Neutralizing efficacy of vaccines against the SARS-CoV-2 Mu variant

  1. Kei Miyakawa
  2. Sundararaj Stanleyraj Jeremiah
  3. Hideaki Kato
  4. Akihide Ryo

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Abstract

The rise of mutant strains of SARS-CoV-2 poses an additional problem to the existing pandemic of COVID-19. There are rising concerns about the Mu variant which can escape humoral immunity acquired from infections from previous strains or vaccines. We examined the neutralizing efficacy of the BNT162b2 mRNA vaccine against the Mu variant and report that the vaccine has 76% neutralizing effectiveness against the Mu compared to 96% with the original strain. We also show that Mu, similar to the Delta variant, causes cell-to-cell fusion which can be an additional factor for the variant to escape vaccine-mediated humoral immunity. Despite the rise in vaccine escape strains, the vaccine still possesses adequate ability to neutralize majority of the mutants.

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  1. ScreenIT

    SciScore for 10.1101/2021.09.23.21264014: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Ethics statement: This study was approved by Yokohama City University Certified Institutional Review Board (Reference No. B210300001), and the protocols used in the study were approved by the ethics committee.
    Consent: Written informed consent was obtained from all the participants.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We calculated NT50 using the curve-fitting tool (ImageJ, NIH).
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)

    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.

  2. Version published to 10.1101/2021.09.23.21264014v1 on medRxiv