Role of SARS-CoV-2 in altering the RNA binding protein and miRNA directed post-transcriptional regulatory networks in humans

  1. Rajneesh Srivastava
  2. Swapna Vidhur Daulatabad
  3. Mansi Srivastava
  4. Sarath Chandra Janga

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Abstract

The outbreak of a novel coronavirus SARS-CoV-2 responsible for COVID-19 pandemic has caused worldwide public health emergency. Due to the constantly evolving nature of the coronaviruses, SARS-CoV-2 mediated alteration on post-transcriptional gene regulation across human tissues remains elusive. In this study, we analyze publicly available genomic datasets to systematically dissect the crosstalk and dysregulation of human post-transcriptional regulatory networks governed by RNA binding proteins (RBPs) and micro-RNAs (miRs), due to SARS-CoV-2 infection. We uncovered that 13 out of 29 SARS-CoV-2 encoded proteins directly interact with 51 human RBPs of which majority of them were abundantly expressed in gonadal tissues and immune cells. We further performed a functional analysis of differentially expressed genes in mock-treated versus SARS-CoV-2 infected lung cells that revealed enrichment for immune response, cytokine-mediated signaling, and metabolism associated genes. This study also characterized the alternative splicing events in SARS-CoV-2 infected cells compared to control demonstrating that skipped exons and mutually exclusive exons were the most abundant events that potentially contributed to differential outcomes in response to viral infection. Motif enrichment analysis on the RNA genomic sequence of SARS-CoV-2 clearly revealed the enrichment for RBPs such as SRSFs, PCBPs, ELAVs, and HNRNPs suggesting the sponging of RBPs by SARS-CoV-2 genome. A similar analysis to study the interactions of miRs with SARS-CoV-2 revealed functionally important miRs that were highly expressed in immune cells, suggesting that these interactions may contribute to the progression of the viral infection and modulate host immune response across other human tissues. Given the need to understand the interactions of SARS-CoV-2 with key post-transcriptional regulators in the human genome, this study provides a systematic computational analysis to dissect the role of dysregulated post-transcriptional regulatory networks controlled by RBPs and miRs, across tissues types during SARS-CoV-2 infection.

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  1. Version published to 10.1101/2020.07.06.190348v2 on bioRxiv
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    SciScore for 10.1101/2020.07.06.190348: (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: Cell Lines
    SentencesResources
    4.1. Dissection of SARS-CoV-2 proteins interacting with human RBPs: We obtained the high confidence mass spectrometry based SARS-CoV-2 viral protein to human protein interaction network established by Gordan et al, 2020 [23] in HEK293 cells.
    HEK293
    suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)
    Software and Algorithms
    SentencesResources
    We dissected the human RBPs directly interacting with viral proteins and integrated with 1st neighbor interacting RBPs (obtained from BioGRID [56]).
    BioGRID
    suggested: (BioGrid Australia, RRID:SCR_006334)
    Differential expression analysis of mock treated versus SARS-CoV-2 infected primary human lung epithelial cells: We downloaded the raw RNA sequencing data deposited in Gene Expression Omnibus (GEO)[65].
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Specifically, we downloaded the paired end raw sequencing (FASTQ) files of mock treated and SARS-CoV-2 (USA-WA1/2020) infected primary human lung epithelial cells (in biological triplicates) using the Sequence Read Archive (SRA) Toolkit (fastq-dump command), from the GEO cohort GSE147507 [64].
    Sequence Read Archive
    suggested: (DDBJ Sequence Read Archive, RRID:SCR_001370)
    The quality of the sequence reads were ensured using FASTX-Toolkit (http://hannonlab.cshl.edu/fastx_toolkit/) with a minimum of Phred quality score 20 for each sample.
    FASTX-Toolkit
    suggested: (FASTX-Toolkit, RRID:SCR_005534)
    Phred
    suggested: (Phred, RRID:SCR_001017)
    SAM (Sequence Alignment/Map) files obtained from HISAT were post-processed using SAMtools (version 0.1.19) [102,
    SAMtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    The sorted BAM files were parsed using the python script provided by StringTie (version 1.2.1) [104] to obtain the count matrix of for gene levels across the samples.
    python
    suggested: (IPython, RRID:SCR_001658)
    StringTie
    suggested: (StringTie , RRID:SCR_016323)
    Functional enrichment analysis of these genes was performed with p-value threshold < 10−10 using ClueGO [66] (a Cytoscape [106
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    rMATS used sorted BAM (Binary Alignment/Map) files, obtained from aligning the fastq files against hg38 reference genome using HISAT (as discussed above).
    HISAT
    suggested: (HISAT2, RRID:SCR_015530)
    It also uses a GTF file (gene transfer file format), downloaded from Ensembl (version 97) [107] for existing annotation of exons.
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Significant clustering (adj. p < 1e-10) of genes enriched in GO-biological processes were generated by ClueGO [66] analysis (a cytoscape [106] plugin).
    ClueGO
    suggested: (ClueGO, RRID:SCR_005748)

    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.

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  3. Version published to 10.1101/2020.07.06.190348v1 on bioRxiv