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      Maturation and persistence of the anti-SARS-CoV-2 memory B cell response

      research-article
      1 , 2 , 18 , 1 , 3 , 18 , 4 , 19 , 1 , 2 , 19 , 5 , 6 , 19 , 2 , 7 , 19 , 2 , 7 , 19 , 4 , 19 , 4 , 5 , 6 , 1 , 2 , 8 , 9 , 8 , 10 , 11 , 2 , 2 , 12 , 13 , 14 , 15 , 16 , 14 , 15 , 5 , 6 , 1 , 4 , 1 , 17 , , 1 , 17 , ∗∗ , 1 , 2 , 7 , 17 , 20 , ∗∗∗
      Cell
      Elsevier Inc.
      COVID-19, germinal center, somatic hypermutation, extrafollicular response, plasma cells, neutralizing antibodies, spike protein, RBD, OC43, HKU1

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          Abstract

          Memory B cells play a fundamental role in host defenses against viruses, but to date, their role has been relatively unsettled in the context of SARS-CoV-2. We report here a longitudinal single-cell and repertoire profiling of the B cell response up to 6 months in mild and severe COVID-19 patients. Distinct SARS-CoV-2 spike-specific activated B cell clones fueled an early antibody-secreting cell burst as well as a durable synchronous germinal center response. While highly mutated memory B cells, including pre-existing cross-reactive seasonal Betacoronavirus-specific clones, were recruited early in the response, neutralizing SARS-CoV-2 RBD-specific clones accumulated with time and largely contributed to the late, remarkably stable, memory B cell pool. Highlighting germinal center maturation, these cells displayed clear accumulation of somatic mutations in their variable region genes over time. Overall, these findings demonstrate that an antigen-driven activation persisted and matured up to 6 months after SARS-CoV-2 infection and may provide long-term protection.

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          Abstract

          The B cell response against SARS-CoV-2 shows a temporal shift from an extrafollicular reaction that includes memory B cells against seasonal coronaviruses toward a germinal center-dependent memory response encoding (spike-specific) neutralizing antibodies.

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          Most cited references69

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          Comprehensive Integration of Single-Cell Data

          Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.
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            Fast, sensitive, and accurate integration of single cell data with Harmony

            The emerging diversity of single cell RNAseq datasets allows for the full transcriptional characterization of cell types across a wide variety of biological and clinical conditions. However, it is challenging to analyze them together, particularly when datasets are assayed with different technologies. Here, real biological differences are interspersed with technical differences. We present Harmony, an algorithm that projects cells into a shared embedding in which cells group by cell type rather than dataset-specific conditions. Harmony simultaneously accounts for multiple experimental and biological factors. In six analyses, we demonstrate the superior performance of Harmony to previously published algorithms. We show that Harmony requires dramatically fewer computational resources. It is the only currently available algorithm that makes the integration of ~106 cells feasible on a personal computer. We apply Harmony to PBMCs from datasets with large experimental differences, 5 studies of pancreatic islet cells, mouse embryogenesis datasets, and cross-modality spatial integration.
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              Antibody responses to SARS-CoV-2 in patients with COVID-19

              We report acute antibody responses to SARS-CoV-2 in 285 patients with COVID-19. Within 19 days after symptom onset, 100% of patients tested positive for antiviral immunoglobulin-G (IgG). Seroconversion for IgG and IgM occurred simultaneously or sequentially. Both IgG and IgM titers plateaued within 6 days after seroconversion. Serological testing may be helpful for the diagnosis of suspected patients with negative RT-PCR results and for the identification of asymptomatic infections.
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                Author and article information

                Journal
                Cell
                Cell
                Cell
                Elsevier Inc.
                0092-8674
                1097-4172
                2 February 2021
                4 March 2021
                2 February 2021
                : 184
                : 5
                : 1201-1213.e14
                Affiliations
                [1 ]Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Université de Paris, Paris, France
                [2 ]Service de Médecine Interne, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hôpitaux de Paris (AP-HP), Université Paris-Est Créteil (UPEC), Créteil, France
                [3 ]Inovarion, Paris, France
                [4 ]Institut Pasteur, Unité de Virologie Structurale, CNRS UMR 3569, Paris, France
                [5 ]Département de Virologie, Bactériologie, Hygiène et Mycologie-Parasitologie, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hôpitaux de Paris (AP-HP), Créteil, France
                [6 ]INSERM U955, équipe 18, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France
                [7 ]INSERM U955, équipe 2, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France
                [8 ]Département Immunologie-Hématologie, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hôpitaux de Paris (AP-HP), Université Paris-Est Créteil (UPEC), 94000 Créteil, France
                [9 ]INSERM U955, équipe immunorégulation et biothérapie (I-BIOT), Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France
                [10 ]Institut de Recherche Vaccinale (VRI), Université Paris-Est Créteil (UPEC), Faculté de Médecine, Créteil, France
                [11 ]INSERM U955, équipe 16, Institut Mondor de Recherche Biomédicale (IMRB), Université Paris-Est Créteil (UPEC), Créteil, France
                [12 ]Département de Santé Publique, Unité de Recherche Clinique (URC), CEpiA (Clinical Epidemiology and Ageing), EA 7376, Institut Mondor de Recherche Biomédicale (IMRB), Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hôpitaux de Paris (AP-HP), Université Paris-Est Créteil (UPEC), Créteil, France
                [13 ]Etablissement Français du Sang, INSERM U955, Université Paris-Est Créteil (UPEC), Créteil, France
                [14 ]Réponses inflammatoires et réseaux transcriptomiques dans les maladies, Institut Imagine, INSERM UMR1163, ATIP-Avenir Team, Université de Paris, Paris, France
                [15 ]Labtech Single-cell@Imagine, Institut Imagine, INSERM UMR 1163, Paris, France
                [16 ]Plateforme de Cytométrie en Flux, Structure Fédérative de Recherche Necker, INSERM US24-CNRS UMS3633, Paris, France
                Author notes
                []Corresponding author
                [∗∗ ]Corresponding author
                [∗∗∗ ]Corresponding author
                [17]

                Senior author

                [18]

                These authors contributed equally

                [19]

                These authors contributed equally

                [20]

                Lead contact

                Article
                S0092-8674(21)00093-3
                10.1016/j.cell.2021.01.050
                7994111
                33571429
                4e93ea44-e6f7-4e5a-a59a-b74f5367c59d
                © 2021 Elsevier Inc.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 18 November 2020
                : 9 January 2021
                : 26 January 2021
                Categories
                Article

                Cell biology
                covid-19,germinal center,somatic hypermutation,extrafollicular response,plasma cells,neutralizing antibodies,spike protein,rbd,oc43,hku1

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