The topology of the bacterial co-conserved protein network and its implications for predicting protein function.
The topology of the bacterial co-conserved protein network and its implications for predicting protein function.
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DOI：
10.1186/1471-2164-9-313
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发表时间：
2008-06-30
期刊：
影响因子：
4.4
通讯作者：
Gill RT
中科院分区：
文献类型：
--
作者：
Karimpour-Fard A;Leach SM;Hunter LE;Gill RT
蛋白质-蛋白质相互作用网络通常由物理蛋白质-蛋白质相互作用数据生成。共保守，也称为系统发育谱，是生成蛋白质相互作用网络的另一种信息来源。共保守方法在蛋白质之间产生相互作用网络，这些蛋白质在进化过程中一起获得或失去。共保守是一种特别有用的技术，在紧凑的细菌基因组。先前在酵母中的研究表明，从物理相互作用测定产生的蛋白质-蛋白质相互作用网络的拓扑结构可以提供对蛋白质功能的重要见解。在这里，我们假设在细菌中，通过共保守信息推导出的蛋白质相互作用网络的拓扑结构可以类似地改善预测蛋白质功能的方法。由于细菌共保守蛋白质-蛋白质相互作用网络的拓扑结构以前没有被深入研究，我们首先在大肠杆菌中对共保守网络进行了这样的分析。coli K12。接下来，我们展示了一种方法，其中网络连接措施和全球和本地的功能分布可以被利用来预测蛋白质的功能，以前未知的蛋白质。我们的研究结果表明，像大多数生物网络一样，我们的细菌共保守蛋白质-蛋白质相互作用网络具有无标度拓扑结构。我们的研究结果表明，物理酵母相互作用网络的一些性质，保持在我们的细菌共保守网络，如必需蛋白质的高连通性。然而，在酵母物理网络中的蛋白质复合物之间的高连接性在使用所有细菌作为参考集的共保守网络中没有看到。我们发现，节点连接性的分布因功能类别而异，可以为功能预测提供信息。通过整合来自不同注释来源的功能信息并使用网络拓扑结构，我们能够推断未表征蛋白质的功能。基于共同保守的相互作用网络可以包含与基于物理或其他相互作用类型的网络不同的信息。我们的研究表明，基于共同保守的网络表现出无标度拓扑结构，正如生物网络所预期的那样。我们还揭示了我们网络中的连接性可以为蛋白质的功能表征提供信息的方式。
Protein-protein interactions networks are most often generated from physical protein-protein interaction data. Co-conservation, also known as phylogenetic profiles, is an alternative source of information for generating protein interaction networks. Co-conservation methods generate interaction networks among proteins that are gained or lost together through evolution. Co-conservation is a particularly useful technique in the compact bacteria genomes. Prior studies in yeast suggest that the topology of protein-protein interaction networks generated from physical interaction assays can offer important insight into protein function. Here, we hypothesize that in bacteria, the topology of protein interaction networks derived via co-conservation information could similarly improve methods for predicting protein function. Since the topology of bacteria co-conservation protein-protein interaction networks has not previously been studied in depth, we first perform such an analysis for co-conservation networks in E. coli K12. Next, we demonstrate one way in which network connectivity measures and global and local function distribution can be exploited to predict protein function for previously uncharacterized proteins. Our results showed, like most biological networks, our bacteria co-conserved protein-protein interaction networks had scale-free topologies. Our results indicated that some properties of the physical yeast interaction network hold in our bacteria co-conservation networks, such as high connectivity for essential proteins. However, the high connectivity among protein complexes in the yeast physical network was not seen in the co-conservation network which uses all bacteria as the reference set. We found that the distribution of node connectivity varied by functional category and could be informative for function prediction. By integrating of functional information from different annotation sources and using the network topology, we were able to infer function for uncharacterized proteins. Interactions networks based on co-conservation can contain information distinct from networks based on physical or other interaction types. Our study has shown co-conservation based networks to exhibit a scale free topology, as expected for biological networks. We also revealed ways that connectivity in our networks can be informative for the functional characterization of proteins.
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5.8
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