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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 and synthetic dosage lethal (SL/SDL) partners o...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9044693/ https://www.ncbi.nlm.nih.gov/pubmed/35502318 http://dx.doi.org/10.1016/j.isci.2022.104311 |
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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 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. |
format | Online Article Text |
id | pubmed-9044693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-90446932022-04-28 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 iScience 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 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. Elsevier 2022-04-27 /pmc/articles/PMC9044693/ /pubmed/35502318 http://dx.doi.org/10.1016/j.isci.2022.104311 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
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/PMC9044693/ https://www.ncbi.nlm.nih.gov/pubmed/35502318 http://dx.doi.org/10.1016/j.isci.2022.104311 |
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