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Shingai M, Iida S, Kawai N, Kawahara M, Sekiya T, Ohno M, Nomura N, Handabile C, Kawakita T, Omori R, Yamagishi J, Sano K, Ainai A, Suzuki T, Ohnishi K, Ito K, Kida H. Extraction of the CDRH3 sequence of the mouse antibody repertoire selected upon influenza virus infection by subtraction of the background antibody repertoire. J Virol 2024; 98:e0199523. [PMID: 38323813 PMCID: PMC10949447 DOI: 10.1128/jvi.01995-23] [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: 12/19/2023] [Accepted: 01/14/2024] [Indexed: 02/08/2024] Open
Abstract
Historically, antibody reactivity to pathogens and vaccine antigens has been evaluated using serological measurements of antigen-specific antibodies. However, it is difficult to evaluate all antibodies that contribute to various functions in a single assay, such as the measurement of the neutralizing antibody titer. Bulk antibody repertoire analysis using next-generation sequencing is a comprehensive method for analyzing the overall antibody response; however, it is unreliable for estimating antigen-specific antibodies due to individual variation. To address this issue, we propose a method to subtract the background signal from the repertoire of data of interest. In this study, we analyzed changes in antibody diversity and inferred the heavy-chain complementarity-determining region 3 (CDRH3) sequences of antibody clones that were selected upon influenza virus infection in a mouse model using bulk repertoire analysis. A decrease in the diversity of the antibody repertoire was observed upon viral infection, along with an increase in neutralizing antibody titers. Using kernel density estimation of sequences in a high-dimensional sequence space with background signal subtraction, we identified several clusters of CDRH3 sequences induced upon influenza virus infection. Most of these repertoires were detected more frequently in infected mice than in uninfected control mice, suggesting that infection-specific antibody sequences can be extracted using this method. Such an accurate extraction of antigen- or infection-specific repertoire information will be a useful tool for vaccine evaluation in the future. IMPORTANCE As specific interactions between antigens and cell-surface antibodies trigger the proliferation of B-cell clones, the frequency of each antibody sequence in the samples reflects the size of each clonal population. Nevertheless, it is extremely difficult to extract antigen-specific antibody sequences from the comprehensive bulk antibody sequences obtained from blood samples due to repertoire bias influenced by exposure to dietary antigens and other infectious agents. This issue can be addressed by subtracting the background noise from the post-immunization or post-infection repertoire data. In the present study, we propose a method to quantify repertoire data from comprehensive repertoire data. This method allowed subtraction of the background repertoire, resulting in more accurate extraction of expanded antibody repertoires upon influenza virus infection. This accurate extraction of antigen- or infection-specific repertoire information is a useful tool for vaccine evaluation.
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Affiliation(s)
- Masashi Shingai
- Division of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Institute for Vaccine Research and Development (HU-IVReD), Hokkaido University, Sapporo, Japan
- Division of Vaccine Immunology, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Sayaka Iida
- Division of Bioinformatics, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Naoko Kawai
- Division of Collaboration and Education, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Mamiko Kawahara
- Division of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Toshiki Sekiya
- Division of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Institute for Vaccine Research and Development (HU-IVReD), Hokkaido University, Sapporo, Japan
- International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Marumi Ohno
- Division of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Institute for Vaccine Research and Development (HU-IVReD), Hokkaido University, Sapporo, Japan
- One Health Research Center, Hokkaido University, Sapporo, Japan
| | - Naoki Nomura
- Division of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Institute for Vaccine Research and Development (HU-IVReD), Hokkaido University, Sapporo, Japan
| | - Chimuka Handabile
- Division of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Institute for Vaccine Research and Development (HU-IVReD), Hokkaido University, Sapporo, Japan
| | - Tomomi Kawakita
- Institute for Vaccine Research and Development (HU-IVReD), Hokkaido University, Sapporo, Japan
- Division of Vaccine Immunology, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Ryosuke Omori
- Division of Bioinformatics, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Junya Yamagishi
- International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Division of Collaboration and Education, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Kaori Sano
- Department of Pathology, National Institute of Infectious Diseases, Tokyo, Japan
| | - Akira Ainai
- Department of Pathology, National Institute of Infectious Diseases, Tokyo, Japan
| | - Tadaki Suzuki
- Department of Pathology, National Institute of Infectious Diseases, Tokyo, Japan
| | - Kazuo Ohnishi
- Department of Immunology, National Institute of Infectious Diseases, Tokyo, Japan
| | - Kimihito Ito
- International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Division of Bioinformatics, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Hiroshi Kida
- Division of Biologics Development, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Institute for Vaccine Research and Development (HU-IVReD), Hokkaido University, Sapporo, Japan
- International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
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Laurent SA, Strauli NB, Eggers EL, Wu H, Michel B, Demuth S, Palanichamy A, Wilson MR, Sirota M, Hernandez RD, Cree BAC, Herman AE, von Büdingen HC. Effect of Ocrelizumab on B- and T-Cell Receptor Repertoire Diversity in Patients With Relapsing Multiple Sclerosis From the Randomized Phase III OPERA Trial. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2023; 10:e200118. [PMID: 37094998 PMCID: PMC10136682 DOI: 10.1212/nxi.0000000000200118] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 02/22/2023] [Indexed: 04/26/2023]
Abstract
BACKGROUND AND OBJECTIVES The B cell-depleting anti-CD20 antibody ocrelizumab (OCR) effectively reduces MS disease activity and slows disability progression. Given the role of B cells as antigen-presenting cells, the primary goal of this study was to evaluate the effect of OCR on the T-cell receptor repertoire diversity. METHODS To examine whether OCR substantially alters the molecular diversity of the T-cell receptor repertoire, deep immune repertoire sequencing (RepSeq) of CD4+ and CD8+ T-cell receptor β-chain variable regions was performed on longitudinal blood samples. The IgM and IgG heavy chain variable region repertoire was also analyzed to characterize the residual B-cell repertoire under OCR treatment. RESULTS Peripheral blood samples for RepSeq were obtained from 8 patients with relapsing MS enrolled in the OPERA I trial over a period of up to 39 months. Four patients each were treated with OCR or interferon β1-a during the double-blind period of OPERA I. All patients received OCR during the open-label extension. The diversity of the CD4+/CD8+ T-cell repertoires remained unaffected in OCR-treated patients. The expected OCR-associated B-cell depletion was mirrored by reduced B-cell receptor diversity in peripheral blood and a shift in immunoglobulin gene usage. Despite deep B-cell depletion, longitudinal persistence of clonally related B-cells was observed. DISCUSSION Our data illustrate that the diversity of CD4+/CD8+ T-cell receptor repertoires remained unaltered in OCR-treated patients with relapsing MS. Persistence of a highly diverse T-cell repertoire suggests that aspects of adaptive immunity remain intact despite extended anti-CD20 therapy. TRIAL REGISTRATION INFORMATION This is a substudy (BE29353) of the OPERA I (WA21092; NCT01247324) trial. Date of registration, November 23, 2010; first patient enrollment, August 31, 2011.
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Affiliation(s)
- Sarah A Laurent
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Nicolas B Strauli
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Erica L Eggers
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Hao Wu
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Brady Michel
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Stanislas Demuth
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Arumugam Palanichamy
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Michael R Wilson
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Marina Sirota
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Ryan D Hernandez
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Bruce Anthony Campbell Cree
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - Ann E Herman
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA
| | - H-Christian von Büdingen
- From the Department of Neurology (S.A.L., E.L.E., H.W., B.M., S.D., A.P., M.R.W., B.A.C.C., H.-C.B.), Weill Institute for Neurosciences; Biomedical Sciences Graduate Program (N.B.S.); Bakar Computational Health Sciences Institute and Department of Pediatrics (M.S.); Department of Bioengineering and Therapeutic Sciences (R.D.H.), University of California, San Francisco, CA; Department of Human Genetics (R.D.H.), McGill University, Montreal, QC, Canada; and OMNI Biomarker Development (A.E.H.), Genentech, Inc., South San Francisco, CA.
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Weber CR, Rubio T, Wang L, Zhang W, Robert PA, Akbar R, Snapkov I, Wu J, Kuijjer ML, Tarazona S, Conesa A, Sandve GK, Liu X, Reddy ST, Greiff V. Reference-based comparison of adaptive immune receptor repertoires. CELL REPORTS METHODS 2022; 2:100269. [PMID: 36046619 PMCID: PMC9421535 DOI: 10.1016/j.crmeth.2022.100269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 04/01/2022] [Accepted: 07/19/2022] [Indexed: 11/26/2022]
Abstract
B and T cell receptor (immune) repertoires can represent an individual's immune history. While current repertoire analysis methods aim to discriminate between health and disease states, they are typically based on only a limited number of parameters. Here, we introduce immuneREF: a quantitative multidimensional measure of adaptive immune repertoire (and transcriptome) similarity that allows interpretation of immune repertoire variation by relying on both repertoire features and cross-referencing of simulated and experimental datasets. To quantify immune repertoire similarity landscapes across health and disease, we applied immuneREF to >2,400 datasets from individuals with varying immune states (healthy, [autoimmune] disease, and infection). We discovered, in contrast to the current paradigm, that blood-derived immune repertoires of healthy and diseased individuals are highly similar for certain immune states, suggesting that repertoire changes to immune perturbations are less pronounced than previously thought. In conclusion, immuneREF enables the population-wide study of adaptive immune response similarity across immune states.
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Affiliation(s)
- Cédric R. Weber
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Teresa Rubio
- Laboratory of Neurobiology, Centro Investigación Príncipe Felipe, Valencia, Spain
| | - Longlong Wang
- BGI-Shenzhen, Shenzhen, China
- BGI-Education Center, University of Chinese Academy of Sciences, Shenzhen, China
| | - Wei Zhang
- BGI-Shenzhen, Shenzhen, China
- Department of Computer Science, City University of Hong Kong, Hong Kong, China
| | - Philippe A. Robert
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Rahmad Akbar
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Igor Snapkov
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo, Norway
| | | | - Marieke L. Kuijjer
- Centre for Molecular Medicine Norway, University of Oslo, Oslo, Norway
- Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
- Leiden Center for Computational Oncology, Leiden University Medical Center, Leiden, the Netherlands
| | - Sonia Tarazona
- Departamento de Estadística e Investigación Operativa Aplicadas y Calidad, Universitat Politècnica de València, Valencia, Spain
| | - Ana Conesa
- Institute for Integrative Systems Biology, Spanish National Research Council, Valencia, Spain
| | - Geir K. Sandve
- Department of Informatics, University of Oslo, Oslo, Norway
| | - Xiao Liu
- BGI-Shenzhen, Shenzhen, China
- Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
| | - Sai T. Reddy
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Victor Greiff
- Department of Immunology and Oslo University Hospital, University of Oslo, Oslo, Norway
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Zheng B, Yang Y, Chen L, Wu M, Zhou S. B-Cell Receptor Repertoire Sequencing: Deeper Digging into the Mechanisms and Clinical Aspects of Immune-mediated Diseases. iScience 2022; 25:105002. [PMID: 36157582 PMCID: PMC9494237 DOI: 10.1016/j.isci.2022.105002] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
B cells play an essential role in adaptive immunity and are intimately correlated with pleiotropic immune-mediated diseases. Each B cell occupies a unique B cell receptor (BCR), and all BCRs throughout our body form “BCR repertoire.” With the development of sequencing technology and coupled bioinformatics, accumulating evidence indicates that BCR repertoire largely varies under physiological and pathological conditions. Therefore, comprehensive grasp of BCR repertoire will provide new insights into the pathogenesis of immune-mediated diseases and help exploit efficient diagnostic and treatment strategies. In this review, we start with an overview of BCR repertoire and related sequencing technologies and summarize their current applications in immune-mediated diseases. We also underscore the challenges of this emerging field and propose promising future directions in advancing BCR repertoire exploration.
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Affiliation(s)
- Bohao Zheng
- Wuxi School of Medicine, Jiangnan University, Wuxi, P. R. China
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, P. R. China
| | - Yuqing Yang
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, P. R. China
| | - Lin Chen
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, P. R. China
| | - Mengrui Wu
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, P. R. China
| | - Shengtao Zhou
- Department of Obstetrics and Gynecology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of MOE and State Key Laboratory of Biotherapy, West China Second Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, P. R. China
- Corresponding author
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Yu K, Ravoor A, Malats N, Pineda S, Sirota M. A Pan-Cancer Analysis of Tumor-Infiltrating B Cell Repertoires. Front Immunol 2022; 12:790119. [PMID: 35069569 PMCID: PMC8767103 DOI: 10.3389/fimmu.2021.790119] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/06/2021] [Indexed: 12/22/2022] Open
Abstract
Tumor-infiltrating B cells can play an important role in anti-tumor responses but their presence is not well understood. In this study, we extracted the B cell receptor repertoires from 9522 tumor and adjacent non-tumor samples across 28 tumor types in the Cancer Genome Atlas project and performed diversity and network analysis. We identified differences in diversity and network statistics across tumor types and subtypes and observed a trend towards increased clonality in primary tumors compared to adjacent non-tumor tissues. We also found significant associations between the repertoire features and mutation load, tumor stage, and age. Our V-gene usage analysis identified similar V-gene usage patterns in colorectal and endometrial cancers. Lastly, we evaluated the prognostic value of the repertoire features and identified significant associations with survival in seven tumor types. This study warrants further research into better understanding the role of tumor-infiltrating B cells across a wide range of tumor types.
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Affiliation(s)
- Katharine Yu
- Bakar Computational Health Sciences Institute, University of California, San Francisco (UCSF), San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco (UCSF), San Francisco, CA, United States
| | - Akshay Ravoor
- Bakar Computational Health Sciences Institute, University of California, San Francisco (UCSF), San Francisco, CA, United States
| | - Núria Malats
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), and Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain
| | - Silvia Pineda
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), and Centro de Investigación Biomédica en Red Cáncer (CIBERONC), Madrid, Spain
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco (UCSF), San Francisco, CA, United States
- Department of Pediatrics, University of California, San Francisco (UCSF), San Francisco, CA, United States
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Arnaout RA, Prak ETL, Schwab N, Rubelt F. The Future of Blood Testing Is the Immunome. Front Immunol 2021; 12:626793. [PMID: 33790897 PMCID: PMC8005722 DOI: 10.3389/fimmu.2021.626793] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 01/19/2021] [Indexed: 12/13/2022] Open
Abstract
It is increasingly clear that an extraordinarily diverse range of clinically important conditions—including infections, vaccinations, autoimmune diseases, transplants, transfusion reactions, aging, and cancers—leave telltale signatures in the millions of V(D)J-rearranged antibody and T cell receptor [TR per the Human Genome Organization (HUGO) nomenclature but more commonly known as TCR] genes collectively expressed by a person’s B cells (antibodies) and T cells. We refer to these as the immunome. Because of its diversity and complexity, the immunome provides singular opportunities for advancing personalized medicine by serving as the substrate for a highly multiplexed, near-universal blood test. Here we discuss some of these opportunities, the current state of immunome-based diagnostics, and highlight some of the challenges involved. We conclude with a call to clinicians, researchers, and others to join efforts with the Adaptive Immune Receptor Repertoire Community (AIRR-C) to realize the diagnostic potential of the immunome.
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Affiliation(s)
- Ramy A Arnaout
- Department of Pathology and Division of Clinical Informatics, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States.,Department of Pathology, Harvard Medical School, Boston, MA, United States
| | - Eline T Luning Prak
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Nicholas Schwab
- Department of Neurology and Institute of Translational Neurology, University of Muenster, Muenster, Germany
| | - Florian Rubelt
- Roche Sequencing Solutions, Pleasanton, CA, United States
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Forgacs D, Abreu RB, Sautto GA, Kirchenbaum GA, Drabek E, Williamson KS, Kim D, Emerling DE, Ross TM. Convergent antibody evolution and clonotype expansion following influenza virus vaccination. PLoS One 2021; 16:e0247253. [PMID: 33617543 PMCID: PMC7899375 DOI: 10.1371/journal.pone.0247253] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 02/03/2021] [Indexed: 12/14/2022] Open
Abstract
Recent advances in high-throughput single cell sequencing have opened up new avenues into the investigation of B cell receptor (BCR) repertoires. In this study, PBMCs were collected from 17 human participants vaccinated with the split-inactivated influenza virus vaccine during the 2016-2017 influenza season. A combination of Immune Repertoire Capture (IRCTM) technology and IgG sequencing was performed on ~7,800 plasmablast (PB) cells and preferential IgG heavy-light chain pairings were investigated. In some participants, a single expanded clonotype accounted for ~22% of their PB BCR repertoire. Approximately 60% (10/17) of participants experienced convergent evolution, possessing public PBs that were elicited independently in multiple participants. Binding profiles of one private and three public PBs confirmed they were all subtype-specific, cross-reactive hemagglutinin (HA) head-directed antibodies. Collectively, this high-resolution antibody repertoire analysis demonstrated the impact evolution can have on BCRs in response to influenza virus vaccination, which can guide future universal influenza prophylactic approaches.
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Affiliation(s)
- David Forgacs
- Center for Vaccines and Immunology, University of Georgia, Athens, GA, United States of America
| | - Rodrigo B. Abreu
- Center for Vaccines and Immunology, University of Georgia, Athens, GA, United States of America
| | - Giuseppe A. Sautto
- Center for Vaccines and Immunology, University of Georgia, Athens, GA, United States of America
| | - Greg A. Kirchenbaum
- Center for Vaccines and Immunology, University of Georgia, Athens, GA, United States of America
| | - Elliott Drabek
- Atreca, Inc., South San Francisco, CA, United States of America
| | | | - Dongkyoon Kim
- Atreca, Inc., South San Francisco, CA, United States of America
| | | | - Ted M. Ross
- Center for Vaccines and Immunology, University of Georgia, Athens, GA, United States of America
- Department of Infectious Diseases, University of Georgia, Athens, GA, United States of America
- * E-mail:
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8
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Abstract
Over the last several years, next-generation sequencing and its recent push toward single-cell resolution have transformed the landscape of immunology research by revealing novel complexities about all components of the immune system. With the vast amounts of diverse data currently being generated, and with the methods of analyzing and combining diverse data improving as well, integrative systems approaches are becoming more powerful. Previous integrative approaches have combined multiple data types and revealed ways that the immune system, both as a whole and as individual parts, is affected by genetics, the microbiome, and other factors. In this review, we explore the data types that are available for studying immunology with an integrative systems approach, as well as the current strategies and challenges for conducting such analyses.
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Affiliation(s)
- Silvia Pineda
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94158, USA
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre, 28029 Madrid, Spain
| | - Daniel G. Bunis
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94158, USA
| | - Idit Kosti
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94158, USA
- Department of Pediatrics, University of California, San Francisco, California 94143, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94158, USA
- Department of Pediatrics, University of California, San Francisco, California 94143, USA
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9
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Mandric I, Rotman J, Yang HT, Strauli N, Montoya DJ, Van Der Wey W, Ronas JR, Statz B, Yao D, Petrova V, Zelikovsky A, Spreafico R, Shifman S, Zaitlen N, Rossetti M, Ansel KM, Eskin E, Mangul S. Profiling immunoglobulin repertoires across multiple human tissues using RNA sequencing. Nat Commun 2020; 11:3126. [PMID: 32561710 PMCID: PMC7305308 DOI: 10.1038/s41467-020-16857-7] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Accepted: 05/24/2020] [Indexed: 11/09/2022] Open
Abstract
Profiling immunoglobulin (Ig) receptor repertoires with specialized assays can be cost-ineffective and time-consuming. Here we report ImReP, a computational method for rapid and accurate profiling of the Ig repertoire, including the complementary-determining region 3 (CDR3), using regular RNA sequencing data such as those from 8,555 samples across 53 tissues types from 544 individuals in the Genotype-Tissue Expression (GTEx v6) project. Using ImReP and GTEx v6 data, we generate a collection of 3.6 million Ig sequences, termed the atlas of immunoglobulin repertoires (TAIR), across a broad range of tissue types that often do not have reported Ig repertoires information. Moreover, the flow of Ig clonotypes and inter-tissue repertoire similarities across immune-related tissues are also evaluated. In summary, TAIR is one of the largest collections of CDR3 sequences and tissue types, and should serve as an important resource for studying immunological diseases. Information on immune receptor repertoire provides important insights on disease progression and therapy development, but can be expensive and time-consuming to obtain. Here the authors report ImReP, a computational method that can extract detailed immune repertoire information from existing tissue-specific RNA sequencing data.
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Affiliation(s)
- Igor Mandric
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA
| | - Jeremy Rotman
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA.,Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1540 Alcazar Street, Los Angeles, CA, 90033, USA
| | - Harry Taegyun Yang
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA.,Bioinformatics Interdepartmental Ph.D. Program, University of California, Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA, 90095-1570, USA
| | - Nicolas Strauli
- Biomedical Sciences Graduate Program, University of California, San Francisco, 1675 Owens Street, Suite 310, San Francisco, CA, 94143-0523, USA
| | - Dennis J Montoya
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, 610 Charles E. Young Drive South, Los Angeles, CA, 90095, USA
| | - William Van Der Wey
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA
| | - Jiem R Ronas
- Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, 609 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Benjamin Statz
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA
| | - Douglas Yao
- Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, 610 Charles E. Young Drive South, Los Angeles, CA, 90095, USA.,Program in Bioinformatics and Integrative Genomics, Harvard Medical School, 10 Shattuck Street, Suite 514, Boston, MA, 02115, USA
| | - Velislava Petrova
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Alex Zelikovsky
- Department of Computer Science, Georgia State University, 33 Gilmer Street SE, Atlanta, GA, 30303, USA.,The Laboratory of Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Roberto Spreafico
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA, 90095, USA
| | - Sagiv Shifman
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, 9190401, Israel
| | - Noah Zaitlen
- Department of Medicine, University of California, San Francisco, 533 Parnassus Avenue, San Francisco, CA, 94143, USA
| | - Maura Rossetti
- Immunogenetics Center, Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, 1000 Veteran Avenue, Los Angeles, CA, 90095-1652, USA
| | - K Mark Ansel
- Sandler Asthma Basic Research Center, Department of Microbiology and Immunology, University of California, San Francisco, 513 Parnassus Avenue, San Francisco, CA, 94143-0414, USA
| | - Eleazar Eskin
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA.,Department of Human Genetics, David Geffen School of Medicine at UCLA, 695 Charles E. Young Drive South, Box 708822, Los Angeles, CA, 90095, USA.,Department of Computational Medicine, David Geffen School of Medicine at UCLA, 73-235 CHS, Los Angeles, CA, 90095, USA
| | - Serghei Mangul
- Department of Computer Science, University of California, Los Angeles, 404 Westwood Plaza, Los Angeles, CA, 90095, USA. .,Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1540 Alcazar Street, Los Angeles, CA, 90033, USA. .,Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, 611 Charles E. Young Drive East, Los Angeles, CA, 90095, USA.
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10
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Adaptive immune receptor repertoires, an overview of this exciting field. Immunol Lett 2020; 221:49-55. [PMID: 32113899 DOI: 10.1016/j.imlet.2020.02.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 02/19/2020] [Accepted: 02/26/2020] [Indexed: 12/30/2022]
Abstract
The adaptive immune response in jawed vertebrates relies on the huge diversity and specificity of the B cell and T cell antigen receptors, the immunoglobulins (IG) or antibodies and the T cell receptors (TR), respectively. The high level of diversity has represented a barrier to a comprehensive analysis of the adaptive immune response before the emergence of high-throughput sequencing (HTS) technologies. The size and complexity of HTS data requires the generation of novel computational and analytical approaches, which are transforming how the adaptive immune responses are deciphered to understand the clonal dynamics and properties of antigen-specific B and T cells in response to different kind of antigens. This exciting and rapidly evolving field is not only impacting human and clinical immunology but also comparative immunology. We are now closer to understanding the evolution of adaptive immune response in jawed vertebrates. This review provides an overview about classical and current strategies developed to assess the IG/TR diversity and their applications in basic and clinical immunology.
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11
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Fowler A, Galson JD, Trück J, Kelly DF, Lunter G. Inferring B cell specificity for vaccines using a Bayesian mixture model. BMC Genomics 2020; 21:176. [PMID: 32087698 PMCID: PMC7036227 DOI: 10.1186/s12864-020-6571-7] [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: 05/01/2019] [Accepted: 02/10/2020] [Indexed: 12/30/2022] Open
Abstract
Background Vaccines have greatly reduced the burden of infectious disease, ranking in their impact on global health second only after clean water. Most vaccines confer protection by the production of antibodies with binding affinity for the antigen, which is the main effector function of B cells. This results in short term changes in the B cell receptor (BCR) repertoire when an immune response is launched, and long term changes when immunity is conferred. Analysis of antibodies in serum is usually used to evaluate vaccine response, however this is limited and therefore the investigation of the BCR repertoire provides far more detail for the analysis of vaccine response. Results Here, we introduce a novel Bayesian model to describe the observed distribution of BCR sequences and the pattern of sharing across time and between individuals, with the goal to identify vaccine-specific BCRs. We use data from two studies to assess the model and estimate that we can identify vaccine-specific BCRs with 69% sensitivity. Conclusion Our results demonstrate that statistical modelling can capture patterns associated with vaccine response and identify vaccine specific B cells in a range of different data sets. Additionally, the B cells we identify as vaccine specific show greater levels of sequence similarity than expected, suggesting that there are additional signals of vaccine response, not currently considered, which could improve the identification of vaccine specific B cells.
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Affiliation(s)
- Anna Fowler
- Department of Biostatistics, University of Liverpool, Liverpool, UK.
| | - Jacob D Galson
- University Children's Hospital Zurich and the Children's Research Center, University of Zurich, Zurich, Switzerland
| | - Johannes Trück
- University Children's Hospital Zurich and the Children's Research Center, University of Zurich, Zurich, Switzerland
| | - Dominic F Kelly
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford and the NIHR Oxford Biomedical Research Center, Oxford, UK
| | - Gerton Lunter
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
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12
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Pineda S, Sigdel TK, Liberto JM, Vincenti F, Sirota M, Sarwal MM. Characterizing pre-transplant and post-transplant kidney rejection risk by B cell immune repertoire sequencing. Nat Commun 2019; 10:1906. [PMID: 31015506 PMCID: PMC6479061 DOI: 10.1038/s41467-019-09930-3] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2018] [Accepted: 04/02/2019] [Indexed: 01/25/2023] Open
Abstract
Studying immune repertoire in the context of organ transplant provides important information on how adaptive immunity may contribute and modulate graft rejection. Here we characterize the peripheral blood immune repertoire of individuals before and after kidney transplant using B cell receptor sequencing in a longitudinal clinical study. Individuals who develop rejection after transplantation have a more diverse immune repertoire before transplant, suggesting a predisposition for post-transplant rejection risk. Additionally, over 2 years of follow-up, patients who develop rejection demonstrate a specific set of expanded clones that persist after the rejection. While there is an overall reduction of peripheral B cell diversity, likely due to increased general immunosuppression exposure in this cohort, the detection of specific IGHV gene usage across all rejecting patients supports that a common pool of immunogenic antigens may drive post-transplant rejection. Our findings may have clinical implications for the prediction and clinical management of kidney transplant rejection.
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MESH Headings
- Adolescent
- Adult
- B-Lymphocytes/immunology
- B-Lymphocytes/pathology
- Child
- Child, Preschool
- Clone Cells
- Female
- Gene Expression
- Graft Rejection/genetics
- Graft Rejection/immunology
- Graft Rejection/pathology
- Graft Survival/genetics
- Humans
- Immunocompromised Host
- Infant
- Kidney/immunology
- Kidney/pathology
- Kidney/surgery
- Kidney Transplantation
- Longitudinal Studies
- Male
- Middle Aged
- Polymorphism, Genetic/immunology
- Receptors, Antigen, B-Cell/genetics
- Receptors, Antigen, B-Cell/immunology
- Renal Insufficiency, Chronic/genetics
- Renal Insufficiency, Chronic/immunology
- Renal Insufficiency, Chronic/pathology
- Renal Insufficiency, Chronic/surgery
- Sequence Analysis, DNA
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Affiliation(s)
- Silvia Pineda
- Bakar Computational Health Sciences Institute, University of California, San Francisco (UCSF), 550 16th Street, San Francisco, CA, 94158, USA.
- Division of Transplant Surgery, Department of Surgery, University of California, San Francisco (UCSF), 505 Parnassus Ave, San Francisco, CA, 94143, USA.
| | - Tara K Sigdel
- Division of Transplant Surgery, Department of Surgery, University of California, San Francisco (UCSF), 505 Parnassus Ave, San Francisco, CA, 94143, USA
| | - Juliane M Liberto
- Division of Transplant Surgery, Department of Surgery, University of California, San Francisco (UCSF), 505 Parnassus Ave, San Francisco, CA, 94143, USA
| | - Flavio Vincenti
- Division of Transplant Surgery, Department of Surgery, University of California, San Francisco (UCSF), 505 Parnassus Ave, San Francisco, CA, 94143, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco (UCSF), 550 16th Street, San Francisco, CA, 94158, USA.
- Department of Pediatrics, University of California, San Francisco (UCSF), 550 16th Street, San Francisco, CA, 94158, USA.
| | - Minnie M Sarwal
- Division of Transplant Surgery, Department of Surgery, University of California, San Francisco (UCSF), 505 Parnassus Ave, San Francisco, CA, 94143, USA.
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13
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Yamayoshi S, Kawaoka Y. Current and future influenza vaccines. Nat Med 2019; 25:212-220. [PMID: 30692696 DOI: 10.1038/s41591-018-0340-z] [Citation(s) in RCA: 109] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 12/19/2018] [Indexed: 11/09/2022]
Abstract
Although antiviral drugs and vaccines have reduced the economic and healthcare burdens of influenza, influenza epidemics continue to take a toll. Over the past decade, research on influenza viruses has revealed a potential path to improvement. The clues have come from accumulated discoveries from basic and clinical studies. Now, virus surveillance allows researchers to monitor influenza virus epidemic trends and to accumulate virus sequences in public databases, which leads to better selection of candidate viruses for vaccines and early detection of drug-resistant viruses. Here we provide an overview of current vaccine options and describe efforts directed toward the development of next-generation vaccines. Finally, we propose a plan for the development of an optimal influenza vaccine.
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Affiliation(s)
- Seiya Yamayoshi
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Yoshihiro Kawaoka
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan. .,Department of Special Pathogens, International Research Center for Infectious Diseases, Institute of Medical Science, University of Tokyo, Tokyo, Japan. .,Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin Madison, Madison, WI, USA.
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14
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Rettig TA, Pecaut MJ, Chapes SK. A comparison of unamplified and massively multiplexed PCR amplification for murine antibody repertoire sequencing. FASEB Bioadv 2019; 1:6-17. [PMID: 30740592 PMCID: PMC6366624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023] Open
Abstract
Sequencing antibody repertoires has steadily become cheaper and easier. Sequencing methods usually rely on some form of amplification, often a massively multiplexed PCR prior to sequencing. To eliminate potential biases and create a data set that could be used for other studies, our lab compared unamplified sequencing results from the splenic heavy-chain repertoire in the mouse to those processed through two commercial applications. We also compared the use of mRNA vs total RNA, reverse transcriptase, and primer usage for cDNA synthesis and submission. The use of mRNA for cDNA synthesis resulted in higher read counts but reverse transcriptase and primer usage had no statistical effects on read count. Although most of the amplified data sets contained more antibody reads than the unamplified data set, we detected more unique V-gene segments in the unamplified data set. Although unique CDR3 detection was much lower in the unamplified data set, RNASeq detected 98% of the high frequency CDR3s. We have shown that unamplified profiling of the antibody repertoire is possible, detects more V-gene segments, and detects high frequency clones in the repertoire.
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Affiliation(s)
- Trisha A. Rettig
- Division of Biology, Kansas State University, Manhattan, KS, USA
| | - Michael J. Pecaut
- Division of Radiation Research, Loma Linda University, Loma Linda, CA, USA
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15
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Mou Y, Zhou XX, Leung K, Martinko AJ, Yu JY, Chen W, Wells JA. Engineering Improved Antiphosphotyrosine Antibodies Based on an Immunoconvergent Binding Motif. J Am Chem Soc 2018; 140:16615-16624. [PMID: 30398859 DOI: 10.1021/jacs.8b08402] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Phosphotyrosine (pY) is one of the most highly studied posttranslational modifications that is responsible for tightly regulating many signaling pathways in eukaryotes. Pan-specific pY antibodies have emerged as powerful tools for understanding the role of these modifications. Nevertheless, structures have not been reported for pan-specific pY antibodies, greatly impeding the further development of tools for integrating this ubiquitous posttranslational modification using structure-guided designs. Here, we present the first crystal structures of two widely utilized pan-specific pY antibodies, PY20 and 4G10. The two antibodies, although developed independently from animal immunizations, have surprisingly similar modes of recognition of the phosphate group, implicating a generic binding structure among pan-specific pY antibodies. Sequence alignments revealed that many pY binding residues are predominant in the mouse V germline genes, which consequently led to the convergent antibodies. On the basis of the convergent structure, we designed a phage display library by lengthening the CDR-L3 loop with the aid of computational modeling. Panning with this library resulted in a series of 4G10 variants with 4 to 11-fold improvements in pY binding affinities. The crystal structure of one improved variant showed remarkable superposition to the computational model, where the lengthened CDR-L3 loop creates an additional hydrogen bond indirectly bound to the phosphate group via a water molecule. The engineered variants exhibited superior performance in Western blot and immunofluorescence.
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Affiliation(s)
- Yun Mou
- Department of Pharmaceutical Chemistry , University of California, San Francisco , San Francisco , California 94143 , United States.,Institute of Biomedical Sciences , Academia Sinica , Taipei 11529 , Taiwan
| | - Xin X Zhou
- Department of Pharmaceutical Chemistry , University of California, San Francisco , San Francisco , California 94143 , United States
| | - Kevin Leung
- Department of Pharmaceutical Chemistry , University of California, San Francisco , San Francisco , California 94143 , United States
| | - Alexander J Martinko
- Department of Pharmaceutical Chemistry , University of California, San Francisco , San Francisco , California 94143 , United States.,Chemistry and Chemical Biology Graduate Program , University of California, San Francisco , San Francisco , California 94143 , United States
| | - Jiun-Yann Yu
- Department of Electrical, Computer, and Energy Engineering , University of Colorado , Boulder , Colorado 80309 , United States
| | - Wentao Chen
- Department of Pharmaceutical Chemistry , University of California, San Francisco , San Francisco , California 94143 , United States
| | - James A Wells
- Department of Pharmaceutical Chemistry , University of California, San Francisco , San Francisco , California 94143 , United States.,Department of Cellular and Molecular Pharmacology , University of California, San Francisco , San Francisco , California 94143 , United States
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16
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Rettig TA, Pecaut MJ, Chapes SK. A comparison of unamplified and massively multiplexed PCR amplification for murine antibody repertoire sequencing. FASEB Bioadv 2018; 1:6-17. [PMID: 32123808 PMCID: PMC6996338 DOI: 10.1096/fba.1017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 08/09/2018] [Accepted: 08/17/2018] [Indexed: 11/26/2022] Open
Abstract
Sequencing antibody repertoires has steadily become cheaper and easier. Sequencing methods usually rely on some form of amplification, often a massively multiplexed PCR prior to sequencing. To eliminate potential biases and create a data set that could be used for other studies, our laboratory compared unamplified sequencing results from the splenic heavy‐chain repertoire in the mouse to those processed through two commercial applications. We also compared the use of mRNA vs total RNA, reverse transcriptase, and primer usage for cDNA synthesis and submission. The use of mRNA for cDNA synthesis resulted in higher read counts but reverse transcriptase and primer usage had no statistical effects on read count. Although most of the amplified data sets contained more antibody reads than the unamplified data set, we detected more unique variable (V)‐gene segments in the unamplified data set. Although unique CDR3 detection was much lower in the unamplified data set, RNASeq detected 98% of the high‐frequency CDR3s. We have shown that unamplified profiling of the antibody repertoire is possible, detects more V‐gene segments, and detects high‐frequency clones in the repertoire.
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Affiliation(s)
- Trisha A Rettig
- Division of Biology Kansas State University Manhattan Kansas
| | - Michael J Pecaut
- Division of Biomedical Engineering Sciences (BMES) Loma Linda University Loma Linda California
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17
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Dunn‐Walters D, Townsend C, Sinclair E, Stewart A. Immunoglobulin gene analysis as a tool for investigating human immune responses. Immunol Rev 2018; 284:132-147. [PMID: 29944755 PMCID: PMC6033188 DOI: 10.1111/imr.12659] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The human immunoglobulin repertoire is a hugely diverse set of sequences that are formed by processes of gene rearrangement, heavy and light chain gene assortment, class switching and somatic hypermutation. Early B cell development produces diverse IgM and IgD B cell receptors on the B cell surface, resulting in a repertoire that can bind many foreign antigens but which has had self-reactive B cells removed. Later antigen-dependent development processes adjust the antigen affinity of the receptor by somatic hypermutation. The effector mechanism of the antibody is also adjusted, by switching the class of the antibody from IgM to one of seven other classes depending on the required function. There are many instances in human biology where positive and negative selection forces can act to shape the immunoglobulin repertoire and therefore repertoire analysis can provide useful information on infection control, vaccination efficacy, autoimmune diseases, and cancer. It can also be used to identify antigen-specific sequences that may be of use in therapeutics. The juxtaposition of lymphocyte development and numerical evaluation of immune repertoires has resulted in the growth of a new sub-speciality in immunology where immunologists and computer scientists/physicists collaborate to assess immune repertoires and develop models of immune action.
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Affiliation(s)
| | | | - Emma Sinclair
- Faculty of Health and Medical SciencesUniversity of SurreyGuildfordUK
| | - Alex Stewart
- Faculty of Health and Medical SciencesUniversity of SurreyGuildfordUK
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18
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Imkeller K, Wardemann H. Assessing human B cell repertoire diversity and convergence. Immunol Rev 2018; 284:51-66. [DOI: 10.1111/imr.12670] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
| | - Hedda Wardemann
- German Cancer Research Center; B Cell Immunology; Heidelberg Germany
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19
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Christley S, Scarborough W, Salinas E, Rounds WH, Toby IT, Fonner JM, Levin MK, Kim M, Mock SA, Jordan C, Ostmeyer J, Buntzman A, Rubelt F, Davila ML, Monson NL, Scheuermann RH, Cowell LG. VDJServer: A Cloud-Based Analysis Portal and Data Commons for Immune Repertoire Sequences and Rearrangements. Front Immunol 2018; 9:976. [PMID: 29867956 PMCID: PMC5953328 DOI: 10.3389/fimmu.2018.00976] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 04/19/2018] [Indexed: 11/13/2022] Open
Abstract
Background Recent technological advances in immune repertoire sequencing have created tremendous potential for advancing our understanding of adaptive immune response dynamics in various states of health and disease. Immune repertoire sequencing produces large, highly complex data sets, however, which require specialized methods and software tools for their effective analysis and interpretation. Results VDJServer is a cloud-based analysis portal for immune repertoire sequence data that provide access to a suite of tools for a complete analysis workflow, including modules for preprocessing and quality control of sequence reads, V(D)J gene segment assignment, repertoire characterization, and repertoire comparison. VDJServer also provides sophisticated visualizations for exploratory analysis. It is accessible through a standard web browser via a graphical user interface designed for use by immunologists, clinicians, and bioinformatics researchers. VDJServer provides a data commons for public sharing of repertoire sequencing data, as well as private sharing of data between users. We describe the main functionality and architecture of VDJServer and demonstrate its capabilities with use cases from cancer immunology and autoimmunity. Conclusion VDJServer provides a complete analysis suite for human and mouse T-cell and B-cell receptor repertoire sequencing data. The combination of its user-friendly interface and high-performance computing allows large immune repertoire sequencing projects to be analyzed with no programming or software installation required. VDJServer is a web-accessible cloud platform that provides access through a graphical user interface to a data management infrastructure, a collection of analysis tools covering all steps in an analysis, and an infrastructure for sharing data along with workflows, results, and computational provenance. VDJServer is a free, publicly available, and open-source licensed resource.
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Affiliation(s)
- Scott Christley
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Walter Scarborough
- Texas Advanced Computing Center, University of Texas at Austin, Austin, TX, United States
| | - Eddie Salinas
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - William H. Rounds
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Inimary T. Toby
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - John M. Fonner
- Texas Advanced Computing Center, University of Texas at Austin, Austin, TX, United States
| | | | - Min Kim
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Stephen A. Mock
- Texas Advanced Computing Center, University of Texas at Austin, Austin, TX, United States
| | - Christopher Jordan
- Texas Advanced Computing Center, University of Texas at Austin, Austin, TX, United States
| | - Jared Ostmeyer
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Adam Buntzman
- Bio5 Institute, University of Arizona, Tucson, AZ, United States
| | - Florian Rubelt
- Department of Microbiology and Immunology, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, United States
| | - Marco L. Davila
- H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, United States
| | - Nancy L. Monson
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX, United States,Department of Immunology, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Richard H. Scheuermann
- J. Craig Venter Institute, La Jolla, CA, United States,Department of Pathology, University of California, San Diego, San Diego, CA, United States,La Jolla Institute for Allergy & Immunology, La Jolla, CA, United States
| | - Lindsay G. Cowell
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States,*Correspondence: Lindsay G. Cowell,
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20
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ImmPort, toward repurposing of open access immunological assay data for translational and clinical research. Sci Data 2018; 5:180015. [PMID: 29485622 PMCID: PMC5827693 DOI: 10.1038/sdata.2018.15] [Citation(s) in RCA: 441] [Impact Index Per Article: 73.5] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 12/29/2017] [Indexed: 12/21/2022] Open
Abstract
Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings. The ImmPort ecosystem consists of four components–Private Data, Shared Data, Data Analysis, and Resources—for data archiving, dissemination, analyses, and reuse. To date, more than 300 studies have been made freely available through the Shared Data portal (www.immport.org/immport-open), which allows research data to be repurposed to accelerate the translation of new insights into discoveries.
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21
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Miho E, Yermanos A, Weber CR, Berger CT, Reddy ST, Greiff V. Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires. Front Immunol 2018; 9:224. [PMID: 29515569 PMCID: PMC5826328 DOI: 10.3389/fimmu.2018.00224] [Citation(s) in RCA: 116] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Accepted: 01/26/2018] [Indexed: 12/21/2022] Open
Abstract
The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic, and (iv) machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.
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Affiliation(s)
- Enkelejda Miho
- Department for Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
- aiNET GmbH, ETH Zürich, Basel, Switzerland
| | - Alexander Yermanos
- Department for Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Cédric R. Weber
- Department for Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Christoph T. Berger
- Department of Biomedicine, University Hospital Basel, Basel, Switzerland
- Department of Internal Medicine, Clinical Immunology, University Hospital Basel, Basel, Switzerland
| | - Sai T. Reddy
- Department for Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Victor Greiff
- Department for Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
- Department of Immunology, University of Oslo, Oslo, Norway
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22
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Mangul S, Yang HT, Strauli N, Gruhl F, Porath HT, Hsieh K, Chen L, Daley T, Christenson S, Wesolowska-Andersen A, Spreafico R, Rios C, Eng C, Smith AD, Hernandez RD, Ophoff RA, Santana JR, Levanon EY, Woodruff PG, Burchard E, Seibold MA, Shifman S, Eskin E, Zaitlen N. ROP: dumpster diving in RNA-sequencing to find the source of 1 trillion reads across diverse adult human tissues. Genome Biol 2018; 19:36. [PMID: 29548336 PMCID: PMC5857127 DOI: 10.1186/s13059-018-1403-7] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Accepted: 02/02/2018] [Indexed: 11/22/2022] Open
Abstract
High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki.
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Affiliation(s)
- Serghei Mangul
- Department of Computer Science, University of California, Los Angeles, CA, USA. .,Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA, USA.
| | - Harry Taegyun Yang
- Department of Computer Science, University of California, Los Angeles, CA, USA
| | - Nicolas Strauli
- Biomedical Sciences Graduate Program, University of California, San Francisco, CA, USA
| | - Franziska Gruhl
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland.,SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Hagit T Porath
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel
| | - Kevin Hsieh
- Department of Computer Science, University of California, Los Angeles, CA, USA
| | - Linus Chen
- Department of Bioengineering, University of California, Los Angeles, CA, USA
| | - Timothy Daley
- Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - Stephanie Christenson
- Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, and Cardiovascular Research Institute, University of California, San Francisco, CA, USA
| | | | - Roberto Spreafico
- Institute for Quantitative and Computational Biosciences, University of California, Los Angeles, CA, USA
| | - Cydney Rios
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, CA, USA
| | - Andrew D Smith
- Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA
| | - Ryan D Hernandez
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA.,Institute for Quantitative Biosciences, University of California, San Francisco, CA, USA.,Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Roel A Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University California, Los Angeles, CA, USA.,Department of Human Genetics, University of California, Los Angeles, CA, USA.,Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Erez Y Levanon
- The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel
| | - Prescott G Woodruff
- Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, and Cardiovascular Research Institute, University of California, San Francisco, CA, USA
| | - Esteban Burchard
- Schools of Pharmacy and Medicine, Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| | - Max A Seibold
- Department of Pediatrics, National Jewish Health, Denver, CO, USA.,University of Colorado School of Medicine, Denver, CO, USA
| | - Sagiv Shifman
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Eleazar Eskin
- Department of Computer Science, University of California, Los Angeles, CA, USA.,Department of Human Genetics, University of California, Los Angeles, CA, USA
| | - Noah Zaitlen
- Division of Pulmonary, Critical Care, Sleep and Allergy, Department of Medicine, and Cardiovascular Research Institute, University of California, San Francisco, CA, USA.
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23
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Bürckert JP, Dubois ARSX, Faison WJ, Farinelle S, Charpentier E, Sinner R, Wienecke-Baldacchino A, Muller CP. Functionally Convergent B Cell Receptor Sequences in Transgenic Rats Expressing a Human B Cell Repertoire in Response to Tetanus Toxoid and Measles Antigens. Front Immunol 2017; 8:1834. [PMID: 29312330 PMCID: PMC5743747 DOI: 10.3389/fimmu.2017.01834] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2017] [Accepted: 12/05/2017] [Indexed: 11/13/2022] Open
Abstract
The identification and tracking of antigen-specific immunoglobulin (Ig) sequences within total Ig repertoires is central to high-throughput sequencing (HTS) studies of infections or vaccinations. In this context, public Ig sequences shared by different individuals exposed to the same antigen could be valuable markers for tracing back infections, measuring vaccine immunogenicity, and perhaps ultimately allow the reconstruction of the immunological history of an individual. Here, we immunized groups of transgenic rats expressing human Ig against tetanus toxoid (TT), Modified Vaccinia virus Ankara (MVA), measles virus hemagglutinin and fusion proteins expressed on MVA, and the environmental carcinogen benzo[a]pyrene, coupled to TT. We showed that these antigens impose a selective pressure causing the Ig heavy chain (IgH) repertoires of the rats to converge toward the expression of antibodies with highly similar IgH CDR3 amino acid sequences. We present a computational approach, similar to differential gene expression analysis, that selects for clusters of CDR3s with 80% similarity, significantly overrepresented within the different groups of immunized rats. These IgH clusters represent antigen-induced IgH signatures exhibiting stereotypic amino acid patterns including previously described TT- and measles-specific IgH sequences. Our data suggest that with the presented methodology, transgenic Ig rats can be utilized as a model to identify antigen-induced, human IgH signatures to a variety of different antigens.
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Affiliation(s)
- Jean-Philippe Bürckert
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Axel R S X Dubois
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - William J Faison
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Sophie Farinelle
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Emilie Charpentier
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Regina Sinner
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | | | - Claude P Muller
- Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
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24
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Greiff V, Weber CR, Palme J, Bodenhofer U, Miho E, Menzel U, Reddy ST. Learning the High-Dimensional Immunogenomic Features That Predict Public and Private Antibody Repertoires. THE JOURNAL OF IMMUNOLOGY 2017; 199:2985-2997. [DOI: 10.4049/jimmunol.1700594] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 08/16/2017] [Indexed: 11/19/2022]
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25
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Khavrutskii IV, Chaudhury S, Stronsky SM, Lee DW, Benko JG, Wallqvist A, Bavari S, Cooper CL. Quantitative Analysis of Repertoire-Scale Immunoglobulin Properties in Vaccine-Induced B-Cell Responses. Front Immunol 2017; 8:910. [PMID: 28855898 PMCID: PMC5557726 DOI: 10.3389/fimmu.2017.00910] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 07/17/2017] [Indexed: 12/15/2022] Open
Abstract
Recent advances in the next-generation sequencing of B-cell receptors (BCRs) enable the characterization of humoral responses at a repertoire-wide scale and provide the capability for identifying unique features of immune repertoires in response to disease, vaccination, or infection. Immunosequencing now readily generates 103–105 sequences per sample; however, statistical analysis of these repertoires is challenging because of the high genetic diversity of BCRs and the elaborate clonal relationships among them. To date, most immunosequencing analyses have focused on reporting qualitative trends in immunoglobulin (Ig) properties, such as usage or somatic hypermutation (SHM) percentage of the Ig heavy chain variable (IGHV) gene segment family, and on reducing complex Ig property distributions to simple summary statistics. However, because Ig properties are typically not normally distributed, any approach that fails to assess the distribution as a whole may be inadequate in (1) properly assessing the statistical significance of repertoire differences, (2) identifying how two repertoires differ, and (3) determining appropriate confidence intervals for assessing the size of the differences and their potential biological relevance. To address these issues, we have developed a technique that uses Wilcox’ robust statistics toolbox to identify statistically significant vaccine-specific differences between Ig repertoire properties. The advantage of this technique is that it can determine not only whether but also where the distributions differ, even when the Ig repertoire properties are non-normally distributed. We used this technique to characterize murine germinal center (GC) B-cell repertoires in response to a complex Ebola virus-like particle (eVLP) vaccine candidate with known protective efficacy. The eVLP-mediated GC B-cell responses were highly diverse, consisting of thousands of clonotypes. Despite this staggering diversity, we identified statistically significant differences between non-immunized, vaccine only, and vaccine-plus-adjuvant groups in terms of Ig properties, including IGHV-family usage, SHM percentage, and characteristics of the BCR complementarity-determining region. Most notably, our analyses identified a robust eVLP-specific feature—enhanced IGHV8-family usage in B-cell repertoires. These findings demonstrate the utility of our technique in identifying statistically significant BCR repertoire differences following vaccination. More generally, our approach is potentially applicable to a wide range of studies in infection, vaccination, auto-immunity, and cancer.
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Affiliation(s)
- Ilja V Khavrutskii
- Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI), Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Sidhartha Chaudhury
- Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI), Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Sabrina M Stronsky
- Molecular and Translational Sciences, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD, United States
| | - Donald W Lee
- Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI), Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Jacqueline G Benko
- Molecular and Translational Sciences, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD, United States
| | - Anders Wallqvist
- Department of Defense Biotechnology High Performance Computing Software Applications Institute (BHSAI), Telemedicine and Advanced Technology Research Center, United States Army Medical Research and Materiel Command, Fort Detrick, MD, United States
| | - Sina Bavari
- Molecular and Translational Sciences, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD, United States
| | - Christopher L Cooper
- Molecular and Translational Sciences, United States Army Medical Research Institute of Infectious Diseases (USAMRIID), Fort Detrick, MD, United States
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26
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Watson CT, Glanville J, Marasco WA. The Individual and Population Genetics of Antibody Immunity. Trends Immunol 2017; 38:459-470. [PMID: 28539189 PMCID: PMC5656258 DOI: 10.1016/j.it.2017.04.003] [Citation(s) in RCA: 79] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 04/06/2017] [Accepted: 04/10/2017] [Indexed: 12/12/2022]
Abstract
Antibodies (Abs) produced by immunoglobulin (IG) genes are the most diverse proteins expressed in humans. While part of this diversity is generated by recombination during B-cell development and mutations during affinity maturation, the germ-line IG loci are also diverse across human populations and ethnicities. Recently, proof-of-concept studies have demonstrated genotype–phenotype correlations between specific IG germ-line variants and the quality of Ab responses during vaccination and disease. However, the functional consequences of IG genetic variation in Ab function and immunological outcomes remain underexplored. In this opinion article, we outline interconnections between IG genomic diversity and Ab-expressed repertoires and structure. We further propose a strategy for integrating IG genotyping with functional Ab profiling data as a means to better predict and optimize humoral responses in genetically diverse human populations, with immediate implications for personalized medicine. Genetic variation in human populations affects how individuals are able to mount functional antibody responses. Different alleles can encode convergent binding motifs that result in successful Ab responses against specific infections and vaccinations. Given the complexity of the IG loci and the diversity of the antibody repertoire, links between IG polymorphism and antibody repertoire variability have not been thoroughly explored. We present a strategy to mine genotype–repertoire–disease associations.
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Affiliation(s)
- Corey T Watson
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, USA.
| | - Jacob Glanville
- Institute for Immunity, Transplantation and Infection, and Computational and Systems Immunology, Stanford University School of Medicine, Stanford, CA, USA.
| | - Wayne A Marasco
- Department of Cancer Immunology and Virology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA.
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27
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Systems Analysis Reveals High Genetic and Antigen-Driven Predetermination of Antibody Repertoires throughout B Cell Development. Cell Rep 2017; 19:1467-1478. [DOI: 10.1016/j.celrep.2017.04.054] [Citation(s) in RCA: 119] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 03/21/2017] [Accepted: 04/19/2017] [Indexed: 12/29/2022] Open
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28
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DeWitt WS, Lindau P, Snyder TM, Sherwood AM, Vignali M, Carlson CS, Greenberg PD, Duerkopp N, Emerson RO, Robins HS. A Public Database of Memory and Naive B-Cell Receptor Sequences. PLoS One 2016; 11:e0160853. [PMID: 27513338 PMCID: PMC4981401 DOI: 10.1371/journal.pone.0160853] [Citation(s) in RCA: 94] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 07/26/2016] [Indexed: 11/25/2022] Open
Abstract
The vast diversity of B-cell receptors (BCR) and secreted antibodies enables the recognition of, and response to, a wide range of epitopes, but this diversity has also limited our understanding of humoral immunity. We present a public database of more than 37 million unique BCR sequences from three healthy adult donors that is many fold deeper than any existing resource, together with a set of online tools designed to facilitate the visualization and analysis of the annotated data. We estimate the clonal diversity of the naive and memory B-cell repertoires of healthy individuals, and provide a set of examples that illustrate the utility of the database, including several views of the basic properties of immunoglobulin heavy chain sequences, such as rearrangement length, subunit usage, and somatic hypermutation positions and dynamics.
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Affiliation(s)
| | - Paul Lindau
- Fred Hutchinson Cancer Research Center, Seattle, United States of America
- University of Washington, Seattle, United States of America
| | | | | | | | | | | | - Natalie Duerkopp
- Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | | | - Harlan S. Robins
- Adaptive Biotechnologies, Seattle, United States of America
- Fred Hutchinson Cancer Research Center, Seattle, United States of America
- * E-mail:
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