COVID-19: viral-host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection

• Published in: Journal of Translational Medicine Vol. 18; no. 1; p. 233
• Main Authors: 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
• Format: Journal Article Web Resource
• Language: English
• Published: England BioMed Central Ltd 10.06.2020; Springer Nature B.V; BioMed Central; BMC
• Subjects: ACE2; Angiotensin-converting enzyme 2; Betacoronavirus - physiology; Chemokines; Coronaviridae; Coronavirus infection; Coronavirus Infections - genetics; Coronavirus Infections - virology; Coronaviruses; COVID-19; Epidemiology; Gene Regulatory Networks; Health aspects; Host-Pathogen Interactions; Humans; Innate immunity; Membrane Glycoproteins - metabolism; Middle East respiratory syndrome; Models, Biological; Pandemics; Phenotypes; Pneumonia, Viral - genetics; Pneumonia, Viral - virology; Protein interaction; Protein Interaction Mapping; Protein-protein interactions; Proteomics; SARS-CoV-2; Severe acute respiratory syndrome coronavirus 2; Signal Transduction - genetics; Spike glycoprotein; Therapeutics; Toll-like receptors; Viral Envelope Proteins; Virus–host interactome; Spike glycoprotein; Virus–host interactome; Coronavirus infection
• ISSN: 1479-5876; 1479-5876
• DOI: 10.1186/s12967-020-02405-w

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. 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. 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. 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.