Stereotypic Neutralizing V H Clonotypes Against SARS-CoV-2 RBD in COVID-19 Patients and the Healthy Population

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Abstract

In six of seven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients, V H clonotypes, encoded by either immunoglobin heavy variable (IGHV)3-53 or IGHV3-66 and immunoglobin heavy joining (IGHJ)6, were identified in IgG 1 , IgA 1 , and IgA 2 subtypes, with minimal mutations, and could be paired with diverse light chains, resulting in binding to the SARS-CoV-2 receptor-binding domain (RBD). Because most human antibodies against the RBD neutralized the virus by inhibiting host cell entry, we selected one of these clonotypes and demonstrated that it could potently inhibit viral replication. Interestingly, these V H clonotypes pre-existed in six of 10 healthy individuals, predominantly as IgM isotypes, which could explain the expeditious and stereotypic development of these clonotypes among SARS-CoV-2 patients.

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  1. SciScore for 10.1101/2020.06.26.174557: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIRB: The study involving human sample collection was approved by the Institutional Ethics Review Board of Seoul National University Hospital (IRB approval number: 2004-230-1119).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.


    Results from OddPub: Thank you for sharing your code and data.


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.