Mosaic nanoparticles elicit cross-reactive immune responses to zoonotic coronaviruses in mice

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Abstract

In the past 20 years, three betacoronaviruses thought to have originated in bats have caused devastating disease in humans. The global pandemic caused by the latest such virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlights the need to protect against other strains that could present a threat to humans. Cohen et al. constructed nanoparticles displaying the protein domain that binds the host cell receptor (receptor-binding domain or RBD), either a homotypic SARS-CoV-2 particle or mosaic particles displaying RBDs from four or eight different betacoronaviruses. In mice, antibodies to the SARS-CoV-2 RBD were elicited just as well by mosaic particles as by homotypic nanoparticles. The mosaic nanoparticles elicited antibodies that, beyond recognizing the strains displayed, also recognized mismatched strains.

Science , this issue p. 735

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  1. SciScore for 10.1101/2020.11.17.387092: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: Concentrations of conjugated mi3 particles were determined using a Bio-Rad Protein Assay. Immunizations: Animal procedures and experiments were performed according to protocols approved by the IACUC.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableExperiments were done using 4-6 week old female Balb/c mice (Charles River Laboratories), with 5 animals each for cohorts immunized with soluble SARS-CoV-2 S or SpyCatcher003-mi3, and 10 animals each for remaining cohorts (Fig 3A).

    Table 2: Resources

    Antibodies
    SentencesResources
    Half-maximal inhibitory dilutions (ID50 values) were determined using 4-parameter nonlinear regression in AntibodyDatabase (57).
    AntibodyDatabase
    suggested: None
    Experimental Models: Organisms/Strains
    SentencesResources
    Experiments were done using 4-6 week old female Balb/c mice (Charles River Laboratories), with 5 animals each for cohorts immunized with soluble SARS-CoV-2 S or SpyCatcher003-mi3, and 10 animals each for remaining cohorts (Fig 3A).
    Balb/c
    suggested: None
    Software and Algorithms
    SentencesResources
    Phylogenetic tree: A sequence alignment of coronavirus RBD domains was made using Clustal Omega (51).
    Clustal Omega
    suggested: (Clustal Omega, RRID:SCR_001591)
    A phylogenetic tree was calculated from this amino acid alignment using PhyML 3.0 (52), and a figure of this tree was made using PRESTO (http://www.atgc-montpellier.fr/presto).
    PhyML
    suggested: (PhyML, RRID:SCR_014629)
    PRESTO
    suggested: (pRESTO, RRID:SCR_001782)
    Curves were plotted and integrated to obtain the area under the curve (AUC) using Graphpad Prism 8.3 assuming a one-site binding model with a Hill coefficient (Fig. 3; fig.
    Graphpad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Statistical Analysis: Comparisons between groups for ELISAs and neutralization assays were calculated with one-way analysis of variance (ANOVA) using Tukey’s post hoc test in Prism 9.0 (Graphpad).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    For correlation analysis between ELISA and neutralization titers, significance (p), Spearman coefficients (rs), and linear plots were calculated using Prism 9.0 (Graphpad).
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)
    Stained cells were analyzed with a SY3200 Cell Sorter (Sony) configured to detect 6 fluorochromes. 2,000,000 events were collected per sample and analyzed via FlowJo software (TreeStar).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.