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In Silico Infection Analysis (iSFA) Identified Coronavirus Infection and Potential Transmission Risk in Mammals
Frontiers in molecular biosciences ; 9, 2022.
Article in English | EuropePMC | ID: covidwho-1695081
ABSTRACT
Coronaviruses are a great source of threat to public health which could infect various species and cause diverse diseases. However, the epidemic’s spreading among different species remains elusive. This study proposed an in silico infection analysis (iSFA) system that includes pathogen genome or transcript mining in transcriptome data of the potential host and performed a comprehensive analysis about the infection of 38 coronaviruses in wild animals, based on 2,257 transcriptome datasets from 89 mammalslung and intestine, and revealed multiple potential coronavirus infections including porcine epidemic diarrhea virus (PEDV) infection in Equus burchellii. Then, through our transmission network analysis, potential intermediate hosts of five coronaviruses were identified. Notably, iSFA results suggested that the expression of coronavirus receptor genes tended to be downregulated after infection by another virus. Finally, binding affinity and interactive interface analysis of S1 protein and ACE2 from different species demonstrated the potential inter-species transmission barrier and cross-species transmission of SARS-CoV-2. Meanwhile, the iSFA system developed in this study could be further applied to conduct the source tracing and host prediction of other pathogen-induced diseases, thus contributing to the epidemic prevention and control.
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Collection: Databases of international organizations Database: EuropePMC Type of study: Prognostic study Language: English Journal: Frontiers in molecular biosciences Year: 2022 Document Type: Article

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Collection: Databases of international organizations Database: EuropePMC Type of study: Prognostic study Language: English Journal: Frontiers in molecular biosciences Year: 2022 Document Type: Article