In vitro measurements of protein–protein interactions show that antibody affinity governs the inhibition of SARS-CoV-2 spike/ACE2 binding in convalescent serum

  1. Sebastian Fiedler
  2. Monika A. Piziorska
  3. Viola Denninger
  4. Alexey S. Morgunov
  5. Alison Ilsley
  6. Anisa Y. Malik
  7. Matthias M. Schneider
  8. Sean R. A. Devenish
  9. Georg Meisl
  10. Adriano Aguzzi
  11. Heike Fiegler
  12. Tuomas P. J. Knowles

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Abstract

The humoral immune response plays a key role in suppressing the pathogenesis of SARS-CoV-2. The molecular determinants underlying the neutralization of the virus remain, however, incompletely understood. Here, we show that the ability of antibodies to disrupt the binding of the viral spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor on the cell, the key molecular event initiating SARS-CoV-2 entry into host cells, is controlled by the affinity of these antibodies to the viral antigen. By using microfluidic antibody-affinity profiling, we were able to quantify the serum-antibody mediated inhibition of ACE2–spike binding in two SARS-CoV-2 seropositive individuals. Measurements to determine the affinity, concentration, and neutralization potential of antibodies were performed directly in human serum. Using this approach, we demonstrate that the level of inhibition in both samples can be quantitatively described using the binding energies of the binary interactions between the ACE2 receptor and the spike protein, and the spike protein and the neutralizing antibody. These experiments represent a new type of in-solution receptor binding competition assay, which has further potential areas of application ranging from decisions on donor selection for convalescent plasma therapy, to identification of lead candidates in therapeutic antibody development, and vaccine development.

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    SciScore for 10.1101/2020.12.20.422820: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: BioIVT sought informed consent from each subject, or the subjects legally authorized representative and appropriately documented this in writing.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    [Ab], [S1], [ACE2], [S1Ab], and [S1ACE2] are equilibrium concentrations of antibody, S1, ACE2, S1–antibody complex, and S1–ACE2 complex, respectively.
    ACE2
    suggested: None
    Software and Algorithms
    SentencesResources
    The equilibrium dissociation constant (KD) was determined by nonlinear least-squares (NLSQ) fitting (Prism, GraphPad Software) in terms of the following binary equilibrium:

    with Rh, Rh,free, and Rh,complex being the effective hydrodynamic radii at equilibrium, of the unbound labeled species and of the complex of unlabeled and labeled species, respectively.

    Prism
    suggested: (PRISM, RRID:SCR_005375)
    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.
    • No funding statement was detected.
    • 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.

  2. Version published to 10.1101/2020.12.20.422820v1 on bioRxiv