Distinct systemic and mucosal immune responses during acute SARS-CoV-2 infection

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Abstract

Coordinated local mucosal and systemic immune responses following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection either protect against coronavirus disease 2019 (COVID-19) pathologies or fail, leading to severe clinical outcomes. To understand this process, we performed an integrated analysis of SARS-CoV-2 spike-specific antibodies, cytokines, viral load and bacterial communities in paired nasopharyngeal swabs and plasma samples from a cohort of clinically distinct patients with COVID-19 during acute infection. Plasma viral load was associated with systemic inflammatory cytokines that were elevated in severe COVID-19, and also with spike-specific neutralizing antibodies. By contrast, nasopharyngeal viral load correlated with SARS-CoV-2 humoral responses but inversely with interferon responses, the latter associating with protective microbial communities. Potential pathogenic microorganisms, often implicated in secondary respiratory infections, were associated with mucosal inflammation and elevated in severe COVID-19. Our results demonstrate distinct tissue compartmentalization of SARS-CoV-2 immune responses and highlight a role for the nasopharyngeal microbiome in regulating local and systemic immunity that determines COVID-19 clinical outcomes.

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  1. SciScore for 10.1101/2021.03.01.21251633: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Biological collection and informed consent were approved by the Direction de la Recherche Clinique et Innovation (DRCI) and the French Ministry of Research (N°2019-3677).
    IRB: The study conforms to the principles outlined in the Declaration of Helsinki, and received approval by the appropriate Institutional Review Board (Cochin-Port Royal Hospital, Paris
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableThe median age of the patients was 55 years (interquartile range, 50 to 63) and 78% were male, while median age of healthy controls was 51 years (interquartile range, 38 to 60) and 72% were male.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    For the IFNγ assay, the MD-1 antibody clone (BioLegend) was used as a capture antibody after coating on paramagnetic beads (0.3 mg/mL), the 25718 antibody clone (R&D Systems) was biotinylated (biotin/antibody ratio = 40/1) and used as the detector antibody at a concentration of 0.3ug/mL.
    MD-1
    suggested: None
    For the IL-17A assay, the BL23 antibody clone (BioLegend) was used as a capture antibody after coating on paramagnetic beads (0.3 mg/mL), the MT504 antibody clone (MabTech), already biotinylated, was used as the detector antibody at a concentration of 0.3ug/mL.
    BL23
    suggested: (BioLegend Cat# 512705, RRID:AB_2783336)
    MT504
    suggested: None
    For the IFNβ assay, the 710322-9 IgG1, kappa, mouse monoclonal antibody (PBL Assay Science) was used as a capture antibody after coating paramagnetic beads (0.3 mg/mL), the 710323-9 IgG1, kappa, mouse monoclonal antibody (PBL Assay Science) was biotinylated (biotin/antibody ratio = 40/1) and used as the detector antibody, and recombinant protein (PBL Assay Science) were used to quantify IFNβ concentrations.
    IgG1
    suggested: None
    For the IFNλ3 assay, the MMHL-3 IgG1 kappa mouse monoclonal antibody (PBL Assay Science) was used as a capture antibody after coating paramagnetic beads (0.3 mg/mL), the 567107R IgG2a mouse monoclonal antibody (R&D systems) was biotinylated (biotin/antibody ratio = 60/1) and used as the detector antibody, and recombinant protein (PBL Assay Science) were used to quantify IFNλ3 concentrations.
    MMHL-3 IgG1
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Briefly, a standard ELISA assay using as target antigens the extracellular domain of the S protein in the form of a trimer (ELISA tri-S) and the S-Flow assay, which is based on the recognition of SARS-CoV-2 S protein expressed on the surface of 293T cells (293T-S), were used to quantify SARS-CoV-2 specific IgG and IgA subtypes in plasma and nasal swab supernatants.
    293T
    suggested: RRID:CVCL_LC70)
    Software and Algorithms
    SentencesResources
    Briefly, amplicons were clustered into operational taxonomic units (OTU) with VSEARCH (v1.4) and aligned against the SILVA database.
    VSEARCH
    suggested: None
    SILVA
    suggested: (SILVA, RRID:SCR_006423)
    Statistical analysis: GraphPad Prism was used for statistical analysis.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Plots were made using the ggplot2 package (v3.3.2).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    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.