Predicting the efficacy of COVID-19 convalescent plasma donor units with the Lumit Dx anti-receptor binding domain assay

  1. Sanath Kumar Janaka
  2. Natasha M. Clark
  3. David T. Evans
  4. Huihui Mou
  5. Michael Farzan
  6. Joseph P. Connor

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Abstract

The novel coronavirus SARS-CoV2 that causes COVID-19 has resulted in the death of more than 2.5 million people, but no cure exists. Although passive immunization with COVID-19 convalescent plasma (CCP) provides a safe and viable therapeutic option, the selection of optimal units for therapy in a timely fashion remains a barrier.

Study design and methods

Since virus neutralization is a necessary characteristic of plasma that can benefit recipients, the neutralizing titers of plasma samples were measured using a retroviral-pseudotype assay. Binding antibody titers to the spike (S) protein were also determined by a clinically available serological assay (Ortho-Vitros total IG), and an in-house ELISA. The results of these assays were compared to a measurement of antibodies directed to the receptor binding domain (RBD) of the SARS-CoV2 S protein (Promega Lumit Dx).

Results

All measures of antibodies were highly variable, but correlated, to different degrees, with each other. However, the anti-RBD antibodies correlated with viral neutralizing titers to a greater extent than the other antibody assays.

Discussion

Our observations support the use of an anti-RBD assay such as the Lumit Dx assay, as an optimal predictor of the neutralization capability of CCP.

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  1. Version published to 10.1371/journal.pone.0253551
  2. ScreenIT

    SciScore for 10.1101/2021.03.08.21253135: (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
    ELISA: A modified ELISA, based on protocols published by Robbiani et al. and Routhu et al. (5, 21), were used to evaluate antibody binding to SARS-CoV-2 spike protein extracellular domain.
    SARS-CoV-2 spike protein extracellular domain.
    suggested: None
    Rhesus Anti-SARS CoV Spike monoclonal antibody (NHP Reagent Resource)
    Anti-SARS
    suggested: None
    , anti-Dengue monoclonal antibody, and 6 negative control plasma samples were added to each plate for validation.
    anti-Dengue
    suggested: None
    After 1h at 37°C, plates were washed and incubated with anti-human IgG secondary antibody conjugated to horseradish peroxidase (HRP) (Jackson Immunoresearch) in blocking buffer (1:5000 dilution) at 37°C for 1 h.
    anti-human IgG
    suggested: None
    Area under the curve (AUC) was calculated (Graphpad Prism) as a measure of the anti-S antibody titers.
    anti-S
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    293T-ACE2 cells were seeded in 96 well plates.
    293T-ACE2
    suggested: RRID:CVCL_YZ65)
    Software and Algorithms
    SentencesResources
    Area under the curve (AUC) was calculated (Graphpad Prism) as a measure of the anti-S antibody titers.
    Graphpad Prism
    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 10.1101/2021.03.08.21253135 on medRxiv