Immunoreactive peptide maps of SARS-CoV-2

  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 S. 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 among the human coronaviruses (HCoVs): 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 peptides that may enable discrimination between exposure to SARS-CoV-2 and other HCoVs. We used a high-density peptide microarray and plasma samples collected at two time points from 50 subjects with SARS-CoV-2 infection confirmed by qPCR, samples collected in 2004–2005 from 11 subjects with IgG antibodies to SARS-CoV-1, 11 subjects with IgG antibodies to other seasonal human coronaviruses (HCoV), and 10 healthy human subjects. Through statistical modeling with linear regression and multidimensional scaling we identified specific peptides that were reassembled to identify 29 linear SARS-CoV-2 epitopes that were immunoreactive with plasma from individuals who had asymptomatic, mild or severe SARS-CoV-2 infections. Larger studies will be required to determine whether these peptides may be useful in serodiagnostics.

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  1. Version published to 10.1038/s42003-021-01743-9
  2. 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

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  3. Version published to 10.1101/2020.08.13.249953v1 on bioRxiv