1
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Zhang T, Yang D, Tang L, Hu Y. Current development of severe acute respiratory syndrome coronavirus 2 neutralizing antibodies (Review). Mol Med Rep 2024; 30:148. [PMID: 38940338 PMCID: PMC11228696 DOI: 10.3892/mmr.2024.13272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 05/21/2024] [Indexed: 06/29/2024] Open
Abstract
The coronavirus disease 2019 pandemic due to severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) seriously affected global public health security. Studies on vaccines, neutralizing antibodies (NAbs) and small molecule antiviral drugs are currently ongoing. In particular, NAbs have emerged as promising therapeutic agents due to their well‑defined mechanism, high specificity, superior safety profile, ease of large‑scale production and simultaneous application for both prevention and treatment of viral infection. Numerous NAb therapeutics have entered the clinical research stages, demonstrating promising therapeutic and preventive effects. These agents have been used for outbreak prevention and control under urgent authorization processes. The present review summarizes the molecular targets of SARS‑CoV‑2‑associated NAbs and screening and identification techniques for NAb development. Moreover, the current shortcomings and challenges that persist with the use of NAbs are discussed. The aim of the present review is to offer a reference for the development of NAbs for any future emergent infectious diseases, including SARS‑CoV‑2.
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Affiliation(s)
- Tong Zhang
- Department of Hematology, Wuhan Union Hospital, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
| | - Di Yang
- Department of Hematology, Wuhan Union Hospital, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
| | - Liang Tang
- Department of Hematology, Wuhan Union Hospital, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
| | - Yu Hu
- Department of Hematology, Wuhan Union Hospital, Huazhong University of Science and Technology, Wuhan, Hubei 430030, P.R. China
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2
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Serwanga J, Oluka GK, Baine C, Ankunda V, Sembera J, Kato L, Katende JS, Odoch G, Auma BO, Gombe B, Musenero M, Kaleebu P. Persistent and robust antibody responses to ChAdOx1-S Oxford-AstraZeneca (ChAdOx1-S, Covishield) SARS-CoV-2 vaccine observed in Ugandans across varied baseline immune profiles. PLoS One 2024; 19:e0303113. [PMID: 39074077 DOI: 10.1371/journal.pone.0303113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 04/18/2024] [Indexed: 07/31/2024] Open
Abstract
Understanding SARS-CoV-2 vaccine-induced antibody responses in varied antigenic and serological prior exposures can guide optimal vaccination strategies for enhanced immunogenicity. We evaluated spike (S)-directed IgG, IgM, and IgA antibody optical densities (ODs) and concentrations to the two-dose ChAdOx1-S Oxford-AstraZeneca (ChAdOx1-S, Covishield) SARS-CoV-2 vaccine in 67 Ugandans, categorised by prior infection and baseline S-IgG histories: uninfected and S-IgG-negative (n = 12); previously infected yet S-IgG-negative (n = 17); and previously infected with S-IgG-positive status (n = 38). Antibody dynamics were compared across eight timepoints from baseline till nine months. S-IgG antibodies remained consistently potent across all groups. Individuals with prior infections maintained robust S-IgG levels, underscoring the endurance of hybrid immunity. In contrast, those without prior exposure experienced an initial surge in S-IgG after the primary dose but no subsequent significant increase post-boost. However, they reached levels parallel to the previously exposed groups. S-IgM levels remained moderate, while S-IgA persisted in individuals with prior antigen exposure. ChAdOx1-S, Covishield vaccine elicited robust and sustained antibody responses in recipients, irrespective of their initial immune profiles. Hybrid immunity showed higher responses, aligning with global observations. Early post-vaccination antibody levels could predict long-term immunity, particularly in individuals without virus exposure. These findings can inform vaccine strategies and pandemic management.
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Affiliation(s)
- Jennifer Serwanga
- Viral Pathogens Theme, MRC/UVRI & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Gerald Kevin Oluka
- Viral Pathogens Theme, MRC/UVRI & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Claire Baine
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Violet Ankunda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Jackson Sembera
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Laban Kato
- Viral Pathogens Theme, MRC/UVRI & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Joseph Ssebwana Katende
- Viral Pathogens Theme, MRC/UVRI & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Geoffrey Odoch
- Viral Pathogens Theme, MRC/UVRI & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Betty Oliver Auma
- Viral Pathogens Theme, MRC/UVRI & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
| | - Ben Gombe
- Viral Pathogens Theme, MRC/UVRI & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
| | - Monica Musenero
- Science, Technology, and Innovation Secretariat, Office of the President, Government of Uganda, Kampala, Uganda
| | - Pontiano Kaleebu
- Viral Pathogens Theme, MRC/UVRI & London School of Hygiene and Tropical Medicine, Uganda Research Unit, Entebbe, Uganda
- Department of Immunology, Uganda Virus Research Institute, Entebbe, Uganda
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3
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Tsay GJ, Zouali M. Cellular pathways and molecular events that shape autoantibody production in COVID-19. J Autoimmun 2024; 147:103276. [PMID: 38936147 DOI: 10.1016/j.jaut.2024.103276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 05/26/2024] [Accepted: 06/18/2024] [Indexed: 06/29/2024]
Abstract
A hallmark of COVID-19 is the variety of complications that follow SARS-CoV-2 infection in some patients, and that target multiple organs and tissues. Also remarkable are the associations with several auto-inflammatory disorders and the presence of autoantibodies directed to a vast array of antigens. The processes underlying autoantibody production in COVID-19 have not been completed deciphered. Here, we review mechanisms involved in autoantibody production in COVID-19, multisystem inflammatory syndrome in children, and post-acute sequelae of COVID19. We critically discuss how genomic integrity, loss of B cell tolerance to self, superantigen effects of the virus, and extrafollicular B cell activation could underly autoantibody proaction in COVID-19. We also offer models that may account for the pathogenic roles of autoantibodies in the promotion of inflammatory cascades, thromboembolic phenomena, and endothelial and vascular deregulations.
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Affiliation(s)
- Gregory J Tsay
- Division of Immunology and Rheumatology, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan; College of Medicine, China Medical University, Taichung, Taiwan
| | - Moncef Zouali
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung, Taiwan.
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4
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Gabernet G, Marquez S, Bjornson R, Peltzer A, Meng H, Aron E, Lee NY, Jensen CG, Ladd D, Polster M, Hanssen F, Heumos S, Yaari G, Kowarik MC, Nahnsen S, Kleinstein SH. nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework. PLoS Comput Biol 2024; 20:e1012265. [PMID: 39058741 PMCID: PMC11305553 DOI: 10.1371/journal.pcbi.1012265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2024] [Revised: 08/07/2024] [Accepted: 06/20/2024] [Indexed: 07/28/2024] Open
Abstract
Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets.
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Affiliation(s)
- Gisela Gabernet
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Susanna Marquez
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Robert Bjornson
- Yale Center for Research Computing, New Haven, Connecticut, United States of America
| | | | - Hailong Meng
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America
| | - Edel Aron
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Noah Y. Lee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Cole G. Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - David Ladd
- oNKo-Innate Pty Ltd, Melbourne, Victoria, Australia
| | - Mark Polster
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Department of Computer Science, Eberhard-Karls University of Tübingen, Tübingen, Germany
- M3 Research Center, University Hospital, Tübingen, Germany
| | - Friederike Hanssen
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Department of Computer Science, Eberhard-Karls University of Tübingen, Tübingen, Germany
- M3 Research Center, University Hospital, Tübingen, Germany
| | - Simon Heumos
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Department of Computer Science, Eberhard-Karls University of Tübingen, Tübingen, Germany
- M3 Research Center, University Hospital, Tübingen, Germany
| | | | - Gur Yaari
- Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel
| | - Markus C. Kowarik
- Department of Neurology and Stroke, Center for Neurology, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Hertie Institute for Clinical Brain Research, Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Sven Nahnsen
- Quantitative Biology Center, Eberhard-Karls University of Tübingen, Tübingen, Germany
- Department of Computer Science, Eberhard-Karls University of Tübingen, Tübingen, Germany
- M3 Research Center, University Hospital, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics (IBMI), Eberhard-Karls University of Tübingen, Tübingen, Germany
| | - Steven H. Kleinstein
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
- Department of Immunobiology, Yale School of Medicine, New Haven, Connecticut, United States of America
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5
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Liu B, Niu X, Deng Y, Zhang Z, Wang Y, Gao X, Liang H, Li Z, Wang Q, Cheng Y, Chen Q, Huang S, Pan Y, Su M, Lin X, Niu C, Chen Y, Yang W, Zhang Y, Yan Q, He J, Zhao J, Chen L, Xiong X. An unconventional VH1-2 antibody tolerates escape mutations and shows an antigenic hotspot on SARS-CoV-2 spike. Cell Rep 2024; 43:114265. [PMID: 38805396 DOI: 10.1016/j.celrep.2024.114265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 11/29/2023] [Accepted: 05/07/2024] [Indexed: 05/30/2024] Open
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike (S) protein continues to evolve antigenically, impacting antibody immunity. D1F6, an affinity-matured non-stereotypic VH1-2 antibody isolated from a patient infected with the SARS-CoV-2 ancestral strain, effectively neutralizes most Omicron variants tested, including XBB.1.5. We identify that D1F6 in the immunoglobulin G (IgG) form is able to overcome the effect of most Omicron mutations through its avidity-enhanced multivalent S-trimer binding. Cryo-electron microscopy (cryo-EM) and biochemical analyses show that three simultaneous epitope mutations are generally needed to substantially disrupt the multivalent S-trimer binding by D1F6 IgG. Antigenic mutations at spike positions 346, 444, and 445, which appeared in the latest variants, have little effect on D1F6 binding individually. However, these mutations are able to act synergistically with earlier Omicron mutations to impair neutralization by affecting the interaction between D1F6 IgG and the S-trimer. These results provide insight into the mechanism by which accumulated antigenic mutations facilitate evasion of affinity-matured antibodies.
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Affiliation(s)
- Banghui Liu
- State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Xuefeng Niu
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
| | - Yijun Deng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zhaoyong Zhang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yanqun Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xijie Gao
- Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Huan Liang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zimu Li
- State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Qian Wang
- Guangzhou Laboratory & Bioland Laboratory, Guangzhou, China
| | - Yuanyi Cheng
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qiuluan Chen
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health - Guangdong Laboratory), Guangzhou, China
| | - Shuangshuang Huang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yingxian Pan
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Mengzhen Su
- State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China; University of Science and Technology of China, Hefei, China
| | - Xiancheng Lin
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chuanying Niu
- State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China; University of Science and Technology of China, Hefei, China
| | - Yinglin Chen
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Wenyi Yang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yudi Zhang
- State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China; University of Chinese Academy of Sciences, Beijing, China
| | - Qihong Yan
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jun He
- State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Jincun Zhao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
| | - Ling Chen
- Guangzhou Laboratory & Bioland Laboratory, Guangzhou, China.
| | - Xiaoli Xiong
- State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China.
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6
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Suthar MS. Durability of immune responses to SARS-CoV-2 infection and vaccination. Semin Immunol 2024; 73:101884. [PMID: 38861769 DOI: 10.1016/j.smim.2024.101884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 05/07/2024] [Accepted: 05/07/2024] [Indexed: 06/13/2024]
Abstract
Infection with SARS-CoV-2 in humans has caused a pandemic of unprecedented dimensions. SARS-CoV-2 is primarily transmitted through respiratory droplets and targets ciliated epithelial cells in the nasal cavity, trachea, and lungs by utilizing the cellular receptor angiotensin-converting enzyme 2 (ACE2). The innate immune response, including type I and III interferons, inflammatory cytokines (IL-6, TNF-α, IL-1β), innate immune cells (monocytes, DCs, neutrophils, natural killer cells), antibodies (IgG, sIgA, neutralizing antibodies), and adaptive immune cells (B cells, CD8+ and CD4+ T cells) play pivotal roles in mitigating COVID-19 disease. Broad and durable B-cell- and T-cell immunity elicited by infection and vaccination is essential for protection against severe disease, hospitalization and death. However, the emergence of SARS-CoV-2 variants that evade neutralizing antibodies continue to jeopardize vaccine efficacy. In this review, we highlight our understanding the infection- and vaccine-mediated humoral, B and T cell responses, the durability of the immune responses, and how variants continue to threaten the efficacy of SARS-CoV-2 vaccines.
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Affiliation(s)
- Mehul S Suthar
- Emory Vaccine Center, Emory National Primate Research Center, Emory Vaccine Center, Emory University, Atlanta, GA, USA; Emory Center of Excellence of Influenza Research and Response (CEIRR), Atlanta, GA, USA; Department of Microbiology and Immunology, Emory University, Atlanta, GA, USA; Center for Childhood Infections and Vaccines of Children's Healthcare of Atlanta, Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA.
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7
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Zhang T, Han Y, Huang W, Wei H, Zhao Y, Shu L, Guo Y, Ye B, Zhou J, Liu J. Neutralizing antibody responses against contemporary and future influenza A(H3N2) viruses in paradoxical clades elicited by repeated and single vaccinations. J Med Virol 2024; 96:e29743. [PMID: 38884419 DOI: 10.1002/jmv.29743] [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: 03/06/2024] [Revised: 05/16/2024] [Accepted: 06/05/2024] [Indexed: 06/18/2024]
Abstract
As one of the most effective measures to prevent seasonal influenza viruses, annual influenza vaccination is globally recommended. Nevertheless, evidence regarding the impact of repeated vaccination to contemporary and future influenza has been inconclusive. A total of 100 subjects singly or repeatedly immunized with influenza vaccines including 3C.2a1 or 3C.3a1 A(H3N2) during 2018-2019 and 2019-2020 influenza season were recruited. We investigated neutralization antibody by microneutralization assay using four antigenically distinct A(H3N2) viruses circulating from 2018 to 2023, and tracked the dynamics of B cell receptor (BCR) repertoire for consecutive vaccinations. We found that vaccination elicited cross-reactive antibody responses against future emerging strains. Broader neutralizing antibodies to A(H3N2) viruses and more diverse BCR repertoires were observed in the repeated vaccination. Meanwhile, a higher frequency of BCR sequences shared among the repeated-vaccinated individuals with consistently boosting antibody response was found than those with a reduced antibody response. Our findings suggest that repeated seasonal vaccination could broaden the breadth of antibody responses, which may improve vaccine protection against future emerging viruses.
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MESH Headings
- Humans
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza Vaccines/immunology
- Influenza Vaccines/administration & dosage
- Antibodies, Neutralizing/blood
- Antibodies, Neutralizing/immunology
- Antibodies, Viral/blood
- Antibodies, Viral/immunology
- Influenza, Human/prevention & control
- Influenza, Human/immunology
- Influenza, Human/virology
- Adult
- Cross Reactions/immunology
- Male
- Female
- Vaccination
- Middle Aged
- Young Adult
- Neutralization Tests
- Receptors, Antigen, B-Cell/immunology
- Receptors, Antigen, B-Cell/genetics
- Adolescent
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Affiliation(s)
- Ting Zhang
- Collaborative Innovation Centre of Regenerative Medicine and Medical Bioresource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
| | - Yang Han
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
- National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Weijuan Huang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hejiang Wei
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yingze Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
| | - Liumei Shu
- Department of Health Care, Beijing Daxing District Hospital, Beijing, China
| | - Yaxin Guo
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
| | - Beiwei Ye
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
| | - Jianfang Zhou
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jun Liu
- Collaborative Innovation Centre of Regenerative Medicine and Medical Bioresource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
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8
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Zaslavsky ME, Craig E, Michuda JK, Sehgal N, Ram-Mohan N, Lee JY, Nguyen KD, Hoh RA, Pham TD, Röltgen K, Lam B, Parsons ES, Macwana SR, DeJager W, Drapeau EM, Roskin KM, Cunningham-Rundles C, Moody MA, Haynes BF, Goldman JD, Heath JR, Nadeau KC, Pinsky BA, Blish CA, Hensley SE, Jensen K, Meyer E, Balboni I, Utz PJ, Merrill JT, Guthridge JM, James JA, Yang S, Tibshirani R, Kundaje A, Boyd SD. Disease diagnostics using machine learning of immune receptors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2022.04.26.489314. [PMID: 35547855 PMCID: PMC9094102 DOI: 10.1101/2022.04.26.489314] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Clinical diagnosis typically incorporates physical examination, patient history, and various laboratory tests and imaging studies, but makes limited use of the human system's own record of antigen exposures encoded by receptors on B cells and T cells. We analyzed immune receptor datasets from 593 individuals to develop MAchine Learning for Immunological Diagnosis (Mal-ID) , an interpretive framework to screen for multiple illnesses simultaneously or precisely test for one condition. This approach detects specific infections, autoimmune disorders, vaccine responses, and disease severity differences. Human-interpretable features of the model recapitulate known immune responses to SARS-CoV-2, Influenza, and HIV, highlight antigen-specific receptors, and reveal distinct characteristics of Systemic Lupus Erythematosus and Type-1 Diabetes autoreactivity. This analysis framework has broad potential for scientific and clinical interpretation of human immune responses.
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Woodruff MC, Faliti CE, Sanz I. Systems biology of B cells in COVID-19. Semin Immunol 2024; 72:101875. [PMID: 38489999 DOI: 10.1016/j.smim.2024.101875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 03/04/2024] [Accepted: 03/04/2024] [Indexed: 03/17/2024]
Abstract
The integration of multi-'omic datasets into complex systems-wide assessments has become a mainstay in immunologic investigation. This focus on high-dimensional data collection and analysis was on full display in the investigation of COVID-19, the respiratory illness resulting from infection by the novel coronavirus SARS-CoV-2. Particularly in the area of B cell biology, tremendous efforts in both cellular and serologic investigation have resulted in an increasingly detailed mapping of the coordinated effector, memory, and antibody secreting cell responses that underpin the development of humoral immunity in response to primary viral infection. Further, the rapid development and deployment of effective vaccines has allowed for the assessment of developing memory responses across a wide variety of immune contexts, including in patients with compromised immune function. The result has been a period of rapid gains in the understanding of B cell biology unrestricted to the study of COVID-19. Here, we outline the systems-level technologies that have been routinely implemented in these investigations throughout the pandemic, and discuss how their use has led to clear and applicable gains in pursuance of the amelioration of human infectious disease and beyond.
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Affiliation(s)
- Matthew C Woodruff
- Department of Medicine, Division of Rheumatology, Lowance Center for Human Immunology, Emory University, Atlanta, GA, USA; Emory Autoimmunity Center of Excellence, Emory University, Atlanta, GA, USA.
| | - Caterina E Faliti
- Department of Medicine, Division of Rheumatology, Lowance Center for Human Immunology, Emory University, Atlanta, GA, USA; Emory Autoimmunity Center of Excellence, Emory University, Atlanta, GA, USA.
| | - Ignacio Sanz
- Department of Medicine, Division of Rheumatology, Lowance Center for Human Immunology, Emory University, Atlanta, GA, USA; Emory Autoimmunity Center of Excellence, Emory University, Atlanta, GA, USA
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10
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Xiao J, Luo Y, Li Y, Yao X. The characteristics of BCR-CDR3 repertoire in COVID-19 patients and SARS-CoV-2 vaccinated volunteers. J Med Virol 2024; 96:e29488. [PMID: 38415507 DOI: 10.1002/jmv.29488] [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: 11/04/2023] [Revised: 02/02/2024] [Accepted: 02/13/2024] [Indexed: 02/29/2024]
Abstract
The global COVID-19 pandemic has caused more than 1 billion infections, and numerous SARS-CoV-2 vaccines developed rapidly have been administered over 10 billion doses. The world is continuously concerned about the cytokine storms induced by the interaction between SARS-CoV-2 and host, long COVID, breakthrough infections postvaccination, and the impact of SARS-CoV-2 variants. BCR-CDR3 repertoire serves as a molecular target for monitoring the antiviral response "trace" of B cells, evaluating the effects, mechanisms, and memory abilities of individual responses to B cells, and has been successfully applied in analyzing the infection mechanisms, vaccine improvement, and neutralizing antibodies preparation of influenza virus, HIV, MERS, and Ebola virus. Based on research on BCR-CDR3 repertoire of COVID-19 patients and volunteers who received different SARS-CoV-2 vaccines in multiple laboratories worldwide, we focus on analyzing the characteristics and changes of BCR-CDR3 repertoire, such as diversity, clonality, V&J genes usage and pairing, SHM, CSR, shared CDR3 clones, as well as the summary on BCR sequences targeting virus-specific epitopes in the preparation and application research of SARS-CoV-2 potential therapeutic monoclonal antibodies. This review provides comparative data and new research schemes for studying the possible mechanisms of differences in B cell response between SARS-CoV-2 infection or vaccination, and supplies a foundation for improving vaccines after SARS-CoV-2 mutations and potential antibody therapy for infected individuals.
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Affiliation(s)
- Jiaping Xiao
- Department of Immunology, Center of Immunomolecular Engineering, Innovation & Practice Base for Graduate Students Education, Zunyi Medical University, Zunyi, Guizhou, China
- Fushun People's Hospital, Zigong, Sichuan, China
| | - Yan Luo
- Department of Immunology, Center of Immunomolecular Engineering, Innovation & Practice Base for Graduate Students Education, Zunyi Medical University, Zunyi, Guizhou, China
| | - Yangyang Li
- Department of Immunology, Center of Immunomolecular Engineering, Innovation & Practice Base for Graduate Students Education, Zunyi Medical University, Zunyi, Guizhou, China
| | - Xinsheng Yao
- Department of Immunology, Center of Immunomolecular Engineering, Innovation & Practice Base for Graduate Students Education, Zunyi Medical University, Zunyi, Guizhou, China
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11
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Teng S, Hu Y, Wang Y, Tang Y, Wu Q, Zheng X, Lu R, Pan D, Liu F, Xie T, Wu C, Li YP, Liu W, Qu X. SARS-CoV-2 spike-reactive naïve B cells and pre-existing memory B cells contribute to antibody responses in unexposed individuals after vaccination. Front Immunol 2024; 15:1355949. [PMID: 38420128 PMCID: PMC10899457 DOI: 10.3389/fimmu.2024.1355949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 01/30/2024] [Indexed: 03/02/2024] Open
Abstract
Introduction Since December 2019, the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) has presented considerable public health challenges. Multiple vaccines have been used to induce neutralizing antibodies (nAbs) and memory B-cell responses against the viral spike (S) glycoprotein, and many essential epitopes have been defined. Previous reports have identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike-reactive naïve B cells and preexisting memory B cells in unexposed individuals. However, the role of these spike-reactive B cells in vaccine-induced immunity remains unknown. Methods To elucidate the characteristics of preexisting SARS-CoV-2 S-reactive B cells as well as their maturation after antigen encounter, we assessed the relationship of spike-reactive B cells before and after vaccination in unexposed human individuals. We further characterized the sequence identity, targeting domain, broad-spectrum binding activity and neutralizing activity of these SARS-CoV-2 S-reactive B cells by isolating monoclonal antibodies (mAbs) from these B cells. Results The frequencies of both spike-reactive naïve B cells and preexisting memory B cells before vaccination correlated with the frequencies of spike-reactive memory B cells after vaccination. Isolated mAbs from spike-reactive naïve B cells before vaccination had fewer somatic hypermutations (SHMs) than mAbs isolated from spike-reactive memory B cells before and after vaccination, but bound SARS-CoV-2 spike in vitro. Intriguingly, these germline-like mAbs possessed broad binding profiles for SARS-CoV-2 and its variants, although with low or no neutralizing capacity. According to tracking of the evolution of IGHV4-4/IGKV3-20 lineage antibodies from a single donor, the lineage underwent SHMs and developed increased binding activity after vaccination. Discussion Our findings suggest that spike-reactive naïve B cells can be expanded and matured by vaccination and cocontribute to vaccine-elicited antibody responses with preexisting memory B cells. Selectively and precisely targeting spike-reactive B cells by rational antigen design may provide a novel strategy for next-generation SARS-CoV-2 vaccine development.
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Affiliation(s)
- Shishan Teng
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Yabin Hu
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - You Wang
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Yinggen Tang
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Qian Wu
- Institute of Human Virology, Zhongshan School of Medicine, and Key Laboratory of Tropical Disease Control of the Ministry of Education, Sun Yat-sen University, Guangzhou, China
| | - Xingyu Zheng
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Rui Lu
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Dong Pan
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Fen Liu
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Tianyi Xie
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Chanfeng Wu
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
- Translational Medicine Institute, The First People’s Hospital of Chenzhou, Hengyang Medical School, University of South China, Chenzhou, China
| | - Yi-Ping Li
- Institute of Human Virology, Zhongshan School of Medicine, and Key Laboratory of Tropical Disease Control of the Ministry of Education, Sun Yat-sen University, Guangzhou, China
| | - Wenpei Liu
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
| | - Xiaowang Qu
- School of Public Health & School of Basic Medicine Sciences, Hengyang Medical School & Ministry of Education Key Laboratory of Rare Pediatric Diseases, University of South China, Hengyang, China
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12
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Balashova D, van Schaik BDC, Stratigopoulou M, Guikema JEJ, Caniels TG, Claireaux M, van Gils MJ, Musters A, Anang DC, de Vries N, Greiff V, van Kampen AHC. Systematic evaluation of B-cell clonal family inference approaches. BMC Immunol 2024; 25:13. [PMID: 38331731 DOI: 10.1186/s12865-024-00600-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 01/18/2024] [Indexed: 02/10/2024] Open
Abstract
The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life and is diverse due to several factors such as gene recombination and somatic hypermutation. The use of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) using next generation sequencing enabled the generation of full BCR repertoires that also include rare CFs. The reconstruction of CFs from AIRR-seq data is challenging and several approaches have been developed to solve this problem. Currently, most methods use the heavy chain (HC) only, as it is more variable than the light chain (LC). CF reconstruction options include the definition of appropriate sequence similarity measures, the use of shared mutations among sequences, and the possibility of reconstruction without preliminary clustering based on V- and J-gene annotation. In this study, we aimed to systematically evaluate different approaches for CF reconstruction and to determine their impact on various outcome measures such as the number of CFs derived, the size of the CFs, and the accuracy of the reconstruction. The methods were compared to each other and to a method that groups sequences based on identical junction sequences and another method that only determines subclones. We found that after accounting for data set variability, in particular sequencing depth and mutation load, the reconstruction approach has an impact on part of the outcome measures, including the number of CFs. Simulations indicate that unique junctions and subclones should not be used as substitutes for CF and that more complex methods do not outperform simpler methods. Also, we conclude that different approaches differ in their ability to correctly reconstruct CFs when not considering the LC and to identify shared CFs. The results showed the effect of different approaches on the reconstruction of CFs and highlighted the importance of choosing an appropriate method.
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Affiliation(s)
- Daria Balashova
- Amsterdam UMC location University of Amsterdam, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands
- Amsterdam Infection and Immunity, Inflammatory Diseases, Amsterdam, The Netherlands
| | - Barbera D C van Schaik
- Amsterdam UMC location University of Amsterdam, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands
- Amsterdam Infection and Immunity, Inflammatory Diseases, Amsterdam, The Netherlands
| | - Maria Stratigopoulou
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Amsterdam UMC location University of Amsterdam, Medical Microbiology and Infection Prevention, Meibergdreef 9, Amsterdam, Netherlands
| | - Jeroen E J Guikema
- Cancer Center Amsterdam, Amsterdam, The Netherlands
- Amsterdam UMC location University of Amsterdam, Pathology, Lymphoma and Myeloma Center Amsterdam, Meibergdreef 9, Amsterdam, Netherlands
| | - Tom G Caniels
- Amsterdam UMC location University of Amsterdam, Medical Microbiology and Infection Prevention, Meibergdreef 9, Amsterdam, Netherlands
- Amsterdam Infection and Immunity, Infectious Diseases, Amsterdam, The Netherlands
| | - Mathieu Claireaux
- Amsterdam UMC location University of Amsterdam, Medical Microbiology and Infection Prevention, Meibergdreef 9, Amsterdam, Netherlands
- Amsterdam Infection and Immunity, Infectious Diseases, Amsterdam, The Netherlands
| | - Marit J van Gils
- Amsterdam UMC location University of Amsterdam, Medical Microbiology and Infection Prevention, Meibergdreef 9, Amsterdam, Netherlands
- Amsterdam Infection and Immunity, Infectious Diseases, Amsterdam, The Netherlands
| | - Anne Musters
- Amsterdam UMC location University of Amsterdam, Experimental Immunology, Meibergdreef 9, Amsterdam, Netherlands
- Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands
| | - Dornatien C Anang
- Amsterdam UMC location University of Amsterdam, Experimental Immunology, Meibergdreef 9, Amsterdam, Netherlands
- Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands
| | - Niek de Vries
- Amsterdam UMC location University of Amsterdam, Experimental Immunology, Meibergdreef 9, Amsterdam, Netherlands
- Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Antoine H C van Kampen
- Amsterdam UMC location University of Amsterdam, Epidemiology and Data Science, Meibergdreef 9, Amsterdam, Netherlands.
- Amsterdam Public Health, Methodology, Amsterdam, The Netherlands.
- Amsterdam Infection and Immunity, Inflammatory Diseases, Amsterdam, The Netherlands.
- Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands.
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13
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Lapuente D, Winkler TH, Tenbusch M. B-cell and antibody responses to SARS-CoV-2: infection, vaccination, and hybrid immunity. Cell Mol Immunol 2024; 21:144-158. [PMID: 37945737 PMCID: PMC10805925 DOI: 10.1038/s41423-023-01095-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 10/13/2023] [Indexed: 11/12/2023] Open
Abstract
The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 prompted scientific, medical, and biotech communities to investigate infection- and vaccine-induced immune responses in the context of this pathogen. B-cell and antibody responses are at the center of these investigations, as neutralizing antibodies (nAbs) are an important correlate of protection (COP) from infection and the primary target of SARS-CoV-2 vaccine modalities. In addition to absolute levels, nAb longevity, neutralization breadth, immunoglobulin isotype and subtype composition, and presence at mucosal sites have become important topics for scientists and health policy makers. The recent pandemic was and still is a unique setting in which to study de novo and memory B-cell (MBC) and antibody responses in the dynamic interplay of infection- and vaccine-induced immunity. It also provided an opportunity to explore new vaccine platforms, such as mRNA or adenoviral vector vaccines, in unprecedented cohort sizes. Combined with the technological advances of recent years, this situation has provided detailed mechanistic insights into the development of B-cell and antibody responses but also revealed some unexpected findings. In this review, we summarize the key findings of the last 2.5 years regarding infection- and vaccine-induced B-cell immunity, which we believe are of significant value not only in the context of SARS-CoV-2 but also for future vaccination approaches in endemic and pandemic settings.
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Affiliation(s)
- Dennis Lapuente
- Institut für klinische und molekulare Virologie, Universitätsklinikum Erlangen und Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Schlossgarten 4, 91054, Erlangen, Germany
| | - Thomas H Winkler
- Department of Biology, Division of Genetics, Nikolaus-Fiebiger-Center for Molecular Medicine, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
- Medical Immunology Campus Erlangen, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Schlossplatz 1, 91054, Erlangen, Germany.
| | - Matthias Tenbusch
- Institut für klinische und molekulare Virologie, Universitätsklinikum Erlangen und Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Schlossgarten 4, 91054, Erlangen, Germany
- Medical Immunology Campus Erlangen, Friedrich-Alexander-Universität (FAU) Erlangen-Nürnberg, Schlossplatz 1, 91054, Erlangen, Germany
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14
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Gabernet G, Marquez S, Bjornson R, Peltzer A, Meng H, Aron E, Lee NY, Jensen C, Ladd D, Hanssen F, Heumos S, Yaari G, Kowarik MC, Nahnsen S, Kleinstein SH. nf-core/airrflow: an adaptive immune receptor repertoire analysis workflow employing the Immcantation framework. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.18.576147. [PMID: 38293151 PMCID: PMC10827190 DOI: 10.1101/2024.01.18.576147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a valuable experimental tool to study the immune state in health and following immune challenges such as infectious diseases, (auto)immune diseases, and cancer. Several tools have been developed to reconstruct B cell and T cell receptor sequences from AIRR-seq data and infer B and T cell clonal relationships. However, currently available tools offer limited parallelization across samples, scalability or portability to high-performance computing infrastructures. To address this need, we developed nf-core/airrflow, an end-to-end bulk and single-cell AIRR-seq processing workflow which integrates the Immcantation Framework following BCR and TCR sequencing data analysis best practices. The Immcantation Framework is a comprehensive toolset, which allows the processing of bulk and single-cell AIRR-seq data from raw read processing to clonal inference. nf-core/airrflow is written in Nextflow and is part of the nf-core project, which collects community contributed and curated Nextflow workflows for a wide variety of analysis tasks. We assessed the performance of nf-core/airrflow on simulated sequencing data with sequencing errors and show example results with real datasets. To demonstrate the applicability of nf-core/airrflow to the high-throughput processing of large AIRR-seq datasets, we validated and extended previously reported findings of convergent antibody responses to SARS-CoV-2 by analyzing 97 COVID-19 infected individuals and 99 healthy controls, including a mixture of bulk and single-cell sequencing datasets. Using this dataset, we extended the convergence findings to 20 additional subjects, highlighting the applicability of nf-core/airrflow to validate findings in small in-house cohorts with reanalysis of large publicly available AIRR datasets. nf-core/airrflow is available free of charge, under the MIT license on GitHub (https://github.com/nf-core/airrflow). Detailed documentation and example results are available on the nf-core website at (https://nf-co.re/airrflow).
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15
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Röltgen K, Boyd SD. Antibody and B Cell Responses to SARS-CoV-2 Infection and Vaccination: The End of the Beginning. ANNUAL REVIEW OF PATHOLOGY 2024; 19:69-97. [PMID: 37738512 DOI: 10.1146/annurev-pathmechdis-031521-042754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/24/2023]
Abstract
As the COVID-19 pandemic has evolved during the past years, interactions between human immune systems, rapidly mutating and selected SARS-CoV-2 viral variants, and effective vaccines have complicated the landscape of individual immunological histories. Here, we review some key findings for antibody and B cell-mediated immunity, including responses to the highly mutated omicron variants; immunological imprinting and other impacts of successive viral antigenic variant exposures on antibody and B cell memory; responses in secondary lymphoid and mucosal tissues and non-neutralizing antibody-mediated immunity; responses in populations vulnerable to severe disease such as those with cancer, immunodeficiencies, and other comorbidities, as well as populations showing apparent resistance to severe disease such as many African populations; and evidence of antibody involvement in postacute sequelae of infection or long COVID. Despite the initial phase of the pandemic ending, human populations will continue to face challenges presented by this unpredictable virus.
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Affiliation(s)
- Katharina Röltgen
- Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Scott D Boyd
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA;
- Sean N. Parker Center for Allergy and Asthma Research, Stanford University School of Medicine, Stanford, California, USA
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16
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Leung JM, Wu MJ, Kheradpour P, Chen C, Drake KA, Tong G, Ridaura VK, Zisser HC, Conrad WA, Hudson N, Allen J, Welberry C, Parsy-Kowalska C, Macdonald I, Tapson VF, Moy JN, deFilippi CR, Rosas IO, Basit M, Krishnan JA, Parthasarathy S, Prabhakar BS, Salvatore M, Kim CC. Early immune factors associated with the development of post-acute sequelae of SARS-CoV-2 infection in hospitalized and non-hospitalized individuals. Front Immunol 2024; 15:1348041. [PMID: 38318183 PMCID: PMC10838987 DOI: 10.3389/fimmu.2024.1348041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Accepted: 01/02/2024] [Indexed: 02/07/2024] Open
Abstract
Background Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can lead to post-acute sequelae of SARS-CoV-2 (PASC) that can persist for weeks to years following initial viral infection. Clinical manifestations of PASC are heterogeneous and often involve multiple organs. While many hypotheses have been made on the mechanisms of PASC and its associated symptoms, the acute biological drivers of PASC are still unknown. Methods We enrolled 494 patients with COVID-19 at their initial presentation to a hospital or clinic and followed them longitudinally to determine their development of PASC. From 341 patients, we conducted multi-omic profiling on peripheral blood samples collected shortly after study enrollment to investigate early immune signatures associated with the development of PASC. Results During the first week of COVID-19, we observed a large number of differences in the immune profile of individuals who were hospitalized for COVID-19 compared to those individuals with COVID-19 who were not hospitalized. Differences between individuals who did or did not later develop PASC were, in comparison, more limited, but included significant differences in autoantibodies and in epigenetic and transcriptional signatures in double-negative 1 B cells, in particular. Conclusions We found that early immune indicators of incident PASC were nuanced, with significant molecular signals manifesting predominantly in double-negative B cells, compared with the robust differences associated with hospitalization during acute COVID-19. The emerging acute differences in B cell phenotypes, especially in double-negative 1 B cells, in PASC patients highlight a potentially important role of these cells in the development of PASC.
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Affiliation(s)
| | - Michelle J. Wu
- Verily Life Sciences, South San Francisco, CA, United States
| | | | - Chen Chen
- Verily Life Sciences, South San Francisco, CA, United States
| | | | - Gary Tong
- Verily Life Sciences, South San Francisco, CA, United States
| | | | | | - William A. Conrad
- Providence Little Company of Mary Medical Center Torrance, Torrance, CA, United States
| | | | - Jared Allen
- Oncimmune Limited, Nottingham, United Kingdom
| | | | | | | | - Victor F. Tapson
- Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - James N. Moy
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, United States
| | | | - Ivan O. Rosas
- Department of Medicine, Baylor College of Medicine, Houston, TX, United States
| | - Mujeeb Basit
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Jerry A. Krishnan
- Breathe Chicago Center, University of Illinois Chicago, Chicago, IL, United States
| | - Sairam Parthasarathy
- Division of Pulmonary, Allergy, Critical Care & Sleep Medicine, University of Arizona, Tucson, AZ, United States
| | - Bellur S. Prabhakar
- Department of Microbiology and Immunology, University of Illinois - College of Medicine, Chicago, IL, United States
| | - Mirella Salvatore
- Department of Medicine and Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States
| | - Charles C. Kim
- Verily Life Sciences, South San Francisco, CA, United States
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Rubinstein A, Kudryavtsev I, Malkova A, Mammedova J, Isakov D, Isakova-Sivak I, Kudlay D, Starshinova A. Sarcoidosis-related autoimmune inflammation in COVID-19 convalescent patients. Front Med (Lausanne) 2023; 10:1271198. [PMID: 38179278 PMCID: PMC10765615 DOI: 10.3389/fmed.2023.1271198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 11/27/2023] [Indexed: 01/06/2024] Open
Abstract
Currently, there are a large number of reports about the development of autoimmune conditions after COVID-19. Also, there have been cases of sarcoid-like granulomas in convalescents as a part of the post-COVID-19 syndrome. Since one of the etiological theories of sarcoidosis considers it to be an autoimmune disease, we decided to study changes in the adaptive humoral immune response in sarcoidosis and SARS-CoV-2 infection and to find out whether COVID-19 can provoke the development of sarcoidosis. This review discusses histological changes in lymphoid organs in sarcoidosis and COVID-19, changes in B cell subpopulations, T-follicular helper cells (Tfh), and T-follicular regulatory cells (Tfr), and analyzes various autoantibodies detected in these pathologies. Based on the data studied, we concluded that SARS-CoV-2 infection may cause the development of autoimmune pathologies, in particular contributing to the onset of sarcoidosis in convalescents.
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Affiliation(s)
- Artem Rubinstein
- Almazov National Medical Research Centre, Saint Petersburg, Russia
- Institution of Experimental Medicine, Saint Petersburg, Russia
| | - Igor Kudryavtsev
- Almazov National Medical Research Centre, Saint Petersburg, Russia
- Institution of Experimental Medicine, Saint Petersburg, Russia
- Far Eastern Federal University, Vladivostok, Russia
| | - Annа Malkova
- Ariel University Faculty of Natural Sciences, Ariel, Israel
| | | | - Dmitry Isakov
- First Saint Petersburg State I. Pavlov Medical University, Saint Petersburg, Russia
| | | | - Dmitry Kudlay
- Institute of Pharmacy, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russia
- NRC Institute of Immunology, Moscow, Russia
- Department of Pharmacognosy and Industrial Pharmacy, Faculty of Fundamental Medicine, Moscow, Russia
| | - Anna Starshinova
- Almazov National Medical Research Centre, Saint Petersburg, Russia
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18
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Ivanova EN, Shwetar J, Devlin JC, Buus TB, Gray-Gaillard S, Koide A, Cornelius A, Samanovic MI, Herrera A, Mimitou EP, Zhang C, Karmacharya T, Desvignes L, Ødum N, Smibert P, Ulrich RJ, Mulligan MJ, Koide S, Ruggles KV, Herati RS, Koralov SB. mRNA COVID-19 vaccine elicits potent adaptive immune response without the acute inflammation of SARS-CoV-2 infection. iScience 2023; 26:108572. [PMID: 38213787 PMCID: PMC10783604 DOI: 10.1016/j.isci.2023.108572] [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: 03/21/2022] [Revised: 09/21/2023] [Accepted: 11/21/2023] [Indexed: 01/13/2024] Open
Abstract
SARS-CoV-2 infection and vaccination elicit potent immune responses. Our study presents a comprehensive multimodal single-cell analysis of blood from COVID-19 patients and healthy volunteers receiving the SARS-CoV-2 vaccine and booster. We profiled immune responses via transcriptional analysis and lymphocyte repertoire reconstruction. COVID-19 patients displayed an enhanced interferon signature and cytotoxic gene upregulation, absent in vaccine recipients. B and T cell repertoire analysis revealed clonal expansion among effector cells in COVID-19 patients and memory cells in vaccine recipients. Furthermore, while clonal αβ T cell responses were observed in both COVID-19 patients and vaccine recipients, expansion of clonal γδ T cells was found only in infected individuals. Our dataset enables side-by-side comparison of immune responses to infection versus vaccination, including clonal B and T cell responses. Our comparative analysis shows that vaccination induces a robust, durable clonal B and T cell responses, without the severe inflammation associated with infection.
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Affiliation(s)
- Ellie N. Ivanova
- Department of Pathology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Jasmine Shwetar
- Institute of Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Joseph C. Devlin
- Institute of Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Terkild B. Buus
- Department of Pathology, New York University Grossman School of Medicine, New York, NY 10016, USA
- LEO Foundation Skin Immunology Research Center, Department of Immunology and Microbiology, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Sophie Gray-Gaillard
- New York University Langone Vaccine Center, New York University Langone Health, New York, NY 10016, USA
| | - Akiko Koide
- Department of Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
- Perlmutter Cancer Center, New York University Langone Health, New York, NY 10016, USA
| | - Amber Cornelius
- New York University Langone Vaccine Center, New York University Langone Health, New York, NY 10016, USA
| | - Marie I. Samanovic
- New York University Langone Vaccine Center, New York University Langone Health, New York, NY 10016, USA
- Department of Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Alberto Herrera
- Department of Pathology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | | | - Chenzhen Zhang
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Trishala Karmacharya
- New York University Langone Vaccine Center, New York University Langone Health, New York, NY 10016, USA
| | - Ludovic Desvignes
- New York University Langone Vaccine Center, New York University Langone Health, New York, NY 10016, USA
- Department of Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
- High Containment Laboratories, Office of Science and Research, New York University Langone Health, New York, NY 10016, USA
| | - Niels Ødum
- LEO Foundation Skin Immunology Research Center, Department of Immunology and Microbiology, University of Copenhagen, 2200 Copenhagen, Denmark
| | | | - Robert J. Ulrich
- New York University Langone Vaccine Center, New York University Langone Health, New York, NY 10016, USA
- Department of Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Mark J. Mulligan
- New York University Langone Vaccine Center, New York University Langone Health, New York, NY 10016, USA
| | - Shohei Koide
- Perlmutter Cancer Center, New York University Langone Health, New York, NY 10016, USA
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Kelly V. Ruggles
- Institute of Systems Genetics, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Ramin S. Herati
- New York University Langone Vaccine Center, New York University Langone Health, New York, NY 10016, USA
- Department of Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Microbiology, New York University Grossman School of Medicine, 430 East 29th Street, New York, NY 10016, USA
| | - Sergei B. Koralov
- Department of Pathology, New York University Grossman School of Medicine, New York, NY 10016, USA
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19
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Mai G, Zhang C, Lan C, Zhang J, Wang Y, Tang K, Tang J, Zeng J, Chen Y, Cheng P, Liu S, Long H, Wen Q, Li A, Liu X, Zhang R, Xu S, Liu L, Niu Y, Yang L, Wang Y, Yin D, Sun C, Chen YQ, Shen W, Zhang Z, Du X. Characterizing the dynamics of BCR repertoire from repeated influenza vaccination. Emerg Microbes Infect 2023; 12:2245931. [PMID: 37542407 PMCID: PMC10438862 DOI: 10.1080/22221751.2023.2245931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 07/12/2023] [Accepted: 08/03/2023] [Indexed: 08/06/2023]
Abstract
Yearly epidemics of seasonal influenza cause an enormous disease burden around the globe. An understanding of the rules behind the immune response with repeated vaccination still presents a significant challenge, which would be helpful for optimizing the vaccination strategy. In this study, 34 healthy volunteers with 16 vaccinated were recruited, and the dynamics of the BCR repertoire for consecutive vaccinations in two seasons were tracked. In terms of diversity, length, network, V and J gene segments usage, somatic hypermutation (SHM) rate and isotype, it was found that the overall changes were stronger in the acute phase of the first vaccination than the second vaccination. However, the V gene segments of IGHV4-39, IGHV3-9, IGHV3-7 and IGHV1-69 were amplified in the acute phase of the first vaccination, with IGHV3-7 dominant. On the other hand, for the second vaccination, the changes were dominated by IGHV1-69, with potential for coding broad neutralizing antibody. Additional analysis indicates that the application of V gene segment for IGHV3-7 in the acute phase of the first vaccination was due to the elevated usage of isotypes IgM and IgG3. While for IGHV1-69 in the second vaccination, it was contributed by isotypes IgG1 and IgG2. Finally, 41 public BCR clusters were identified in the vaccine group, with both IGHV3-7 and IGHV1-69 were involved and representative complementarity determining region 3 (CDR3) motifs were characterized. This study provides insights into the immune response dynamics following repeated influenza vaccination in humans and can inform universal vaccine design and vaccine strategies in the future.
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Affiliation(s)
- Guoqin Mai
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Chi Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Chunhong Lan
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Center for Precision Medicine, Guangdong Academy of Medical Sciences, Medical Research Institute, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, People’s Republic of 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, People’s Republic of China
| | - Jie Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yuanyuan Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Kang Tang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Jing Tang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Jinfeng Zeng
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yilin Chen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Peiwen Cheng
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Shuning Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Haoyu Long
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Qilan Wen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Aqin Li
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Xuan Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Ruitong Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Shuyang Xu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Lin Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yanlan Niu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Lan Yang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yihan Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Di Yin
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Caijun Sun
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yao-Qing Chen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Wei Shen
- Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Zhenhai Zhang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Center for Precision Medicine, Guangdong Academy of Medical Sciences, Medical Research Institute, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, People’s Republic of 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, People’s Republic of 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, People’s Republic of China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
- Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou, People’s Republic of China
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20
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Gervásio J, Ferreira A, Felicori LF. Yclon: Ultrafast clustering of B cell clones from high-throughput immunoglobulin repertoire sequencing data. J Immunol Methods 2023; 523:113576. [PMID: 37966818 DOI: 10.1016/j.jim.2023.113576] [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: 05/18/2023] [Accepted: 10/17/2023] [Indexed: 11/16/2023]
Abstract
MOTIVATION The next-generation sequencing technologies have transformed our understanding of immunoglobulin (Ig) profiles in various immune states. Clonotyping, which groups Ig sequences into B cell clones, is crucial in investigating the diversity of repertoires and changes in antigen exposure. Despite its importance, there is no widely accepted method for clonotyping, and existing methods are computationally intensive for large sequencing datasets. RESULTS To address this challenge, we introduce YClon, a fast and efficient approach for clonotyping Ig repertoire data. YClon uses a hierarchical clustering approach, similar to other methods, to group Ig sequences into B cell clones in a highly sensitive and specific manner. Notably, our approach outperforms other methods by being more than 30 to 5000 times faster in processing the repertoires analyzed. Astonishingly, YClon can effortlessly handle up to 2 million Ig sequences on a standard laptop computer. This enables in-depth analysis of large and numerous antibody repertoires. AVAILABILITY AND IMPLEMENTATION YClon was implemented in Python3 and is freely available on GitHub.
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Affiliation(s)
- João Gervásio
- Laboratory of Synthetic Biology and Biomimetics, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil
| | - Alice Ferreira
- Laboratory of Synthetic Biology and Biomimetics, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil
| | - Liza F Felicori
- Laboratory of Synthetic Biology and Biomimetics, Departamento de Bioquímica e Imunologia, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil.
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21
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Feng B, Zheng D, Yang L, Su Z, Tang L, Zhu Y, Xu X, Wang Q, Lin Q, Hu J, Lin M, Huang L, Zhou X, Liu H, Li S, Pan W, Shi R, Lu Y, Wu B, Ding B, Wang Z, Guo J, Zhang Z, Zheng G, Liu Y. Post-hospitalization rehabilitation alleviates long-term immune repertoire alteration in COVID-19 convalescent patients. Cell Prolif 2023; 56:e13450. [PMID: 36938980 PMCID: PMC10542649 DOI: 10.1111/cpr.13450] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/27/2023] [Accepted: 03/02/2023] [Indexed: 03/21/2023] Open
Abstract
The global pandemic of Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an once-in-a-lifetime public health crisis. Among hundreds of millions of people who have contracted with or are being infected with COVID-19, the question of whether COVID-19 infection may cause long-term health concern, even being completely recovered from the disease clinically, especially immune system damage, needs to be addressed. Here, we performed seven-chain adaptome immune repertoire analyses on convalescent COVID-19 patients who have been discharged from hospitals for at least 6 months. Surprisingly, we discovered lymphopenia, reduced number of unique CDR3s, and reduced diversity of the TCR/BCR immune repertoire in convalescent COVID-19 patients. In addition, the BCR repertoire appears to be activated, which is consistent with the protective antibody titres, but serological experiments reveal significantly lower IL-4 and IL-7 levels in convalescent patients compared to those in healthy controls. Finally, in comparison with convalescent patients who did not receive post-hospitalization rehabilitation, the convalescent patients who received post-hospitalization rehabilitation had attenuated immune repertoire abnormality, almost back to the level of healthy control, despite no detectable clinic demographic difference. Overall, we report the potential long-term immunological impairment for COVID-19 infection, and correction of this impairment via post-hospitalization rehabilitation may offer a new prospect for COVID-19 recovery strategy.
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22
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Arons E, Henry K, Haas C, Gould M, Tsintolas J, Mauter J, Zhou H, Burbelo PD, Cohen JI, Kreitman RJ. Characterization of B-cell receptor clonality and immunoglobulin gene usage at multiple time points during active SARS-CoV-2 infection. J Med Virol 2023; 95:e29179. [PMID: 37877800 DOI: 10.1002/jmv.29179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/05/2023] [Accepted: 10/06/2023] [Indexed: 10/26/2023]
Abstract
Although monoclonal antibodies to the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) are known, B-cell receptor repertoire and its change in patients during coronavirus disease-2019 (COVID-19) progression is underreported. We aimed to study this molecularly. We used immunoglobulin heavy chain (IGH) variable region (IGHV) spectratyping and next-generation sequencing of peripheral blood B-cell genomic DNA collected at multiple time points during disease evolution to study B-cell response to SARS-CoV-2 infection in 14 individuals with acute COVID-19. We found a broad distribution of responding B-cell clones. The IGH gene usage was not significantly skewed but frequencies of individual IGH genes changed repeatedly. We found predominant usage of unmutated and low mutation-loaded IGHV rearrangements characterizing naïve and extrafollicular B cells among the majority of expanded peripheral B-cell clonal lineages at most tested time points in most patients. IGH rearrangement usage showed no apparent relation to anti-SARS-CoV-2 antibody titers. Some patients demonstrated mono/oligoclonal populations carrying highly mutated IGHV rearrangements indicating antigen experience at some of the time points tested, including even before anti-SARS-CoV-2 antibodies were detected. We present evidence demonstrating that the B-cell response to SARS-CoV-2 is individual and includes different lineages of B cells at various time points during COVID-19 progression.
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Affiliation(s)
- Evgeny Arons
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | | | - Christopher Haas
- Medstar Franklin Square Medical Center, Baltimore, Maryland, USA
| | - Mory Gould
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Jack Tsintolas
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Jack Mauter
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Hong Zhou
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, Maryland, USA
| | - Peter D Burbelo
- National Institute of Dental and Craniofacial Research, NIH, Bethesda, Maryland, USA
| | - Jeffrey I Cohen
- Laboratory of Infectious Diseases, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, Maryland, USA
| | - Robert J Kreitman
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, Maryland, USA
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23
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Moyo S, Simbayi LC, Zuma K, Zungu N, Marinda E, Jooste S, Ramlagan S, Fortuin M, Singh B, Mabaso M, Reddy T, Parker WA, Naidoo I, Manda S, Goga A, Ngandu N, Cawood C, Moore PL, Puren A. Seroprevalence survey of anti-SARS-CoV-2 antibody and associated factors in South Africa: Findings of the 2020-2021 population-based household survey. PLOS GLOBAL PUBLIC HEALTH 2023; 3:e0002358. [PMID: 37747851 PMCID: PMC10519586 DOI: 10.1371/journal.pgph.0002358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 08/13/2023] [Indexed: 09/27/2023]
Abstract
Population-based serological testing is important to understand the epidemiology and estimate the true cumulative incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to inform public health interventions. This study reports findings of a national household population SARS-CoV-2 serosurvey in people 12 years and older in South Africa. This cross-sectional multi-stage random stratified cluster survey undertaken from November 2020 to June 2021 collected sociodemographic data, medical history, behavioural data, and blood samples from consenting participants. The samples were tested for SARS-CoV-2 antibodies using the Roche ElecsysAnti-SARS-CoV-2 chemiluminescence immunoassay (CLIA) Total Antibody Test. The survey data were weighted by age, race, sex, and province with final individual weights benchmarked against the 2020 mid-year population estimates and accounted for clustering. Descriptive statistics summarize the characteristics of participants and seroprevalence. Logistic regression analyses were used to identify factors associated with seropositivity. From 13290 survey participants (median age 33 years, interquartile range (IQR) 23-46 years), SARS-CoV-2 seroprevalence was 37.8% [95% Confidence Interval (CI) 35.4-40.4] and varied substantially across the country's nine provinces, and by sex, age and locality type. In the final adjusted model, the odds of seropositivity were higher in women than in men [aOR = 1.3 (95% CI: 1.0-1.6), p = 0.027], and those living with HIV (self-report) [aOR = 1.6 (95% CI: 1.0-2.4), p = 0.031]. The odds were lower among those 50 years and older compared to adolescents 12-19 years old [aOR = 0.6 (95% CI: 0.5-0.8), p<0.001] and in those who did not attend events or gatherings [aOR = 0.7 (95% CI: 0.6-1.0), p = 0.020]. The findings help us understand the epidemiology of SARS-CoV-2 within different regions in a low-middle-income country. The survey highlights the higher risk of infection in women in South Africa likely driven by their home and workplace roles and also highlighted a need to actively target and include younger people in the COVID-19 response.
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Affiliation(s)
- Sizulu Moyo
- Human Sciences Research Council, Pretoria, South Africa
- School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Leickness C. Simbayi
- Human Sciences Research Council, Pretoria, South Africa
- Department of Psychiatry & Mental Health, University of Cape Town, Cape Town, South Africa
| | - Khangelani Zuma
- Human Sciences Research Council, Pretoria, South Africa
- School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Nompumelelo Zungu
- Human Sciences Research Council, Pretoria, South Africa
- Department of Psychology, University of Pretoria, Pretoria, South Africa
| | - Edmore Marinda
- Human Sciences Research Council, Pretoria, South Africa
- School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Sean Jooste
- Human Sciences Research Council, Pretoria, South Africa
| | | | - Mirriam Fortuin
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Beverley Singh
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | | | - Tarylee Reddy
- Biostatistics Research Unit (TR and SMa)/ HIV and other Infectious Diseases Research Unit (AG and NN), South African Medical Research Council, Cape Town, South Africa
| | | | | | - Samuel Manda
- Biostatistics Research Unit (TR and SMa)/ HIV and other Infectious Diseases Research Unit (AG and NN), South African Medical Research Council, Cape Town, South Africa
| | - Ameena Goga
- Biostatistics Research Unit (TR and SMa)/ HIV and other Infectious Diseases Research Unit (AG and NN), South African Medical Research Council, Cape Town, South Africa
- Department of Paediatrics and Child Health, University of Pretoria, Pretoria, South Africa
| | - Nobubelo Ngandu
- Biostatistics Research Unit (TR and SMa)/ HIV and other Infectious Diseases Research Unit (AG and NN), South African Medical Research Council, Cape Town, South Africa
| | | | - Penny L. Moore
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- SAMRC Antibody Immunity Research Unit, Division of Virology and Immunology, University of the Witwatersrand, Johannesburg, South Africa
| | - Adrian Puren
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- Division of Virology, School of Pathology, University of the Witwatersrand Medical School, Johannesburg, South Africa
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Curtis NC, Shin S, Hederman AP, Connor RI, Wieland-Alter WF, Ionov S, Boylston J, Rose J, Sakharkar M, Dorman DB, Dessaint JA, Gwilt LL, Crowley AR, Feldman J, Hauser BM, Schmidt AG, Ashare A, Walker LM, Wright PF, Ackerman ME, Lee J. Characterization of SARS-CoV-2 Convalescent Patients' Serological Repertoire Reveals High Prevalence of Iso-RBD Antibodies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.08.556349. [PMID: 37745524 PMCID: PMC10515772 DOI: 10.1101/2023.09.08.556349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
While our understanding of SARS-CoV-2 pathogenesis and antibody responses following infection and vaccination has improved tremendously since the outbreak in 2019, the sequence identities and relative abundances of the individual constituent antibody molecules in circulation remain understudied. Using Ig-Seq, we proteomically profiled the serological repertoire specific to the whole ectodomain of SARS-CoV-2 prefusion-stabilized spike (S) as well as to the receptor binding domain (RBD) over a 6-month period in four subjects following SARS-CoV-2 infection before SARS-CoV-2 vaccines were available. In each individual, we identified between 59 and 167 unique IgG clonotypes in serum. To our surprise, we discovered that ∼50% of serum IgG specific for RBD did not recognize prefusion-stabilized S (referred to as iso-RBD antibodies), suggesting that a significant fraction of serum IgG targets epitopes on RBD inaccessible on the prefusion-stabilized conformation of S. On the other hand, the abundance of iso-RBD antibodies in nine individuals who received mRNA-based COVID-19 vaccines encoding prefusion-stabilized S was significantly lower (∼8%). We expressed a panel of 12 monoclonal antibodies (mAbs) that were abundantly present in serum from two SARS-CoV-2 infected individuals, and their binding specificities to prefusion-stabilized S and RBD were all in agreement with the binding specificities assigned based on the proteomics data, including 1 iso-RBD mAb which bound to RBD but not to prefusion-stabilized S. 2 of 12 mAbs demonstrated neutralizing activity, while other mAbs were non-neutralizing. 11 of 12 mAbs also bound to S (B.1.351), but only 1 maintained binding to S (B.1.1.529). This particular mAb binding to S (B.1.1.529) 1) represented an antibody lineage that comprised 43% of the individual's total S-reactive serum IgG binding titer 6 months post-infection, 2) bound to the S from a related human coronavirus, HKU1, and 3) had a high somatic hypermutation level (10.9%), suggesting that this antibody lineage likely had been elicited previously by pre-pandemic coronavirus and was re-activated following the SARS-CoV-2 infection. All 12 mAbs demonstrated their ability to engage in Fc-mediated effector function activities. Collectively, our study provides a quantitative overview of the serological repertoire following SARS-CoV-2 infection and the significant contribution of iso-RBD antibodies, demonstrating how vaccination strategies involving prefusion-stabilized S may have reduced the elicitation of iso-RBD serum antibodies which are unlikely to contribute to protection.
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25
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Uzun S, Zinner CP, Beenen AC, Alborelli I, Bartoszek EM, Yeung J, Calgua B, Reinscheid M, Bronsert P, Stalder AK, Haslbauer JD, Vosbeck J, Mazzucchelli L, Hoffmann T, Terracciano LM, Hutter G, Manz M, Panne I, Boettler T, Hofmann M, Bengsch B, Heim MH, Bernsmeier C, Jiang S, Tzankov A, Terziroli Beretta-Piccoli B, Matter MS. Morphologic and molecular analysis of liver injury after SARS-CoV-2 vaccination reveals distinct characteristics. J Hepatol 2023; 79:666-676. [PMID: 37290592 PMCID: PMC10245467 DOI: 10.1016/j.jhep.2023.05.020] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 05/10/2023] [Accepted: 05/19/2023] [Indexed: 06/10/2023]
Abstract
BACKGROUND & AIMS Liver injury after COVID-19 vaccination is very rare and shows clinical and histomorphological similarities with autoimmune hepatitis (AIH). Little is known about the pathophysiology of COVID-19 vaccine-induced liver injury (VILI) and its relationship to AIH. Therefore, we compared VILI with AIH. METHODS Formalin-fixed and paraffin-embedded liver biopsy samples from patients with VILI (n = 6) and from patients with an initial diagnosis of AIH (n = 9) were included. Both cohorts were compared by histomorphological evaluation, whole-transcriptome and spatial transcriptome sequencing, multiplex immunofluorescence, and immune repertoire sequencing. RESULTS Histomorphology was similar in both cohorts but showed more pronounced centrilobular necrosis in VILI. Gene expression profiling showed that mitochondrial metabolism and oxidative stress-related pathways were more and interferon response pathways were less enriched in VILI. Multiplex analysis revealed that inflammation in VILI was dominated by CD8+ effector T cells, similar to drug-induced autoimmune-like hepatitis. In contrast, AIH showed a dominance of CD4+ effector T cells and CD79a+ B and plasma cells. T-cell receptor (TCR) and B-cell receptor sequencing showed that T and B cell clones were more dominant in VILI than in AIH. In addition, many T cell clones detected in the liver were also found in the blood. Interestingly, analysis of TCR beta chain and Ig heavy chain variable-joining gene usage further showed that TRBV6-1, TRBV5-1, TRBV7-6, and IgHV1-24 genes are used differently in VILI than in AIH. CONCLUSIONS Our analyses support that SARS-CoV-2 VILI is related to AIH but also shows distinct differences from AIH in histomorphology, pathway activation, cellular immune infiltrates, and TCR usage. Therefore, VILI may be a separate entity, which is distinct from AIH and more closely related to drug-induced autoimmune-like hepatitis. IMPACT AND IMPLICATIONS Little is known about the pathophysiology of COVID-19 vaccine-induced liver injury (VILI). Our analysis shows that COVID-19 VILI shares some similarities with autoimmune hepatitis, but also has distinct differences such as increased activation of metabolic pathways, a more prominent CD8+ T cell infiltrate, and an oligoclonal T and B cell response. Our findings suggest that VILI is a distinct disease entity. Therefore, there is a good chance that many patients with COVID-19 VILI will recover completely and will not develop long-term autoimmune hepatitis.
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Affiliation(s)
- Sarp Uzun
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | - Carl P Zinner
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | - Amke C Beenen
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | - Ilaria Alborelli
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | - Ewelina M Bartoszek
- Microscopy Core Facility, Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Jason Yeung
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Byron Calgua
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | - Matthias Reinscheid
- Department of Medicine II (Gastroenterology, Hepatology, Endocrinology and Infectious Diseases), Freiburg University Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Peter Bronsert
- Institute for Surgical Pathology, Freiburg University Medical Center, University of Freiburg, Freiburg, Germany; Core Facility for Histopathology and Digital Pathology, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Anna K Stalder
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | | | - Juerg Vosbeck
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | | | | | - Luigi M Terracciano
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy; IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Gregor Hutter
- Brain Tumor Immunotherapy Lab, Department of Biomedicine, University of Basel, Basel, Switzerland; Department of Neurosurgery, University Hospital Basel, Basel, Switzerland
| | - Michael Manz
- Gastroenterology and Hepatology, University Centre for Gastrointestinal and Liver Diseases Basel, Switzerland
| | - Isabelle Panne
- Gastroenterology and Hepatology, University Centre for Gastrointestinal and Liver Diseases Basel, Switzerland
| | - Tobias Boettler
- Department of Medicine II (Gastroenterology, Hepatology, Endocrinology and Infectious Diseases), Freiburg University Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Maike Hofmann
- Department of Medicine II (Gastroenterology, Hepatology, Endocrinology and Infectious Diseases), Freiburg University Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Bertram Bengsch
- Department of Medicine II (Gastroenterology, Hepatology, Endocrinology and Infectious Diseases), Freiburg University Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, Germany; Partner Site Freiburg, German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Markus H Heim
- Gastroenterology and Hepatology, University Centre for Gastrointestinal and Liver Diseases Basel, Switzerland; Department of Biomedicine, University of Basel, Switzerland
| | - Christine Bernsmeier
- Gastroenterology and Hepatology, University Centre for Gastrointestinal and Liver Diseases Basel, Switzerland; Department of Biomedicine, University of Basel, Switzerland
| | - Sizun Jiang
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Pathology, Dana Farber Cancer Institute, Boston, MA, USA; Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Alexandar Tzankov
- Institute of Pathology, University Hospital Basel, Basel, Switzerland
| | - Benedetta Terziroli Beretta-Piccoli
- Faculty of Biomedical Sciences, Università Della Svizzera Italiana, Lugano, Switzerland; Epatocentro Ticino, Lugano, Switzerland; MowatLabs, Faculty of Life Sciences and Medicine, King's College London, King's College Hospital, London, UK
| | - Matthias S Matter
- Institute of Pathology, University Hospital Basel, Basel, Switzerland.
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26
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Ivanova EN, Shwetar J, Devlin JC, Buus TB, Gray-Gaillard S, Koide A, Cornelius A, Samanovic MI, Herrera A, Mimitou EP, Zhang C, Karmacharya T, Desvignes L, Ødum N, Smibert P, Ulrich RJ, Mulligan MJ, Koide S, Ruggles KV, Herati RS, Koralov SB. mRNA COVID-19 vaccine elicits potent adaptive immune response without the persistent inflammation seen in SARS-CoV-2 infection. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2021.04.20.21255677. [PMID: 33907755 PMCID: PMC8077568 DOI: 10.1101/2021.04.20.21255677] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
SARS-CoV-2 infection and vaccination elicit potent immune responses. Our study presents a comprehensive multimodal single-cell dataset of peripheral blood of patients with acute COVID-19 and of healthy volunteers before and after receiving the SARS-CoV-2 mRNA vaccine and booster. We compared host immune responses to the virus and vaccine using transcriptional profiling, coupled with B/T cell receptor repertoire reconstruction. COVID-19 patients displayed an enhanced interferon signature and cytotoxic gene upregulation, absent in vaccine recipients. These findings were validated in an independent dataset. Analysis of B and T cell repertoires revealed that, while the majority of clonal lymphocytes in COVID-19 patients were effector cells, clonal expansion was more evident among circulating memory cells in vaccine recipients. Furthermore, while clonal αβ T cell responses were observed in both COVID-19 patients and vaccine recipients, dramatic expansion of clonal γδT cells was found only in infected individuals. Our dataset enables comparative analyses of immune responses to infection versus vaccination, including clonal B and T cell responses. Integrating our data with publicly available datasets allowed us to validate our findings in larger cohorts. To our knowledge, this is the first dataset to include comprehensive profiling of longitudinal samples from healthy volunteers pre/post SARS-CoV-2 vaccine and booster.
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27
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Vieira MC, Palm AKE, Stamper CT, Tepora ME, Nguyen KD, Pham TD, Boyd SD, Wilson PC, Cobey S. Germline-encoded specificities and the predictability of the B cell response. PLoS Pathog 2023; 19:e1011603. [PMID: 37624867 PMCID: PMC10484431 DOI: 10.1371/journal.ppat.1011603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 09/07/2023] [Accepted: 08/07/2023] [Indexed: 08/27/2023] Open
Abstract
Antibodies result from the competition of B cell lineages evolving under selection for improved antigen recognition, a process known as affinity maturation. High-affinity antibodies to pathogens such as HIV, influenza, and SARS-CoV-2 are frequently reported to arise from B cells whose receptors, the precursors to antibodies, are encoded by particular immunoglobulin alleles. This raises the possibility that the presence of particular germline alleles in the B cell repertoire is a major determinant of the quality of the antibody response. Alternatively, initial differences in germline alleles' propensities to form high-affinity receptors might be overcome by chance events during affinity maturation. We first investigate these scenarios in simulations: when germline-encoded fitness differences are large relative to the rate and effect size variation of somatic mutations, the same germline alleles persistently dominate the response of different individuals. In contrast, if germline-encoded advantages can be easily overcome by subsequent mutations, allele usage becomes increasingly divergent over time, a pattern we then observe in mice experimentally infected with influenza virus. We investigated whether affinity maturation might nonetheless strongly select for particular amino acid motifs across diverse genetic backgrounds, but we found no evidence of convergence to similar CDR3 sequences or amino acid substitutions. These results suggest that although germline-encoded specificities can lead to similar immune responses between individuals, diverse evolutionary routes to high affinity limit the genetic predictability of responses to infection and vaccination.
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Affiliation(s)
- Marcos C. Vieira
- Department of Ecology and Evolution, University of Chicago, Chicago, United States of America
| | - Anna-Karin E. Palm
- Department of Medicine, Section of Rheumatology, University of Chicago, Chicago, United States of America
| | - Christopher T. Stamper
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden
- Committee on Immunology, University of Chicago, Chicago, United States of America
| | - Micah E. Tepora
- Department of Medicine, Section of Rheumatology, University of Chicago, Chicago, United States of America
| | - Khoa D. Nguyen
- Department of Pathology, Stanford University School of Medicine, Stanford, United States of America
| | - Tho D. Pham
- Department of Pathology, Stanford University School of Medicine, Stanford, United States of America
| | - Scott D. Boyd
- Department of Pathology, Stanford University School of Medicine, Stanford, United States of America
| | - Patrick C. Wilson
- Department of Medicine, Section of Rheumatology, University of Chicago, Chicago, United States of America
- Gale and Ira Drukier Institute for Children’s Health, Weill Cornell Medicine, New York City, United States of America
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, United States of America
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28
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Chiang HL, Liang KH, Lu RM, Kuo TW, Lin YL, Wu HC. Broadly neutralizing human antibodies against Omicron subvariants of SARS-CoV-2. J Biomed Sci 2023; 30:59. [PMID: 37525188 PMCID: PMC10388472 DOI: 10.1186/s12929-023-00955-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 07/18/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND The COVID-19 pandemic continues to pose a significant worldwide threat to human health, as emerging SARS-CoV-2 Omicron variants exhibit resistance to therapeutic antibodies and the ability to evade vaccination-induced antibodies. Here, we aimed to identify human antibodies (hAbs) from convalescent patients that are potent and broadly neutralizing toward Omicron sublineages. METHODS Using a single B-cell cloning approach, we isolated BA.5 specific human antibodies. We further examined the neutralizing activities of the most promising neutralizing hAbs toward different variants of concern (VOCs) with pseudotyped virus. RESULTS Sixteen hAbs showed strong neutralizing activities against Omicron BA.5 with low IC50 values (IC50 < 20 ng/mL). Among four of the most promising neutralizing hAbs (RBD-hAb-B22, -B23, -B25 and -B34), RBD-hAb-B22 exhibited the most potent and broad neutralization profiles across Omicron subvariant pseudoviruses, with low IC50 values (7.7-41.6 ng/mL) and a low PRNT50 value (3.8 ng/mL) in plaque assays with authentic BA.5. It also showed potent therapeutic effects in BA.5-infected K18-hACE2 mice. CONCLUSIONS Thus, our efficient screening of BA.5-specific neutralizing hAbs from breakthrough infectious convalescent donors successfully yielded hAbs with potent therapeutic potential against multiple SARS-CoV-2 variants.
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Affiliation(s)
- Hsiao-Ling Chiang
- Biomedical Translation Research Center (BioTReC), Academia Sinica, Taipei, Taiwan
| | - Kang-Hao Liang
- Biomedical Translation Research Center (BioTReC), Academia Sinica, Taipei, Taiwan
| | - Ruei-Min Lu
- Biomedical Translation Research Center (BioTReC), Academia Sinica, Taipei, Taiwan
| | - Ting-Wen Kuo
- Biomedical Translation Research Center (BioTReC), Academia Sinica, Taipei, Taiwan
| | - Yi-Ling Lin
- Biomedical Translation Research Center (BioTReC), Academia Sinica, Taipei, Taiwan
- Institute of Biomedical Sciences (IBMS), Academia Sinica, Taipei, Taiwan
| | - Han-Chung Wu
- Biomedical Translation Research Center (BioTReC), Academia Sinica, Taipei, Taiwan.
- Institute of Cellular and Organismic Biology (ICOB), Academia Sinica, No. 128, Academia Road, Section 2, Nankang, Taipei, 11529, Taiwan.
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29
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Lopes de Assis F, Hoehn KB, Zhang X, Kardava L, Smith CD, El Merhebi O, Buckner CM, Trihemasava K, Wang W, Seamon CA, Chen V, Schaughency P, Cheung F, Martins AJ, Chiang CI, Li Y, Tsang JS, Chun TW, Kleinstein SH, Moir S. Tracking B cell responses to the SARS-CoV-2 mRNA-1273 vaccine. Cell Rep 2023; 42:112780. [PMID: 37440409 PMCID: PMC10529190 DOI: 10.1016/j.celrep.2023.112780] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 03/15/2023] [Accepted: 06/23/2023] [Indexed: 07/15/2023] Open
Abstract
Protective immunity following vaccination is sustained by long-lived antibody-secreting cells and resting memory B cells (MBCs). Responses to two-dose SARS-CoV-2 mRNA-1273 vaccination are evaluated longitudinally by multimodal single-cell analysis in three infection-naïve individuals. Integrated surface protein, transcriptomics, and B cell receptor (BCR) repertoire analysis of sorted plasmablasts and spike+ (S-2P+) and S-2P- B cells reveal clonal expansion and accumulating mutations among S-2P+ cells. These cells are enriched in a cluster of immunoglobulin G-expressing MBCs and evolve along a bifurcated trajectory rooted in CXCR3+ MBCs. One branch leads to CD11c+ atypical MBCs while the other develops from CD71+ activated precursors to resting MBCs, the dominant population at month 6. Among 12 evolving S-2P+ clones, several are populated with plasmablasts at early timepoints as well as CD71+ activated and resting MBCs at later timepoints, and display intra- and/or inter-cohort BCR convergence. These relationships suggest a coordinated and predictable evolution of SARS-CoV-2 vaccine-generated MBCs.
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Affiliation(s)
- Felipe Lopes de Assis
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kenneth B Hoehn
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA
| | - Xiaozhen Zhang
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lela Kardava
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Connor D Smith
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Omar El Merhebi
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Clarisa M Buckner
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Krittin Trihemasava
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Wei Wang
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Catherine A Seamon
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Vicky Chen
- Integrated Data Sciences Section, Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Paul Schaughency
- Integrated Data Sciences Section, Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Foo Cheung
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Andrew J Martins
- Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Chi-I Chiang
- Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA
| | - Yuxing Li
- Institute for Bioscience and Biotechnology Research, Rockville, MD 20850, USA; Department of Microbiology and Immunology and Center for Biomolecular Therapeutics, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - John S Tsang
- NIH Center for Human Immunology, NIAID, NIH, Bethesda, MD 20892, USA; Multiscale Systems Biology Section, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD 20892, USA
| | - Tae-Wook Chun
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA
| | - Steven H Kleinstein
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520, USA
| | - Susan Moir
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA.
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Troelnikov A, Armour B, Putty T, Aggarwal A, Akerman A, Milogiannakis V, Chataway T, King J, Turville SG, Gordon TP, Wang JJ. Immunoglobulin repertoire restriction characterizes the serological responses of patients with predominantly antibody deficiency. J Allergy Clin Immunol 2023; 152:290-301.e7. [PMID: 36965845 DOI: 10.1016/j.jaci.2023.02.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 02/06/2023] [Accepted: 02/09/2023] [Indexed: 03/27/2023]
Abstract
BACKGROUND Predominantly antibody deficiency (PAD) is the most common category of inborn errors of immunity and is underpinned by impaired generation of appropriate antibody diversity and quantity. In the clinic, responses are interrogated by assessment of vaccination responses, which is central to many PAD diagnoses. However, the composition of the generated antibody repertoire is concealed from traditional quantitative measures of serological responses. Leveraging modern mass spectrometry-based proteomics (MS-proteomics), it is possible to elaborate the molecular features of specific antibody repertoires, which may address current limitations of diagnostic vaccinology. OBJECTIVES We sought to evaluate serum antibody responses in patients with PAD following vaccination with a neo-antigen (severe acute respiratory syndrome coronavirus-2 vaccination) using MS-proteomics. METHODS Following severe acute respiratory syndrome coronavirus-2 vaccination, serological responses in individuals with PAD and healthy controls (HCs) were assessed by anti-S1 subunit ELISA and neutralization assays. Purified anti-S1 subunit IgG and IgM was profiled by MS-proteomics for IGHV subfamily usage and somatic hypermutation analysis. RESULTS Twelve patients with PAD who were vaccine-responsive were recruited with 11 matched vaccinated HCs. Neutralization and end point anti-S1 titers were lower in PAD. All subjects with PAD demonstrated restricted anti-S1 IgG antibody repertoires, with usage of <5 IGHV subfamilies (median: 3; range 2-4), compared to ≥5 for the 11 HC subjects (P < .001). IGHV3-7 utilization was far less common in patients with PAD than in HCs (2 of 12 vs 10 of 11; P = .001). Amino acid substitutions due to somatic hypermutation per subfamily did not differ between groups. Anti-S1 IgM was present in 64% and 50% of HC and PAD cohorts, respectively, and did not differ significantly between HCs and patients with PAD. CONCLUSIONS This study demonstrates the breadth of anti-S1 antibodies elicited by vaccination at the proteome level and identifies stereotypical restriction of IGHV utilization in the IgG repertoire in patients with PAD compared with HC subjects. Despite uniformly pauci-clonal antibody repertoires some patients with PAD generated potent serological responses, highlighting a possible limitation of traditional serological techniques. These findings suggest that IgG repertoire restriction is a key feature of antibody repertoires in PAD.
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Affiliation(s)
- Alexander Troelnikov
- College of Medicine and Public Health, Flinders University, Bedford Park, Australia; SA Pathology, Adelaide, Australia.
| | - Bridie Armour
- College of Medicine and Public Health, Flinders University, Bedford Park, Australia; SA Pathology, Adelaide, Australia
| | - Trishni Putty
- College of Medicine and Public Health, Flinders University, Bedford Park, Australia; SA Pathology, Adelaide, Australia
| | | | | | | | - Tim Chataway
- College of Medicine and Public Health, Flinders University, Bedford Park, Australia
| | - Jovanka King
- SA Pathology, Adelaide, Australia; Women's and Children's Hospital Network, Adelaide, Australia; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, Australia
| | | | - Tom P Gordon
- College of Medicine and Public Health, Flinders University, Bedford Park, Australia; SA Pathology, Adelaide, Australia; Flinders Medical Centre, Bedford Park, Australia
| | - Jing Jing Wang
- College of Medicine and Public Health, Flinders University, Bedford Park, Australia; SA Pathology, Adelaide, Australia
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Mohandas S, Jagannathan P, Henrich TJ, Sherif ZA, Bime C, Quinlan E, Portman MA, Gennaro M, Rehman J. Immune mechanisms underlying COVID-19 pathology and post-acute sequelae of SARS-CoV-2 infection (PASC). eLife 2023; 12:e86014. [PMID: 37233729 PMCID: PMC10219649 DOI: 10.7554/elife.86014] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 05/18/2023] [Indexed: 05/27/2023] Open
Abstract
With a global tally of more than 500 million cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections to date, there are growing concerns about the post-acute sequelae of SARS-CoV-2 infection (PASC), also known as long COVID. Recent studies suggest that exaggerated immune responses are key determinants of the severity and outcomes of the initial SARS-CoV-2 infection as well as subsequent PASC. The complexity of the innate and adaptive immune responses in the acute and post-acute period requires in-depth mechanistic analyses to identify specific molecular signals as well as specific immune cell populations which promote PASC pathogenesis. In this review, we examine the current literature on mechanisms of immune dysregulation in severe COVID-19 and the limited emerging data on the immunopathology of PASC. While the acute and post-acute phases may share some parallel mechanisms of immunopathology, it is likely that PASC immunopathology is quite distinct and heterogeneous, thus requiring large-scale longitudinal analyses in patients with and without PASC after an acute SARS-CoV-2 infection. By outlining the knowledge gaps in the immunopathology of PASC, we hope to provide avenues for novel research directions that will ultimately lead to precision therapies which restore healthy immune function in PASC patients.
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Affiliation(s)
- Sindhu Mohandas
- Division of Infectious Diseases, Children’s Hospital Los Angeles, Keck School of Medicine, University of Southern CaliforniaLos AngelesUnited States
| | - Prasanna Jagannathan
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford UniversityStanfordUnited States
| | - Timothy J Henrich
- Division of Experimental Medicine, University of California, San FranciscoSan FranciscoUnited States
| | - Zaki A Sherif
- Department of Biochemistry & Molecular Biology, Howard University College of MedicineWashingtonUnited States
| | - Christian Bime
- Division of Pulmonary, Allergy, Critical Care & Sleep Medicine, Department of Medicine, University of Arizona College of MedicineTucsonUnited States
| | - Erin Quinlan
- National Center for Complementary and Integrative Health, National Institutes of HealthBethesdaUnited States
| | - Michael A Portman
- Seattle Children’s Hospital, Division of Pediatric Cardiology, Department of Pediatrics, University of WashingtonSeattleUnited States
| | - Marila Gennaro
- Public Health Research Institute and Department of Medicine, Rutgers New Jersey Medical SchoolNewarkUnited States
| | - Jalees Rehman
- Department of Biochemistry and Molecular Genetics, University of Illinois, College of MedicineChicagoUnited States
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32
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Liu KJ, Zelazowska MA, McBride KM. The Longitudinal Analysis of Convergent Antibody VDJ Regions in SARS-CoV-2-Positive Patients Using RNA-Seq. Viruses 2023; 15:1253. [PMID: 37376553 DOI: 10.3390/v15061253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Revised: 05/23/2023] [Accepted: 05/25/2023] [Indexed: 06/29/2023] Open
Abstract
Severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) is an ongoing pandemic that continues to evolve and reinfect individuals. To understand the convergent antibody responses that evolved over the course of the pandemic, we evaluated the immunoglobulin repertoire of individuals infected by different SARS-CoV-2 variants for similarity between patients. We utilized four public RNA-seq data sets collected between March 2020 and March 2022 from the Gene Expression Omnibus (GEO) in our longitudinal analysis. This covered individuals infected with Alpha and Omicron variants. In total, from 269 SARS-CoV-2-positive patients and 26 negative patients, 629,133 immunoglobulin heavy-chain variable region V(D)J sequences were reconstructed from sequencing data. We grouped samples based on the SARS-CoV-2 variant type and/or the time they were collected from patients. Our comparison of patients within each SARS-CoV-2-positive group found 1011 common V(D)Js (same V gene, J gene and CDR3 amino acid sequence) shared by more than one patient and no common V(D)Js in the noninfected group. Taking convergence into account, we clustered based on similar CDR3 sequence and identified 129 convergent clusters from the SARS-CoV-2-positive groups. Within the top 15 clusters, 4 contain known anti-SARS-CoV-2 immunoglobulin sequences with 1 cluster confirmed to cross-neutralize variants from Alpha to Omicron. In our analysis of longitudinal groups that include Alpha and Omicron variants, we find that 2.7% of the common CDR3s found within groups were also present in more than one group. Our analysis reveals common and convergent antibodies, which include anti-SARS-CoV-2 antibodies, in patient groups over various stages of the pandemic.
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Affiliation(s)
- Kate J Liu
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Monika A Zelazowska
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Kevin M McBride
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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Gaspar-Castillo C, Rodríguez MH, Ortiz-Navarrete V, Alpuche-Aranda CM, Martinez-Barnetche J. Structural and immunological basis of cross-reactivity between dengue and Zika infections: Implications in serosurveillance in endemic regions. Front Microbiol 2023; 14:1107496. [PMID: 37007463 PMCID: PMC10063793 DOI: 10.3389/fmicb.2023.1107496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 02/24/2023] [Indexed: 03/19/2023] Open
Abstract
Dengue and Zika are arthropod-borne viral diseases present in more than 100 countries around the world. In the past decade, Zika emerged causing widespread outbreaks in new regions, where dengue has been endemic-epidemic for a long period. The wide and extensive dissemination of the mosquito vectors, Aedes aegypti, and Ae. albopictus, favor the co-existence of both infections in the same regions. Together with an important proportion of asymptomatic infections, similar clinical manifestations, and a short time window for acute infection confirmatory tests, it is difficult to differentially estimate both dengue and Zika incidence and prevalence. DENV and ZIKV flavivirus share high structural similarity, inducing a cross-reactive immune response that leads to false positives in serological tests particularly in secondary infections. This results in overestimation of recent Zika outbreaks seroprevalence in dengue endemic regions. In this review, we address the biological basis underlying DENV and ZIKV structural homology; the structural and cellular basis of immunological cross reactivity; and the resulting difficulties in measuring dengue and Zika seroprevalence. Finally, we offer a perspective about the need for more research to improve serological tests performance.
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Affiliation(s)
- Carlos Gaspar-Castillo
- Center for Infectious Diseases Research, National Institute of Public Health, Cuernavaca, Mexico
| | - Mario H. Rodríguez
- Center for Infectious Diseases Research, National Institute of Public Health, Cuernavaca, Mexico
| | - Vianney Ortiz-Navarrete
- Department of Molecular Biomedicine, Center for Research and Advanced Studies of the National Polytechnic Institute, Mexico City, Mexico
| | - Celia M. Alpuche-Aranda
- Center for Infectious Diseases Research, National Institute of Public Health, Cuernavaca, Mexico
- Celia M. Alpuche-Aranda,
| | - Jesus Martinez-Barnetche
- Center for Infectious Diseases Research, National Institute of Public Health, Cuernavaca, Mexico
- *Correspondence: Jesus Martinez-Barnetche,
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Demultiplexing Ig repertoires by parallel mRNA/DNA sequencing shows major differential alterations in severe COVID-19. iScience 2023; 26:106260. [PMID: 36845033 PMCID: PMC9942447 DOI: 10.1016/j.isci.2023.106260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 01/14/2023] [Accepted: 02/17/2023] [Indexed: 02/24/2023] Open
Abstract
To understand the fine differential elements that can lead to or prevent acute respiratory distress syndrome (ARDS) in COVID-19 patients, it is crucial to investigate the immune response architecture. We herein dissected the multiple layers of B cell responses by flow cytometry and Ig repertoire analysis from acute phase to recovery. Flow cytometry with FlowSOM analysis showed major changes associated with COVID-19 inflammation such as an increase of double-negative B-cells and ongoing plasma cell differentiation. This paralleled COVID-19-driven expansion of two disconnected B-cell repertoires. Demultiplexing successive DNA and RNA Ig repertoire patterns characterized an early expansion of IgG1 clonotypes with atypically long and uncharged CDR3, the abundance of this inflammatory repertoire being correlated with ARDS and likely pejorative. A superimposed convergent response included convergent anti-SARS-CoV-2 clonotypes. It featured progressively increasing somatic hypermutation together with normal-length or short CDR3 and it persisted until a quiescent memory B-cell stage after recovery.
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Vakhitova M, Myshkin M, Staroverov D, Shagina I, Izraelson M, Tverdova N, Britanova O, Merzlyak E. A Rapid Method for Detection of Antigen-Specific B Cells. Cells 2023; 12:cells12050774. [PMID: 36899909 PMCID: PMC10000731 DOI: 10.3390/cells12050774] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/17/2023] [Accepted: 02/24/2023] [Indexed: 03/05/2023] Open
Abstract
The global SARS-CoV-2 pandemic has united the efforts of many scientists all over the world to develop wet-lab techniques and computational approaches aimed at the identification of antigen-specific T and B cells. The latter provide specific humoral immunity that is essential for the survival of COVID-19 patients, and vaccine development has essentially been based on these cells. Here, we implemented an approach that integrates the sorting of antigen-specific B cells and B-cell receptor mRNA sequencing (BCR-seq), followed by computational analysis. This rapid and cost-efficient method allowed us to identify antigen-specific B cells in the peripheral blood of patients with severe COVID-19 disease. Subsequently, specific BCRs were extracted, cloned, and produced as full antibodies. We confirmed their reactivity toward the spike RBD domain. Such an approach can be effective for the monitoring and identification of B cells participating in an individual immune response.
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Affiliation(s)
- Mariia Vakhitova
- Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
| | - Mikhail Myshkin
- Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
| | - Dmitriy Staroverov
- Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
- Institute of Translation Medicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia
| | - Irina Shagina
- Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
- Institute of Translation Medicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia
| | - Mark Izraelson
- Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
| | - Nadezhda Tverdova
- Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
| | - Olga Britanova
- Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
- Institute of Translation Medicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia
- Correspondence: (O.B.); (E.M.)
| | - Ekaterina Merzlyak
- Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
- Institute of Translation Medicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia
- Correspondence: (O.B.); (E.M.)
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Yu H, Liu B, Zhang Y, Gao X, Wang Q, Xiang H, Peng X, Xie C, Wang Y, Hu P, Shi J, Shi Q, Zheng P, Feng C, Tang G, Liu X, Guo L, Lin X, Li J, Liu C, Huang Y, Yang N, Chen Q, Li Z, Su M, Yan Q, Pei R, Chen X, Liu L, Hu F, Liang D, Ke B, Ke C, Li F, He J, Wang M, Chen L, Xiong X, Tang X. Somatically hypermutated antibodies isolated from SARS-CoV-2 Delta infected patients cross-neutralize heterologous variants. Nat Commun 2023; 14:1058. [PMID: 36828833 PMCID: PMC9951844 DOI: 10.1038/s41467-023-36761-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 02/10/2023] [Indexed: 02/26/2023] Open
Abstract
SARS-CoV-2 Omicron variants feature highly mutated spike proteins with extraordinary abilities in evading antibodies isolated earlier in the pandemic. Investigation of memory B cells from patients primarily with breakthrough infections with the Delta variant enables isolation of a number of neutralizing antibodies cross-reactive to heterologous variants of concern (VOCs) including Omicron variants (BA.1-BA.4). Structural studies identify altered complementarity determining region (CDR) amino acids and highly unusual heavy chain CDR2 insertions respectively in two representative cross-neutralizing antibodies-YB9-258 and YB13-292. These features are putatively introduced by somatic hypermutation and they are heavily involved in epitope recognition to broaden neutralization breadth. Previously, insertions/deletions were rarely reported for antiviral antibodies except for those induced by HIV-1 chronic infections. These data provide molecular mechanisms for cross-neutralization of heterologous SARS-CoV-2 variants by antibodies isolated from Delta variant infected patients with implications for future vaccination strategy.
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Affiliation(s)
- Haisheng Yu
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
| | - Banghui Liu
- The State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, the Chinese Academy of Sciences, Guangzhou, China
| | - Yudi Zhang
- The State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, the Chinese Academy of Sciences, Guangzhou, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xijie Gao
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health-Guangdong Laboratory), Guangzhou, China
| | - Qian Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Haitao Xiang
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Xiaofang Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Caixia Xie
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Yaping Wang
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Peiyu Hu
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health-Guangdong Laboratory), Guangzhou, China
- Guangzhou Laboratory, Guangzhou International Bio Island, Guangzhou, China
| | - Jingrong Shi
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Quan Shi
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Pingqian Zheng
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health-Guangdong Laboratory), Guangzhou, China
- Guangzhou Laboratory, Guangzhou International Bio Island, Guangzhou, China
| | - Chengqian Feng
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Guofang Tang
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Xiaopan Liu
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Liliangzi Guo
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Xiumei Lin
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Jiaojiao Li
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Chuanyu Liu
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Yaling Huang
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Naibo Yang
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Qiuluan Chen
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health-Guangdong Laboratory), Guangzhou, China
| | - Zimu Li
- The State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, the Chinese Academy of Sciences, Guangzhou, China
| | - Mengzhen Su
- The State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, the Chinese Academy of Sciences, Guangzhou, China
- University of Science and Technology of China, Hefei, Anhui, China
| | - Qihong Yan
- The State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, the Chinese Academy of Sciences, Guangzhou, China
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Rongjuan Pei
- State Key Laboratory of Virology, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China
| | - Xinwen Chen
- Guangzhou Laboratory, Guangzhou International Bio Island, Guangzhou, China
- State Key Laboratory of Virology, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China
| | - Longqi Liu
- BGI-Shenzhen, Shenzhen, China
- China National GeneBank, BGI-Shenzhen, Shenzhen, China
| | - Fengyu Hu
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China
| | - Dan Liang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Bixia Ke
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China
| | - Changwen Ke
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
| | - Feng Li
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
| | - Jun He
- The State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, the Chinese Academy of Sciences, Guangzhou, China.
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health-Guangdong Laboratory), Guangzhou, China.
| | - Meiniang Wang
- BGI-Shenzhen, Shenzhen, China.
- China National GeneBank, BGI-Shenzhen, Shenzhen, China.
| | - Ling Chen
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
- The State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, the Chinese Academy of Sciences, Guangzhou, China.
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health-Guangdong Laboratory), Guangzhou, China.
- Guangzhou Laboratory, Guangzhou International Bio Island, Guangzhou, China.
| | - Xiaoli Xiong
- The State Key Laboratory of Respiratory Disease, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong Provincial Key Laboratory of Biocomputing, Center for Cell Lineage and Development, Guangzhou Institutes of Biomedicine and Health, the Chinese Academy of Sciences, Guangzhou, China.
- Bioland Laboratory (Guangzhou Regenerative Medicine and Health-Guangdong Laboratory), Guangzhou, China.
| | - Xiaoping Tang
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, China.
- Guangzhou Laboratory, Guangzhou International Bio Island, Guangzhou, China.
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Proof-of-Concept Analysis of B Cell Receptor Repertoire in COVID-19 Patients Undergoing ECMO by Single-Cell V(D)J and Gene Expression Sequencing. Curr Issues Mol Biol 2023; 45:1471-1482. [PMID: 36826040 PMCID: PMC9955795 DOI: 10.3390/cimb45020095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/06/2023] [Accepted: 02/08/2023] [Indexed: 02/12/2023] Open
Abstract
SARS-CoV-2, which causes COVID-19, has altered human activities all over the world and has become a global hazard to public health. Despite considerable advancements in pandemic containment techniques, in which vaccination played a key role, COVID-19 remains a global threat, particularly for frail patients and unvaccinated individuals, who may be more susceptible to developing ARDS. Several studies reported that patients with COVID-19-related ARDS who were treated with ECMO had a similar survival rate to those with COVID-19-unrelated ARDS. In order to shed light on the potential mechanisms underlying the COVID-19 infection, we conducted this proof-of-concept study using single-cell V(D)J and gene expression sequencing of B cells to examine the dynamic changes in the transcriptomic BCR repertoire present in patients with COVID-19 at various stages. We compared a recovered and a deceased COVID-19 patient supported by ECMO with one COVID-19-recovered patient who did not receive ECMO treatment and one healthy subject who had never been infected previously. Our analysis revealed a downregulation of FXYD, HLA-DRB1, and RPS20 in memory B cells; MTATP8 and HLA-DQA1 in naïve cells; RPS4Y1 in activated B cells; and IGHV3-73 in plasma cells in COVID-19 patients. We further described an increased ratio of IgA + IgG to IgD + IgM, suggestive of an intensive memory antibody response, in the COVID ECMO D patient. Finally, we assessed a V(D)J rearrangement of heavy chain IgHV3, IGHJ4, and IGHD3/IGHD2 families in COVID-19 patients regardless of the severity of the disease.
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38
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Ruiz Ortega M, Spisak N, Mora T, Walczak AM. Modeling and predicting the overlap of B- and T-cell receptor repertoires in healthy and SARS-CoV-2 infected individuals. PLoS Genet 2023; 19:e1010652. [PMID: 36827454 PMCID: PMC10075420 DOI: 10.1371/journal.pgen.1010652] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 04/05/2023] [Accepted: 02/02/2023] [Indexed: 02/26/2023] Open
Abstract
Adaptive immunity's success relies on the extraordinary diversity of protein receptors on B and T cell membranes. Despite this diversity, the existence of public receptors shared by many individuals gives hope for developing population-wide vaccines and therapeutics. Using probabilistic modeling, we show many of these public receptors are shared by chance in healthy individuals. This predictable overlap is driven not only by biases in the random generation process of receptors, as previously reported, but also by their common functional selection. However, the model underestimates sharing between repertoires of individuals infected with SARS-CoV-2, suggesting strong specific antigen-driven convergent selection. We exploit this discrepancy to identify COVID-associated receptors, which we validate against datasets of receptors with known viral specificity. We study their properties in terms of sequence features and network organization, and use them to design an accurate diagnostic tool for predicting SARS-CoV-2 status from repertoire data.
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Affiliation(s)
- María Ruiz Ortega
- Laboratoire de physique de l’École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
| | - Natanael Spisak
- Laboratoire de physique de l’École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
| | - Thierry Mora
- Laboratoire de physique de l’École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
| | - Aleksandra M. Walczak
- Laboratoire de physique de l’École Normale Supérieure, CNRS, PSL University, Sorbonne Université, and Université de Paris, Paris, France
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39
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Asashima H, Mohanty S, Comi M, Ruff WE, Hoehn KB, Wong P, Klein J, Lucas C, Cohen I, Coffey S, Lele N, Greta L, Raddassi K, Chaudhary O, Unterman A, Emu B, Kleinstein SH, Montgomery RR, Iwasaki A, Dela Cruz CS, Kaminski N, Shaw AC, Hafler DA, Sumida TS. PD-1 highCXCR5 -CD4 + peripheral helper T cells promote CXCR3 + plasmablasts in human acute viral infection. Cell Rep 2023; 42:111895. [PMID: 36596303 PMCID: PMC9806868 DOI: 10.1016/j.celrep.2022.111895] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 06/15/2022] [Accepted: 12/08/2022] [Indexed: 01/03/2023] Open
Abstract
T cell-B cell interaction is the key immune response to protect the host from severe viral infection. However, how T cells support B cells to exert protective humoral immunity in humans is not well understood. Here, we use COVID-19 as a model of acute viral infections and analyze CD4+ T cell subsets associated with plasmablast expansion and clinical outcome. Peripheral helper T cells (Tph cells; denoted as PD-1highCXCR5-CD4+ T cells) are significantly increased, as are plasmablasts. Tph cells exhibit "B cell help" signatures and induce plasmablast differentiation in vitro. Interestingly, expanded plasmablasts show increased CXCR3 expression, which is positively correlated with higher frequency of activated Tph cells and better clinical outcome. Mechanistically, Tph cells help B cell differentiation and produce more interferon γ (IFNγ), which induces CXCR3 expression on plasmablasts. These results elucidate a role for Tph cells in regulating protective B cell response during acute viral infection.
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Affiliation(s)
- Hiromitsu Asashima
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Subhasis Mohanty
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Michela Comi
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - William E Ruff
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Kenneth B Hoehn
- Department of Pathology, Yale School of Medicine, New Haven, CT, USA
| | - Patrick Wong
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Jon Klein
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Carolina Lucas
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Inessa Cohen
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Sarah Coffey
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Nikhil Lele
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Leissa Greta
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Khadir Raddassi
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Omkar Chaudhary
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Avraham Unterman
- Section of Pulmonary, Critical Care and Sleep Medicine Section, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Brinda Emu
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Steven H Kleinstein
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA; Department of Pathology, Yale School of Medicine, New Haven, CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Ruth R Montgomery
- Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Akiko Iwasaki
- Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA; Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Charles S Dela Cruz
- Section of Pulmonary, Critical Care and Sleep Medicine Section, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Naftali Kaminski
- Section of Pulmonary, Critical Care and Sleep Medicine Section, Department of Internal Medicine, School of Medicine, Yale University, New Haven, CT, USA
| | - Albert C Shaw
- Section of Infectious Diseases, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - David A Hafler
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Tomokazu S Sumida
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
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40
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Pennell M, Rodriguez OL, Watson CT, Greiff V. The evolutionary and functional significance of germline immunoglobulin gene variation. Trends Immunol 2023; 44:7-21. [PMID: 36470826 DOI: 10.1016/j.it.2022.11.001] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 11/07/2022] [Indexed: 12/04/2022]
Abstract
The recombination between immunoglobulin (IG) gene segments determines an individual's naïve antibody repertoire and, consequently, (auto)antigen recognition. Emerging evidence suggests that mammalian IG germline variation impacts humoral immune responses associated with vaccination, infection, and autoimmunity - from the molecular level of epitope specificity, up to profound changes in the architecture of antibody repertoires. These links between IG germline variants and immunophenotype raise the question on the evolutionary causes and consequences of diversity within IG loci. We discuss why the extreme diversity in IG loci remains a mystery, why resolving this is important for the design of more effective vaccines and therapeutics, and how recent evidence from multiple lines of inquiry may help us do so.
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Affiliation(s)
- Matt Pennell
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA; Department of Biological Sciences, University of Southern California, Los Angeles, CA, USA.
| | - Oscar L Rodriguez
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, USA
| | - Corey T Watson
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, USA
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway.
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41
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Safra M, Tamari Z, Polak P, Shiber S, Matan M, Karameh H, Helviz Y, Levy-Barda A, Yahalom V, Peretz A, Ben-Chetrit E, Brenner B, Tuller T, Gal-Tanamy M, Yaari G. Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity. Front Immunol 2023; 14:1031914. [PMID: 37153628 PMCID: PMC10154551 DOI: 10.3389/fimmu.2023.1031914] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 03/22/2023] [Indexed: 05/10/2023] Open
Abstract
Introduction The success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance. Methods We report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls. Results In contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients. Discussion These features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges.
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Affiliation(s)
- Modi Safra
- Bio-engineering, Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel
- Bar Ilan Institute of Nanotechnologies and Advanced Materials, Bar Ilan University, Ramat Gan, Israel
| | - Zvi Tamari
- Bio-engineering, Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel
- Bar Ilan Institute of Nanotechnologies and Advanced Materials, Bar Ilan University, Ramat Gan, Israel
| | - Pazit Polak
- Bio-engineering, Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel
- Bar Ilan Institute of Nanotechnologies and Advanced Materials, Bar Ilan University, Ramat Gan, Israel
| | - Shachaf Shiber
- Emergency Department, Rabin Medical Center-Belinson Campus, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Moshe Matan
- Clinical Microbiology Laboratory, Baruch Padeh Medical Center, Poriya, Israel
| | - Hani Karameh
- Jesselson Integrated Heart Center, Shaare Zedek Medical Center, Hebrew University School of Medicine, Jerusalem, Israel
| | - Yigal Helviz
- Intensive Care Unit, Shaare Zedek Medical Center, Hebrew University School of Medicine, Jerusalem, Israel
| | - Adva Levy-Barda
- Biobank, Department of Pathology, Rabin Medical Center-Belinson Campus, Petah Tikva, Israel
| | - Vered Yahalom
- Blood Services and Apheresis Institute, Rabin Medical Center, Petah Tikva, Israel
| | - Avi Peretz
- Clinical Microbiology Laboratory, Baruch Padeh Medical Center, Poriya, Israel
- The Azrieli Faculty of Medicine, Bar-Ilan University, Safed, Israel
| | - Eli Ben-Chetrit
- Infectious Diseases Unit, Shaare Zedek Medical Center, Hebrew University School of Medicine, Jerusalem, Israel
| | - Baruch Brenner
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Institute of Oncology, Rabin Medical Center-Belinson Campus, Petah Tikva, Israel
| | - Tamir Tuller
- Department of Biomedical Engineering and The Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | | | - Gur Yaari
- Bio-engineering, Faculty of Engineering, Bar Ilan University, Ramat Gan, Israel
- Bar Ilan Institute of Nanotechnologies and Advanced Materials, Bar Ilan University, Ramat Gan, Israel
- *Correspondence: Gur Yaari,
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42
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Kanduri C, Scheffer L, Pavlović M, Rand KD, Chernigovskaya M, Pirvandy O, Yaari G, Greiff V, Sandve GK. simAIRR: simulation of adaptive immune repertoires with realistic receptor sequence sharing for benchmarking of immune state prediction methods. Gigascience 2022; 12:giad074. [PMID: 37848619 PMCID: PMC10580376 DOI: 10.1093/gigascience/giad074] [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: 02/21/2023] [Revised: 07/20/2023] [Accepted: 08/29/2023] [Indexed: 10/19/2023] Open
Abstract
BACKGROUND Machine learning (ML) has gained significant attention for classifying immune states in adaptive immune receptor repertoires (AIRRs) to support the advancement of immunodiagnostics and therapeutics. Simulated data are crucial for the rigorous benchmarking of AIRR-ML methods. Existing approaches to generating synthetic benchmarking datasets result in the generation of naive repertoires missing the key feature of many shared receptor sequences (selected for common antigens) found in antigen-experienced repertoires. RESULTS We demonstrate that a common approach to generating simulated AIRR benchmark datasets can introduce biases, which may be exploited for undesired shortcut learning by certain ML methods. To mitigate undesirable access to true signals in simulated AIRR datasets, we devised a simulation strategy (simAIRR) that constructs antigen-experienced-like repertoires with a realistic overlap of receptor sequences. simAIRR can be used for constructing AIRR-level benchmarks based on a range of assumptions (or experimental data sources) for what constitutes receptor-level immune signals. This includes the possibility of making or not making any prior assumptions regarding the similarity or commonality of immune state-associated sequences that will be used as true signals. We demonstrate the real-world realism of our proposed simulation approach by showing that basic ML strategies perform similarly on simAIRR-generated and real-world experimental AIRR datasets. CONCLUSIONS This study sheds light on the potential shortcut learning opportunities for ML methods that can arise with the state-of-the-art way of simulating AIRR datasets. simAIRR is available as a Python package: https://github.com/KanduriC/simAIRR.
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Affiliation(s)
- Chakravarthi Kanduri
- Centre for Bioinformatics, Department of Informatics, University of Oslo, 0373 Oslo, Norway
- UiORealArt Convergence Environment, University of Oslo, 0373 Oslo, Norway
| | - Lonneke Scheffer
- Centre for Bioinformatics, Department of Informatics, University of Oslo, 0373 Oslo, Norway
| | - Milena Pavlović
- Centre for Bioinformatics, Department of Informatics, University of Oslo, 0373 Oslo, Norway
- UiORealArt Convergence Environment, University of Oslo, 0373 Oslo, Norway
| | - Knut Dagestad Rand
- Centre for Bioinformatics, Department of Informatics, University of Oslo, 0373 Oslo, Norway
| | - Maria Chernigovskaya
- Department of Immunology and Oslo University Hospital, University of Oslo, 0373 Oslo, Norway
| | - Oz Pirvandy
- Faculty of Engineering, Bar-Ilan University, 5290002, Israel
| | - Gur Yaari
- Faculty of Engineering, Bar-Ilan University, 5290002, Israel
| | - Victor Greiff
- Department of Immunology and Oslo University Hospital, University of Oslo, 0373 Oslo, Norway
| | - Geir K Sandve
- Centre for Bioinformatics, Department of Informatics, University of Oslo, 0373 Oslo, Norway
- UiORealArt Convergence Environment, University of Oslo, 0373 Oslo, Norway
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43
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Kuraoka M, Curtis NC, Watanabe A, Tanno H, Shin S, Ye K, Macdonald E, Lavidor O, Kong S, Von Holle T, Windsor I, Ippolito GC, Georgiou G, Walter EB, Kelsoe G, Harrison SC, Moody MA, Bajic G, Lee J. Infant Antibody Repertoires during the First Two Years of Influenza Vaccination. mBio 2022; 13:e0254622. [PMID: 36314798 PMCID: PMC9765176 DOI: 10.1128/mbio.02546-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 01/11/2023] Open
Abstract
The first encounter with influenza virus biases later immune responses. This "immune imprinting," formerly from infection within a few years of birth, is in the United States now largely from immunization with a quadrivalent, split vaccine (IIV4 [quadrivalent inactivated influenza vaccine]). In a pilot study of IIV4 imprinting, we used single-cell cultures, next-generation sequencing, and plasma antibody proteomics to characterize the primary antibody responses to influenza in two infants during their first 2 years of seasonal influenza vaccination. One infant, who received only a single vaccination in year 1, contracted an influenza B virus (IBV) infection between the 2 years, allowing us to compare imprinting by infection and vaccination. That infant had a shift in hemagglutinin (HA)-reactive B cell specificity from largely influenza A virus (IAV) specific in year 1 to IBV specific in year 2, both before and after the year 2 vaccination. HA-reactive B cells from the other infant maintained a more evenly distributed specificity. In year 2, class-switched HA-specific B cell IGHV somatic hypermutation (SHM) levels reached the average levels seen in adults. The HA-reactive plasma antibody repertoires of both infants comprised a relatively small number of antibody clonotypes, with one or two very abundant clonotypes. Thus, after the year 2 boost, both infants had overall B cell profiles that resembled those of adult controls. IMPORTANCE Influenza virus is a moving target for the immune system. Variants emerge that escape protection from antibodies elicited by a previously circulating variant ("antigenic drift"). The immune system usually responds to a drifted influenza virus by mutating existing antibodies rather than by producing entirely new ones. Thus, immune memory of the earliest influenza virus exposure has a major influence on later responses to infection or vaccination ("immune imprinting"). In the many studies of influenza immunity in adult subjects, imprinting has been from an early infection, since only in the past 2 decades have infants received influenza immunizations. The work reported in this paper is a pilot study of imprinting by the flu vaccine in two infants, who received the vaccine before experiencing an influenza virus infection. The results suggest that a quadrivalent (four-subtype) vaccine may provide an immune imprint less dominated by one subtype than does a monovalent infection.
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Affiliation(s)
- Masayuki Kuraoka
- Department of Immunology, Duke University, Durham, North Carolina, USA
| | - Nicholas C. Curtis
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
| | - Akiko Watanabe
- Department of Immunology, Duke University, Durham, North Carolina, USA
| | - Hidetaka Tanno
- Department of Chemical Engineering, University of Texas, Austin, Texas, USA
- Department of Molecular Biosciences, University of Texas, Austin, Texas, USA
- Department of Biomedical Engineering, University of Texas, Austin, Texas, USA
- Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas, USA
| | - Seungmin Shin
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
| | - Kevin Ye
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
| | - Elizabeth Macdonald
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Olivia Lavidor
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Susan Kong
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Tarra Von Holle
- Department of Pediatrics, Duke University, Durham, North Carolina, USA
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, USA
| | - Ian Windsor
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Gregory C. Ippolito
- Department of Molecular Biosciences, University of Texas, Austin, Texas, USA
- Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas, USA
| | - George Georgiou
- Department of Chemical Engineering, University of Texas, Austin, Texas, USA
- Department of Molecular Biosciences, University of Texas, Austin, Texas, USA
- Department of Biomedical Engineering, University of Texas, Austin, Texas, USA
- Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas, USA
| | - Emmanuel B. Walter
- Department of Pediatrics, Duke University, Durham, North Carolina, USA
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, USA
| | - Garnett Kelsoe
- Department of Immunology, Duke University, Durham, North Carolina, USA
- Department of Surgery, Duke University, Durham, North Carolina, USA
| | - Stephen C. Harrison
- Laboratory of Molecular Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Howard Hughes Medical Institute, Harvard Medical School, Boston, Massachusetts, USA
| | - M. Anthony Moody
- Department of Immunology, Duke University, Durham, North Carolina, USA
- Department of Pediatrics, Duke University, Durham, North Carolina, USA
- Duke Human Vaccine Institute, Duke University, Durham, North Carolina, USA
| | - Goran Bajic
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jiwon Lee
- Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
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44
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Goldman JD, Wang K, Röltgen K, Nielsen SCA, Roach JC, Naccache SN, Yang F, Wirz OF, Yost KE, Lee JY, Chun K, Wrin T, Petropoulos CJ, Lee I, Fallen S, Manner PM, Wallick JA, Algren HA, Murray KM, Hadlock J, Chen D, Dai CL, Yuan D, Su Y, Jeharajah J, Berrington WR, Pappas GP, Nyatsatsang ST, Greninger AL, Satpathy AT, Pauk JS, Boyd SD, Heath JR. Reinfection with SARS-CoV-2 and Waning Humoral Immunity: A Case Report. Vaccines (Basel) 2022; 11:5. [PMID: 36679852 PMCID: PMC9861578 DOI: 10.3390/vaccines11010005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/15/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022] Open
Abstract
Recovery from COVID-19 is associated with production of anti-SARS-CoV-2 antibodies, but it is uncertain whether these confer immunity. We describe viral RNA shedding duration in hospitalized patients and identify patients with recurrent shedding. We sequenced viruses from two distinct episodes of symptomatic COVID-19 separated by 144 days in a single patient, to conclusively describe reinfection with a different strain harboring the spike variant D614G. This case of reinfection was one of the first cases of reinfection reported in 2020. With antibody, B cell and T cell analytics, we show correlates of adaptive immunity at reinfection, including a differential response in neutralizing antibodies to a D614G pseudovirus. Finally, we discuss implications for vaccine programs and begin to define benchmarks for protection against reinfection from SARS-CoV-2.
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Affiliation(s)
- Jason D. Goldman
- Division of Infectious Diseases, Swedish Medical Center, Seattle, WA 98122, USA
- Providence St. Joseph Health, Renton, WA 98057, USA
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, WA 98195, USA
| | - Kai Wang
- Institute for Systems Biology, Seattle, WA 98103, USA
| | - Katharina Röltgen
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | | | | | | | - Fan Yang
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Oliver F. Wirz
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Kathryn E. Yost
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Ji-Yeun Lee
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Kelly Chun
- LabCorp Esoterix, Calabasas, CA 91301, USA
| | - Terri Wrin
- Monogram Biosciences, South San Francisco, CA 94080, USA
| | | | - Inyoul Lee
- Institute for Systems Biology, Seattle, WA 98103, USA
| | | | - Paula M. Manner
- Providence St. Joseph Health, Renton, WA 98057, USA
- Swedish Center for Research and Innovation, Swedish Medical Center, Seattle, WA 98104, USA
| | - Julie A. Wallick
- Providence St. Joseph Health, Renton, WA 98057, USA
- Swedish Center for Research and Innovation, Swedish Medical Center, Seattle, WA 98104, USA
| | - Heather A. Algren
- Providence St. Joseph Health, Renton, WA 98057, USA
- Swedish Center for Research and Innovation, Swedish Medical Center, Seattle, WA 98104, USA
| | - Kim M. Murray
- Institute for Systems Biology, Seattle, WA 98103, USA
| | - Jennifer Hadlock
- Providence St. Joseph Health, Renton, WA 98057, USA
- Institute for Systems Biology, Seattle, WA 98103, USA
| | - Daniel Chen
- Institute for Systems Biology, Seattle, WA 98103, USA
| | | | - Dan Yuan
- Institute for Systems Biology, Seattle, WA 98103, USA
| | - Yapeng Su
- Institute for Systems Biology, Seattle, WA 98103, USA
| | - Joshua Jeharajah
- Division of Infectious Diseases, Polyclinic, Seattle, WA 98104, USA
| | - William R. Berrington
- Division of Infectious Diseases, Swedish Medical Center, Seattle, WA 98122, USA
- Providence St. Joseph Health, Renton, WA 98057, USA
| | - George P. Pappas
- Division of Pulmonology and Critical Care Medicine, Swedish Medical Center, Seattle, WA 98104, USA
| | - Sonam T. Nyatsatsang
- Division of Infectious Diseases, Swedish Medical Center, Seattle, WA 98122, USA
- Providence St. Joseph Health, Renton, WA 98057, USA
| | - Alexander L. Greninger
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA 98109, USA
- Vaccine and Infectious Disease Division, Fred Hutch, Seattle, DC 98109, USA
| | | | - John S. Pauk
- Division of Infectious Diseases, Swedish Medical Center, Seattle, WA 98122, USA
- Providence St. Joseph Health, Renton, WA 98057, USA
| | - Scott D. Boyd
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Sean N. Parker Center for Allergy and Asthma Research, Stanford, CA 94304, USA
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45
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He B, Liu S, Xu M, Hu Y, Lv K, Wang Y, Ma Y, Zhai Y, Yue X, Liu L, Lu H, Zhou S, Li P, Mai G, Huang X, Li C, Chen S, Ye S, Zhao P, Yang Y, Li X, Jie Y, Shi M, Yang J, Shu Y, Chen YQ. Comparative global B cell receptor repertoire difference induced by SARS-CoV-2 infection or vaccination via single-cell V(D)J sequencing. Emerg Microbes Infect 2022; 11:2007-2020. [PMID: 35899581 PMCID: PMC9377262 DOI: 10.1080/22221751.2022.2105261] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/30/2022] [Accepted: 07/19/2022] [Indexed: 02/05/2023]
Abstract
Dynamic changes of the paired heavy and light chain B cell receptor (BCR) repertoire provide an essential insight into understanding the humoral immune response post-SARS-CoV-2 infection and vaccination. However, differences between the endogenous paired BCR repertoire kinetics in SARS-CoV-2 infection and previously recovered/naïve subjects treated with the inactivated vaccine remain largely unknown. We performed single-cell V(D)J sequencing of B cells from six healthy donors with three shots of inactivated SARS-CoV-2 vaccine (BBIBP-CorV), five people who received the BBIBP-CorV vaccine after having recovered from COVID-19, five unvaccinated COVID-19 recovered patients and then integrated with public data of B cells from four SARS-CoV-2-infected subjects. We discovered that BCR variable (V) genes were more prominently used in the SARS-CoV-2 exposed groups (both in the group with active infection and in the group that had recovered) than in the vaccinated groups. The VH gene that expanded the most after SARS-CoV-2 infection was IGHV3-33, while IGHV3-23 in the vaccinated groups. SARS-CoV-2-infected group enhanced more BCR clonal expansion and somatic hypermutation than the vaccinated healthy group. A small proportion of public clonotypes were shared between the SARS-CoV-2 infected, vaccinated healthy, and recovered groups. Moreover, several public antibodies had been identified against SARS-CoV-2 spike protein. We comprehensively characterize the paired heavy and light chain BCR repertoire from SARS-CoV-2 infection to vaccination, providing further guidance for the development of the next-generation precision vaccine.
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Affiliation(s)
- Bing He
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Shuning Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Mengxin Xu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Yunqi Hu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Kexin Lv
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Yuanyuan Wang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Yong Ma
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Yanmei Zhai
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Xinyu Yue
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Lin Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Hongjie Lu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Siwei Zhou
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Pengbin Li
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Guoqin Mai
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Xiaoping Huang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Chenhang Li
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Shifeng Chen
- Department of Respiratory and Critical Care Medicine, The 74(th) Group Army Hospital, Guangzhou, People’s Republic of China
| | - Shupei Ye
- SSL Central Hospital of Dongguan City, Dongguan, People’s Republic of China
| | - Pingsen Zhao
- Laboratory for Diagnosis of Clinical Microbiology and Infection, Medical Research Center, Yuebei People’s Hospital, Shantou University Medical College, Shaoguan, People’s Republic of China
| | - Yuedong Yang
- School of Data and Computer Science, Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Xinhua Li
- Department of Infectious Diseases and Key Laboratory of Liver Disease of Guangdong Province, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yusheng Jie
- Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Mang Shi
- The Centre for Infection and Immunity Studies, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Jingyi Yang
- Vaccine and Immunology Research Center, Translational Medical Research Institute, Shanghai Public Health Clinical Center, Fudan University, Shanghai, People’s Republic of China
| | - Yuelong Shu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
| | - Yao-Qing Chen
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, People’s Republic of China
- b School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
- k Ministry of Education, Key Laboratory of Tropical Disease Control (Sun Yat-sen University), Guangzhou, People’s Republic of China
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46
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Ismanto HS, Xu Z, Saputri DS, Wilamowski J, Li S, Nugraha DK, Horiguchi Y, Okada M, Arase H, Standley DM. Landscape of infection enhancing antibodies in COVID-19 and healthy donors. Comput Struct Biotechnol J 2022; 20:6033-6040. [PMCID: PMC9635252 DOI: 10.1016/j.csbj.2022.11.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/01/2022] [Accepted: 11/01/2022] [Indexed: 11/06/2022] Open
Affiliation(s)
- Hendra S. Ismanto
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
| | - Zichang Xu
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
| | - Dianita S. Saputri
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
| | - Jan Wilamowski
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
| | - Songling Li
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Department of System Immunology, Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka 565-0871, Japan
| | - Dendi K. Nugraha
- Deparment of Molecular Bacteriology, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
| | - Yasuhiko Horiguchi
- Deparment of Molecular Bacteriology, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka 565-0871, Japan
| | - Masato Okada
- Deparment of Oncogene Research, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Department of Oncogene Research, Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka 565-0871, Japan
| | - Hisashi Arase
- Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Department of Immunochemistry, Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka 565-0871, Japan
| | - Daron M Standley
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Department of System Immunology, Immunology Frontier Research Center, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka 565-0871, Japan
- Corresponding author at: Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita 565-0871, Japan.
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47
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Xu Z, Ismanto HS, Zhou H, Saputri DS, Sugihara F, Standley DM. Advances in antibody discovery from human BCR repertoires. FRONTIERS IN BIOINFORMATICS 2022; 2:1044975. [PMID: 36338807 PMCID: PMC9631452 DOI: 10.3389/fbinf.2022.1044975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/11/2022] [Indexed: 11/06/2022] Open
Abstract
Antibodies make up an important and growing class of compounds used for the diagnosis or treatment of disease. While traditional antibody discovery utilized immunization of animals to generate lead compounds, technological innovations have made it possible to search for antibodies targeting a given antigen within the repertoires of B cells in humans. Here we group these innovations into four broad categories: cell sorting allows the collection of cells enriched in specificity to one or more antigens; BCR sequencing can be performed on bulk mRNA, genomic DNA or on paired (heavy-light) mRNA; BCR repertoire analysis generally involves clustering BCRs into specificity groups or more in-depth modeling of antibody-antigen interactions, such as antibody-specific epitope predictions; validation of antibody-antigen interactions requires expression of antibodies, followed by antigen binding assays or epitope mapping. Together with innovations in Deep learning these technologies will contribute to the future discovery of diagnostic and therapeutic antibodies directly from humans.
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Affiliation(s)
- Zichang Xu
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Hendra S. Ismanto
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Hao Zhou
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Dianita S. Saputri
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Fuminori Sugihara
- Core Instrumentation Facility, Immunology Frontier Research Center, Osaka University, Suita, Japan
| | - Daron M. Standley
- Department of Genome Informatics, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
- Department Systems Immunology, Immunology Frontier Research Center, Osaka University, Suita, Japan
- *Correspondence: Daron M. Standley,
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48
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Taft JM, Weber CR, Gao B, Ehling RA, Han J, Frei L, Metcalfe SW, Overath MD, Yermanos A, Kelton W, Reddy ST. Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain. Cell 2022; 185:4008-4022.e14. [PMID: 36150393 PMCID: PMC9428596 DOI: 10.1016/j.cell.2022.08.024] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 06/22/2022] [Accepted: 08/25/2022] [Indexed: 01/26/2023]
Abstract
The continual evolution of SARS-CoV-2 and the emergence of variants that show resistance to vaccines and neutralizing antibodies threaten to prolong the COVID-19 pandemic. Selection and emergence of SARS-CoV-2 variants are driven in part by mutations within the viral spike protein and in particular the ACE2 receptor-binding domain (RBD), a primary target site for neutralizing antibodies. Here, we develop deep mutational learning (DML), a machine-learning-guided protein engineering technology, which is used to investigate a massive sequence space of combinatorial mutations, representing billions of RBD variants, by accurately predicting their impact on ACE2 binding and antibody escape. A highly diverse landscape of possible SARS-CoV-2 variants is identified that could emerge from a multitude of evolutionary trajectories. DML may be used for predictive profiling on current and prospective variants, including highly mutated variants such as Omicron, thus guiding the development of therapeutic antibody treatments and vaccines for COVID-19.
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Affiliation(s)
- Joseph M. Taft
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland,Botnar Research Centre for Child Health, Basel 4058, Switzerland
| | - Cédric R. Weber
- Alloy Therapeutics (Switzerland) AG, Basel 4058, Switzerland
| | - Beichen Gao
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland,Botnar Research Centre for Child Health, Basel 4058, Switzerland
| | - Roy A. Ehling
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland
| | - Jiami Han
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland,Botnar Research Centre for Child Health, Basel 4058, Switzerland
| | - Lester Frei
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland,Botnar Research Centre for Child Health, Basel 4058, Switzerland
| | - Sean W. Metcalfe
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland
| | - Max D. Overath
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland
| | - Alexander Yermanos
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland,Botnar Research Centre for Child Health, Basel 4058, Switzerland,Department of Biology, Institute of Microbiology and Immunology, ETH Zurich, Zurich 8093, Switzerland,Department of Pathology and Immunology, University of Geneva, Geneva 1211, Switzerland
| | - William Kelton
- Te Huataki Waiora School of Health, University of Waikato, Hamilton 3240, New Zealand
| | - Sai T. Reddy
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4058, Switzerland,Botnar Research Centre for Child Health, Basel 4058, Switzerland,Corresponding author
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49
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Yang X, Chi H, Wu M, Wang Z, Lang Q, Han Q, Wang X, Liu X, Li Y, Wang X, Huang N, Bi J, Liang H, Gao Y, Zhao Y, Feng N, Yang S, Wang T, Xia X, Ge L. Discovery and characterization of SARS-CoV-2 reactive and neutralizing antibodies from humanized CAMouseHG mice through rapid hybridoma screening and high-throughput single-cell V(D)J sequencing. Front Immunol 2022; 13:992787. [PMID: 36211410 PMCID: PMC9545174 DOI: 10.3389/fimmu.2022.992787] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 08/26/2022] [Indexed: 11/13/2022] Open
Abstract
The coronavirus disease 2019 pandemic has caused more than 532 million infections and 6.3 million deaths to date. The reactive and neutralizing fully human antibodies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are effective detection tools and therapeutic measures. During SARS-CoV-2 infection, a large number of SARS-CoV-2 reactive and neutralizing antibodies will be produced. Most SARS-CoV-2 reactive and neutralizing fully human antibodies are isolated from human and frequently encoded by convergent heavy-chain variable genes. However, SARS-CoV-2 viruses can mutate rapidly during replication and the resistant variants of neutralizing antibodies easily survive and evade the immune response, especially in the face of such focused antibody responses in humans. Therefore, additional tools are needed to develop different kinds of fully human antibodies to compensate for current deficiency. In this study, we utilized antibody humanized CAMouseHG mice to develop a rapid antibody discovery method and examine the antibody repertoire of SARS-CoV-2 RBD-reactive hybridoma cells derived from CAMouseHG mice by using high-throughput single-cell V(D)J sequencing analysis. CAMouseHG mice were immunized by 28-day rapid immunization method. After electrofusion and semi-solid medium screening on day 12 post-electrofusion, 171 hybridoma clones were generated based on the results of SARS-CoV-2 RBD binding activity assay. A rather obvious preferential usage of IGHV6-1 family was found in these hybridoma clones derived from CAMouseHG mice, which was significantly different from the antibodies found in patients with COVID-19. After further virus neutralization screening and antibody competition assays, we generated a noncompeting two-antibody cocktail, which showed a potent prophylactic protective efficacy against SARS-CoV-2 in cynomolgus macaques. These results indicate that humanized CAMouseHG mice not only provide a valuable platform to obtain fully human reactive and neutralizing antibodies but also have a different antibody repertoire from humans. Thus, humanized CAMouseHG mice can be used as a good complementary tool in discovery of fully human therapeutic and diagnostic antibodies.
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Affiliation(s)
- Xi Yang
- Institute of Bioengineering, ChongQing Academy of Animal Sciences, Chongqing, China
| | - Hang Chi
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
| | - Meng Wu
- Institute of Bioengineering, ChongQing Academy of Animal Sciences, Chongqing, China
| | - Zhenshan Wang
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
- College of Veterinary Medicine, Jilin Agricultural University, Changchun, China
| | - Qiaoli Lang
- Institute of Bioengineering, ChongQing Academy of Animal Sciences, Chongqing, China
| | - Qiuxue Han
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
- Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences (CAMS) and Comparative Medicine Center, Peking Union Medical College (PUMC), Beijing, China
| | - Xinyue Wang
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
- College of Wildlife and Protected Area, Northeast Forestry University, Harbin, China
| | - Xueqin Liu
- Institute of Bioengineering, ChongQing Academy of Animal Sciences, Chongqing, China
| | - Yuanguo Li
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
| | - Xiwen Wang
- Food and Drug Inspection Laboratory, Administration for Drug and Instrument Supervision and Inspection, Beijing, China
| | - Nan Huang
- Institute of Bioengineering, ChongQing Academy of Animal Sciences, Chongqing, China
| | - Jinhao Bi
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
- College of Veterinary Medicine, Jilin Agricultural University, Changchun, China
| | - Hao Liang
- Institute of Bioengineering, ChongQing Academy of Animal Sciences, Chongqing, China
| | - Yuwei Gao
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
| | - Yongkun Zhao
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
| | - Na Feng
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
| | - Songtao Yang
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
| | - Tiecheng Wang
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
- *Correspondence: Liangpeng Ge, ; Tiecheng Wang, ; Xianzhu Xia,
| | - Xianzhu Xia
- Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun, China
- *Correspondence: Liangpeng Ge, ; Tiecheng Wang, ; Xianzhu Xia,
| | - Liangpeng Ge
- Institute of Bioengineering, ChongQing Academy of Animal Sciences, Chongqing, China
- *Correspondence: Liangpeng Ge, ; Tiecheng Wang, ; Xianzhu Xia,
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50
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Wang M, Chang W, Zhang L, Zhang Y. Pyroptotic cell death in SARS-CoV-2 infection: revealing its roles during the immunopathogenesis of COVID-19. Int J Biol Sci 2022; 18:5827-5848. [PMID: 36263178 PMCID: PMC9576507 DOI: 10.7150/ijbs.77561] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/10/2022] [Indexed: 01/12/2023] Open
Abstract
The rapid dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), remains a global public health emergency. The host immune response to SARS-CoV-2 plays a key role in COVID-19 pathogenesis. SARS-CoV-2 can induce aberrant and excessive immune responses, leading to cytokine storm syndrome, autoimmunity, lymphopenia, neutrophilia and dysfunction of monocytes and macrophages. Pyroptosis, a proinflammatory form of programmed cell death, acts as a host defense mechanism against infections. Pyroptosis deprives the replicative niche of SARS-CoV-2 by inducing the lysis of infected cells and exposing the virus to extracellular immune attack. Notably, SARS-CoV-2 has evolved sophisticated mechanisms to hijack this cell death mode for its own survival, propagation and shedding. SARS-CoV-2-encoded viral products act to modulate various key components in the pyroptosis pathways, including inflammasomes, caspases and gasdermins. SARS-CoV-2-induced pyroptosis contriubtes to the development of COVID-19-associated immunopathologies through leakage of intracellular contents, disruption of immune system homeostasis or exacerbation of inflammation. Therefore, pyroptosis has emerged as an important mechanism involved in COVID-19 immunopathogenesis. However, the entangled links between pyroptosis and SARS-CoV-2 pathogenesis lack systematic clarification. In this review, we briefly summarize the characteristics of SARS-CoV-2 and COVID-19-related immunopathologies. Moreover, we present an overview of the interplay between SARS-CoV-2 infection and pyroptosis and highlight recent research advances in the understanding of the mechanisms responsible for the implication of the pyroptosis pathways in COVID-19 pathogenesis, which will provide informative inspirations and new directions for further investigation and clinical practice. Finally, we discuss the potential value of pyroptosis as a therapeutic target in COVID-19. An in-depth discussion of the underlying mechanisms of COVID-19 pathogenesis will be conducive to the identification of potential therapeutic targets and the exploration of effective treatment measures aimed at conquering SARS-CoV-2-induced COVID-19.
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Affiliation(s)
- Man Wang
- ✉ Corresponding author: Man Wang, Institute for Translational Medicine, The Affiliated Hospital of Qingdao University, College of Medicine, Qingdao University, 38 Dengzhou Road, Qingdao 266021, China. Tel.: +86-532-82991791; E-mail address:
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