1
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Tsareva A, Shelyakin PV, Shagina IA, Myshkin MY, Merzlyak EM, Kriukova VV, Apt AS, Linge IA, Chudakov DM, Britanova OV. Aberrant adaptive immune response underlies genetic susceptibility to tuberculosis. Front Immunol 2024; 15:1380971. [PMID: 38799462 PMCID: PMC11116662 DOI: 10.3389/fimmu.2024.1380971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 04/11/2024] [Indexed: 05/29/2024] Open
Abstract
Mycobacterium tuberculosis (Mtb) remains a major threat worldwide, although only a fraction of infected individuals develops tuberculosis (TB). TB susceptibility is shaped by multiple genetic factors, and we performed comparative immunological analysis of two mouse strains to uncover relevant mechanisms underlying susceptibility and resistance. C57BL/6 mice are relatively TB-resistant, whereas I/St mice are prone to develop severe TB, partly due to the MHC-II allelic variant that shapes suboptimal CD4+ T cell receptor repertoire. We investigated the repertoires of lung-infiltrating helper T cells and B cells at the progressed stage in both strains. We found that lung CD4+ T cell repertoires of infected C57BL/6 but not I/St mice contained convergent TCR clusters with functionally confirmed Mtb specificity. Transcriptomic analysis revealed a more prominent Th1 signature in C57BL/6, and expression of pro-inflammatory IL-16 in I/St lung-infiltrating helper T cells. The two strains also showed distinct Th2 signatures. Furthermore, the humoral response of I/St mice was delayed, less focused, and dominated by IgG/IgM isotypes, whereas C57BL/6 mice generated more Mtb antigen-focused IgA response. We conclude that the inability of I/St mice to produce a timely and efficient anti-Mtb adaptive immune responses arises from a suboptimal helper T cell landscape that also impacts the humoral response, leading to diffuse inflammation and severe disease.
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Affiliation(s)
- Anastasiia Tsareva
- Precision Oncology Division, Boston Gene Laboratory, Waltham, MA, United States
| | - Pavel V. Shelyakin
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Abu Dhabi Stem Cells Center, Abu Dhabi, United Arab Emirates
| | - Irina A. Shagina
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Mikhail Yu. Myshkin
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Ekaterina M. Merzlyak
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Valeriia V. Kriukova
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Alexander S. Apt
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Irina A. Linge
- Laboratory for Immunogenetics, Central Tuberculosis Research Institute, Moscow, Russia
| | - Dmitriy M. Chudakov
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Abu Dhabi Stem Cells Center, Abu Dhabi, United Arab Emirates
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Central European Institute of Technology, Masaryk University, Brno, Czechia
| | - Olga V. Britanova
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
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2
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Chi H, Pepper M, Thomas PG. Principles and therapeutic applications of adaptive immunity. Cell 2024; 187:2052-2078. [PMID: 38670065 PMCID: PMC11177542 DOI: 10.1016/j.cell.2024.03.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 03/01/2024] [Accepted: 03/25/2024] [Indexed: 04/28/2024]
Abstract
Adaptive immunity provides protection against infectious and malignant diseases. These effects are mediated by lymphocytes that sense and respond with targeted precision to perturbations induced by pathogens and tissue damage. Here, we review key principles underlying adaptive immunity orchestrated by distinct T cell and B cell populations and their extensions to disease therapies. We discuss the intracellular and intercellular processes shaping antigen specificity and recognition in immune activation and lymphocyte functions in mediating effector and memory responses. We also describe how lymphocytes balance protective immunity against autoimmunity and immunopathology, including during immune tolerance, response to chronic antigen stimulation, and adaptation to non-lymphoid tissues in coordinating tissue immunity and homeostasis. Finally, we discuss extracellular signals and cell-intrinsic programs underpinning adaptive immunity and conclude by summarizing key advances in vaccination and engineering adaptive immune responses for therapeutic interventions. A deeper understanding of these principles holds promise for uncovering new means to improve human health.
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Affiliation(s)
- Hongbo Chi
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA.
| | - Marion Pepper
- Department of Immunology, University of Washington, Seattle, WA, USA.
| | - Paul G Thomas
- Department of Host-Microbe Interactions and Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA.
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3
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Pavlova AV, Zvyagin IV, Shugay M. Detecting T-cell clonal expansions and quantifying clone survival using deep profiling of immune repertoires. Front Immunol 2024; 15:1321603. [PMID: 38633256 PMCID: PMC11021634 DOI: 10.3389/fimmu.2024.1321603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Accepted: 03/12/2024] [Indexed: 04/19/2024] Open
Abstract
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.
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Affiliation(s)
- Anastasia V. Pavlova
- Institute of Translational Medicine, Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Ivan V. Zvyagin
- Institute of Translational Medicine, Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
- Dmitriy Rogachev National Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia
| | - Mikhail Shugay
- Institute of Translational Medicine, Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, Moscow, Russia
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
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4
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Yin R, Melton S, Huseby ES, Kardar M, Chakraborty AK. How persistent infection overcomes peripheral tolerance mechanisms to cause T cell-mediated autoimmune disease. Proc Natl Acad Sci U S A 2024; 121:e2318599121. [PMID: 38446856 PMCID: PMC10945823 DOI: 10.1073/pnas.2318599121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/06/2024] [Indexed: 03/08/2024] Open
Abstract
T cells help orchestrate immune responses to pathogens, and their aberrant regulation can trigger autoimmunity. Recent studies highlight that a threshold number of T cells (a quorum) must be activated in a tissue to mount a functional immune response. These collective effects allow the T cell repertoire to respond to pathogens while suppressing autoimmunity due to circulating autoreactive T cells. Our computational studies show that increasing numbers of pathogenic peptides targeted by T cells during persistent or severe viral infections increase the probability of activating T cells that are weakly reactive to self-antigens (molecular mimicry). These T cells are easily re-activated by the self-antigens and contribute to exceeding the quorum threshold required to mount autoimmune responses. Rare peptides that activate many T cells are sampled more readily during severe/persistent infections than in acute infections, which amplifies these effects. Experiments in mice to test predictions from these mechanistic insights are suggested.
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Affiliation(s)
- Rose Yin
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Samuel Melton
- Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Eric S. Huseby
- Basic Pathology, Department of Pathology, University of Massachusetts Medical School, Worcester, MA01655
| | - Mehran Kardar
- Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Arup K. Chakraborty
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA02139
- Physics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA02139
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA02139
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA02139
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5
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Böttcher L, Wald S, Chou T. Mathematical Characterization of Private and Public Immune Receptor Sequences. Bull Math Biol 2023; 85:102. [PMID: 37707621 PMCID: PMC10501991 DOI: 10.1007/s11538-023-01190-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 07/26/2023] [Indexed: 09/15/2023]
Abstract
Diverse T and B cell repertoires play an important role in mounting effective immune responses against a wide range of pathogens and malignant cells. The number of unique T and B cell clones is characterized by T and B cell receptors (TCRs and BCRs), respectively. Although receptor sequences are generated probabilistically by recombination processes, clinical studies found a high degree of sharing of TCRs and BCRs among different individuals. In this work, we use a general probabilistic model for T/B cell receptor clone abundances to define "publicness" or "privateness" and information-theoretic measures for comparing the frequency of sampled sequences observed across different individuals. We derive mathematical formulae to quantify the mean and the variances of clone richness and overlap. Our results can be used to evaluate the effect of different sampling protocols on abundances of clones within an individual as well as the commonality of clones across individuals. Using synthetic and empirical TCR amino acid sequence data, we perform simulations to study expected clonal commonalities across multiple individuals. Based on our formulae, we compare these simulated results with the analytically predicted mean and variances of the repertoire overlap. Complementing the results on simulated repertoires, we derive explicit expressions for the richness and its uncertainty for specific, single-parameter truncated power-law probability distributions. Finally, the information loss associated with grouping together certain receptor sequences, as is done in spectratyping, is also evaluated. Our approach can be, in principle, applied under more general and mechanistically realistic clone generation models.
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Affiliation(s)
- Lucas Böttcher
- Department of Computational Science and Philosophy, Frankfurt School of Finance and Management, 60322 Frankfurt am Main, Germany
- Department of Computational Medicine, University of California, Los Angeles, 621 Charles E. Young Dr. S., Los Angeles, 90095-1766 CA USA
- Department of Medicine, University of Florida, Gainesville, 32610 FL USA
| | - Sascha Wald
- Statistical Physics Group, Centre for Fluid and Complex Systems, Coventry University, Priory Street, Coventry, CV1 5FB UK
| | - Tom Chou
- Department of Computational Medicine, University of California, Los Angeles, 621 Charles E. Young Dr. S., Los Angeles, 90095-1766 CA USA
- Department of Mathematics, University of California, Los Angeles, 520 Portola Plaza, Los Angeles, 90095-1555 CA USA
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6
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Bravi B, Di Gioacchino A, Fernandez-de-Cossio-Diaz J, Walczak AM, Mora T, Cocco S, Monasson R. A transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity. eLife 2023; 12:e85126. [PMID: 37681658 PMCID: PMC10522340 DOI: 10.7554/elife.85126] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 09/07/2023] [Indexed: 09/09/2023] Open
Abstract
Antigen immunogenicity and the specificity of binding of T-cell receptors to antigens are key properties underlying effective immune responses. Here we propose diffRBM, an approach based on transfer learning and Restricted Boltzmann Machines, to build sequence-based predictive models of these properties. DiffRBM is designed to learn the distinctive patterns in amino-acid composition that, on the one hand, underlie the antigen's probability of triggering a response, and on the other hand the T-cell receptor's ability to bind to a given antigen. We show that the patterns learnt by diffRBM allow us to predict putative contact sites of the antigen-receptor complex. We also discriminate immunogenic and non-immunogenic antigens, antigen-specific and generic receptors, reaching performances that compare favorably to existing sequence-based predictors of antigen immunogenicity and T-cell receptor specificity.
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Affiliation(s)
- Barbara Bravi
- Department of Mathematics, Imperial College LondonLondonUnited Kingdom
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris-CitéParisFrance
| | - Andrea Di Gioacchino
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris-CitéParisFrance
| | - Jorge Fernandez-de-Cossio-Diaz
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris-CitéParisFrance
| | - Aleksandra M Walczak
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris-CitéParisFrance
| | - Thierry Mora
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris-CitéParisFrance
| | - Simona Cocco
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris-CitéParisFrance
| | - Rémi Monasson
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université Paris-CitéParisFrance
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7
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Li X, Liang H, Fan J. Prospects of Cytomegalovirus-Specific T-Cell Receptors in Clinical Diagnosis and Therapy. Viruses 2023; 15:1334. [PMID: 37376633 DOI: 10.3390/v15061334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 06/03/2023] [Accepted: 06/04/2023] [Indexed: 06/29/2023] Open
Abstract
Human cytomegalovirus (HCMV) is responsible for widespread infections worldwide. In immunocompetent individuals it is typically latent, while infection or reactivation in immunocompromised individuals can result in severe clinical symptoms or even death. Although there has been significant progress in the treatment and diagnosis of HCMV infection in recent years, numerous shortcomings and developmental limitations persist. There is an urgent need to develop innovative, safe, and effective treatments, as well as to explore early and timely diagnostic strategies for HCMV infection. Cell-mediated immune responses are the primary factor controlling HCMV infection and replication, but the protective role of humoral immune responses remains controversial. T-cells, key effector cells of the cellular immune system, are critical for clearing and preventing HCMV infection. The T-cell receptor (TCR) lies at the heart of T-cell immune responses, and its diversity enables the immune system to differentiate between self and non-self. Given the significant influence of cellular immunity on human health and the indispensable role of the TCR in T-cell immune responses, we posit that the impact of TCR on the development of novel diagnostic and prognostic methods, as well as on patient monitoring and management of clinical HCMV infection, will be far-reaching and profound. High-throughput and single-cell sequencing technologies have facilitated unprecedented quantitative detection of TCR diversity. With these current sequencing technologies, researchers have already obtained a vast number of TCR sequences. It is plausible that in the near future studies on TCR repertoires will be instrumental in assessing vaccine efficacy, immunotherapeutic strategies, and the early diagnosis of HCMV infection.
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Affiliation(s)
- Xuejie Li
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Hanying Liang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Jun Fan
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310003, China
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8
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Jiang Y, Li SC. Deep autoregressive generative models capture the intrinsics embedded in T-cell receptor repertoires. Brief Bioinform 2023; 24:7031156. [PMID: 36752378 DOI: 10.1093/bib/bbad038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 01/07/2023] [Accepted: 01/18/2023] [Indexed: 02/09/2023] Open
Abstract
T-cell receptors (TCRs) play an essential role in the adaptive immune system. Probabilistic models for TCR repertoires can help decipher the underlying complex sequence patterns and provide novel insights into understanding the adaptive immune system. In this work, we develop TCRpeg, a deep autoregressive generative model to unravel the sequence patterns of TCR repertoires. TCRpeg largely outperforms state-of-the-art methods in estimating the probability distribution of a TCR repertoire, boosting the average accuracy from 0.672 to 0.906 measured by the Pearson correlation coefficient. Furthermore, with promising performance in probability inference, TCRpeg improves on a range of TCR-related tasks: profiling TCR repertoire probabilistically, classifying antigen-specific TCRs, validating previously discovered TCR motifs, generating novel TCRs and augmenting TCR data. Our results and analysis highlight the flexibility and capacity of TCRpeg to extract TCR sequence information, providing a novel approach for deciphering complex immunogenomic repertoires.
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Affiliation(s)
- Yuepeng Jiang
- Department of Computer science, City University of Hong Kong, Kowloon Tong, Hong Kong
| | - Shuai Cheng Li
- Department of Computer science, City University of Hong Kong, Kowloon Tong, Hong Kong
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9
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Ruiz Ortega M, Spisak N, Mora T, Walczak AM. Modeling and predicting the overlap of B- and T-cell receptor repertoires in healthy and SARS-CoV-2 infected individuals. PLoS Genet 2023; 19:e1010652. [PMID: 36827454 PMCID: PMC10075420 DOI: 10.1371/journal.pgen.1010652] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 04/05/2023] [Accepted: 02/02/2023] [Indexed: 02/26/2023] Open
Abstract
Adaptive immunity's success relies on the extraordinary diversity of protein receptors on B and T cell membranes. Despite this diversity, the existence of public receptors shared by many individuals gives hope for developing population-wide vaccines and therapeutics. Using probabilistic modeling, we show many of these public receptors are shared by chance in healthy individuals. This predictable overlap is driven not only by biases in the random generation process of receptors, as previously reported, but also by their common functional selection. However, the model underestimates sharing between repertoires of individuals infected with SARS-CoV-2, suggesting strong specific antigen-driven convergent selection. We exploit this discrepancy to identify COVID-associated receptors, which we validate against datasets of receptors with known viral specificity. We study their properties in terms of sequence features and network organization, and use them to design an accurate diagnostic tool for predicting SARS-CoV-2 status from repertoire data.
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Affiliation(s)
- María Ruiz Ortega
- Laboratoire de physique de l’École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
| | - Natanael Spisak
- Laboratoire de physique de l’École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
| | - Thierry Mora
- Laboratoire de physique de l’École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
| | - Aleksandra M. Walczak
- Laboratoire de physique de l’École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
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10
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Camaglia F, Ryvkin A, Greenstein E, Reich-Zeliger S, Chain B, Mora T, Walczak AM, Friedman N. Quantifying changes in the T cell receptor repertoire during thymic development. eLife 2023; 12:81622. [PMID: 36661220 PMCID: PMC9934861 DOI: 10.7554/elife.81622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 01/18/2023] [Indexed: 01/21/2023] Open
Abstract
One of the feats of adaptive immunity is its ability to recognize foreign pathogens while sparing the self. During maturation in the thymus, T cells are selected through the binding properties of their antigen-specific T-cell receptor (TCR), through the elimination of both weakly (positive selection) and strongly (negative selection) self-reactive receptors. However, the impact of thymic selection on the TCR repertoire is poorly understood. Here, we use transgenic Nur77-mice expressing a T-cell activation reporter to study the repertoires of thymic T cells at various stages of their development, including cells that do not pass selection. We combine high-throughput repertoire sequencing with statistical inference techniques to characterize the selection of the TCR in these distinct subsets. We find small but significant differences in the TCR repertoire parameters between the maturation stages, which recapitulate known differentiation pathways leading to the CD4+ and CD8+ subtypes. These differences can be simulated by simple models of selection acting linearly on the sequence features. We find no evidence of specific sequences or sequence motifs or features that are suppressed by negative selection. These results favour a collective or statistical model for T-cell self non-self discrimination, where negative selection biases the repertoire away from self recognition, rather than ensuring lack of self-reactivity at the single-cell level.
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Affiliation(s)
- Francesco Camaglia
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Arie Ryvkin
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
| | - Erez Greenstein
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
| | | | - Benny Chain
- Division of Infection and Immunity, University College LondonLondonUnited Kingdom
| | - Thierry Mora
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Aleksandra M Walczak
- Laboratoire de physique de l’École normale supérieure, CNRS, PSL University, Sorbonne Université, and Université de ParisParisFrance
| | - Nir Friedman
- Department of Immunology, Weizmann Institute of ScienceRehovotIsrael
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11
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Krishnamurthy K, Hermundstad AM, Mora T, Walczak AM, Balasubramanian V. Disorder and the Neural Representation of Complex Odors. Front Comput Neurosci 2022; 16:917786. [PMID: 36003684 PMCID: PMC9393645 DOI: 10.3389/fncom.2022.917786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 05/17/2022] [Indexed: 11/25/2022] Open
Abstract
Animals smelling in the real world use a small number of receptors to sense a vast number of natural molecular mixtures, and proceed to learn arbitrary associations between odors and valences. Here, we propose how the architecture of olfactory circuits leverages disorder, diffuse sensing and redundancy in representation to meet these immense complementary challenges. First, the diffuse and disordered binding of receptors to many molecules compresses a vast but sparsely-structured odor space into a small receptor space, yielding an odor code that preserves similarity in a precise sense. Introducing any order/structure in the sensing degrades similarity preservation. Next, lateral interactions further reduce the correlation present in the low-dimensional receptor code. Finally, expansive disordered projections from the periphery to the central brain reconfigure the densely packed information into a high-dimensional representation, which contains multiple redundant subsets from which downstream neurons can learn flexible associations and valences. Moreover, introducing any order in the expansive projections degrades the ability to recall the learned associations in the presence of noise. We test our theory empirically using data from Drosophila. Our theory suggests that the neural processing of sparse but high-dimensional olfactory information differs from the other senses in its fundamental use of disorder.
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Affiliation(s)
- Kamesh Krishnamurthy
- Joseph Henry Laboratories of Physics and Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States
| | - Ann M. Hermundstad
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
| | - Thierry Mora
- Laboratoire de Physique Statistique, UMR8550, CNRS, UPMC and École Normale Supérieure, Paris, France
| | - Aleksandra M. Walczak
- Laboratoire de Physique Théorique, UMR8549m CNRS, UPMC and École Normale Supérieure, Paris, France
| | - Vijay Balasubramanian
- David Rittenhouse and Richards Laboratories, University of Pennsylvania, Philadelphia, PA, United States
- *Correspondence: Vijay Balasubramanian
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12
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Katayama Y, Kobayashi TJ. Comparative Study of Repertoire Classification Methods Reveals Data Efficiency of k-mer Feature Extraction. Front Immunol 2022; 13:797640. [PMID: 35936014 PMCID: PMC9346074 DOI: 10.3389/fimmu.2022.797640] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 06/20/2022] [Indexed: 01/18/2023] Open
Abstract
The repertoire of T cell receptors encodes various types of immunological information. Machine learning is indispensable for decoding such information from repertoire datasets measured by next-generation sequencing (NGS). In particular, the classification of repertoires is the most basic task, which is relevant for a variety of scientific and clinical problems. Supported by the recent appearance of large datasets, efficient but data-expensive methods have been proposed. However, it is unclear whether they can work efficiently when the available sample size is severely restricted as in practical situations. In this study, we demonstrate that their performances can be impaired substantially below critical sample sizes. To complement this drawback, we propose MotifBoost, which exploits the information of short k-mer motifs of TCRs. MotifBoost can perform the classification as efficiently as a deep learning method on large datasets while providing more stable and reliable results on small datasets. We tested MotifBoost on the four small datasets which consist of various conditions such as Cytomegalovirus (CMV), HIV, α-chain, β-chain and it consistently preserved the stability. We also clarify that the robustness of MotifBoost can be attributed to the efficiency of k-mer motifs as representation features of repertoires. Finally, by comparing the predictions of these methods, we show that the whole sequence identity and sequence motifs encode partially different information and that a combination of such complementary information is necessary for further development of repertoire analysis.
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Affiliation(s)
- Yotaro Katayama
- Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- *Correspondence: Yotaro Katayama,
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13
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Katayama Y, Yokota R, Akiyama T, Kobayashi TJ. Machine Learning Approaches to TCR Repertoire Analysis. Front Immunol 2022; 13:858057. [PMID: 35911778 PMCID: PMC9334875 DOI: 10.3389/fimmu.2022.858057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 06/07/2022] [Indexed: 11/13/2022] Open
Abstract
Sparked by the development of genome sequencing technology, the quantity and quality of data handled in immunological research have been changing dramatically. Various data and database platforms are now driving the rapid progress of machine learning for immunological data analysis. Of various topics in immunology, T cell receptor repertoire analysis is one of the most important targets of machine learning for assessing the state and abnormalities of immune systems. In this paper, we review recent repertoire analysis methods based on machine learning and deep learning and discuss their prospects.
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Affiliation(s)
- Yotaro Katayama
- Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- *Correspondence: Yotaro Katayama,
| | - Ryo Yokota
- National Research Institute of Police Science, Kashiwa, Chiba, Japan
| | - Taishin Akiyama
- Laboratory for Immune Homeostasis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Graduate School of Medical Life Science, Yokohama City University, Yokohama, Japan
| | - Tetsuya J. Kobayashi
- Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
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14
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Dessalles R, Pan Y, Xia M, Maestrini D, D'Orsogna MR, Chou T. How Naive T-Cell Clone Counts Are Shaped By Heterogeneous Thymic Output and Homeostatic Proliferation. Front Immunol 2022; 12:735135. [PMID: 35250963 PMCID: PMC8891377 DOI: 10.3389/fimmu.2021.735135] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
The specificity of T cells is that each T cell has only one T cell receptor (TCR). A T cell clone represents a collection of T cells with the same TCR sequence. Thus, the number of different T cell clones in an organism reflects the number of different T cell receptors (TCRs) that arise from recombination of the V(D)J gene segments during T cell development in the thymus. TCR diversity and more specifically, the clone abundance distribution, are important factors in immune functions. Specific recombination patterns occur more frequently than others while subsequent interactions between TCRs and self-antigens are known to trigger proliferation and sustain naive T cell survival. These processes are TCR-dependent, leading to clone-dependent thymic export and naive T cell proliferation rates. We describe the heterogeneous steady-state population of naive T cells (those that have not yet been antigenically triggered) by using a mean-field model of a regulated birth-death-immigration process. After accounting for random sampling, we investigate how TCR-dependent heterogeneities in immigration and proliferation rates affect the shape of clone abundance distributions (the number of different clones that are represented by a specific number of cells, or “clone counts”). By using reasonable physiological parameter values and fitting predicted clone counts to experimentally sampled clone abundances, we show that realistic levels of heterogeneity in immigration rates cause very little change to predicted clone-counts, but that modest heterogeneity in proliferation rates can generate the observed clone abundances. Our analysis provides constraints among physiological parameters that are necessary to yield predictions that qualitatively match the data. Assumptions of the model and potentially other important mechanistic factors are discussed.
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Affiliation(s)
- Renaud Dessalles
- Department of Computational Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
| | - Yunbei Pan
- Department of Mathematics, California State University at Northridge, Los Angeles, CA, United States
| | - Mingtao Xia
- Department of Mathematics, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
| | - Davide Maestrini
- Department of Computational Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
| | - Maria R D'Orsogna
- Department of Computational Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States.,Department of Mathematics, California State University at Northridge, Los Angeles, CA, United States
| | - Tom Chou
- Department of Computational Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States.,Department of Mathematics, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
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15
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Massey J, Jackson K, Singh M, Hughes B, Withers B, Ford C, Khoo M, Hendrawan K, Zaunders J, Charmeteau-De Muylder B, Cheynier R, Luciani F, Ma D, Moore J, Sutton I. Haematopoietic Stem Cell Transplantation Results in Extensive Remodelling of the Clonal T Cell Repertoire in Multiple Sclerosis. Front Immunol 2022; 13:798300. [PMID: 35197974 PMCID: PMC8859174 DOI: 10.3389/fimmu.2022.798300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 01/13/2022] [Indexed: 12/29/2022] Open
Abstract
Autologous haematopoietic stem cell transplantation (AHSCT) is a vital therapeutic option for patients with highly active multiple sclerosis (MS). Rates of remission suggest AHSCT is the most effective form of immunotherapy in controlling the disease. Despite an evolving understanding of the biology of immune reconstitution following AHSCT, the mechanism by which AHSCT enables sustained disease remission beyond the period of lymphopenia remains to be elucidated. Auto-reactive T cells are considered central to MS pathogenesis. Here, we analyse T cell reconstitution for 36 months following AHSCT in a cohort of highly active MS patients. Through longitudinal analysis of sorted naïve and memory T cell clones, we establish that AHSCT induces profound changes in the dominant T cell landscape of both CD4+ and CD8+ memory T cell clones. Lymphopenia induced homeostatic proliferation is followed by clonal attrition; with only 19% of dominant CD4 (p <0.025) and 13% of dominant CD8 (p <0.005) clones from the pre-transplant repertoire detected at 36 months. Recovery of a thymically-derived CD4 naïve T cell repertoire occurs at 12 months and is ongoing at 36 months, however diversity of the naïve populations is not increased from baseline suggesting the principal mechanism of durable remission from MS after AHSCT relates to depletion of putative auto-reactive clones. In a cohort of MS patients expressing the MS risk allele HLA DRB1*15:01, public clones are probed as potential biomarkers of disease. AHSCT appears to induce sustained periods of disease remission with dynamic changes in the clonal T cell repertoire out to 36 months post-transplant.
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Affiliation(s)
- Jennifer Massey
- Department of Haematology, St Vincent’s Hospital, Darlinghurst, NSW, Australia
- Department of Neurology, St Vincent’s Hospital, Darlinghurst, NSW, Australia
- Blood Stem Cell and Cancer Research Group, St Vincent’s Centre for Applied Medical Research, Darlinghurst, NSW, Australia
- St. Vincent’s Clinical School, Faculty of Medicine, University of New South Wales (UNSW), Darlinghurst, NSW, Australia
- *Correspondence: Jennifer Massey,
| | - Katherine Jackson
- Immunogenomics Lab, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Mandeep Singh
- St. Vincent’s Clinical School, Faculty of Medicine, University of New South Wales (UNSW), Darlinghurst, NSW, Australia
- Immunogenomics Lab, Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
| | - Brendan Hughes
- School of Medical Sciences and Kirby Institute for Infection and Immunity, University of New South Wales (UNSW), Kensington, NSW, Australia
| | - Barbara Withers
- Department of Haematology, St Vincent’s Hospital, Darlinghurst, NSW, Australia
- Blood Stem Cell and Cancer Research Group, St Vincent’s Centre for Applied Medical Research, Darlinghurst, NSW, Australia
- St. Vincent’s Clinical School, Faculty of Medicine, University of New South Wales (UNSW), Darlinghurst, NSW, Australia
| | - Carole Ford
- Blood Stem Cell and Cancer Research Group, St Vincent’s Centre for Applied Medical Research, Darlinghurst, NSW, Australia
| | - Melissa Khoo
- Blood Stem Cell and Cancer Research Group, St Vincent’s Centre for Applied Medical Research, Darlinghurst, NSW, Australia
| | - Kevin Hendrawan
- Blood Stem Cell and Cancer Research Group, St Vincent’s Centre for Applied Medical Research, Darlinghurst, NSW, Australia
| | - John Zaunders
- Immunology Laboratory, St Vincent’s Centre for Applied Medical Research, Darlinghurst, NSW, Australia
| | | | - Rémi Cheynier
- Université de Paris, INSERM, CNRS, Institut Cochin, Paris, France
| | - Fabio Luciani
- School of Medical Sciences and Kirby Institute for Infection and Immunity, University of New South Wales (UNSW), Kensington, NSW, Australia
| | - David Ma
- Department of Haematology, St Vincent’s Hospital, Darlinghurst, NSW, Australia
- Blood Stem Cell and Cancer Research Group, St Vincent’s Centre for Applied Medical Research, Darlinghurst, NSW, Australia
- St. Vincent’s Clinical School, Faculty of Medicine, University of New South Wales (UNSW), Darlinghurst, NSW, Australia
| | - John Moore
- Department of Haematology, St Vincent’s Hospital, Darlinghurst, NSW, Australia
- Blood Stem Cell and Cancer Research Group, St Vincent’s Centre for Applied Medical Research, Darlinghurst, NSW, Australia
- St. Vincent’s Clinical School, Faculty of Medicine, University of New South Wales (UNSW), Darlinghurst, NSW, Australia
| | - Ian Sutton
- St. Vincent’s Clinical School, Faculty of Medicine, University of New South Wales (UNSW), Darlinghurst, NSW, Australia
- Department of Neurology, St Vincent’s Clinic, Darlinghurst, NSW, Australia
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16
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Joshi K, Milighetti M, Chain BM. Application of T cell receptor (TCR) repertoire analysis for the advancement of cancer immunotherapy. Curr Opin Immunol 2022; 74:1-8. [PMID: 34454284 DOI: 10.1016/j.coi.2021.07.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/13/2021] [Accepted: 07/13/2021] [Indexed: 12/14/2022]
Abstract
T cell receptor (TCR) sequencing has emerged as a powerful new technology in analysis of the host-tumour interaction. The advances in NextGen sequencing technologies, coupled with powerful novel bioinformatic tools, allow quantitative and reproducible characterisation of repertoires from tumour and blood samples from an increasing number of patients with a variety of solid cancers. In this review, we consider how global metrics such as T cell clonality and diversity can be extracted from these repertoires and used to give insight into the mechanism of action of immune checkpoint blockade. Furthermore, we explore how the analysis of TCR overlap between repertories can help define spatial and temporal heterogeneity of the anti-tumoural immune response. Finally, we review how analysis of TCR sequence and structure, either of individual TCRs or from sets of related TCRs can be used to annotate the antigenic specificity, with important implications for the development of personalised adoptive cellular immunotherapies.
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Affiliation(s)
- Kroopa Joshi
- Department of Medical Oncology, The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Martina Milighetti
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Benjamin M Chain
- Division of Infection and Immunity, University College London, London, United Kingdom; Department of Computer Science, University College London, London, United Kingdom.
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17
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Tian G, Li M, Lv G. Analysis of T-Cell Receptor Repertoire in Transplantation: Fingerprint of T Cell-mediated Alloresponse. Front Immunol 2022; 12:778559. [PMID: 35095851 PMCID: PMC8790170 DOI: 10.3389/fimmu.2021.778559] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/22/2021] [Indexed: 11/13/2022] Open
Abstract
T cells play a key role in determining allograft function by mediating allogeneic immune responses to cause rejection, and recent work pointed their role in mediating tolerance in transplantation. The unique T-cell receptor (TCR) expressed on the surface of each T cell determines the antigen specificity of the cell and can be the specific fingerprint for identifying and monitoring. Next-generation sequencing (NGS) techniques provide powerful tools for deep and high-throughput TCR profiling, and facilitate to depict the entire T cell repertoire profile and trace antigen-specific T cells in circulation and local tissues. Tailing T cell transcriptomes and TCR sequences at the single cell level provides a full landscape of alloreactive T-cell clones development and biofunction in alloresponse. Here, we review the recent advances in TCR sequencing techniques and computational tools, as well as the recent discovery in overall TCR profile and antigen-specific T cells tracking in transplantation. We further discuss the challenges and potential of using TCR sequencing-based assays to profile alloreactive TCR repertoire as the fingerprint for immune monitoring and prediction of rejection and tolerance.
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Affiliation(s)
| | - Mingqian Li
- Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, Changchun, China
| | - Guoyue Lv
- Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, Changchun, China
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18
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Integrating T cell receptor sequences and transcriptional profiles by clonotype neighbor graph analysis (CoNGA). Nat Biotechnol 2022; 40:54-63. [PMID: 34426704 PMCID: PMC8832949 DOI: 10.1038/s41587-021-00989-2] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 06/18/2021] [Indexed: 02/07/2023]
Abstract
Links between T cell clonotypes, as defined by T cell receptor (TCR) sequences, and phenotype, as reflected in gene expression (GEX) profiles, surface protein expression and peptide:major histocompatibility complex binding, can reveal functional relationships beyond the features shared by clonally related cells. Here we present clonotype neighbor graph analysis (CoNGA), a graph theoretic approach that identifies correlations between GEX profile and TCR sequence through statistical analysis of GEX and TCR similarity graphs. Using CoNGA, we uncovered associations between TCR sequence and GEX profiles that include a previously undescribed 'natural lymphocyte' population of human circulating CD8+ T cells and a set of TCR sequence determinants of differentiation in thymocytes. These examples show that CoNGA might help elucidate complex relationships between TCR sequence and T cell phenotype in large, heterogeneous, single-cell datasets.
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19
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Fang M, Su Z, Abolhassani H, Zhang W, Jiang C, Cheng B, Luo L, Wu J, Wang S, Lin L, Wang X, Wang L, Aghamohammadi A, Li T, Zhang X, Hammarström L, Liu X. T Cell Repertoire Abnormality in Immunodeficiency Patients with DNA Repair and Methylation Defects. J Clin Immunol 2021; 42:375-393. [PMID: 34825286 PMCID: PMC8821531 DOI: 10.1007/s10875-021-01178-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 11/01/2021] [Indexed: 12/25/2022]
Abstract
Both DNA damage response and methylation play a crucial role in antigen receptor recombination by creating a diverse repertoire in developing lymphocytes, but how their defects relate to T cell repertoire and phenotypic heterogeneity of immunodeficiency remains obscure. We studied the TCR repertoire in patients with the mutation in different genes (ATM, DNMT3B, ZBTB24, RAG1, DCLRE1C, and JAK3) and uncovered distinct characteristics of repertoire diversity. We propose that early aberrancies in thymus T cell development predispose to the heterogeneous phenotypes of the immunodeficiency spectrum. Shorter CDR3 lengths in ATM-deficient patients, resulting from a decreased number of nucleotide insertions during VDJ recombination in the pre-selected TCR repertoire, as well as the increment of CDR3 tyrosine residues, lead to the enrichment of pathology-associated TCRs, which may contribute to the phenotypes of ATM deficiency. Furthermore, patients with DNMT3B and ZBTB24 mutations who exhibit discrepant phenotypes present longer CDR3 lengths and reduced number of known pathology-associated TCRs.
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Affiliation(s)
- Mingyan Fang
- BGI-Shenzhen, Shenzhen, 518083, China.,Division of Clinical Immunology at the Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, 141 86, Stockholm, Sweden
| | - Zheng Su
- School of Biotechnology and Biomolecular Sciences, Faculty of Science, The University of New South Wales, Sydney, NSW, Australia
| | - Hassan Abolhassani
- Division of Clinical Immunology at the Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, 141 86, Stockholm, Sweden.,Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran.,Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden
| | - Wei Zhang
- BGI-Shenzhen, Shenzhen, 518083, China.,Department of Computer Science, City University of Hong Kong, Hong Kong, 999077, China
| | | | | | - Lihua Luo
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | | | - Liya Lin
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Xie Wang
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Asghar Aghamohammadi
- Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Tao Li
- BGI-Shenzhen, Shenzhen, 518083, China
| | | | - Lennart Hammarström
- BGI-Shenzhen, Shenzhen, 518083, China. .,Division of Clinical Immunology at the Department of Laboratory Medicine, Karolinska Institutet at Karolinska University Hospital Huddinge, 141 86, Stockholm, Sweden. .,Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden.
| | - Xiao Liu
- BGI-Shenzhen, Shenzhen, 518083, China. .,Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China.
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20
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Tune C, Hahn J, Autenrieth SE, Meinhardt M, Pagel R, Schampel A, Schierloh LK, Kalies K, Westermann J. Sleep restriction prior to antigen exposure does not alter the T cell receptor repertoire but impairs germinal center formation during a T cell-dependent B cell response in murine spleen. Brain Behav Immun Health 2021; 16:100312. [PMID: 34589803 PMCID: PMC8474616 DOI: 10.1016/j.bbih.2021.100312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 07/28/2021] [Indexed: 11/25/2022] Open
Abstract
It is well known that sleep promotes immune functions. In line with this, a variety of studies in animal models and humans have shown that sleep restriction following an antigen challenge dampens the immune response on several levels which leads to e.g. worsening of disease outcome and reduction of vaccination efficiency, respectively. However, the inverse scenario with sleep restriction preceding an antigen challenge is only investigated in a few animal models where it has been shown to reduce antigen uptake and presentation as well as pathogen clearance and survival rates. Here, we use injection of sheep red blood cells to investigate the yet unknown effect on a T cell-dependent B cell response in a well-established mouse model. We found that 6 h of sleep restriction prior to the antigen challenge does not impact the T cell reaction including the T cell receptor repertoire but dampens the development of germinal centers which correlates with reduced antigen-specific antibody titer indicating an impaired B cell response. These changes concerned a functionally more relevant level than those found in the same experimental model with the inverse scenario when sleep restriction followed the antigen challenge. Taken together, our findings showed that the outcome of the T cell-dependent B cell response is indeed impacted by sleep restriction prior to the antigen challenge which highlights the clinical significance of this scenario and the need for further investigations in humans, for example concerning the effect of sleep restriction preceding a vaccination.
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Key Words
- Antigen presentation
- BCZ, B cell zone
- CCL, C–C motif ligand
- CCR, C–C motif receptor
- CD, cluster of differentiation
- CIITA, class II major histocompatibility complex transactivator
- CXCL, C-X-C motif ligand
- FDR, false discovery rate
- GC, germinal center
- Germinal center
- IFN, interferon
- IL, interleukin
- IgG, Immunglobulin G
- MHC-II, major histocompatibility complex II
- Mouse
- RP, red pulp
- SD, standard deviation
- SLO, secondary lymphoid organ
- SRBC, sheep red blood cells
- Sheep red blood cells
- Sleep deprivation
- Spleen
- T cell-dependent B cell response
- TCR, T cell receptor
- TCR-R, T cell receptor repertoire
- TCZ, T cell zone
- Tfh, follicular T helper cells
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Affiliation(s)
- Cornelia Tune
- Institute of Anatomy, University of Luebeck, Germany
| | - Julia Hahn
- Department of Internal Medicine II, University of Tuebingen, Germany
| | | | | | - Rene Pagel
- Institute of Anatomy, University of Luebeck, Germany
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21
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Bravi B, Balachandran VP, Greenbaum BD, Walczak AM, Mora T, Monasson R, Cocco S. Probing T-cell response by sequence-based probabilistic modeling. PLoS Comput Biol 2021; 17:e1009297. [PMID: 34473697 PMCID: PMC8476001 DOI: 10.1371/journal.pcbi.1009297] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 09/27/2021] [Accepted: 07/22/2021] [Indexed: 11/26/2022] Open
Abstract
With the increasing ability to use high-throughput next-generation sequencing to quantify the diversity of the human T cell receptor (TCR) repertoire, the ability to use TCR sequences to infer antigen-specificity could greatly aid potential diagnostics and therapeutics. Here, we use a machine-learning approach known as Restricted Boltzmann Machine to develop a sequence-based inference approach to identify antigen-specific TCRs. Our approach combines probabilistic models of TCR sequences with clone abundance information to extract TCR sequence motifs central to an antigen-specific response. We use this model to identify patient personalized TCR motifs that respond to individual tumor and infectious disease antigens, and to accurately discriminate specific from non-specific responses. Furthermore, the hidden structure of the model results in an interpretable representation space where TCRs responding to the same antigen cluster, correctly discriminating the response of TCR to different viral epitopes. The model can be used to identify condition specific responding TCRs. We focus on the examples of TCRs reactive to candidate neoantigens and selected epitopes in experiments of stimulated TCR clone expansion.
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Affiliation(s)
- Barbara Bravi
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, Paris, France
| | - Vinod P. Balachandran
- Immuno-Oncology Service, Human Oncology and Pathogenesis Program, Hepatopancreatobiliary Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, New York State, United States of America
| | - Benjamin D. Greenbaum
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York State, United States of America
| | - Aleksandra M. Walczak
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, Paris, France
| | - Thierry Mora
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, Paris, France
| | - Rémi Monasson
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, Paris, France
| | - Simona Cocco
- Laboratoire de Physique de l’Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, Paris, France
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22
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Peacock T, Chain B. Information-Driven Docking for TCR-pMHC Complex Prediction. Front Immunol 2021; 12:686127. [PMID: 34177934 PMCID: PMC8219952 DOI: 10.3389/fimmu.2021.686127] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 05/07/2021] [Indexed: 12/16/2022] Open
Abstract
T cell receptor (TCR) recognition of peptides presented by major histocompatibility complex (MHC) molecules is a fundamental process in the adaptive immune system. An understanding of this recognition process at the molecular level is crucial for TCR based therapeutics and vaccine design. The broad nature of TCR diversity and cross-reactivity presents a challenge for traditional structural resolution. Computational modelling of TCR-pMHC complexes offers an efficient alternative. This study compares the ability of four general-purpose docking platforms (ClusPro, LightDock, ZDOCK and HADDOCK) to make use of varying levels of binding interface information for accurate TCR-pMHC modelling. Each platform was tested on an expanded benchmark set of 44 TCR-pMHC docking cases. In general, HADDOCK is shown to be the best performer. Docking strategy guidance is provided to obtain the best models for each platform for future research. The TCR-pMHC docking cases used in this study can be downloaded from https://github.com/innate2adaptive/ExpandedBenchmark.
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Affiliation(s)
- Thomas Peacock
- Division of Infection and Immunity, University College London, London, United Kingdom.,The UCL Centre for Computation, Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), Department Computer Science, University College London, London, United Kingdom
| | - Benny Chain
- Division of Infection and Immunity, University College London, London, United Kingdom
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23
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Montague Z, Lv H, Otwinowski J, DeWitt WS, Isacchini G, Yip GK, Ng WW, Tsang OTY, Yuan M, Liu H, Wilson IA, Peiris JSM, Wu NC, Nourmohammad A, Mok CKP. Dynamics of B cell repertoires and emergence of cross-reactive responses in patients with different severities of COVID-19. Cell Rep 2021; 35:109173. [PMID: 33991510 PMCID: PMC8106887 DOI: 10.1016/j.celrep.2021.109173] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 04/05/2021] [Accepted: 05/04/2021] [Indexed: 02/06/2023] Open
Abstract
Individuals with the 2019 coronavirus disease (COVID-19) show varying severity of the disease, ranging from asymptomatic to requiring intensive care. Although monoclonal antibodies specific to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been identified, we still lack an understanding of the overall landscape of B cell receptor (BCR) repertoires in individuals with COVID-19. We use high-throughput sequencing of bulk and plasma B cells collected at multiple time points during infection to characterize signatures of the B cell response to SARS-CoV-2 in 19 individuals. Using principled statistical approaches, we associate differential features of BCRs with different disease severity. We identify 38 significantly expanded clonal lineages shared among individuals as candidates for responses specific to SARS-CoV-2. Using single-cell sequencing, we verify the reactivity of BCRs shared among individuals to SARS-CoV-2 epitopes. Moreover, we identify the natural emergence of a BCR with cross-reactivity to SARS-CoV-1 and SARS-CoV-2 in some individuals. Our results provide insights important for development of rational therapies and vaccines against COVID-19.
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Affiliation(s)
- Zachary Montague
- Department of Physics, University of Washington, 3910 15th Ave. Northeast, Seattle, WA 98195, USA
| | - Huibin Lv
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Jakub Otwinowski
- Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany
| | - William S DeWitt
- Department of Genome Sciences, University of Washington, 3720 15th Ave. NE, Seattle, WA 98195, USA; Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N, Seattle, WA 98109, USA
| | - Giulio Isacchini
- Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany; Laboratoire de physique de l'ecole normale supérieure (PSL University), CNRS, Sorbonne Université, and Université de Paris, 75005 Paris, France
| | - Garrick K Yip
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Wilson W Ng
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Owen Tak-Yin Tsang
- Infectious Diseases Centre, Princess Margaret Hospital, Hospital Authority of Hong Kong, Hong Kong SAR, China
| | - Meng Yuan
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Hejun Liu
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Ian A Wilson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA; The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - J S Malik Peiris
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Nicholas C Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
| | - Armita Nourmohammad
- Department of Physics, University of Washington, 3910 15th Ave. Northeast, Seattle, WA 98195, USA; Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany; Fred Hutchinson Cancer Research Center, 1100 Fairview Ave. N, Seattle, WA 98109, USA.
| | - Chris Ka Pun Mok
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China; Li Ka Shing Institute of Health Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR, China.
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24
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Isacchini G, Sethna Z, Elhanati Y, Nourmohammad A, Walczak AM, Mora T. Generative models of T-cell receptor sequences. Phys Rev E 2021; 101:062414. [PMID: 32688532 DOI: 10.1103/physreve.101.062414] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 05/14/2020] [Indexed: 01/16/2023]
Abstract
T-cell receptors (TCR) are key proteins of the adaptive immune system, generated randomly in each individual, whose diversity underlies our ability to recognize infections and malignancies. Modeling the distribution of TCR sequences is of key importance for immunology and medical applications. Here, we compare two inference methods trained on high-throughput sequencing data: a knowledge-guided approach, which accounts for the details of sequence generation, supplemented by a physics-inspired model of selection; and a knowledge-free variational autoencoder based on deep artificial neural networks. We show that the knowledge-guided model outperforms the deep network approach at predicting TCR probabilities, while being more interpretable, at a lower computational cost.
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Affiliation(s)
- Giulio Isacchini
- Max Planck Institute for Dynamics and Self-organization, Am Faßberg 17, 37077 Göttingen, Germany.,Laboratoire de Physique de l'École Normale Supérieure (PSL University), CNRS, Sorbonne Université, and Université de Paris, 75005 Paris, France
| | - Zachary Sethna
- Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA
| | - Yuval Elhanati
- Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA
| | - Armita Nourmohammad
- Max Planck Institute for Dynamics and Self-organization, Am Faßberg 17, 37077 Göttingen, Germany.,Department of Physics, University of Washington, 3910 15th Avenue Northeast, Seattle, Washington 98195, USA.,Fred Hutchinson cancer Research Center, 1100 Fairview ave N, Seattle, Washington 98109, USA
| | - Aleksandra M Walczak
- Laboratoire de Physique de l'École Normale Supérieure (PSL University), CNRS, Sorbonne Université, and Université de Paris, 75005 Paris, France
| | - Thierry Mora
- Laboratoire de Physique de l'École Normale Supérieure (PSL University), CNRS, Sorbonne Université, and Université de Paris, 75005 Paris, France
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25
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Lin X, George JT, Schafer NP, Chau KN, Birnbaum ME, Clementi C, Onuchic JN, Levine H. Rapid Assessment of T-Cell Receptor Specificity of the Immune Repertoire. NATURE COMPUTATIONAL SCIENCE 2021; 1:362-373. [PMID: 36090450 PMCID: PMC9455901 DOI: 10.1038/s43588-021-00076-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Accurate assessment of TCR-antigen specificity at the whole immune repertoire level lies at the heart of improved cancer immunotherapy, but predictive models capable of high-throughput assessment of TCR-peptide pairs are lacking. Recent advances in deep sequencing and crystallography have enriched the data available for studying TCR-p-MHC systems. Here, we introduce a pairwise energy model, RACER, for rapid assessment of TCR-peptide affinity at the immune repertoire level. RACER applies supervised machine learning to efficiently and accurately resolve strong TCR-peptide binding pairs from weak ones. The trained parameters further enable a physical interpretation of interacting patterns encoded in each specific TCR-p-MHC system. When applied to simulate thymic selection of an MHC-restricted T-cell repertoire, RACER accurately estimates recognition rates for tumor-associated neoantigens and foreign peptides, thus demonstrating its utility in helping address the large computational challenge of reliably identifying the properties of tumor antigen-specific T-cells at the level of an individual patient's immune repertoire.
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Affiliation(s)
- Xingcheng Lin
- Center for Theoretical Biological Physics, Rice University, Houston, TX
- Department of Physics and Astronomy, Rice University, Houston, TX
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA
| | - Jason T. George
- Center for Theoretical Biological Physics, Rice University, Houston, TX
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX
| | - Nicholas P. Schafer
- Center for Theoretical Biological Physics, Rice University, Houston, TX
- Departments of Chemistry, Rice University, Houston, TX
| | - Kevin Ng Chau
- Department of Physics, Northeastern University, Boston, MA
| | - Michael E. Birnbaum
- Koch Institute for Integrative Cancer Research, Cambridge, MA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA
- Ragon Institute of MIT, MGH, and Harvard, Cambridge, MA
| | - Cecilia Clementi
- Center for Theoretical Biological Physics, Rice University, Houston, TX
- Departments of Chemistry, Rice University, Houston, TX
- Department of Physics, Freie Universität, Berlin, Germany
| | - José N. Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, TX
- Department of Physics and Astronomy, Rice University, Houston, TX
- Departments of Chemistry, Rice University, Houston, TX
- Department of Biosciences, Rice University, Houston, TX
- To whom correspondence should be addressed: ,
| | - Herbert Levine
- Center for Theoretical Biological Physics, Rice University, Houston, TX
- Department of Physics, Northeastern University, Boston, MA
- To whom correspondence should be addressed: ,
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26
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Modeling the Dynamics of T-Cell Development in the Thymus. ENTROPY 2021; 23:e23040437. [PMID: 33918050 PMCID: PMC8069328 DOI: 10.3390/e23040437] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 04/01/2021] [Accepted: 04/05/2021] [Indexed: 12/24/2022]
Abstract
The thymus hosts the development of a specific type of adaptive immune cells called T cells. T cells orchestrate the adaptive immune response through recognition of antigen by the highly variable T-cell receptor (TCR). T-cell development is a tightly coordinated process comprising lineage commitment, somatic recombination of Tcr gene loci and selection for functional, but non-self-reactive TCRs, all interspersed with massive proliferation and cell death. Thus, the thymus produces a pool of T cells throughout life capable of responding to virtually any exogenous attack while preserving the body through self-tolerance. The thymus has been of considerable interest to both immunologists and theoretical biologists due to its multi-scale quantitative properties, bridging molecular binding, population dynamics and polyclonal repertoire specificity. Here, we review experimental strategies aimed at revealing quantitative and dynamic properties of T-cell development and how they have been implemented in mathematical modeling strategies that were reported to help understand the flexible dynamics of the highly dividing and dying thymic cell populations. Furthermore, we summarize the current challenges to estimating in vivo cellular dynamics and to reaching a next-generation multi-scale picture of T-cell development.
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27
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Isacchini G, Walczak AM, Mora T, Nourmohammad A. Deep generative selection models of T and B cell receptor repertoires with soNNia. Proc Natl Acad Sci U S A 2021; 118:e2023141118. [PMID: 33795515 PMCID: PMC8040596 DOI: 10.1073/pnas.2023141118] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Subclasses of lymphocytes carry different functional roles to work together and produce an immune response and lasting immunity. Additionally to these functional roles, T and B cell lymphocytes rely on the diversity of their receptor chains to recognize different pathogens. The lymphocyte subclasses emerge from common ancestors generated with the same diversity of receptors during selection processes. Here, we leverage biophysical models of receptor generation with machine learning models of selection to identify specific sequence features characteristic of functional lymphocyte repertoires and subrepertoires. Specifically, using only repertoire-level sequence information, we classify CD4+ and CD8+ T cells, find correlations between receptor chains arising during selection, and identify T cell subsets that are targets of pathogenic epitopes. We also show examples of when simple linear classifiers do as well as more complex machine learning methods.
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Affiliation(s)
- Giulio Isacchini
- Statistical Physics of Evolving Systems, Max Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany
- Laboratoire de Physique de l'Ecole Normale Supérieure, Paris Sciences & Lettres (PSL) University, CNRS, Sorbonne Université and Université de Paris, 75005 Paris, France
| | - Aleksandra M Walczak
- Laboratoire de Physique de l'Ecole Normale Supérieure, Paris Sciences & Lettres (PSL) University, CNRS, Sorbonne Université and Université de Paris, 75005 Paris, France;
| | - Thierry Mora
- Laboratoire de Physique de l'Ecole Normale Supérieure, Paris Sciences & Lettres (PSL) University, CNRS, Sorbonne Université and Université de Paris, 75005 Paris, France;
| | - Armita Nourmohammad
- Statistical Physics of Evolving Systems, Max Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany;
- Department of Physics, University of Washington, Seattle, WA 98195
- Herbold Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109
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28
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Montague Z, Lv H, Otwinowski J, DeWitt WS, Isacchini G, Yip GK, Ng WW, Tsang OTY, Yuan M, Liu H, Wilson IA, Peiris JSM, Wu NC, Nourmohammad A, Mok CKP. Dynamics of B-cell repertoires and emergence of cross-reactive responses in COVID-19 patients with different disease severity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2020.07.13.20153114. [PMID: 32699862 PMCID: PMC7373151 DOI: 10.1101/2020.07.13.20153114] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
COVID-19 patients show varying severity of the disease ranging from asymptomatic to requiring intensive care. Although a number of SARS-CoV-2 specific monoclonal antibodies have been identified, we still lack an understanding of the overall landscape of B-cell receptor (BCR) repertoires in COVID-19 patients. Here, we used high-throughput sequencing of bulk and plasma B-cells collected over multiple time points during infection to characterize signatures of B-cell response to SARS-CoV-2 in 19 patients. Using principled statistical approaches, we determined differential features of BCRs associated with different disease severity. We identified 38 significantly expanded clonal lineages shared among patients as candidates for specific responses to SARS-CoV-2. Using single-cell sequencing, we verified reactivity of BCRs shared among individuals to SARS-CoV-2 epitopes. Moreover, we identified natural emergence of a BCR with cross-reactivity to SARS-CoV-1 and SARS-CoV-2 in a number of patients. Our results provide important insights for development of rational therapies and vaccines against COVID-19.
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Affiliation(s)
- Zachary Montague
- Department of Physics, University of Washington, 3910 15th Ave Northeast, Seattle, WA 98195, USA
| | - Huibin Lv
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Jakub Otwinowski
- Max Planck Institute for Dynamics and Self-organization, Am Faßberg 17, 37077 Göttingen, Germany
| | - William S. DeWitt
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195, USA
- Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
| | - Giulio Isacchini
- Max Planck Institute for Dynamics and Self-organization, Am Faßberg 17, 37077 Göttingen, Germany
- Laboratoire de physique de l’ecole normale supérieure (PSL University), CNRS, Sorbonne Université, and Université de Paris, 75005 Paris, France
| | - Garrick K. Yip
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Wilson W. Ng
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Owen Tak-Yin Tsang
- Infectious Diseases Centre, Princess Margaret Hospital, Hospital Authority of Hong Kong
| | - Meng Yuan
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Hejun Liu
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - Ian A. Wilson
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
- The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
| | - J. S. Malik Peiris
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Nicholas C. Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Armita Nourmohammad
- Department of Physics, University of Washington, 3910 15th Ave Northeast, Seattle, WA 98195, USA
- Max Planck Institute for Dynamics and Self-organization, Am Faßberg 17, 37077 Göttingen, Germany
- Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
| | - Chris Ka Pun Mok
- HKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
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29
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Mhanna V, Fourcade G, Barennes P, Quiniou V, Pham HP, Ritvo PG, Brimaud F, Gouritin B, Churlaud G, Six A, Mariotti-Ferrandiz E, Klatzmann D. Impaired Activated/Memory Regulatory T Cell Clonal Expansion Instigates Diabetes in NOD Mice. Diabetes 2021; 70:976-985. [PMID: 33479057 DOI: 10.2337/db20-0896] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 01/19/2021] [Indexed: 11/13/2022]
Abstract
Regulatory T cell (Treg) insufficiency licenses the destruction of insulin-producing pancreatic β-cells by autoreactive effector T cells (Teffs), causing spontaneous autoimmune diabetes in NOD mice. We investigated the contribution to diabetes of the T-cell receptor (TCR) repertoires of naive regulatory T cells (nTregs), activated/memory Tregs (amTregs), and CD4+ Teffs from prediabetic NOD mice and normal C57BL/6 (B6) mice. NOD mice amTreg and Teff repertoire diversity was unexpectedly higher than that of B6 mice. This was due to the presence of highly expanded clonotypes in B6 amTregs and Teffs that were largely lost in their NOD counterparts. Interleukin-2 (IL-2) administration to NOD mice restored such amTreg clonotype expansions and prevented diabetes development. In contrast, IL-2 administration only led to few or no clonotype expansions in nTregs and Teffs, respectively. Noteworthily, IL-2-expanded amTreg and nTreg clonotypes were markedly enriched in islet-antigen specific TCRs. Altogether, our results highlight the link between a reduced clonotype expansion within the activated Treg repertoire and the development of an autoimmune disease. They also indicate that the repertoire of amTregs is amenable to rejuvenation by IL-2.
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Affiliation(s)
- Vanessa Mhanna
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
| | - Gwladys Fourcade
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
| | - Pierre Barennes
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
| | - Valentin Quiniou
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
- Clinical Investigation Center in Biotherapy and Inflammation-Immunopathology-Biotherapy Department, Assistance Publique-Hôpitaux de Paris, Hôpital Universitaire Pitié-Salpêtrière, Paris, France
| | - Hang P Pham
- Statistics Department, ILTOO Pharma, Paris, France
| | - Paul-Gydeon Ritvo
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
| | - Faustine Brimaud
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
| | - Bruno Gouritin
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
| | - Guillaume Churlaud
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
- Clinical Investigation Center in Biotherapy and Inflammation-Immunopathology-Biotherapy Department, Assistance Publique-Hôpitaux de Paris, Hôpital Universitaire Pitié-Salpêtrière, Paris, France
| | - Adrien Six
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
| | | | - David Klatzmann
- Sorbonne Universite, INSERM, UMRS959 Immunology-Immunopathology-Immunotherapy Laboratory, Paris, France
- Clinical Investigation Center in Biotherapy and Inflammation-Immunopathology-Biotherapy Department, Assistance Publique-Hôpitaux de Paris, Hôpital Universitaire Pitié-Salpêtrière, Paris, France
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30
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Turner CT, Brown J, Shaw E, Uddin I, Tsaliki E, Roe JK, Pollara G, Sun Y, Heather JM, Lipman M, Chain B, Noursadeghi M. Persistent T Cell Repertoire Perturbation and T Cell Activation in HIV After Long Term Treatment. Front Immunol 2021; 12:634489. [PMID: 33732256 PMCID: PMC7959740 DOI: 10.3389/fimmu.2021.634489] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Accepted: 01/11/2021] [Indexed: 12/11/2022] Open
Abstract
Objective In people living with HIV (PLHIV), we sought to test the hypothesis that long term anti-retroviral therapy restores the normal T cell repertoire, and investigate the functional relationship of residual repertoire abnormalities to persistent immune system dysregulation. Methods We conducted a case-control study in PLHIV and HIV-negative volunteers, of circulating T cell receptor repertoires and whole blood transcriptomes by RNA sequencing, complemented by metadata from routinely collected health care records. Results T cell receptor sequencing revealed persistent abnormalities in the clonal T cell repertoire of PLHIV, characterized by reduced repertoire diversity and oligoclonal T cell expansion correlated with elevated CD8 T cell counts. We found no evidence that these expansions were driven by cytomegalovirus or another common antigen. Increased frequency of long CDR3 sequences and reduced frequency of public sequences among the expanded clones implicated abnormal thymic selection as a contributing factor. These abnormalities in the repertoire correlated with systems level evidence of persistent T cell activation in genome-wide blood transcriptomes. Conclusions The diversity of T cell receptor repertoires in PLHIV on long term anti-retroviral therapy remains significantly depleted, and skewed by idiosyncratic clones, partly attributable to altered thymic output and associated with T cell mediated chronic immune activation. Further investigation of thymic function and the antigenic drivers of T cell clonal selection in PLHIV are critical to efforts to fully re-establish normal immune function.
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Affiliation(s)
- Carolin T. Turner
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - James Brown
- Departments of HIV and Respiratory Medicine, Royal Free London NHS Foundation Trust, London, United Kingdom
- UCL Respiratory, Division of Medicine, University College London, London, United Kingdom
| | - Emily Shaw
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Imran Uddin
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Evdokia Tsaliki
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Jennifer K. Roe
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Gabriele Pollara
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Yuxin Sun
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - James M. Heather
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Marc Lipman
- Departments of HIV and Respiratory Medicine, Royal Free London NHS Foundation Trust, London, United Kingdom
- UCL Respiratory, Division of Medicine, University College London, London, United Kingdom
| | - Benny Chain
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Mahdad Noursadeghi
- Division of Infection and Immunity, University College London, London, United Kingdom
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31
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Sethna Z, Isacchini G, Dupic T, Mora T, Walczak AM, Elhanati Y. Population variability in the generation and selection of T-cell repertoires. PLoS Comput Biol 2020; 16:e1008394. [PMID: 33296360 PMCID: PMC7725366 DOI: 10.1371/journal.pcbi.1008394] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/11/2020] [Indexed: 12/21/2022] Open
Abstract
The diversity of T-cell receptor (TCR) repertoires is achieved by a combination of two intrinsically stochastic steps: random receptor generation by VDJ recombination, and selection based on the recognition of random self-peptides presented on the major histocompatibility complex. These processes lead to a large receptor variability within and between individuals. However, the characterization of the variability is hampered by the limited size of the sampled repertoires. We introduce a new software tool SONIA to facilitate inference of individual-specific computational models for the generation and selection of the TCR beta chain (TRB) from sequenced repertoires of 651 individuals, separating and quantifying the variability of the two processes of generation and selection in the population. We find not only that most of the variability is driven by the VDJ generation process, but there is a large degree of consistency between individuals with the inter-individual variance of repertoires being about ∼2% of the intra-individual variance. Known viral-specific TCRs follow the same generation and selection statistics as all TCRs.
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Affiliation(s)
- Zachary Sethna
- Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
| | - Giulio Isacchini
- Laboratoire de physique de l'École Normale Supérieure, PSL University, CNRS, Sorbonne Université, Université de Paris 24 rue Lhomond, Paris, France.,Max Planck Institute for Dynamics and Self-organization, Am Faßberg 17, Göttingen, Germany
| | - Thomas Dupic
- Laboratoire de physique de l'École Normale Supérieure, PSL University, CNRS, Sorbonne Université, Université de Paris 24 rue Lhomond, Paris, France
| | - Thierry Mora
- Laboratoire de physique de l'École Normale Supérieure, PSL University, CNRS, Sorbonne Université, Université de Paris 24 rue Lhomond, Paris, France
| | - Aleksandra M Walczak
- Laboratoire de physique de l'École Normale Supérieure, PSL University, CNRS, Sorbonne Université, Université de Paris 24 rue Lhomond, Paris, France
| | - Yuval Elhanati
- Computational Oncology, Department of Epidemiology and Biostatistics, and Parker Institute for Cancer Immunotherapy, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America
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32
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Diagnostic differentiation of Zika and dengue virus exposure by analyzing T cell receptor sequences from peripheral blood of infected HLA-A2 transgenic mice. PLoS Negl Trop Dis 2020; 14:e0008896. [PMID: 33270635 PMCID: PMC7738164 DOI: 10.1371/journal.pntd.0008896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 12/15/2020] [Accepted: 10/15/2020] [Indexed: 11/19/2022] Open
Abstract
Zika virus (ZIKV) is a significant global health threat due to its potential for rapid emergence and association with severe congenital malformations during infection in pregnancy. Despite the urgent need, accurate diagnosis of ZIKV infection is still a major hurdle that must be overcome. Contributing to the inaccuracy of most serologically-based diagnostic assays for ZIKV, is the substantial geographic and antigenic overlap with other flaviviruses, including the four serotypes of dengue virus (DENV). Within this study, we have utilized a novel T cell receptor (TCR) sequencing platform to distinguish between ZIKV and DENV infections. Using high-throughput TCR sequencing of lymphocytes isolated from DENV and ZIKV infected mice, we were able to develop an algorithm which could identify virus-associated TCR sequences uniquely associated with either a prior ZIKV or DENV infection in mice. Using this algorithm, we were then able to separate mice that had been exposed to ZIKV or DENV infection with 97% accuracy. Overall this study serves as a proof-of-principle that T cell receptor sequencing can be used as a diagnostic tool capable of distinguishing between closely related viruses. Our results demonstrate the potential for this innovative platform to be used to accurately diagnose Zika virus infection and potentially the next emerging pathogen(s). Diagnostic differentiation between dengue virus and Zika virus infections is a challenge due to serological cross-reactivity. In this study, we used a novel T cell receptor sequencing platform to identify T cell receptor sequences significantly associated with either dengue or Zika virus infection in HLA-A2 transgenic mice. These libraries were used to computationally train diagnostic classifiers which were capable of distinguishing between dengue and Zika virus in independent cohorts of infected mice.
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33
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Krishna C, Chowell D, Gönen M, Elhanati Y, Chan TA. Genetic and environmental determinants of human TCR repertoire diversity. Immun Ageing 2020; 17:26. [PMID: 32944053 PMCID: PMC7487954 DOI: 10.1186/s12979-020-00195-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 08/06/2020] [Indexed: 12/22/2022]
Abstract
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.
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Affiliation(s)
- Chirag Krishna
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
| | - Diego Chowell
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
- Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
| | - Mithat Gönen
- Department of Epidemiology and Biostatistics, Sloan Kettering Institute for Cancer Research, New York, NY 10065 USA
| | - Yuval Elhanati
- Department of Epidemiology and Biostatistics, Sloan Kettering Institute for Cancer Research, New York, NY 10065 USA
- Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
| | - Timothy A. Chan
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
- Immunogenomics and Precision Oncology Platform, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA
- Weill Cornell School of Medicine, New York, NY 10065 USA
- Center for Immunotherapy and Precision Immuno-Oncology, Cleveland Clinic, Cleveland, OH 44195 USA
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34
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Schober K, Fuchs P, Mir J, Hammel M, Fanchi L, Flossdorf M, Busch DH. The CMV-Specific CD8 + T Cell Response Is Dominated by Supra-Public Clonotypes with High Generation Probabilities. Pathogens 2020; 9:pathogens9080650. [PMID: 32823573 PMCID: PMC7460440 DOI: 10.3390/pathogens9080650] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Revised: 07/01/2020] [Accepted: 08/11/2020] [Indexed: 12/12/2022] Open
Abstract
Evolutionary processes govern the selection of T cell clonotypes that are optimally suited to mediate efficient antigen-specific immune responses against pathogens and tumors. While the theoretical diversity of T cell receptor (TCR) sequences is vast, the antigen-specific TCR repertoire is restricted by its peptide epitope and the presenting major histocompatibility complex (pMHC). It remains unclear how many TCR sequences are recruited into an antigen-specific T cell response, both within and across different organisms, and which factors shape both of these distributions. Infection of mice with ovalbumin-expressing cytomegalovirus (IE2-OVA-mCMV) represents a well-studied model system to investigate T cell responses given their size and longevity. Here we investigated > 180,000 H2kb/SIINFEKL-recognizing TCR CDR3α or CDR3β sequences from 25 individual mice spanning seven different time points during acute infection and memory inflation. In-depth repertoire analysis revealed that from a pool of highly diverse, but overall limited sequences, T cell responses were dominated by public clonotypes, partly with unexpectedly extreme degrees of sharedness between individual mice ("supra-public clonotypes"). Public clonotypes were found exclusively in a fraction of TCRs with a high generation probability. Generation probability and degree of sharedness select for highly functional TCRs, possibly mediated through elevating intraindividual precursor frequencies of clonotypes.
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Affiliation(s)
- Kilian Schober
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München (TUM), 81675 Munich, Germany; (J.M.); (M.H.); (M.F.)
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
- Correspondence: (K.S.); (D.H.B.); Tel.: +49-89-4140-6870 (K.S.); +49-89-4140-4120 (D.H.B.)
| | - Pim Fuchs
- ENPICOM B.V., 5211 AX ‘s-Hertogenbosch, The Netherlands; (P.F.); (L.F.)
| | - Jonas Mir
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München (TUM), 81675 Munich, Germany; (J.M.); (M.H.); (M.F.)
| | - Monika Hammel
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München (TUM), 81675 Munich, Germany; (J.M.); (M.H.); (M.F.)
| | - Lorenzo Fanchi
- ENPICOM B.V., 5211 AX ‘s-Hertogenbosch, The Netherlands; (P.F.); (L.F.)
| | - Michael Flossdorf
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München (TUM), 81675 Munich, Germany; (J.M.); (M.H.); (M.F.)
| | - Dirk H. Busch
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München (TUM), 81675 Munich, Germany; (J.M.); (M.H.); (M.F.)
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
- Correspondence: (K.S.); (D.H.B.); Tel.: +49-89-4140-6870 (K.S.); +49-89-4140-4120 (D.H.B.)
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35
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Isacchini G, Olivares C, Nourmohammad A, Walczak AM, Mora T. SOS: online probability estimation and generation of T-and B-cell receptors. Bioinformatics 2020; 36:4510-4512. [DOI: 10.1093/bioinformatics/btaa574] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 05/18/2020] [Accepted: 06/10/2020] [Indexed: 11/12/2022] Open
Abstract
Abstract
Summary
Recent advances in modelling VDJ recombination and subsequent selection of T- and B-cell receptors provide useful tools to analyse and compare immune repertoires across time, individuals and tissues. A suite of tools—IGoR, OLGA and SONIA—have been publicly released to the community that allow for the inference of generative and selection models from high-throughput sequencing data. However, using these tools requires some scripting or command-line skills and familiarity with complex datasets. As a result, the application of the above models has not been available to a broad audience. In this application note, we fill this gap by presenting Simple OLGA & SONIA (SOS), a web-based interface where users with no coding skills can compute the generation and post-selection probabilities of their sequences, as well as generate batches of synthetic sequences. The application also functions on mobile phones.
Availability and implementation
SOS is freely available to use at sites.google.com/view/statbiophysens/sos with source code at github.com/statbiophys/sos.
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Affiliation(s)
- Giulio Isacchini
- Laboratoire de physique de l’École normale supérieure (PSL University), CNRS, Sorbonne Université, Université de Paris, 75005 Paris, France
- Max Planck Institute for Dynamics and Self-organization, 37077 Göttingen, Germany
| | - Carlos Olivares
- Laboratoire de physique de l’École normale supérieure (PSL University), CNRS, Sorbonne Université, Université de Paris, 75005 Paris, France
| | - Armita Nourmohammad
- Max Planck Institute for Dynamics and Self-organization, 37077 Göttingen, Germany
- Department of Physics, University of Washington, Seattle, WA 98195, USA
- Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Aleksandra M Walczak
- Laboratoire de physique de l’École normale supérieure (PSL University), CNRS, Sorbonne Université, Université de Paris, 75005 Paris, France
| | - Thierry Mora
- Laboratoire de physique de l’École normale supérieure (PSL University), CNRS, Sorbonne Université, Université de Paris, 75005 Paris, France
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36
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Yermanos A, Kräutler NJ, Pedrioli A, Menzel U, Greiff V, Stadler T, Oxenius A, Reddy ST. IgM Antibody Repertoire Fingerprints in Mice Are Personalized but Robust to Viral Infection Status. Front Cell Infect Microbiol 2020; 10:254. [PMID: 32547966 PMCID: PMC7270205 DOI: 10.3389/fcimb.2020.00254] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 04/30/2020] [Indexed: 01/11/2023] Open
Abstract
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.
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Affiliation(s)
- Alexander Yermanos
- Institute of Microbiology, ETH Zurich, Zurich, Switzerland.,Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
| | | | | | - Ulrike Menzel
- Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
| | - Victor Greiff
- Department of Immunology, University of Oslo, Oslo, Norway
| | - Tanja Stadler
- Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
| | | | - Sai T Reddy
- Department of Biosystems and Engineering, ETH Zurich, Basel, Switzerland
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37
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Inter- and intraspecies comparison of phylogenetic fingerprints and sequence diversity of immunoglobulin variable genes. Immunogenetics 2020; 72:279-294. [PMID: 32367185 DOI: 10.1007/s00251-020-01164-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Accepted: 04/13/2020] [Indexed: 10/24/2022]
Abstract
Protection and neutralization of a vast array of pathogens is accomplished by the tremendous diversity of the B cell receptor (BCR) repertoire. For jawed vertebrates, this diversity is initiated via the somatic recombination of immunoglobulin (Ig) germline elements. While it is clear that the number of these germline segments differs from species to species, the extent of cross-species sequence diversity remains largely uncharacterized. Here we use extensive computational and statistical methods to investigate the sequence diversity and evolutionary relationship between Ig variable (V), diversity (D), and joining (J) germline segments across nine commonly studied species ranging from zebrafish to human. Metrics such as guanine-cytosine (GC) content showed low redundancy across Ig germline genes within a given species. Other comparisons, including amino acid motifs, evolutionary selection, and sequence diversity, revealed species-specific properties. Additionally, we showed that the germline-encoded diversity differs across antibody (recombined V-D-J) repertoires of various B cell subsets. To facilitate future comparative immunogenomics analysis, we created VDJgermlines, an R package that contains the germline sequences from multiple species. Our study informs strategies for the humanization and engineering of therapeutic antibodies.
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38
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de Greef PC, Oakes T, Gerritsen B, Ismail M, Heather JM, Hermsen R, Chain B, de Boer RJ. The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes. eLife 2020; 9:e49900. [PMID: 32187010 PMCID: PMC7080410 DOI: 10.7554/elife.49900] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 03/03/2020] [Indexed: 12/24/2022] Open
Abstract
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.
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MESH Headings
- Adaptive Immunity
- Algorithms
- Antigens/immunology
- Clonal Evolution/genetics
- Computational Biology/methods
- High-Throughput Nucleotide Sequencing
- Humans
- Immunologic Memory
- Models, Biological
- Organ Specificity/genetics
- Organ Specificity/immunology
- Receptors, Antigen, T-Cell/genetics
- Receptors, Antigen, T-Cell/metabolism
- Receptors, Antigen, T-Cell, alpha-beta/genetics
- Receptors, Antigen, T-Cell, alpha-beta/metabolism
- T-Lymphocyte Subsets/immunology
- T-Lymphocyte Subsets/metabolism
- T-Lymphocytes/immunology
- T-Lymphocytes/metabolism
- V(D)J Recombination
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Affiliation(s)
- Peter C de Greef
- Theoretical Biology and Bioinformatics, Utrecht UniversityUtrechtNetherlands
| | - Theres Oakes
- Division of Infection and Immunity, University College LondonLondonUnited Kingdom
| | - Bram Gerritsen
- Theoretical Biology and Bioinformatics, Utrecht UniversityUtrechtNetherlands
- Department of Pathology, Yale School of MedicineNew HavenUnited States
| | - Mazlina Ismail
- Division of Infection and Immunity, University College LondonLondonUnited Kingdom
| | - James M Heather
- Division of Infection and Immunity, University College LondonLondonUnited Kingdom
| | - Rutger Hermsen
- Theoretical Biology and Bioinformatics, Utrecht UniversityUtrechtNetherlands
| | - Benjamin Chain
- Division of Infection and Immunity, University College LondonLondonUnited Kingdom
| | - Rob J de Boer
- Theoretical Biology and Bioinformatics, Utrecht UniversityUtrechtNetherlands
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39
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Wolf K, Hether T, Gilchuk P, Kumar A, Rajeh A, Schiebout C, Maybruck J, Buller RM, Ahn TH, Joyce S, DiPaolo RJ. Identifying and Tracking Low-Frequency Virus-Specific TCR Clonotypes Using High-Throughput Sequencing. Cell Rep 2019; 25:2369-2378.e4. [PMID: 30485806 PMCID: PMC7770954 DOI: 10.1016/j.celrep.2018.11.009] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 09/18/2018] [Accepted: 10/31/2018] [Indexed: 12/30/2022] Open
Abstract
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.
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Affiliation(s)
- Kyle Wolf
- Department of Molecular Microbiology and Immunology, Saint Louis University, Saint Louis, MO 63104, USA
| | - Tyler Hether
- Adaptive Biotechnologies, Seattle, WA 98102, USA
| | - Pavlo Gilchuk
- Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN 37212, USA; Department of Pathology, Microbiology, and Immunology, Vanderbilt University, Nashville, TN 37232, USA
| | - Amrendra Kumar
- Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN 37212, USA; Department of Pathology, Microbiology, and Immunology, Vanderbilt University, Nashville, TN 37232, USA
| | - Ahmad Rajeh
- Program in Bioinformatics and Computational Biology, Saint Louis University, Saint Louis, MO 63104, USA
| | - Courtney Schiebout
- Program in Bioinformatics and Computational Biology, Saint Louis University, Saint Louis, MO 63104, USA
| | - Julie Maybruck
- Federal Bureau of Investigation, Washington, DC 20535, USA
| | - R Mark Buller
- Department of Molecular Microbiology and Immunology, Saint Louis University, Saint Louis, MO 63104, USA
| | - Tae-Hyuk Ahn
- Department of Computer Science, Saint Louis University, Saint Louis, MO 63104, USA; Program in Bioinformatics and Computational Biology, Saint Louis University, Saint Louis, MO 63104, USA
| | - Sebastian Joyce
- Department of Veterans Affairs, Tennessee Valley Healthcare System, Nashville, TN 37212, USA; Department of Pathology, Microbiology, and Immunology, Vanderbilt University, Nashville, TN 37232, USA
| | - Richard J DiPaolo
- Department of Molecular Microbiology and Immunology, Saint Louis University, Saint Louis, MO 63104, USA.
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40
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Thomas PG, Crawford JC. Selected before selection: A case for inherent antigen bias in the T cell receptor repertoire. ACTA ACUST UNITED AC 2019; 18:36-43. [PMID: 32601606 DOI: 10.1016/j.coisb.2019.10.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
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.
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Affiliation(s)
- Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105
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41
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Olson BJ, Moghimi P, Schramm CA, Obraztsova A, Ralph D, Vander Heiden JA, Shugay M, Shepherd AJ, Lees W, Matsen FA. sumrep: A Summary Statistic Framework for Immune Receptor Repertoire Comparison and Model Validation. Front Immunol 2019; 10:2533. [PMID: 31736960 PMCID: PMC6838214 DOI: 10.3389/fimmu.2019.02533] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 10/11/2019] [Indexed: 12/28/2022] Open
Abstract
The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce sumrep, an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how sumrep can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.
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Affiliation(s)
- Branden J Olson
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States.,Department of Statistics, University of Washington, Seattle, WA, United States
| | - Pejvak Moghimi
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
| | - Chaim A Schramm
- Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States
| | - Anna Obraztsova
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
| | - Duncan Ralph
- Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Jason A Vander Heiden
- Department of Bioinformatics and Computational Biology, Genentech, Inc., South San Francisco, CA, United States
| | - Mikhail Shugay
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia.,Department of Molecular Technologies, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Adrian J Shepherd
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
| | - William Lees
- Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, University of London, London, United Kingdom
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42
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Abstract
Despite their differences, biological systems at different spatial scales tend to exhibit common organizational patterns. Unfortunately, these commonalities are often hard to grasp due to the highly specialized nature of modern science and the parcelled terminology employed by various scientific sub-disciplines. To explore these common organizational features, this paper provides a comparative study of diverse applications of the maximum entropy principle, which has found many uses at different biological spatial scales ranging from amino acids up to societies. By presenting these studies under a common approach and language, this paper aims to establish a unified view over these seemingly highly heterogeneous scenarios.
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43
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Davidsen K, Olson BJ, DeWitt WS, Feng J, Harkins E, Bradley P, Matsen FA. Deep generative models for T cell receptor protein sequences. eLife 2019; 8:e46935. [PMID: 31487240 PMCID: PMC6728137 DOI: 10.7554/elife.46935] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2019] [Accepted: 08/21/2019] [Indexed: 02/06/2023] Open
Abstract
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.
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Affiliation(s)
- Kristian Davidsen
- University of WashingtonSeattleUnited States
- Fred Hutchinson Cancer Research CenterSeattleUnited States
| | - Branden J Olson
- University of WashingtonSeattleUnited States
- Fred Hutchinson Cancer Research CenterSeattleUnited States
| | - William S DeWitt
- University of WashingtonSeattleUnited States
- Fred Hutchinson Cancer Research CenterSeattleUnited States
| | - Jean Feng
- University of WashingtonSeattleUnited States
- Fred Hutchinson Cancer Research CenterSeattleUnited States
| | - Elias Harkins
- University of WashingtonSeattleUnited States
- Fred Hutchinson Cancer Research CenterSeattleUnited States
| | - Philip Bradley
- University of WashingtonSeattleUnited States
- Fred Hutchinson Cancer Research CenterSeattleUnited States
| | - Frederick A Matsen
- University of WashingtonSeattleUnited States
- Fred Hutchinson Cancer Research CenterSeattleUnited States
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44
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Deng C, Daley T, De Sena Brandine G, Smith AD. Molecular Heterogeneity in Large-Scale Biological Data: Techniques and Applications. Annu Rev Biomed Data Sci 2019. [DOI: 10.1146/annurev-biodatasci-072018-021339] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
High-throughput sequencing technologies have evolved at a stellar pace for almost a decade and have greatly advanced our understanding of genome biology. In these sampling-based technologies, there is an important detail that is often overlooked in the analysis of the data and the design of the experiments, specifically that the sampled observations often do not give a representative picture of the underlying population. This has long been recognized as a problem in statistical ecology and in the broader statistics literature. In this review, we discuss the connections between these fields, methodological advances that parallel both the needs and opportunities of large-scale data analysis, and specific applications in modern biology. In the process we describe unique aspects of applying these approaches to sequencing technologies, including sequencing error, population and individual heterogeneity, and the design of experiments.
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Affiliation(s)
- Chao Deng
- Department of Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089, USA
| | - Timothy Daley
- Department of Statistics and Department of Bioengineering, Stanford University, Stanford, California 94305, USA
| | - Guilherme De Sena Brandine
- Department of Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089, USA
| | - Andrew D. Smith
- Department of Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089, USA
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45
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Chu ND, Bi HS, Emerson RO, Sherwood AM, Birnbaum ME, Robins HS, Alm EJ. Longitudinal immunosequencing in healthy people reveals persistent T cell receptors rich in highly public receptors. BMC Immunol 2019; 20:19. [PMID: 31226930 PMCID: PMC6588944 DOI: 10.1186/s12865-019-0300-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 06/06/2019] [Indexed: 11/18/2022] Open
Abstract
Background The adaptive immune system maintains a diversity of T cells capable of recognizing a broad array of antigens. Each T cell’s specificity for antigens is determined by its T cell receptors (TCRs), which together across all T cells form a repertoire of millions of unique receptors in each individual. Although many studies have examined how TCR repertoires change in response to disease or drugs, few have explored the temporal dynamics of the TCR repertoire in healthy individuals. Results Here we report immunosequencing of TCR β chains (TCRβ) from the blood of three healthy individuals at eight time points over one year. TCRβ repertoires of all peripheral-blood T cells and sorted memory T cells clustered clearly by individual, systematically demonstrating that TCRβ repertoires are specific to individuals across time. This individuality was absent from TCRβs from naive T cells, suggesting that the differences resulted from an individual’s antigen exposure history, not genetic background. Many characteristics of the TCRβ repertoire (e.g., diversity, clonality) were stable across time, although we found evidence of T cell expansion dynamics even within healthy individuals. We further identified a subset of “persistent” TCRβs present across all time points. These receptors were rich in clonal and highly public receptors and may play a key role in immune system maintenance. Conclusions Our results highlight the importance of longitudinal sampling of the immune system, providing a much-needed baseline for TCRβ dynamics in healthy individuals. Such a baseline will improve interpretation of changes in the TCRβ repertoire during disease or treatment. Electronic supplementary material The online version of this article (10.1186/s12865-019-0300-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Nathaniel D Chu
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.,Microbiology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA, USA.,Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Haixin Sarah Bi
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.,Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA.,Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | | | - Michael E Birnbaum
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Harlan S Robins
- Adaptive Biotechnologies, Seattle, WA, USA.,Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Eric J Alm
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. .,Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA. .,Broad Institute, Cambridge, MA, 02139, USA.
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46
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Pogorelyy MV, Minervina AA, Shugay M, Chudakov DM, Lebedev YB, Mora T, Walczak AM. Detecting T cell receptors involved in immune responses from single repertoire snapshots. PLoS Biol 2019; 17:e3000314. [PMID: 31194732 PMCID: PMC6592544 DOI: 10.1371/journal.pbio.3000314] [Citation(s) in RCA: 79] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Revised: 06/25/2019] [Accepted: 05/21/2019] [Indexed: 11/19/2022] Open
Abstract
Hypervariable T cell receptors (TCRs) play a key role in adaptive immunity, recognizing a vast diversity of pathogen-derived antigens. Our ability to extract clinically relevant information from large high-throughput sequencing of TCR repertoires (RepSeq) data is limited, because little is known about TCR-disease associations. We present Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences (ALICE), a statistical approach that identifies TCR sequences actively involved in current immune responses from a single RepSeq sample and apply it to repertoires of patients with a variety of disorders - patients with autoimmune disease (ankylosing spondylitis [AS]), under cancer immunotherapy, or subject to an acute infection (live yellow fever [YF] vaccine). We validate the method with independent assays. ALICE requires no longitudinal data collection nor large cohorts, and it is directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with diseases and conditions, which can be used for diagnostics and rational vaccine design.
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Affiliation(s)
- Mikhail V. Pogorelyy
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Pirogov Russian National Research Medical University, Moscow, Russia
| | | | - Mikhail Shugay
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Pirogov Russian National Research Medical University, Moscow, Russia
- Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Center of Life Sciences, Skoltech, Moscow, Russia
- Masaryk University, Central European Institute of Technology, Brno, Czech Republic
| | - Dmitriy M. Chudakov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Pirogov Russian National Research Medical University, Moscow, Russia
- Privolzhsky Research Medical University, Nizhny Novgorod, Russia
- Center of Life Sciences, Skoltech, Moscow, Russia
- Masaryk University, Central European Institute of Technology, Brno, Czech Republic
| | - Yuri B. Lebedev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia
- Moscow State University, Moscow, Russia
| | - Thierry Mora
- Laboratoire de physique statistique, CNRS, Sorbonne Université, Université Paris-Diderot, and École normale supérieure (PSL University), Paris, France
- * E-mail: (TM); (AW)
| | - Aleksandra M. Walczak
- Laboratoire de physique théorique, CNRS, Sorbonne Université, Université Paris-Diderot, and École normale supérieure (PSL University), Paris, France
- * E-mail: (TM); (AW)
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47
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Dupic T, Marcou Q, Walczak AM, Mora T. Genesis of the αβ T-cell receptor. PLoS Comput Biol 2019; 15:e1006874. [PMID: 30830899 PMCID: PMC6417744 DOI: 10.1371/journal.pcbi.1006874] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2018] [Revised: 03/14/2019] [Accepted: 02/17/2019] [Indexed: 11/18/2022] Open
Abstract
The T-cell (TCR) repertoire relies on the diversity of receptors composed of two chains, called α and β, to recognize pathogens. Using results of high throughput sequencing and computational chain-pairing experiments of human TCR repertoires, we quantitively characterize the αβ generation process. We estimate the probabilities of a rescue recombination of the β chain on the second chromosome upon failure or success on the first chromosome. Unlike β chains, α chains recombine simultaneously on both chromosomes, resulting in correlated statistics of the two genes which we predict using a mechanistic model. We find that ∼35% of cells express both α chains. Altogether, our statistical analysis gives a complete quantitative mechanistic picture that results in the observed correlations in the generative process. We learn that the probability to generate any TCRαβ is lower than 10(-12) and estimate the generation diversity and sharing properties of the αβ TCR repertoire.
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MESH Headings
- Chromosomes, Human
- Humans
- Probability
- Receptors, Antigen, T-Cell, alpha-beta/biosynthesis
- Receptors, Antigen, T-Cell, alpha-beta/genetics
- Receptors, Antigen, T-Cell, alpha-beta/immunology
- Recombination, Genetic
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Affiliation(s)
- Thomas Dupic
- Laboratoire de physique théorique et hautes énergies, CNRS and Sorbonne Université, 4 Place Jussieu, 75005 Paris, France
- Laboratoire de physique de l’ENS, CNRS, Sorbonne Université, and École normale supérieure (PSL), 24 rue Lhomond, 75005 Paris, France
| | - Quentin Marcou
- Laboratoire de physique de l’ENS, CNRS, Sorbonne Université, and École normale supérieure (PSL), 24 rue Lhomond, 75005 Paris, France
| | - Aleksandra M. Walczak
- Laboratoire de physique de l’ENS, CNRS, Sorbonne Université, and École normale supérieure (PSL), 24 rue Lhomond, 75005 Paris, France
- * E-mail: (AMW); (TM)
| | - Thierry Mora
- Laboratoire de physique de l’ENS, CNRS, Sorbonne Université, and École normale supérieure (PSL), 24 rue Lhomond, 75005 Paris, France
- * E-mail: (AMW); (TM)
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48
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Schober K, Buchholz VR, Busch DH. TCR repertoire evolution during maintenance of CMV-specific T-cell populations. Immunol Rev 2019; 283:113-128. [PMID: 29664573 DOI: 10.1111/imr.12654] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
During infections and cancer, the composition of the T-cell receptor (TCR) repertoire of antigen-specific CD8+ T cells changes over time. TCR avidity is thought to be a major driver of this process, thereby interacting with several additional regulators of T-cell responses to form a composite immune response architecture. Infections with latent viruses, such as cytomegalovirus (CMV), can lead to large T-cell responses characterized by an oligoclonal TCR repertoire. Here, we review the current status of experimental studies and theoretical models of TCR repertoire evolution during CMV infection. We will particularly discuss the degree to which this process may be determined through structural TCR avidity. As engineered TCR-redirected T cells have moved into the spotlight for providing more effective immunotherapies, it is essential to understand how the key features of a given TCR influence T-cell expansion and maintenance in settings of infection or malignancy. Deeper insights into these mechanisms will improve our basic understanding of T-cell immunology and help to identify optimal TCRs for immunotherapy.
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Affiliation(s)
- Kilian Schober
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München (TUM), Munich, Germany
| | - Veit R Buchholz
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München (TUM), Munich, Germany
| | - Dirk H Busch
- Institute for Medical Microbiology, Immunology and Hygiene, Technische Universität München (TUM), Munich, Germany.,Focus Group 'Clinical Cell Processing and Purification', Institute for Advanced Study, TUM, Munich, Germany.,National Centre for Infection Research (DZIF), Munich, Germany
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49
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Bradley P, Thomas PG. Using T Cell Receptor Repertoires to Understand the Principles of Adaptive Immune Recognition. Annu Rev Immunol 2019; 37:547-570. [PMID: 30699000 DOI: 10.1146/annurev-immunol-042718-041757] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Adaptive immune recognition is mediated by antigen receptors on B and T cells generated by somatic recombination during lineage development. The high level of diversity resulting from this process posed technical limitations that previously limited the comprehensive analysis of adaptive immune recognition. Advances over the last ten years have produced data and approaches allowing insights into how T cells develop, evolutionary signatures of recombination and selection, and the features of T cell receptors that mediate epitope-specific binding and T cell activation. The size and complexity of these data have necessitated the generation of novel computational and analytical approaches, which are transforming how T cell immunology is conducted. Here we review the development and application of novel biological, theoretical, and computational methods for understanding T cell recognition and discuss the potential for improved models of receptor:antigen interactions.
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Affiliation(s)
- Philip Bradley
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA; .,Institute for Protein Design, University of Washington, Seattle, Washington 98195, USA
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA;
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50
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Chen H, Chakraborty AK, Kardar M. How nonuniform contact profiles of T cell receptors modulate thymic selection outcomes. Phys Rev E 2018; 97:032413. [PMID: 29776088 DOI: 10.1103/physreve.97.032413] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Indexed: 11/07/2022]
Abstract
T cell receptors (TCRs) bind foreign or self-peptides attached to major histocompatibility complex (MHC) molecules, and the strength of this interaction determines T cell activation. Optimizing the ability of T cells to recognize a diversity of foreign peptides yet be tolerant of self-peptides is crucial for the adaptive immune system to properly function. This is achieved by selection of T cells in the thymus, where immature T cells expressing unique, stochastically generated TCRs interact with a large number of self-peptide-MHC; if a TCR does not bind strongly enough to any self-peptide-MHC, or too strongly with at least one self-peptide-MHC, the T cell dies. Past theoretical work cast thymic selection as an extreme value problem and characterized the statistical enrichment or depletion of amino acids in the postselection TCR repertoire, showing how T cells are selected to be able to specifically recognize peptides derived from diverse pathogens yet have limited self-reactivity. Here, we investigate how the diversity of the postselection TCR repertoire is modified when TCRs make nonuniform contacts with peptide-MHC. Specifically, we were motivated by recent experiments showing that amino acids at certain positions of a TCR sequence have large effects on thymic selection outcomes, and crystal structure data that reveal a nonuniform contact profile between a TCR and its peptide-MHC ligand. Using a representative TCR contact profile as an illustration, we show via simulations that the statistical enrichment or depletion of amino acids now varies by position according to the contact profile, and, importantly, it depends on the implementation of nonuniform contacts during thymic selection. We explain these nontrivial results analytically. Our study has implications for understanding the selection forces that shape the functionality of the postselection TCR repertoire.
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Affiliation(s)
- Hanrong Chen
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Arup K Chakraborty
- Departments of Chemical Engineering, Chemistry, and Biological Engineering, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.,Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Mehran Kardar
- Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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