Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire

Tfh Cells in Health and Immunity: Potential Targets for Systems Biology Approaches to Vaccination

T follicular helper (Tfh) cells are a specialised subset of CD4+ T cells that play a significant role in the adaptive immune response, providing critical help to B cells within the germinal centres (GC) of secondary lymphoid organs. The B cell receptors of GC B cells undergo multiple rounds of somatic hypermutation and affinity maturation within the GC response, a process dependent on cognate interactions with Tfh cells. B cells that receive sufficient help from Tfh cells form antibody-producing long-lived plasma and memory B cells that provide the basis of decades of effective and efficient protection and are considered the gold standard in correlates of protection post-vaccination. However, the T cell response to vaccination has been understudied, and over the last 10 years, exponential improvements in the technological underpinnings of sampling techniques, experimental and analytical tools have allowed multidisciplinary characterisation of the role of T cells and the immune system as a whole. Of particular interest to the field of vaccinology are GCs and Tfh cells, representing a unique target for improving immunisation strategies. Here, we discuss recent insights into the unique journey of Tfh cells from thymus to lymph node during differentiation and their role in the production of high-quality antibody responses as well as their journey back to the periphery as a population of memory cells. Further, we explore their function in health and disease and the power of next-generation sequencing techniques to uncover their potential as modulators of vaccine-induced immunity.

How age and infection history shape the antigen-specific CD8+ T-cell repertoire: Implications for vaccination strategies in older adults

Older adults often show signs of impaired CD8⁺ T‐cell immunity, reflected by weaker responses against new infections and vaccinations, and decreased protection against reinfection. This immune impairment is in part thought to be the consequence of a decrease in both T‐cell numbers and repertoire diversity. If this is indeed the case, a strategy to prevent infectious diseases in older adults could be the induction of protective memory responses through vaccination at a younger age. However, this requires that the induced immune responses are maintained until old age. It is therefore important to obtain insights into the long‐term maintenance of the antigen‐specific T‐cell repertoire. Here, we review the literature on the maintenance of antigen‐experienced CD8⁺ T‐cell repertoires against acute and chronic infections. We describe the complex interactions that play a role in shaping the memory T‐cell repertoire, and the effects of age, infection history, and T‐cell avidity. We discuss the implications of these findings for the development of new vaccination strategies to protect older adults.

immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking

Summary

B- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor repertoires for immunoinformatics tool benchmarking. Therefore, we developed immuneSIM, an R package that allows the simulation of native-like and aberrant synthetic full-length variable region immune receptor sequences by tuning the following immune receptor features: (i) species and chain type (BCR, TCR, single and paired), (ii) germline gene usage, (iii) occurrence of insertions and deletions, (iv) clonal abundance, (v) somatic hypermutation and (vi) sequence motifs. Each simulated sequence is annotated by the complete set of simulation events that contributed to its in silico generation. immuneSIM permits the benchmarking of key computational tools for immune receptor analysis, such as germline gene annotation, diversity and overlap estimation, sequence similarity, network architecture, clustering analysis and machine learning methods for motif detection.

Availability and implementation

The package is available via https://github.com/GreiffLab/immuneSIM and on CRAN at https://cran.r-project.org/web/packages/immuneSIM. The documentation is hosted at https://immuneSIM.readthedocs.io.

Contact

sai.reddy@ethz.ch or victor.greiff@medisin.uio.no

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

UM171-Expanded Cord Blood Transplants Support Robust T Cell Reconstitution with Low Rates of Severe Infections

Rapid T cell reconstitution following hematopoietic stem cell transplantation (HSCT) is essential for protection against infections and has been associated with lower incidence of chronic graft-versus-host disease (cGVHD), relapse, and transplant-related mortality (TRM). While cord blood (CB) transplants are associated with lower rates of cGVHD and relapse, their low stem cell content results in slower immune reconstitution and higher risk of graft failure, severe infections, and TRM. Recently, results of a phase I/II trial revealed that single UM171-expanded CB transplant allowed the use of smaller CB units without compromising engraftment (www.clinicaltrials.gov, NCT02668315). We assessed T cell reconstitution in patients who underwent transplantation with UM171-expanded CB grafts and retrospectively compared it to that of patients receiving unmanipulated CB transplants. While median T cell dose infused was at least 2 to 3 times lower than that of unmanipulated CB, numbers and phenotype of T cells at 3, 6, and 12 months post-transplant were similar between the 2 cohorts. T cell receptor sequencing analyses revealed that UM171 patients had greater T cell diversity and higher numbers of clonotypes at 12 months post-transplant. This was associated with higher counts of naive T cells and recent thymic emigrants, suggesting active thymopoiesis and correlating with the demonstration that UM171 expands common lymphoid progenitors in vitro. UM171 patients also showed rapid virus-specific T cell reactivity and significantly reduced incidence of severe infections. These results suggest that UM171 patients benefit from rapid T cell reconstitution, which likely contributes to the absence of moderate/severe cGVHD, infection-related mortality, and late TRM observed in this cohort.

Immune Literacy: Reading, Writing, and Editing Adaptive Immunity

Advances in reading, writing, and editing DNA are providing unprecedented insights into the complexity of immunological systems. This combination of systems and synthetic biology methods is enabling the quantitative and precise understanding of molecular recognition in adaptive immunity, thus providing a framework for reprogramming immune responses for translational medicine. In this review, we will highlight state-of-the-art methods such as immune repertoire sequencing, immunoinformatics, and immunogenomic engineering and their application toward adaptive immunity. We showcase novel and interdisciplinary approaches that have the promise of transforming the design and breadth of molecular and cellular immunotherapies.

PIRD: Pan Immune Repertoire Database

MOTIVATION

T and B cell receptors (TCRs and BCRs) play a pivotal role in the adaptive immune system by recognizing an enormous variety of external and internal antigens. Understanding these receptors is critical for exploring the process of immunoreaction and exploiting potential applications in immunotherapy and antibody drug design. Although a large number of samples have had their TCR and BCR repertoires sequenced using high-throughput sequencing in recent years, very few databases have been constructed to store these kinds of data. To resolve this issue, we developed a database.

RESULTS

We developed a database, the Pan Immune Repertoire Database (PIRD), located in China National GeneBank (CNGBdb), to collect and store annotated TCR and BCR sequencing data, including from Homo sapiens and other species. In addition to data storage, PIRD also provides functions of data visualization and interactive online analysis. Additionally, a manually curated database of TCRs and BCRs targeting known antigens (TBAdb) was also deposited in PIRD.

AVAILABILITY AND IMPLEMENTATION

PIRD can be freely accessed at https://db.cngb.org/pird.

Magnitude and Dynamics of the T-Cell Response to SARS-CoV-2 Infection at Both Individual and Population Levels

T cells are involved in the early identification and clearance of viral infections and also support the development of antibodies by B cells. This central role for T cells makes them a desirable target for assessing the immune response to SARS-CoV-2 infection. Here, we combined two high-throughput immune profiling methods to create a quantitative picture of the T-cell response to SARS-CoV-2. First, at the individual level, we deeply characterized 3 acutely infected and 58 recovered COVID-19 subjects by experimentally mapping their CD8 T-cell response through antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I presented viral peptides (class II data in a forthcoming study). Then, at the population level, we performed T-cell repertoire sequencing on 1,815 samples (from 1,521 COVID-19 subjects) as well as 3,500 controls to identify shared "public" T-cell receptors (TCRs) associated with SARS-CoV-2 infection from both CD8 and CD4 T cells. Collectively, our data reveal that CD8 T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the T-cell response to SARS-CoV-2 peaks about one to two weeks after infection and is detectable for at least several months after recovery. As an application of these data, we trained a classifier to diagnose SARS-CoV-2 infection based solely on TCR sequencing from blood samples, and observed, at 99.8% specificity, high early sensitivity soon after diagnosis (Day 3-7 = 85.1% [95% CI = 79.9-89.7]; Day 8-14 = 94.8% [90.7-98.4]) as well as lasting sensitivity after recovery (Day 29+/convalescent = 95.4% [92.1-98.3]). These results demonstrate an approach to reliably assess the adaptive immune response both soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points. This blood-based molecular approach to characterizing the cellular immune response has applications in clinical diagnostics as well as in vaccine development and monitoring.

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.

Ultra-efficient sequencing of T Cell receptor repertoires reveals shared responses in muscle from patients with Myositis

BACKGROUND

Myositis, or idiopathic inflammatory myopathy (IIM), is a group disorders of unknown etiology characterized by the inflammation of skeletal muscle. The role of T cells and their antigenic targets in IIM initiation and progression is poorly understood. T cell receptor (TCR) repertoire sequencing is a powerful approach for characterizing complex T cell responses. However, current TCR sequencing methodologies are complex, expensive, or both, greatly limiting the scale of feasible studies.

METHODS

Here we present Framework Region 3 AmplifiKation sequencing ("FR3AK-seq"), a simplified multiplex PCR-based approach for the ultra-efficient and quantitative analysis of TCR complementarity determining region 3 (CDR3) repertoires. By using minimal primer sets targeting a conserved region immediately upstream of CDR3, undistorted amplicons are analyzed via short read, single-end sequencing. We also introduce the novel algorithm Inferring Sequences via Efficiency Projection and Primer Incorporation ("ISEPPI") for linking CDR3s to their associated variable genes.

FINDINGS

We find that FR3AK-seq is sensitive and quantitative, performing comparably to two different industry standards. FR3AK-seq and ISEPPI were used to efficiently and inexpensively characterize the T cell infiltrates of surgical muscle biopsies obtained from 145 patients with IIM and controls. A cluster of closely related TCRs was identified in samples from patients with sporadic inclusion body myositis (IBM).

INTERPRETATION

The ease and minimal cost of FR3AK-seq removes critical barriers to routine, large-scale TCR CDR3 repertoire analyses, thereby democratizing the quantitative assessment of human TCR repertoires in disease-relevant target tissues. Importantly, discovery of closely related TCRs in muscle from patients with IBM provides evidence for a shared antigen-driven T cell response in this disease of unknown pathogenesis.

FUNDING

This work was supported by NIH grant U24AI118633 and a Prostate Cancer Foundation Young Investigator Award.

Prediction of Specific TCR-Peptide Binding From Large Dictionaries of TCR-Peptide Pairs

Current sequencing methods allow for detailed samples of T cell receptors (TCR) repertoires. To determine from a repertoire whether its host had been exposed to a target, computational tools that predict TCR-epitope binding are required. Currents tools are based on conserved motifs and are applied to peptides with many known binding TCRs. We employ new Natural Language Processing (NLP) based methods to predict whether any TCR and peptide bind. We combined large-scale TCR-peptide dictionaries with deep learning methods to produce ERGO (pEptide tcR matchinG predictiOn), a highly specific and generic TCR-peptide binding predictor. A set of standard tests are defined for the performance of peptide-TCR binding, including the detection of TCRs binding to a given peptide/antigen, choosing among a set of candidate peptides for a given TCR and determining whether any pair of TCR-peptide bind. ERGO reaches similar results to state of the art methods in these tests even when not trained specifically for each test. The software implementation and data sets are available at https://github.com/louzounlab/ERGO. ERGO is also available through a webserver at: http://tcr.cs.biu.ac.il/.

De novo prediction of cancer-associated T cell receptors for noninvasive cancer detection

The adaptive immune system recognizes tumor antigens at an early stage to eradicate cancer cells. This process is accompanied by systemic proliferation of the tumor antigen-specific T lymphocytes. While detection of asymptomatic early-stage cancers is challenging due to small tumor size and limited somatic alterations, tracking peripheral T cell repertoire changes may provide an attractive solution to cancer diagnosis. Here, we developed a deep learning method called DeepCAT to enable de novo prediction of cancer-associated T cell receptors (TCRs). We validated DeepCAT using cancer-specific or non-cancer TCRs obtained from multiple major histocompatibility complex I (MHC-I) multimer-sorting experiments and demonstrated its prediction power for TCRs specific to cancer antigens. We blindly applied DeepCAT to distinguish over 250 patients with cancer from over 600 healthy individuals using blood TCR sequences and observed high prediction accuracy, with area under the curve (AUC) ≥ 0.95 for multiple early-stage cancers. This work sets the stage for using the peripheral blood TCR repertoire for noninvasive cancer detection.

T cell receptor sequence clustering and antigen specificity

There has been increasing interest in the role of T cells and their involvement in cancer, autoimmune and infectious diseases. However, the nature of T cell receptor (TCR) epitope recognition at a repertoire level is not yet fully understood. Due to technological advances a plethora of TCR sequences from a variety of disease and treatment settings has become readily available. Current efforts in TCR specificity analysis focus on identifying characteristics in immune repertoires which can explain or predict disease outcome or progression, or can be used to monitor the efficacy of disease therapy. In this context, clustering of TCRs by sequence to reflect biological similarity, and especially to reflect antigen specificity have become of paramount importance. We review the main TCR sequence clustering methods and the different similarity measures they use, and discuss their performance and possible improvement. We aim to provide guidance for non-specialists who wish to use TCR repertoire sequencing for disease tracking, patient stratification or therapy prediction, and to provide a starting point for those aiming to develop novel techniques for TCR annotation through clustering.

A large-scale database of T-cell receptor beta (TCRβ) sequences and binding associations from natural and synthetic exposure to SARS-CoV-2

We describe the establishment and current content of the ImmuneCODE™ database, which includes hundreds of millions of T-cell Receptor (TCR) sequences from over 1,400 subjects exposed to or infected with the SARS-CoV-2 virus, as well as over 135,000 high-confidence SARS-CoV-2-specific TCRs. This database is made freely available, and the data contained in it can be downloaded and analyzed online or offline to assist with the global efforts to understand the immune response to the SARS-CoV-2 virus and develop new interventions.

Deciphering the TCR Repertoire to Solve the COVID-19 Mystery

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected several millions and killed more than quarter of a million worldwide to date. Important questions have remained unanswered: why some patients develop severe disease, while others do not; and what roles do genetic variabilities play in the individual immune response to this viral infection. Here, we discuss the critical role T cells play in the orchestration of the antiviral response underlying the pathogenesis of the disease, COVID-19. We highlight the scientific rationale for comprehensive and longitudinal TCR analyses in COVID-19 and reason that analyzing TCR repertoire in COVID-19 patients would reveal important findings that may explain the outcome disparity observed in these patients. Finally, we provide a framework describing the different strategies, the advantages, and the challenges involved in obtaining useful TCR repertoire data to advance our fight against COVID-19.

Study of B Cell Repertoire in Patients With Anti-N-Methyl-D-Aspartate Receptor Encephalitis

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is the most common antibody-mediated encephalitis. There are several studies on B cell repertoire of anti-NMDAR encephalitis in Caucasians. Here, the cerebrospinal fluid (CSF) samples of 12 Chinese patients with first-episode anti-NMDAR encephalitis were collected to investigate the B cell receptor (BCR) binding to NMDAR by single cell amplification of BCR and Sanger sequencing. BCR data of healthy persons, and of patients with anti-leucine-rich glioma inactivated 1 (anti-LGI1) encephalitis, multiple sclerosis (MS), and neuromyelitis optica spectrum disorder (NMOSD) from the public databases were used as control. A heavy chain common clone IGHV1-18^*04,IGHD1-26^*01/ IGHD2-2^*03/IGHD2-8^*01, IGHJ3^*02_(CDR3) ARVGSKYGFETFDI was found in 11 of 12 enrolled patients but not in the comparison data set. In addition, 4 shared clonotypes were found among these patients, and three of them contained the common clone. This study also revealed that the antibody gene family usage preference between patients and healthy controls were different, while they had similar antibody mutation rate. Our findings may have potential clinical implications for the diagnosis of anti-NMDAR encephalitis.

Methods for sequence and structural analysis of B and T cell receptor repertoires

B cell receptors (BCRs) and T cell receptors (TCRs) make up an essential network of defense molecules that, collectively, can distinguish self from non-self and facilitate destruction of antigen-bearing cells such as pathogens or tumors. The analysis of BCR and TCR repertoires plays an important role in both basic immunology as well as in biotechnology. Because the repertoires are highly diverse, specialized software methods are needed to extract meaningful information from BCR and TCR sequence data. Here, we review recent developments in bioinformatics tools for analysis of BCR and TCR repertoires, with an emphasis on those that incorporate structural features. After describing the recent sequencing technologies for immune receptor repertoires, we survey structural modeling methods for BCR and TCRs, along with methods for clustering such models. We review downstream analyses, including BCR and TCR epitope prediction, antibody-antigen docking and TCR-peptide-MHC Modeling. We also briefly discuss molecular dynamics in this context.

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.

T cell repertoire remodeling following post-transplant T cell therapy coincides with clinical response

BACKGROUNDImpaired T cell immunity in transplant recipients is associated with infection-related morbidity and mortality. We recently reported the successful use of adoptive T cell therapy (ACT) against drug-resistant/recurrent cytomegalovirus in solid-organ transplant recipients.METHODSIn the present study, we used high-throughput T cell receptor Vβ sequencing and T cell functional profiling to delineate the impact of ACT on T cell repertoire remodeling in the context of pretherapy immunity and ACT products.RESULTSThese analyses indicated that a clinical response was coincident with significant changes in the T cell receptor Vβ landscape after therapy. This restructuring was associated with the emergence of effector memory T cells in responding patients, while nonresponders displayed dramatic pretherapy T cell expansions with minimal change following ACT. Furthermore, immune reconstitution included both adoptively transferred clonotypes and endogenous clonotypes not detected in the ACT products.CONCLUSIONThese observations demonstrate that immune control following ACT requires significant repertoire remodeling, which may be impaired in nonresponders because of the preexisting immune environment. Immunological interventions that can modulate this environment may improve clinical outcomes.TRIAL REGISTRATIONAustralian New Zealand Clinical Trial Registry, ACTRN12613000981729.FUNDINGThis study was supported by funding from the National Health and Medical Research Council, Australia (APP1132519 and APP1062074).

OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs

MOTIVATION

High-throughput sequencing of large immune repertoires has enabled the development of methods to predict the probability of generation by V(D)J recombination of T- and B-cell receptors of any specific nucleotide sequence. These generation probabilities are very non-homogeneous, ranging over 20 orders of magnitude in real repertoires. Since the function of a receptor really depends on its protein sequence, it is important to be able to predict this probability of generation at the amino acid level. However, brute-force summation over all the nucleotide sequences with the correct amino acid translation is computationally intractable. The purpose of this paper is to present a solution to this problem.

RESULTS

We use dynamic programming to construct an efficient and flexible algorithm, called OLGA (Optimized Likelihood estimate of immunoGlobulin Amino-acid sequences), for calculating the probability of generating a given CDR3 amino acid sequence or motif, with or without V/J restriction, as a result of V(D)J recombination in B or T cells. We apply it to databases of epitope-specific T-cell receptors to evaluate the probability that a typical human subject will possess T cells responsive to specific disease-associated epitopes. The model prediction shows an excellent agreement with published data. We suggest that OLGA may be a useful tool to guide vaccine design.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/zsethna/OLGA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

IgM Antibody Repertoire Fingerprints in Mice Are Personalized but Robust to Viral Infection Status

Antibody repertoire sequencing provides a molecular fingerprint of current and past pathogens encountered by the immune system. Most repertoire studies in humans require measuring the B cell response in the blood, resulting in a large bias to the IgM isotype. The extent to which the circulating IgM antibody repertoire correlates to lymphoid tissue-resident B cells in the setting of viral infection remains largely uncharacterized. Therefore, we compared the IgM repertoires from both blood and bone marrow (BM) plasma cells (PCs) following acute or chronic lymphocytic choriomeningitis virus (LCMV) infection in mice. Despite previously reported serum alterations between acute and chronic infection, IgM repertoire signatures based on clonal diversity metrics, public clones, network, and phylogenetic analysis were largely unable to distinguish infection cohorts. Our findings, however, revealed mouse-specific repertoire fingerprints between the blood and PC repertoires irrespective of infection status.

Endocrine Autoimmune Disease as a Fragility of Immune Surveillance against Hypersecreting Mutants

Some endocrine organs are frequent targets of autoimmune attack. Here, we addressed the origin of autoimmune disease from the viewpoint of feedback control. Endocrine tissues maintain mass through feedback loops that balance cell proliferation and removal according to hormone-driven regulatory signals. We hypothesized the existence of a dedicated mechanism that detects and removes mutant cells that missense the signal and therefore hyperproliferate and hypersecrete with potential to disrupt organismal homeostasis. In this mechanism, hypersecreting cells are preferentially eliminated by autoreactive T cells at the cost of a fragility to autoimmune disease. The "autoimmune surveillance of hypersecreting mutants" (ASHM) hypothesis predicts the presence of autoreactive T cells in healthy individuals and the nature of self-antigens as peptides from hormone secretion pathway. It explains why some tissues get prevalent autoimmune disease, whereas others do not and instead show prevalent mutant-expansion disease (e.g., hyperparathyroidism). The ASHM hypothesis is testable, and we discuss experimental follow-up.

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.

VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium

Here, we report an update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens. The update further provides a new database infrastructure featuring two additional analysis modes that facilitate database querying and real-world data analysis. The increased yield of TCR specificity identification methods and the overall increase in the number of studies in the field has allowed us to expand the database more than 5-fold. Furthermore, several new analysis methods are included. For example, batch annotation of TCR repertoire sequencing samples allows for annotating large datasets on-line. Using recently developed bioinformatic methods for TCR motif mining, we have built a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest. These additions enhance the versatility of the VDJdb in the task of exploring T-cell antigen specificities. The database is available at https://vdjdb.cdr3.net.

Maternal T Cells in the Human Placental Villi Support an Allograft Response during Noninfectious Villitis

During human pregnancy, proinflammatory responses in the placenta can cause severe fetal complications, including growth restriction, preterm birth, and stillbirth. Villitis of unknown etiology (VUE), an inflammatory condition characterized by the infiltration of maternal CD8⁺ T cells into the placenta, is hypothesized to be secondary to either a tissue rejection response to the haploidentical fetus or from an undiagnosed infection. In this study, we characterized the global TCR β-chain profile in human T cells isolated from placentae diagnosed with VUE compared with control and infectious villitis-placentae by immunoSEQ. Immunosequencing demonstrated that VUE is driven predominantly by maternal T cell infiltration, which is significantly different from controls and infectious cases; however, these T cell clones show very little overlap between subjects. Mapping TCR clones to common viral epitopes (CMV, EBV, and influenza A) demonstrated that Ag specificity in VUE was equal to controls and significantly lower than CMV-specific clones in infectious villitis. Our data indicate VUE represents an allograft response, not an undetected infection. These observations support the development of screening methods to predict those at risk for VUE and the use of specific immunomodulatory therapies during gestation to improve outcomes in affected fetuses.

A Prospective, Phase 1 Trial of Nivolumab, Ipilimumab, and Radiotherapy in Patients with Advanced Melanoma

PURPOSE

Preclinical data suggest that radiotherapy (RT) is beneficial in combination with immune checkpoint blockade. Clinical trials have explored RT with single-agent immune checkpoint blockade, but no trials have reported RT with the combination of nivolumab and ipilimumab.

PATIENTS AND METHODS

We conducted a phase 1 study of patients with stage IV melanoma receiving nivolumab and ipilimumab with two different dose-fractionation schemes of RT. Patients had at least one melanoma metastasis that would benefit from palliative RT and one metastasis that would not be irradiated. Nivolumab 1 mg/kg + ipilimumab 3 mg/kg and extracranial RT with a dose of 30 Gy in 10 fractions was administered in Cohort A, and then 27 Gy in 3 fractions was administered in Cohort B. The primary outcome was safety.

RESULTS

Twenty patients were treated (10 in each cohort). The rates of treatment-related grade 3-4 adverse events in Cohort A and B were 40% and 30%, respectively. There were no grade ≥3 adverse events attributed to RT. Patients responded to treatment outside of the irradiated volume (Cohort A 5/10; Cohort B 1/9). No evaluable patients had progression of irradiated metastases. Immunologic changes were seen in the peripheral blood with increases in T-cell receptor diversity in some responding patients.

CONCLUSIONS

RT with nivolumab and ipilimumab was safe compared with historical data of nivolumab and ipilimumab alone. Immunologic effects were observed in the peripheral blood. Randomized studies are ongoing to assess whether RT increases the efficacy of nivolumab and ipilimumab.

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.

Epstein-Barr Virus Epitope-Major Histocompatibility Complex Interaction Combined with Convergent Recombination Drives Selection of Diverse T Cell Receptor α and β Repertoires

Recognition modes of individual T cell receptors (TCRs) are well studied, but factors driving the selection of TCR repertoires from primary through persistent human virus infections are less well understood. Using deep sequencing, we demonstrate a high degree of diversity of Epstein-Barr virus (EBV)-specific clonotypes in acute infectious mononucleosis (AIM). Only 9% of unique clonotypes detected in AIM persisted into convalescence; the majority (91%) of unique clonotypes detected in AIM were not detected in convalescence and were seeming replaced by equally diverse "de novo" clonotypes. The persistent clonotypes had a greater probability of being generated than nonpersistent clonotypes due to convergence recombination of multiple nucleotide sequences to encode the same amino acid sequence, as well as the use of shorter complementarity-determining regions 3 (CDR3s) with fewer nucleotide additions (i.e., sequences closer to germ line). Moreover, the two most immunodominant HLA-A2-restricted EBV epitopes, BRLF1109 and BMLF1280, show highly distinct antigen-specific public (i.e., shared between individuals) features. In fact, TCRα CDR3 motifs played a dominant role, while TCRβ played a minimal role, in the selection of TCR repertoire to an immunodominant EBV epitope, BRLF1. This contrasts with the majority of previously reported repertoires, which appear to be selected either on TCRβ CDR3 interactions with peptide/major histocompatibility complex (MHC) or in combination with TCRα CDR3. Understanding of how TCR-peptide-MHC complex interactions drive repertoire selection can be used to develop optimal strategies for vaccine design or generation of appropriate adoptive immunotherapies for viral infections in transplant settings or for cancer.IMPORTANCE Several lines of evidence suggest that TCRα and TCRβ repertoires play a role in disease outcomes and treatment strategies during viral infections in transplant patients and in cancer and autoimmune disease therapy. Our data suggest that it is essential that we understand the basic principles of how to drive optimum repertoires for both TCR chains, α and β. We address this important issue by characterizing the CD8 TCR repertoire to a common persistent human viral infection (EBV), which is controlled by appropriate CD8 T cell responses. The ultimate goal would be to determine if the individuals who are infected asymptomatically develop a different TCR repertoire than those that develop the immunopathology of AIM. Here, we begin by doing an in-depth characterization of both CD8 T cell TCRα and TCRβ repertoires to two immunodominant EBV epitopes over the course of AIM, identifying potential factors that may be driving their selection.

The Landscape and Prognosis Potential of the T-Cell Repertoire in Membranous Nephropathy

Membranous nephropathy (MN), a common pathological type of adult nephrotic syndrome, is an antibody-mediated kidney disease. It is widely accepted now that MN is an immune-related disease that involves the whole immune system. In this study, we analyzed the T-cell receptor beta chain (TCRβ) repertoire of the circulating T lymphocytes of MN patients and healthy controls using high-throughput sequencing. We compared multiple aspects of the TCRβ repertoire, including diversity and the Vβ and Jβ genes between MN patients and healthy controls, and we found that the diversities within the VJ cassette combination in the peripheral blood of MN patients were lower than in the healthy controls. We also found the TCRβ repertoire similarity between pre- and post-therapy could reflect the clinical outcome, and two Vβ genes in pre-therapy had the potential to predict the therapeutic effect. These findings indicated the potential of the TCRβ repertoire as non-invasive biomarkers for the prognosis prediction of MN. The characteristics of circulating T-lymphocyte repertoires shed light on MN detection, treatment, and surveillance.

Biophysicochemical motifs in T cell receptor sequences as a potential biomarker for high-grade serous ovarian carcinoma

We previously showed, in a pilot study with publicly available data, that T cell receptor (TCR) repertoires from tumor infiltrating lymphocytes (TILs) could be distinguished from adjacent healthy tissue repertoires by the presence of TCRs bearing specific, biophysicochemical motifs in their antigen binding regions. We hypothesized that such motifs might allow development of a novel approach to cancer detection. The motifs were cancer specific and achieved high classification accuracy: we found distinct motifs for breast versus colorectal cancer-associated repertoires, and the colorectal cancer motif achieved 93% accuracy, while the breast cancer motif achieved 94% accuracy. In the current study, we sought to determine whether such motifs exist for ovarian cancer, a cancer type for which detection methods are urgently needed. We made two significant advances over the prior work. First, the prior study used patient-matched TILs and healthy repertoires, collecting healthy tissue adjacent to the tumors. The current study collected TILs from patients with high-grade serous ovarian carcinoma (HGSOC) and healthy ovary repertoires from cancer-free women undergoing hysterectomy/salpingo-oophorectomy for benign disease. Thus, the classification task is distinguishing women with cancer from women without cancer. Second, in the prior study, classification accuracy was measured by patient-hold-out cross-validation on the training data. In the current study, classification accuracy was additionally assessed on an independent cohort not used during model development to establish the generalizability of the motif to unseen data. Classification accuracy was 95% by patient-hold-out cross-validation on the training set and 80% when the model was applied to the blinded test set. The results on the blinded test set demonstrate a biophysicochemical TCR motif found overwhelmingly in women with HGSOC but rarely in women with healthy ovaries, strengthening the proposal that cancer detection approaches might benefit from incorporation of TCR motif-based biomarkers. Furthermore, these results call for studies on large cohorts to establish higher classification accuracies, as well as for studies in other cancer types.

A Bayesian framework for high-throughput T cell receptor pairing

MOTIVATION

The study of T cell receptor (TCR) repertoires has generated new insights into immune system recognition. However, the ability to robustly characterize these populations has been limited by technical barriers and an inability to reliably infer heterodimeric chain pairings for TCRs.

RESULTS

Here, we describe a novel analytical approach to an emerging immune repertoire sequencing method, improving the resolving power of this low-cost technology. This method relies upon the distribution of a T cell population across a 96-well plate, followed by barcoding and sequencing of the relevant transcripts from each T cell. Multicell Analytical Deconvolution for High Yield Paired-chain Evaluation (MAD-HYPE) uses Bayesian inference to more accurately extract TCR information, improving our ability to study and characterize T cell populations for immunology and immunotherapy applications.

AVAILABILITY AND IMPLEMENTATION

The MAD-HYPE algorithm is released as an open-source project under the Apache License and is available from https://github.com/birnbaumlab/MAD-HYPE.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

T Cell Responses to Mycobacterial Glycolipids: On the Spectrum of "Innateness"

Diseases due to mycobacteria, including tuberculosis, leprosy, and Buruli ulcer, rank among the top causes of death and disability worldwide. Animal studies have revealed the importance of T cells in controlling these infections. However, the specific antigens recognized by T cells that confer protective immunity and their associated functions remain to be definitively established. T cells that respond to mycobacterial peptide antigens exhibit classical features of adaptive immunity and have been well-studied in humans and animal models. Recently, innate-like T cells that recognize lipid and metabolite antigens have also been implicated. Specifically, T cells that recognize mycobacterial glycolipid antigens (mycolipids) have been shown to confer protection to tuberculosis in animal models and share some biological characteristics with adaptive and innate-like T cells. Here, we review the existing data suggesting that mycolipid-specific T cells exist on a spectrum of “innateness,” which will influence how they can be leveraged to develop new diagnostics and vaccines for mycobacterial diseases.

TCR Convergence in Individuals Treated With Immune Checkpoint Inhibition for Cancer

Tumor antigen-driven selection may expand T cells having T cell receptors (TCRs) of shared antigen specificity but different amino acid or nucleotide sequence in a process known as TCR convergence. Substitution sequencing errors introduced by TCRβ (TCRB) repertoire sequencing may create artifacts resembling TCR convergence. Given the anticipated differences in substitution error rates across different next-generation sequencing platforms, the choice of platform could be consequential. To test this, we performed TCRB sequencing on the same peripheral blood mononuclear cells (PBMC) from individuals with cancer receiving anti-CTLA-4 or anti-PD-1 using an Illumina-based approach (Sequenta) and an Ion Torrent-based approach (Oncomine TCRB-LR). While both approaches found similar TCR diversity, clonality, and clonal overlap, we found that Illumina-based sequencing resulted in higher TCR convergence than with the Ion Torrent approach. To build upon this initial observation we conducted a systematic comparison of Illumina-based TCRB sequencing assays, including those employing molecular barcodes, with the Oncomine assay, revealing differences in the frequency of convergent events, purportedly artifactual rearrangements, and sensitivity of detection. Finally, we applied the Ion Torrent-based approach to evaluate clonality and convergence in a cohort of individuals receiving anti-CTLA-4 blockade for cancer. We found that clonality and convergence independently predicted response and could be combined to improve the accuracy of a logistic regression classifier. These results demonstrate the importance of the sequencing platform in assessing TCRB convergence.

High-throughput sequencing of CD4+ T cell repertoire reveals disease-specific signatures in IgG4-related disease

Background

CD4⁺ T cells play critical roles in the pathogenesis of IgG4-related disease (IgG4-RD). The aim of this study was to investigate the TCR repertoire of peripheral blood CD4⁺ T cells in IgG4-RD.

Methods

The peripheral blood was collected from six healthy controls and eight IgG4-RD patients. TCR β-chain libraries of CD4⁺ T cells were constructed by 5′-rapid amplification of cDNA ends (5′-RACE) and sequenced by Illumina Miseq platform. The relative similarity of TCR repertoires between samples was evaluated according to the total frequencies of shared clonotypes (metric F), correlation of frequencies of shared clonotypes (metric R), and total number of shared clonotypes (metric D).

Results

The clonal expansion and diversity of CD4⁺ T cell repertoire were comparable between healthy controls and IgG4-RD patients, while the proportion of expanded and coding degenerated clones, as an indicator of antigen-driven clonal expansion, was significantly higher in IgG4-RD patients. There was no significant difference in TRBV and TRBJ gene usage between healthy controls and IgG4-RD patients. The complementarity determining region 3 (CDR3) length distribution was skewed towards longer fragments in IgG4-RD. Visualization of relative similarity of TCR repertoires by multi-dimensional scaling analysis showed that TCR repertoires of IgG4-RD patients were separated from that of healthy controls in F and D metrics. We identified 11 IgG4-RD-specific CDR3 amino acid sequences that were expanded in at least 2 IgG4-RD patients, while not detected in healthy controls. According to TCR clonotype networks constructed by connecting all the CDR3 sequences with a Levenshtein distance of 1, 3 IgG4-RD-specific clusters were identified. We annotated the TCR sequences with known antigen specificity according to McPAS-TCR database and found that the frequencies of TCR sequences associated with each disease or immune function were comparable between healthy controls and IgG4-RD patients.

Conclusion

According to our study of CD4⁺ T cells from eight IgG4-RD patients, TCR repertoires of IgG4-RD patients were different from that of healthy controls in the proportion of expanded and coding degenerated clones and CDR3 length distribution. In addition, IgG4-RD-specific TCR sequences and clusters were identified in our study.

CD8+ T cell-mediated endotheliopathy is a targetable mechanism of neuro-inflammation in Susac syndrome

Neuroinflammation is often associated with blood-brain-barrier dysfunction, which contributes to neurological tissue damage. Here, we reveal the pathophysiology of Susac syndrome (SuS), an enigmatic neuroinflammatory disease with central nervous system (CNS) endotheliopathy. By investigating immune cells from the blood, cerebrospinal fluid, and CNS of SuS patients, we demonstrate oligoclonal expansion of terminally differentiated activated cytotoxic CD8+ T cells (CTLs). Neuropathological data derived from both SuS patients and a newly-developed transgenic mouse model recapitulating the disease indicate that CTLs adhere to CNS microvessels in distinct areas and polarize granzyme B, which most likely results in the observed endothelial cell injury and microhemorrhages. Blocking T-cell adhesion by anti-α4 integrin-intervention ameliorates the disease in the preclinical model. Similarly, disease severity decreases in four SuS patients treated with natalizumab along with other therapy. Our study identifies CD8+ T-cell-mediated endotheliopathy as a key disease mechanism in SuS and highlights therapeutic opportunities.

Investigation of Antigen-Specific T-Cell Receptor Clusters in Human Cancers

PURPOSE

Cancer antigen-specific T cells are key components in antitumor immune response, yet their identification in the tumor microenvironment remains challenging, as most cancer antigens are unknown. Recent advance in immunology suggests that similar T-cell receptor (TCR) sequences can be clustered to infer shared antigen specificity. This study aims to identify antigen-specific TCRs from the tumor genomics sequencing data.

EXPERIMENTAL DESIGN

We used the TRUST (Tcr Repertoire Utilities for Solid Tissue) algorithm to assemble the TCR hypervariable CDR3 regions from 9,700 bulk tumor RNA-sequencing (RNA-seq) samples, and developed a computational method, iSMART, to group similar TCRs into antigen-specific clusters. Integrative analysis on the TCR clusters with multi-omics datasets was performed to profile cancer-associated T cells and to uncover novel cancer antigens.

RESULTS

Clustered TCRs are associated with signatures of T-cell activation after antigen encounter. We further elucidated the phenotypes of clustered T cells using single-cell RNA-seq data, which revealed a novel subset of tissue-resident memory T-cell population with elevated metabolic status. An exciting application of the TCR clusters is to identify novel cancer antigens, exemplified by our identification of a candidate cancer/testis gene, HSFX1, through integrated analysis of HLA alleles and genomics data. The target was further validated using vaccination of humanized HLA-A*02:01 mice and ELISpot assay. Finally, we showed that clustered tumor-infiltrating TCRs can differentiate patients with early-stage cancer from healthy donors, using blood TCR repertoire sequencing data, suggesting potential applications in noninvasive cancer detection.

CONCLUSIONS

Our analysis on the antigen-specific TCR clusters provides a unique resource for alternative antigen discovery and biomarker identification for cancer immunotherapies.

Identifying and Tracking Low-Frequency Virus-Specific TCR Clonotypes Using High-Throughput Sequencing

Tracking antigen-specific T cell responses over time within individuals is difficult because of lack of knowledge of antigen-specific TCR sequences, limitations in sample size, and assay sensitivities. We hypothesized that analyses of high-throughput sequencing of TCR clonotypes could provide functional readouts of individuals' immunological histories. Using high-throughput TCR sequencing, we develop a database of TCRβ sequences from large cohorts of mice before (naive) and after smallpox vaccination. We computationally identify 315 vaccine-associated TCR sequences (VATS) that are used to train a diagnostic classifier that distinguishes naive from vaccinated samples in mice up to 9 months post-vaccination with >99% accuracy. We determine that the VATS library contains virus-responsive TCRs by in vitro expansion assays and virus-specific tetramer sorting. These data outline a platform for advancing our capabilities to identify pathogen-specific TCR sequences, which can be used to identify and quantitate low-frequency pathogen-specific TCR sequences in circulation over time with exceptional sensitivity.

Stochastic Expansions Maintain the Clonal Stability of CD8+ T Cell Populations Undergoing Memory Inflation Driven by Murine Cytomegalovirus

Clonal stability is a feature of memory inflation.

Stochastic expansions maintain clonal stability during memory inflation.

Persistent clonotypes are often public in the context of memory inflation.

CMV is an obligate and persistent intracellular pathogen that continually drives the production of highly differentiated virus-specific CD8⁺ T cells in an Ag-dependent manner, a phenomenon known as memory inflation. Extensive proliferation is required to generate and maintain inflationary CD8⁺ T cell populations, which are counterintuitively short-lived and typically exposed to limited amounts of Ag during the chronic phase of infection. An apparent discrepancy therefore exists between the magnitude of expansion and the requirement for ongoing immunogenic stimulation. To address this issue, we explored the clonal dynamics of memory inflation. First, we tracked congenically marked OT-I cell populations in recipient mice infected with murine CMV (MCMV) expressing the cognate Ag OVA. Irrespective of numerical dominance, stochastic expansions were observed in each population, such that dominant and subdominant OT-I cells were maintained at stable frequencies over time. Second, we characterized endogenous CD8⁺ T cell populations specific for two classic inflationary epitopes, M38 and IE3. Multiple clonotypes simultaneously underwent Ag-driven proliferation during latent infection with MCMV. In addition, the corresponding CD8⁺ T cell repertoires were stable over time and dominated by persistent clonotypes, many of which also occurred in more than one mouse. Collectively, these data suggest that stochastic encounters with Ag occur frequently enough to maintain oligoclonal populations of inflationary CD8⁺ T cells, despite intrinsic constraints on epitope display at individual sites of infection with MCMV.

Detection of Enriched T Cell Epitope Specificity in Full T Cell Receptor Sequence Repertoires

High-throughput T cell receptor (TCR) sequencing allows the characterization of an individual's TCR repertoire and directly queries their immune state. However, it remains a non-trivial task to couple these sequenced TCRs to their antigenic targets. In this paper, we present a novel strategy to annotate full TCR sequence repertoires with their epitope specificities. The strategy is based on a machine learning algorithm to learn the TCR patterns common to the recognition of a specific epitope. These results are then combined with a statistical analysis to evaluate the occurrence of specific epitope-reactive TCR sequences per epitope in repertoire data. In this manner, we can directly study the capacity of full TCR repertoires to target specific epitopes of the relevant vaccines or pathogens. We demonstrate the usability of this approach on three independent datasets related to vaccine monitoring and infectious disease diagnostics by independently identifying the epitopes that are targeted by the TCR repertoire. The developed method is freely available as a web tool for academic use at tcrex.biodatamining.be.

CDR3α drives selection of the immunodominant Epstein Barr virus (EBV) BRLF1-specific CD8 T cell receptor repertoire in primary infection

The T cell receptor (TCR) repertoire is an essential component of the CD8 T-cell immune response. Here, we seek to investigate factors that drive selection of TCR repertoires specific to the HLA-A2-restricted immunodominant epitope BRLF1_109-117 (YVLDHLIVV) over the course of primary Epstein Barr virus (EBV) infection. Using single-cell paired TCRαβ sequencing of tetramer sorted CD8 T cells ex vivo, we show at the clonal level that recognition of the HLA-A2-restricted BRLF1 (YVL-BR, BRLF-1₁₀₉) epitope is mainly driven by the TCRα chain. For the first time, we identify a CDR3α (complementarity determining region 3 α) motif, KDTDKL, resulting from an obligate AV8.1-AJ34 pairing that was shared by all four individuals studied. This observation coupled with the fact that this public AV8.1-KDTDKL-AJ34 TCR pairs with multiple different TCRβ chains within the same donor (median 4; range: 1–9), suggests that there are some unique structural features of the interaction between the YVL-BR/MHC and the AV8.1-KDTDKL-AJ34 TCR that leads to this high level of selection. Newly developed TCR motif algorithms identified a lysine at position 1 of the CDR3α motif that is highly conserved and likely important for antigen recognition. Crystal structure analysis of the YVL-BR/HLA-A2 complex revealed that the MHC-bound peptide bulges at position 4, exposing a negatively charged aspartic acid that may interact with the positively charged lysine of CDR3α. TCR cloning and site-directed mutagenesis of the CDR3α lysine ablated YVL-BR-tetramer staining and substantially reduced CD69 upregulation on TCR mutant-transduced cells following antigen-specific stimulation. Reduced activation of T cells expressing this CDR3 motif was also observed following exposure to mutated (D4A) peptide. In summary, we show that a highly public TCR repertoire to an immunodominant epitope of a common human virus is almost completely selected on the basis of CDR3α and provide a likely structural basis for the selection. These studies emphasize the importance of examining TCRα, as well as TCRβ, in understanding the CD8 T cell receptor repertoire.

EBV is a ubiquitous human virus that has been linked to several diseases, including cancers and post-transplant lymphoproliferative disorders. CD8 T cells are important for controlling EBV replication. Generation and maintenance of virus-specific CD8 T cells is dependent on specific interaction between MHC-peptide complexes on the infected cell and the TCR. In this study, we performed single cell sequencing of paired TCR α and β chains from EBV-specific CD8 T cells isolated at two time points (primary infection and convalescence) from four individuals undergoing acute EBV infection. We describe a TCRα sequence that was shared by all four individuals and identify conserved residues within this sequence that likely contribute to viral recognition. Examination of the crystal structure of the peptide-MHC complex and subsequent experimental data suggest that a specific interaction between a negatively charged aspartic acid at position 4 of the peptide and a positively charged lysine in the TCR may be particularly important. These findings are highly relevant to current efforts to understand how the TCR repertoire may contribute to or protect against disease, the development of TCR diagnostics for diseases, and at improving the efficacy of T cell based therapies.

An overview of immunoinformatics approaches and databases linking T cell receptor repertoires to their antigen specificity

Recent advances in molecular and bioinformatic methods have greatly improved our ability to study the formation of an adaptive immune response towards foreign pathogens, self-antigens, and cancer neoantigens. T cell receptors (TCR) are the key players in this process that recognize peptides presented by major histocompatibility complex (MHC). Owing to the huge diversity of both TCR sequence variants and peptides they recognize, accumulation and complex analysis of large amounts of TCR-antigen specificity data is required for understanding the structure and features of adaptive immune responses towards pathogens, vaccines, cancer, as well as autoimmune responses. In the present review, we summarize recent efforts on gathering and interpreting TCR-antigen specificity data and outline the critical role of tighter integration with other immunoinformatics data sources that include epitope MHC restriction, TCR repertoire structure models, and TCR/peptide/MHC structural data. We suggest that such integration can lead to the ability to accurately annotate individual TCR repertoires, efficiently estimate epitope and neoantigen immunogenicity, and ultimately, in silico identify TCRs specific to yet unstudied antigens and predict self-peptides related to autoimmunity.

Lack of specific T- and B-cell clonal expansions in multiple sclerosis patients with progressive multifocal leukoencephalopathy

Progressive multifocal leukoencephalopathy (PML) is a rare, potentially devastating myelin-degrading disease caused by the JC virus. PML occurs preferentially in patients with compromised immune system, but has been also observed in multiple sclerosis (MS) patients treated with disease-modifying drugs. We characterized T and B cells in 5 MS patients that developed PML, 4 during natalizumab therapy and one after alemtuzumab treatment, and in treated patients who did not develop the disease. Results revealed that: i) thymic and bone marrow output was impaired in 4 out 5 patients at the time of PML development; ii) T-cell repertoire was restricted; iii) clonally expanded T cells were present in all patients. However, common usage or pairings of T-cell receptor beta variable or joining genes, specific clonotypes or obvious “public” T-cell response were not detected at the moment of PML onset. Similarly, common restrictions were not found in the immunoglobulin heavy chain repertoire. The data indicate that no JCV-related specific T- and B-cell expansions were mounted at the time of PML. The current results enhance our understanding of JC virus infection and PML, and should be taken into account when choosing targeted therapies.

Selected before selection: A case for inherent antigen bias in the T cell receptor repertoire

T cell receptor recombination is frequently described as a random or semi-random process that belies the now well-established principle that recombination is extremely biased towards the generation of particular receptor chains. Here we describe the experimental and theoretical work arising from new TCR repertoire sequencing approaches, including the recognition of high rates of public receptors across individuals, estimates of the size and distribution of receptors in the naive repertoire, and the roles of evolutionary, thymic, and peripheral selection in generating public, pathogen-specific responses. Molecular studies of recombination that have identified epigenetic, transcriptional, and topological contributions to variable segment usage are presented as examples of possible mechanisms shaped by natural selection to bias the TCR repertoire. Lastly, we suggest experimental approaches that might contribute to resolving some of the controversies in these areas.

A Framework for Annotation of Antigen Specificities in High-Throughput T-Cell Repertoire Sequencing Studies

Recently developed molecular methods allow large-scale profiling of T-cell receptor (TCR) sequences that encode for antigen specificity and immunological memory of these cells. However, it is well-known that the even unperturbed TCR repertoire structure is extremely complex due to the high diversity of TCR rearrangements and multiple biases imprinted by VDJ rearrangement process. The latter gives rise to the phenomenon of "public" TCR clonotypes that can be shared across multiple individuals and non-trivial structure of the TCR similarity network. Here, we outline a framework for TCR sequencing data analysis that can control for these biases in order to infer TCRs that are involved in response to antigens of interest. We apply two previously published methods, ALICE and TCRNET, to detect groups of homologous TCRs that are enriched in samples of interest. Using an example dataset of donors with known HLA haplotype and CMV status, we demonstrate that by applying HLA restriction rules and matching against a database of TCRs with known antigen specificity, it is possible to robustly detect motifs of epitope-specific responses in individual repertoires. We also highlight potential shortcomings of TCR clustering methods and demonstrate that highly expanded TCRs should be individually assessed to get the full picture of antigen-specific response.

Deep generative models for T cell receptor protein sequences

Probabilistic models of adaptive immune repertoire sequence distributions can be used to infer the expansion of immune cells in response to stimulus, differentiate genetic from environmental factors that determine repertoire sharing, and evaluate the suitability of various target immune sequences for stimulation via vaccination. Classically, these models are defined in terms of a probabilistic V(D)J recombination model which is sometimes combined with a selection model. In this paper we take a different approach, fitting variational autoencoder (VAE) models parameterized by deep neural networks to T cell receptor (TCR) repertoires. We show that simple VAE models can perform accurate cohort frequency estimation, learn the rules of VDJ recombination, and generalize well to unseen sequences. Further, we demonstrate that VAE-like models can distinguish between real sequences and sequences generated according to a recombination-selection model, and that many characteristics of VAE-generated sequences are similar to those of real sequences.

T-Cell Receptor Cognate Target Prediction Based on Paired α and β Chain Sequence and Structural CDR Loop Similarities

T-cell receptors (TCR) mediate immune responses recognizing peptides in complex with major histocompatibility complexes (pMHC) displayed on the surface of cells. Resolving the challenge of predicting the cognate pMHC target of a TCR would benefit many applications in the field of immunology, including vaccine design/discovery and the development of immunotherapies. Here, we developed a model for prediction of TCR targets based on similarity to a database of TCRs with known targets. Benchmarking the model on a large set of TCRs with known target, we demonstrated how the predictive performance is increased (i) by focusing on CDRs rather than the full length TCR protein sequences, (ii) by incorporating information from paired α and β chains, and (iii) integrating information for all 6 CDR loops rather than just CDR3. Finally, we show how integration of the structure of CDR loops, as obtained through homology modeling, boosts the predictive power of the model, in particular in situations where no high-similarity TCRs are available for the query. These findings demonstrate that TCRs that bind to the same target also share, to a very high degree, sequence, and structural features. This observation has profound impact for future development of prediction models for TCR-pMHC interactions and for the use of such models for the rational design of T cell based therapies.

Recent progress in the analysis of αβT cell and B cell receptor repertoires

T cell receptors (TCRs) and B cell receptors (BCRs) are vertebrate evolution's best answer to the threat of microbial pathogens that can evolve much faster than ourselves. These antigen receptors are generated during T cell or B cell development by combinatorial rearrangement of germline genome V, D and J gene segments, and with junctional residues capable of enormous diversity. For decades the complexity of these receptor repertoires has limited their analysis, but advances in DNA sequencing technology and an array of complementary tools have now made their study much more tractable, filling a major gap in our ability to understand immunology as a system. Here, we summarize the recent approaches and discoveries that are enabling these advances, with some suggestions as to what may lie ahead.