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Synthetic lethality-based prediction of anti-SARS-CoV-2 targets

Authors :
Lipika R. Pal
Kuoyuan Cheng
Nishanth Ulhas Nair
Laura Martin-Sancho
Sanju Sinha
Yuan Pu
Laura Riva
Xin Yin
Fiorella Schischlik
Joo Sang Lee
Sumit K. Chanda
Eytan Ruppin
Source :
iScience, Vol 25, Iss 5, Pp 104311- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Summary: Novel strategies are needed to identify drug targets and treatments for the COVID-19 pandemic. The altered gene expression of virus-infected host cells provides an opportunity to specifically inhibit viral propagation via targeting the synthetic lethal and synthetic dosage lethal (SL/SDL) partners of such altered host genes. Pursuing this disparate antiviral strategy, here we comprehensively analyzed multiple in vitro and in vivo bulk and single-cell RNA-sequencing datasets of SARS-CoV-2 infection to predict clinically relevant candidate antiviral targets that are SL/SDL with altered host genes. The predicted SL/SDL-based targets are highly enriched for infected cell inhibiting genes reported in four SARS-CoV-2 CRISPR-Cas9 genome-wide genetic screens. We further selected a focused subset of 26 genes that we experimentally tested in a targeted siRNA screen using human Caco-2 cells. Notably, as predicted, knocking down these targets reduced viral replication and cell viability only under the infected condition without harming noninfected healthy cells.

Details

Language :
English
ISSN :
25890042
Volume :
25
Issue :
5
Database :
Directory of Open Access Journals
Journal :
iScience
Publication Type :
Academic Journal
Accession number :
edsdoj.38f812d912a2472cacf9acc270fddacc
Document Type :
article
Full Text :
https://doi.org/10.1016/j.isci.2022.104311