Ultrastructural analysis of SARS-CoV-2 interactions with the host cell via high resolution scanning electron microscopy

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Abstract

SARS-CoV-2 is the cause of the ongoing COVID-19 pandemic. Here, we investigated the interaction of this new coronavirus with Vero cells using high resolution scanning electron microscopy. Surface morphology, the interior of infected cells and the distribution of viral particles in both environments were observed 2 and 48 h after infection. We showed areas of viral processing, details of vacuole contents, and viral interactions with the cell surface. Intercellular connections were also approached, and viral particles were adhered to these extensions suggesting direct cell-to-cell transmission of SARS-CoV-2.

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  1. SciScore for 10.1101/2020.06.10.144642: (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

    Experimental Models: Cell Lines
    SentencesResources
    The virus was grown in Vero cells in the Laboratory of Molecular Virology, at Federal University of Rio de Janeiro, Brazil.
    Vero
    suggested: CLS Cat# 605372/p622_VERO, RRID:CVCL_0059)

    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.