Microscopy‐based assay for semi‐quantitative detection of SARS‐CoV‐2 specific antibodies in human sera

  1. Constantin Pape
  2. Roman Remme
  3. Adrian Wolny
  4. Sylvia Olberg
  5. Steffen Wolf
  6. Lorenzo Cerrone
  7. Mirko Cortese
  8. Severina Klaus
  9. Bojana Lucic
  10. Stephanie Ullrich
  11. Maria Anders‐Össwein
  12. Stefanie Wolf
  13. Berati Cerikan
  14. Christopher J. Neufeldt
  15. Markus Ganter
  16. Paul Schnitzler
  17. Uta Merle
  18. Marina Lusic
  19. Steeve Boulant
  20. Megan Stanifer
  21. Ralf Bartenschlager
  22. Fred A. Hamprecht
  23. Anna Kreshuk
  24. Christian Tischer
  25. Hans‐Georg Kräusslich
  26. Barbara Müller
  27. Vibor Laketa

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Abstract

Emergence of the novel pathogenic coronavirus SARS‐CoV‐2 and its rapid pandemic spread presents challenges that demand immediate attention. Here, we describe the development of a semi‐quantitative high‐content microscopy‐based assay for detection of three major classes (IgG, IgA, and IgM) of SARS‐CoV‐2 specific antibodies in human samples. The possibility to detect antibodies against the entire viral proteome together with a robust semi‐automated image analysis workflow resulted in specific, sensitive and unbiased assay that complements the portfolio of SARS‐CoV‐2 serological assays. Sensitive, specific and quantitative serological assays are urgently needed for a better understanding of humoral immune response against the virus as a basis for developing public health strategies to control viral spread. The procedure described here has been used for clinical studies and provides a general framework for the application of quantitative high‐throughput microscopy to rapidly develop serological assays for emerging virus infections.

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  1. Version published to 10.1002/bies.202000257
  2. Version published to 10.1101/2020.06.15.152587v3 on bioRxiv
  3. Version published to 10.1101/2020.06.15.152587v2 on bioRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.06.15.152587: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: SARS-CoV-2 positive sera were collected from 29 PCR confirmed symptomatic COVID-19 inpatients (n=17) or outpatients (n=12) treated at the University Hospital Heidelberg under general informed consent (ethics votum no S-148/2020, University Hospital Heidelberg).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Next, cells were incubated with patient serum (prediluted 1:1 in 0,4% Triton-X100 in PBS; further dilution 1:50 in PBS if not stated otherwise) and anti-ds-RNA mouse monoclonal J2 antibody (Scicons, 1:4000) in PBS for 30 min at room temperature.
    anti-ds-RNA
    suggested: None
    J2
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Only very few infected calls were detected in the case of hepatocyte-derived carcinoma cells (HUH-7), human embryonic kidney (HEK293T) and human alveolar basal epithelial (A549) cells (Fig. S1).
    HEK293T
    suggested: None
    A549
    suggested: NCI-DTP Cat# A549, RRID:CVCL_0023)
    Calu-3 cells grew in small clumps, often on top of each other which impacted our microscopy-based readout.
    Calu-3
    suggested: KCLB Cat# 30055, RRID:CVCL_0609)
    For serum screening by IF microscopy, VeroE6 cells were seeded at a density of 7,000 cells per well into a black-wall glass-bottom 96 well plates (Corning, Product Number 353219) or on glass coverslips placed in a 24-well plate.
    VeroE6
    suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 32. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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.

  5. Version published to 10.1101/2020.06.15.152587v1 on bioRxiv