Whole-Genome Sequences of the Severe Acute Respiratory Syndrome Coronavirus-2 obtained from Romanian patients between March and June of 2020

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Abstract

Impact of mutations on the evolution of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) are needed for ongoing global efforts to track and trace the current pandemic, in order to enact effective prevention and treatment options. SARS-Co-V-2 viral genomes were detected and sequenced from 18 Romanian patients suffering from coronavirus disease-2019. Viral Spike S glycoprotein sequences were used to generate model structures and assess the role of mutations on protein stability. We integrated the phylogenetic tree within the available European SARS-Co-V-2 genomic sequences. We further provide an epidemiological overview of the pre-existing conditions that are lethal in relevant Romanian patients. Non-synonymous mutations in the viral Spike glycoprotein relating to infectivity are constructed in models of protein structures. Continuing search to limit and treat SARS-CoV-2 benefit from our contribution in delineating the viral Spike glycoprotein mutations, as well as from assessment of their role on protein stability or complex formation with human receptor angiotensin-converting enzyme 2. Our results help implement and extend worldwide genomic surveillance of coronavirus disease-2019.

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  1. SciScore for 10.1101/2020.06.28.175802: (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

    Software and Algorithms
    SentencesResources
    Spike protein sequences from our genomes were modeled using I-Tasser [7] and the quality of models of Spike S proteins was assessed with MolProbity [8].
    I-Tasser
    suggested: (I-TASSER, RRID:SCR_014627)
    MolProbity
    suggested: (MolProbity, RRID:SCR_014226)
    All molecular structures were visualized with PyMol.
    PyMol
    suggested: (PyMOL, RRID:SCR_000305)

    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.