Single-cell profiling of the antigen-specific response to BNT162b2 SARS-CoV-2 RNA vaccine

  1. Kevin J. Kramer
  2. Erin M. Wilfong
  3. Kelsey Voss
  4. Sierra M. Barone
  5. Andrea R. Shiakolas
  6. Nagarajan Raju
  7. Caroline E. Roe
  8. Naveenchandra Suryadevara
  9. Lauren M. Walker
  10. Steven C. Wall
  11. Ariana Paulo
  12. Samuel Schaefer
  13. Debolanle Dahunsi
  14. Camille S. Westlake
  15. James E. Crowe
  16. Robert H. Carnahan
  17. Jeffrey C. Rathmell
  18. Rachel H. Bonami
  19. Ivelin S. Georgiev
  20. Jonathan M. Irish

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Abstract

RNA-based vaccines against SARS-CoV-2 have proven critical to limiting COVID-19 disease severity and spread. Cellular mechanisms driving antigen-specific responses to these vaccines, however, remain uncertain. Here we identify and characterize antigen-specific cells and antibody responses to the RNA vaccine BNT162b2 using multiple single-cell technologies for in depth analysis of longitudinal samples from a cohort of healthy participants. Mass cytometry and unbiased machine learning pinpoint an expanding, population of antigen-specific memory CD4 + and CD8 + T cells with characteristics of follicular or peripheral helper cells. B cell receptor sequencing suggest progression from IgM, with apparent cross-reactivity to endemic coronaviruses, to SARS-CoV-2-specific IgA and IgG memory B cells and plasmablasts. Responding lymphocyte populations correlate with eventual SARS-CoV-2 IgG, and a participant lacking these cell populations failed to sustain SARS-CoV-2-specific antibodies and experienced breakthrough infection. These integrated proteomic and genomic platforms identify an antigen-specific cellular basis of RNA vaccine-based immunity.

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  1. Version published to 10.1038/s41467-022-31142-5
  2. ScreenIT

    SciScore for 10.1101/2021.07.28.453981: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Informed consent was obtained, and a baseline health questionnaire was also completed.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    In vitro characterization of CD38+ICOS+ Cells: Quantification of CD38+ICOS+ CD4 and CD8 T cells by flow cytometry: To quantify CD38+ICOS+ CD4 and CD8 T cells, PBMCs were first resuspended with Human TruStain Fcx (Biolegend) for 10 minutes at room temperature and then stained with the following antibodies in FACS buffer (PBS+ 2% fetal bovine serum): CD8a e450 (Invitrogen 48-0086-42,
    CD38+ICOS+
    suggested: None
    CD4
    suggested: None
    Additional intracellular antibodies were: TNF-a AF488 (Biolegend 502915, 1:100)
    AF488
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Triplicate wells containing virus only (maximal CPE in the absence of mAb) and wells containing only Vero cells in medium (no-CPE wells) were included as controls.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)
    Software and Algorithms
    SentencesResources
    Mass cytometry datasets in this manuscript have been deposited in FlowRepository (http://flowrepository.org/).
    FlowRepository
    suggested: (FLOWRepository, RRID:SCR_013779)
    Comparisons of population frequencies pre- and post-vaccination as well as correlations between post-vaccine cell frequencies and IgG titers were done in GraphPad Prism version 9.0.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Cells were analyzed on a Miltenyi MACSQuant16 Analyzer with single-stain control PBMC samples used for compensation conducted in FlowJo v10.6.2.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    ) sequencing core at an appropriate target concentration for 10X Genomics library preparation and subsequent sequencing.
    Genomics
    suggested: (UTHSCSA Genomics Core, RRID:SCR_012239)
    Briefly, 50 μL of cell culture medium (DMEM supplemented with 2% FBS) was added to each well of a 96-well E-plate using a ViaFlo384 liquid handler (Integra Biosciences) to obtain background reading.
    Integra Biosciences
    suggested: None
    RTCA IC50 values were determined by nonlinear regression analysis using Prism software.
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    Single-Cell RNA-Seq analysis: Single-cell analysis was performed using Seurat v4.0.0 (14)
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)

    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 pages 34, 35, 36 and 50. 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

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  3. Version published to 10.1101/2021.07.28.453981v1 on bioRxiv