51
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Pogorelyy MV, Fedorova AD, McLaren JE, Ladell K, Bagaev DV, Eliseev AV, Mikelov AI, Koneva AE, Zvyagin IV, Price DA, Chudakov DM, Shugay M. Exploring the pre-immune landscape of antigen-specific T cells. Genome Med 2018; 10:68. [PMID: 30144804 PMCID: PMC6109350 DOI: 10.1186/s13073-018-0577-7] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 08/06/2018] [Indexed: 12/26/2022] Open
Abstract
Background Adaptive immune responses to newly encountered pathogens depend on the mobilization of antigen-specific clonotypes from a vastly diverse pool of naive T cells. Using recent advances in immune repertoire sequencing technologies, models of the immune receptor rearrangement process, and a database of annotated T cell receptor (TCR) sequences with known specificities, we explored the baseline frequencies of T cells specific for defined human leukocyte antigen (HLA) class I-restricted epitopes in healthy individuals. Methods We used a database of TCR sequences with known antigen specificities and a probabilistic TCR rearrangement model to estimate the baseline frequencies of TCRs specific to distinct antigens epitopespecificT-cells. We verified our estimates using a publicly available collection of TCR repertoires from healthy individuals. We also interrogated a database of immunogenic and non-immunogenic peptides is used to link baseline T-cell frequencies with epitope immunogenicity. Results Our findings revealed a high degree of variability in the prevalence of T cells specific for different antigens that could be explained by the physicochemical properties of the corresponding HLA class I-bound peptides. The occurrence of certain rearrangements was influenced by ancestry and HLA class I restriction, and umbilical cord blood samples contained higher frequencies of common pathogen-specific TCRs. We also identified a quantitative link between specific T cell frequencies and the immunogenicity of cognate epitopes presented by defined HLA class I molecules. Conclusions Our results suggest that the population frequencies of specific T cells are strikingly non-uniform across epitopes that are known to elicit immune responses. This inference leads to a new definition of epitope immunogenicity based on specific TCR frequencies, which can be estimated with a high degree of accuracy in silico, thereby providing a novel framework to integrate computational and experimental genomics with basic and translational research efforts in the field of T cell immunology. Electronic supplementary material The online version of this article (10.1186/s13073-018-0577-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Alla D Fedorova
- Department of Genomics of Adaptive Immunity, IBCH RAS, Moscow, Russia
| | - James E McLaren
- Division of Infection and Immunity, Cardiff University School of Medicine, Cardiff, UK
| | - Kristin Ladell
- Division of Infection and Immunity, Cardiff University School of Medicine, Cardiff, UK
| | - Dmitri V Bagaev
- Department of Genomics of Adaptive Immunity, IBCH RAS, Moscow, Russia
| | - Alexey V Eliseev
- Department of Genomics of Adaptive Immunity, IBCH RAS, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Artem I Mikelov
- Department of Genomics of Adaptive Immunity, IBCH RAS, Moscow, Russia.,Center for Data-Intensive Biomedicine and Biotechnology, Skoltech, Moscow, Russia
| | - Anna E Koneva
- Department of Genomics of Adaptive Immunity, IBCH RAS, Moscow, Russia
| | - Ivan V Zvyagin
- Department of Genomics of Adaptive Immunity, IBCH RAS, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia
| | - David A Price
- Division of Infection and Immunity, Cardiff University School of Medicine, Cardiff, UK.,Systems Immunity Research Institute, Cardiff University School of Medicine, Cardiff, UK
| | - Dmitry M Chudakov
- Department of Genomics of Adaptive Immunity, IBCH RAS, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia.,Center for Data-Intensive Biomedicine and Biotechnology, Skoltech, Moscow, Russia.,Central European Institute of Technology, CEITEC, Brno, Czech Republic
| | - Mikhail Shugay
- Department of Genomics of Adaptive Immunity, IBCH RAS, Moscow, Russia. .,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia. .,Center for Data-Intensive Biomedicine and Biotechnology, Skoltech, Moscow, Russia.
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52
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Egorov ES, Kasatskaya SA, Zubov VN, Izraelson M, Nakonechnaya TO, Staroverov DB, Angius A, Cucca F, Mamedov IZ, Rosati E, Franke A, Shugay M, Pogorelyy MV, Chudakov DM, Britanova OV. The Changing Landscape of Naive T Cell Receptor Repertoire With Human Aging. Front Immunol 2018; 9:1618. [PMID: 30087674 PMCID: PMC6066563 DOI: 10.3389/fimmu.2018.01618] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 06/29/2018] [Indexed: 12/22/2022] Open
Abstract
Human aging is associated with a profound loss of thymus productivity, yet naïve T lymphocytes still maintain their numbers by division in the periphery for many years. The extent of such proliferation may depend on the cytokine environment, including IL-7 and T-cell receptor (TCR) “tonic” signaling mediated by self pMHCs recognition. Additionally, intrinsic properties of distinct subpopulations of naïve T cells could influence the overall dynamics of aging-related changes within the naïve T cell compartment. Here, we investigated the differences in the architecture of TCR beta repertoires for naïve CD4, naïve CD8, naïve CD4+CD25−CD31+ (enriched with recent thymic emigrants, RTE), and mature naïve CD4+CD25−CD31− peripheral blood subsets between young and middle-age/old healthy individuals. In addition to observing the accumulation of clonal expansions (as was shown previously), we reveal several notable changes in the characteristics of T cell repertoire. We observed significant decrease of CDR3 length, NDN insert, and number of non-template added N nucleotides within TCR beta CDR3 with aging, together with a prominent change of physicochemical properties of the central part of CDR3 loop. These changes were similar across CD4, CD8, RTE-enriched, and mature CD4 subsets of naïve T cells, with minimal or no difference observed between the latter two subsets for individuals of the same age group. We also observed an increase in “publicity” (fraction of shared clonotypes) of CD4, but not CD8 naïve T cell repertoires. We propose several explanations for these phenomena built upon previous studies of naïve T-cell homeostasis, and call for further studies of the mechanisms causing the observed changes and of consequences of these changes in respect of the possible holes formed in the landscape of naïve T cell TCR repertoire.
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Affiliation(s)
- Evgeny S Egorov
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Sofya A Kasatskaya
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Vasiliy N Zubov
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Mark Izraelson
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | | | | | - Andrea Angius
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato, Italy
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche, Monserrato, Italy
| | - Ilgar Z Mamedov
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Elisa Rosati
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Kiel University, Kiel, Germany
| | - Mikhail Shugay
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | | | - Dmitriy M Chudakov
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Olga V Britanova
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
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53
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Elhanati Y, Sethna Z, Callan CG, Mora T, Walczak AM. Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination. Immunol Rev 2018; 284:167-179. [PMID: 29944757 PMCID: PMC6033145 DOI: 10.1111/imr.12665] [Citation(s) in RCA: 71] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Despite the extreme diversity of T-cell repertoires, many identical T-cell receptor (TCR) sequences are found in a large number of individual mice and humans. These widely shared sequences, often referred to as "public," have been suggested to be over-represented due to their potential immune functionality or their ease of generation by V(D)J recombination. Here, we show that even for large cohorts, the observed degree of sharing of TCR sequences between individuals is well predicted by a model accounting for the known quantitative statistical biases in the generation process, together with a simple model of thymic selection. Whether a sequence is shared by many individuals is predicted to depend on the number of queried individuals and the sampling depth, as well as on the sequence itself, in agreement with the data. We introduce the degree of publicness conditional on the queried cohort size and the size of the sampled repertoires. Based on these observations, we propose a public/private sequence classifier, "PUBLIC" (Public Universal Binary Likelihood Inference Classifier), based on the generation probability, which performs very well even for small cohort sizes.
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Affiliation(s)
- Yuval Elhanati
- Joseph Henry LaboratoriesPrinceton UniversityPrincetonNJUSA
| | - Zachary Sethna
- Joseph Henry LaboratoriesPrinceton UniversityPrincetonNJUSA
| | | | - Thierry Mora
- Laboratoire de physique statistiqueCNRSSorbonne UniversitéUniversité Paris‐Diderot, and École Normale Supérieure (PSL University)ParisFrance
| | - Aleksandra M. Walczak
- Laboratoire de physique théoriqueCNRSSorbonne Université, and École Normale Supérieure (PSL University)ParisFrance
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54
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Abstract
Probabilistic modeling is fundamental to the statistical analysis of complex data. In addition to forming a coherent description of the data-generating process, probabilistic models enable parameter inference about given datasets. This procedure is well developed in the Bayesian perspective, in which one infers probability distributions describing to what extent various possible parameters agree with the data. In this paper, we motivate and review probabilistic modeling for adaptive immune receptor repertoire data then describe progress and prospects for future work, from germline haplotyping to adaptive immune system deployment across tissues. The relevant quantities in immune sequence analysis include not only continuous parameters such as gene use frequency but also discrete objects such as B-cell clusters and lineages. Throughout this review, we unravel the many opportunities for probabilistic modeling in adaptive immune receptor analysis, including settings for which the Bayesian approach holds substantial promise (especially if one is optimistic about new computational methods). From our perspective, the greatest prospects for progress in probabilistic modeling for repertoires concern ancestral sequence estimation for B-cell receptor lineages, including uncertainty from germline genotype, rearrangement, and lineage development.
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Affiliation(s)
- Branden Olson
- Computational Biology Program Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Mail stop: M1-B514 Seattle, WA 98109-1024 phone: +1 206 667 7318
| | - Frederick A. Matsen
- Computational Biology Program Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N., Mail stop: M1-B514 Seattle, WA 98109-1024 phone: +1 206 667 7318
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55
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Pogorelyy MV, Minervina AA, Chudakov DM, Mamedov IZ, Lebedev YB, Mora T, Walczak AM. Method for identification of condition-associated public antigen receptor sequences. eLife 2018. [PMID: 29533178 PMCID: PMC5873893 DOI: 10.7554/elife.33050] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type one diabetes responsive TCRβ sequences .
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Affiliation(s)
- Mikhail V Pogorelyy
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia
| | - Anastasia A Minervina
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia
| | - Dmitriy M Chudakov
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia.,Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, Russia.,Central European Institute of Technology, Brno, Czech republic
| | - Ilgar Z Mamedov
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia
| | - Yuri B Lebedev
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia.,Biological Faculty, Moscow State University, Moscow, Russia
| | - Thierry Mora
- Laboratoire de Physique Statistique, CNRS, Sorbonne University, Paris-Diderot University, École Normale Supérieure, Paris, France
| | - Aleksandra M Walczak
- Laboratoire de Physique Theorique, CNRS, Sorbonne University, École Normale Supérieure, Paris, France
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56
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Komech EA, Pogorelyy MV, Egorov ES, Britanova OV, Rebrikov DV, Bochkova AG, Shmidt EI, Shostak NA, Shugay M, Lukyanov S, Mamedov IZ, Lebedev YB, Chudakov DM, Zvyagin IV. CD8+ T cells with characteristic T cell receptor beta motif are detected in blood and expanded in synovial fluid of ankylosing spondylitis patients. Rheumatology (Oxford) 2018; 57:1097-1104. [DOI: 10.1093/rheumatology/kex517] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Indexed: 12/11/2022] Open
Affiliation(s)
- Ekaterina A Komech
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Mikhail V Pogorelyy
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Evgeniy S Egorov
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Olga V Britanova
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Denis V Rebrikov
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Gynecology and Perinatology, Kulakov Research Center for Obstetrics, Moscow, Russia
| | - Anna G Bochkova
- V.A. Nasonova Research Institute of Rheumatology, Moscow, Russia
| | - Evgeniya I Shmidt
- City Clinical Hospital #1, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Nadejda A Shostak
- City Clinical Hospital #1, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Mikhail Shugay
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, Russia
| | - Sergey Lukyanov
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Ilgar Z Mamedov
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Gynecology and Perinatology, Kulakov Research Center for Obstetrics, Moscow, Russia
| | - Yuriy B Lebedev
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Biological Department, Lomonosov Moscow State University, Moscow, Russia
| | - Dmitriy M Chudakov
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Adaptive Immunity Group, Central European Institute of Technology, Brno, Czech Republic
| | - Ivan V Zvyagin
- Molecular Technologies Department, Translational Medicine Institute, Pirogov Russian National Research Medical University, Moscow, Russia
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
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57
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Sycheva AL, Pogorelyy MV, Komech EA, Minervina AA, Zvyagin IV, Staroverov DB, Chudakov DM, Lebedev YB, Mamedov IZ. Quantitative profiling reveals minor changes of T cell receptor repertoire in response to subunit inactivated influenza vaccine. Vaccine 2018; 36:1599-1605. [PMID: 29454515 DOI: 10.1016/j.vaccine.2018.02.027] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2017] [Revised: 01/22/2018] [Accepted: 02/02/2018] [Indexed: 12/26/2022]
Abstract
Vaccination against influenza is widely used to protect against seasonal flu epidemic although its effectiveness is debated. Here we performed deep quantitative T cell receptor repertoire profiling in peripheral blood of a healthy volunteer in response to trivalent subunit influenza vaccine. We did not observe significant rebuilding of peripheral blood T cell receptors composition in response to vaccination. However, we found several clonotypes in memory T cell fraction that were undetectable before the vaccination and had a maximum concentration at day 45 after vaccine administration. These cells were found in lower concentration in the course of repertoire monitoring for two years period. Our observation suggests a potential for recruitment of only a limited number of new T cells after each seasonal influenza vaccination.
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Affiliation(s)
- Anastasiia L Sycheva
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia
| | - Mikhail V Pogorelyy
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia
| | - Ekaterina A Komech
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia; Pirogov Russian National Research Medical University, 117997 Moscow, Russia
| | - Anastasia A Minervina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia
| | - Ivan V Zvyagin
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia; Pirogov Russian National Research Medical University, 117997 Moscow, Russia
| | - Dmitriy B Staroverov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia; Pirogov Russian National Research Medical University, 117997 Moscow, Russia
| | - Dmitriy M Chudakov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia; Pirogov Russian National Research Medical University, 117997 Moscow, Russia; Skolkovo Institute of Science and Technology, Skolkovo 143025, Russia; Central European Institute of Technology, Brno 60177, Czech Republic
| | - Yuri B Lebedev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia; Pirogov Russian National Research Medical University, 117997 Moscow, Russia
| | - Ilgar Z Mamedov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Science, Miklukho-Maklaya 16/10, 117997 Moscow, Russia; Pirogov Russian National Research Medical University, 117997 Moscow, Russia.
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58
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Marcou Q, Mora T, Walczak AM. High-throughput immune repertoire analysis with IGoR. Nat Commun 2018; 9:561. [PMID: 29422654 PMCID: PMC5805751 DOI: 10.1038/s41467-018-02832-w] [Citation(s) in RCA: 144] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 01/03/2018] [Indexed: 12/21/2022] Open
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.
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MESH Headings
- B-Lymphocytes/cytology
- B-Lymphocytes/immunology
- Base Sequence
- Benchmarking
- DNA, Complementary/genetics
- DNA, Complementary/immunology
- Gene Expression
- High-Throughput Nucleotide Sequencing
- Humans
- Immunity, Innate
- Molecular Sequence Annotation
- Receptors, Antigen, B-Cell/genetics
- Receptors, Antigen, B-Cell/immunology
- Receptors, Antigen, T-Cell/genetics
- Receptors, Antigen, T-Cell/immunology
- Software
- T-Lymphocytes/cytology
- T-Lymphocytes/immunology
- V(D)J Recombination
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Affiliation(s)
- Quentin Marcou
- Laboratoire de Physique Théorique, CNRS, Sorbonne Université and École Normale Supérieure (PSL), 24, Rue Lhomond, 75005, Paris, France
| | - Thierry Mora
- Laboratoire de Physique Statistique, CNRS, Sorbonne Université, Université Paris-Diderot, and École normale supérieure (PSL), 24, Rue Lhomond, 75005, Paris, France.
| | - Aleksandra M Walczak
- Laboratoire de Physique Théorique, CNRS, Sorbonne Université and École Normale Supérieure (PSL), 24, Rue Lhomond, 75005, Paris, France.
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59
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Mora T. [IGoR: a tool for learning and simulating the random generation of antigen receptors]. Biol Aujourdhui 2018; 211:229-231. [PMID: 29412133 DOI: 10.1051/jbio/2017033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2017] [Indexed: 06/08/2023]
Abstract
Antigen receptors, which form the base of the adaptive immune system, are created stochastically by a DNA editing process called V(D)J recombination. As high-throughput sequencing enables to study the repertoire of these receptors, it is now possible to learn the probabilistic laws of this random process, and to use them to analyse receptors of interest, generate synthetic repertoires to create controls, or aid the identification of receptors that are specific to diseases, with possible applications for medical diagnostics. This article describes how these tasks can be performed using the IGoR software, which can learn statistical models from data, annotate existing sequences, or generate new synthetic ones with the same laws as the recombination process.
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Affiliation(s)
- Thierry Mora
- Laboratoire de physique statistique, École Normale Supérieure, CNRS, UPMC et UPD, 24 rue Lhomond, 75005 Paris, France
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60
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Carey AJ, Hope JL, Mueller YM, Fike AJ, Kumova OK, van Zessen DBH, Steegers EAP, van der Burg M, Katsikis PD. Public Clonotypes and Convergent Recombination Characterize the Naïve CD8 + T-Cell Receptor Repertoire of Extremely Preterm Neonates. Front Immunol 2017; 8:1859. [PMID: 29312340 PMCID: PMC5742125 DOI: 10.3389/fimmu.2017.01859] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Accepted: 12/07/2017] [Indexed: 01/03/2023] Open
Abstract
Respiratory support improvements have aided survival of premature neonates, but infection susceptibility remains a predominant problem. We previously reported that neonatal mice have a rapidly evolving T-cell receptor (TCR) repertoire that impairs CD8+ T cell immunity. To understand the impact of prematurity on the human CD8+ TCR repertoire, we performed next-generation sequencing of the complementarity-determining region 3 (CDR3) from the rearranged TCR variable beta (Vβ) in sorted, naïve CD8+ T cells from extremely preterm neonates (23–27 weeks gestation), term neonates (37–41 weeks gestation), children (16–56 months), and adults (25–50 years old). Strikingly, preterm neonates had an increased frequency of public clonotypes shared between unrelated individuals. Public clonotypes identified in preterm infants were encoded by germline gene sequences, and some of these clonotypes persisted into adulthood. The preterm neonatal naïve CD8+ TCR repertoire exhibited convergent recombination, characterized by different nucleotide sequences encoding the same amino acid CDR3 sequence. As determined by Pielou’s evenness and iChao1 metrics, extremely preterm neonates have less clonality, and a much lower bound for the number of unique TCR within an individual preterm neonate, which indicates a less rich and diverse repertoire, as compared to term neonates, children, and adults. This suggests that T cell selection in the preterm neonate may be less stringent or different. Our analysis is the first to compare the TCR repertoire of naïve CD8+ T cells between viable preterm neonates and term neonates. We find preterm neonates have a repertoire immaturity which potentially contributes to their increased infection susceptibility. A developmentally regulated, evenly distributed repertoire in preterm neonates may lead to the inclusion of public TCR CDR3β sequences that overlap between unrelated individuals in the preterm repertoire.
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Affiliation(s)
- Alison J Carey
- Department of Pediatrics, Drexel University College of Medicine, Philadelphia, PA, United States.,Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Jennifer L Hope
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States.,Department of Immunology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Yvonne M Mueller
- Department of Immunology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Adam J Fike
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
| | - Ogan K Kumova
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States
| | - David B H van Zessen
- Department of Immunology, Erasmus University Medical Center, Rotterdam, Netherlands.,Department of Bioinformatics, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Eric A P Steegers
- Department of Obstetrics and Gynecology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Mirjam van der Burg
- Department of Immunology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Peter D Katsikis
- Department of Immunology, Erasmus University Medical Center, Rotterdam, Netherlands
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61
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Izraelson M, Nakonechnaya TO, Moltedo B, Egorov ES, Kasatskaya SA, Putintseva EV, Mamedov IZ, Staroverov DB, Shemiakina II, Zakharova MY, Davydov AN, Bolotin DA, Shugay M, Chudakov DM, Rudensky AY, Britanova OV. Comparative analysis of murine T-cell receptor repertoires. Immunology 2017; 153:133-144. [PMID: 29080364 DOI: 10.1111/imm.12857] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Revised: 10/06/2017] [Accepted: 10/06/2017] [Indexed: 12/21/2022] Open
Abstract
For understanding the rules and laws of adaptive immunity, high-throughput profiling of T-cell receptor (TCR) repertoires becomes a powerful tool. The structure of TCR repertoires is instructive even before the antigen specificity of each particular receptor becomes available. It embodies information about the thymic and peripheral selection of T cells; the readiness of an adaptive immunity to withstand new challenges; the character, magnitude and memory of immune responses; and the aetiological and functional proximity of T-cell subsets. Here, we describe our current analytical approaches for the comparative analysis of murine TCR repertoires, and show several examples of how these approaches can be applied for particular experimental settings. We analyse the efficiency of different metrics used for estimation of repertoire diversity, repertoire overlap, V-gene and J-gene segments usage similarity, and amino acid composition of CDR3. We discuss basic differences of these metrics and their advantages and limitations in different experimental models, and we provide guidelines for choosing an efficient way to lead a comparative analysis of TCR repertoires. Applied to the various known and newly developed mouse models, such analysis should allow us to disentangle multiple sophisticated puzzles in adaptive immunity.
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Affiliation(s)
- Mark Izraelson
- Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia.,Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia
| | - Tatiana O Nakonechnaya
- Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia.,Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia
| | - Bruno Moltedo
- Howard Hughes Medical Institute and Immunology Program, Ludwig Center at Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Evgeniy S Egorov
- Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia.,Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia
| | - Sofya A Kasatskaya
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia
| | | | - Ilgar Z Mamedov
- Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia.,Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia
| | - Dmitriy B Staroverov
- Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia.,Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia
| | - Irina I Shemiakina
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Maria Y Zakharova
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | | | - Dmitriy A Bolotin
- Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia.,MiLaboratory LLC, Skolkovo Innovation Centre, Moscow, Russia
| | - Mikhail Shugay
- Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia.,Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia.,Central European Institute of Technology, Brno, Czech Republic.,Centre for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Skolkovo, Russia
| | - Dmitriy M Chudakov
- Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia.,Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia.,Central European Institute of Technology, Brno, Czech Republic.,Centre for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Skolkovo, Russia
| | - Alexander Y Rudensky
- Howard Hughes Medical Institute and Immunology Program, Ludwig Center at Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Olga V Britanova
- Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia.,Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Pirogov Russian National Research Medical University, Moscow, Russia
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62
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Brodin J, Zanini F, Thebo L, Lanz C, Bratt G, Neher RA, Albert J. Establishment and stability of the latent HIV-1 DNA reservoir. eLife 2016; 5. [PMID: 27855060 PMCID: PMC5201419 DOI: 10.7554/elife.18889] [Citation(s) in RCA: 98] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Accepted: 11/01/2016] [Indexed: 12/11/2022] Open
Abstract
HIV-1 infection cannot be cured because the virus persists as integrated proviral DNA in long-lived cells despite years of suppressive antiretroviral therapy (ART). In a previous paper (Zanini et al, 2015) we documented HIV-1 evolution in 10 untreated patients. Here we characterize establishment, turnover, and evolution of viral DNA reservoirs in the same patients after 3–18 years of suppressive ART. A median of 14% (range 0–42%) of the DNA sequences were defective due to G-to-A hypermutation. Remaining DNA sequences showed no evidence of evolution over years of suppressive ART. Most sequences from the DNA reservoirs were very similar to viruses actively replicating in plasma (RNA sequences) shortly before start of ART. The results do not support persistent HIV-1 replication as a mechanism to maintain the HIV-1 reservoir during suppressive therapy. Rather, the data indicate that DNA variants are turning over as long as patients are untreated and that suppressive ART halts this turnover. DOI:http://dx.doi.org/10.7554/eLife.18889.001
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Affiliation(s)
- Johanna Brodin
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden
| | - Fabio Zanini
- Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Lina Thebo
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden
| | - Christa Lanz
- Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Göran Bratt
- Department of Clinical Science and Education, Stockholm South General Hospital, Stockholm, Sweden.,Venhälsan, Stockholm South General Hospital, Stockholm, Sweden
| | - Richard A Neher
- Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Jan Albert
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden.,Department of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden
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