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利用周期性震荡优化代谢产物的生成。

Optimizing metabolite production using periodic oscillations.

机构信息

Microbiology Graduate Program, University of Texas at Austin, Austin, Texas, United States of America.

McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas, United States of America.

出版信息

PLoS Comput Biol. 2014 Jun 5;10(6):e1003658. doi: 10.1371/journal.pcbi.1003658. eCollection 2014 Jun.

Abstract

Methods for improving microbial strains for metabolite production remain the subject of constant research. Traditionally, metabolic tuning has been mostly limited to knockouts or overexpression of pathway genes and regulators. In this paper, we establish a new method to control metabolism by inducing optimally tuned time-oscillations in the levels of selected clusters of enzymes, as an alternative strategy to increase the production of a desired metabolite. Using an established kinetic model of the central carbon metabolism of Escherichia coli, we formulate this concept as a dynamic optimization problem over an extended, but finite time horizon. Total production of a metabolite of interest (in this case, phosphoenolpyruvate, PEP) is established as the objective function and time-varying concentrations of the cellular enzymes are used as decision variables. We observe that by varying, in an optimal fashion, levels of key enzymes in time, PEP production increases significantly compared to the unoptimized system. We demonstrate that oscillations can improve metabolic output in experimentally feasible synthetic circuits.

摘要

改善微生物菌株以生产代谢物的方法仍然是不断研究的主题。传统上,代谢调控主要局限于敲除或过表达途径基因和调控因子。在本文中,我们建立了一种通过诱导选定酶簇的最佳调谐时间波动来控制代谢的新方法,作为增加所需代谢物产量的替代策略。我们使用大肠杆菌中心碳代谢的已建立动力学模型,将这一概念表述为在扩展但有限的时间范围内的动态优化问题。感兴趣的代谢物(在这种情况下为磷酸烯醇丙酮酸,PEP)的总产量被确定为目标函数,细胞酶的时变浓度被用作决策变量。我们观察到,通过以最佳方式随时间改变关键酶的水平,与未优化系统相比,PEP 的产量显著增加。我们证明,在实验上可行的合成回路中,振荡可以提高代谢产物的输出。

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