Liang Zhi, Xu Meng, Teng Maikun, Niu Liwen
Hefei National Laboratory for Physical Sciences at Microscale and School of Life Sciences, University of Science & Technology of China, 96 Jinzhai Road, Hefei, Anhui 230027, China.
BMC Bioinformatics. 2006 Oct 17;7:457. doi: 10.1186/1471-2105-7-457.
Recent progresses in high-throughput proteomics have provided us with a first chance to characterize protein interaction networks (PINs), but also raised new challenges in interpreting the accumulating data.
Motivated by the need of analyzing and interpreting the fast-growing data in the field of proteomics, we propose a comparative strategy to carry out global analysis of PINs. We compare two PINs by combining interaction topology and sequence similarity to identify conserved network substructures (CoNSs). Using this approach we perform twenty-one pairwise comparisons among the seven recently available PINs of E.coli, H.pylori, S.cerevisiae, C.elegans, D.melanogaster, M.musculus and H.sapiens. In spite of the incompleteness of data, PIN comparison discloses species conservation at the network level and the identified CoNSs are also functionally conserved and involve in basic cellular functions. We investigate the yeast CoNSs and find that many of them correspond to known complexes. We also find that different species harbor many conserved interaction regions that are topologically identical and these regions can constitute larger interaction regions that are topologically different but similar in framework. Based on the species-to-species difference in CoNSs, we infer potential species divergence. It seems that different species organize orthologs in similar but not necessarily the same topology to achieve similar or the same function. This attributes much to duplication and divergence of genes and their associated interactions. Finally, as the application of CoNSs, we predict 101 protein-protein interactions (PPIs), annotate 339 new protein functions and deduce 170 pairs of orthologs.
Our result demonstrates that the cross-species comparison strategy we adopt is powerful for the exploration of biological problems from the perspective of networks.
高通量蛋白质组学的最新进展为我们首次提供了描绘蛋白质相互作用网络（PINs）的机会，但也在解释不断积累的数据方面带来了新挑战。
受蛋白质组学领域分析和解释快速增长数据需求的推动，我们提出了一种比较策略来对PINs进行全局分析。我们通过结合相互作用拓扑结构和序列相似性来比较两个PINs，以识别保守的网络子结构（CoNSs）。使用这种方法，我们对大肠杆菌、幽门螺杆菌、酿酒酵母、秀丽隐杆线虫、黑腹果蝇、小家鼠和智人的七个最近可用的PINs进行了21次成对比较。尽管数据不完整，但PIN比较揭示了网络水平上的物种保守性，并且所识别的CoNSs在功能上也是保守的，且涉及基本细胞功能。我们研究了酵母CoNSs，发现其中许多对应于已知复合物。我们还发现不同物种含有许多拓扑结构相同的保守相互作用区域，这些区域可以构成拓扑结构不同但框架相似的更大相互作用区域。基于CoNSs中的物种间差异，我们推断了潜在的物种分化。似乎不同物种以相似但不一定相同的拓扑结构组织直系同源物以实现相似或相同的功能。这很大程度上归因于基因及其相关相互作用的复制和分化。最后，作为CoNSs的应用，我们预测了101种蛋白质-蛋白质相互作用（PPIs），注释了339种新的蛋白质功能，并推断出170对直系同源物。
我们的结果表明，我们采用的跨物种比较策略对于从网络角度探索生物学问题很强大。
