Genetic analysis of SARS-CoV-2 isolates collected from Bangladesh: insights into the origin, mutation spectrum, and possible pathomechanism

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Abstract

As the coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), rages across the world, killing hundreds of thousands and infecting millions, researchers are racing against time to elucidate the viral genome. Some Bangladeshi institutes are also in this race, sequenced a few isolates of the virus collected from Bangladesh. Here, we present a genomic analysis of 14 isolates. The analysis revealed that SARS-CoV-2 isolates sequenced from Dhaka and Chittagong were the lineage of Europe and the Middle East, respectively. Our analysis identified a total of 42 mutations, including three large deletions, half of which were synonymous. Most of the missense mutations in Bangladeshi isolates found to have weak effects on the pathogenesis. Some mutations may lead the virus to be less pathogenic than the other countries. Molecular docking analysis to evaluate the effect of the mutations on the interaction between the viral spike proteins and the human ACE2 receptor, though no significant interaction was observed. This study provides some preliminary insights into the origin of Bangladeshi SARS-CoV-2 isolates, mutation spectrum and its possible pathomechanism, which may give an essential clue for designing therapeutics and management of COVID-19 in Bangladesh.

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  1. SciScore for 10.1101/2020.06.07.138800: (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
    Identification of Nucleotide Variations in Bangladeshi Strain: We performed multiple sequence alignment using Clustal Omega [15, 16], and the sequence of the strain China [EPI_ISL_402124] was used as a reference genome.
    Clustal Omega
    suggested: (Clustal Omega, RRID:SCR_001591)
    Prediction of Viral Genome and Identification of Selected Genes: FGENESV of SoftBerry (http://linux1.softberry.com/berry.phtml), which is a Trained Pattern/Markov chain-based viral gene prediction tools, was adopted for the prediction of the genes as well as the proteins from the viral genomes.
    SoftBerry
    suggested: (SoftBerry, RRID:SCR_000902)
    Homology Modeling of Spike Proteins and Validation: The BLASTp program at the NCBI interface (link) was used to find the most suitable template for homology modeling.
    BLASTp
    suggested: (BLASTP, RRID:SCR_001010)
    First, the crystal structure of human ACE2 (PDB ID 6D0G) was obtained from Protein Data Bank, and PyMOL was used to clean the structure to remove all the complex molecules and water [24, 25].
    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.