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

• DOI: 10.1186/s12967-020-02405-w
• Publication Date: 2020-06-10T14:02:53Z
• Authors: Francesco Messina; Emanuela Giombini; Chiara Agrati; Francesco Vairo; Tommaso Ascoli Ba...; Samir Al Moghazi; Mauro Piacentini; Franco Locatelli; Gary Kobinger; Markus Maeurer; Alimuddin Zumla; Maria R. Capobianchi; Francesco Nicola ...; Giuseppe Ippolito; ; Isabella Abbate; Chiara Agrati; Samir Al Moghazi; Tommaso Ascoli Ba...; Barbara Bartolini; Maria R. Capobianchi; Alessandro Capone; Delia Goletti; Gabriella Rozera; Carla Nisii; Roberta Gagliardini; Fabiola Ciccosanti; Gian Maria Fimia; Emanuele Nicastri; Emanuela Giombini; Simone Lanini; Alessandra D’Abramo; Gabriele Rinonapoli; Enrico Girardi; Chiara Montaldo; Raffaella Marconi; Antonio Addis; Bradley Maron; Ginestra Bianconi; Bertrand De Meulder; Jason Kennedy; Shabaana Abdul Kh...; Francesca Luca; Markus Maeurer; Mauro Piacentini; Stefano Merler; Giuseppe Pantaleo; Rafick-Pierre Sekaly; Serena Sanna; Nicola Segata; Alimuddin Zumla; Francesco Messina; Francesco Vairo; Francesco Nicola ...; Giuseppe Ippolito
• Keywords: 0301 basic medicine; Pneumonia, Viral; Virus-host interactome; Models, Biological; Betacoronavirus; 03 medical and health sciences; Viral Envelope Proteins; Protein Interaction Mapping; Coronavirus infection; Humans; Gene Regulatory Networks; Pandemics; Virus–host interactome; 0303 health sciences; Membrane Glycoproteins; SARS-CoV-2; Research; R; COVID-19; Virus–host interactome ; COVID-19 ; Coronavirus infection ; Spike glycoprotein; 3. Good health; coronavirus infection; spike glycoprotein; virus-host interactome; Host-Pathogen Interactions; Medicine; Spike glycoprotein; Coronavirus Infections; Signal Transduction

Abstract 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.