Zhang Kang, Li Yuejiao, Li Tengjiao, Li Zhi-Gang, Hsiang Tom, Zhang Ziding, Sun Wenxian
Department of Plant Pathology and the Ministry of Agriculture Key Laboratory for Plant Pathology, China Agricultural University , Beijing 100193, China.
School of Environmental Sciences, University of Guelph , Guelph, Ontario N1G 2W1, Canada.
J Proteome Res. 2017 Mar 3;16(3):1193-1206. doi: 10.1021/acs.jproteome.6b00720. Epub 2017 Feb 7.
Rice false smut, caused by Ustilaginoidea virens, produces significant losses in rice yield and grain quality and has recently emerged as one of the most important rice diseases worldwide. Despite its importance in rice production, relatively few studies have been conducted to illustrate the complex interactome and the pathogenicity gene interactions. Here a protein-protein interaction network of U. virens was built through two well-recognized approaches, interolog- and domain-domain interaction-based methods. A total of 20 217 interactions associated with 3305 proteins were predicted after strict filtering. The reliability of the network was assessed computationally and experimentally. The topology of the interactome network revealed highly connected proteins. A pathogenicity-related subnetwork involving up-regulated genes during early U. virens infection was also constructed, and many novel pathogenicity proteins were predicted in the subnetwork. In addition, we built an interspecies PPI network between U. virens and Oryza sativa, providing new insights for molecular interactions of this host-pathogen pathosystem. A web-based publicly available interactive database based on these interaction networks has also been released. In summary, a proteome-scale map of the PPI network was described for U. virens, which will provide new perspectives for finely dissecting interactions of genes related to its pathogenicity.
稻曲病由稻绿核菌引起，会导致水稻产量和品质大幅下降，最近已成为全球最重要的水稻病害之一。尽管其在水稻生产中具有重要性，但相对较少有研究阐明其复杂的相互作用组和致病基因相互作用。在此，通过两种公认的方法，即基于同源互作和结构域 - 结构域相互作用的方法，构建了稻绿核菌的蛋白质 - 蛋白质相互作用网络。经过严格筛选后，共预测到与3305个蛋白质相关的20217个相互作用。通过计算和实验评估了该网络的可靠性。相互作用组网络的拓扑结构揭示了高度连接的蛋白质。还构建了一个与稻绿核菌早期感染期间上调基因相关的致病性子网络，并在该子网络中预测了许多新的致病蛋白。此外，我们构建了稻绿核菌与水稻之间的种间蛋白质 - 蛋白质相互作用网络，为该宿主 - 病原体病理系统的分子相互作用提供了新的见解。基于这些相互作用网络的一个基于网络的公开交互式数据库也已发布。总之，描述了稻绿核菌蛋白质 - 蛋白质相互作用网络的蛋白质组规模图谱，这将为精细剖析与其致病性相关的基因相互作用提供新的视角。
