SARS-CoV-2 RBD219-N1C1: A Yeast-Expressed SARS-CoV-2 Recombinant Receptor-Binding Domain Candidate Vaccine Stimulates Virus Neutralizing Antibodies and T-cell Immunity in Mice

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Abstract

There is an urgent need for an accessible and low-cost COVID-19 vaccine suitable for low- and middle-income countries. Here we report on the development of a SARS-CoV-2 receptor-binding domain (RBD) protein, expressed at high levels in yeast ( Pichia pastoris ), as a suitable vaccine candidate against COVID-19. After introducing two modifications into the wild-type RBD gene to reduce yeast-derived hyperglycosylation and improve stability during protein expression, we show that the recombinant protein, RBD219-N1C1, is equivalent to the wild-type RBD recombinant protein (RBD219-WT) in an in vitro ACE-2 binding assay. Immunogenicity studies of RBD219-N1C1 and RBD219-WT proteins formulated with Alhydrogel ® were conducted in mice, and, after two doses, both the RBD219-WT and RBD219-N1C1 vaccines induced high levels of binding IgG antibodies. Using a SARS-CoV-2 pseudovirus, we further showed that sera obtained after a two-dose immunization schedule of the vaccines were sufficient to elicit strong neutralizing antibody titers in the 1:1,000 to 1:10,000 range, for both antigens tested. The vaccines induced IFN-γ, IL-6, and IL-10 secretion, among other cytokines. Overall, these data suggest that the RBD219-N1C1 recombinant protein, produced in yeast, is suitable for further evaluation as a human COVID-19 vaccine, in particular, in an Alhydrogel ® containing formulation and possibly in combination with other immunostimulants.

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  1. SciScore for 10.1101/2020.11.04.367359: (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.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The expression level of select colonies was identified by SDS-PAGE and immunoblotting using anti-SARS-CoV-2 antibodies (anti-SARS-CoV-2 spike rabbit monoclonal antibody, Sino Biological, Cat # 40150-R007), and research seed stocks of the highest expressing clones were frozen at −80 °C.
    anti-SARS-CoV-2
    suggested: None
    Subsequently, 1:6,000 diluted goat anti-mouse IgG HRP antibody (100 μL/well) was added in 0.1% BSA in PBST.
    anti-mouse IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    2.6 Pseudovirus assay: Pseudovirus was prepared in HEK-293T cells by previously reported methods with modifications24.
    HEK-293T
    suggested: None
    Next, 100 μL of these sera-pseudovirus mixtures were added to 293T-hACE2 cells in 96-well poly-D-lysine coated culture plates.
    293T-hACE2
    suggested: None
    Software and Algorithms
    SentencesResources
    Gels were stained using Coomassie Blue and analyzed using a Bio-Rad G900 densitometer with Image Lab software.
    Image Lab
    suggested: (Image Lab Software, RRID:SCR_014210)

    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.