Metabolic flux analysis in a nonstationary system:: Fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol
Metabolic flux analysis in a nonstationary system:: Fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol
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DOI：
10.1016/j.ymben.2007.01.003
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发表时间：
2007-05-01
影响因子：
8.4
通讯作者：
Stephanopoulos, Gregory
中科院分区：
文献类型：
--
作者：
Antoniewicz, Maciek R.;Kraynie, David F.;Stephanopoulos, Gregory
从稳定 - 同位素研究中估计的代谢通量为理解细胞生理和代谢的调节提供了关键。代谢通量分析（MFA）的经典方法的局限性是同位素稳态的要求。为了将通量确定的范围从固定系统扩展到非组织系统，我们提出了一种新型的建模策略，该策略结合了同位素光谱分析（ISA）和固定MFA的关键思想。前体池和采样产物的同位素瞬变分别通过两个参数D和G参数描述，这些参数被整合到通量模型中。 g值是样品中标记的产品的比例，d值是饲料生产标记产品的分数贡献。我们用非机构系统与工业生产条件相似的非机构系统说明了新型的建模策略，即产生1,3-丙二醇（PDO）的大肠杆菌的饲料批次发酵。代谢通量和D和G参数是通过拟合通过GC/MS测量的生物量氨基酸的标记分布与E大肠杆菌代谢模型估算的。我们从数据中获得了高度一致的拟合，并具有82个冗余测量值。在发酵过程中，估计代谢通量为20个时间点。因此，我们首次建立了体内通量的详细时间概况。我们发现，在饲料批处理期间，细胞内通量发生了显着变化。与PDO途径相关的细胞内通量增加了10％。同时，我们观察到糖酵解和五磷酸五磷酸五磷酸五磷酸途径的分裂比从70/30到50150的降低。另一方面，TCA循环通量在整个发酵过程中保持恒定。此外，我们的通量结果为支持该生物体的假定基因型提供了更多的见解。 （c）2007 Elsevier Inc.保留所有权利。
Metabolic fluxes estimated from stable-isotope studies provide a key to understanding cell physiology and regulation of metabolism. A limitation of the classical method for metabolic flux analysis (MFA) is the requirement for isotopic steady state. To extend the scope of flux determination from stationary to nonstationary systems, we present a novel modeling strategy that combines key ideas from isotopomer spectral analysis (ISA) and stationary MFA. Isotopic transients of the precursor pool and the sampled products are described by two parameters, D and G parameters, respectively, which are incorporated into the flux model. The G value is the fraction of labeled product in the sample, and the D value is the fractional contribution of the feed for the production of labeled products. We illustrate the novel modeling strategy with a nonstationary system that closely resembles industrial production conditions, i.e. fed-batch fermentation of Escherichia coli that produces 1,3-propanediol (PDO). Metabolic fluxes and the D and G parameters were estimated by fitting labeling distributions of biomass amino acids measured by GC/MS to a model of E coli metabolism. We obtained highly consistent fits from the data with 82 redundant measurements. Metabolic fluxes were estimated for 20 time points during course of the fermentation. As such we established, for the first time, detailed time profiles of in vivo fluxes. We found that intracellular fluxes changed significantly during the fed-batch. The intracellular flux associated with PDO pathway increased by 10%. Concurrently, we observed a decrease in the split ratio between glycolysis and pentose phosphate pathway from 70/30 to 50150 as a function of time. The TCA cycle flux, on the other hand, remained constant throughout the fermentation. Furthermore, our flux results provided additional insight in support of the assumed genotype of the organism. (c) 2007 Elsevier Inc. All rights reserved.