The connectivity structure, giant strong component and centrality of metabolic networks
The connectivity structure, giant strong component and centrality of metabolic networks
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DOI：
10.1093/bioinformatics/btg177
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发表时间：
2003-07-22
期刊：
影响因子：
5.8
通讯作者：
Zeng, AP
中科院分区：
文献类型：
--
作者：
Ma, HW;Zeng, AP
动机：基于基因组的大规模代谢网络的结构和功能分析对于从系统水平理解代谢的设计原理和调控具有重要意义。代谢网络通常被认为是高度集成的，非常复杂。一个合理的减少代谢网络的核心结构和更深入地了解其功能模块是important.Results：在这项工作中，我们表明，代谢网络中的代谢物是远远没有完全连接。在65个完全测序的生物体的代谢网络中发现了一个由4个主要的代谢物和反应子集组成的连接结构，即一个完全连接的子网络、一个底物子集、一个产物子集和一个孤立子集。代谢网络中最大的全连通部分称为“巨强连通部分”（GSC），是网络中最复杂的部分，也是网络的核心，具有无标度网络的特征。整个网络的平均路径长度主要取决于GSC的平均路径长度。对于大多数生物体，GSC通常包含不到三分之一的网络节点。这种连接结构与万维网的“蝴蝶结”结构非常相似。我们的结果表明，蝴蝶结结构可能是常见的大规模有向网络。更重要的是，未被发现的结构特征使得大规模代谢网络的结构和功能分析更容易进行。如这项工作所示，比较GSC中节点的接近中心性可以识别代谢网络中最中心的代谢物。为了定量描述GSC的整体连接结构，我们引入了术语“整体紧密集中度指数（OCCI）”。OCCI与GSC的平均路径长度很好地相关，并且是用于不同生物体的代谢网络的系统级比较的有用参数。
Motivation: Structural and functional analysis of genome-based large-scale metabolic networks is important for understanding the design principles and regulation of the metabolism at a system level. The metabolic network is conventionally considered to be highly integrated and very complex. A rational reduction of the metabolic network to its core structure and a deeper understanding of its functional modules are important.Results: In this work, we show that the metabolites in a metabolic network are far from fully connected. A connectivity structure consisting of four major subsets of metabolites and reactions, i.e. a fully connected sub-network, a substrate subset, a product subset and an isolated subset is found to exist in metabolic networks of 65 fully sequenced organisms. The largest fully connected part of a metabolic network, called 'the giant strong component (GSC)', represents the most complicated part and the core of the network and has the feature of scale-free networks. The average path length of the whole network is primarily determined by that of the GSC. For most of the organisms, GSC normally contains less than one-third of the nodes of the network. This connectivity structure is very similar to the 'bow-tie' structure of World Wide Web. Our results indicate that the bow-tie structure may be common for large-scale directed networks. More importantly, the uncovered structure feature makes a structural and functional analysis of large-scale metabolic network more amenable. As shown in this work, comparing the closeness centrality of the nodes in the GSC can identify the most central metabolites of a metabolic network. To quantitatively characterize the overall connection structure of the GSC we introduced the term 'overall closeness centralization index (OCCI)'. OCCI correlates well with the average path length of the GSC and is a useful parameter for a system-level comparison of metabolic networks of different organisms.