T cell differentiation pathways between patients responding and resistant to ICB. Finally, scRNA-derived signatures of tissue-resident T cells and TAMs are associated with response to ICB and targeted therapies across multiple independent cohorts. Our study establishes a multimodal interrogation of the cellular programs underlying therapeutic efficacy in ccRCC.

A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity

T cell receptor (TCR) antigen-specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide-major histocompatibility complex) interactions and a neural network-based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen-specific interactions for basic immunological research and clinical immune monitoring.

Contribution of T Cell Receptor Alpha and Beta CDR3, MHC Typing, V and J Genes to Peptide Binding Prediction

Introduction

Predicting the binding specificity of T Cell Receptors (TCR) to MHC-peptide complexes (pMHCs) is essential for the development of repertoire-based biomarkers. This affinity may be affected by different components of the TCR, the peptide, and the MHC allele. Historically, the main element used in TCR-peptide binding prediction was the Complementarity Determining Region 3 (CDR3) of the beta chain. However, recently the contribution of other components, such as the alpha chain and the other V gene CDRs has been suggested. We use a highly accurate novel deep learning-based TCR-peptide binding predictor to assess the contribution of each component to the binding.

Methods

We have previously developed ERGO-I (pEptide tcR matchinG predictiOn), a sequence-based T-cell receptor (TCR)-peptide binding predictor that employs natural language processing (NLP) -based methods. We improved it to create ERGO-II by adding the CDR3 alpha segment, the MHC typing, V and J genes, and T cell type (CD4+ or CD8+) as to the predictor. We then estimate the contribution of each component to the prediction.

Results and Discussion

ERGO-II provides for the first time high accuracy prediction of TCR-peptide for previously unseen peptides. For most tested peptides and all measures of binding prediction accuracy, the main contribution was from the beta chain CDR3 sequence, followed by the beta chain V and J and the alpha chain, in that order. The MHC allele was the least contributing component. ERGO-II is accessible as a webserver at http://tcr2.cs.biu.ac.il/ and as a standalone code at https://github.com/IdoSpringer/ERGO-II.

STARTRAC analyses of scRNAseq data from tumor models reveal T cell dynamics and therapeutic targets

Single-cell RNA sequencing is a powerful tool to examine cellular heterogeneity, novel markers and target genes, and therapeutic mechanisms in human cancers and animal models. Here, we analyzed single-cell RNA sequencing data of T cells obtained from multiple mouse tumor models by PCA-based subclustering coupled with TCR tracking using the STARTRAC algorithm. This approach revealed various differentiated T cell subsets and activation states, and a correspondence of T cell subsets between human and mouse tumors. STARTRAC analyses demonstrated peripheral T cell subsets that were developmentally connected with tumor-infiltrating CD8⁺ cells, CD4⁺ Th1 cells, and T reg cells. In addition, large amounts of paired TCRα/β sequences enabled us to identify a specific enrichment of paired public TCR clones in tumor. Finally, we identified CCR8 as a tumor-associated T reg cell marker that could preferentially deplete tumor-associated T reg cells. We showed that CCR8-depleting antibody treatment provided therapeutic benefit in CT26 tumors and synergized with anti–PD-1 treatment in MC38 and B16F10 tumor models.

Deep generative selection models of T and B cell receptor repertoires with soNNia

Subclasses of lymphocytes carry different functional roles to work together and produce an immune response and lasting immunity. Additionally to these functional roles, T and B cell lymphocytes rely on the diversity of their receptor chains to recognize different pathogens. The lymphocyte subclasses emerge from common ancestors generated with the same diversity of receptors during selection processes. Here, we leverage biophysical models of receptor generation with machine learning models of selection to identify specific sequence features characteristic of functional lymphocyte repertoires and subrepertoires. Specifically, using only repertoire-level sequence information, we classify CD4+ and CD8+ T cells, find correlations between receptor chains arising during selection, and identify T cell subsets that are targets of pathogenic epitopes. We also show examples of when simple linear classifiers do as well as more complex machine learning methods.

Engineering soluble T-cell receptors for therapy

Immunotherapy approaches that target peptide-human leukocyte antigen (pHLA) complexes are becoming highly attractive because of their potential to access virtually all foreign and cellular proteins. For this reason, there has been considerable interest in the development of the natural ligand for pHLA, the T-cell receptor (TCR), as a soluble drug to target disease-associated pHLA presented at the cell surface. However, native TCR stability is suboptimal for soluble drug development, and natural TCRs generally have weak affinities for pHLAs, limiting their potential to reach efficacious receptor occupancy levels as soluble drugs. To overcome these limitations and make full use of the TCR as a soluble drug platform, several protein engineering solutions have been applied to TCRs to enhance both their stability and affinity, with a focus on retaining target specificity and selectivity. Here, we review these advances and look to the future for the next generation of soluble TCR-based therapies that can target monomorphic HLA-like proteins presenting both peptide and nonpeptide antigens.

Dynamics of thymus function and T cell receptor repertoire breadth in health and disease

T cell recognition of unknown antigens relies on the tremendous diversity of the T cell receptor (TCR) repertoire; generation of which can only occur in the thymus. TCR repertoire breadth is thus critical for not only coordinating the adaptive response against pathogens but also for mounting a response against malignancies. However, thymic function is exquisitely sensitive to negative stimuli, which can come in the form of acute insult, such as that caused by stress, infection, or common cancer therapies; or chronic damage such as the progressive decline in thymic function with age. Whether it be prolonged T cell deficiency after hematopoietic cell transplantation (HCT) or constriction in the breadth of the peripheral TCR repertoire with age; these insults result in poor adaptive immune responses. In this review, we will discuss the importance of thymic function for generation of the TCR repertoire and how acute and chronic thymic damage influences immune health. We will also discuss methods that are used to measure thymic function in patients and strategies that have been developed to boost thymic function.

Selection influences naive CD8+ TCR-β repertoire sharing

Within each individual, the adaptive immune system generates a repertoire of cells expressing receptors capable of recognizing diverse potential pathogens. The theoretical diversity of the T-cell receptor (TCR) repertoire exceeds the actual size of the T-cell population in an individual by several orders of magnitude - making the observation of identical TCRs in different individuals extremely improbable if all receptors were equally likely. Despite this disparity between the theoretical and the realized diversity of the repertoire, these 'public' receptor sequences have been identified in autoimmune, cancer and pathogen interaction contexts. Biased generation processes explain the presence of public TCRs in the naive repertoire, but do not adequately explain the different abundances of these public TCRs. We investigate and characterize the distribution of genomic TCR-β sequences of naive CD8+ T cells from three genetically identical mice, comparing non-productive (non-functional sequences) and productive sequences. We find public TCR-β sequences at higher abundances compared with unshared sequences in the productive, but not in the non-productive, repertoire. We show that neutral processes such as recombination biases, codon degeneracy and generation probability do not fully account for these differences, and conclude that thymic or peripheral selection plays an important role in increasing the abundances of public TCR-β sequences.

Predicting Cross-Reactivity and Antigen Specificity of T Cell Receptors

Adaptive immune recognition is mediated by specific interactions between heterodimeric T cell receptors (TCRs) and their cognate peptide-MHC (pMHC) ligands, and the methods to accurately predict TCR:pMHC interaction would have profound clinical, therapeutic and pharmaceutical applications. Herein, we review recent developments in predicting cross-reactivity and antigen specificity of TCR recognition. We discuss current experimental and computational approaches to investigate cross-reactivity and antigen-specificity of TCRs and highlight how integrating kinetic, biophysical and structural features may offer valuable insights in modeling immunogenicity. We further underscore the close inter-relationship of these two interconnected notions and the need to investigate each in the light of the other for a better understanding of T cell responsiveness for the effective clinical applications.

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.

T cell antigen discovery

T cells respond to threats in an antigen-specific manner using T cell receptors (TCRs) that recognize short peptide antigens presented on major histocompatibility complex (MHC) proteins. The TCR-peptide-MHC interaction mediated between a T cell and its target cell dictates its function and thereby influences its role in disease. A lack of approaches for antigen discovery has limited the fundamental understanding of the antigenic landscape of the overall T cell response. Recent advances in high-throughput sequencing, mass cytometry, microfluidics and computational biology have led to a surge in approaches to address the challenge of T cell antigen discovery. Here, we summarize the scope of this challenge, discuss in depth the recent exciting work and highlight the outstanding questions and remaining technical hurdles in this field.

Structure of MHC-Independent TCRs and Their Recognition of Native Antigen CD155

During normal T cell development in the thymus, αβ TCRs signal immature thymocytes to differentiate into mature T cells by binding to peptide-MHC ligands together with CD4/CD8 coreceptors. Conversely, in MHC and CD4/CD8 coreceptor-deficient mice, the thymus generates mature T cells expressing MHC-independent TCRs that recognize native conformational epitopes rather than linear antigenic-peptides presented by MHC. To date, no structural information of MHC-independent TCRs is available, and their structural recognition of non-MHC ligand remains unknown. To our knowledge in this study, we determined the first structures of two murine MHC-independent TCRs (A11 and B12A) that bind with high nanomolar affinities to mouse adhesion receptor CD155. Solution binding demonstrated the Vαβ-domain is responsible for MHC-independent B12A recognition of its ligand. Analysis of A11 and B12A sequences against various MHC-restricted and -independent TCR sequence repertoires showed that individual V-genes of A11 and B12A did not exhibit preference against MHC-restriction. Likewise, CDR3 alone did not discriminate against MHC binding, suggesting VDJ recombination together with Vα/Vβ pairing determine their MHC-independent specificity for CD155. The structures of A11 and B12A TCR are nearly identical to those of MHC-restricted TCR, including the conformations of CDR1 and 2. Mutational analysis, together with negative-staining electron microscopy images, showed that the CDR regions of A11 and B12A recognized epitopes on D1 domain of CD155, a region also involved in CD155 binding to poliovirus and Tactile in human. Taken together, MHC-independent TCRs adopt canonical TCR structures to recognize native Ags, highlighting the importance of thymic selection in determining TCR ligand specificity.