Dataset Information

Programmable biomolecular switches for rewiring flux in Escherichia coli.

ABSTRACT: Synthetic biology aims to develop programmable tools to perform complex functions such as redistributing metabolic flux in industrial microorganisms. However, development of protein-level circuits is limited by availability of designable, orthogonal, and composable tools. Here, with the aid of engineered viral proteases and proteolytic signals, we build two sets of controllable protein units, which can be rationally configured to three tools. Using a protease-based dynamic regulation circuit to fine-tune metabolic flow, we achieve 12.63?g?L-1 shikimate titer in minimal medium without inducer. In addition, the carbon catabolite repression is alleviated by protease-based inverter-mediated flux redistribution under multiple carbon sources. By coordinating reaction rate using a protease-based oscillator in E. coli, we achieve D-xylonate productivity of 7.12?g?L-1?h-1 with a titer of 199.44?g?L-1. These results highlight the applicability of programmable protein switches to metabolic engineering for valuable chemicals production.

SUBMITTER: Gao C

PROVIDER: S-EPMC6704175 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Programmable biomolecular switches for rewiring flux in Escherichia coli.

Gao Cong C Hou Jianshen J Xu Peng P Xu Peng P Guo Liang L Chen Xiulai X Hu Guipeng G Ye Chao C Edwards Harley H Chen Jian J Chen Wei W Liu Liming L

Nature communications 20190821 1

Synthetic biology aims to develop programmable tools to perform complex functions such as redistributing metabolic flux in industrial microorganisms. However, development of protein-level circuits is limited by availability of designable, orthogonal, and composable tools. Here, with the aid of engineered viral proteases and proteolytic signals, we build two sets of controllable protein units, which can be rationally configured to three tools. Using a protease-based dynamic regulation circuit to ...[more]

PMID: 31434894

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Project description:BackgroundMetabolic responses are essential for the adaptation of microorganisms to changing environmental conditions. The repertoire of flux responses that the metabolic network can display in different external conditions may be quantified applying flux variability analysis to genome-scale metabolic reconstructions.ResultsA procedure is developed to classify and quantify the sources of flux variability. We apply the procedure to the latest Escherichia coli metabolic reconstruction, in glucose minimal medium, with an additional constraint to account for the mechanism coordinating carbon and nitrogen utilization mediated by α-ketoglutarate. Flux variability can be decomposed into three components: internal, external and growth variability. Unexpectedly, growth variability is the only significant component of flux variability in the physiological ranges of glucose, oxygen and ammonia uptake rates. To obtain substantial increases in metabolic flexibility, E. coli must decrease growth rate to suboptimal values. This growth-flexibility trade-off gives a straightforward interpretation to recent work showing that most overall cell-to-cell flux variability in a population of E. coli can be attained sampling a small number of enzymes most likely to constrain cell growth. Importantly, it provides an explanation for the global reorganization occurring in metabolic networks during adaptations to environmental challenges. The calculations were repeated with a pathogenic strain and an old reconstruction of the commensal strain, having less than 50% of the reactions of the latest reconstruction, obtaining the same general conclusions.ConclusionsIn E. coli growing on glucose, growth variability is the only significant component of flux variability for all physiological conditions explored. Increasing flux variability requires reducing growth to suboptimal values. The growth-flexibility trade-off operates in physiological and evolutionary adaptations, and provides an explanation for the global reorganization occurring during adaptations to environmental challenges. The results obtained do not rely on the knowledge of kinetic and regulatory details of the system and are highly robust to incomplete or incorrect knowledge of the reaction network.

Dataset Information

Programmable biomolecular switches for rewiring flux in Escherichia coli.

Publications

Programmable biomolecular switches for rewiring flux in Escherichia coli.

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