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The prediction of protein-protein interaction networks in rice blast fungus

机译:稻瘟病菌蛋白质-蛋白质相互作用网络的预测

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Background 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. Results 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. Conclusion 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 webcite .
机译:背景蛋白质-蛋白质相互作用(PPI)图是研究基因的细胞功能的有用工具。迄今为止,尚未对造成最严重水稻疾病的稻瘟病菌Magnaporthe grisea实施大规模的PPI绘图项目。受PPI预测最新进展的启发,我们构建了这种重要真菌的PPI图。结果使用公认的内部同源物方法,我们已经预测了3,017 M. grisea蛋白之间的11,674个相互作用。尽管构建图谱的比例仅覆盖了稻瘟病菌蛋白质组的四分之一,但这是该关键生物的首个PPI图谱,因此将为稻瘟病菌的功能基因组学提供新的见识。着眼于已知致病性基因编码的蛋白质的网络拓扑,我们发现致病性蛋白质倾向于与更高数量的蛋白质相互作用。整个网络中的致病蛋白及其相互作用伙伴随后被用来构建一个称为致病网络的子网。这些数据可能为研究这些致病性蛋白提供进一步的线索。最终,已确定稻瘟病菌中分泌的蛋白质与较少的蛋白质相互作用。这些分泌的蛋白质及其相互作用的伙伴也被编译成一个分泌蛋白质的网络,这可能有助于在稻瘟病菌和水稻之间建立一个相互作用基因组。结论我们预测了稻瘟病菌的PPI,并将其编译到名为MPID的数据库服务器中。希望MPID将为这种真菌的功能基因组学提供新的提示。可从http://bioinformatics.cau.edu.cn/zzd_lab/MPID.html网站上获得MPID。

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