Suppr超能文献

基于宿主蛋白的哺乳动物病毒跨物种传播预测

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

作者信息

Zhang Zheng, Lu Congyu, Mo Bocheng, Bai Kehan, Ge Xing-Yi, Deng Li, Peng Yousong

机构信息

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

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

出版信息

Microbiol Spectr. 2023 Sep 27;11(5):e0536822. doi: 10.1128/spectrum.05368-22.

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 , and , 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.

摘要

大多数新兴病毒都是从哺乳动物中溢出的。了解病毒跨物种传播的机制并在其出现之前识别出人畜共患病毒对于新兴病毒的预防和控制至关重要。本研究基于1271对病毒与哺乳动物的相互作用,系统地研究了与哺乳动物病毒跨物种传播相关的宿主蛋白,这些相互作用包括来自33个病毒科的382种病毒和来自11个目73种哺乳动物。发现许多宿主蛋白有助于哺乳动物病毒的跨物种传播。潜在有助于病毒跨物种传播的宿主蛋白具有病毒科特异性,在不同病毒科中观察到的此类宿主蛋白几乎没有重叠。基于这些宿主蛋白,构建了随机森林(RF)模型来预测哺乳动物病毒的跨物种传播潜力。将所有病毒一起使用时,模型性能中等。然而,按病毒科进行建模时,RF模型的性能在不同病毒科之间差异很大。在诸如 、 和 等13个病毒科中,RF模型的AUC大于0.8。最后,评估了病毒受体对跨物种传播的贡献,发现病毒受体在预测哺乳动物病毒跨物种传播方面作用较小。该研究加深了我们对病毒跨物种传播机制的理解,并为预测哺乳动物病毒的跨物种传播提供了一个框架。重要性新兴病毒对人类构成严重威胁。了解病毒跨物种传播的机制并在其出现之前识别出人畜共患病毒对于新兴病毒的预防和控制至关重要。本研究系统地鉴定了与哺乳动物病毒跨物种传播相关的宿主因素,并进一步基于包括病毒受体在内的宿主因素构建了用于预测病毒跨物种传播的机器学习模型。该研究不仅加深了我们对病毒跨物种传播机制的理解,还为基于宿主因素预测哺乳动物病毒的跨物种传播提供了一个框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4170/10581197/53e3677154a3/spectrum.05368-22.f001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验