Forst Christian V, Flamm Christoph, Hofacker Ivo L, Stadler Peter F
Bioscience Division, Los Alamos National Laboratory, Mailstop M888, PO Box 1663, Los Alamos, NM 87545, USA.
BMC Bioinformatics. 2006 Feb 14;7:67. doi: 10.1186/1471-2105-7-67.
Comparison of metabolic networks is typically performed based on the organisms' enzyme contents. This approach disregards functional replacements as well as orthologies that are misannotated. Direct comparison of the structure of metabolic networks can circumvent these problems.
Metabolic networks are naturally represented as directed hypergraphs in such a way that metabolites are nodes and enzyme-catalyzed reactions form (hyper)edges. The familiar operations from set algebra (union, intersection, and difference) form a natural basis for both the pairwise comparison of networks and identification of distinct metabolic features of a set of algorithms. We report here on an implementation of this approach and its application to the procaryotes.
We demonstrate that metabolic networks contain valuable phylogenetic information by comparing phylogenies obtained from network comparisons with 16S RNA phylogenies. The algebraic approach to metabolic networks is suitable to study metabolic innovations in two sets of organisms, free living microbes and Pyrococci, as well as obligate intracellular pathogens.
代谢网络的比较通常基于生物体的酶含量进行。这种方法忽略了功能替代以及错误注释的直系同源物。代谢网络结构的直接比较可以规避这些问题。
代谢网络自然地表示为有向超图，其中代谢物是节点，酶催化反应形成（超）边。集合代数中常见的运算（并集、交集和差集）构成了网络成对比较和一组算法独特代谢特征识别的自然基础。我们在此报告这种方法的实现及其在原核生物中的应用。
通过将从网络比较中获得的系统发育与16S RNA系统发育进行比较，我们证明代谢网络包含有价值的系统发育信息。代谢网络的代数方法适用于研究两组生物体中的代谢创新，即自由生活的微生物和嗜热栖热菌，以及专性细胞内病原体。
