DMFA-based operation model for fermentation processes

被引:4
作者
Gao, Yan [1 ]
Zhao, Zhonggai [1 ]
Liu, Fei [1 ]
机构
[1] Jiangnan Univ, Minist Educ, Key Lab Adv Proc Control Light Ind, Wuxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Dynamic metabolic flux analysis; Operation model; Macro-micro mapping; Multi-model modeling; Fermentation process; METABOLIC FLUX DISTRIBUTIONS; PENICILLIUM-CHRYSOGENUM; REGRESSION; GROWTH; NETWORKS; IDENTIFICATION; SELECTION; SYSTEM; EM;
D O I
10.1016/j.compchemeng.2017.11.008
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The existing dynamical fermentation models only reveal approximate macroscopic properties involving no internal mechanism, while dynamic metabolic flux analysis (DMFA) provides internal microscopic dynamic features, but without regulation from external operation conditions. This is the first attempt to bridge the mapping between macro operation variables and micro metabolic fluxes. Based on the macro-micro mapping relationship, a new operation model was constructed, which can use macro operation variables to regulate micro metabolic fluxes. Firstly, metabolic network was analyzed based on DMFA to derive flux distribution. Next, the fluxes defined as outputs were related to macro operation variables to establish the operation model. The complexity of cellular growth and diversity of flux distribution led to nonlinear and multi-stage characteristics of the mapping relationship, and thus a multi-model modeling method was employed as key algorithm. Finally, a simulation and a lab-scale experiment were conducted to demonstrate the application of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:138 / 150
页数:13
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