Replicating bacterium-vectored vaccine expressing SARS-CoV-2 Membrane and Nucleocapsid proteins protects against severe COVID-19 disease in hamsters

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Abstract

An inexpensive readily manufactured COVID-19 vaccine that protects against severe disease is needed to combat the pandemic. We have employed the LVS Δ capB vector platform, previously used successfully to generate potent vaccines against the Select Agents of tularemia, anthrax, plague, and melioidosis, to generate a COVID-19 vaccine. The LVS Δ capB vector, a replicating intracellular bacterium, is a highly attenuated derivative of a tularemia vaccine (LVS) previously administered to millions of people. We generated vaccines expressing SARS-CoV-2 structural proteins and evaluated them for efficacy in the golden Syrian hamster, which develops severe COVID-19 disease. Hamsters immunized intradermally or intranasally with a vaccine co-expressing the Membrane (M) and Nucleocapsid (N) proteins, then challenged 5-weeks later with a high dose of SARS-CoV-2, were protected against severe weight loss and lung pathology and had reduced viral loads in the oropharynx and lungs. Protection by the vaccine, which induces murine N-specific interferon-gamma secreting T cells, was highly correlated with pre-challenge serum anti-N TH1-biased IgG. This potent vaccine against severe COVID-19 should be safe and easily manufactured, stored, and distributed, and given the high homology between MN proteins of SARS-CoV and SARS-CoV-2, has potential as a universal vaccine against the SARS subset of pandemic causing β-coronaviruses.

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  1. SciScore for 10.1101/2020.11.17.387555: (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.

    Table 2: Resources

    No key resources detected.


    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.