In Silico Infection Analysis (iSFA) Identified Coronavirus Infection and Potential Transmission Risk in Mammals.

Yanyan Zou,Chengchao Wu,Xiaojian Cao,Bing Yang,Shuang Dong,Lulu Deng,Gang Cao,Wentao Li,Yangyang Xu

doi:10.3389/fmolb.2022.831876

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 mammals’ lung 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.

Highlights

Coronaviruses are a great source of threat to humans which causes diverse diseases ranging from asymptomatic to severe respiratory defection (Kahn and McIntosh, 2005)
To explore the coronavirus infection in mammals, we performed in silico coronaviral genome screening in mammalian transcriptome datasets, except for widely studied Homo sapiens, Mus musculus, and Rattus norvegicus including lungs and intestines (Figure 1A)
In this in silico infection analysis, the sequence of the genomic fragment of 38 coronaviruses was screened from 388 intestine datasets and 1,869 lung datasets of 89 mammal species from the NCBI Sequence Read Archive (SRA)

Summary

Introduction

Coronaviruses are a great source of threat to humans which causes diverse diseases ranging from asymptomatic to severe respiratory defection (Kahn and McIntosh, 2005). Coronaviruses could be divided into four subtypes, including alpha-coronavirus, beta-coronavirus, deltacoronavirus, and gamma-coronavirus. Some of the known beta-coronavirus such as SARS-CoV, MERS-CoV, and recently emerged SARS-CoV-2 can lead to fatal repository health crisis in humans. The traditional epidemiological research methods which include statistics on the prevalence of large group, retrospective analysis have played an important role in clarifying the epidemic pattern, formulating prevention and control iSFA of Coronavirus Infection iSFA of Coronavirus Infection countermeasures of emerging infectious diseases (Cho, 2020; Qiu et al, 2020). Its traceability analysis is often restricted by tedious and limited sample collection and testing work which may expend much manpower and financial resources (Chen et al, 2020b; Hao et al, 2020)

Objectives

Methods

Results

Conclusion