Rapid development of SARS-CoV-2 receptor binding domain-conjugated nanoparticle vaccine candidate

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Abstract

The ongoing of coronavirus disease 2019 (COVID-19) pandemic caused by novel SARS-CoV-2 coronavirus, resulting in economic losses and seriously threating the human health in worldwide, highlighting the urgent need of a stabilized, easily produced and effective preventive vaccine. The SARS-COV-2 spike protein receptor binding region (RBD) plays an important role in the process of viral binding receptor angiotensin-converting enzyme 2 (ACE2) and membrane fusion, making it an ideal target for vaccine development. In this study, we designed three different RBD-conjugated nanoparticles vaccine candidates, RBD-Ferritin (24-mer), RBD-mi3 (60-mer) and RBD-I53-50 (120-mer), with the application of covalent bond linking by SpyTag-SpyCatcher system. It was demonstrated that the neutralizing capability of sera from mice immunized with three RBD-conjugated nanoparticles adjuvanted with AddaVax or Sigma Systerm Adjuvant (SAS) after each immunization was ~8-to 120-fold greater than monomeric RBD group in SARS-CoV-2 pseudovirus and authentic virus neutralization assay. Most importantly, sera from RBD-conjugated NPs groups more efficiently blocked the binding of RBD to ACE2 or neutralizing antibody in vitro, a further proof of promising immunization effect. Besides, high physical stability and flexibility in assembly consolidated the benefit for rapid scale-up production of vaccine. These results supported that our designed SARS-CoV-2 RBD-conjugated nanoparticle was competitive vaccine candidate and the carrier nanoparticles could be adopted as universal platform for future vaccine development.

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  1. SciScore for 10.1101/2020.11.03.366138: (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.