Sequence analysis of Indian SARS-CoV-2 isolates shows a stronger interaction of mutant receptor-binding domain with ACE2

  1. Pujarini Dash
  2. Jyotirmayee Turuk
  3. Santosh K. Behera
  4. Subrata Kumar Palo
  5. Sunil K. Raghav
  6. Arup Ghosh
  7. Jyotsnamayee Sabat
  8. Sonalika Rath
  9. Subhra Subhadra
  10. Khokan Rana
  11. Debdutta Bhattacharya
  12. Srikanta Kanungo
  13. Jaya Singh Kshatri
  14. Bijaya Kumar Mishra
  15. Saroj Dash
  16. Ajay Parida
  17. Sanghamitra Pati

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Abstract

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  1. Version published to 10.1016/j.ijid.2021.01.020
  2. ScreenIT

    SciScore for 10.1101/2020.08.28.271601: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The libraries were prepared for WGS using ACTIC amplicon based sequencing kits from Qiagen as per manufacturer recommended protocol.
    WGS
    suggested: None
    The detailed information and method have been described by Raghav et al., 20209 Sequence alignment of RMRC spike genes with reference sequence: For sequence alignment, full length genome sequence of SARS-CoV-2 isolate of Wuhan-Hu-1 (Accession no.NC_045512) was downloaded from NCBI database and used as reference sequence for all further analysis.
    NCBI
    suggested: (NCBI, RRID:SCR_006472)
    Alignment of all 35 RMRC spike nucleotide sequences with the reference genome was carried out using BLASTN (align two/more
    BLASTN
    suggested: (BLASTN, RRID:SCR_001598)
    Multiple sequence alignment of all 35 RBDs (amino acid sequences) was carried out using Clustal X tool.
    Clustal X tool
    suggested: None
    A phylogenetic tree was generated using the MEGA software version 6 with 1000 bootstrap replications as instructed in MEGA software.
    MEGA
    suggested: (Mega BLAST, RRID:SCR_011920)
    , 805 amino acids), Indian bat (Cynopterus sphinx) (Uniprot QZF77831, 807 amino acids) (probable natural hosts for SARS-CoV-2) and human (Homo Sapiens) ACE2 (UniprotKB Q9BYF1
    UniprotKB
    suggested: (UniProtKB, RRID:SCR_004426)
    Protein Data Bank (PDB) did not provide any experimental structure of ACE2 receptors of pangolin, hamster, Chinese and Indian bat, which has prompted us to predict their three dimensional (3D) structure through homology modelling using Modeller v 9.19 tool followed by structure validation.
    Modeller
    suggested: (MODELLER, RRID:SCR_008395)
    Suitable templates were identified for 3D model building of ACE2 using BLASTp11 search against PDB (Protein Data Bank) database.
    BLASTp11
    suggested: None
    Side chain optimization was performed using WHATIF13 and GalaxyRefine14 tool.
    GalaxyRefine14
    suggested: None
    In silico translation of RBD sequences and their interaction with ACE2 receptor of different natural reservoirs: Four nucleotide sequences of RMRC RBDs were selected and translated to protein sequence using EMBOSS Transeq tool of European Bioinformatics Institute (EBI).
    EMBOSS
    suggested: (EMBOSS, RRID:SCR_008493)

    Results from OddPub: Thank you for sharing your data.

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 17, 18 and 20. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • 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 10.1101/2020.08.28.271601 on bioRxiv