In Silico Infection Analysis (iSFA) Identified Coronavirus Infection and Potential Transmission Risk in Mammals - Zou, Yanyan; Cao, Xiaojian; Yang, Bing; Deng, Lulu; Xu, Yangyang; Dong, Shuang; Li, Wentao; Wu, Chengchao; Cao, Gang (Frontiers in Molecular Biosciences, 2022)
Coronaviruses are a great source of threat to public health which could infect various species and causes 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 transcripts mining in transcriptome data of potential host and performed a comprehensive analysis about the infection of 38 coronaviruses in wild animals, based on 2257 transcriptome datasets from 89 mammals’ lung and intestine, and revealed multiple potential coronaviruses infections including PEDV infection in Equus burchellii. Then, through our transmission network analysis, potential intermediate hosts of 5 coronaviruses were identified. Notably, iSFA results suggested that the expression of coronaviruses receptor genes tended to be down-regulated 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, host prediction of other pathogen-induced diseases, thus contributing to the epidemic prevention and control.