Epitope-specific antibody responses differentiate COVID-19 outcomes and variants of concern

  1. Courtney Voss
  2. Sally Esmail
  3. Xuguang Liu
  4. Michael J. Knauer
  5. Suzanne Ackloo
  6. Tomonori Kaneko
  7. Lori Lowes
  8. Peter Stogios
  9. Almagul Seitova
  10. Ashley Hutchinson
  11. Farhad Yusifov
  12. Tatiana Skarina
  13. Elena Evdokimova
  14. Peter Loppnau
  15. Pegah Ghiabi
  16. Taraneh Haijan
  17. Shanshan Zhong
  18. Husam Abdoh
  19. Benjamin D. Hedley
  20. Vipin Bhayana
  21. Claudio M. Martin
  22. Marat Slessarev
  23. Benjamin Chin-Yee
  24. Douglas D. Fraser
  25. Ian Chin-Yee
  26. Shawn S.C. Li

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The role of humoral immunity in COVID-19 is not fully understood, owing, in large part, to the complexity of antibodies produced in response to the SARS-CoV-2 infection. There is a pressing need for serology tests to assess patient-specific antibody response and predict clinical outcome.

METHODS

Using SARS-CoV-2 proteome and peptide microarrays, we screened 146 COVID-19 patients’ plasma samples to identify antigens and epitopes. This enabled us to develop a master epitope array and an epitope-specific agglutination assay to gauge antibody responses systematically and with high resolution.

RESULTS

We identified linear epitopes from the spike (S) and nucleocapsid (N) proteins and showed that the epitopes enabled higher resolution antibody profiling than the S or N protein antigen. Specifically, we found that antibody responses to the S-811–825, S-881–895, and N-156–170 epitopes negatively or positively correlated with clinical severity or patient survival. Moreover, we found that the P681H and S235F mutations associated with the coronavirus variant of concern B.1.1.7 altered the specificity of the corresponding epitopes.

CONCLUSION

Epitope-resolved antibody testing not only affords a high-resolution alternative to conventional immunoassays to delineate the complex humoral immunity to SARS-CoV-2 and differentiate between neutralizing and non-neutralizing antibodies, but it also may potentially be used to predict clinical outcome. The epitope peptides can be readily modified to detect antibodies against variants of concern in both the peptide array and latex agglutination formats.

FUNDING

Ontario Research Fund (ORF) COVID-19 Rapid Research Fund, Toronto COVID-19 Action Fund, Western University, Lawson Health Research Institute, London Health Sciences Foundation, and Academic Medical Organization of Southwestern Ontario (AMOSO) Innovation Fund.

Article activity feed

  1. Version published to 10.1172/jci.insight.148855
  2. ScreenIT

    SciScore for 10.1101/2021.03.16.21253716: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Blood sample collection: Blood samples were collected following a protocol (study number: 116284) approved by the Research Ethics Board (REB) of Western University.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Slides were then rinsed quickly three times followed by three 5min washes with TBST before probing with goat anti-human IgG HRP antibody at 1:10,000 (Millipore Sigma) in ChonBlock for 1h.
    anti-human IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Array Quantification: Peptide walking arrays, literature-reported epitope peptide arrays and the master epitope arrays were quantified using ImageJ software(42).
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    Statistical analysis: All statistical analyses were done using the GraphPad Prism9 software.
    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: 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 10.1101/2021.03.16.21253716v1 on medRxiv