Looking for pathways related to COVID-19 phenotypes: Confirmation of pathogenic mechanisms by SARS-CoV-2 - Host interactome
Abstract In the last months, many studies have clearly described several mechanisms of SARS-CoV-2 infection at cell and tissue level. Host conditions and comorbidities were identified as risk factors for severe and fatal disease courses, but the mechanisms of interaction between host and SARS-CoV-2 determining the grade of COVID- 19 severity, are still unknown.We provide a network analysis on protein–protein interactions (PPI) between viral and host proteins to better identify host biological responses, induced by both whole proteome of SARS-CoV-2 and specific viral proteins. A host-virus interactome was inferred on published PPI, using an explorative algorithm (Random Walk with Restart) triggered by all the 28 proteins of SARS-CoV-2, or each single viral protein one-by-one. The functional analysis for all proteins, linked to many aspects of COVID-19 pathogenesis, allows to identify the subcellular districts, where SARS-CoV-2 proteins seem to be distributed, while in each interactome built around one single viral protein, a different response was described, underlining as ORF8 and ORF3a modulated cardiovascular diseases and pro-inflammatory pathways, respectively. Finally, an explorative network-based approach was applied to Bradykinin Storm, highlighting a possible direct action of ORF3a and NS7b to enhancing this condition.This network-based model for SARS-CoV-2 infection could be a framework for pathogenic evaluation of specific clinical outcomes. We identified possible host responses induced by specific proteins of SARS-CoV-2, underlining the important role of specific viral accessory proteins in pathogenic phenotypes of severe COVID-19 patients..
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Preprint| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
bioRxiv.org - (2022) vom: 26. Nov. Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Messina, Francesco [VerfasserIn] |
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| doi: |
10.1101/2020.11.03.366666 |
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| PPN (Katalog-ID): |
XBI019263473 |
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| 100 | 1 | |a Messina, Francesco |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Looking for pathways related to COVID-19 phenotypes: Confirmation of pathogenic mechanisms by SARS-CoV-2 - Host interactome |
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| 520 | |a Abstract In the last months, many studies have clearly described several mechanisms of SARS-CoV-2 infection at cell and tissue level. Host conditions and comorbidities were identified as risk factors for severe and fatal disease courses, but the mechanisms of interaction between host and SARS-CoV-2 determining the grade of COVID- 19 severity, are still unknown.We provide a network analysis on protein–protein interactions (PPI) between viral and host proteins to better identify host biological responses, induced by both whole proteome of SARS-CoV-2 and specific viral proteins. A host-virus interactome was inferred on published PPI, using an explorative algorithm (Random Walk with Restart) triggered by all the 28 proteins of SARS-CoV-2, or each single viral protein one-by-one. The functional analysis for all proteins, linked to many aspects of COVID-19 pathogenesis, allows to identify the subcellular districts, where SARS-CoV-2 proteins seem to be distributed, while in each interactome built around one single viral protein, a different response was described, underlining as ORF8 and ORF3a modulated cardiovascular diseases and pro-inflammatory pathways, respectively. Finally, an explorative network-based approach was applied to Bradykinin Storm, highlighting a possible direct action of ORF3a and NS7b to enhancing this condition.This network-based model for SARS-CoV-2 infection could be a framework for pathogenic evaluation of specific clinical outcomes. We identified possible host responses induced by specific proteins of SARS-CoV-2, underlining the important role of specific viral accessory proteins in pathogenic phenotypes of severe COVID-19 patients. | ||
| 650 | 4 | |a Biology |7 (dpeaa)DE-84 | |
| 650 | 4 | |a 570 |7 (dpeaa)DE-84 | |
| 700 | 1 | |a Giombini, Emanuela |e verfasserin |4 aut | |
| 700 | 1 | |a Montaldo, Chiara |e verfasserin |4 aut | |
| 700 | 1 | |a Sharma, Ashish Arunkumar |e verfasserin |4 aut | |
| 700 | 1 | |a Piacentini, Mauro |e verfasserin |4 aut | |
| 700 | 1 | |a Zoccoli, Antonio |e verfasserin |4 aut | |
| 700 | 1 | |a Sekaly, Rafick-Pierre |e verfasserin |4 aut | |
| 700 | 1 | |a Locatelli, Franco |e verfasserin |4 aut | |
| 700 | 1 | |a Zumla, Alimuddin |e verfasserin |4 aut | |
| 700 | 1 | |a Maeurer, Markus |e verfasserin |4 aut | |
| 700 | 1 | |a Capobianchi, Maria R. |e verfasserin |4 aut | |
| 700 | 1 | |a Lauria, Francesco Nicola |e verfasserin |4 aut | |
| 700 | 1 | |a Ippolito, Giuseppe |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t bioRxiv.org |g (2022) vom: 26. Nov. |
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| 856 | 4 | 0 | |u http://dx.doi.org/10.1101/2020.11.03.366666 |z kostenfrei |3 Volltext |
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