In:
PLOS Computational Biology, Public Library of Science (PLoS), Vol. 18, No. 4 ( 2022-4-11), p. e1010021-
Abstract:
Comparing SARS-CoV-2 infection-induced gene expression signatures to drug treatment-induced gene expression signatures is a promising bioinformatic tool to repurpose existing drugs against SARS-CoV-2. The general hypothesis of signature-based drug repurposing is that drugs with inverse similarity to a disease signature can reverse disease phenotype and thus be effective against it. However, in the case of viral infection diseases, like SARS-CoV-2, infected cells also activate adaptive, antiviral pathways, so that the relationship between effective drug and disease signature can be more ambiguous. To address this question, we analysed gene expression data from in vitro SARS-CoV-2 infected cell lines, and gene expression signatures of drugs showing anti-SARS-CoV-2 activity. Our extensive functional genomic analysis showed that both infection and treatment with in vitro effective drugs leads to activation of antiviral pathways like NFkB and JAK-STAT. Based on the similarity—and not inverse similarity—between drug and infection-induced gene expression signatures, we were able to predict the in vitro antiviral activity of drugs. We also identified SREBF1/2, key regulators of lipid metabolising enzymes, as the most activated transcription factors by several in vitro effective antiviral drugs. Using a fluorescently labeled cholesterol sensor, we showed that these drugs decrease the cholesterol levels of plasma-membrane. Supplementing drug-treated cells with cholesterol reversed the in vitro antiviral effect, suggesting the depleting plasma-membrane cholesterol plays a key role in virus inhibitory mechanism. Our results can help to more effectively repurpose approved drugs against SARS-CoV-2, and also highlights key mechanisms behind their antiviral effect.
Type of Medium:
Online Resource
ISSN:
1553-7358
DOI:
10.1371/journal.pcbi.1010021
DOI:
10.1371/journal.pcbi.1010021.g001
DOI:
10.1371/journal.pcbi.1010021.g002
DOI:
10.1371/journal.pcbi.1010021.g003
DOI:
10.1371/journal.pcbi.1010021.g004
DOI:
10.1371/journal.pcbi.1010021.g005
DOI:
10.1371/journal.pcbi.1010021.s001
DOI:
10.1371/journal.pcbi.1010021.s002
DOI:
10.1371/journal.pcbi.1010021.s003
DOI:
10.1371/journal.pcbi.1010021.s004
DOI:
10.1371/journal.pcbi.1010021.s005
DOI:
10.1371/journal.pcbi.1010021.r001
DOI:
10.1371/journal.pcbi.1010021.r002
DOI:
10.1371/journal.pcbi.1010021.r003
DOI:
10.1371/journal.pcbi.1010021.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2022
detail.hit.zdb_id:
2193340-6
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