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

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.

Keywords: Coronavirus infection; Spike glycoprotein; Virus–host interactome.

Fig. 1

KEGG human pathway and Reactome pathways enrichment analysis for 200 proteins identified by RWR algorithm using S-glycoprotein of HCoV-229E

Fig. 2

PPI-COEX multilayer analysis, based on human PPI interactome and COEX network, with top 50 closest proteins/genes identified by RWR, using S-glycoprotein of HCoV-229E. Edges in blue represent protein-protein interactions, while red edges are coexpressions

Fig. 3

KEGG human pathway and Reactome pathways enrichment analyses for 200 proteins identified by RWR algorithm using S-glycoprotein of SARS-CoV

Fig. 4

PPI-COEX multilayer analysis based on human PPI interactome and COEX network, with top 50 closest proteins/genes identified by RWR, using S-glycoprotein of SARS-CoV. Edges in blue represent protein-protein interactions, while red edges are coexpressions

Fig. 5

KEGG human pathway and Reactome pathways enrichment for 200 proteins identified by RWR algorithm using S-glycoprotein of MERS-CoV

Fig. 6

PPI-COEX multilayer analysis based on human PPI interactome and COEX network, with top 50 closest proteins/genes identified by RWR, using S-glycoprotein of MERS-CoV. Edges in blue represent protein-protein interactions, while red edges indicate coexpressions