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首页> 外文期刊>Biotechnology Progress >The Identification of Enzyme Targets for the Optimization of a Valine Producing Corynebacterium glutamicum Strain Using a Kinetic Model
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The Identification of Enzyme Targets for the Optimization of a Valine Producing Corynebacterium glutamicum Strain Using a Kinetic Model

机译：使用动力学模型鉴定用于优化缬氨酸生产谷氨酸棒杆菌菌株的酶靶标

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摘要

The enzyme targets for the rational optimization of a Corynebacterium glutamicum strain constructed for valine production are identified by analyzing the control of flux in the valine! leucine pathway. The control analysis is based on measurements of the intracellular metabolite concentrations and on a kinetic model of the reactions in the investigated pathway. Data-driven and model-based methods are used and evaluated against each other. The approach taken gives a quantitative evaluation of the flux control and it is demonstrated how the understanding of flux control is used to reach specific recommendations for strain optimization. The flux control coefficients (FCCs) with respect to the valine excretion rate were calculated,and it was found that the control is distributed mainly between the acetohydroxyacid synthase enzyme (FCC = 0.32),the branched chain amino acid transaminase (FCC = 027),and the exporting translo-case (FCC = 0.43). The availability of the precursor pyruvate has substantial influence on the valine flux,whereas the cometabolites are less important as demonstrated by the calculation of the respective response coefficients. The model is further used to make in-silico predictions of the change in valine flux following a change in enzyme level. A doubling of the enzyme level of valine translocase will result in an increase in valine flux of 31%. By optimizing the enzyme levels with respect to valine flux it was found that the valine flux can be increased by a factor 2.5 when the optimal enzyme levels are implemented.
机译：通过分析缬氨酸中通量的控制，确定合理优化用于缬氨酸生产的谷氨酸棒杆菌菌株的酶靶标！亮氨酸途径。对照分析基于细胞内代谢物浓度的测量以及所研究途径中反应的动力学模型。数据驱动和基于模型的方法相互使用并进行评估。所采用的方法对磁通量控制进行了定量评估，并演示了如何使用对磁通量控制的理解来获得应变优化的特定建议。计算了相对于缬氨酸排泄率的通量控制系数（FCCs），发现控制主要分布在乙酰羟酸合酶（FCC = 0.32）和支链氨基酸转氨酶（FCC = 027）之间，以及导出的横案（FCC = 0.43）。丙酮酸前体的可利用性对缬氨酸通量有很大的影响，而如相应的响应系数的计算所证明的那样，代谢产物的重要性就不那么重要了。该模型还可用于对酶水平变化后缬氨酸通量的变化进行计算机内预测。缬氨酸转位酶的酶水平加倍将导致缬氨酸通量增加31％。通过优化关于缬氨酸通量的酶水平，发现当实施最佳酶水平时，缬氨酸通量可以增加2.5倍。

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