Prediction of mammalian virus cross-species transmission based on host proteins

Author:

Zhang Zheng12ORCID,Lu Congyu1,Mo Bocheng2,Bai Kehan3,Ge Xing-Yi1,Deng Li4,Peng Yousong1ORCID

Affiliation:

1. Bioinformatics Center, College of Biology, Hunan Provincial Key Laboratory of Medical Virology, Hunan University , Changsha, Hunan, China

2. Hunan Engineering and Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University , Changsha, Hunan, China

3. Hunan Juyoubiotech Co., Ltd , Changsha, Hunan, China

4. Department of Internal Medicine-Neurology, The Third Hospital of Changsha , Changsha, Hunan, China

Abstract

ABSTRACT Most emerging viruses are spilled over from mammals. Understanding the mechanism of virus cross-species transmission and identifying zoonotic viruses before their emergence are critical for the prevention and control of newly emerging viruses. This study systematically investigated the host proteins associated with the cross-species transmission of mammalian viruses based on 1,271 pairs of virus-mammal interactions including 382 viruses from 33 viral families and 73 mammal species from 11 orders. Numerous host proteins were found to contribute to the cross-species transmission of mammalian viruses. Host proteins potentially contributing to virus cross-species transmission are specific to viral families, and few overlaps of such host proteins are observed in different viral families. Based on these host proteins, the random-forest (RF) models were built to predict the cross-species transmission potential of mammalian viruses. Moderate performance was obtained when using all viruses together. However, when modeling by viral family, the performance of the RF models varied much among viral families. In 13 viral families such as Flaviviridae , Retroviridae, and Poxviridae , the AUC of the RF model was greater than 0.8. Finally, the contribution of virus receptors to cross-species transmission was evaluated, and the virus receptor was found to have a minor effect in predicting the cross-species transmission of mammalian viruses. The study deepens our understanding of the mechanism of virus cross-species transmission and provides a framework for predicting the cross-species transmission of mammalian viruses. IMPORTANCE Emerging viruses pose serious threats to humans. Understanding the mechanism of virus cross-species transmission and identifying zoonotic viruses before their emergence are critical for the prevention and control of emerging viruses. This study systematically identified host factors associated with cross-species transmission of mammalian viruses and further built machine-learning models for predicting cross-species transmission of the viruses based on host factors including virus receptors. The study not only deepens our understanding of the mechanism of virus cross-species transmission but also provides a framework for predicting the cross-species transmission of mammalian viruses based on host factors.

Funder

MOST | National Natural Science Foundation of China

HSTD | Natural Science Foundation of Hunan Province

Xiaohe Sci-Tech Talents Special Funding under Hunan Provincial Sci-Tech Talents Sponsorship Program

Scientific Research program of the Educational Department of Hunan Province

Double-First Class Construction Funds of Hunan University

Publisher

American Society for Microbiology

Subject

Infectious Diseases,Cell Biology,Microbiology (medical),Genetics,General Immunology and Microbiology,Ecology,Physiology

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Current Trend and Performance Evaluation of Machine Learning Methods for Predicting Host-Pathogen Protein-Protein Interactions;2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG);2024-04-02

2. RNAVirHost: a machine learning–based method for predicting hosts of RNA viruses through viral genomes;GigaScience;2024

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