Master Regulator Analysis of the SARS-CoV-2/Human Interactome

  1. Pietro H. Guzzi
  2. Daniele Mercatelli
  3. Carmine Ceraolo
  4. Federico M. Giorgi

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Abstract

The recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. In this paper, we set out to shed light on the SARS-CoV-2/host receptor recognition, a crucial factor for successful virus infection. Based on the current knowledge of the interactome between SARS-CoV-2 and host cell proteins, we performed Master Regulator Analysis to detect which parts of the human interactome are most affected by the infection. We detected, amongst others, affected apoptotic and mitochondrial mechanisms, and a downregulation of the ACE2 protein receptor, notions that can be used to develop specific therapies against this new virus.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.15.992925: (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

    Experimental Models: Organisms/Strains
    SentencesResources
    Datasets of MERS and SARS infection: We obtained two datasets describing transcriptome-wide effects of coronavirus infection of human cultured 2B4 bronchial epithelial cells.
    We
    suggested: None
    Software and Algorithms
    SentencesResources
    The first dataset (available as ArrayExpress [31] dataset E-GEOD-17400) measured SARS-CoV infection using the microarray platform Affymetrix Human Genome U133 Plus 2.0 [
    ArrayExpress
    suggested: (ArrayExpress, RRID:SCR_002964)
    The dataset was normalized using RMA [33] and probeset mapping was performed using the most updated annotation from CustomCDF v24.0.0 [34].
    CustomCDF
    suggested: (CustomCDF, RRID:SCR_018527)
    BLAST: Pairwise protein identity and coverage was calculated using BLAST protein v2.6.0 [20] with BLOSUM62 matrix and default parameters.
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    FASTQ sequences were retrieved from the Sequence Read Archive (SRA) using SRA-toolkit v2.9.6-1 [37] using project PRJNA573298 run ids SRR10168377 and SRR10168378, which provided a DNA readout of the pangolin viral metagenome [38].
    Sequence Read Archive
    suggested: (DDBJ Sequence Read Archive, RRID:SCR_001370)
    Reads were mapped over the reference 2019-nCoV genome NC_045512.2 using Hisat2 v2.1.0 [39] with default parameters (with option --no-spliced-alignment).
    Hisat2
    suggested: (HISAT2, RRID:SCR_015530)
    Environment programs were samtools v1.9 and bedtools v 2.26.0.
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    bedtools
    suggested: (BEDTools, RRID:SCR_006646)
    Genome assembly of the virus genome-mapping reads was performed using Abyss v 2.1.5 with default parameters [40].
    Abyss
    suggested: (ABySS, RRID:SCR_010709)
    Multiple Sequence Alignment (MSA) of all 201 genomic sequences was performed using MUSCLE v3.8.31 [41] and is available in FASTA format as Supplementary File S1.
    MUSCLE
    suggested: (MUSCLE, RRID:SCR_011812)
    MSA visualization was generated via Jalview v 2.11.0 [42]
    Jalview
    suggested: (Jalview, RRID:SCR_006459)
    Phylogenetic model generation and tree visualization was done using MEGAX v 10.1.7 [43], using the Maximum Likelihood method and Tamura-Nei model [44].
    MEGAX
    suggested: None
    The tree in Figure 4 collapsed the SARS-nCoV-2 subtree, but a full tree is available at Supplementary Figure S1. 3D structural analysis: The protein structure representation has been produced with Chimera v1.14 [46] based on Protein Data Bank structure id 1R42 [47].
    Chimera
    suggested: (Chimera, RRID:SCR_002959)

    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: 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.

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  2. Version published to 10.3390/jcm9040982
  3. Version published to 10.1101/2020.03.15.992925v1 on bioRxiv