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Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics

SARS-CoV-2 is the causative agent for coronavirus disease-19 (COVID-19) and belongs to the family Coronaviridae that causes sickness varying from the common cold to more severe illnesses such as severe acute respiratory syndrome, sudden stroke, neurological complications (Neuro-COVID), multiple orga...

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Autores principales: Pushparaj, Peter Natesan, Abdulkareem, Angham Abdulrahman, Naseer, Muhammad Imran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438179/
https://www.ncbi.nlm.nih.gov/pubmed/34531741
http://dx.doi.org/10.3389/fphar.2021.688227
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author Pushparaj, Peter Natesan
Abdulkareem, Angham Abdulrahman
Naseer, Muhammad Imran
author_facet Pushparaj, Peter Natesan
Abdulkareem, Angham Abdulrahman
Naseer, Muhammad Imran
author_sort Pushparaj, Peter Natesan
collection PubMed
description SARS-CoV-2 is the causative agent for coronavirus disease-19 (COVID-19) and belongs to the family Coronaviridae that causes sickness varying from the common cold to more severe illnesses such as severe acute respiratory syndrome, sudden stroke, neurological complications (Neuro-COVID), multiple organ failure, and mortality in some patients. The gene expression profiles of COVID-19 infection models can be used to decipher potential therapeutics for COVID-19 and related pathologies, such as Neuro-COVID. Here, we used the raw RNA-seq reads (Single-End) in quadruplicates derived using Illumina Next Seq 500 from SARS-CoV-infected primary human bronchial epithelium (NHBE) and mock-treated NHBE cells obtained from the Gene Expression Omnibus (GEO) (GSE147507), and the quality control (QC) was evaluated using the CLC Genomics Workbench 20.0 (Qiagen, United States) before the RNA-seq analysis using BioJupies web tool and iPathwayGuide for gene ontologies (GO), pathways, upstream regulator genes, small molecules, and natural products. Additionally, single-cell transcriptomics data (GSE163005) of meta clusters of immune cells from the cerebrospinal fluid (CSF), such as T-cells/natural killer cells (NK) (TcMeta), dendritic cells (DCMeta), and monocytes/granulocyte (monoMeta) cell types for comparison, namely, Neuro-COVID versus idiopathic intracranial hypertension (IIH), were analyzed using iPathwayGuide. L1000 fireworks display (L1000FWD) and L1000 characteristic direction signature search engine (L1000 CDS(2)) web tools were used to uncover the small molecules that could potentially reverse the COVID-19 and Neuro-COVID-associated gene signatures. We uncovered small molecules such as camptothecin, importazole, and withaferin A, which can potentially reverse COVID-19 associated gene signatures. In addition, withaferin A, trichostatin A, narciclasine, camptothecin, and JQ1 have the potential to reverse Neuro-COVID gene signatures. Furthermore, the gene set enrichment analysis (GSEA) preranked method and Metascape web tool were used to decipher and annotate the gene signatures that were potentially reversed by these small molecules. In conclusion, our study unravels a rapid approach for applying next-generation knowledge discovery (NGKD) platforms to discover small molecules with therapeutic potential against COVID-19 and its related disease pathologies.
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spelling pubmed-84381792021-09-15 Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics Pushparaj, Peter Natesan Abdulkareem, Angham Abdulrahman Naseer, Muhammad Imran Front Pharmacol Pharmacology SARS-CoV-2 is the causative agent for coronavirus disease-19 (COVID-19) and belongs to the family Coronaviridae that causes sickness varying from the common cold to more severe illnesses such as severe acute respiratory syndrome, sudden stroke, neurological complications (Neuro-COVID), multiple organ failure, and mortality in some patients. The gene expression profiles of COVID-19 infection models can be used to decipher potential therapeutics for COVID-19 and related pathologies, such as Neuro-COVID. Here, we used the raw RNA-seq reads (Single-End) in quadruplicates derived using Illumina Next Seq 500 from SARS-CoV-infected primary human bronchial epithelium (NHBE) and mock-treated NHBE cells obtained from the Gene Expression Omnibus (GEO) (GSE147507), and the quality control (QC) was evaluated using the CLC Genomics Workbench 20.0 (Qiagen, United States) before the RNA-seq analysis using BioJupies web tool and iPathwayGuide for gene ontologies (GO), pathways, upstream regulator genes, small molecules, and natural products. Additionally, single-cell transcriptomics data (GSE163005) of meta clusters of immune cells from the cerebrospinal fluid (CSF), such as T-cells/natural killer cells (NK) (TcMeta), dendritic cells (DCMeta), and monocytes/granulocyte (monoMeta) cell types for comparison, namely, Neuro-COVID versus idiopathic intracranial hypertension (IIH), were analyzed using iPathwayGuide. L1000 fireworks display (L1000FWD) and L1000 characteristic direction signature search engine (L1000 CDS(2)) web tools were used to uncover the small molecules that could potentially reverse the COVID-19 and Neuro-COVID-associated gene signatures. We uncovered small molecules such as camptothecin, importazole, and withaferin A, which can potentially reverse COVID-19 associated gene signatures. In addition, withaferin A, trichostatin A, narciclasine, camptothecin, and JQ1 have the potential to reverse Neuro-COVID gene signatures. Furthermore, the gene set enrichment analysis (GSEA) preranked method and Metascape web tool were used to decipher and annotate the gene signatures that were potentially reversed by these small molecules. In conclusion, our study unravels a rapid approach for applying next-generation knowledge discovery (NGKD) platforms to discover small molecules with therapeutic potential against COVID-19 and its related disease pathologies. Frontiers Media S.A. 2021-08-31 /pmc/articles/PMC8438179/ /pubmed/34531741 http://dx.doi.org/10.3389/fphar.2021.688227 Text en Copyright © 2021 Pushparaj, Abdulkareem and Naseer. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Pushparaj, Peter Natesan
Abdulkareem, Angham Abdulrahman
Naseer, Muhammad Imran
Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics
title Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics
title_full Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics
title_fullStr Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics
title_full_unstemmed Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics
title_short Identification of Novel Gene Signatures using Next-Generation Sequencing Data from COVID-19 Infection Models: Focus on Neuro-COVID and Potential Therapeutics
title_sort identification of novel gene signatures using next-generation sequencing data from covid-19 infection models: focus on neuro-covid and potential therapeutics
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438179/
https://www.ncbi.nlm.nih.gov/pubmed/34531741
http://dx.doi.org/10.3389/fphar.2021.688227
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