ABSTRACT
Human leucocyte antigen B*27 (HLA-B*27) is strongly associated with inflammatory diseases of the spine and pelvis (for example, ankylosing spondylitis (AS)) and the eye (that is, acute anterior uveitis (AAU))1. How HLA-B*27 facilitates disease remains unknown, but one possible mechanism could involve presentation of pathogenic peptides to CD8+ T cells. Here we isolated orphan T cell receptors (TCRs) expressing a disease-associated public ß-chain variable region-complementary-determining region 3ß (BV9-CDR3ß) motif2-4 from blood and synovial fluid T cells from individuals with AS and from the eye in individuals with AAU. These TCRs showed consistent α-chain variable region (AV21) chain pairing and were clonally expanded in the joint and eye. We used HLA-B*27:05 yeast display peptide libraries to identify shared self-peptides and microbial peptides that activated the AS- and AAU-derived TCRs. Structural analysis revealed that TCR cross-reactivity for peptide-MHC was rooted in a shared binding motif present in both self-antigens and microbial antigens that engages the BV9-CDR3ß TCRs. These findings support the hypothesis that microbial antigens and self-antigens could play a pathogenic role in HLA-B*27-associated disease.
Subject(s)
Autoimmunity , HLA-B Antigens , Peptides , Receptors, Antigen, T-Cell , Humans , Autoantigens/chemistry , Autoantigens/immunology , Autoantigens/metabolism , CD8-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/metabolism , HLA-B Antigens/immunology , HLA-B Antigens/metabolism , Peptides/chemistry , Peptides/immunology , Peptides/metabolism , Receptors, Antigen, T-Cell/chemistry , Receptors, Antigen, T-Cell/immunology , Receptors, Antigen, T-Cell/metabolism , Synovial Fluid/immunology , Spondylitis, Ankylosing/immunology , Uveitis, Anterior/immunology , Peptide Library , Cross Reactions , Amino Acid MotifsABSTRACT
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.
Subject(s)
Computational Biology/methods , Databases, Genetic , Nucleotide Motifs , Receptors, Antigen, T-Cell/genetics , V(D)J Recombination , Amino Acid Sequence , High-Throughput Nucleotide Sequencing , Humans , Position-Specific Scoring Matrices , Receptors, Antigen, T-Cell/chemistry , Sequence Analysis, DNA , Software , Web BrowserABSTRACT
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.
Subject(s)
Computational Biology/methods , Databases, Protein , Epitopes, T-Lymphocyte/immunology , Receptors, Antigen, T-Cell/immunology , T-Cell Antigen Receptor Specificity/immunology , Animals , HumansABSTRACT
The ability to decode antigen specificities encapsulated in the sequences of rearranged T-cell receptor (TCR) genes is critical for our understanding of the adaptive immune system and promises significant advances in the field of translational medicine. Recent developments in high-throughput sequencing methods (immune repertoire sequencing technology, or RepSeq) and single-cell RNA sequencing technology have allowed us to obtain huge numbers of TCR sequences from donor samples and link them to T-cell phenotypes. However, our ability to annotate these TCR sequences still lags behind, owing to the enormous diversity of the TCR repertoire and the scarcity of available data on T-cell specificities. In this paper, we present VDJdb, a database that stores and aggregates the results of published T-cell specificity assays and provides a universal platform that couples antigen specificities with TCR sequences. We demonstrate that VDJdb is a versatile instrument for the annotation of TCR repertoire data, enabling a concatenated view of antigen-specific TCR sequence motifs. VDJdb can be accessed at https://vdjdb.cdr3.net and https://github.com/antigenomics/vdjdb-db.
Subject(s)
Antigens/chemistry , Databases, Protein , Molecular Sequence Annotation , Receptors, Antigen, T-Cell/chemistry , Software , Amino Acid Sequence , Animals , Antigens/immunology , Antigens/metabolism , Binding Sites , High-Throughput Nucleotide Sequencing , Humans , Internet , Macaca mulatta , Major Histocompatibility Complex/genetics , Major Histocompatibility Complex/immunology , Mice , Models, Molecular , Protein Binding , Protein Interaction Domains and Motifs , Protein Structure, Secondary , Receptors, Antigen, T-Cell/immunology , Receptors, Antigen, T-Cell/metabolism , Sequence Alignment , Sequence Homology, Amino Acid , Single-Cell Analysis , T-Lymphocytes/cytology , T-Lymphocytes/immunologyABSTRACT
Objective: The risk of AS is associated with genomic variants related to antigen presentation and specific cytokine signalling pathways, suggesting the involvement of cellular immunity in disease initiation/progression. The aim of the present study was to explore the repertoire of TCR sequences in healthy donors and AS patients to uncover AS-linked TCR variants. Methods: Using quantitative molecular-barcoded 5'-RACE, we performed deep TCR ß repertoire profiling of peripheral blood (PB) and SF samples for 25 AS patients and 108 healthy donors. AS-linked TCR variants were identified using a new computational approach that relies on a probabilistic model of the VDJ rearrangement process. Results: Using the donor-agnostic probabilistic model, we reveal a TCR ß motif characteristic for PB of AS patients, represented by eight highly homologous amino acid sequence variants. Some of these variants were previously reported in SF and PB of patients with ReA and in PB of AS patients. We demonstrate that identified AS-linked clones have a CD8+ phenotype, present at relatively low frequencies in PB, and are significantly enriched in matched SF samples of AS patients. Conclusion: Our results suggest the involvement of a particular antigen-specific subset of CD8+ T cells in AS pathogenesis, confirming and expanding earlier findings. The high similarity of the clonotypes with the ones found in ReA implies common mechanisms for the initiation of the diseases.
Subject(s)
CD8-Positive T-Lymphocytes/immunology , DNA/genetics , POU Domain Factors/genetics , Spondylitis, Ankylosing/genetics , Synovial Fluid/metabolism , Female , Humans , Male , POU Domain Factors/metabolism , Polymerase Chain Reaction , Prohibitins , Spondylitis, Ankylosing/immunology , Spondylitis, Ankylosing/metabolism , Synovial Fluid/immunologyABSTRACT
Adaptive immunity in humans is provided by hypervariable Ig-like molecules on the surface of B and T cells. The final set of these molecules in each organism is formed under the influence of two forces: individual genetic traits and the environment, which includes the diverse spectra of alien and self-antigens. Here we assess the impact of individual genetic factors on the formation of the adaptive immunity by analyzing the T-cell receptor (TCR) repertoires of three pairs of monozygous twins by next-generation sequencing. Surprisingly, we found that an overlap between the TCR repertoires of monozygous twins is similar to an overlap between the TCR repertoires of nonrelated individuals. However, the number of identical complementary determining region 3 sequences in two individuals is significantly increased for twin pairs in the fraction of highly abundant TCR molecules, which is enriched by the antigen-experienced T cells. We found that the initial recruitment of particular TCR V genes for recombination and subsequent selection in the thymus is strictly determined by individual genetic factors. J genes of TCRs are selected randomly for recombination; however, the subsequent selection in the thymus gives preference to some α but not ß J segments. These findings provide a deeper insight into the mechanism of TCR repertoire generation.
Subject(s)
High-Throughput Nucleotide Sequencing , Receptors, Antigen, T-Cell/genetics , Twins, Monozygotic/genetics , Clone Cells , Complementarity Determining Regions/genetics , Female , Gene Library , Genetic Variation , Humans , Sequence Analysis, DNA , T-Lymphocytes/metabolism , Thymus Gland/metabolismABSTRACT
BACKGROUND: The repertoire of T- and B-cell receptor sequences encodes the antigen specificity of adaptive immunity system, determines its present state and guides its ability to mount effective response against encountered antigens in future. High throughput sequencing of immune repertoires (Rep-Seq) is a promising technique that allows to profile millions of antigen receptors of an individual in a single experiment. While a substantial number of tools for mapping and assembling Rep-Seq data were published recently, the field still lacks an intuitive and flexible tool that can be used by researchers with little or no computational background for in-depth analysis of immune repertoire profiles. RESULTS: Here we report VDJviz, a web tool that can be used to browse, analyze and perform quality control of Rep-Seq results generated by various pre-processing software. On a set of real data examples we show that VDJviz can be used to explore key repertoire characteristics such as spectratype, repertoire clonality, V-(D)-J recombination patterns and to identify shared clonotypes. We also demonstrate the utility of VDJviz in detection of critical Rep-Seq biases such as artificial repertoire diversity and cross-sample contamination. CONCLUSIONS: VDJviz is a versatile and lightweight tool that can be easily employed by biologists, immunologists and immunogeneticists for routine analysis and quality control of Rep-Seq data. The software is freely available for non-commercial purposes, and can be downloaded from: https://github.com/antigenomics/vdjviz .
Subject(s)
Genomics/methods , Software , V(D)J Recombination , B-Lymphocytes/immunology , B-Lymphocytes/metabolism , Clonal Evolution/genetics , Cluster Analysis , Complementarity Determining Regions/genetics , Computational Biology/methods , Computational Biology/standards , Genomics/standards , Humans , T-Lymphocytes/immunology , T-Lymphocytes/metabolism , Web BrowserABSTRACT
Despite the growing number of immune repertoire sequencing studies, the field still lacks software for analysis and comprehension of this high-dimensional data. Here we report VDJtools, a complementary software suite that solves a wide range of T cell receptor (TCR) repertoires post-analysis tasks, provides a detailed tabular output and publication-ready graphics, and is built on top of a flexible API. Using TCR datasets for a large cohort of unrelated healthy donors, twins, and multiple sclerosis patients we demonstrate that VDJtools greatly facilitates the analysis and leads to sound biological conclusions. VDJtools software and documentation are available at https://github.com/mikessh/vdjtools.
Subject(s)
Computational Biology/methods , Receptors, Antigen, T-Cell/chemistry , Receptors, Antigen, T-Cell/genetics , Sequence Analysis, DNA/methods , Software , Adolescent , Adult , Child , Cluster Analysis , Hematopoietic Stem Cell Transplantation , Humans , Multiple Sclerosis/genetics , Receptors, Antigen, T-Cell/metabolism , Twins/genetics , Young AdultABSTRACT
BACKGROUND: The Immunoglobulins (IG) and the T cell receptors (TR) play the key role in antigen recognition during the adaptive immune response. Recent progress in next-generation sequencing technologies has provided an opportunity for the deep T cell receptor repertoire profiling. However, a specialised software is required for the rational analysis of massive data generated by next-generation sequencing. RESULTS: Here we introduce tcR, a new R package, representing a platform for the advanced analysis of T cell receptor repertoires, which includes diversity measures, shared T cell receptor sequences identification, gene usage statistics computation and other widely used methods. The tool has proven its utility in recent research studies. CONCLUSIONS: tcR is an R package for the advanced analysis of T cell receptor repertoires after primary TR sequences extraction from raw sequencing reads. The stable version can be directly installed from The Comprehensive R Archive Network ( http://cran.r-project.org/mirrors.html ). The source code and development version are available at tcR GitHub ( http://imminfo.github.io/tcr/ ) along with the full documentation and typical usage examples.
Subject(s)
High-Throughput Nucleotide Sequencing/methods , Immunoglobulins/genetics , Receptors, Antigen, T-Cell/genetics , Receptors, Antigen, T-Cell/immunology , Sequence Analysis, DNA/methods , Software , Humans , Programming LanguagesABSTRACT
Our ability to analyze adaptive immunity and engineer its activity has long been constrained by our limited ability to identify native pairs of heavy-light antibody chains and alpha-beta T-cell receptor (TCR) chains--both of which comprise coupled "halves of a key", collectively capable of recognizing specific antigens. Here, we report a cell-based emulsion RT-PCR approach that allows the selective fusion of the native pairs of amplified TCR alpha and beta chain genes for complex samples. A new type of PCR suppression technique was developed that makes it possible to amplify the fused library with minimal noise for subsequent analysis by high-throughput paired-end Illumina sequencing. With this technique, single analysis of a complex blood sample allows identification of multiple native TCR chain pairs. This approach may be extended to identify native antibody chain pairs and, more generally, pairs of mRNA molecules that are coexpressed in the same living cells.
Subject(s)
Immunoglobulin Heavy Chains/immunology , Immunoglobulin Light Chains/immunology , Receptors, Antigen, T-Cell, alpha-beta/genetics , Receptors, Antigen, T-Cell, alpha-beta/immunology , Base Sequence , Gene Amplification , Humans , Immunoglobulin Heavy Chains/analysis , Immunoglobulin Light Chains/analysis , Leukocytes, Mononuclear , Male , Middle Aged , Nucleic Acid Amplification Techniques , Polymerase Chain Reaction , Sequence Analysis, DNAABSTRACT
An individual's T-cell repertoire constantly changes under the influence of external and internal factors. Cells that do not receive a stimulatory signal die, while those that encounter and recognize a pathogen or receive a co-stimulatory signal divide, resulting in clonal expansions. T-cell clones can be traced by monitoring the presence of their unique T-cell receptor (TCR) sequence, which is assembled de novo through a process known as V(D)J rearrangement. Tracking T cells can provide valuable insights into the survival of cells after hematopoietic stem cell transplantation (HSCT) or cancer treatment response and can indicate the induction of protective immunity by vaccination. In this study, we report a bioinformatic method for quantifying the T-cell repertoire dynamics from TCR sequencing data. We demonstrate its utility by measuring the T-cell repertoire stability in healthy donors, by quantifying the effect of donor lymphocyte infusion (DLI), and by tracking the fate of the different T-cell subsets in HSCT patients and the expansion of pathogen-specific clones in vaccinated individuals.
Subject(s)
Hematopoietic Stem Cell Transplantation , Receptors, Antigen, T-Cell , Humans , T-Lymphocyte Subsets , Clone CellsABSTRACT
T cell receptor (TCR) recognition of foreign peptides presented by major histocompatibility complex protein is a major event in triggering the adaptive immune response to pathogens or cancer. The prediction of TCR-peptide interactions has great importance for therapy of cancer as well as infectious and autoimmune diseases but remains a major challenge, particularly for novel (unseen) peptide epitopes. Here we present TCRen, a structure-based method for ranking candidate unseen epitopes for a given TCR. The first stage of the TCRen pipeline is modeling of the TCR-peptide-major histocompatibility complex structure. Then a TCR-peptide residue contact map is extracted from this structure and used to rank all candidate epitopes on the basis of an interaction score with the target TCR. Scoring is performed using an energy potential derived from the statistics of TCR-peptide contact preferences in existing crystal structures. We show that TCRen has high performance in discriminating cognate versus unrelated peptides and can facilitate the identification of cancer neoepitopes recognized by tumor-infiltrating lymphocytes.
Subject(s)
Receptors, Antigen, T-Cell , Receptors, Antigen, T-Cell/immunology , Receptors, Antigen, T-Cell/chemistry , Receptors, Antigen, T-Cell/metabolism , Humans , Peptides/immunology , Peptides/chemistry , Epitopes/immunology , Epitopes/chemistry , Models, Molecular , Neoplasms/immunology , Epitopes, T-Lymphocyte/immunology , Epitopes, T-Lymphocyte/chemistry , Major Histocompatibility Complex/immunology , Protein Conformation , Lymphocytes, Tumor-Infiltrating/immunology , Lymphocytes, Tumor-Infiltrating/metabolismABSTRACT
Adenovirus vaccines, particularly the COVID-19 Ad5-nCoV adenovirus vaccine, have emerged as promising tools in the fight against infectious diseases. In this study, we investigated the structure of the T cell response to the Spike protein of the SARS-CoV-2 virus used in the COVID-19 Ad5-nCoV adenoviral vaccine in a phase 3 clinical trial (NCT04540419). In 69 participants, we collected peripheral blood samples at four time points after vaccination or placebo injection. Sequencing of T cell receptor repertoires from Spike-stimulated T cell cultures at day 14 from 17 vaccinated revealed a more diverse CD4+ T cell repertoire compared to CD8+. Nevertheless, CD8+ clonotypes accounted for more than half of the Spike-specific repertoire. Our longitudinal analysis showed a peak T cell response at day 14, followed by a decline until month 6. Remarkably, multiple T cell clonotypes persisted for at least 6 months after vaccination, as demonstrated by ex vivo stimulation. Examination of CDR3 regions revealed homologous sequences in both CD4+ and CD8+ clonotypes, with major CD8+ clonotypes sharing high similarity with annotated sequences specific for the NYNYLYRLF peptide, suggesting potential immunodominance. In conclusion, our study demonstrates the immunogenicity of the Ad5-nCoV adenoviral vaccine and highlights its ability to induce robust and durable T cell responses. These findings provide valuable insight into the efficacy of the vaccine against COVID-19 and provide critical information for ongoing efforts to control infectious diseases.
Subject(s)
COVID-19 , Communicable Diseases , Vaccines , Humans , COVID-19 Vaccines , Spike Glycoprotein, Coronavirus , COVID-19/prevention & control , SARS-CoV-2 , T-Lymphocytes , Adenoviridae/geneticsABSTRACT
The TCR repertoire is a mirror of the human immune system that reflects processes caused by infections, cancer, autoimmunity, and aging. Next generation sequencing (NGS) is becoming a powerful tool for deep TCR profiling; yet, questions abound regarding the methodological approaches for sample preparation and correct data interpretation. Accumulated PCR and sequencing errors along with library preparation bottlenecks and uneven PCR efficiencies lead to information loss, biased quantification, and generation of huge artificial TCR diversity. Here, we compare Illumina, 454, and Ion Torrent platforms for individual TCR profiling, evaluate the rate and character of errors, and propose advanced platform-specific algorithms to correct massive sequencing data. These developments are applicable to a wide variety of next generation sequencing applications. We demonstrate that advanced correction allows the removal of the majority of artificial TCR diversity with concomitant rescue of most of the sequencing information. Thus, this correction enhances the accuracy of clonotype identification and quantification as well as overall TCR diversity measurements.
Subject(s)
Algorithms , High-Throughput Nucleotide Sequencing/instrumentation , High-Throughput Nucleotide Sequencing/methods , Receptors, Antigen, T-Cell/genetics , Sequence Analysis, DNA/methods , Adaptive Immunity/genetics , Adaptive Immunity/immunology , Adult , Base Sequence , Humans , Male , Molecular Sequence Data , Reproducibility of Results , Sequence Analysis, DNA/instrumentationABSTRACT
Introduction: T-cell receptor (TCR) recognition of foreign peptides presented by the major histocompatibility complex (MHC) initiates the adaptive immune response against pathogens. While a large number of TCR sequences specific to different antigenic peptides are known to date, the structural data describing the conformation and contacting residues for TCR-peptide-MHC complexes is relatively limited. In the present study we aim to extend and analyze the set of available structures by performing highly accurate template-based modeling of these complexes using TCR sequences with known specificity. Methods: Identification of CDR3 sequences and their further clustering, based on available spatial structures, V- and J-genes of corresponding T-cell receptors, and epitopes, was performed using the VDJdb database. Modeling of the selected CDR3 loops was conducted using a stepwise introduction of single amino acid substitutions to the template PDB structures, followed by optimization of the TCR-peptide-MHC contacting interface using the Rosetta package applications. Statistical analysis and recursive feature elimination procedures were carried out on computed energy values and properties of contacting amino acid residues between CDR3 loops and peptides, using R. Results: Using the set of 29 complex templates (including a template with SARS-CoV-2 antigen) and 732 specificity records, we built a database of 1585 model structures carrying substitutions in either TCRα or TCRß chains with some models representing the result of different mutation pathways for the same final structure. This database allowed us to analyze features of amino acid contacts in TCR - peptide interfaces that govern antigen recognition preferences and interpret these interactions in terms of physicochemical properties of interacting residues. Conclusion: Our results provide a methodology for creating high-quality TCR-peptide-MHC models for antigens of interest that can be utilized to predict TCR specificity.
Subject(s)
COVID-19 , Humans , SARS-CoV-2 , Antibody Specificity , T-Cell Antigen Receptor Specificity , Amino Acids , Complement System ProteinsABSTRACT
Autoimmunity is intrinsically driven by memory T and B cell clones inappropriately targeted at self-antigens. Selective depletion or suppression of self-reactive T cells remains a holy grail of autoimmune therapy, but disease-associated T cell receptors (TCRs) and cognate antigenic epitopes remained elusive. A TRBV9-containing CD8+ TCR motif was recently associated with the pathogenesis of ankylosing spondylitis, psoriatic arthritis and acute anterior uveitis, and cognate HLA-B*27-presented epitopes were identified. Following successful testing in nonhuman primate models, here we report human TRBV9+ T cell elimination in ankylosing spondylitis. The patient achieved remission within 3 months and ceased anti-TNF therapy after 5 years of continuous use. Complete remission has now persisted for 4 years, with three doses of anti-TRBV9 administered per year. We also observed a profound improvement in spinal mobility metrics and the Bath Ankylosing Spondylitis Metrology Index (BASMI). This represents a possibly curative therapy of an autoimmune disease via selective depletion of a TRBV-defined group of T cells. The anti-TRBV9 therapy could potentially be applicable to other HLA-B*27-associated spondyloarthropathies. Such targeted elimination of the underlying cause of the disease without systemic immunosuppression could offer a new generation of safe and efficient therapies for autoimmunity.
Subject(s)
Spondylitis, Ankylosing , Humans , Epitopes , HLA-B Antigens , Immunotherapy , Receptors, Antigen, T-Cell/genetics , Receptors, Antigen, T-Cell/therapeutic use , Spondylitis, Ankylosing/drug therapy , T-Lymphocytes , Tumor Necrosis Factor Inhibitors/therapeutic useABSTRACT
T cells play a pivotal role in reducing disease severity during SARS-CoV-2 infection and formation of long-term immune memory. We studied 50 COVID-19 convalescent patients and found that T cell response was induced more frequently and persisted longer than circulating antibodies. We identified 756 clonotypes specific to nine CD8+ T cell epitopes. Some epitopes were recognized by highly similar public clonotypes. Receptors for other epitopes were extremely diverse, suggesting alternative modes of recognition. We tracked persistence of epitope-specific response and individual clonotypes for a median of eight months after infection. The number of recognized epitopes per patient and quantity of epitope-specific clonotypes decreased over time, but the studied epitopes were characterized by uneven decline in the number of specific T cells. Epitopes with more clonally diverse TCR repertoires induced more pronounced and durable responses. In contrast, the abundance of specific clonotypes in peripheral circulation had no influence on their persistence.
Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Epitopes, T-Lymphocyte , CD8-Positive T-Lymphocytes , Clone CellsABSTRACT
Human leukocyte antigen (HLA) genes are the most polymorphic loci in the human genome and code for proteins that play a key role in guiding adaptive immune responses by presenting foreign and self peptides (ligands) to T cells. Each person carries up to 6 HLA class I variants (maternal and paternal copies of HLA-A, HLA-B and HLA-C genes) and also multiple HLA class II variants, which cumulatively define the landscape of peptides presented to T cells. Each HLA variant has its own repertoire of presented peptides with a certain sequence motif which is mainly defined by peptide anchor residues (typically the second and the last positions for HLA class I ligands) forming key interactions with the peptide-binding groove of HLA. In this study, we aimed to characterize HLA binding preferences in terms of molecular functions of presented proteins. To focus on the ligand presentation bias introduced specifically by HLA-peptide interaction we performed large-scale in silico predictions of binding of all peptides from human proteome for a wide range of HLA variants and established which functions are characteristic for proteins that are more or less preferentially presented by different HLA variants using statistical calculations and gene ontology (GO) analysis. We demonstrated marked distinctions between HLA variants in molecular functions of preferentially presented proteins (e.g. some HLA variants preferentially present membrane and receptor proteins, while others - ribosomal and DNA-binding proteins) and reduced presentation of extracellular matrix and collagen proteins by the majority of HLA variants. To explain these observations we demonstrated that HLA preferentially presents proteins enriched in amino acids which are required as anchor residues for the particular HLA variant. Our observations can be extrapolated to explain the protective effect of certain HLA alleles in infectious diseases, and we hypothesize that they can also explain susceptibility to certain autoimmune diseases and cancers. We demonstrate that these differences lead to differential presentation of HIV, influenza virus, SARS-CoV-1 and SARS-CoV-2 proteins by various HLA alleles. Taking into consideration that HLA alleles are inherited in haplotypes, we hypothesized that haplotypes composed of a combination of HLA variants with different presentation preferences should be more advantageous as they allow presenting a larger repertoire of peptides and avoiding holes in immunopeptidome. Indeed, we demonstrated that HLA-A/HLA-B and HLA-A/HLA-C haplotypes which have a high frequency in the human population are comprised of HLA variants that are more distinct in terms of functions of preferentially presented proteins than the control pairs.
Subject(s)
HLA-A Antigens , HLA-B Antigens , HLA-C Antigens , Haplotypes , Humans , HLA-A Antigens/genetics , HLA-B Antigens/genetics , HLA-C Antigens/genetics , PeptidesABSTRACT
The stability and plasticity of B cell-mediated immune memory ensures the ability to respond to the repeated challenges. We have analyzed the longitudinal dynamics of immunoglobulin heavy chain repertoires from memory B cells, plasmablasts, and plasma cells from the peripheral blood of generally healthy volunteers. We reveal a high degree of clonal persistence in individual memory B cell subsets, with inter-individual convergence in memory and antibody-secreting cells (ASCs). ASC clonotypes demonstrate clonal relatedness to memory B cells, and are transient in peripheral blood. We identify two clusters of expanded clonal lineages with differing prevalence of memory B cells, isotypes, and persistence. Phylogenetic analysis revealed signs of reactivation of persisting memory B cell-enriched clonal lineages, accompanied by new rounds of affinity maturation during proliferation and differentiation into ASCs. Negative selection contributes to both persisting and reactivated lineages, preserving the functionality and specificity of B cell receptors (BCRs) to protect against current and future pathogens.
Subject(s)
Antibody-Producing Cells , Immunologic Memory , Humans , Immunoglobulin Heavy Chains/genetics , Phylogeny , Receptors, Antigen, B-Cell/geneticsABSTRACT
The development and implementation of vaccines have been growing exponentially, remaining one of the major successes of healthcare over the last century. Nowadays, active regular immunizations prevent epidemics of many viral diseases, including tick-borne encephalitis (TBE). Along with the generation of virus-specific antibodies, a highly effective vaccine should induce T cell responses providing long-term immune defense. In this study, we performed longitudinal high-throughput T cell receptor (TCR) sequencing to characterize changes in individual T cell repertoires of 11 donors immunized with an inactivated TBE vaccine. After two-step immunization, we found significant clonal expansion of both CD4+ and CD8+ T cells, ranging from 302 to 1706 vaccine-associated TCRß clonotypes in different donors. We detected several waves of T cell clonal expansion generated by distinct groups of vaccine-responding clones. Both CD4+ and CD8+ vaccine-responding T cell clones formed 17 motifs in TCRß sequences shared by donors with identical HLA alleles. Our results indicate that TBE vaccination leads to a robust T cell response due to the production of a variety of T cell clones with a memory phenotype, which recognize a large set of epitopes.