Memory B cells control SARS-CoV-2 variants upon mRNA vaccination of naive and COVID-19 recovered individuals

  1. Aurélien Sokal
  2. Giovanna Barba-Spaeth
  3. Ignacio Fernández
  4. Matteo Broketa
  5. Imane Azzaoui
  6. Andrea de La Selle
  7. Alexis Vandenberghe
  8. Slim Fourati
  9. Anais Roeser
  10. Annalisa Meola
  11. Magali Bouvier-Alias
  12. Etienne Crickx
  13. Laetitia Languille
  14. Marc Michel
  15. Bertrand Godeau
  16. Sébastien Gallien
  17. Giovanna Melica
  18. Yann Nguyen
  19. Virginie Zarrouk
  20. Florence Canoui-Poitrine
  21. France Noizat-Pirenne
  22. Jérôme Megret
  23. Jean-Michel Pawlotsky
  24. Simon Fillatreau
  25. Pierre Bruhns
  26. Felix A. Rey
  27. Jean-Claude Weill
  28. Claude-Agnès Reynaud
  29. Pascal Chappert
  30. Matthieu Mahévas

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Abstract

How a previous SARS-CoV-2 infection may amplify and model the memory B cell (MBC) response elicited by mRNA vaccines was addressed by a comparative longitudinal study of two cohorts, naive individuals and disease-recovered patients, up to 2 months after vaccination. The quality of the memory response was assessed by analysis of the VDJ repertoire, affinity and neutralization against variants of concerns (VOC), using unbiased cultures of 2452 MBCs. Upon boost, the MBC pool of recovered patients selectively expanded, further matured and harbored potent neutralizers against VOC. Maturation of the MBC response in naive individuals was much less pronounced. Nevertheless, and as opposed to their weaker neutralizing serum response, half of their RBD-specific MBCs displayed high affinity towards multiple VOC and one-third retained neutralizing potency against B.1.351. Thus, repeated vaccine challenges could reduce these differences by recall of affinity-matured MBCs and allow naive vaccinees to cope efficiently with VOC.

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  1. ScreenIT

    SciScore for 10.1101/2021.06.17.448459: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Anti-RBD (S) SARS-CoV-2 antibodies assay: Serum samples were analyzed for IgG anti-S-RBD IgG titration with the SARS-CoV-2 IgG Quant II assay (ARCHITECT®, Abbott Laboratories).
    Anti-RBD
    suggested: None
    SARS-CoV-2
    suggested: None
    anti-S-RBD IgG
    suggested: None
    Cells were washed and resuspended in the same conditions, then the fluorochrome-conjugated antibody cocktail including the 2 anti-His antibodies was added at pre-titrated concentrations for 20 min at 4°C and viable cells were identified using a LIVE/DEAD Fixable Aqua Dead Cell Stain Kit (Thermo Fisher Scientific) incubated with conjugated antibodies.
    anti-His
    suggested: None
    Anti-Human Fc Capture (AHC) biosensors (18-5060) were immersed in supernatants from single-cell memory B cell culture (or control monoclonal antibody) at 25°C for 1800 seconds.
    Anti-Human Fc Capture ( AHC
    suggested: None
    Cells were fixed with 4% formaldehyde and foci were revealed using a rabbit anti-SARS-CoV-2 N antibody (gift of Nicolas Escriou) and anti-rabbit secondary HRP-conjugated secondary antibody.
    anti-SARS-CoV-2 N
    suggested: None
    anti-rabbit
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Vero E6 cells were seeded at 2×104 cells/well in a 96-well plate 24h before the assay.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Anti-RBD (S) SARS-CoV-2 antibodies assay: Serum samples were analyzed for IgG anti-S-RBD IgG titration with the SARS-CoV-2 IgG Quant II assay (ARCHITECT®, Abbott Laboratories).
    Abbott Laboratories
    suggested: None
    Data were analyzed with FlowJo or Kaluza softwares.
    Kaluza
    suggested: (Kaluza, RRID:SCR_016182)
    The UMAP (v3.1) plugin in FlowJO was used to calculate the UMAP coordinates for the resulting 536.161 cells (with 30 neighbors, metric = euclidian and minimum distance = 0.5 as default parameters).
    FlowJO
    suggested: (FlowJo, RRID:SCR_008520)
    Both UMAP and FlowSOM plugin were run taking into account fluorescent intensities from the following parameters: FSC-A, SSC-A, CD19, CD21, CD11c, CD71, CD38, CD27 and IgD.
    FlowSOM
    suggested: (FlowSOM, RRID:SCR_016899)
    For visualization purposes, only the outermost density representing 95% of the total gated cells was kept for the final figure, all other levels were removed in Adobe Illustrator.
    Adobe Illustrator
    suggested: (Adobe Illustrator, RRID:SCR_010279)
    Sequence quality was verified with the CodonCode Aligner software (CodonCode Corporation).
    CodonCode Aligner
    suggested: None
    Computational analyses of VDJ sequences: Processed FASTA sequences from cultured single-cell VH sequencing were annotated using Igblast v1.16.0 against the human IMGT reference database.
    Igblast
    suggested: (IgBLAST, RRID:SCR_002873)
    VH repartitions and Shannon entropies were calculated using the countGenes() and alphaDiversity() functions from the Immcantation/alakazam v1.1.0 R package.
    Immcantation/alakazam
    suggested: None
    Graphics were obtained using the ggplot2 v3.3.3, pheatmap v1.0.12 and circlize v0.4.12 packages.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    pheatmap
    suggested: (pheatmap, RRID:SCR_016418)
    circlize
    suggested: (circlize, RRID:SCR_002141)
    Sera IC50 were calculated over 6 four-fold serial dilutions from 1/10 to 1/10000 using the equation log (inhibitor) vs. normalized response – Variable slope in Prism 9 (GraphPad software LLC).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Statistical analyses were all performed using GraphPad Prism 9.0 (La Jolla, CA, USA).
    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04402892Not yet recruitingCOVID-19: SARS-CoV-2 Specific Memory B and T-CD4+ Cells

    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.

    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 10.1101/2021.06.17.448459v1 on bioRxiv