SARS-CoV-2 genome-wide T cell epitope mapping reveals immunodominance and substantial CD8 + T cell activation in COVID-19 patients

  1. Sunil Kumar Saini
  2. Ditte Stampe Hersby
  3. Tripti Tamhane
  4. Helle Rus Povlsen
  5. Susana Patricia Amaya Hernandez
  6. Morten Nielsen
  7. Anne Ortved Gang
  8. Sine Reker Hadrup

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Abstract

CD8 + T cell recognition is detected throughout the SARS-CoV-2 genome and is associated with COVID-19 disease severity.

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  1. Version published to 10.1126/sciimmunol.abf7550
  2. ScreenIT

    SciScore for 10.1101/2020.10.19.344911: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Clinical samples: Approval for the study design and sample collection was obtained from the Commitee on Health Research Ethics in the Capital Region of Denmark.
    Consent: All included patients and health care employees gave their informed written consent for inclusion.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Cells were then mixed with 20 μL antibody staining solution CD8-BV480 (BD B566121) (final dilution 1/50), dump channel antibodies (CD4-FITC (BD 345768) (final dilution 1/80), CD14-FITC (BD 345784) (final dilution 1/32), CD19-FITC (BD 345776) (final dilution 1/16), CD40-FITC (Serotech MCA1590F) (final dilution 1/40), CD16-FITC (BD 335035) (final dilution 1/64)) and a dead cell marker (LIVE/DEAD Fixable Near-IR; Invitrogen L10119) (final dilution 1/1000) and incubated for 30 min at 4°C.
    CD40-FITC
    suggested: (Sigma-Aldrich Cat# SAB4700177, RRID:AB_10897459)
    Surface marker antibodies CD3-FITC (BD Biosciences 345764 (final dilution 1/20)), CD4-BUV395 (BD Biosciences 742738 (final dilution 1/300), CD8-BV480 (BD Biosciences B566121 (final dilution 1/50)), and dead cell marker (LIVE/DEAD Fixable Near-IR; Invitrogen L10119) (final dilution 1/1000)) were used to identify CD8+ T cells producing intracellular cytokines (Gating strategy, Supplementary Figure 5).
    CD8-BV480
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    The similarity of SARS-CoV-2 ligands and epitopes from both patient and healthy donor cohorts to a set of human common cold corona viruses (HCoV-HKU1, HCoV-229E, HCoV-NL63, HCoV-OC43) was tested using two methods.
    HCoV-NL63
    suggested: RRID:CVCL_RW88)
    Software and Algorithms
    SentencesResources
    , Becton Dickinson) and gated by the FACSDiva acquisition program (Becton Dickinson), and all the PE-positive (SARS-CoV-2 multimer binding) and APC-positive (CEF multimer binding) cells of CD8+ gate were sorted into pre-saturated tubes (2% BSA, 100 μl barcode cytometry buffer) (Supplementary Figure 9A)
    FACSDiva
    suggested: (BD FACSDiva Software, RRID:SCR_001456)
    The analysis of barcode enrichment was based on methods designed for the analysis of RNA-seq data and was implemented in the R package edgeR.
    edgeR
    suggested: (edgeR, RRID:SCR_012802)
    downsampled (FlowJo plugin), and visualized using UMAP (Version 2.2,
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    The data was plotted using python 3.7.4.
    python
    suggested: (IPython, RRID:SCR_001658)
    Box plots for data quantification and visualization were generated, and their related statistical analyses were performed using GraphPad Prism (GraphPad Software Inc.) (Figure 2C; Figure 3C, D, F; Figure 4A, B, D) or R studio (Supplementary Figure 8).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    For unpaired comparisons Mann-Whitney test was done using GraphPad Prism, all p values are indicated in figure legends.
    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: 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.

  3. Version published to 10.1101/2020.10.19.344911 on bioRxiv