RTCR: a pipeline for complete and accurate recovery of T cell repertoires from high throughput sequencing data

TCRosetta: An Integrated Analysis and Annotation Platform for T-cell Receptor Sequences

T cells and T-cell receptors (TCRs) are essential components of the adaptive immune system. Characterization of the TCR repertoire offers a promising and highly informative source for understanding the functions of T cells in the immune response and immunotherapy. Although TCR repertoire studies have attracted much attention, there are few online servers available for TCR repertoire analysis, especially for TCR sequence annotation or advanced analyses. Therefore, we developed TCRosetta, a comprehensive online server that integrates analytical methods for TCR repertoire analysis and visualization. TCRosetta combines general feature analysis, large-scale sequence clustering, network construction, peptide-TCR binding prediction, generation probability calculation, and k-mer motif analysis for TCR sequences, making TCR data analysis as simple as possible. The TCRosetta server accepts multiple input data formats and can analyze ∼ 20,000 TCR sequences in less than 3 min. TCRosetta is the most comprehensive web server available for TCR repertoire analysis and is freely available at https://guolab.wchscu.cn/TCRosetta/.

Development and characterization of human T-cell receptor (TCR) alpha and beta clones' library as biological standards and resources for TCR sequencing and engineering

Characterization of T-cell receptors (TCRs) repertoire was revolutionized by next-generation sequencing technologies; however, standardization using biological controls to facilitate precision of current alignment and assembly tools remains a challenge. Additionally, availability of TCR libraries for off-the-shelf cloning and engineering TCR-specific T cells is a valuable resource for TCR-based immunotherapies. We established nine human TCR α and β clones that were evaluated using the 5'-rapid amplification of cDNA ends-like RNA-based TCR sequencing on the Illumina platform. TCR sequences were extracted and aligned using MiXCR, TRUST4, and CATT to validate their sensitivity and specificity and to validate library preparation methods. The correlation between actual and expected TCR ratios within libraries confirmed accuracy of the approach. Our findings established the development of biological standards and library of TCR clones to be leveraged in TCR sequencing and engineering. The remaining human TCR clones' libraries for a more diverse biological control will be generated.

The TCR assigns naive T cells to a preferred lymph node

Naive T cells recirculate between the spleen and lymph nodes where they mount immune responses when meeting dendritic cells presenting foreign antigen. As this may happen anywhere, naive T cells ought to visit all lymph nodes. Here, deep sequencing almost-complete TCR repertoires led to a comparison of different lymph nodes within and between individual mice. We find strong evidence for a deterministic CD4/CD8 lineage choice and a consistent spatial structure. Specifically, some T cells show a preference for one or multiple lymph nodes, suggesting that their TCR interacts with locally presented (self-)peptides. These findings are mirrored in TCR-transgenic mice showing localized CD69 expression, retention, and cell division. Thus, naive T cells intermittently sense antigenically dissimilar niches, which is expected to affect their homeostatic competition.

EBV T-cell immunotherapy generated by peptide selection has enhanced effector functionality compared to LCL stimulation

Adoptive immunotherapy with Epstein-Barr virus (EBV)-specific T cells is an effective treatment for relapsed or refractory EBV-induced post-transplant lymphoproliferative disorders (PTLD) with overall survival rates of up to 69%. EBV-specific T cells have been conventionally made by repeated stimulation with EBV-transformed lymphoblastoid cell lines (LCL), which act as antigen-presenting cells. However, this process is expensive, takes many months, and has practical risks associated with live virus. We have developed a peptide-based, virus-free, serum-free closed system to manufacture a bank of virus-specific T cells (VST) for clinical use. We compared these with standard LCL-derived VST using comprehensive characterization and potency assays to determine differences that might influence clinical benefits. Multi-parameter flow cytometry revealed that peptide-derived VST had an expanded central memory population and less exhaustion marker expression than LCL-derived VST. A quantitative HLA-matched allogeneic cytotoxicity assay demonstrated similar specific killing of EBV-infected targets, though peptide-derived EBV T cells had a significantly higher expression of antiviral cytokines and degranulation markers after antigen recall. High-throughput T cell receptor-beta (TCRβ) sequencing demonstrated oligoclonal repertoires, with more matches to known EBV-binding complementary determining region 3 (CDR3) sequences in peptide-derived EBV T cells. Peptide-derived products showed broader and enhanced specificities to EBV nuclear antigens (EBNAs) in both CD8 and CD4 compartments, which may improve the targeting of highly expressed latency antigens in PTLD. Importantly, peptide-based isolation and expansion allows rapid manufacture and significantly increased product yield over conventional LCL-based approaches.

The Memory-CD8+-T-Cell Response to Conserved Influenza Virus Epitopes in Mice Is Not Influenced by Time Since Previous Infection

To protect older adults against influenza A virus (IAV) infection, innovative strategies are imperative to overcome the decrease in protective immune response with age. One approach involves the boosting of CD8+ T cells at middle age that were previously induced by natural infection. At this stage, the immune system is still fit. Given the high conservation of T-cell epitopes within internal viral proteins, such a response may confer lasting protection against evolving influenza strains at older age, also reducing the high number of influenza immunizations currently required. However, at the time of vaccination, some individuals may have been more recently exposed to IAV than others, which could affect the T-cell response. We therefore investigated the fundamental principle of how the interval between the last infection and booster immunization during middle age influences the CD8+ T-cell response. To model this, female mice were infected at either 6 or 9 months of age and subsequently received a heterosubtypic infection booster at middle age (12 months). Before the booster infection, 6-month-primed mice displayed lower IAV-specific CD8+ T-cell responses in the spleen and lung than 9-month-primed mice. Both groups were better protected against the subsequent heterosubtypic booster infection compared to naïve mice. Notably, despite the different CD8+ T-cell levels between the 6-month- and 9-month-primed mice, we observed comparable responses after booster infection, based on IFNγ responses, and IAV-specific T-cell frequencies and repertoire diversity. Lung-derived CD8+ T cells of 6- and 9-month-primed mice expressed similar levels of tissue-resident memory-T-cell markers 30 days post booster infection. These data suggest that the IAV-specific CD8+ T-cell response after boosting is not influenced by the time post priming.

Machine learning analysis of the T cell receptor repertoire identifies sequence features of self-reactivity

The T cell receptor (TCR) determines specificity and affinity for both foreign and self-peptides presented by the major histocompatibility complex (MHC). Although the strength of TCR interactions with self-pMHC impacts T cell function, it has been challenging to identify TCR sequence features that predict T cell fate. To discern patterns distinguishing TCRs from naive CD4+ T cells with low versus high self-reactivity, we used data from 42 mice to train a machine learning (ML) algorithm that identifies population-level differences between TCRβ sequence sets. This approach revealed that weakly self-reactive T cell populations were enriched for longer CDR3β regions and acidic amino acids. We tested our ML predictions of self-reactivity using retrogenic mice with fixed TCRβ sequences. Extrapolating our analyses to independent datasets, we predicted high self-reactivity for regulatory T cells and slightly reduced self-reactivity for T cells responding to chronic infections. Our analyses suggest a potential trade-off between TCR repertoire diversity and self-reactivity. A record of this paper's transparent peer review process is included in the supplemental information.

Human adipose tissue as a major reservoir of cytomegalovirus-reactive T cells

Introduction

Cytomegalovirus (CMV) is a common herpesvirus with a high prevalence worldwide. After the acute infection phase, CMV can remain latent in several tissues. CD8 T cells in the lungs and salivary glands mainly control its reactivation control. White adipose tissue (WAT) contains a significant population of memory T cells reactive to viral antigens, but CMV specificity has mainly been studied in mouse WAT. Therefore, we obtained blood, omental WAT (oWAT), subcutaneous WAT (sWAT), and liver samples from 11 obese donors to characterize the human WAT adaptive immune landscape from a phenotypic and immune receptor specificity perspective.

Methods

We performed high-throughput sequencing of the T cell receptor (TCR) locus to analyze tissue and blood TCR repertoires of the 11 donors. The presence of TCRs specific to CMV epitopes was tested through ELISpot assays. Moreover, phenotypic characterization of T cells was carried out through flow cytometry.

Results

High-throughput sequencing analyses revealed that tissue TCR repertoires in oWAT, sWAT, and liver samples were less diverse and dominated by hyperexpanded clones when compared to blood samples. Additionally, we predicted the presence of TCRs specific to viral epitopes, particularly from CMV, which was confirmed by ELISpot assays. Remarkably, we found that oWAT has a higher proportion of CMV-reactive T cells than blood or sWAT. Finally, flow cytometry analyses indicated that most WAT-infiltrated lymphocytes were tissue-resident effector memory CD8 T cells.

Discussion

Overall, these findings postulate human oWAT as a major reservoir of CMV-specific T cells, presumably for latent viral reactivation control. This study enhances our understanding of the adaptive immune response in human WAT and highlights its potential role in antiviral defense.

Modified influenza M158-66 peptide vaccination induces non-relevant T-cells and may enhance pathology after challenge

CD8 + T cells are promising targets for vaccination against influenza A virus (IAV) infection. Their induction via peptide vaccination is not trivial, because peptides are weakly immunogenic. One strategy to overcome this is by vaccination with chemically enhanced altered peptide ligands (CPLs), which have improved MHC-binding and immunogenicity. It remains unknown how peptide-modification affects the resulting immune response. We studied the effect of CPLs derived from the influenza M158-66 epitope (GILGFVFTL) on the T-cell response. In HLA-A2*0201 transgenic mice, CPL-vaccination led to higher T-cell frequencies, but only a small percentage of the induced T cells recognized the GILG-wildtype (WT) peptide. CPL-vaccination resulted in a lower richness of the GILG-WT-specific T-cell repertoire and no improved protection against IAV-infection compared to GILG-WT peptide-vaccination. One CPL even appeared to enhance pathology after IAV-challenge. CPL-vaccination thus induces T cells not targeting the original peptide, which may lead to potential unwanted side effects.

On the feasibility of using TCR sequencing to follow a vaccination response - lessons learned

T cells recognize pathogens by their highly specific T-cell receptor (TCR), which can bind small fragments of an antigen presented on the Major Histocompatibility Complex (MHC). Antigens that are provided through vaccination cause specific T cells to respond by expanding and forming specific memory to combat a future infection. Quantification of this T-cell response could improve vaccine monitoring or identify individuals with a reduced ability to respond to a vaccination. In this proof-of-concept study we use longitudinal sequencing of the TCRβ repertoire to quantify the response in the CD4+ memory T-cell pool upon pneumococcal conjugate vaccination. This comes with several challenges owing to the enormous size and diversity of the T-cell pool, the limited frequency of vaccine-specific TCRs in the total repertoire, and the variation in sample size and quality. We defined quantitative requirements to classify T-cell expansions and identified critical parameters that aid in reliable analysis of the data. In the context of pneumococcal conjugate vaccination, we were able to detect robust T-cell expansions in a minority of the donors, which suggests that the T-cell response against the conjugate in the pneumococcal vaccine is small and/or very broad. These results indicate that there is still a long way to go before TCR sequencing can be reliably used as a personal biomarker for vaccine-induced protection. Nevertheless, this study highlights the importance of having multiple samples containing sufficient T-cell numbers, which will support future studies that characterize T-cell responses using longitudinal TCR sequencing.

Compartmentalization and persistence of dominant (regulatory) T cell clones indicates antigen skewing in juvenile idiopathic arthritis

Autoimmune inflammation is characterized by tissue infiltration and expansion of antigen-specific T cells. Although this inflammation is often limited to specific target tissues, it remains yet to be explored whether distinct affected sites are infiltrated with the same, persistent T cell clones. Here, we performed CyTOF analysis and T cell receptor (TCR) sequencing to study immune cell composition and (hyper-)expansion of circulating and joint-derived Tregs and non-Tregs in juvenile idiopathic arthritis (JIA). We studied different joints affected at the same time, as well as over the course of relapsing-remitting disease. We found that the composition and functional characteristics of immune infiltrates are strikingly similar between joints within one patient, and observed a strong overlap between dominant T cell clones, especially Treg, of which some could also be detected in circulation and persisted over the course of relapsing-remitting disease. Moreover, these T cell clones were characterized by a high degree of sequence similarity, indicating the presence of TCR clusters responding to the same antigens. These data suggest that in localized autoimmune disease, there is autoantigen-driven expansion of both Teffector and Treg clones that are highly persistent and are (re)circulating. These dominant clones might represent interesting therapeutic targets.

T-cell repertoire diversity: friend or foe for protective antitumor response?

Profiling the T-Cell Receptor (TCR) repertoire is establishing as a potent approach to investigate autologous and treatment-induced antitumor immune response. Technical and computational breakthroughs, including high throughput next-generation sequencing (NGS) approaches and spatial transcriptomics, are providing unprecedented insight into the mechanisms underlying antitumor immunity. A precise spatiotemporal variation of T-cell repertoire, which dynamically mirrors the functional state of the evolving host-cancer interaction, allows the tracking of the T-cell populations at play, and may identify the key cells responsible for tumor eradication, the evaluation of minimal residual disease and the identification of biomarkers of response to immunotherapy. In this review we will discuss the relationship between global metrics characterizing the TCR repertoire such as T-cell clonality and diversity and the resultant functional responses. In particular, we will explore how specific TCR repertoires in cancer patients can be predictive of prognosis or response to therapy and in particular how a given TCR re-arrangement, following immunotherapy, can predict a specific clinical outcome. Finally, we will examine current improvements in terms of T-cell sequencing, discussing advantages and challenges of current methodologies.

T-Cell Receptor Repertoire Sequencing and Its Applications: Focus on Infectious Diseases and Cancer

The immune system is a dynamic feature of each individual and a footprint of our unique internal and external exposures. Indeed, the type and level of exposure to physical and biological agents shape the development and behavior of this complex and diffuse system. Many pathological conditions depend on how our immune system responds or does not respond to a pathogen or a disease or on how the regulation of immunity is altered by the disease itself. T-cells are important players in adaptive immunity and, together with B-cells, define specificity and monitor the internal and external signals that our organism perceives through its specific receptors, TCRs and BCRs, respectively. Today, high-throughput sequencing (HTS) applied to the TCR repertoire has opened a window of opportunity to disclose T-cell repertoire development and behavior down to the clonal level. Although TCR repertoire sequencing is easily accessible today, it is important to deeply understand the available technologies for choosing the best fit for the specific experimental needs and questions. Here, we provide an updated overview of TCR repertoire sequencing strategies, providers and applications to infectious diseases and cancer to guide researchers’ choice through the multitude of available options. The possibility of extending the TCR repertoire to HLA characterization will be of pivotal importance in the near future to understand how specific HLA genes shape T-cell responses in different pathological contexts and will add a level of comprehension that was unthinkable just a few years ago.

Techniques for Profiling the Cellular Immune Response and Their Implications for Interventional Oncology

In recent years there has been increased interest in using the immune contexture of the primary tumors to predict the patient's prognosis. The tumor microenvironment of patients with cancers consists of different types of lymphocytes, tumor-infiltrating leukocytes, dendritic cells, and others. Different technologies can be used for the evaluation of the tumor microenvironment, all of which require a tissue or cell sample. Image-guided tissue sampling is a cornerstone in the diagnosis, stratification, and longitudinal evaluation of therapeutic efficacy for cancer patients receiving immunotherapies. Therefore, interventional radiologists (IRs) play an essential role in the evaluation of patients treated with systemically administered immunotherapies. This review provides a detailed description of different technologies used for immune assessment and analysis of the data collected from the use of these technologies. The detailed approach provided herein is intended to provide the reader with the knowledge necessary to not only interpret studies containing such data but also design and apply these tools for clinical practice and future research studies.

Machine Learning Approaches to TCR Repertoire Analysis

Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects.

How Naive T-Cell Clone Counts Are Shaped By Heterogeneous Thymic Output and Homeostatic Proliferation

The specificity of T cells is that each T cell has only one T cell receptor (TCR). A T cell clone represents a collection of T cells with the same TCR sequence. Thus, the number of different T cell clones in an organism reflects the number of different T cell receptors (TCRs) that arise from recombination of the V(D)J gene segments during T cell development in the thymus. TCR diversity and more specifically, the clone abundance distribution, are important factors in immune functions. Specific recombination patterns occur more frequently than others while subsequent interactions between TCRs and self-antigens are known to trigger proliferation and sustain naive T cell survival. These processes are TCR-dependent, leading to clone-dependent thymic export and naive T cell proliferation rates. We describe the heterogeneous steady-state population of naive T cells (those that have not yet been antigenically triggered) by using a mean-field model of a regulated birth-death-immigration process. After accounting for random sampling, we investigate how TCR-dependent heterogeneities in immigration and proliferation rates affect the shape of clone abundance distributions (the number of different clones that are represented by a specific number of cells, or “clone counts”). By using reasonable physiological parameter values and fitting predicted clone counts to experimentally sampled clone abundances, we show that realistic levels of heterogeneity in immigration rates cause very little change to predicted clone-counts, but that modest heterogeneity in proliferation rates can generate the observed clone abundances. Our analysis provides constraints among physiological parameters that are necessary to yield predictions that qualitatively match the data. Assumptions of the model and potentially other important mechanistic factors are discussed.

Revealing Clonal Responses of Tumor-Reactive T-Cells Through T Cell Receptor Repertoire Analysis

CD8⁺ T cells are the key effector cells that contribute to the antitumor immune response. They comprise various T-cell clones with diverse antigen-specific T-cell receptors (TCRs). Thus, elucidating the overall antitumor responses of diverse T-cell clones is an emerging challenge in tumor immunology. With the recent advancement in next-generation DNA sequencers, comprehensive analysis of the collection of TCR genes (TCR repertoire analysis) is feasible and has been used to investigate the clonal responses of antitumor T cells. However, the immunopathological significance of TCR repertoire indices is still undefined. In this review, we introduce two approaches that facilitate an immunological interpretation of the TCR repertoire data: inter-organ clone tracking analysis and single-cell TCR sequencing. These approaches for TCR repertoire analysis will provide a more accurate understanding of the response of tumor-specific T cells in the tumor microenvironment.

Longitudinal Characterization of the Mumps-Specific HLA-A2 Restricted T-Cell Response after Mumps Virus Infection

Waning of the mumps virus (MuV)-specific humoral response after vaccination has been suggested as a cause for recent mumps outbreaks in vaccinated young adults, although it cannot explain all cases. Moreover, CD8+ T cells may play an important role in the response against MuV; however, little is known about the characteristics and dynamics of the MuV-specific CD8+ T-cell response after MuV infection. Here, we had the opportunity to follow the CD8+ T-cell response to three recently identified HLA-A2*02:01-restricted MuV-specific epitopes from 1.5 to 36 months post-MuV infection in five previously vaccinated and three unvaccinated individuals. The infection-induced CD8+ T-cell response was dominated by T cells specific for the ALDQTDIRV and LLDSSTTRV epitopes, while the response to the GLMEGQIVSV epitope was subdominant. MuV-specific CD8+ T-cell frequencies in the blood declined between 1.5 and 9 months after infection. This decline was not explained by changes in the expression of inhibitory receptors or homing markers. Despite the ongoing changes in the frequencies and phenotype of MuV-specific CD8+ T cells, TCRβ analyses revealed a stable MuV-specific T-cell repertoire over time. These insights in the maintenance of the cellular response against mumps may provide hallmarks for optimizing vaccination strategies towards a long-term cellular memory response.

TCRβ rearrangements without a D segment are common, abundant, and public

The human body detects foreign pathogens by T cells with specific receptors. These are not directly encoded in the genome but generated in a random process that combines small gene segments into functional subunits of the receptor. The β-chain of the T cell receptor is normally composed of three such gene segments. Here we identify a group of T cells that lack the middle segment in their receptor sequence. We find that such sequences are mostly generated before birth, persist over a human lifetime, and, as a result, are excessively shared between individuals.

T cells play an important role in adaptive immunity. An enormous clonal diversity of T cells with a different specificity, encoded by the T cell receptor (TCR), protect the body against infection. Most TCRβ chains are generated from a V, D, and J segment during recombination in the thymus. Although complete absence of the D segment is not easily detectable from sequencing data, we find convincing evidence for a substantial proportion of TCRβ rearrangements lacking a D segment. Additionally, sequences without a D segment are more likely to be abundant within individuals and/or shared between individuals. Our analysis indicates that such sequences are preferentially generated during fetal development and persist within the elderly. Summarizing, TCRβ rearrangements without a D segment are not uncommon, and tend to allow for TCRβ chains with a high abundance in the naive repertoire.

Tools for fundamental analysis functions of TCR repertoires: a systematic comparison

The full set of T cell receptors (TCRs) in an individual is known as his or her TCR repertoire. Defining TCR repertoires under physiological conditions and in response to a disease or vaccine may lead to a better understanding of adaptive immunity and thus has great biological and clinical value. In the past decade, several high-throughput sequencing-based tools have been developed to assign TCRs to germline genes and to extract complementarity-determining region 3 (CDR3) sequences using different algorithms. Although these tools claim to be able to perform the full range of fundamental TCR repertoire analyses, there is no clear consensus of which tool is best suited to particular projects. Here, we present a systematic analysis of 12 available TCR repertoire analysis tools using simulated data, with an emphasis on fundamental analysis functions. Our results shed light on the detailed functions of TCR repertoire analysis tools and may therefore help researchers in the field to choose the right tools for their particular experimental design.

Latent CMV Infection Is Associated With Lower Influenza Virus-Specific Memory T-Cell Frequencies, but Not With an Impaired T-Cell Response to Acute Influenza Virus Infection

Latent infection with cytomegalovirus (CMV) is assumed to contribute to the age-associated decline of the immune system. CMV induces large changes in the T-cell pool and may thereby affect other immune responses. CMV is expected to impact especially older adults, who are already at higher risk of severe disease and hospitalization upon infections such as influenza virus (IAV) infection. Here, we investigated the impact of CMV infection on IAV-specific CD8⁺ T-cell frequencies in healthy individuals (n=96) and the response to IAV infection in older adults (n=72). IAV-specific memory T-cell frequencies were lower in healthy CMV⁺ older individuals compared to healthy CMV^- older individuals. Upon acute IAV infection, CMV serostatus or CMV-specific antibody levels were not negatively associated with IAV-specific T-cell frequencies, function, phenotype or T-cell receptor repertoire diversity. This suggests that specific T-cell responses upon acute IAV infection are not negatively affected by CMV. In addition, we found neither an association between CMV infection and inflammatory cytokine levels in serum during acute IAV infection nor between cytokine levels and the height of the IAV-specific T-cell response upon infection. Finally, CMV infection was not associated with increased severity of influenza-related symptoms. In fact, CMV infection was even associated with increased IAV-specific T-cell responses early upon acute IAV infection. In conclusion, although associated with lower frequencies of memory IAV-specific T cells in healthy individuals, CMV infection does not seem to hamper the induction of a proper T-cell response during acute IAV infection in older adults.

Age and CMV-Infection Jointly Affect the EBV-Specific CD8+ T-Cell Repertoire

CD8+ T cells play an important role in protection against viral infections. With age, changes in the T-cell pool occur, leading to diminished responses against both new and recurring infections in older adults. This is thought to be due to a decrease in both T-cell numbers and T-cell receptor (TCR) diversity. Latent infection with cytomegalovirus (CMV) is assumed to contribute to this age-associated decline of the immune system. The observation that the level of TCR diversity in the total memory T-cell pool stays relatively stable during aging is remarkable in light of the constant input of new antigen-specific memory T cells. What happens with the diversity of the individual antigen-specific T-cell repertoires in the memory pool remains largely unknown. Here we studied the effect of aging on the phenotype and repertoire diversity of CMV-specific and Epstein-Barr virus (EBV)-specific CD8+ T cells, as well as the separate effects of aging and CMV-infection on the EBV-specific T-cell repertoire. Antigen-specific T cells against both persistent viruses showed an age-related increase in the expression of markers associated with a more differentiated phenotype, including KLRG-1, an increase in the fraction of terminally differentiated T cells, and a decrease in the diversity of the T-cell repertoire. Not only age, but also CMV infection was associated with a decreased diversity of the EBV-specific T-cell repertoire. This suggests that both CMV infection and age can impact the T-cell repertoire against other antigens.

iCAT: diagnostic assessment tool of immunological history using high-throughput T-cell receptor sequencing

The pathogen exposure history of an individual is recorded in their T-cell repertoire and can be accessed through the study of T-cell receptors (TCRs) if the tools to identify them were available. For each T-cell, the TCR loci undergoes genetic rearrangement that creates a unique DNA sequence. In theory these unique sequences can be used as biomarkers for tracking T-cell responses and cataloging immunological history. We developed the immune Cell Analysis Tool (iCAT), an R software package that analyzes TCR sequencing data from exposed (positive) and unexposed (negative) samples to identify TCR sequences statistically associated with positive samples. The presence and absence of associated sequences in samples trains a classifier to diagnose pathogen-specific exposure. We demonstrate the high accuracy of iCAT by testing on three TCR sequencing datasets. First, iCAT successfully diagnosed smallpox vaccinated versus naïve samples in an independent cohort of mice with 95% accuracy. Second, iCAT displayed 100% accuracy classifying naïve and monkeypox vaccinated mice. Finally, we demonstrate the use of iCAT on human samples before and after exposure to SARS-CoV-2, the virus behind the COVID-19 global pandemic. We were able to correctly classify the exposed samples with perfect accuracy. These experimental results show that iCAT capitalizes on the power of TCR sequencing to simplify infection diagnostics. iCAT provides the option of a graphical, user-friendly interface on top of usual R interface allowing it to reach a wider audience.

An ultra-sensitive T-cell receptor detection method for TCR-Seq and RNA-Seq data

MOTIVATION

T-cell receptors (TCRs) function to recognize antigens and play vital roles in T-cell immunology. Surveying TCR repertoires by characterizing complementarity-determining region 3 (CDR3) is a key issue. Due to the high diversity of CDR3 and technological limitation, accurate characterization of CDR3 repertoires remains a great challenge.

RESULTS

We propose a computational method named CATT for ultra-sensitive and precise TCR CDR3 sequences detection. CATT can be applied on TCR sequencing, RNA-Seq and single-cell TCR(RNA)-Seq data to characterize CDR3 repertoires. CATT integrated de Bruijn graph-based micro-assembly algorithm, data-driven error correction model and Bayesian inference algorithm, to self-adaptively and ultra-sensitively characterize CDR3 repertoires with high performance. Benchmark results of datasets from in silico and experimental data demonstrated that CATT showed superior recall and precision compared with existing tools, especially for data with short read length and small size and single-cell sequencing data. Thus, CATT will be a useful tool for TCR analysis in researches of cancer and immunology.

AVAILABILITY AND IMPLEMENTATION

http://bioinfo.life.hust.edu.cn/CATT or https://github.com/GuoBioinfoLab/CATT.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Longitudinal analysis of T-cell receptor repertoires reveals persistence of antigen-driven CD4+ and CD8+ T-cell clusters in systemic sclerosis

The T-cell receptor (TCR) is a highly polymorphic surface receptor that allows T-cells to recognize antigenic peptides presented on the major histocompatibility complex (MHC). Changes in the TCR repertoire have been observed in several autoimmune conditions, and these changes are suggested to predispose autoimmunity. Multiple lines of evidence have implied an important role for T-cells in the pathogenesis of Systemic Sclerosis (SSc), a complex autoimmune disease. One of the major questions regarding the roles of T-cells is whether expansion and activation of T-cells observed in the diseases pathogenesis is antigen driven. To investigate the temporal TCR repertoire dynamics in SSc, we performed high-throughput sequencing of CD4⁺ and CD8⁺ TCRβ chains on longitudinal samples obtained from four SSc patients collected over a minimum of two years. Repertoire overlap analysis revealed that samples taken from the same individual over time shared a high number of TCRβ sequences, indicating a clear temporal persistence of the TCRβ repertoire in CD4⁺ as well as CD8⁺ T-cells. Moreover, the TCRβs that were found with a high frequency at one time point were also found with a high frequency at the other time points (even after almost four years), showing that frequencies of dominant TCRβs are largely consistent over time. We also show that TCRβ generation probability and observed TCR frequency are not related in SSc samples, showing that clonal expansion and persistence of TCRβs is caused by antigenic selection rather than convergent recombination. Moreover, we demonstrate that TCRβ diversity is lower in CD4⁺ and CD8⁺ T-cells from SSc patients compared with memory T-cells from healthy individuals, as SSc TCRβ repertoires are largely dominated by clonally expanded persistent TCRβ sequences. Lastly, using "Grouping of Lymphocyte Interactions by Paratope Hotspots" (GLIPH2), we identify clusters of TCRβ sequences with homologous sequences that potentially recognize the same antigens and contain TCRβs that are persist in SSc patients. In conclusion, our results show that CD4⁺ and CD8⁺ T-cells are highly persistent in SSc patients over time, and this persistence is likely a result from antigenic selection. Moreover, persistent TCRs form high similarity clusters with other (non-)persistent sequences that potentially recognize the same epitopes. These data provide evidence for an antigen driven expansion of CD4⁺/CD8⁺ T-cells in SSc.

The Identity Card of T Cells-Clinical Utility of T-cell Receptor Repertoire Analysis in Transplantation

There is a clear medical need to change the current strategy of "one-size-fits-all" immunosuppression for controlling transplant rejection to precision medicine and targeted immune intervention. As T cells play a key role in both undesired graft rejection and protection, a better understanding of the fate and function of both alloreactive graft-deteriorating T cells and those protecting to infections is required. The T-cell receptor (TCR) is the individual identity card of each T cell clone and can help to follow single specificities. In this context, tracking of lymphocytes with certain specificity in blood and tissue in clinical follow up is of especial importance. After overcoming technical limitations of the past, novel molecular technologies opened new avenues of diagnostics. Using advantages of next generation sequencing, a method was established for T-cell tracing by detection of variable TCR region as identifiers of individual lymphocyte clones. The current review describes principles of laboratory and computational methods of TCR repertoire analysis, and gives an overview on applications for the basic understanding of transplant biology and immune monitoring. The review also delineates methodological pitfalls and challenges. With the outlook on prediction of antigens in immune-mediated processes including those of unknown causative pathogens, monitoring the fate and function of individual T cell clones, and the adoptive transfer of protective effector or regulatory T cells, this review highlights the current and future capability of TCR repertoire analysis.

On the viability of unsupervised T-cell receptor sequence clustering for epitope preference

MOTIVATION

The T-cell receptor (TCR) is responsible for recognizing epitopes presented on cell surfaces. Linking TCR sequences to their ability to target specific epitopes is currently an unsolved problem, yet one of great interest. Indeed, it is currently unknown how dissimilar TCR sequences can be before they no longer bind the same epitope. This question is confounded by the fact that there are many ways to define the similarity between two TCR sequences. Here we investigate both issues in the context of TCR sequence unsupervised clustering.

RESULTS

We provide an overview of the performance of various distance metrics on two large independent datasets with 412 and 2835 TCR sequences respectively. Our results confirm the presence of structural distinct TCR groups that target identical epitopes. In addition, we put forward several recommendations to perform unsupervised T-cell receptor sequence clustering.

AVAILABILITY AND IMPLEMENTATION

Source code implemented in Python 3 available at https://github.com/pmeysman/TCRclusteringPaper.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular T-Cell Repertoire Analysis as Source of Prognostic and Predictive Biomarkers for Checkpoint Blockade Immunotherapy

The T cells are key players of the response to checkpoint blockade immunotherapy (CBI) and monitoring the strength and specificity of antitumor T-cell reactivity remains a crucial but elusive component of precision immunotherapy. The entire assembly of T-cell receptor (TCR) sequences accounts for antigen specificity and strength of the T-cell immune response. The TCR repertoire hence represents a “footprint” of the conditions faced by T cells that dynamically evolves according to the challenges that arise for the immune system, such as tumor neo-antigenic load. Hence, TCR repertoire analysis is becoming increasingly important to comprehensively understand the nature of a successful antitumor T-cell response, and to improve the success and safety of current CBI.

The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes

The clone size distribution of the human naive T-cell receptor (TCR) repertoire is an important determinant of adaptive immunity. We estimated the abundance of TCR sequences in samples of naive T cells from blood using an accurate quantitative sequencing protocol. We observe most TCR sequences only once, consistent with the enormous diversity of the repertoire. However, a substantial number of sequences were observed multiple times. We detect abundant TCR sequences even after exclusion of methodological confounders such as sort contamination, and multiple mRNA sampling from the same cell. By combining experimental data with predictions from models we describe two mechanisms contributing to TCR sequence abundance. TCRα abundant sequences can be primarily attributed to many identical recombination events in different cells, while abundant TCRβ sequences are primarily derived from large clones, which make up a small percentage of the naive repertoire, and could be established early in the development of the T-cell repertoire.

Characterization of the ferret TRB locus guided by V, D, J, and C gene expression analysis

The domestic ferret, Mustela putorius furo, is an important mammalian animal model to study human respiratory infection. However, insufficient genomic annotation hampers detailed studies of ferret T cell responses. In this study, we analyzed the published T cell receptor beta (TRB) locus and performed high-throughput sequencing (HTS) of peripheral blood of four healthy adult ferrets to identify expressed V, D, J, and C genes. The HTS data is used as a guide to manually curate the expressed V, D, J, and C genes. The ferret locus appears to be most similar to that of the dog. Like other mammalian TRB loci, the ferret TRB locus contains a library of variable genes located upstream of two D-J-C gene clusters, followed by a (in the ferret non-functional) V gene with an inverted transcriptional orientation. All TRB genes (expressed or not) reported here have been approved by the IMGT/WHO-IUIS nomenclature committee.

Systematic comparative study of computational methods for T-cell receptor sequencing data analysis

High-throughput sequencing technologies have exposed the possibilities for the in-depth evaluation of T-cell receptor (TCR) repertoires. These studies are highly relevant to gain insights into human adaptive immunity and to decipher the composition and diversity of antigen receptors in physiological and disease conditions. The major objective of TCR sequencing data analysis is the identification of V, D and J gene segments, complementarity-determining region 3 (CDR3) sequence extraction and clonality analysis. With the advancement in sequencing technologies, new TCR analysis approaches and programs have been developed. However, there is still a deficit of systematic comparative studies to assist in the selection of an optimal analysis approach. Here, we present a detailed comparison of 10 state-of-the-art TCR analysis tools on samples with different complexities by taking into account many aspects such as clonotype detection [unique V(D)J combination], CDR3 identification or accuracy in error correction. We used our in silico and experimental data sets with known clonalities enabling the identification of potential tool biases. We also established a new strategy, named clonal plane, which allows quantifying and comparing the clonality of multiple samples. Our results provide new insights into the effect of method selection on analysis results, and it will assist users in the selection of an appropriate analysis method.

Bioinformatic methods for cancer neoantigen prediction

Tumor cells accumulate aberrations not present in normal cells, leading to presentation of neoantigens on MHC molecules on their surface. These non-self neoantigens distinguish tumor cells from normal cells to the immune system and are thus targets for cancer immunotherapy. The rapid development of molecular profiling platforms, such as next-generation sequencing, has enabled the generation of large datasets characterizing tumor cells. The simultaneous development of algorithms has enabled rapid and accurate processing of these data. Bioinformatic software tools encoding the algorithms can be strung together in a workflow to identify neoantigens. Here, with a focus on high-throughput sequencing, we review state-of-the art bioinformatic tools along with the steps and challenges involved in neoantigen identification and recognition.

The Human CD4+ T Cell Response against Mumps Virus Targets a Broadly Recognized Nucleoprotein Epitope

Recent outbreaks of mumps among vaccinated young adults have been reported worldwide. Humoral responses against mumps virus (MuV) are well characterized, although no correlate of protection has been elucidated, stressing the need to better understand cellular MuV-specific immunity. In this study, we identified the first MuV T cell epitope, which is derived from the viral nucleoprotein (MuV-N) and was recognized by a cytotoxic/Th1 CD4⁺ T cell clone that was isolated from a mumps case. Moreover, the epitope was predicted to bind a broad variety of common HLA-DRB1 alleles, which was confirmed by the epitope-specific cytotoxic/Th1 CD4⁺ T cell responses observed in multiple mumps cases with various HLA-DRB1 genotypes. The identified epitope is completely conserved among various mumps strains. These findings qualify this promiscuous MuV T cell epitope as a useful tool for further in-depth exploration of MuV-specific T cell immunity after natural mumps virus infection or induced by vaccination.

Mumps outbreaks among vaccinated young adults stress the need for a better understanding of mumps virus (MuV)-induced immunity. Antibody responses to MuV are well characterized, but studies on T cell responses are limited. We recently isolated a MuV-specific CD4⁺ T cell clone by stimulating peripheral blood mononuclear cells (PBMCs) from a mumps case with the viral nucleoprotein (MuV-N). In this study, we further explored the identity and relevance of the epitope recognized by the CD4⁺ T cell clone and ex vivo by T cells in a cohort of mumps cases. Using a two-dimensional matrix peptide pool of 15-mer peptides covering the complete MuV-N, we identified the epitope recognized by the T cell clone as MuV-N_110–124 GTYRLIPNARANLTA, present in a well-conserved region of the viral protein. Upon peptide-specific stimulation, the T cell clone expressed the activation marker CD137 and produced gamma interferon, tumor necrosis factor, and interleukin-10 in a HLA-DR4-restricted manner. Moreover, the CD4⁺ T cells exerted a cytotoxic phenotype and specifically killed cells presenting MuV-N_110–124. Furthermore, the identified peptide is widely applicable to the general population since it is predicted to bind various common HLA-DR molecules, and epitope-specific CD4⁺ T cells displaying cytotoxic/Th1-type properties were found in all tested mumps cases expressing different HLA-DR alleles. This first broadly recognized human MuV-specific CD4⁺ T cell epitope could provide a useful tool to detect and evaluate virus-specific T cell responses upon MuV infection or following vaccination.

IMPORTANCE Recent outbreaks of mumps among vaccinated young adults have been reported worldwide. Humoral responses against mumps virus (MuV) are well characterized, although no correlate of protection has been elucidated, stressing the need to better understand cellular MuV-specific immunity. In this study, we identified the first MuV T cell epitope, which is derived from the viral nucleoprotein (MuV-N) and was recognized by a cytotoxic/Th1 CD4⁺ T cell clone that was isolated from a mumps case. Moreover, the epitope was predicted to bind a broad variety of common HLA-DRB1 alleles, which was confirmed by the epitope-specific cytotoxic/Th1 CD4⁺ T cell responses observed in multiple mumps cases with various HLA-DRB1 genotypes. The identified epitope is completely conserved among various mumps strains. These findings qualify this promiscuous MuV T cell epitope as a useful tool for further in-depth exploration of MuV-specific T cell immunity after natural mumps virus infection or induced by vaccination.

Using T Cell Receptor Repertoires to Understand the Principles of Adaptive Immune Recognition

Adaptive immune recognition is mediated by antigen receptors on B and T cells generated by somatic recombination during lineage development. The high level of diversity resulting from this process posed technical limitations that previously limited the comprehensive analysis of adaptive immune recognition. Advances over the last ten years have produced data and approaches allowing insights into how T cells develop, evolutionary signatures of recombination and selection, and the features of T cell receptors that mediate epitope-specific binding and T cell activation. The size and complexity of these data have necessitated the generation of novel computational and analytical approaches, which are transforming how T cell immunology is conducted. Here we review the development and application of novel biological, theoretical, and computational methods for understanding T cell recognition and discuss the potential for improved models of receptor:antigen interactions.

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.

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

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

Bioinformatics Meets Virology: The European Virus Bioinformatics Center's Second Annual Meeting

The Second Annual Meeting of the European Virus Bioinformatics Center (EVBC), held in Utrecht, Netherlands, focused on computational approaches in virology, with topics including (but not limited to) virus discovery, diagnostics, (meta-)genomics, modeling, epidemiology, molecular structure, evolution, and viral ecology. The goals of the Second Annual Meeting were threefold: (i) to bring together virologists and bioinformaticians from across the academic, industrial, professional, and training sectors to share best practice; (ii) to provide a meaningful and interactive scientific environment to promote discussion and collaboration between students, postdoctoral fellows, and both new and established investigators; (iii) to inspire and suggest new research directions and questions. Approximately 120 researchers from around the world attended the Second Annual Meeting of the EVBC this year, including 15 renowned international speakers. This report presents an overview of new developments and novel research findings that emerged during the meeting.

Quantitative Characterization of the T Cell Receptor Repertoire of Naïve and Memory Subsets Using an Integrated Experimental and Computational Pipeline Which Is Robust, Economical, and Versatile

The T cell receptor (TCR) repertoire can provide a personalized biomarker for infectious and non-infectious diseases. We describe a protocol for amplifying, sequencing, and analyzing TCRs which is robust, sensitive, and versatile. The key experimental step is ligation of a single-stranded oligonucleotide to the 3' end of the TCR cDNA. This allows amplification of all possible rearrangements using a single set of primers per locus. It also introduces a unique molecular identifier to label each starting cDNA molecule. This molecular identifier is used to correct for sequence errors and for effects of differential PCR amplification efficiency, thus producing more accurate measures of the true TCR frequency within the sample. This integrated experimental and computational pipeline is applied to the analysis of human memory and naive subpopulations, and results in consistent measures of diversity and inequality. After error correction, the distribution of TCR sequence abundance in all subpopulations followed a power law over a wide range of values. The power law exponent differed between naïve and memory populations, but was consistent between individuals. The integrated experimental and analysis pipeline we describe is appropriate to studies of T cell responses in a broad range of physiological and pathological contexts.

VDJPipe: a pipelined tool for pre-processing immune repertoire sequencing data

Background

Pre-processing of high-throughput sequencing data for immune repertoire profiling is essential to insure high quality input for downstream analysis. VDJPipe is a flexible, high-performance tool that can perform multiple pre-processing tasks with just a single pass over the data files.

Results

Processing tasks provided by VDJPipe include base composition statistics calculation, read quality statistics calculation, quality filtering, homopolymer filtering, length and nucleotide filtering, paired-read merging, barcode demultiplexing, 5′ and 3′ PCR primer matching, and duplicate reads collapsing. VDJPipe utilizes a pipeline approach whereby multiple processing steps are performed in a sequential workflow, with the output of each step passed as input to the next step automatically. The workflow is flexible enough to handle the complex barcoding schemes used in many immunosequencing experiments. Because VDJPipe is designed for computational efficiency, we evaluated this by comparing execution times with those of pRESTO, a widely-used pre-processing tool for immune repertoire sequencing data. We found that VDJPipe requires <10% of the run time required by pRESTO.

Conclusions

VDJPipe is a high-performance tool that is optimized for pre-processing large immune repertoire sequencing data sets.

T Cell Receptor Profiling in Type 1 Diabetes

PURPOSE OF REVIEW

The genetic susceptibility and dominant protection for type 1 diabetes (T1D) associated with human leukocyte antigen (HLA) haplotypes, along with minor risk variants, have long been thought to shape the T cell receptor (TCR) repertoire and eventual phenotype of autoreactive T cells that mediate β-cell destruction. While autoantibodies provide robust markers of disease progression, early studies tracking autoreactive T cells largely failed to achieve clinical utility.

RECENT FINDINGS

Advances in acquisition of pancreata and islets from T1D organ donors have facilitated studies of T cells isolated from the target tissues. Immunosequencing of TCR α/β-chain complementarity determining regions, along with transcriptional profiling, offers the potential to transform biomarker discovery. Herein, we review recent studies characterizing the autoreactive TCR signature in T1D, emerging technologies, and the challenges and opportunities associated with tracking TCR molecular profiles during the natural history of T1D.

Reconstructing Antibody Repertoires from Error-Prone Immunosequencing Reads

Transforming error-prone immunosequencing datasets into Ab repertoires is a fundamental problem in immunogenomics, and a prerequisite for studies of immune responses. Although various repertoire reconstruction algorithms were released in the last 3 y, it remains unclear how to benchmark them and how to assess the accuracy of the reconstructed repertoires. We describe an accurate IgReC algorithm for constructing Ab repertoires from high-throughput immunosequencing datasets and a new framework for assessing the quality of reconstructed repertoires. Surprisingly, Ab repertoires constructed by IgReC from barcoded immunosequencing datasets in the blind mode (without using information about unique molecular identifiers) improved upon the repertoires constructed by the state-of-the-art tools that use barcoding. This finding suggests that IgReC may alleviate the need to generate repertoires using the barcoding technology (the workhorse of current immunogenomics efforts) because our computational approach to error correction of immunosequencing data is nearly as powerful as the experimental approach based on barcoding.

Overview of methodologies for T-cell receptor repertoire analysis

Background

The T-cell receptor (TCR), located on the surface of T cells, is responsible for the recognition of the antigen-major histocompatibility complex, leading to the initiation of an inflammatory response. Analysing the TCR repertoire may help to gain a better understanding of the immune system features and of the aetiology and progression of diseases, in particular those with unknown antigenic triggers. The extreme diversity of the TCR repertoire represents a major analytical challenge; this has led to the development of specialized methods which aim to characterize the TCR repertoire in-depth. Currently, next generation sequencing based technologies are most widely employed for the high-throughput analysis of the immune cell repertoire.

Results

Here, we report on the latest methodological advancements in the field by describing and comparing the available tools; from the choice of the starting material and library preparation method, to the sequencing technologies and data analysis.

Finally, we provide a practical example and our own experience by reporting some exemplary results from a small internal benchmark study, where current approaches from the literature and the market are employed and compared.

Conclusions

Several valid methods for clonotype identification and TCR repertoire analysis exist, however, a gold standard method for the field has not yet been identified. Depending on the purpose of the scientific study, some approaches may be more suitable than others. Finally, due to possible method specific biases, scientists must be careful when comparing results obtained using different methods.

Electronic supplementary material

The online version of this article (doi:10.1186/s12896-017-0379-9) contains supplementary material, which is available to authorized users.

Quantifiable predictive features define epitope-specific T cell receptor repertoires

T cells are defined by a heterodimeric surface receptor, the T cell receptor (TCR), that mediates recognition of pathogen-associated epitopes through interactions with peptide and major histocompatibility complexes (pMHCs). TCRs are generated by genomic rearrangement of the germline TCR locus, a process termed V(D)J recombination, that has the potential to generate marked diversity of TCRs (estimated to range from 10¹⁵ (ref. 1) to as high as 10⁶¹ (ref. 2) possible receptors). Despite this potential diversity, TCRs from T cells that recognize the same pMHC epitope often share conserved sequence features, suggesting that it may be possible to predictively model epitope specificity. Here we report the in-depth characterization of ten epitope-specific TCR repertoires of CD8⁺ T cells from mice and humans, representing over 4,600 in-frame single-cell-derived TCRαβ sequence pairs from 110 subjects. We developed analytical tools to characterize these epitope-specific repertoires: a distance measure on the space of TCRs that permits clustering and visualization, a robust repertoire diversity metric that accommodates the low number of paired public receptors observed when compared to single-chain analyses, and a distance-based classifier that can assign previously unobserved TCRs to characterized repertoires with robust sensitivity and specificity. Our analyses demonstrate that each epitope-specific repertoire contains a clustered group of receptors that share core sequence similarities, together with a dispersed set of diverse 'outlier' sequences. By identifying shared motifs in core sequences, we were able to highlight key conserved residues driving essential elements of TCR recognition. These analyses provide insights into the generalizable, underlying features of epitope-specific repertoires and adaptive immune recognition.