Institute of Informatics, University of Warsaw, Warsaw, Poland.
BMC Bioinformatics. 2009 Nov 30;10:393. doi: 10.1186/1471-2105-10-393.
The assembly of reliable and complete protein-protein interaction (PPI) maps remains one of the significant challenges in systems biology. Computational methods which integrate and prioritize interaction data can greatly aid in approaching this goal.
We developed a Bayesian inference framework which uses phylogenetic relationships to guide the integration of PPI evidence across multiple datasets and species, providing more accurate predictions. We apply our framework to reconcile seven eukaryotic interactomes: H. sapiens, M. musculus, R. norvegicus, D. melanogaster, C. elegans, S. cerevisiae and A. thaliana. Comprehensive GO-based quality assessment indicates a 5% to 44% score increase in predicted interactomes compared to the input data. Further support is provided by gold-standard MIPS, CYC2008 and HPRD datasets. We demonstrate the ability to recover known PPIs in well-characterized yeast and human complexes (26S proteasome, endosome and exosome) and suggest possible new partners interacting with the putative SWI/SNF chromatin remodeling complex in A. thaliana.
Our phylogeny-guided approach compares favorably to two standard methods for mapping PPIs across species. Detailed analysis of predictions in selected functional modules uncovers specific PPI profiles among homologous proteins, establishing interaction-based partitioning of protein families. Provided evidence also suggests that interactions within core complex subunits are in general more conserved and easier to transfer accurately to other organisms, than interactions between these subunits.
可靠且完整的蛋白质-蛋白质相互作用（PPI）图谱的组装仍然是系统生物学中的重大挑战之一。整合和优先化交互数据的计算方法可以极大地帮助实现这一目标。
我们开发了一种贝叶斯推断框架，该框架利用系统发育关系来指导跨多个数据集和物种整合 PPI 证据，从而提供更准确的预测。我们将该框架应用于整合七个真核生物相互作用组：H. sapiens、M. musculus、R. norvegicus、D. melanogaster、C. elegans、S. cerevisiae 和 A. thaliana。基于全面的 GO 质量评估，与输入数据相比，预测的相互作用组的得分提高了 5%至 44%。MIPS、CYC2008 和 HPRD 等黄金标准数据集提供了进一步的支持。我们证明了在酵母和人类复合物（26S 蛋白酶体、内体和外体）中恢复已知的 PPI 的能力，并提出了与拟南芥中假定的 SWI/SNF 染色质重塑复合物相互作用的可能的新伙伴。
我们的基于系统发育的方法与两种跨物种映射 PPI 的标准方法相比具有优势。在选定的功能模块中对预测进行详细分析，可以揭示同源蛋白之间特定的 PPI 特征，从而建立基于相互作用的蛋白质家族划分。提供的证据还表明，核心复合物亚基内的相互作用通常比这些亚基之间的相互作用更保守且更容易准确地转移到其他生物体。
