He Fei, Zhang Yan, Chen Hao, Zhang Ziding, Peng You-Liang
State Key Laboratory for ArgoBiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, PR China.
BMC Genomics. 2008 Nov 2;9:519. doi: 10.1186/1471-2164-9-519.
Protein-protein interaction (PPI) maps are useful tools for investigating the cellular functions of genes. Thus far, large-scale PPI mapping projects have not been implemented for the rice blast fungus Magnaporthe grisea, which is responsible for the most severe rice disease. Inspired by recent advances in PPI prediction, we constructed a PPI map of this important fungus.
Using a well-recognized interolog approach, we have predicted 11,674 interactions among 3,017 M. grisea proteins. Although the scale of the constructed map covers approximately only one-fourth of the M. grisea's proteome, it is the first PPI map for this crucial organism and will therefore provide new insights into the functional genomics of the rice blast fungus. Focusing on the network topology of proteins encoded by known pathogenicity genes, we have found that pathogenicity proteins tend to interact with higher numbers of proteins. The pathogenicity proteins and their interacting partners in the entire network were then used to construct a subnet called a pathogenicity network. These data may provide further clues for the study of these pathogenicity proteins. Finally, it has been established that secreted proteins in M. grisea interact with fewer proteins. These secreted proteins and their interacting partners were also compiled into a network of secreted proteins, which may be helpful in constructing an interactome between the rice blast fungus and rice.
We predicted the PPIs of M. grisea and compiled them into a database server called MPID. It is hoped that MPID will provide new hints as to the functional genomics of this fungus. MPID is available at http://bioinformatics.cau.edu.cn/zzd_lab/MPID.html.
蛋白质-蛋白质相互作用（PPI）图谱是研究基因细胞功能的有用工具。迄今为止，尚未针对引起最严重水稻病害的稻瘟病菌开展大规模PPI图谱绘制项目。受PPI预测方面最新进展的启发，我们构建了这种重要真菌的PPI图谱。
使用一种公认的同源互作方法，我们预测了3017个稻瘟病菌蛋白质之间的11674个相互作用。尽管构建图谱的规模仅覆盖了稻瘟病菌蛋白质组的约四分之一，但它是这种关键生物体的首张PPI图谱，因此将为稻瘟病菌的功能基因组学提供新的见解。聚焦于已知致病基因编码的蛋白质的网络拓扑结构，我们发现致病蛋白倾向于与更多数量的蛋白质相互作用。然后，利用整个网络中的致病蛋白及其相互作用伙伴构建了一个称为致病网络的子网。这些数据可能为这些致病蛋白的研究提供进一步线索。最后，已确定稻瘟病菌中的分泌蛋白与较少的蛋白质相互作用。这些分泌蛋白及其相互作用伙伴也被汇编成一个分泌蛋白网络，这可能有助于构建稻瘟病菌与水稻之间的相互作用组。
我们预测了稻瘟病菌的PPI，并将其汇编到一个名为MPID的数据库服务器中。希望MPID能为这种真菌的功能基因组学提供新的线索。MPID可在http://bioinformatics.cau.edu.cn/zzd_lab/MPID.html获取。
