摘要
揭示工程化设计的人工合成途径与底盘细胞整体代谢网络的交互作用及适配性机制是合成生物学研究的关键共性科学问题。细胞内酰基CoA是微生物合成生物活性物质如聚酮、芪类及黄酮类、生物碱、生物能源及生物材料等的前体,提高细胞内酰基CoA供应水平,能够促进微生物合成产率升高;酰基CoA也是蛋白质酰基化修饰的酰基基团供体,酰基CoA积累导致合成代谢途径相关酶的酰基化水平提高,抑制代谢酶催化活性及合成效率。本文从酰基CoA平衡及酰基化修饰的角度,重点阐述了酰基CoA双重效应(酰基化供体及代谢前体)的相互影响与平衡,随后通过红霉素、丁醇、赤松素的实例总结了翻译后修饰代谢工程在调节微生物合成途径各元件间、合成途径与底盘之间的适配性,促进产物合成方面的实际应用。
The complexity of chassis cell influences the effectiveness of synthetic constructs and resource allocation.The effect of regulatory systems on the engineered biosynthetic pathways in microorganisms remains incompletely understood.Acyl-CoAs function as key precursors for the biosynthesis of various natural products as well as the dominant donors for protein acylation.Increasing supply of acyl-CoAs contributes to the increased yield,while oversupply also leads to an increase in the global acylation level thereby decreasing the biosynthesis of natural products.Here we provide an overview of the host-construct interactions in the view of the intricate balance of cellular concentrations for acyl-CoAs and the yields of acyl-CoAs-derived products.In particular,we highlight the application of post-translational modification metabolic engineering(PTM-ME)on the biosynthesis of erythromycin,butanol and pinosylvin biosynthesis via raising acyl-CoAs supply,and in the same time bypassing the feedback inhibition caused by acylation.In conclusion,the system-level understanding of PTM with proteins offers a conceptual and technological framework for creating new metabolic enzymes/pathways to optimize the optimal production of desired products.
作者
尤迪
叶邦策
YOU Di;YE Bangce(Laboratory of Biosystems and Microanalysis,State Key Laboratory of Bioreactor Engineering,East China University of Science and Technology,Shanghai 200237,China;Institute of Engineering Biology and Health,Collaborative Innovation Center of Yangtze River Delta Region Green Pharmaceuticals,College of Pharmaceutical Sciences,Zhejiang University of Technology,Hangzhou 310014,Zhejiang,China)
出处
《合成生物学》
2020年第2期212-225,共14页
Synthetic Biology Journal
基金
国家自然科学基金(31730004和31700058)
国家重点研发计划“合成生物学”重点专项(2018YFA0900404)。