SARS-CoV-2 sculpts the immune system to induce sustained virus-specific naïve-like and memory B cell responses

  1. Leire de Campos-Mata
  2. Sonia Tejedor Vaquero
  3. Roser Tachó-Piñot
  4. Janet Piñero
  5. Emilie K. Grasset
  6. Itziar Arrieta Aldea
  7. Natalia Rodrigo Melero
  8. Carlo Carolis
  9. Juan P. Horcajada
  10. Andrea Cerutti
  11. Judit Villar-García
  12. Giuliana Magri

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Abstract

SARS-CoV-2 infection induces virus-reactive memory B cells expressing unmutated antibodies, which hints at their emergence from naïve B cells. Yet, the dynamics of virus-specific naïve B cells and their impact on immunity and immunopathology remain unclear. Here, we longitudinally studied moderate to severe COVID-19 patients to dissect SARS-CoV-2-specific B cell responses overtime. We found a broad virus-specific antibody response during acute infection, which evolved into an IgG1-dominated response during convalescence. Acute infection was associated with increased mature B cell progenitors in the circulation and the unexpected expansion of virus-targeting naïve-like B cells that further augmented during convalescence together with virus-specific memory B cells. In addition to a transitory increase in tissue-homing CXCR3 + plasmablasts and extrafollicular memory B cells, most COVID-19 patients showed persistent activation of CD4 + and CD8 + T cells along with transient or long-lasting changes of key innate immune cells. Remarkably, virus-specific antibodies and the frequency of naïve B cells were among the major variables defining distinct immune signatures associated with disease severity and inflammation. Aside from providing new insights into the complexity of the immune response to SARS-CoV-2, our findings indicate that the de novo recruitment of mature B cell precursors into the periphery may be central to the induction of antiviral immunity.

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  1. ScreenIT

    SciScore for 10.1101/2021.04.29.21256002: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Experimental Model and Subject Details Study Cohort: Blood samples were collected from COVID-19 patients (n = 25) in acute phase of infection (COVT1) hospitalized at the Hospital del Mar (Barcelona, Spain), with patient informed consent.
    IRB: All procedures followed were approved by the Ethical Committee for Clinical Investigation of the Institut Hospital del Mar d’Investigacions Mèdiques (Number 2020/9189/I).
    Sex as a biological variable52 % were males.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    After washing, plates were incubated with horseradish peroxidase (HRP)-conjugated anti-human Ig secondary antibodies diluted in PBS containing 0.05% Tween 20 1% BSA for 45 minutes at RT.
    anti-human Ig secondary
    suggested: None
    To assess the distribution of the different IgG antibody subclasses, HRP-conjugated anti-human IgG1, IgG2, IgG3 and IgG4 (Southern Biotech) were used at a 1:3000 dilution.
    anti-human IgG1
    suggested: None
    IgG2, IgG3
    suggested: None
    IgG4
    suggested: None
    To quantitate the level of each viral antigen-specific antibody class or subclasses optical density (OD) values were calculated after subtraction of background (OD450 of serum dilutions on PBS-coated plates) and the area under the curve (AUC) derived from optical density measurements of six serial dilutions was determined using Prism 8 (GraphPad).
    antigen-specific
    suggested: None
    Cells were then resuspended in 2 mL of LIVE/DEAD Fixable Yellow Dead Cell Stain Kit (Thermo Fisher Scientific) 1:20000 in PBS, incubated for 30 min at RT and stained with two different fluorophore-conjugated antibody cocktails (Table S2 and S4).
    S4
    suggested: None
    Anti-CCR7 antibody was added first and incubated for 10 min.
    Anti-CCR7
    suggested: None
    Then, all other anti-chemokine receptor antibodies (CXCR3, CXCR4, CXCR5, CCR4 and CCR6 for MIX3, and CXCR3 and CXCR4 for MIX 1) were added to the corresponding tubes and incubated for 10 min.
    anti-chemokine receptor
    suggested: None
    CXCR3
    suggested: None
    CXCR4
    suggested: None
    CXCR5
    suggested: None
    CCR4
    suggested: None
    CCR6
    suggested: None
    MIX3
    suggested: None
    Cells were then washed and stained with the MIX 2 antibody cocktail for 10 min using anti-human IgA AmCyan instead of anti-human IgA FITC (Table S3) and DAPI fluorescent dye (Sigma Aldrich).
    anti-human IgA
    suggested: None
    Principal component analysis (PCA) was used to identify the most important features from 41 variables (including antibody titers and immune parameters; Data File S1) using COVT1 (n = 25), COVT2 (n = 20) and healthy controls (n = 16).
    COVT1
    suggested: None
    COVT2
    suggested: None
    Recombinant DNA
    SentencesResources
    The pLVX-EF1alpha-nCoV2019-N-2xStrep-IRES-Puro construct, encoding for the full-length SARS-CoV-2 nucleocapsid protein (NP) fused to a double Strep-tag at the C-terminus was a gift from Dr Krogan (University of California, San Francisco USA).
    pLVX-EF1alpha-nCoV2019-N-2xStrep-IRES-Puro
    suggested: None
    Software and Algorithms
    SentencesResources
    To quantitate the level of each viral antigen-specific antibody class or subclasses optical density (OD) values were calculated after subtraction of background (OD450 of serum dilutions on PBS-coated plates) and the area under the curve (AUC) derived from optical density measurements of six serial dilutions was determined using Prism 8 (GraphPad).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    High-dimensional data analysis of flow cytometry data: t-Distributed Stochastic Neighbor Embedding (tSNE) analyses were performed with Flowjo V10.6.2 software.
    Flowjo
    suggested: (FlowJo, RRID:SCR_008520)
    Data analysis and visualization: GraphPad Prism (version 8.0) and R (version 3.6.3, R Core Team (2019).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 36. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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.

  2. Version published to 10.1101/2021.04.29.21256002 on medRxiv
  3. Version published to 10.1002/cti2.1339