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

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 (SL) partners of such altered host genes. Pursu...

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Autores principales: Pal, Lipika R., Cheng, Kuoyuan, Nair, Nishanth Ulhas, Martin-Sancho, Laura, Sinha, Sanju, Pu, Yuan, Riva, Laura, Yin, Xin, Schischlik, Fiorella, Lee, Joo Sang, Chanda, Sumit K., Ruppin, Eytan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452092/
https://www.ncbi.nlm.nih.gov/pubmed/34545363
http://dx.doi.org/10.1101/2021.09.14.460408
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author Pal, Lipika R.
Cheng, Kuoyuan
Nair, Nishanth Ulhas
Martin-Sancho, Laura
Sinha, Sanju
Pu, Yuan
Riva, Laura
Yin, Xin
Schischlik, Fiorella
Lee, Joo Sang
Chanda, Sumit K.
Ruppin, Eytan
author_facet Pal, Lipika R.
Cheng, Kuoyuan
Nair, Nishanth Ulhas
Martin-Sancho, Laura
Sinha, Sanju
Pu, Yuan
Riva, Laura
Yin, Xin
Schischlik, Fiorella
Lee, Joo Sang
Chanda, Sumit K.
Ruppin, Eytan
author_sort Pal, Lipika R.
collection PubMed
description 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 (SL) partners of such altered host genes. Pursuing this 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 with altered host genes. The predicted SL-based targets are highly enriched for infected cell inhibiting genes reported in four SARS-CoV-2 CRISPR-Cas9 genome-wide genetic screens. Integrating our predictions with the results of these 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 non-infected cells. Our results are made publicly available, to facilitate their in vivo testing and further validation.
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spelling pubmed-84520922021-09-21 Synthetic lethality-based prediction of anti-SARS-CoV-2 targets Pal, Lipika R. Cheng, Kuoyuan Nair, Nishanth Ulhas Martin-Sancho, Laura Sinha, Sanju Pu, Yuan Riva, Laura Yin, Xin Schischlik, Fiorella Lee, Joo Sang Chanda, Sumit K. Ruppin, Eytan bioRxiv Article 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 (SL) partners of such altered host genes. Pursuing this 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 with altered host genes. The predicted SL-based targets are highly enriched for infected cell inhibiting genes reported in four SARS-CoV-2 CRISPR-Cas9 genome-wide genetic screens. Integrating our predictions with the results of these 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 non-infected cells. Our results are made publicly available, to facilitate their in vivo testing and further validation. Cold Spring Harbor Laboratory 2021-09-15 /pmc/articles/PMC8452092/ /pubmed/34545363 http://dx.doi.org/10.1101/2021.09.14.460408 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Pal, Lipika R.
Cheng, Kuoyuan
Nair, Nishanth Ulhas
Martin-Sancho, Laura
Sinha, Sanju
Pu, Yuan
Riva, Laura
Yin, Xin
Schischlik, Fiorella
Lee, Joo Sang
Chanda, Sumit K.
Ruppin, Eytan
Synthetic lethality-based prediction of anti-SARS-CoV-2 targets
title Synthetic lethality-based prediction of anti-SARS-CoV-2 targets
title_full Synthetic lethality-based prediction of anti-SARS-CoV-2 targets
title_fullStr Synthetic lethality-based prediction of anti-SARS-CoV-2 targets
title_full_unstemmed Synthetic lethality-based prediction of anti-SARS-CoV-2 targets
title_short Synthetic lethality-based prediction of anti-SARS-CoV-2 targets
title_sort synthetic lethality-based prediction of anti-sars-cov-2 targets
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8452092/
https://www.ncbi.nlm.nih.gov/pubmed/34545363
http://dx.doi.org/10.1101/2021.09.14.460408
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