Libourel Igor G L, Shachar-Hill Yair
Department of Plant Biology, Michigan State University, East Lansing, Michigan 48824, USA.
Annu Rev Plant Biol. 2008;59:625-50. doi: 10.1146/annurev.arplant.58.032806.103822.
Metabolic flux analysis (MFA) is a rapidly developing field concerned with the quantification and understanding of metabolism at the systems level. The application of MFA has produced detailed maps of flow through metabolic networks of a range of plant systems. These maps represent detailed metabolic phenotypes, contribute significantly to our understanding of metabolism in plants, and have led to the discovery of new metabolic routes. The presentation of thorough statistical evaluation with current flux maps has set a new standard for the quality of quantitative flux studies. In microbial systems, powerful methods have been developed for the reconstruction of metabolic networks from genomic and transcriptomic data, pathway analysis, and predictive modeling. This review brings together the recent developments in quantitative MFA and predictive modeling. The application of predictive tools to high quality flux maps in particular promises to be important in the rational metabolic engineering of plants.
代谢通量分析(MFA)是一个快速发展的领域,致力于在系统层面量化和理解新陈代谢。MFA的应用已生成了一系列植物系统代谢网络的详细流量图。这些图代表了详细的代谢表型,极大地促进了我们对植物新陈代谢的理解,并促成了新代谢途径的发现。对当前通量图进行全面的统计评估,为定量通量研究的质量设定了新标准。在微生物系统中,已开发出强大的方法用于从基因组和转录组数据重建代谢网络、进行途径分析以及预测建模。本综述汇集了定量MFA和预测建模的最新进展。尤其是将预测工具应用于高质量通量图,有望在植物的合理代谢工程中发挥重要作用。