Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases

  1. Alison Tarke
  2. John Sidney
  3. Conner K. Kidd
  4. Jennifer M. Dan
  5. Sydney I. Ramirez
  6. Esther Dawen Yu
  7. Jose Mateus
  8. Ricardo da Silva Antunes
  9. Erin Moore
  10. Paul Rubiro
  11. Nils Methot
  12. Elizabeth Phillips
  13. Simon Mallal
  14. April Frazier
  15. Stephen A. Rawlings
  16. Jason A. Greenbaum
  17. Bjoern Peters
  18. Davey M. Smith
  19. Shane Crotty
  20. Daniela Weiskopf
  21. Alba Grifoni
  22. Alessandro Sette

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Abstract

No abstract available

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  1. Version published to 10.1016/j.xcrm.2021.100204
  2. ScreenIT

    SciScore for 10.1101/2020.12.08.416750: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    RESOURCE AVAILABILITY: EXPERIMENTAL MODEL AND SUBJECT DETAILS: METHOD DETAILS: BIOINFORMATIC AND STATISTICAL ANALYSIS: FlowJo 10 and GraphPad Prism 8.4 were used to perform data and statistical analyses, unless otherwise stated.
    BIOINFORMATIC
    suggested: (QFAB Bioinformatics, RRID:SCR_012513)
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    GraphPad
    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: We detected the following sentences addressing limitations in the study:
    Limitations and future directions: To maximize cell usage, our analysis was focused on the most dominantly recognized proteins. Screening for less commonly recognized proteins would require a larger cohort to enable identification of a sufficient number of donors responding to each protein. However, such expanded studies would be expected to yield additional epitopes. The limited number of donors studied also did not allow investigation of responses directed against relatively rare HLA alleles, and HLA restrictions were not experimentally verified. The predictions utilized for HLA class I included the top 200 candidates for each allele. Utilizing more generous prediction thresholds is likely to allow for identification of additional epitopes. The limited number of donors also did not allow for the evaluation of potential differences in terms of ethnic background, disease severity, age, and gender. Future investigations will include validation of the epitope pools as potential diagnostic tools, establish a robust, user-friendly T cell assay, and investigate differences in T cell reactivity as a function of ethnicity, disease severity, age, and gender.

    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 10.1101/2020.12.08.416750v1 on bioRxiv