Rapid and Quantitative Detection of Human Antibodies against the 2019 Novel Coronavirus SARS CoV2 and Its Variants as a Result of Vaccination and Infection

  1. Benjamin Taubner
  2. Ruben Peredo-Wende
  3. Ananthakrishnan Ramani
  4. Gurpreet Singh
  5. Klemen Strle
  6. Nathaniel C. Cady

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

In this work, a novel biosensor technology was used to measure antibody levels that resulted from vaccination against COVID-19 and/or from infection with the virus. Importantly, this approach enables quantification of antibody levels, which can provide information about the timing and level of immune response.

Article activity feed

  1. Version published to 10.1128/spectrum.00890-21
  2. ScreenIT

    SciScore for 10.1101/2021.07.13.21260442: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Lancet devices (27 ga.) and Whatman 903 protein saver collection cards were sent to volunteers with instructions and consent form approved by the SUNY Polytechnic Institute Institutional Review Board (protocol #IRB-2020-10 and #IRB-2021-2).
    IRB: Lancet devices (27 ga.) and Whatman 903 protein saver collection cards were sent to volunteers with instructions and consent form approved by the SUNY Polytechnic Institute Institutional Review Board (protocol #IRB-2020-10 and #IRB-2021-2).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The fluorescence intensity of all spots was normalized to the human IgG (Hum IgG) internal control spots on each chip, to account for variability between individual chips and individual experiments, generating a “GC-FP detection ratio” for every protein/antigen included in the GC-FP microchip (12):

    To determine if GC-FP antibody binding data for 2019 SARS CoV2 vs. B.1.1.7 and B.1.351 variant antigens was consistent with standard methods, an ELISA-based ACE2 competitive binding assay (Ray Biotech) was used, as per the manufacturer’s instructions.

    human IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Ciencia image analysis LabView software was used to define a region of interest (ROI) for each individual spot on the GC-FP biosensor chip and the fluorescence intensity of each spot was measured.
    LabView
    suggested: (LabView , RRID:SCR_014325)
    Percent binding inhibition was calculated for each sample by the following method:

    Data Analysis: GC-FP diagnostic ratio data and percent binding inhibition data for the ACE2 competitive assay were analyzed using GraphPad Prism 8.0 software (ROC analysis, correlation, and statistical analysis).

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.07.13.21260442 on medRxiv