Determining the transport mechanism of an enzyme-catalytic complex metabolic network based on biological robustness

Wang, Lei

doi:10.1007/s00449-012-0800-7

Cited by 28 publications

(15 citation statements)

References 26 publications

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“…Clearly, (11) measures the rate at which the process yield changes in response to small changes in the model parameters. Thus, a low value for system sensitivity indicates that the system is robust.…”

Section: Optimal Control Versus Robust Control: a Trade-offmentioning

confidence: 99%

“…An experimental investigation into the multiple inhibitions of the fermentation process is given in [8], and studies based on metabolic flux and metabolic pathway analysis are given in [9][10][11][12][13]. Mathematical models of the microbial conversion process, together with various process control strategies, have been considered in [14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

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Robust Optimal Control of a Microbial Batch Culture Process

Cheng

Wang

Loxton

et al. 2014

J Optim Theory Appl

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This paper considers the microbial batch culture process for producing 1,3-propanediol (1,3-PD) via glycerol fermentation. Our goal was to design an optimal control scheme for this process, with the aim of balancing two (perhaps competing) objectives: (i) the process should yield a sufficiently high concentration of 1,3-PD at the terminal time and (ii) the process should be robust with respect to changes in various uncertain system parameters. Accordingly, we pose an optimal control problem, in which both process yield and process sensitivity are considered in the objective function. The control variables in this problem are the terminal time of the batch culture process and the initial concentrations of biomass and glycerol in the batch reactor. By performing a time-scaling transformation and introducing an auxiliary dynamic system to calculate process sensitivity, we obtain an equivalent optimal control problem Communicated by Mimmo Iannelli. 123J Optim Theory Appl in standard form. We then develop a particle swarm optimization algorithm for solving this equivalent problem. Finally, we explore the trade-off between process efficiency and process robustness via numerical simulations.

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Section: Optimal Control Versus Robust Control: a Trade-offmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Optimal Control of a Microbial Batch Culture Process

Cheng

Wang

Loxton

et al. 2014

J Optim Theory Appl

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“…Up to 2008, the intracellular dynamics of this bioprocess was firstly studied by Sun et al [11]. Thereafter, we introduced several quantitative measures of biological robustness to estimate the kinetic parameters of Sun's model in the context where the intracellular data were limited and some of the metabolic mechanisms were 2 Mathematical Problems in Engineering not completely known [12][13][14]. The problem is that huge computing workload will be faced in the evaluation of the biological robustness index, even though the scale of the metabolic network is not too large.…”

Section: Introductionmentioning

confidence: 99%

Dynamics Analysis and Prediction of Genetic Regulation in Glycerol Metabolic Network via Structural Kinetic Modelling

Huang

et al. 2015

Mathematical Problems in Engineering

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Glycerol can be biologically converted to 1,3-propanediol (1,3-PD) byKlebsiella pneumoniae. In the synthesis pathway of 1,3-PD, the accumulation of an intermediary metabolite 3-hydroxypropionaldehyde (3-HPA) would cause an irreversible cessation of the dynamic system. Genetic manipulation on the key enzymes which control the formation rate and consumption rate of 3-HPA would decrease the accumulation of 3-HPA, resulting in nonlinear regulation on the dynamic system. The interest of this work is to focus on analyzing the influence of 3-HPA inhibition on the stability of the dynamic system. Due to the lack of intracellular knowledge, structural kinetic modelling is applied. On the basis of statistical account of the dynamical capabilities of the system in the parameter space, we conclude that, under weak or no inhibition to the reaction of 3-HPA consumption, the system is much easier to obtain a stable state, whereas strong inhibition to its formation is in favor of stabilizing the system. In addition, the existence of Hopf bifurcation in this system is also verified. The obtained results are helpful for deeply understanding the metabolic and genetic regulations of glycerol fermentation byKlebsiella pneumoniae.

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“…The methods of glycerol bioconversion to 1,3-PD consist of batch, continuous [9] and fed-batch [10,11] cultures, among which glycerol fermentation in batch culture can obtain the highest production concentration and molar yield 1,3-PD to glycerol [12]. So the nonlinear dynamical systems in this culture have been extensively studied in recent years in its modelling with a view to facilitate its design, control and optimization [13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%