ILRUN Downregulates ACE2 Expression and Blocks Infection of Human Cells by SARS-CoV-2

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Abstract

There is no doubt that the current rapid global spread of COVID-19 has had significant and far-reaching impacts on our health and economy and will continue to do so. Research in emerging infectious diseases, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is growing rapidly, with new breakthroughs in the understanding of host-virus interactions to assist with the development of innovative and exciting therapeutic strategies.

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  1. SciScore for 10.1101/2020.11.13.381343: (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

    Antibodies
    SentencesResources
    Cells were subsequently stained with 1/1,000 dilution of an anti-rabbit AF488 antibody (Invitrogen catalogue number A11008).
    anti-rabbit
    suggested: (Molecular Probes Cat# A-11008, RRID:AB_143165)
    Experimental Models: Cell Lines
    SentencesResources
    Caco-2 cells were maintained in Gibco Modified Eagles Medium (MEM) supplemented with 20 % (v/v) FCS, 10 mM HEPES, 0.1 mM non-essential amino acids, 2 mM glutamine, 1 mM sodium pyruvate, 100 U/mL penicillin, and 100 μg/mL streptomycin (Life Technologies).
    Caco-2
    suggested: None
    The isolate of SARS-CoV-2 (BetaCoV/Australia/VIC01/2020) was received from the Victorian Infectious Disease Reference Laboratory (VIDRL, Melbourne, Australia) and passaged in VeroE6 cells for isolation, followed by passaging in VeroE6 cells for stock generation.
    VeroE6
    suggested: JCRB Cat# JCRB1819, RRID:CVCL_YQ49)
    Software and Algorithms
    SentencesResources
    http://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
    http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
    suggested: (FastQC, RRID:SCR_014583)
    Bioinformatic analysis of RNA-seq data: Quality and adapter trimming was performed using TrimGalore v0.6.4 (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) with default settings for automatic adapter detection.
    TrimGalore
    suggested: None
    http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/
    suggested: (Trim Galore, RRID:SCR_011847)
    Trimmed reads were mapped to the National Cener for Biotechnology Information (NCBI) human reference genome (GRCh38) downloaded from Illumina iGenomes (http://igenomes.illumina.com.s3-website-us-east-1.amazonaws.com/Homo_sapiens/NCBI/GRCh38/Homo_sapiens_NCBI_GRCh38.ta r.gz) using Tophat v2.1.1 (49).
    Tophat
    suggested: (TopHat, RRID:SCR_013035)
    The number of reads overlapping each gene in the NCBI annotated reference genome (GRCh38) were counted using htseq-count v0.11.2 within Python v3.7.2 (50), using the intersection-nonempty mode to handle reads overlapping more than one feature.
    htseq-count
    suggested: (htseq-count, RRID:SCR_011867)
    The Bioconductor package DESeq2 was used to test for differential expression between different experimental groups (51).
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    KEGG) pathway mapping (52), custom python scripts were used to prepare input lists for conversion of gene symbols to Entrez gene IDs using bioDBnet’s db2db tool (https://biodbnet-abcc.ncifcrf.gov/db/db2db.php) and generation of hex codes based on fold change for colour mapping of KEGG pathways (https://www.genome.jp/kegg/tool/map_pathway2.html).
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    python
    suggested: (IPython, RRID:SCR_001658)
    Trimmed reads were mapped to a SARS-CoV-2 reference genome of the virus used in experiments (MT007544; SARS-CoV-2/human/AUS/VIC01/2020) using bowtie v2.3.4 (53).
    bowtie
    suggested: (Bowtie, RRID:SCR_005476)
    Mapped viral reads were counted using samtools v1.10.0 (Li et al., 2009) and coverview v1.4.4 (54) then normalised to library read content.
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    Analysis of publicly available data: The NCBI Gene Expression Omnibus was searched for suitable RNA-seq datasets and GSE Accession number entered into the GREIN : GEO RNA-seq Experiments Interactive Navigator (http://www.ilincs.org/apps/grein/) to retrieve metadata and normalized counts.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Normalised counts were plotted for each gene using ggplot2 package in R.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Statistics: The difference between two groups was analysed in GraphPad Prism by a two-tailed Student’s t test and between multiple groups by one-way ANOVA.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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

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