Epigenetic regulator miRNA pattern differences among SARS-CoV, SARS-CoV-2 and SARS-CoV-2 world-wide isolates delineated the mystery behind the epic pathogenicity and distinct clinical characteristics of pandemic COVID-19

  1. Md. Abdullah-Al-Kamran Khan
  2. Md. Rabi Us Sany
  3. Md. Shafiqul Islam
  4. Md. Saheb Mehebub
  5. Abul Bashar Mir Md. Khademul Islam

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Abstract

Detailed molecular mechanism of SARS-CoV-2 pathogenesis is still elusive to address its deadlier nature and to design effective theraputics. Here, we present our study elucidating the interplay between the SARS-CoV and SARS-CoV-2 viruses’; and host’s miRNAs, an epigenetic regulator, as a mode of pathogenesis, and enlightened how the SARS-CoV and SARS-CoV-2 infections differ in terms of their miRNA mediated interactions with host and its implications in the disease complexity. We have utilized computational approaches to predict potential host and viral miRNAs, and their possible roles in different important functional pathways. We have identified several putative host antiviral miRNAs that can target the SARS viruses, and also SARS viruses’ encoded miRNAs targeting host genes. In silico predicted targets were also integrated with SARS infected human cells microarray and RNA-seq gene expression data. Comparison of the host miRNA binding profiles on 67 different SARS-CoV-2 genomes from 24 different countries with respective country’s normalized death count surprisingly uncovered some miRNA clusters which are associated with increased death rates. We have found that induced cellular miRNAs can be both a boon and a bane to the host immunity, as they have possible roles in neutralizing the viral threat, parallelly, they can also function as proviral factors. On the other hand, from over representation analysis, interestingly our study revealed that although both SARS-CoV and SARS-CoV-2 viral miRNAs could target broad immune signaling pathways; only some of the SARS-CoV-2 miRNAs are found to uniquely target some immune signaling pathways like-autophagy, IFN-I signaling etc, which might suggest their immune-escape mechanisms for prolonged latency inside some hosts without any symptoms of COVID-19. Further, SARS-CoV-2 can modulate several important cellular pathways which might lead to the increased anomalies in patients with comorbidities like-cardiovascular diseases, diabetes, breathing complications, etc. This might suggest that miRNAs can be a key epigenetic modulator behind the overcomplications amongst the COVID-19 patients. Our results support that miRNAs of host and SARS-CoV-2 can indeed play a role in the pathogenesis which can be further concluded with more experiments. These results will also be useful in designing RNA therapeutics to alleviate the complications from COVID-19.

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    SciScore for 10.1101/2020.05.06.081026: (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
    2.8 RNA-seq expression data analysis: RNA-seq raw read-count data on SARS-CoV-2 mediated expression changes in primary human lung epithelium (NHBE) and transformed lung alveolar (A549) cells were obtained from the GEO database (GSE147507) (Barrett et al., 2012).
    A549
    suggested: None
    Software and Algorithms
    SentencesResources
    2.1 Obtaining SARS-CoV and SARS-CoV2 Genome sequences: The reference genome of SARS-CoV (RefSeq Accession no. NC_004718.3) and SARS-CoV-2 (RefSeq Accession no. NC_045512.2) was fetched from NCBI RefSeq database (NCBI-RefSeq, 2020).
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    2.6 Target genes functional enrichment analysis: 2.7 Microarray expression data analysis: Microarray data for change in gene expression induced by SARS-CoV on 2B4 cells infected with SARS-CoV or remained uninfected for 12, 24, and 48hrs obtained from Gene Expression Omnibus (
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    ) (version 3.2.4 under Bioconductor version 3.10; R version 3.6.0).
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)
    To determine genes that are differentially expressed (DE) between two experimental conditions, Bioconductor package Limma (Smyth, 2005) was utilized to generate contrast matrices and fit the corresponding linear model.
    Limma
    suggested: (LIMMA, RRID:SCR_010943)
    Probe annotations to genes were done using the Ensembl gene model (Ensembl version 99) as extracted from Biomart (Flicek et al., 2007) and using in-house python script.
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    For differential expression (DE) analysis we used Bioconductor package DESeq2 (version 1.38.0) (Anders and Huber, 2010) with R version 3.6.0 (Team, 1999) with a model based on the negative binomial distribution.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    To avoid false positive, we considered only those transcripts where at least 10 reads are annotated and a p-value of 0.01. 2.9 MicroRNA Clustering: The hierarchal clustering of human miRNAs that could target SARS-CoV-2 genomes (binary mode) obtained from various countries was done using Manhattan distance and complete linkage analysis with the Genesis tool (Sturn et al., 2002).
    Genesis
    suggested: (Genesis, RRID:SCR_015775)

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.05.06.081026 on bioRxiv