Evaluation of predicted network modules in yeast metabolism using NMR-based metabolite profiling
Evaluation of predicted network modules in yeast metabolism using NMR-based metabolite profiling
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DOI：
10.1101/gr.5662207
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发表时间：
2007-04-01
期刊：
影响因子：
7
通讯作者：
Brindle, Kevin M.
中科院分区：
文献类型：
--
作者：
Bundy, Jacob G.;Papp, Balazs;Brindle, Kevin M.
基因组尺度的代谢模型承诺了对细胞功能的重要见解。然而，在这些模型中以及一般的生化文献中，通路和功能网络模块的定义通常是基于直觉推理的。虽然已经提出了数学方法来识别模块，这些模块被定义为具有相关通量的反应组，但仍需要实验验证。我们在此表明，对酵母特定代谢途径中单基因缺失突变体的核磁共振衍生的细胞内和细胞外代谢物谱进行多元统计分析，发现了异常值，其谱与其他突变体在各自途径中的谱明显不同。对该酵母代谢模型的通量偶联分析表明，在一个外围突变体中缺失的基因编码了一种酶，该酶与该途径中其他酶不属于同一功能网络模块。我们建议，像这样的代谢组学方法，不需要任何关于基因缺失如何扰乱代谢网络的知识，为验证和最终完善预测的网络结构提供了一种经验方法。
Genome-scale metabolic models promise important insights into cell function. However, the definition of pathways and functional network modules within these models, and in the biochemical literature in general, is often based on intuitive reasoning. Although mathematical methods have been proposed to identify modules, which are defined as groups of reactions with correlated fluxes, there is a need for experimental verification. We show here that multivariate statistical analysis of the NMR-derived intra- and extracellular metabolite profiles of single-gene deletion mutants in specific metabolic pathways in the yeast Saccharomyces cerevisiae identified outliers whose profiles were markedly different from those of the other mutants in their respective pathways. Application of flux coupling analysis to a metabolic model of this yeast showed that the deleted gene in an outlying mutant encoded an enzyme that was not part of the same functional network module as the other enzymes in the pathway. We suggest that metabolomic methods such as this, which do not require any knowledge of how a gene deletion might perturb the metabolic network, provide an empirical method for validating and ultimately refining the predicted network structure.