A transcription regulatory network within the ACE2 locus may promote a pro-viral environment for SARS-CoV-2 by modulating expression of host factors

  1. Tayaza Fadason
  2. Sreemol Gokuladhas
  3. Evgeniia Golovina
  4. Daniel Ho
  5. Sophie Farrow
  6. Denis Nyaga
  7. Hong Pan
  8. Neerja Karnani
  9. Conroy Wong
  10. Antony Cooper
  11. William Schierding
  12. Justin M. O’Sullivan

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Introduction

A novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was recently identified as the pathogen responsible for the COVID-19 outbreak. SARS-CoV-2 triggers severe pneumonia, which leads to acute respiratory distress syndrome and death in severe cases. As reported, SARS-CoV-2 is 80% genetically identical to the 2003 SARS-CoV virus. Angiotensin-converting enzyme 2 (ACE2) has been identified as the main receptor for entry of both SARS-CoV and SARS-CoV-2 into human cells. ACE2 is normally expressed in cardiovascular and lung type II alveolar epithelial cells, where it positively modulates the RAS system that regulates blood flow, pressure, and fluid homeostasis. Thus, virus-induced reduction of ACE2 gene expression is considered to make a significant contribution to severe acute respiratory failure. Chromatin remodeling plays a significant role in the regulation of ACE2 gene expression and the activity of regulatory elements within the genome.

Methods

Here, we integrated data on physical chromatin interactions within the genome organization (captured by Hi-C) with tissue-specific gene expression data to identify spatial expression quantitative trait loci (eQTLs) and thus regulatory elements located within the ACE2 gene.

Results

We identified regulatory elements within ACE2 that control the expression of PIR, CA5B, and VPS13C in the lung. The gene products of these genes are involved in inflammatory responses, de novo pyrimidine and polyamine synthesis, and the endoplasmic reticulum, respectively.

Conclusion

Our study, although limited by the fact that the identification of the regulatory interactions is putative until proven by targeted experiments, supports the hypothesis that viral silencing of ACE2 alters the activity of gene regulatory regions and promotes an intra-cellular environment suitable for viral replication.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.14.042002: (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

    Experimental Models: Cell Lines
    SentencesResources
    To get lung-specific spatial connections, we identified SNP-gene pairs across lung-specific Hi-C libraries using published data for IMR90, A549, and NCI-H460 cell lines and lung tissue (GEO accession numbers GSE35156, GSE43070, GSE63525, GSE105600, GSE105725, GSE92819, GSE87112, S1 Table).
    A549
    suggested: None
    NCI-H460
    suggested: None
    Software and Algorithms
    SentencesResources
    Identification of SNPs in the ACE locus: We selected all common single nucleotide polymorphisms (SNPs) from dbSNP (build153) with a minor allele frequency (MAF) > 1% that were located within chrX:15,519,996-15,643,106, which included the ACE2 gene and its flanking region (hereafter ACE2 locus).
    dbSNP
    suggested: (dbSNP, RRID:SCR_002338)
    URLs: GEO database: https://www.ncbi.nlm.nih.gov/geo/ CoDeS3D pipeline: https://github.com/Genome3d/codes3d-v2 GTEx Portal: https://gtexportal.org/home/ GUSTO study: http://www.gusto.sg/ Data and code availability: All python and R scripts used for data analysis and visualization are available at https://github.com/Genome3d/ACE2-regulatory-network.
    https://www.ncbi.nlm.nih.gov/geo/
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    CoDeS3D
    suggested: None
    R version 3.5.2 and RStudio version 1.2.5033 were used for all R scripts.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)
    All python scripts used Python 3.7.6.
    python
    suggested: (IPython, RRID:SCR_001658)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Finally, the GTEx database has recognized limitations, including the ethnic diversity of the samples. These limitations will form the basis of future studies.

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2020.04.14.042002v2 on bioRxiv
  3. Version published to 10.1101/2020.04.14.042002v1 on bioRxiv