Stoney Ruth A, Ames Ryan M, Nenadic Goran, Robertson David L, Schwartz Jean-Marc
BMC Syst Biol. 2015;9 Suppl 6(Suppl 6):S3. doi: 10.1186/1752-0509-9-S6-S3. Epub 2015 Dec 9.
Biological processes at the molecular level are usually represented by molecular interaction networks. Function is organised and modularity identified based on network topology, however, this approach often fails to account for the dynamic and multifunctional nature of molecular components. For example, a molecule engaging in spatially or temporally independent functions may be inappropriately clustered into a single functional module. To capture biologically meaningful sets of interacting molecules, we use experimentally defined pathways as spatial/temporal units of molecular activity.
We defined functional profiles of Saccharomyces cerevisiae based on a minimal set of Gene Ontology terms sufficient to represent each pathway's genes. The Gene Ontology terms were used to annotate 271 pathways, accounting for pathway multi-functionality and gene pleiotropy. Pathways were then arranged into a network, linked by shared functionality. Of the genes in our data set, 44% appeared in multiple pathways performing a diverse set of functions. Linking pathways by overlapping functionality revealed a modular network with energy metabolism forming a sparse centre, surrounded by several denser clusters comprised of regulatory and metabolic pathways. Signalling pathways formed a relatively discrete cluster connected to the centre of the network. Genetic interactions were enriched within the clusters of pathways by a factor of 5.5, confirming the organisation of our pathway network is biologically significant.
Our representation of molecular function according to pathway relationships enables analysis of gene/protein activity in the context of specific functional roles, as an alternative to typical molecule-centric graph-based methods. The pathway network demonstrates the cooperation of multiple pathways to perform biological processes and organises pathways into functionally related clusters with interdependent outcomes.
分子水平的生物学过程通常由分子相互作用网络表示。基于网络拓扑结构来组织功能并识别模块性,然而,这种方法常常无法考虑分子成分的动态和多功能性质。例如,参与空间或时间上独立功能的分子可能会被不恰当地聚类到单个功能模块中。为了捕获具有生物学意义的相互作用分子集,我们使用实验定义的途径作为分子活性的空间/时间单位。
我们基于足以代表每个途径基因的最小基因本体术语集定义了酿酒酵母的功能概况。基因本体术语用于注释271条途径,考虑到途径的多功能性和基因的多效性。然后将途径排列成一个网络,通过共享功能相连。在我们的数据集中,44%的基因出现在执行多种不同功能的多个途径中。通过重叠功能连接途径揭示了一个模块化网络,其中能量代谢形成一个稀疏的中心,周围是由调节和代谢途径组成的几个更密集的簇。信号传导途径形成一个相对离散的簇,与网络中心相连。遗传相互作用在途径簇中的富集倍数为5.5,证实了我们的途径网络的组织具有生物学意义。
我们根据途径关系对分子功能的表示能够在特定功能角色的背景下分析基因/蛋白质活性,作为典型的以分子为中心的基于图的方法的替代方法。途径网络展示了多种途径合作执行生物学过程,并将途径组织成具有相互依赖结果的功能相关簇。