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COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection
BACKGROUND: Epidemiological, virological and pathogenetic characteristics of SARS-CoV-2 infection are under evaluation. A better understanding of the pathophysiology associated with COVID-19 is crucial to improve treatment modalities and to develop effective prevention strategies. Transcriptomic and...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286221/ https://www.ncbi.nlm.nih.gov/pubmed/32522207 http://dx.doi.org/10.1186/s12967-020-02405-w |
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author | Messina, Francesco Giombini, Emanuela Agrati, Chiara Vairo, Francesco Ascoli Bartoli, Tommaso Al Moghazi, Samir Piacentini, Mauro Locatelli, Franco Kobinger, Gary Maeurer, Markus Zumla, Alimuddin Capobianchi, Maria R. Lauria, Francesco Nicola Ippolito, Giuseppe |
author_facet | Messina, Francesco Giombini, Emanuela Agrati, Chiara Vairo, Francesco Ascoli Bartoli, Tommaso Al Moghazi, Samir Piacentini, Mauro Locatelli, Franco Kobinger, Gary Maeurer, Markus Zumla, Alimuddin Capobianchi, Maria R. Lauria, Francesco Nicola Ippolito, Giuseppe |
author_sort | Messina, Francesco |
collection | PubMed |
description | BACKGROUND: Epidemiological, virological and pathogenetic characteristics of SARS-CoV-2 infection are under evaluation. A better understanding of the pathophysiology associated with COVID-19 is crucial to improve treatment modalities and to develop effective prevention strategies. Transcriptomic and proteomic data on the host response against SARS-CoV-2 still have anecdotic character; currently available data from other coronavirus infections are therefore a key source of information. METHODS: We investigated selected molecular aspects of three human coronavirus (HCoV) infections, namely SARS-CoV, MERS-CoV and HCoV-229E, through a network based-approach. A functional analysis of HCoV–host interactome was carried out in order to provide a theoretic host–pathogen interaction model for HCoV infections and in order to translate the results in prediction for SARS-CoV-2 pathogenesis. The 3D model of S-glycoprotein of SARS-CoV-2 was compared to the structure of the corresponding SARS-CoV, HCoV-229E and MERS-CoV S-glycoprotein. SARS-CoV, MERS-CoV, HCoV-229E and the host interactome were inferred through published protein–protein interactions (PPI) as well as gene co-expression, triggered by HCoV S-glycoprotein in host cells. RESULTS: Although the amino acid sequences of the S-glycoprotein were found to be different between the various HCoV, the structures showed high similarity, but the best 3D structural overlap shared by SARS-CoV and SARS-CoV-2, consistent with the shared ACE2 predicted receptor. The host interactome, linked to the S-glycoprotein of SARS-CoV and MERS-CoV, mainly highlighted innate immunity pathway components, such as Toll Like receptors, cytokines and chemokines. CONCLUSIONS: In this paper, we developed a network-based model with the aim to define molecular aspects of pathogenic phenotypes in HCoV infections. The resulting pattern may facilitate the process of structure-guided pharmaceutical and diagnostic research with the prospect to identify potential new biological targets. |
format | Online Article Text |
id | pubmed-7286221 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72862212020-06-11 COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection Messina, Francesco Giombini, Emanuela Agrati, Chiara Vairo, Francesco Ascoli Bartoli, Tommaso Al Moghazi, Samir Piacentini, Mauro Locatelli, Franco Kobinger, Gary Maeurer, Markus Zumla, Alimuddin Capobianchi, Maria R. Lauria, Francesco Nicola Ippolito, Giuseppe J Transl Med Research BACKGROUND: Epidemiological, virological and pathogenetic characteristics of SARS-CoV-2 infection are under evaluation. A better understanding of the pathophysiology associated with COVID-19 is crucial to improve treatment modalities and to develop effective prevention strategies. Transcriptomic and proteomic data on the host response against SARS-CoV-2 still have anecdotic character; currently available data from other coronavirus infections are therefore a key source of information. METHODS: We investigated selected molecular aspects of three human coronavirus (HCoV) infections, namely SARS-CoV, MERS-CoV and HCoV-229E, through a network based-approach. A functional analysis of HCoV–host interactome was carried out in order to provide a theoretic host–pathogen interaction model for HCoV infections and in order to translate the results in prediction for SARS-CoV-2 pathogenesis. The 3D model of S-glycoprotein of SARS-CoV-2 was compared to the structure of the corresponding SARS-CoV, HCoV-229E and MERS-CoV S-glycoprotein. SARS-CoV, MERS-CoV, HCoV-229E and the host interactome were inferred through published protein–protein interactions (PPI) as well as gene co-expression, triggered by HCoV S-glycoprotein in host cells. RESULTS: Although the amino acid sequences of the S-glycoprotein were found to be different between the various HCoV, the structures showed high similarity, but the best 3D structural overlap shared by SARS-CoV and SARS-CoV-2, consistent with the shared ACE2 predicted receptor. The host interactome, linked to the S-glycoprotein of SARS-CoV and MERS-CoV, mainly highlighted innate immunity pathway components, such as Toll Like receptors, cytokines and chemokines. CONCLUSIONS: In this paper, we developed a network-based model with the aim to define molecular aspects of pathogenic phenotypes in HCoV infections. The resulting pattern may facilitate the process of structure-guided pharmaceutical and diagnostic research with the prospect to identify potential new biological targets. BioMed Central 2020-06-10 /pmc/articles/PMC7286221/ /pubmed/32522207 http://dx.doi.org/10.1186/s12967-020-02405-w Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Messina, Francesco Giombini, Emanuela Agrati, Chiara Vairo, Francesco Ascoli Bartoli, Tommaso Al Moghazi, Samir Piacentini, Mauro Locatelli, Franco Kobinger, Gary Maeurer, Markus Zumla, Alimuddin Capobianchi, Maria R. Lauria, Francesco Nicola Ippolito, Giuseppe COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection |
title | COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection |
title_full | COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection |
title_fullStr | COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection |
title_full_unstemmed | COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection |
title_short | COVID-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection |
title_sort | covid-19: viral–host interactome analyzed by network based-approach model to study pathogenesis of sars-cov-2 infection |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286221/ https://www.ncbi.nlm.nih.gov/pubmed/32522207 http://dx.doi.org/10.1186/s12967-020-02405-w |
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