Department of Bioinformatics, School of Biology and Pharmacy, University of Jena, Ernst-Abbe-Pl. 2, D-07743 Jena, Germany.
Biochem Soc Trans. 2010 Oct;38(5):1202-5. doi: 10.1042/BST0381202.
Elementary-modes analysis has become a well-established theoretical tool in metabolic pathway analysis. It allows one to decompose complex metabolic networks into the smallest functional entities, which can be interpreted as biochemical pathways. This analysis has, in medium-size metabolic networks, led to the successful theoretical prediction of hitherto unknown pathways. For illustration, we discuss the example of the phosphoenolpyruvate-glyoxylate cycle in Escherichia coli. Elementary-modes analysis meets with the problem of combinatorial explosion in the number of pathways with increasing system size, which has hampered scaling it up to genome-wide models. We present a novel approach to overcoming this obstacle. That approach is based on elementary flux patterns, which are defined as sets of reactions representing the basic routes through a particular subsystem that are compatible with admissible fluxes in a (possibly) much larger metabolic network. The subsystem can be made up by reactions in which we are interested in, for example, reactions producing a certain metabolite. This allows one to predict novel metabolic pathways in genome-scale networks.
元模式分析已成为代谢途径分析中一种成熟的理论工具。它允许将复杂的代谢网络分解成最小的功能实体，可以将其解释为生化途径。在中等规模的代谢网络中，这种分析成功地预测了迄今未知的途径。例如，我们讨论大肠杆菌中磷酸烯醇丙酮酸-乙醛酸循环的例子。元模式分析在系统规模增加时遇到了途径数量的组合爆炸问题，这阻碍了将其扩展到全基因组模型。我们提出了一种克服这一障碍的新方法。该方法基于元流模式，它被定义为一组反应，代表与（可能）更大的代谢网络中允许通量相容的特定子系统的基本途径。子系统可以由我们感兴趣的反应组成，例如产生特定代谢物的反应。这允许在全基因组网络中预测新的代谢途径。
