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Zhu Y, Tang H, Xie W, Chen S, Zeng H, Lan C, Guan J, Ma C, Yang X, Wang Q, Wei L, Zhang Z, Yu X. The multilevel extensive diversity across the cynomolgus macaque captured by ultra-deep adaptive immune receptor repertoire sequencing. SCIENCE ADVANCES 2024; 10:eadj5640. [PMID: 38266093 PMCID: PMC10807814 DOI: 10.1126/sciadv.adj5640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 12/22/2023] [Indexed: 01/26/2024]
Abstract
The extent to which AIRRs differ among and within individuals remains elusive. Via ultra-deep repertoire sequencing of 22 and 25 tissues in three cynomolgus macaques, respectively, we identified 84 and 114 novel IGHV and TRBV alleles, confirming 72 (85.71%) and 100 (87.72%) of them. The heterogeneous V gene usage patterns were influenced, in turn, by genetics, isotype (for BCRs only), tissue group, and tissue. A higher proportion of intragroup shared clones in the intestinal tissues than those in other tissues suggests a close intra-intestinal adaptive immunity network. Significantly higher mutation burdens in the public clones and the inter-tissue shared IgM and IgD clones indicate that they might target the shared antigens. This study reveals the extensive heterogeneity of the AIRRs at various levels and has broad fundamental and clinical implications. The data generated here will serve as an invaluable resource for future studies on adaptive immunity in health and diseases.
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Affiliation(s)
- Yan Zhu
- Center for Precision Medicine, Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Haipei Tang
- Center for Precision Medicine, Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
| | - Wenxi Xie
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Sen Chen
- Center for Precision Medicine, Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Huikun Zeng
- Center for Precision Medicine, Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Division of Nephrology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Chunhong Lan
- Center for Precision Medicine, Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Junjie Guan
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Cuiyu Ma
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
| | - Xiujia Yang
- Center for Precision Medicine, Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
| | - Qilong Wang
- Center for Precision Medicine, Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
| | - Lai Wei
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510060, China
| | - Zhenhai Zhang
- Center for Precision Medicine, Medical Research Institute, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou 510515, China
| | - Xueqing Yu
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou 510080, China
- Division of Nephrology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
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2
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Feng F, Yuen R, Wang Y, Hua A, Kepler TB, Wetzler LM. Characterizing adjuvants' effects at murine immunoglobulin repertoire level. iScience 2024; 27:108749. [PMID: 38269092 PMCID: PMC10805652 DOI: 10.1016/j.isci.2023.108749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 09/29/2023] [Accepted: 12/12/2023] [Indexed: 01/26/2024] Open
Abstract
Generating large-scale, high-fidelity sequencing data is challenging and, furthermore, not much has been done to characterize adjuvants' effects at the repertoire level. Thus, we introduced an IgSeq pipeline that standardized library prep protocols and data analysis functions for accurate repertoire profiling. We then studied systemically effects of CpG and Alum on the Ig heavy chain repertoire using the ovalbumin (OVA) murine model. Ig repertoires of different tissues (spleen and bone marrow) and isotypes (IgG and IgM) were examined and compared in IGHV mutation, gene usage, CDR3 length, clonal diversity, and clonal selection. We found Ig repertoires of different compartments exhibited distinguishable profiles at the non-immunized steady state, and distinctions became more pronounced upon adjuvanted immunizations. Notably, Alum and CpG effects exhibited different tissue- and isotype-preferences. The former led to increased diversity of abundant clones in bone marrow, and the latter promoted the selection of IgG clones in both tissues.
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Affiliation(s)
- Feng Feng
- Department of Microbiology, Boston University, Boston, MA 02118, USA
| | - Rachel Yuen
- Department of Microbiology, Boston University, Boston, MA 02118, USA
| | - Yumei Wang
- Department of Microbiology, Boston University, Boston, MA 02118, USA
| | - Axin Hua
- Department of Microbiology, Boston University, Boston, MA 02118, USA
| | - Thomas B. Kepler
- Department of Microbiology, Boston University, Boston, MA 02118, USA
- Department of Mathematics and Statistics, Boston University, Boston, MA 02118, USA
| | - Lee M. Wetzler
- Department of Microbiology, Boston University, Boston, MA 02118, USA
- Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA 02118, USA
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3
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Olson BJ, Schattgen SA, Thomas PG, Bradley P, Matsen IV FA. Comparing T cell receptor repertoires using optimal transport. PLoS Comput Biol 2022; 18:e1010681. [PMID: 36476997 PMCID: PMC9728925 DOI: 10.1371/journal.pcbi.1010681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 10/24/2022] [Indexed: 12/12/2022] Open
Abstract
The complexity of entire T cell receptor (TCR) repertoires makes their comparison a difficult but important task. Current methods of TCR repertoire comparison can incur a high loss of distributional information by considering overly simplistic sequence- or repertoire-level characteristics. Optimal transport methods form a suitable approach for such comparison given some distance or metric between values in the sample space, with appealing theoretical and computational properties. In this paper we introduce a nonparametric approach to comparing empirical TCR repertoires that applies the Sinkhorn distance, a fast, contemporary optimal transport method, and a recently-created distance between TCRs called TCRdist. We show that our methods identify meaningful differences between samples from distinct TCR distributions for several case studies, and compete with more complicated methods despite minimal modeling assumptions and a simpler pipeline.
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Affiliation(s)
- Branden J. Olson
- Department of Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- Department of Statistics, University of Washington, Seattle, Washington, United States of America
| | - Stefan A. Schattgen
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, Tennessee, United States of America
| | - Paul G. Thomas
- Department of Immunology, St. Jude Children’s Research Hospital, Memphis, Tennessee, United States of America
| | - Philip Bradley
- Department of Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- Institute for Protein Design, Department of Biochemistry, University of Washington, Seattle, Washington, United States of America
- * E-mail: (PB); (FAM)
| | - Frederick A. Matsen IV
- Department of Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- Department of Statistics, University of Washington, Seattle, Washington, United States of America
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
- Howard Hughes Medical Institute, Seattle, Washington, United States of America
- * E-mail: (PB); (FAM)
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4
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Tang Q, Leung J, Peng Y, Sanchez-Fueyo A, Lozano JJ, Lam A, Lee K, Greenland JR, Hellerstein M, Fitch M, Li KW, Esensten JH, Putnam AL, Lares A, Nguyen V, Liu W, Bridges ND, Odim J, Demetris AJ, Levitsky J, Taner T, Feng S. Selective decrease of donor-reactive T regs after liver transplantation limits T reg therapy for promoting allograft tolerance in humans. Sci Transl Med 2022; 14:eabo2628. [PMID: 36322627 PMCID: PMC11016119 DOI: 10.1126/scitranslmed.abo2628] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2024]
Abstract
Promoting immune tolerance to transplanted organs can minimize the amount of immunosuppressive drugs that patients need to take, reducing lifetime risks of mortality and morbidity. Regulatory T cells (Tregs) are essential for immune tolerance, and preclinical studies have shown their therapeutic efficacy in inducing transplantation tolerance. Here, we report the results of a phase 1/2 trial (ARTEMIS, NCT02474199) of autologous donor alloantigen-reactive Treg (darTreg) therapy in individuals 2 to 6 years after receiving a living donor liver transplant. The primary efficacy endpoint was calcineurin inhibitor dose reduction by 75% with stable liver function tests for at least 12 weeks. Among 10 individuals who initiated immunosuppression withdrawal, 1 experienced rejection before planned darTreg infusion, 5 received darTregs, and 4 were not infused because of failure to manufacture the minimal infusible dose of 100 × 106 cells. darTreg infusion was not associated with adverse events. Two darTreg-infused participants reached the primary endpoint, but an insufficient number of recipients were treated for assessing the efficacy of darTregs. Mechanistic studies revealed generalized Treg activation, senescence, and selective reduction of donor reactivity after liver transplantation. Overall, the ARTEMIS trial features a design concept for evaluating the efficacy of Treg therapy in transplantation. The mechanistic insight gained from the study may help guide the design of future trials.
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Affiliation(s)
- Qizhi Tang
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
- Diabetes Center, University of California, San Francisco, San Francisco, CA 94143, USA
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA 94158, USA
| | - Joey Leung
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Yani Peng
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Alberto Sanchez-Fueyo
- Institute of Liver Studies, School of Immunology and Microbial Sciences, King’s College London University, London WC2R 2LS, UK
| | - Juan-Jose Lozano
- Bioinformatic Platform, Biomedical Research Center in Hepatic and Digestive Diseases, Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Alice Lam
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Karim Lee
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - John R. Greenland
- Department of Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
- Medical Service, San Francisco VA Health Care System, San Francisco, CA 94121, USA
| | - Marc Hellerstein
- Nutrition Sciences and Toxicology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Mark Fitch
- Nutrition Sciences and Toxicology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Kelvin W. Li
- Nutrition Sciences and Toxicology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Jonathan H. Esensten
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA 94158, USA
- Department of Lab Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Amy L. Putnam
- Diabetes Center, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Angela Lares
- Diabetes Center, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Vinh Nguyen
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Weihong Liu
- Diabetes Center, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Nancy D. Bridges
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20852, USA
| | - Jonah Odim
- National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20852, USA
| | - Anthony J. Demetris
- Thomas E. Starzl Transplantation Institute and Department of Pathology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Josh Levitsky
- Department of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Timucin Taner
- Departments of Surgery and Immunology, Mayo Clinic, Rochester, MN 55905, USA
| | - Sandy Feng
- Department of Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
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Jaffe DB, Shahi P, Adams BA, Chrisman AM, Finnegan PM, Raman N, Royall AE, Tsai F, Vollbrecht T, Reyes DS, Hepler NL, McDonnell WJ. Functional antibodies exhibit light chain coherence. Nature 2022; 611:352-357. [PMID: 36289331 PMCID: PMC9607724 DOI: 10.1038/s41586-022-05371-z] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 09/21/2022] [Indexed: 11/08/2022]
Abstract
The vertebrate adaptive immune system modifies the genome of individual B cells to encode antibodies that bind particular antigens1. In most mammals, antibodies are composed of heavy and light chains that are generated sequentially by recombination of V, D (for heavy chains), J and C gene segments. Each chain contains three complementarity-determining regions (CDR1-CDR3), which contribute to antigen specificity. Certain heavy and light chains are preferred for particular antigens2-22. Here we consider pairs of B cells that share the same heavy chain V gene and CDRH3 amino acid sequence and were isolated from different donors, also known as public clonotypes23,24. We show that for naive antibodies (those not yet adapted to antigens), the probability that they use the same light chain V gene is around 10%, whereas for memory (functional) antibodies, it is around 80%, even if only one cell per clonotype is used. This property of functional antibodies is a phenomenon that we call light chain coherence. We also observe this phenomenon when similar heavy chains recur within a donor. Thus, although naive antibodies seem to recur by chance, the recurrence of functional antibodies reveals surprising constraint and determinism in the processes of V(D)J recombination and immune selection. For most functional antibodies, the heavy chain determines the light chain.
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Wu TH, Liao HT, Li TH, Tsai HC, Lin NC, Chen CY, Tsai SF, Huang TH, Tsai CY, Yu CL. High-Throughput Sequencing of Complementarity Determining Region 3 in the Heavy Chain of B-Cell Receptor in Renal Transplant Recipients: A Preliminary Report. J Clin Med 2022; 11:jcm11112980. [PMID: 35683373 PMCID: PMC9181060 DOI: 10.3390/jcm11112980] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 05/01/2022] [Accepted: 05/23/2022] [Indexed: 01/27/2023] Open
Abstract
Background: Graft failure resulting from rejection or any other adverse event usually originates from an aberrant and/or exaggerated immune response and is often catastrophic in renal transplantation. So, it is essential to monitor patients’ immune status for detecting a rejection/graft failure early on. Methods: We monitored the sequence change of complementary determining region 3 (CDR3) in B-cell receptor (BCR) immunoglobulin heavy-chain (IGH) immune repertoire (iR) in 14 renal transplant patients using next-generation sequencing (NGS), correlating its diversity to various clinical events occurring after transplantation. BCR-IGH-CDR3 in peripheral blood mononuclear cells was sequenced along the post-transplantation course by NGS using the iRweb server. Results: Datasets covering VDJ regions of BCR-IGH-CDR3 indicated clonal diversity (D50) variations along the post-transplant course. Furthermore, principal component analysis showed the clustering of these sequence variations. A total of 544 shared sequences were identified before transplantation. D50 remained low in three patients receiving rituximab. Among them, one’s D50 resumed after 3 m, indicating graft tolerance. The D50 rapidly increased after grafting and decreased thereafter in four patients without rejection, decreased in two patients with T-cell-mediated rejection (TCMR) and exhibited a sharp down-sliding after 3 m in two patients receiving donations after cardiac death (DCD). In another two patients with TCMR, D50 was low just before individual episodes, but either became persistently low or returned to a plateau, depending on the failure or success of the immunosuppressive treatments. Shared CDR3 clonal expansions correlated to D50 changes. Agglomerative hierarchical clustering showed a commonly shared CDR3 sequence and at least two different clusters in five patients. Conclusions: Clonal diversity in BCR-IGH-CDR3 varied depending on clinical courses of 14 renal transplant patients, including B-cell suppression therapy, TCMR, DCD, and graft tolerance. Adverse events on renal graft failure might lead to different clustering of BCR iR. However, these preliminary data need further verification in further studies for the possible applications of iR changes as genetic expression biomarkers or laboratory parameters to detect renal graft failure/rejection earlier.
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Affiliation(s)
- Tsai-Hung Wu
- Division of Nephrology, Taipei Veterans General Hospital, Taipei 11217, Taiwan;
| | - Hsien-Tzung Liao
- Division of Allergy, Immunology & Rheumatology, Taipei Veterans General Hospital, Taipei 11217, Taiwan; (H.-T.L.); (H.-C.T.)
| | - Tzu-Hao Li
- Division of Immunology & Rheumatology, Shin Kong Wu Ho Su Memorial Hospital, Taipei 11101, Taiwan;
| | - Hung-Cheng Tsai
- Division of Allergy, Immunology & Rheumatology, Taipei Veterans General Hospital, Taipei 11217, Taiwan; (H.-T.L.); (H.-C.T.)
| | - Niang-Cheng Lin
- Division of Transplantation Surgery, Taipei Veterans General Hospital, Taipei 11217, Taiwan; (N.-C.L.); (C.-Y.C.)
| | - Cheng-Yen Chen
- Division of Transplantation Surgery, Taipei Veterans General Hospital, Taipei 11217, Taiwan; (N.-C.L.); (C.-Y.C.)
| | - Shih-Feng Tsai
- Institute of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan 35053, Taiwan;
| | - Tzu-Hao Huang
- Department of Urology, Taipei Veterans General Hospital, Taipei 11217, Taiwan;
| | - Chang-Youh Tsai
- Division of Allergy, Immunology & Rheumatology, Fu Jen Catholic University Hospital, New Taipei City 24352, Taiwan
- Correspondence: or (C.-Y.T.); (C.-L.Y.)
| | - Chia-Li Yu
- Department of Internal Medicine, National Taiwan University Hospital, Taipei 100225, Taiwan
- Correspondence: or (C.-Y.T.); (C.-L.Y.)
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Analysis of B cell receptor repertoires reveals key signatures of systemic B cell response after SARS-CoV-2 infection. J Virol 2021; 96:e0160021. [PMID: 34878902 PMCID: PMC8865482 DOI: 10.1128/jvi.01600-21] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
A comprehensive study of the B cell response against SARS-CoV-2 could be significant for understanding the immune response and developing therapeutical antibodies and vaccines. To define the dynamics and characteristics of the antibody repertoire following SARS-CoV-2 infection, we analyzed the mRNA transcripts of immunoglobulin heavy chain (IgH) repertoires of 24 peripheral blood samples collected between 3 and 111 days after symptom onset from 10 COVID-19 patients. Massive clonal expansion of naive B cells with limited somatic hypermutation (SHM) was observed in the second week after symptom onset. The proportion of low-SHM IgG clones strongly correlated with spike-specific IgG antibody titers, highlighting the significant activation of naive B cells in response to a novel virus infection. The antibody isotype switching landscape showed a transient IgA surge in the first week after symptom onset, followed by a sustained IgG elevation that lasted for at least 3 months. SARS-CoV-2 infection elicited poly-germ line reactive antibody responses. Interestingly, 17 different IGHV germ line genes recombined with IGHJ6 showed significant clonal expansion. By comparing the IgH repertoires that we sequenced with the 774 reported SARS-CoV-2–reactive monoclonal antibodies (MAbs), 13 shared spike-specific IgH clusters were found. These shared spike-specific IgH clusters are derived from the same lineage of several recently published neutralizing MAbs, including CC12.1, CC12.3, C102, REGN10977, and 4A8. Furthermore, identical spike-specific IgH sequences were found in different COVID-19 patients, suggesting a highly convergent antibody response to SARS-CoV-2. Our analysis based on sequencing antibody repertoires from different individuals revealed key signatures of the systemic B cell response induced by SARS-CoV-2 infection. IMPORTANCE Although the canonical delineation of serum antibody responses following SARS-CoV-2 infection has been well established, the dynamics of antibody repertoire at the mRNA transcriptional level has not been well understood, especially the correlation between serum antibody titers and the antibody mRNA transcripts. In this study, we analyzed the IgH transcripts and characterized the B cell clonal expansion and differentiation, isotype switching, and somatic hypermutation in COVID-19 patients. This study provided insights at the repertoire level for the B cell response after SARS-CoV-2 infection.
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Braddom AE, Bol S, Gonzales SJ, Reyes RA, Musinguzi K, Nankya F, Ssewanyana I, Greenhouse B, Bunnik EM. B Cell Receptor Repertoire Analysis in Malaria-Naive and Malaria-Experienced Individuals Reveals Unique Characteristics of Atypical Memory B Cells. mSphere 2021; 6:e0072621. [PMID: 34523978 PMCID: PMC8550134 DOI: 10.1128/msphere.00726-21] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 08/31/2021] [Indexed: 11/24/2022] Open
Abstract
Malaria, caused by parasites of the Plasmodium genus, is responsible for significant morbidity and mortality globally. Chronic Plasmodium falciparum exposure affects the B cell compartment, leading to the accumulation of atypical memory B cells (atMBCs). IgM-positive (IgM+) and IgG+ atMBCs have not been compared in-depth in the context of malaria, nor is it known if atMBCs in malaria-experienced individuals are different from phenotypically similar B cells in individuals with no known history of Plasmodium exposure. To address these questions, we characterized the B cell receptor (BCR) repertoire of naive B cells (NBCs), IgM+ and IgG+ classical MBCs (cMBCs), and IgM+ and IgG+ atMBCs from 13 malaria-naive American adults and 7 malaria-experienced Ugandan adults. Our results demonstrate that P. falciparum exposure mainly drives changes in atMBCs. In comparison to malaria-naive adults, the BCR repertoire of Plasmodium-exposed adults showed increased levels of somatic hypermutation in the heavy chain V region in IgM+ and IgG+ atMBCs, shorter heavy chain complementarity-determining region 3 (HCDR3) in IgG+ atMBCs, and increased usage of IGHV3-73 in IgG+ cMBCs and both IgM+ and IgG+ atMBCs. Irrespective of Plasmodium exposure, IgM+ atMBCs closely resembled NBCs, while IgG+ atMBCs resembled IgG+ cMBCs. Physicochemical properties of the HCDR3 seemed to be intrinsic to cell type and independent of malaria experience. The resemblance between atMBCs from Plasmodium-exposed and naive adults suggests similar differentiation pathways regardless of chronic antigen exposure. Moreover, these data demonstrate that IgM+ and IgG+ atMBCs are distinct populations that should be considered separately in future analyses. IMPORTANCE Malaria, caused by Plasmodium parasites, still contributes to a high global burden of disease, mainly in children under 5 years of age. Chronic and recurrent Plasmodium infections affect the development of B cell memory against the parasite and promote the accumulation of atypical memory B cells (atMBCs), which have an unclear function in the immune response. Understanding where these cells originate from and whether they are beneficial in the immune response to Plasmodium will help inform vaccination development efforts. We found differences in B cell receptor (BCR) properties of atMBCs between malaria-naive and malaria-experienced adults that are suggestive of divergent selection processes, resulting in more somatic hypermutation and differential immunoglobulin heavy chain V (IGHV) gene usage. Despite these differences, atMBCs from malaria-naive and malaria-experienced adults also showed many similarities in BCR characteristics, such as physicochemical properties of the HCDR3 region, suggesting that atMBCs undergo similar differentiation pathways in response to different pathogens. Our study provides new insights into the effects of malaria experience on the B cell compartment and the relationships between atMBCs and other B cell populations.
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Affiliation(s)
- Ashley E. Braddom
- Department of Microbiology, Immunology and Molecular Genetics, Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Sebastiaan Bol
- Department of Microbiology, Immunology and Molecular Genetics, Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - S. Jake Gonzales
- Department of Microbiology, Immunology and Molecular Genetics, Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | - Raphael A. Reyes
- Department of Microbiology, Immunology and Molecular Genetics, Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
| | | | | | - Isaac Ssewanyana
- Infectious Disease Research Collaboration, Kampala, Uganda
- London School of Hygiene and Tropical Medicine, London, UK
| | - Bryan Greenhouse
- Department of Medicine, University of California San Francisco, San Francisco, California, USA
| | - Evelien M. Bunnik
- Department of Microbiology, Immunology and Molecular Genetics, Long School of Medicine, The University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
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9
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Li Y, Wang J, Wu L, Li X, Zhang X, Zhang G, Xu S, Sun S, Jiao S. Diversity of Dominant Peripheral T Cell Receptor Clone and Soluble Immune Checkpoint Proteins Associated With Clinical Outcomes Following Immune Checkpoint Inhibitor Treatment in Advanced Cancers. Front Immunol 2021; 12:649343. [PMID: 34163469 PMCID: PMC8216394 DOI: 10.3389/fimmu.2021.649343] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 04/13/2021] [Indexed: 11/13/2022] Open
Abstract
Dynamic changes of the peripheral T cell receptor (TCR) and soluble receptors and ligands (sRLs) have the potential to be used as biomarkers to monitor the evolution of the immune system in tumor patients undergoing immunotherapy. These functional biomarkers could be used to predict immune response to treatment with immune checkpoint inhibitors (ICIs) and to provide high-value information on the immune function status of cancer patients, thereby helping physicians to make effective clinical decisions. We collected paired pre- and post-treatment peripheral blood samples from 31 solid tumor patients treated with ICIs. TCR and sRL status were investigated using next-generation sequencing and magnetic bead panels. We found that the diversity of the dominant TCR clone at baseline was correlated with durable clinical benefit in patients receiving single-agent treatment. The D50 index, the diversity from the cumulative 50% of the total complementary determinant region 3, was obtained during treatment. A significant difference in progression-free survival was demonstrated between the D50 high and D50 low groups. This result was validated in an independent cohort. A signature including soluble immune checkpoint proteins (sICPs) was identified. Upregulation of the signature during treatment was correlated with durable clinical benefit. All these results indicate that a novel biomarker based on peripheral TCR and sICPs has the potential to be used in prognostic prediction and for rapid determination of therapeutic outcomes in patients treated with immune checkpoint inhibitors.
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Affiliation(s)
- Ye Li
- Department of Radiotherapy, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Oncology Laboratory, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Medical School of Chinese PLA, Beijing, China
| | - Jiaqian Wang
- YuceBio, Shenzhen, China
- YutaiAntigen, Shenzhen, China
| | - Liangliang Wu
- Oncology Laboratory, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiaoting Li
- YuceBio, Shenzhen, China
- YutaiAntigen, Shenzhen, China
| | - Xiaoyun Zhang
- Oncology Laboratory, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Guoqing Zhang
- Department of Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Shengqiang Xu
- YuceBio, Shenzhen, China
- YutaiAntigen, Shenzhen, China
| | - Shengjie Sun
- Department of Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Shunchang Jiao
- Oncology Laboratory, First Medical Center of Chinese PLA General Hospital, Beijing, China
- Department of Oncology, First Medical Center of Chinese PLA General Hospital, Beijing, China
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10
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Liu WJ, Xiao H, Dai L, Liu D, Chen J, Qi X, Bi Y, Shi Y, Gao GF, Liu Y. Avian influenza A (H7N9) virus: from low pathogenic to highly pathogenic. Front Med 2021; 15:507-527. [PMID: 33860875 PMCID: PMC8190734 DOI: 10.1007/s11684-020-0814-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Accepted: 07/08/2020] [Indexed: 12/13/2022]
Abstract
The avian influenza A (H7N9) virus is a zoonotic virus that is closely associated with live poultry markets. It has caused infections in humans in China since 2013. Five waves of the H7N9 influenza epidemic occurred in China between March 2013 and September 2017. H7N9 with low-pathogenicity dominated in the first four waves, whereas highly pathogenic H7N9 influenza emerged in poultry and spread to humans during the fifth wave, causing wide concern. Specialists and officials from China and other countries responded quickly, controlled the epidemic well thus far, and characterized the virus by using new technologies and surveillance tools that were made possible by their preparedness efforts. Here, we review the characteristics of the H7N9 viruses that were identified while controlling the spread of the disease. It was summarized and discussed from the perspectives of molecular epidemiology, clinical features, virulence and pathogenesis, receptor binding, T-cell responses, monoclonal antibody development, vaccine development, and disease burden. These data provide tools for minimizing the future threat of H7N9 and other emerging and re-emerging viruses, such as SARS-CoV-2.
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Affiliation(s)
- William J Liu
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Third People's Hospital, Shenzhen, 518114, China.
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China.
| | - Haixia Xiao
- Laboratory of Protein Engineering and Vaccines, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences (CAS), Tianjin, 300308, China
| | - Lianpan Dai
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Di Liu
- CAS Key Laboratory of Special Pathogens and Biosafety, Chinese Academy of Sciences, Wuhan, 430071, China
- National Virus Resource Center, Chinese Academy of Sciences, Wuhan, 430071, China
- University of Chinese Academy Sciences, Beijing, 100049, China
- Center for Influenza Research and Early Warning, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jianjun Chen
- CAS Key Laboratory of Special Pathogens and Biosafety, Chinese Academy of Sciences, Wuhan, 430071, China
- National Virus Resource Center, Chinese Academy of Sciences, Wuhan, 430071, China
- University of Chinese Academy Sciences, Beijing, 100049, China
- Center for Influenza Research and Early Warning, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xiaopeng Qi
- Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Yuhai Bi
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Third People's Hospital, Shenzhen, 518114, China
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy Sciences, Beijing, 100049, China
- Center for Influenza Research and Early Warning, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yi Shi
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Third People's Hospital, Shenzhen, 518114, China
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy Sciences, Beijing, 100049, China
- Center for Influenza Research and Early Warning, Chinese Academy of Sciences, Beijing, 100101, China
| | - George F Gao
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 102206, China
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
- Chinese Center for Disease Control and Prevention, Beijing, 102206, China
| | - Yingxia Liu
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Third People's Hospital, Shenzhen, 518114, China.
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11
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Recapitulation of posttransfusion purpura by cross-strain platelet immunization in mice. Blood Adv 2021; 4:287-295. [PMID: 31968077 DOI: 10.1182/bloodadvances.2019000661] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Accepted: 12/13/2019] [Indexed: 02/07/2023] Open
Abstract
Posttransfusion purpura (PTP) is an uncommon but life-threatening condition characterized by profound thrombocytopenia occurring ∼1 week after a blood transfusion. The hallmark of PTP is a potent immunoglobulin G antibody specific for a transfused platelet-specific alloantigen, usually located on glycoprotein IIb/IIIa (GPIIb/IIIa; αIIb/β3 integrin). It is widely thought that this alloantibody somehow causes the thrombocytopenia, despite absence from host platelets of the alloantigen for which it is specific. In studies described here, we found that cross-strain platelet immunization in mice commonly induces GPIIb/IIIa-specific alloantibodies combined with platelet-specific autoantibodies and varying degrees of thrombocytopenia, and we identified 1 strain combination (129S1Svlm/PWKPhJ) in which 95% of immunized mice made both types of antibody and developed severe thrombocytopenia. There was a strong inverse correlation between autoantibody strength and platelet decline (P < .0001) and plasma from mice that produced autoantibodies caused thrombocytopenia when transfused to syngeneic animals, arguing that autoantibodies were the cause of thrombocytopenia. The findings define a model in which a routine alloimmune response to platelets regularly transitions to an autoimmune reaction capable of causing severe thrombocytopenia and support the hypothesis that PTP is an autoimmune disorder.
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12
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Zhang X, Zeng J, Tong Y, Zhang L, Lu X, Zhu S, Li Z. CDR3 sequences in IgA nephropathy are shorter and exhibit reduced diversity. FEBS Open Bio 2020; 10:2702-2711. [PMID: 33067920 PMCID: PMC7714077 DOI: 10.1002/2211-5463.13006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 09/20/2020] [Accepted: 10/15/2020] [Indexed: 11/10/2022] Open
Abstract
Immunoglobulin (Ig) A nephropathy (IgAN) is the most common glomerulonephritis, which is characterized by the deposition of IgA antibody in the glomerulus. Systematic dissection of immune composition may contribute to a better understanding of the alternations in the immune system in IgAN. To this end, here we applied immune repertoire sequencing technology for parallel analysis of the complementary determining region 3 (CDR3) of all B cell receptors, including all five antibody subtypes (IgA, IgG, IgM, IgE and IgD), in 13 patients with IgAN and 7 healthy individuals. A significant decrease in CDR3 length was observed in the IgAN group. In particular, the JH6 family was significantly increased in IgAN. Amino acid usage was also altered in IgAN. Shannon, Simpson, Gini and Diversity 50 indices also revealed significant differences in the diversity of IgG, IgM and IgA antibodies as compared with controls. The proportions of IgA and IgG were increased, whereas IgM was decreased in IgAN. Moreover, a greater number of CDR3 sequences was shared between patients with IgAN. These findings suggest that the BCR immune repertoire is dramatically altered in IgAN, as characterized by shortened CDR3 length, as well as decreased overall diversity of CDR3.
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Affiliation(s)
- Xi Zhang
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.,Core Research Facilities, Southern University of Science and Technology, Shenzhen, China
| | - Jianming Zeng
- Faculty of Health Sciences, University of Macau, Macau, China
| | - Yin Tong
- Cancer Informatics and System Biology Lab, The University of Hong Kong, Hong Kong, China
| | - Li Zhang
- MD Anderson Cancer Center, Houston, TX, USA
| | - Xibin Lu
- Core Research Facilities, Southern University of Science and Technology, Shenzhen, China
| | - Shenglang Zhu
- Department of Nephrology, The 6th Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, China
| | - Zhoufang Li
- Core Research Facilities, Southern University of Science and Technology, Shenzhen, China
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13
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Genomic profiling of intestinal T-cell receptor repertoires in inflammatory bowel disease. Genes Immun 2020; 21:109-118. [PMID: 32029881 DOI: 10.1038/s41435-020-0092-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 01/11/2020] [Accepted: 01/21/2020] [Indexed: 12/11/2022]
Abstract
Growing evidence shows that inflammatory bowel disease (IBD) results from dysregulation of immune responses to gut microbes. T-cell receptors (TCRs) expressed on the T-cell surface play critical roles in discriminating pathogens from commensal intestinal microorganisms at the front line of the adaptive immune system. The breakdown of this interaction may trigger persistent inflammatory responses to gut bacteria, resulting in IBD. Taking advantage of high-throughput sequencing, we developed an integrated approach to dissect the intestinal TCR repertoires underlying IBD by collecting peripheral blood and inflamed intestine from the same set of 11 IBD cases. The intestinal TCR repertoires show lower clonotype diversity (p < 0.05) and stronger clonal expansion (p < 0.02) than those in the blood. This pattern becomes more profound in TCRs unique to the inflamed tissue compared with shared TCRs. Our approach further identified the increased usage of TRAV12-3 (false discovery rate, FDR < 5%), which biases its choices of J genes towards the reduction of TRAJ37 and TRAJ43 usage (FDR < 20%) in the inflamed intestine. Our genomic profiling suggests that this selective bias of V and J gene usage may lead to a loss of diversity in the intestinal TCR repertoires and result in mucosal inflammation in IBD.
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14
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Niu X, Yan Q, Yao Z, Zhang F, Qu L, Wang C, Wang C, Lei H, Chen C, Liang R, Luo J, Wang Q, Zhao L, Zhang Y, Luo K, Wang L, Wu H, Liu T, Li P, Zheng Z, Tan YJ, Feng L, Zhang Z, Han J, Zhang F, Chen L. Longitudinal analysis of the antibody repertoire of a Zika virus-infected patient revealed dynamic changes in antibody response. Emerg Microbes Infect 2020; 9:111-123. [PMID: 31906823 PMCID: PMC6968589 DOI: 10.1080/22221751.2019.1701953] [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] [Indexed: 12/16/2022]
Abstract
The Zika virus (ZIKV) is a mosquito-borne flavivirus that causes neonatal abnormalities and other disorders. Antibodies to the ZIKV envelope (E) protein can block infection. In this study, next-generation sequencing (NGS) of immunoglobulin heavy chain (IgH) mRNA transcripts was combined with single-cell PCR cloning of E-binding monoclonal antibodies for analysing antibody response in a patient from the early stages of infection to more than one year after the clearance of the virus. The patient's IgH repertoire 14 and 64 days after symptom onset showed dramatic dominant clonal expansion but low clonal diversity. IgH repertoire 6 months after disease-free status had few dominant clones but increased diversity. E-binding antibodies appeared abundantly in the repertoire during the early stages of infection but quickly declined after clearance of the virus. Certain VH genes such as VH5-10-1 and VH4-39 appeared to be preferentially enlisted for a rapid antibody response to ZIKV infection. Most of these antibodies require relatively few somatic hypermutations to acquire the ability to bind to the E protein, pointing to a possible mechanism for rapid defence against ZIKV infection. This study provides a unique and holistic view of the dynamic changes and characteristics of the antibody response to ZIKV infection.
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Affiliation(s)
- Xuefeng Niu
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China
| | - Qihong Yan
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China.,University of Chinese Academy of Science, Beijing, People's Republic of China
| | - Zhipeng Yao
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China.,Institute of Physical Science and Information Technology, Anhui University, Hefei, People's Republic of China
| | - Fan Zhang
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China.,Institute of Physical Science and Information Technology, Anhui University, Hefei, People's Republic of China
| | - Linbing Qu
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China
| | - Chunlin Wang
- HudsonAlpha Institute of Biotechnology, Huntsville, AL, USA
| | - Chengrui Wang
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China
| | - Hui Lei
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China
| | - Chaoming Chen
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China
| | - Renshan Liang
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China
| | - Jia Luo
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China
| | - Qian Wang
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China.,University of Chinese Academy of Science, Beijing, People's Republic of China
| | - Lingzhai Zhao
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, People's Republic of China
| | - Yudi Zhang
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China.,University of Chinese Academy of Science, Beijing, People's Republic of China
| | - Kun Luo
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China.,University of Chinese Academy of Science, Beijing, People's Republic of China
| | - Longyu Wang
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China.,Institute of Physical Science and Information Technology, Anhui University, Hefei, People's Republic of China
| | - Hongkai Wu
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China
| | - Tingting Liu
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China
| | - Pingchao Li
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China
| | - Zhiqiang Zheng
- Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University Health System (NUHS), National University of Singapore, Singapore, Singapore
| | - Yee Joo Tan
- Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University Health System (NUHS), National University of Singapore, Singapore, Singapore
| | - Liqiang Feng
- Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China
| | - Zhenhai Zhang
- Department of Cardiology, State Key Laboratory of Organ Failure Research, Nanfang Hospital, Southern Medical University, Guangzhou, People's Republic of China
| | - Jian Han
- HudsonAlpha Institute of Biotechnology, Huntsville, AL, USA
| | - Fuchun Zhang
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, People's Republic of China
| | - Ling Chen
- State Key Laboratory of Respiratory Disease, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People's Republic of China.,Guangdong Laboratory of Computational Biomedicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China
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15
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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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16
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Liu J, Liu Z, Zhu Y, Dong B, Cai Z, Liang Q, Wang K. T Cell Receptor Immune Repertoires Are Promptly Reconstituted After Methicillin-Resistant Staphylococcus aureus Infection. Front Microbiol 2019; 10:2012. [PMID: 31543872 PMCID: PMC6730595 DOI: 10.3389/fmicb.2019.02012] [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: 05/11/2019] [Accepted: 08/16/2019] [Indexed: 12/28/2022] Open
Abstract
T cells represent a subset of lymphocytes characterized by immunosurveillance and immunoregulation function. Peripheral blood mononuclear cells (PBMCs) are enriched in T cells, which exert critical antimicrobial roles in infectious diseases. High-throughput sequencing of the T cell receptor (TCR) provides deep insight into monitoring the immune microenvironment. Flow cytometry was used to analyse the distribution of αβ/γδ T cells and their CD69, IFN-γ/IL-17 expression from PBMCs. Here, we utilized next-generation sequencing (NGS) to detect the complementarity determining region 3 (CDR3) of TCRβ (TRB) and TCRδ (TRD) chain after methicillin-resistant Staphylococcus aureus (MRSA) infection. Our data demonstrated a significant increase in the activation of αβ and γδ T cells after MRSA infection. Simultaneously, significantly high CDR3 amino acid (AA) diversity and markedly reconstituted TCR immune repertoires were observed after MRSA infection. Finally, we identified several MRSA-specific initial CDR3 AA motifs after MRSA infection. Our work reveals the profiles of TRB and TRD immune repertoires in response to MRSA and demonstrates a reconstitution of the TCR immune repertoire after MRSA infection.
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Affiliation(s)
- Jiangjun Liu
- Department of Basic Medical Sciences, School of Medicine, Xiamen University, Xiamen, China.,Department of Orthopedic Surgery, Qilu Hospital of Shandong University, Shandong, China
| | - Zhongqiang Liu
- Department of Clinical Laboratory, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China
| | - Yuanqi Zhu
- Department of Clinical Laboratory, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China
| | - Bingzi Dong
- Department of Endocrinology and Metabolism, The Affiliated Hospital of Qingdao University, Qingdao University, Qingdao, China
| | - Zheng Cai
- Department of Pharmaceutics, Changhai Hospital, Second Military Medical University, Shanghai, China
| | - Qing Liang
- Department of Basic Medical Sciences, School of Medicine, Xiamen University, Xiamen, China
| | - Kejia Wang
- Department of Basic Medical Sciences, School of Medicine, Xiamen University, Xiamen, China
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17
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Li X, Zhang W, Huang M, Ren Z, Nie C, Liu X, Yang S, Zhang X, Yang N. Selection of potential cytokeratin-18 monoclonal antibodies following IGH repertoire evaluation in mice. J Immunol Methods 2019; 474:112647. [PMID: 31421082 DOI: 10.1016/j.jim.2019.112647] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 07/12/2019] [Accepted: 08/13/2019] [Indexed: 12/12/2022]
Abstract
Cytokeratin 18 (CK18), the main scaffold protein of keratinocyte, is distributed in epithelial cells. This structural protein maintains the integrity and continuity of epithelial tissue. Cytokeratin is also frequently used as an immunohistochemical marker of tumor growth. In recent years, immune repertoire (IR) evaluation using next-generation sequencing (NGS) have become increasingly efficient. Here we deep sequenced the mouse IR of the immunoglobulin heavy chain (IGH) after CK18 immunization. We comprehensively analyzed the IR based on complementarity determining region 3 (CDR3) abundance, germline gene usage polarization, clone diversity, and lineage. We found many convergence characteristics after CK18 immunization. Convergence represents a phenomenon that antigen stimulation or pathogen exposure induces the antigen specific clone expansion and enrichment. The convergence could be used for the immune evaluation and antibody screen. After immunization, the IGHV5 gene clusters became preponderant. The abundance and length of the most frequent CDR3 both increased, nevertheless the IR diversity level decreased. From the convergent IGH repertoires, we selected and expressed six antibodies with the most frequent CDR3s and IGH V-J combinations. The ELISA results suggested all screened six antibodies bound CK18 specifically. The most potential antibody had 9.424E-10M M affinity for the interaction with the CK18. Therefore, this is the NGS platform has been first used for anti-CK18 monoclonal antibodies (MAbs) discovery. These analyses methods could also be used for vaccine evaluation.
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Affiliation(s)
- Xinyang Li
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Wei Zhang
- BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Mi Huang
- BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Zhe Ren
- BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Chao Nie
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Xiao Liu
- BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Shuang Yang
- BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Xiuqing Zhang
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen 518083, China; BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Naibo Yang
- BGI-Shenzhen, Shenzhen 518083, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China; Complete Genomics, Inc., 2904 Orchard Parkway, San Jose, CA 95134, USA.
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18
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Kirpach J, Colone A, Bürckert JP, Faison WJ, Dubois ARSX, Sinner R, Reye AL, Muller CP. Detection of a Low Level and Heterogeneous B Cell Immune Response in Peripheral Blood of Acute Borreliosis Patients With High Throughput Sequencing. Front Immunol 2019; 10:1105. [PMID: 31156648 PMCID: PMC6532064 DOI: 10.3389/fimmu.2019.01105] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Accepted: 04/30/2019] [Indexed: 01/08/2023] Open
Abstract
The molecular diagnosis of acute Borreliosis is complicated and better strategies to improve the diagnostic processes are warranted. High Throughput Sequencing (HTS) of human B cell repertoires after e.g., Dengue virus infection or influenza vaccination revealed antigen-associated “CDR3 signatures” which may have the potential to support diagnosis in infectious diseases. The human B cell immune response to Borrelia burgdorferi sensu lato—the causative agent of Borreliosis—has mainly been studied at the antibody level, while less attention has been given to the cellular part of the humoral immune response. There are indications that Borrelia actively influence the B cell immune response and that it is therefore not directly comparable to responses induced by other infections. The main goal of this study was to identify B cell features that could be used to support diagnosis of Borreliosis. Therefore, we characterized the B cell immune response in these patients by combining multicolor flow cytometry, single Borrelia-reactive B cell receptor (BCR) sequencing, and B cell repertoire deep sequencing. Our phenotyping experiments showed, that there is no significant difference between B cell subpopulations of acute Borreliosis patients and controls. BCR sequences from individual epitope-reactive B cells had little in common between each other. HTS showed, however, a higher complementarity determining region 3 (CDR3) amino acid (aa) sequence overlap between samples from different timepoints in patients as compared to controls. This indicates, that HTS is sensitive enough to detect ongoing B cell immune responses in these patients. Although each individual's repertoire was dominated by rather unique clones, clustering of bulk BCR repertoire sequences revealed a higher overlap of IgG BCR repertoire sequences between acute patients than controls. Even if we have identified a few Borrelia-associated CDR3aa sequences, they seem to be rather unique for each patient and therefore not suitable as biomarkers.
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Affiliation(s)
- Josiane Kirpach
- Vaccinology and B Cell Immunology, Infectious Diseases Research Unit, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Alessia Colone
- Vaccinology and B Cell Immunology, Infectious Diseases Research Unit, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Jean-Philippe Bürckert
- Vaccinology and B Cell Immunology, Infectious Diseases Research Unit, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - William J Faison
- Vaccinology and B Cell Immunology, Infectious Diseases Research Unit, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Axel R S X Dubois
- Vaccinology and B Cell Immunology, Infectious Diseases Research Unit, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Regina Sinner
- Vaccinology and B Cell Immunology, Infectious Diseases Research Unit, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Anna L Reye
- Vaccinology and B Cell Immunology, Infectious Diseases Research Unit, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
| | - Claude P Muller
- Vaccinology and B Cell Immunology, Infectious Diseases Research Unit, Department of Infection and Immunity, Luxembourg Institute of Health, Esch-sur-Alzette, Luxembourg
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19
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Lai M, Wang Q, Lu Y, Xu X, Xia Y, Tu M, Liu Y, Zhang Q, Peng Y, Zheng X. Signatures of B-cell receptor diversity in B lymphocytes following Epstein-Barr virus transformation. Physiol Genomics 2019; 51:197-207. [PMID: 31002588 DOI: 10.1152/physiolgenomics.00124.2018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Epstein-Barr virus (EBV) is a widespread human virus that establishes latent infection, potentially leading to tumors, hematological disorders, and other severe diseases. EBV infections are associated with diverse symptoms and affect various organs; therefore, early diagnosis and treatment are crucial. B cell receptor (BCR) repertoires of B cell surface immunoglobulins have been widely studied for their association with various infectious diseases. However, the specific genetic changes that modulate the BCR repertoires after an EBV infection are still poorly understood. In this study, we employed high-throughput sequencing (HTS) to investigate the diversity of BCR repertoires in an EBV-transformed lymphoblastic cell line (LCL). Compared with the noninfected control B cell line, the LCL exhibited a decrease in overall BCR diversity but displayed an increase in the expansion of some dominant rearrangements such as IGHV4-31/IGHJ4, IGHV4-59/IGHJ4, IGHV5-51/IGHJ3, and IGHV3-74/IGHJ3. A higher frequency of occurrence of these rearrangement types was confirmed in patients with EBV infection. Interestingly, the IGHV3-74 rearrangement was only detected in EBV-infected children, suggesting that our experimental observations were not coincidental. In addition, we identified a highly dominant consensus motif, CAR(xRx)YGSG(xYx)FD, in complementarity-determining region 3 (CDR3) sequences of the heavy chain in the LCL. Our findings demonstrated the utility of HTS technology for studying the variations in signature motifs of the BCR repertoires after EBV infection. We propose that the analysis of BCR repertoire sequences represents a promising method for diagnosing early EBV infections and developing novel antibody- and vaccine-based therapies against such infections.
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Affiliation(s)
- Meimei Lai
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Qiongdan Wang
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Yutian Lu
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Xi Xu
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Ying Xia
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Mengyun Tu
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Yanqing Liu
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Qi Zhang
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Ying Peng
- School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
| | - Xiaoqun Zheng
- Department of Clinical Laboratory, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University , Wenzhou, Zhejiang , China.,School of Laboratory Medicine and Life Sciences, Wenzhou Medical University , Wenzhou, Zhejiang , China.,Key Laboratory of Laboratory Medicine, Ministry of Education , Wenzhou, Zhejiang , China
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20
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Peripheral T cell receptor beta immune repertoire is promptly reconstituted after acute myocardial infarction. J Transl Med 2019; 17:40. [PMID: 30728066 PMCID: PMC6366076 DOI: 10.1186/s12967-019-1788-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 02/04/2019] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Acute myocardial infarction (AMI) is characterized by an inflammatory process in which T cell plays a key role. However, the profile of immune microenvironment in AMI is still uncertain. High-throughput sequencing of T cell receptor (TCR) provides deep insight into monitoring the immune microenvironment. METHODS 30 patients with AMI were enrolled and 30 healthy individuals were recruited as controls. Flow cytometer were used to analyze the distribution of αβ T cells and their CD69 expression from peripheral leukomonocytes. TCRβ repertoire library was amplified by two-round multiplex PCR and detected by next-generation sequencing (NGS). RESULTS The percentage of αβ T cells in AMI patients were significantly restricted than those in healthy controls, while the highly activated αβ T cells along with distinguishing usage of variable (V), diversity (D) and joining (J) gene segments were also found in AMI patients. In addition, AMI induced a significantly restricted CDR3 amino acid (AA) diversity and remarkably reconstituted TCR immune repertoires. Finally, we identified several AMI-associated tendency of CDR3 AAs expression after AMI. CONCLUSIONS Our work suggests that the aberrant αβ T cells distribution and activation may associated with the pathogenesis of AMI and demonstrates a reconstitution of TCRβ immune repertoire after AMI.
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Simon JS, Botero S, Simon SM. Sequencing the peripheral blood B and T cell repertoire - Quantifying robustness and limitations. J Immunol Methods 2018; 463:137-147. [PMID: 30312601 DOI: 10.1016/j.jim.2018.10.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 10/04/2018] [Accepted: 10/04/2018] [Indexed: 12/27/2022]
Abstract
The adaptive immune response generates a large repertoire of T cells with T-cell receptors (TCRalpha and TCRbeta) and B cells with immunoglobulins (Ig). The repertoire changes in response to antigen stimulation both through amplification of specific cells (clonal expansion) as well as somatic hypermutation of immunoglobulins. Alterations of the immune repertoire have been observed in response to acute disease, such as external pathogens, or chronic diseases, such as autoimmunity and cancer. Here we establish experimental and analytical protocols for quantifying the peripheral blood of healthy human individuals by profiling the immune repertoire for the Complementarity determining region 3 (CDR3) of the variable regions of TCRbeta (CDRβ3) and the IgG heavy chain (CDRH1, CDRH2, CDRH3). The results demonstrate that 40 ml of blood are sufficient to reliably capture the 10,000 most common TCRbeta and 1000 most common IgG and determine their relative frequency in the circulation. We conclude that by using an accessible sample size of human PBMC one is able to robustly monitor alterations in the immune repertoire.
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Affiliation(s)
- Joel S Simon
- Laboratory of Cellular Biophysics, The Rockefeller University, 1230 York Avenue, New York, NY 10065, United States
| | - Sergio Botero
- Laboratory of Cellular Biophysics, The Rockefeller University, 1230 York Avenue, New York, NY 10065, United States
| | - Sanford M Simon
- Laboratory of Cellular Biophysics, The Rockefeller University, 1230 York Avenue, New York, NY 10065, United States.
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22
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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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23
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Abstract
Somatic assembly of T cell receptor and B cell receptor (BCR) genes produces a vast diversity of lymphocyte antigen recognition capacity. The advent of efficient high-throughput sequencing of lymphocyte antigen receptor genes has recently generated unprecedented opportunities for exploration of adaptive immune responses. With these opportunities have come significant challenges in understanding the analysis techniques that most accurately reflect underlying biological phenomena. In this regard, sample preparation and sequence analysis techniques, which have largely been borrowed and adapted from other fields, continue to evolve. Here, we review current methods and challenges of library preparation, sequencing and statistical analysis of lymphocyte receptor repertoire studies. We discuss the general steps in the process of immune repertoire generation including sample preparation, platforms available for sequencing, processing of sequencing data, measurable features of the immune repertoire, and the statistical tools that can be used for analysis and interpretation of the data. Because BCR analysis harbors additional complexities, such as immunoglobulin (Ig) (i.e., antibody) gene somatic hypermutation and class switch recombination, the emphasis of this review is on Ig/BCR sequence analysis.
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Affiliation(s)
- Neha Chaudhary
- Division of Rheumatology, Department of Medicine, Immunology and Allergy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Duane R. Wesemann
- Division of Rheumatology, Department of Medicine, Immunology and Allergy, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States
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24
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Zheng J, Perlman S. Immune responses in influenza A virus and human coronavirus infections: an ongoing battle between the virus and host. Curr Opin Virol 2018; 28:43-52. [PMID: 29172107 PMCID: PMC5835172 DOI: 10.1016/j.coviro.2017.11.002] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 11/02/2017] [Indexed: 12/25/2022]
Abstract
Respiratory viruses, especially influenza A viruses and coronaviruses such as MERS-CoV, represent continuing global threats to human health. Despite significant advances, much needs to be learned. Recent studies in virology and immunology have improved our understanding of the role of the immune system in protection and in the pathogenesis of these infections and of co-evolution of viruses and their hosts. These findings, together with sophisticated molecular structure analyses, omics tools and computer-based models, have helped delineate the interaction between respiratory viruses and the host immune system, which will facilitate the development of novel treatment strategies and vaccines with enhanced efficacy.
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Affiliation(s)
- Jian Zheng
- Department of Microbiology and Immunology, The University of Iowa, Iowa City, IA 52242, United States
| | - Stanley Perlman
- Department of Microbiology and Immunology, The University of Iowa, Iowa City, IA 52242, United States.
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25
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A Potent Germline-like Human Monoclonal Antibody Targets a pH-Sensitive Epitope on H7N9 Influenza Hemagglutinin. Cell Host Microbe 2017; 22:471-483.e5. [PMID: 28966056 PMCID: PMC6290738 DOI: 10.1016/j.chom.2017.08.011] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2017] [Revised: 07/12/2017] [Accepted: 08/22/2017] [Indexed: 11/20/2022]
Abstract
The H7N9 influenza virus causes high-mortality disease in humans but no effective therapeutics are available. Here we report a human monoclonal antibody, m826, that binds to H7 hemagglutinin (HA) and protects against H7N9 infection. m826 binds to H7N9 HA with subnanomolar affinity at acidic pH and 10-fold lower affinity at neutral pH. The high-resolution (1.9 Å) crystal structure of m826 complexed with H7N9 HA indicates that m826 binds an epitope that may be fully exposed upon pH-induced conformational changes in HA. m826 fully protects mice against lethal challenge with H7N9 virus through mechanisms likely involving antibody-dependent cell-mediated cytotoxicity. Interestingly, immunogenetic analysis indicates that m826 is a germline antibody, and m826-like sequences can be identified in H7N9-infected patients, healthy adults, and newborn babies. These m826 properties offer a template for H7N9 vaccine immunogens, a promising candidate therapeutic, and a tool for exploring mechanisms of virus infection inhibition by antibodies.
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