期刊
METABOLIC ENGINEERING
卷 54, 期 -, 页码 109-116出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ymben.2019.03.009
关键词
Genetic circuits; Metabolic engineering; Dynamic population control; Growth fitness; Synthetic biology
资金
- Cellular & Biochem Engineering Program of the National Science Foundation [1805139]
- Department of Chemical, Biochemical and Environmental Engineering at University of Maryland Baltimore County
- China Scholarship Council
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [1805139] Funding Source: National Science Foundation
Metabolic engineering entails target modification of cell metabolism to maximize cell's production potential. Due to the complexity of cell metabolism, feedback genetic circuits have emerged as basic tools to combat metabolic heterogeneity, enhance microbial cooperation as well as boost cell's productivity. This is generally achieved by applying social reward-punishment rules to eliminate cheaters and reward winners in a mixed cell population. With metabolite-responsive transcriptional factors to rewire gene expression, metabolic engineers are well-positioned to integrate feedback genetic circuits with growth fitness and achieve dynamic population control. Towards this goal, we argue that feedback genetic circuits and microbial interactions will be a golden mine for future metabolic engineering. We will summarize the design principles of engineering burden-driven feedback control to combat metabolic stress, implementing population quality control to eliminate cheater cell, applying product addiction to reward productive cell, as well as layering dual dynamic regulation to decouple cell growth from product formation. Collectively, these strategies will be useful to improve community-level cellular performance. Encoding such decision-marking functions and reprogramming cellular logics at population level will enable metabolic engineers to deliver robust cell factories and pave the way for intelligent bioproduction. We envision that various cellular regulation mechanisms and genetic/metabolic circuits could be exploited to achieve self-adaptive or autonomous metabolic function for diverse biotechnological and medical applications. Applying these design rules may offer us a genetic solution beyond bioprocess engineering strategies to further improve the cost-competitiveness of industrial fermentation.
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