Evaluating SARS-CoV-2 spike and nucleocapsid proteins as targets for antibody detection in severe and mild COVID-19 cases using a Luminex bead-based assay

  1. Joachim Mariën
  2. Ann Ceulemans
  3. Johan Michiels
  4. Leo Heyndrickx
  5. Karen Kerkhof
  6. Nikki Foque
  7. Marc-Alain Widdowson
  8. Laure Mortgat
  9. Els Duysburgh
  10. Isabelle Desombere
  11. Hilde Jansens
  12. Marjan Van Esbroeck
  13. Kevin K. Ariën

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. Version published to 10.1016/j.jviromet.2020.114025
  2. ScreenIT

    SciScore for 10.1101/2020.07.25.20161943: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Subsequently, 100µl of a 1:400 secondary antibody (R-phycoerythrin-conjugated AffiniPure F(ab′)2 fragment of goat anti-human IgG, Jackson Immuno Research Laboratories) dilution in PBS-BN was added to each well.
    anti-human IgG
    suggested: None
    EUROIMMUN IgG/IgA ELISA: Samples from hospitalized cases were also analysed for level of antigen-binding antibodies against SARS-CoV-2 using the Anti-SARS-CoV-2 ELISA (IgA) and Anti-SARS-CoV-2 ELISA (IgG) (Euroimmun, Lübeck, Germany) following the manufacturer’s instructions.
    Anti-SARS-CoV-2 ELISA ( IgA
    suggested: None
    Anti-SARS-CoV-2 ELISA ( IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Sample-virus mixtures and virus/cell controls were added to Vero cells (18.000cells/well) in a 96well plate and incubated for 5 days (37°C / 7% CO2).
    Vero
    suggested: None

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04373889Active, not recruitingCOVID-19 Among Healthcare Workers in Belgian Hospitals

    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 10.1101/2020.07.25.20161943v1 on medRxiv