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Guenthoer J, Garrett ME, Lilly M, Depierreux DM, Ruiz F, Chi M, Stoddard CI, Chohan V, Yaffe ZA, Sung K, Ralph D, Chu HY, Matsen FA, Overbaugh J. The S2 subunit of spike encodes diverse targets for functional antibody responses to SARS-CoV-2. PLoS Pathog 2024; 20:e1012383. [PMID: 39093891 PMCID: PMC11324185 DOI: 10.1371/journal.ppat.1012383] [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: 02/27/2024] [Revised: 08/14/2024] [Accepted: 07/01/2024] [Indexed: 08/04/2024] Open
Abstract
The SARS-CoV-2 virus responsible for the COVID-19 global pandemic has exhibited a striking capacity for viral evolution that drives continued evasion from vaccine and infection-induced immune responses. Mutations in the receptor binding domain of the S1 subunit of the spike glycoprotein have led to considerable escape from antibody responses, reducing the efficacy of vaccines and monoclonal antibody (mAb) therapies. Therefore, there is a need to interrogate more constrained regions of spike, such as the S2 subdomain. Here, we present a collection of S2 mAbs from two SARS-CoV-2 convalescent individuals that target multiple regions in S2, including regions outside of those commonly reported. One of the S2 mAbs, C20.119, which bound to a highly conserved epitope in the fusion peptide, was able to broadly neutralize across SARS-CoV-2 variants, SARS-CoV-1, and closely related zoonotic sarbecoviruses. The majority of the mAbs were non-neutralizing; however, many of them could mediate antibody-dependent cellular cytotoxicity (ADCC) at levels similar to the S1-targeting mAb S309 that was previously authorized for treatment of SARS-CoV-2 infections. Several of the mAbs with ADCC function also bound to spike trimers from other human coronaviruses (HCoVs), such as MERS-CoV and HCoV-HKU1. Our findings suggest S2 mAbs can target diverse epitopes in S2, including functional mAbs with HCoV and sarbecovirus breadth that likely target functionally constrained regions of spike. These mAbs could be developed for potential future pandemics, while also providing insight into ideal epitopes for eliciting a broad HCoV response.
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Affiliation(s)
- Jamie Guenthoer
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Meghan E. Garrett
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Michelle Lilly
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Delphine M. Depierreux
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Felicitas Ruiz
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Margaret Chi
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Caitlin I. Stoddard
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Vrasha Chohan
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Zak A. Yaffe
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Kevin Sung
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Duncan Ralph
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Helen Y. Chu
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, United States of America
| | - Frederick A. Matsen
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
- Howard Hughes Medical Institute, Seattle, Washington, United States of America
| | - Julie Overbaugh
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
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2
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Voss K, Kaur KM, Banerjee R, Breden F, Pennell M. Evaluating methods for B-cell clonal family assignment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.29.596491. [PMID: 38853833 PMCID: PMC11160721 DOI: 10.1101/2024.05.29.596491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
The adaptive immune response relies on a diverse repertoire of B-cell receptors, each of which is characterized by a distinct sequence resulting from VDJ-recombination. Upon binding to an antigen, B-cells undergo clonal expansion and in a process unique to B-cells the overall binding affinity of the repertoire is further enhanced by somatic hypermutations in the receptor sequence. For B-cell repertoires it is therefore particularly important to analyze the dynamics of clonal expansion and patterns of somatic hypermutations and thus it is necessary to group the sequences into distinct clones to determine the number and identity of expanding clonal families responding to an antigen. Multiple methods are currently used to identify clones from sequences, employing distinct approaches to the problem. Until now there has not been an extensive comparison of how well these methods perform under the same conditions. Furthermore, since this is fundamentally a phylogenetics problem, we speculated that the mPTP method, which delimits species based on an analysis of changes in the underlying process of diversification, might perform as well as or better than existing methods. Here we conducted extensive simulations of B-cell repertoires under a diverse set of conditions and studied errors in clonal assignment and in downstream ancestral state reconstruction. We demonstrated that SCOPer-H consistently yielded superior results across parameters. However, this approach relies on a good reference assembly for the germline immunoglobulin genes which is lacking for many species. Using mPTP had lower error rates than tailor-made immunogenetic methods and should therefore be considered by researchers studying antibody evolution in non-model organisms without a reference genome.
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Affiliation(s)
- Katalin Voss
- Department of Quantitative and Computational Biology, University of Southern California, USA
| | - Katrina M. Kaur
- Department of Zoology, University of British Columbia, Canada
| | - Rituparna Banerjee
- Bioinformatics Graduate Program, Faculty of Science, University of British Columbia, Canada
| | - Felix Breden
- Department of Biological Sciences, Simon Fraser University, Canada
| | - Matt Pennell
- Department of Quantitative and Computational Biology, University of Southern California, USA
- Department of Biological Sciences, University of Southern California, USA
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3
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Jensen CG, Sumner JA, Kleinstein SH, Hoehn KB. Inferring B Cell Phylogenies from Paired H and L Chain BCR Sequences with Dowser. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2024; 212:1579-1588. [PMID: 38557795 PMCID: PMC11073909 DOI: 10.4049/jimmunol.2300851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/07/2024] [Indexed: 04/04/2024]
Abstract
Abs are vital to human immune responses and are composed of genetically variable H and L chains. These structures are initially expressed as BCRs. BCR diversity is shaped through somatic hypermutation and selection during immune responses. This evolutionary process produces B cell clones, cells that descend from a common ancestor but differ by mutations. Phylogenetic trees inferred from BCR sequences can reconstruct the history of mutations within a clone. Until recently, BCR sequencing technologies separated H and L chains, but advancements in single-cell sequencing now pair H and L chains from individual cells. However, it is unclear how these separate genes should be combined to infer B cell phylogenies. In this study, we investigated strategies for using paired H and L chain sequences to build phylogenetic trees. We found that incorporating L chains significantly improved tree accuracy and reproducibility across all methods tested. This improvement was greater than the difference between tree-building methods and persisted even when mixing bulk and single-cell sequencing data. However, we also found that many phylogenetic methods estimated significantly biased branch lengths when some L chains were missing, such as when mixing single-cell and bulk BCR data. This bias was eliminated using maximum likelihood methods with separate branch lengths for H and L chain gene partitions. Thus, we recommend using maximum likelihood methods with separate H and L chain partitions, especially when mixing data types. We implemented these methods in the R package Dowser: https://dowser.readthedocs.io.
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Affiliation(s)
- Cole G. Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
| | - Jacob A. Sumner
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, 06520, USA
| | - Steven H. Kleinstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA
- Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520, USA
| | - Kenneth B. Hoehn
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA
- Current address: Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
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4
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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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5
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Hoehn KB, Kleinstein SH. B cell phylogenetics in the single cell era. Trends Immunol 2024; 45:62-74. [PMID: 38151443 PMCID: PMC10872299 DOI: 10.1016/j.it.2023.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 11/22/2023] [Accepted: 11/24/2023] [Indexed: 12/29/2023]
Abstract
The widespread availability of single-cell RNA sequencing (scRNA-seq) has led to the development of new methods for understanding immune responses. Single-cell transcriptome data can now be paired with B cell receptor (BCR) sequences. However, RNA from BCRs cannot be analyzed like most other genes because BCRs are genetically diverse within individuals. In humans, BCRs are shaped through recombination followed by mutation and selection for antigen binding. As these processes co-occur with cell division, B cells can be studied using phylogenetic trees representing the mutations within a clone. B cell trees can link experimental timepoints, tissues, or cellular subtypes. Here, we review the current state and potential of how B cell phylogenetics can be combined with single-cell data to understand immune responses.
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Affiliation(s)
- Kenneth B Hoehn
- Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, 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 06520, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520, USA
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6
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Jensen CG, Sumner JA, Kleinstein SH, Hoehn KB. Inferring B cell phylogenies from paired heavy and light chain BCR sequences with Dowser. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.29.560187. [PMID: 37873135 PMCID: PMC10592837 DOI: 10.1101/2023.09.29.560187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Antibodies are vital to human immune responses and are composed of genetically variable heavy and light chains. These structures are initially expressed as B cell receptors (BCRs). BCR diversity is shaped through somatic hypermutation and selection during immune responses. This evolutionary process produces B cell clones, cells that descend from a common ancestor but differ by mutations. Phylogenetic trees inferred from BCR sequences can reconstruct the history of mutations within a clone. Until recently, BCR sequencing technologies separated heavy and light chains, but advancements in single cell sequencing now pair heavy and light chains from individual cells. However, it is unclear how these separate genes should be combined to infer B cell phylogenies. In this study, we investigated strategies for using paired heavy and light chain sequences to build phylogenetic trees. We found incorporating light chains significantly improved tree accuracy and reproducibility across all methods tested. This improvement was greater than the difference between tree building methods and persisted even when mixing bulk and single cell sequencing data. However, we also found that many phylogenetic methods estimated significantly biased branch lengths when some light chains were missing, such as when mixing single cell and bulk BCR data. This bias was eliminated using maximum likelihood methods with separate branch lengths for heavy and light chain gene partitions. Thus, we recommend using maximum likelihood methods with separate heavy and light chain partitions, especially when mixing data types. We implemented these methods in the R package Dowser: https://dowser.readthedocs.io.
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Affiliation(s)
- Cole G. Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
| | - Jacob A. Sumner
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, 06520, USA
| | - Steven H. Kleinstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA
- Department of Immunobiology, Yale School of Medicine, New Haven, CT 06520, USA
| | - Kenneth B. Hoehn
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA
- Current address: Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Hanover, NH 03755, USA
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7
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Lubow J, Levoir LM, Ralph DK, Belmont L, Contreras M, Cartwright-Acar CH, Kikawa C, Kannan S, Davidson E, Duran V, Rebellon-Sanchez DE, Sanz AM, Rosso F, Doranz BJ, Einav S, Matsen IV FA, Goo L. Single B cell transcriptomics identifies multiple isotypes of broadly neutralizing antibodies against flaviviruses. PLoS Pathog 2023; 19:e1011722. [PMID: 37812640 PMCID: PMC10586629 DOI: 10.1371/journal.ppat.1011722] [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: 05/17/2023] [Revised: 10/19/2023] [Accepted: 09/28/2023] [Indexed: 10/11/2023] Open
Abstract
Sequential dengue virus (DENV) infections often generate neutralizing antibodies against all four DENV serotypes and sometimes, Zika virus. Characterizing cross-flavivirus broadly neutralizing antibody (bnAb) responses can inform countermeasures that avoid enhancement of infection associated with non-neutralizing antibodies. Here, we used single cell transcriptomics to mine the bnAb repertoire following repeated DENV infections. We identified several new bnAbs with comparable or superior breadth and potency to known bnAbs, and with distinct recognition determinants. Unlike all known flavivirus bnAbs, which are IgG1, one newly identified cross-flavivirus bnAb (F25.S02) was derived from IgA1. Both IgG1 and IgA1 versions of F25.S02 and known bnAbs displayed neutralizing activity, but only IgG1 enhanced infection in monocytes expressing IgG and IgA Fc receptors. Moreover, IgG-mediated enhancement of infection was inhibited by IgA1 versions of bnAbs. We demonstrate a role for IgA in flavivirus infection and immunity with implications for vaccine and therapeutic strategies.
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Affiliation(s)
- Jay Lubow
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Lisa M. Levoir
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Duncan K. Ralph
- Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Laura Belmont
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
- Molecular and Cellular Biology Graduate Program, University of Washington, Seattle, Washington, United States of America
| | - Maya Contreras
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Catiana H. Cartwright-Acar
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Caroline Kikawa
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
- Medical Scientist Training Program, University of Washington, Seattle, Washington, United States of America
| | - Shruthi Kannan
- Integral Molecular, Inc., Philadelphia, Pennsylvania, United States of America
| | - Edgar Davidson
- Integral Molecular, Inc., Philadelphia, Pennsylvania, United States of America
| | - Veronica Duran
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
| | | | - Ana M. Sanz
- Clinical Research Center, Fundación Valle del Lili, Cali, Colombia
| | - Fernando Rosso
- Clinical Research Center, Fundación Valle del Lili, Cali, Colombia
- Department of Internal Medicine, Division of Infectious Diseases, Fundación Valle del Lili, Cali, Colombia
| | - Benjamin J. Doranz
- Integral Molecular, Inc., Philadelphia, Pennsylvania, United States of America
| | - Shirit Einav
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
- Chan Zuckerberg Biohub, San Francisco, California, United States of America
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California, United States of America
| | - Frederick A. Matsen IV
- Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
- Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America
- Department of Statistics, University of Washington, Seattle, Washington, United States of America
- Howard Hughes Medical Institute, Seattle, Washington, United States of America
| | - Leslie Goo
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
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8
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Lubow J, Levoir LM, Ralph DK, Belmont L, Contreras M, Cartwright-Acar CH, Kikawa C, Kannan S, Davidson E, Doranz BJ, Duran V, Sanchez DE, Sanz AM, Rosso F, Einav S, Matsen FA, Goo L. Single B cell transcriptomics identifies multiple isotypes of broadly neutralizing antibodies against flaviviruses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.09.536175. [PMID: 37090561 PMCID: PMC10120628 DOI: 10.1101/2023.04.09.536175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Sequential dengue virus (DENV) infections often generate neutralizing antibodies against all four DENV serotypes and sometimes, Zika virus. Characterizing cross-flavivirus broadly neutralizing antibody (bnAb) responses can inform countermeasure strategies that avoid infection enhancement associated with non-neutralizing antibodies. Here, we used single cell transcriptomics to mine the bnAb repertoire following secondary DENV infection. We identified several new bnAbs with comparable or superior breadth and potency to known bnAbs, and with distinct recognition determinants. Unlike all known flavivirus bnAbs, which are IgG1, one newly identified cross-flavivirus bnAb (F25.S02) was derived from IgA1. Both IgG1 and IgA1 versions of F25.S02 and known bnAbs displayed neutralizing activity, but only IgG1 enhanced infection in monocytes expressing IgG and IgA Fc receptors. Moreover, IgG-mediated enhancement of infection was inhibited by IgA1 versions of bnAbs. We demonstrate a role for IgA in flavivirus infection and immunity with implications for vaccine and therapeutic strategies.
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