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Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19

Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome cor...

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Autores principales: Nambou, Komi, Anakpa, Manawa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374176/
https://www.ncbi.nlm.nih.gov/pubmed/32707288
http://dx.doi.org/10.1016/j.meegid.2020.104471
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author Nambou, Komi
Anakpa, Manawa
author_facet Nambou, Komi
Anakpa, Manawa
author_sort Nambou, Komi
collection PubMed
description Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, based on publicly available genomic data, we analyzed the codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host, identified CoV-responsive human genes and their functional roles on the basis of both the relative synonymous codon usage (RSCU)-based correlation of viral genes with human genes and differential gene expression analysis, and predicted potential drugs for COVID-19 treatment based on these genes. The relatively high codon adaptation index (CAI) values (>0.70) signposted the gene expressivity efficiency of CoVs in human. The ENc-GC3 plot indicated that SARS-CoV-2 genome was under strict selection pressure while SARS-CoV and MERS-CoV were under selection and mutational pressures. The RSCU-based correlation analysis indicated that the viral genomes shared similar codons with a panoply of human genes. The merging of RSCU-based correlation data and SARS-CoV-2-responsive differentially expressed genes allowed the identification of human genes potentially affected by SARS-CoV-2 infection. Functional enrichment analysis indicated that these genes were enriched in biological processes and pathways related to host response to viral infection and immune response. Using the drug-gene interaction database, we screened a list of drugs that could target these genes as potential COVID-19 therapeutics. Our findings not only will contribute in vaccine development but also provide a useful set of drugs that could guide practitioners in strategical monitoring of COVID-19. We recommend practitioners to scrupulously screen this list of predicted drugs in order to authenticate those qualified for treating COVID-19 symptoms.
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spelling pubmed-73741762020-07-22 Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19 Nambou, Komi Anakpa, Manawa Infect Genet Evol Research Paper Coronavirus disease 2019 (COVID-19) has caused thousands of deaths worldwide and has become an urgent public health concern. The extraordinary interhuman transmission of this disease has urged scientists to examine the various facets of its pathogenic agent, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Herein, based on publicly available genomic data, we analyzed the codon usage co-adaptation profiles of SARS-CoV-2 and other respiratory coronaviruses (CoVs) with their human host, identified CoV-responsive human genes and their functional roles on the basis of both the relative synonymous codon usage (RSCU)-based correlation of viral genes with human genes and differential gene expression analysis, and predicted potential drugs for COVID-19 treatment based on these genes. The relatively high codon adaptation index (CAI) values (>0.70) signposted the gene expressivity efficiency of CoVs in human. The ENc-GC3 plot indicated that SARS-CoV-2 genome was under strict selection pressure while SARS-CoV and MERS-CoV were under selection and mutational pressures. The RSCU-based correlation analysis indicated that the viral genomes shared similar codons with a panoply of human genes. The merging of RSCU-based correlation data and SARS-CoV-2-responsive differentially expressed genes allowed the identification of human genes potentially affected by SARS-CoV-2 infection. Functional enrichment analysis indicated that these genes were enriched in biological processes and pathways related to host response to viral infection and immune response. Using the drug-gene interaction database, we screened a list of drugs that could target these genes as potential COVID-19 therapeutics. Our findings not only will contribute in vaccine development but also provide a useful set of drugs that could guide practitioners in strategical monitoring of COVID-19. We recommend practitioners to scrupulously screen this list of predicted drugs in order to authenticate those qualified for treating COVID-19 symptoms. Elsevier B.V. 2020-11 2020-07-22 /pmc/articles/PMC7374176/ /pubmed/32707288 http://dx.doi.org/10.1016/j.meegid.2020.104471 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Research Paper
Nambou, Komi
Anakpa, Manawa
Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19
title Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19
title_full Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19
title_fullStr Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19
title_full_unstemmed Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19
title_short Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19
title_sort deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for covid-19
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374176/
https://www.ncbi.nlm.nih.gov/pubmed/32707288
http://dx.doi.org/10.1016/j.meegid.2020.104471
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