A high-throughput neutralizing antibody assay for COVID-19 diagnosis and vaccine evaluation

  1. Antonio E. Muruato
  2. Camila R. Fontes-Garfias
  3. Ping Ren
  4. Mariano A. Garcia-Blanco
  5. Vineet D. Menachery
  6. Xuping Xie
  7. Pei-Yong Shi

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Abstract

Virus neutralization remains the gold standard for determining antibody efficacy. Therefore, a high-throughput assay to measure SARS-CoV-2 neutralizing antibodies is urgently needed for COVID-19 serodiagnosis, convalescent plasma therapy, and vaccine development. Here, we report on a fluorescence-based SARS-CoV-2 neutralization assay that detects SARS-CoV-2 neutralizing antibodies in COVID-19 patient specimens and yields comparable results to plaque reduction neutralizing assay, the gold standard of serological testing. The fluorescence-based neutralization assay is specific to measure COVID-19 neutralizing antibodies without cross reacting with patient specimens with other viral, bacterial, or parasitic infections. Collectively, our approach offers a rapid platform that can be scaled to screen people for antibody protection from COVID-19, a key parameter necessary to safely reopen local communities.

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  1. Version published to 10.1038/s41467-020-17892-0
  2. ScreenIT

    SciScore for 10.1101/2020.05.21.109546: (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
    For testing cross reactivity, a total of 138 de-identified specimens from patients with antigens or antibodies against different viruses, bacteria, and parasites were tested in the mNeonGreen SARS-COV-2 neutralization assay (Table 1).
    antigens
    suggested: None
    For testing interfering substances, nineteen de-identified serum specimens with albumin, elevated bilirubin, cholesterol, rheumatoid factor, and autoimmune nuclear antibodies were tested in the reporter neutralization assay.
    albumin, elevated bilirubin, cholesterol, rheumatoid factor,
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    The virus-serum mixture was transferred to the Vero E6 cell plate with the final multiplicity of infection (MOI) of 0.5.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    Statistical analysis: The correlation of the NT50 values from mNeonGreen reporter SARS-CoV-2 assay and the PRNT50 values from plaque neutralization assay was analyzed using a linear regression model in the software Prism 8 (GraphPad).
    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 10.1101/2020.05.21.109546v1 on bioRxiv