The SARS-CoV-2 RNA interactome

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Abstract

SARS-CoV-2 is an RNA virus whose success as a pathogen relies on its ability to repurpose host RNA-binding proteins (RBPs) to form its own RNA interactome. Here, we developed and applied a robust ribonucleoprotein capture protocol to uncover the SARS-CoV-2 RNA interactome. We report 109 host factors that directly bind to SARS-CoV-2 RNAs including general antiviral factors such as ZC3HAV1, TRIM25, and PARP12. Applying RNP capture on another coronavirus HCoV-OC43 revealed evolutionarily conserved interactions between viral RNAs and host proteins. Network and transcriptome analyses delineated antiviral RBPs stimulated by JAK-STAT signaling and proviral RBPs responsible for hijacking multiple steps of the mRNA life cycle. By knockdown experiments, we further found that these viral-RNA-interacting RBPs act against or in favor of SARS-CoV-2. Overall, this study provides a comprehensive list of RBPs regulating coronaviral replication and opens new avenues for therapeutic interventions.

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  1. SciScore for 10.1101/2020.11.02.364497: (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
    Vero and HCT-8 cells were maintained in DMEM (Welgene) and RPMI 1640 (Welgene) respectively, both with 1X Antibiotic-Antimycotic (Gibco) and 10% FBS (Gibco) and cultured in CO2 incubator with 5% CO2 37 DC.
    HCT-8
    suggested: RRID:CVCL_5947)
    For SARS-CoV-2 infection, 7 ⍰ 106 Vero cells were plated in T-175 flasks 24 hours before infection.
    Vero
    suggested: None
    For siRNA transfection, 3.5 ⍰ 105 Calu-3 cells, maintained in DMEM with 1X Antibiotic-Antimycotic and 10% FBS in CO2 incubator with 5% CO2 37 □C, were plated in 12 well plate and final 50 nM siRNAs were reverse-transfected using Lipofectamine RNAiMAX (Invitrogen) and ON-TARGETplus SMARTpool siRNAs (Horizon Discovery).
    Calu-3
    suggested: KCLB Cat# 30055, RRID:CVCL_0609)
    Software and Algorithms
    SentencesResources
    Preparation of antisense oligonucleotide templates: By scanning the genomic RNAs of SARS-CoV-2 (NCBI RefSeq accession NC_045512.2) and HCoV-OC43 (GenBank accession AY391777.1) from head to tail, partially overlapping 90 nt tiles were enumerated.
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    Peptides from common contaminant proteins were identified by utilizing the contaminant database provided by MaxQuant.
    MaxQuant
    suggested: (MaxQuant, RRID:SCR_014485)
    To improve the explanatory power of this analysis, we used the weight01 algorithm (Alexa et al., 2006) from the topGO R package which accounts for the GO graph structure and reduces local dependencies between GO terms.
    topGO
    suggested: (topGO, RRID:SCR_014798)
    Detailed information of the Gene Ontology was from the GO.db R package (version 3.8.2), and GO gene annotations were from the org.
    GO.db
    suggested: None
    Protein-protein interaction network analysis: We integrated protein-protein interaction data from the BioGRID database (Release 3.5.187) (Stark et al., 2006) and retrieved other proteins that do not necessarily bind to the SARS-CoV-2 RNA but form either transient or stable physical interactions with the host proteins identified from the RNP capture experiments.
    BioGRID
    suggested: (BioGrid Australia, RRID:SCR_006334)
    Protein domain enrichment analysis: Pfam database (version 33.1) (El-Gebali et al., 2019) was used for protein domain enrichment analysis.
    Pfam
    suggested: (Pfam, RRID:SCR_004726)

    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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