Immunosequencing identifies signatures of cytomegalovirus exposure history and HLA-mediated effects on the T cell repertoire
TL;DR: A statistical classification framework is developed that could diagnose CMV status from the resulting catalog of TCRβ sequences with high specificity and sensitivity in both the original cohort and a validation cohort of 120 different subjects.
Abstract: Ryan Emerson and colleagues report immunosequencing of the variable region of the TCRβ chain in 666 individuals with known cytomegalovirus (CMV) status. They show that CMV status and HLA genotype shape the T cell repertoire and demonstrate proof of principle that TCRβ sequencing can be used as a specific diagnostic of pathogen exposure. An individual's T cell repertoire dynamically encodes their pathogen exposure history. To determine whether pathogen exposure signatures can be identified by documenting public T cell receptors (TCRs), we profiled the T cell repertoire of 666 subjects with known cytomegalovirus (CMV) serostatus by immunosequencing. We developed a statistical classification framework that could diagnose CMV status from the resulting catalog of TCRβ sequences with high specificity and sensitivity in both the original cohort and a validation cohort of 120 different subjects. We also confirmed that three of the identified CMV-associated TCRβ molecules bind CMV in vitro, and, moreover, we used this approach to accurately predict the HLA-A and HLA-B alleles of most subjects in the first cohort. As all memory T cell responses are encoded in the common format of somatic TCR recombination, our approach could potentially be generalized to a wide variety of disease states, as well as other immunological phenotypes, as a highly parallelizable diagnostic strategy.
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TL;DR: Huang et al. as discussed by the authors performed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data and patient-reported symptoms.
443 citations
Journal Article•
TL;DR: In this article, the authors performed a comprehensive experimental and mathematical analysis to reveal that a single patient-derived autoimmune CD8+ T cell clone of pathogenic relevance in human type I diabetes recognizes >one million distinct decamer peptides in the context of a single MHC class I molecule.
Abstract: Background: How does a limited pool of <108 T cell receptors (TCRs) provide immunity to >1015 antigens? Results: A single TCR can respond to >one million different decamer peptides. Conclusion: This unprecedented level of receptor promiscuity explains how the naïve TCR repertoire achieves effective immunity. Significance: TCR degeneracy has enormous potential to be the root cause of autoimmune disease. The T cell receptor (TCR) orchestrates immune responses by binding to foreign peptides presented at the cell surface in the context of major histocompatibility complex (MHC) molecules. Effective immunity requires that all possible foreign peptide-MHC molecules are recognized or risks leaving holes in immune coverage that pathogens could quickly evolve to exploit. It is unclear how a limited pool of <108 human TCRs can successfully provide immunity to the vast array of possible different peptides that could be produced from 20 proteogenic amino acids and presented by self-MHC molecules (>1015 distinct peptide-MHCs). One possibility is that T cell immunity incorporates an extremely high level of receptor degeneracy, enabling each TCR to recognize multiple peptides. However, the extent of such TCR degeneracy has never been fully quantified. Here, we perform a comprehensive experimental and mathematical analysis to reveal that a single patient-derived autoimmune CD8+ T cell clone of pathogenic relevance in human type I diabetes recognizes >one million distinct decamer peptides in the context of a single MHC class I molecule. A large number of peptides that acted as substantially better agonists than the wild-type “index” preproinsulin-derived peptide (ALWGPDPAAA) were identified. The RQFGPDFPTI peptide (sampled from >108 peptides) was >100-fold more potent than the index peptide despite differing from this sequence at 7 of 10 positions. Quantification of this previously unappreciated high level of CD8+ T cell cross-reactivity represents an important step toward understanding the system requirements for adaptive immunity and highlights the enormous potential of TCR degeneracy to be the causative factor in autoimmune disease.
284 citations
TL;DR: The McPAS‐TCR database currently contains more than 5000 sequences of TCRs associated with various pathologic conditions and their respective antigens in humans and in mice and provides interesting insights on pathology‐associated TCR sequences.
Abstract: Motivation While growing numbers of T cell receptor (TCR) repertoires are being mapped by high-throughput sequencing, existing methods do not allow for computationally connecting a given TCR sequence to its target antigen, or relating it to a specific pathology. As an alternative, a manually-curated database can relate TCR sequences with their cognate antigens and associated pathologies based on published experimental data. Results We present McPAS-TCR, a manually curated database of TCR sequences associated with various pathologies and antigens based on published literature. Our database currently contains more than 5000 sequences of TCRs associated with various pathologic conditions (including pathogen infections, cancer and autoimmunity) and their respective antigens in humans and in mice. A web-based tool allows for searching the database based on different criteria, and for finding annotated sequences from the database in users' data. The McPAS-TCR website assembles information from a large number of studies that is very hard to dissect otherwise. Initial analyses of the data provide interesting insights on pathology-associated TCR sequences. Availability and implementation Free access at http://friedmanlab.weizmann.ac.il/McPAS-TCR/ . Contact nir.friedman@weizmann.ac.il.
245 citations
TL;DR: An update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens and a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest are reported.
Abstract: 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.
239 citations
TL;DR: A software tool, IGoR, that calculates the likelihoods of potential V(D)J recombination and somatic hypermutation scenarios from raw immune sequence reads and outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization.
Abstract: High-throughput immune repertoire sequencing is promising to lead to new statistical diagnostic tools for medicine and biology. Successful implementations of these methods require a correct characterization, analysis, and interpretation of these data sets. We present IGoR (Inference and Generation Of Repertoires)—a comprehensive tool that takes B or T cell receptor sequence reads and quantitatively characterizes the statistics of receptor generation from both cDNA and gDNA. It probabilistically annotates sequences and its modular structure can be used to investigate models of increasing biological complexity for different organisms. For B cells, IGoR returns the hypermutation statistics, which we use to reveal co-localization of hypermutations along the sequence. We demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization. B and T cell receptor diversity can be studied by high-throughput immune receptor sequencing. Here, the authors develop a software tool, IGoR, that calculates the likelihoods of potential V(D)J recombination and somatic hypermutation scenarios from raw immune sequence reads.
194 citations
References
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TL;DR: This work proposes an approach to measuring statistical significance in genomewide studies based on the concept of the false discovery rate, which offers a sensible balance between the number of true and false positives that is automatically calibrated and easily interpreted.
Abstract: With the increase in genomewide experiments and the sequencing of multiple genomes, the analysis of large data sets has become commonplace in biology. It is often the case that thousands of features in a genomewide data set are tested against some null hypothesis, where a number of features are expected to be significant. Here we propose an approach to measuring statistical significance in these genomewide studies based on the concept of the false discovery rate. This approach offers a sensible balance between the number of true and false positives that is automatically calibrated and easily interpreted. In doing so, a measure of statistical significance called the q value is associated with each tested feature. The q value is similar to the well known p value, except it is a measure of significance in terms of the false discovery rate rather than the false positive rate. Our approach avoids a flood of false positive results, while offering a more liberal criterion than what has been used in genome scans for linkage.
9,239 citations
TL;DR: This view of T-cell recognition has implications for how the receptors might be selected in the thymus and how they (and immunoglobulins) may have arisen during evolution.
Abstract: The four distinct T-cell antigen receptor polypeptides (alpha, beta, gamma, delta) form two different heterodimers (alpha:beta and gamma:delta) that are very similar to immunoglobulins in primary sequence, gene organization and modes of rearrangement. Whereas antibodies have both soluble and membrane forms that can bind to antigens alone, T-cell receptors exist only on cell surfaces and recognize antigen fragments only when they are embedded in major histocompatibility complex (MHC) molecules. Patterns of diversity in T-cell receptor genes together with structural features of immunoglobulin and MHC molecules suggest a model for how this recognition might occur. This view of T-cell recognition has implications for how the receptors might be selected in the thymus and how they (and immunoglobulins) may have arisen during evolution.
2,858 citations
2,227 citations
TL;DR: A novel experimental and computational approach is developed to measure TCR CDR3 diversity based on single-molecule DNA sequencing, and it is found that total TCRbeta receptor diversity is at least 4-fold higher than previous estimates, and the diversity in the subset of CD45RO(+) antigen-experienced alphabeta T cells is at at least 10-foldHigher than previously estimates.
1,074 citations
TL;DR: It is discussed how the particular composition of the peptide–MHC ligandomes that are presented by specific APC subsets not only shapes the T cell repertoire in the thymus but may also indelibly imprint the behaviour of mature T cells in the periphery.
Abstract: The fate of developing T cells is specified by the interaction of their antigen receptors with self-peptide-MHC complexes that are displayed by thymic antigen-presenting cells (APCs). Various subsets of thymic APCs are strategically positioned in particular thymic microenvironments and they coordinate the selection of a functional and self-tolerant T cell repertoire. In this Review, we discuss the different strategies that these APCs use to sample and process self antigens and to thereby generate partly unique, 'idiosyncratic' peptide-MHC ligandomes. We discuss how the particular composition of the peptide-MHC ligandomes that are presented by specific APC subsets not only shapes the T cell repertoire in the thymus but may also indelibly imprint the behaviour of mature T cells in the periphery.
1,069 citations