Analysis of SARS-CoV-2 antibodies in COVID-19 convalescent blood using a coronavirus antigen microarray

  1. Rafael R. de Assis
  2. Aarti Jain
  3. Rie Nakajima
  4. Algis Jasinskas
  5. Jiin Felgner
  6. Joshua M. Obiero
  7. Philip J. Norris
  8. Mars Stone
  9. Graham Simmons
  10. Anil Bagri
  11. Johannes Irsch
  12. Martin Schreiber
  13. Andreas Buser
  14. Andreas Holbro
  15. Manuel Battegay
  16. Philip Hosimer
  17. Charles Noesen
  18. Oluwasanmi Adenaiye
  19. Sheldon Tai
  20. Filbert Hong
  21. Donald K. Milton
  22. D. Huw Davies
  23. Paul Contestable
  24. Laurence M. Corash
  25. Michael P. Busch
  26. Philip L. Felgner
  27. Saahir Khan

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Abstract

The current practice for diagnosis of COVID-19, based on SARS-CoV-2 PCR testing of pharyngeal or respiratory specimens in a symptomatic patient at high epidemiologic risk, likely underestimates the true prevalence of infection. Serologic methods can more accurately estimate the disease burden by detecting infections missed by the limited testing performed to date. Here, we describe the validation of a coronavirus antigen microarray containing immunologically significant antigens from SARS-CoV-2, in addition to SARS-CoV, MERS-CoV, common human coronavirus strains, and other common respiratory viruses. A comparison of antibody profiles detected on the array from control sera collected prior to the SARS-CoV-2 pandemic versus convalescent blood specimens from virologically confirmed COVID-19 cases demonstrates near complete discrimination of these two groups, with improved performance from use of antigen combinations that include both spike protein and nucleoprotein. This array can be used as a diagnostic tool, as an epidemiologic tool to more accurately estimate the disease burden of COVID-19, and as a research tool to correlate antibody responses with clinical outcomes.

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  1. Version published to 10.1038/s41467-020-20095-2
  2. ScreenIT

    SciScore for 10.1101/2020.04.15.043364: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: These were sourced from discarded clinical laboratory specimens exempted from informed consent and IRB approval under condition of patient anonymity.
    IRB: Electronic informed consents including future research use authorization was obtained under protocols approved by the Institutional Review Boards (IRBs) of the University of Maryland and the Department of Navy Human Research Protections Office.
    RandomizationFor this, the samples were randomly partitioned into two groups, at a ratio of 75%/25%, using the caret package (version 6.9-86).
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    A mixture of human IgG and IgA secondary antibodies conjugated to quantum dot fluorophores Q800 and Q585 respectively was applied to each of the microarray pads and incubated for 2 hours at room temperature, and pads were then washed with T-TBS 3 times for 5 minutes each and dried.
    IgA
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Specimen Testing on Coronavirus Antigen Microarray: The coronavirus antigen microarray used in this investigation includes 67 antigens across subtypes expressed in either baculovirus or HEK-293 cells (Supplementary Table 2).
    HEK-293
    suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)
    Software and Algorithms
    SentencesResources
    Data visualization was performed using the ggplot2 package (version 3.3.0) or pROC package.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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 10.1101/2020.04.15.043364v2 on bioRxiv
  4. Version published to 10.1101/2020.04.15.043364v1 on bioRxiv