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模型判别实验设计在发酵补料分批L-缬氨酸生产过程建模与开发中的应用。

Application of model discriminating experimental design for modeling and development of a fermentative fed-batch L-valine production process.

作者信息

Brik Ternbach Michel, Bollman Christian, Wandrey Christian, Takors Ralf

机构信息

Forschungszentrum Jülich, 52425 Jülich, Germany.

出版信息

Biotechnol Bioeng. 2005 Aug 5;91(3):356-68. doi: 10.1002/bit.20504.

Abstract

A model discriminating experimental design approach for fed-batch processes has been developed and applied to the fermentative production of L-valine by a genetically modified Corynebacterium glutamicum strain possessing multiple auxotrophies as an example. Being faced with the typical situation of uncertain model information based on preliminary experiments, model discriminating design was successfully applied to improve discrimination between five competing models. Within the same modeling and experimental design framework, also the planning of an optimized production process with respect to the total volumetric productivity is shown. Simulation results were experimentally affirmed, yielding an increased total volumetric productivity of 6.2 mM L-valine per hour. However, also so far unknown metabolic mechanisms were observed in the optimized process, underlining the importance of process optimization during modeling to avoid problems of extreme extrapolation of model predictions during the final process optimization.

摘要

已开发出一种用于补料分批过程的模型判别实验设计方法,并将其应用于以具有多种营养缺陷型的基因工程谷氨酸棒杆菌菌株发酵生产L-缬氨酸为例。面对基于初步实验的模型信息不确定的典型情况,模型判别设计成功应用于提高五个竞争模型之间的判别能力。在相同的建模和实验设计框架内,还展示了关于总体积生产率的优化生产过程规划。模拟结果得到了实验验证,使总体积生产率提高到每小时6.2 mM L-缬氨酸。然而,在优化过程中还观察到了迄今未知的代谢机制,这突出了建模过程中进行过程优化的重要性,以避免在最终过程优化期间模型预测过度外推的问题。

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