Immunoreactive peptide maps of SARS-CoV-2 and other human coronaviruses

  1. Nischay Mishra
  2. Xi Huang
  3. Shreyas Joshi
  4. Cheng Guo
  5. James Ng
  6. Riddhi Thakkar
  7. Yongjian Wu
  8. Xin Dong
  9. Qianlin Li
  10. Richard Pinapati
  11. Eric Sullivan
  12. Adrian Caciula
  13. Rafal Tokarz
  14. Thomas Briese
  15. Jiahai Lu
  16. W. Ian Lipkin

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Abstract

Serodiagnosis of SARS-CoV-2 infection is impeded by immunological cross-reactivity to the human coronaviruses (HCoV) SARS-CoV-2, SARS-CoV-1, MERS-CoV, OC43, 229E, HKU1, and NL63. Here we report the identification of humoral immune responses to SARS-CoV-2 and other HCoV peptides that can be used to detect asymptomatic, mild and, severe SARS-CoV-2 infections, and may enable the discovery of biomarkers for immunity following infection or vaccination.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.13.249953: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Samples & experimental design: The study was approved by the Medical Ethical Committee of Sun Yat-Sen University (approval number 2020-060).
    Consent: An informed and written consent was obtained by patients.
    Randomization1000 randomly selected 12 aa long scrambled peptides were added for background correction and nonspecific binding of peptides.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    To enable differential detection of antibodies specific for SARS-CoV-2 infections, we created a database comprising the proteomes of seven human coronaviruses: SARS-CoV-2, SARS, MERS, NL-63, OC-43, 229E and HKU1 (Supplementary Table 1).
    HKU1
    suggested: None
    Secondary antibodies IgG (cat no. 109-605-098, Alexa Fluor 647-AffiniPure Goat Anti-Human IgG, Fcy fragment specific, Jackson ImmunoResearch Labs) and IgM (cat no. 109-165-129, Cy™3
    Anti-Human IgG
    suggested: None
    IgM
    suggested: None
    Software and Algorithms
    SentencesResources
    The normalization, background correction and statistical comparison of peptide microarray intensities between groups was performed using the edgeR package17.
    edgeR
    suggested: (edgeR, RRID:SCR_012802)
    The code for reassembly and plots was prepared using Rstudio v 1.2.501919.
    Rstudio
    suggested: (RStudio, RRID:SCR_000432)
    The Heatmap plots were generated using ggplot2 package20.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Alignment of reactive epitopes on SARS-CoV-2 proteome was performed using Geneious version 10.0.9.
    Geneious
    suggested: (Geneious, RRID:SCR_010519)

    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.

  2. Version published to 10.1101/2020.08.13.249953 on bioRxiv