Comparative determination of biomass composition in differentially active metabolic States.
Comparative determination of biomass composition in differentially active metabolic States.
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不同活性代谢状态下生物质组成的比较测定。
DOI：
10.1142/9781848163003_0015
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Segrè,Daniel
中科院分区：
文献类型：
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作者：
Chiu,Hsuan-Chao;Segrè,Daniel
通量平衡分析(FBA)已被成功地应用于促进对模式生物中细胞代谢的了解。FBA的标准配方可以应用于大型系统，但预测的准确性可能会因环境条件、遗传扰动或复杂的未知监管限制而显著不同。在这里，我们提出了一种基于FBA的方法来推断最能描述细胞多种生理状态的生物量组成。具体地说，我们寻求使用实验数据(如通量测量或mRNA表达水平)来推断最佳匹配的化学计量平衡通量和代谢物汇。我们的算法是基于对两种代谢状态(例如野生型和基因敲除，或两个不同的时间点)的比较分析来提供预测，从而独立于可能的任意比例因子。我们使用野生型和基因缺失菌株的代谢流量的实验数据来测试我们的算法。除了展示我们的方法正确识别已知交换通量和生物量组成的能力外，我们还分析了大肠杆菌的中心碳代谢，以显示代谢目标的变化和对戊糖磷酸途径中单酶基因缺失导致的功率降低的潜在补偿。
Flux Balance Analysis (FBA) has been successfully applied to facilitate the understanding of cellular metabolism in model organisms. Standard formulations of FBA can be applied to large systems, but the accuracy of predictions may vary significantly depending on environmental conditions, genetic perturbations, or complex unknown regulatory constraints. Here we present an FBA-based approach to infer the biomass compositions that best describe multiple physiological states of a cell. Specifically, we seek to use experimental data (such as flux measurements, or mRNA expression levels) to infer best matching stoichiometrically balanced fluxes and metabolite sinks. Our algorithm is designed to provide predictions based on the comparative analysis of two metabolic states (eg wild-type and knockout, or two different time points), so as to be independent from possible arbitrary scaling factors. We test our algorithm using experimental data for metabolic fluxes in wild type and gene deletion strains of E. coli. In addition to demonstrating the capacity of our approach to correctly identify known exchange fluxes and biomass compositions, we analyze E. coli central carbon metabolism to show the changes of metabolic objectives and potential compensation for reducing power due to single enzyme gene deletion in pentose phosphate pathway.