Integrate structural analysis, isoform diversity, and interferon-inductive propensity of ACE2 to predict SARS-CoV2 susceptibility in vertebrates

  1. Eric R. Sang
  2. Yun Tian
  3. Yuanying Gong
  4. Laura C. Miller
  5. Yongming Sang

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Abstract

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  1. Version published to 10.1016/j.heliyon.2020.e04818
  2. ScreenIT

    SciScore for 10.1101/2020.06.27.174961: (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
    Protein and promoter sequence extraction and alignment: The amino acid sequences of ACE2 proteins and DNA sequences of the proximal promoters of each ACE2 genes were extracted from NCBI Gene and relevant databases (https://www.ncbi.nlm.nih.gov/gene).
    NCBI Gene
    suggested: None
    https://www.ncbi.nlm.nih.gov/gene
    suggested: (Entrez Gene, RRID:SCR_002473)
    In most cases, the annotations were double verified through the same Gene entries at Ensembl (https://www.ensembl.org).
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    https://www.ensembl.org
    suggested: (Homologous Sequences in Ensembl Animal Genomes, RRID:SCR_008356)
    The protein and DNA sequences were aligned using the multiple sequence alignment tools of ClustalW or Muscle through an EMBL-EBI port (https://www.ebi.ac.uk/).
    ClustalW
    suggested: (ClustalW, RRID:SCR_017277)
    Muscle
    suggested: (MUSCLE, RRID:SCR_011812)
    https://www.ebi.ac.uk/
    suggested: (European Bioinformatics Institute, RRID:SCR_004727)
    Other sequence management was conducted using programs at the Sequence Manipulation Suite (http://www.bioinformatics.org).
    http://www.bioinformatics.org
    suggested: (Bioinformatics Organization, RRID:SCR_012008)
    Sequence alignments were visualized using Jalview (http://www.jalview.org) and MEGAx (https://www.megasoftware.net).
    Jalview
    suggested: (Jalview, RRID:SCR_006459)
    Phylogenic analysis: The phylogenic analysis and tree visualization were performed using MEGAx and an online program, EvoView.
    MEGAx
    suggested: None
    Structural visualization were using Pymol.
    Pymol
    suggested: (PyMOL, RRID:SCR_000305)
    Profiling transcription factor binding sites in ACE2 promoters and PWM scoring: The regulatory elements (and pertinent binding factors) in the ~2.5 kb proximal promoter regions was examined against both human/animal TFD Database using a program Nsite (Version 5.2013, at http://www.softberry.com).
    http://www.softberry.com
    suggested: (SoftBerry, RRID:SCR_000902)
    The mean position weight matrix (PWM) of key cis-elements in the proximal promoters were calculated using PWM tools through https://ccg.epfl.ch/cgi-bin/pwmtools, and the binding motif matrices of examined TFs were extracted from JASPAR Core 2018 vertebrates (http://jaspar.genereg.net/).
    http://jaspar.genereg.net/
    suggested: (JASPAR, RRID:SCR_003030)
    RNA-Seq and data analysis: For expression confirmation, several sets of RNA-Seq data from NCBI Gene databases, and one of ours generated from porcine alveolar macrophages (BioProject with an accession number of SRP033717), were analyzed for verification of the differential expression of ACE2 genes in most annotated animal species.
    BioProject
    suggested: (NCBI BioProject, RRID:SCR_004801)
    Significantly differentially expressed genes (DEGs) between two treatments were called using an edgeR package and visualized using heatmaps or bar charts as previously described [58].
    edgeR
    suggested: (edgeR, RRID:SCR_012802)

    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.

  3. Version published to 10.1101/2020.06.27.174961v1 on bioRxiv