Department of Chemical & Biological Engineering and Advanced Biomanufacturing Centre, The University of Sheffield, Sir Robert Hadfield Building, Mappin Street, Sheffield S1 3JD, United Kingdom.
Department of Chemical, Biochemical and Environmental Engineering, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, United States.
Metab Eng. 2017 Nov;44:253-264. doi: 10.1016/j.ymben.2017.10.011. Epub 2017 Oct 31.
Malonyl-CoA is the basic building block for synthesizing a range of important compounds including fatty acids, phenylpropanoids, flavonoids and non-ribosomal polyketides. Centering around malonyl-CoA, we summarized here the various metabolic engineering strategies employed recently to regulate and control malonyl-CoA metabolism and improve cellular productivity. Effective metabolic engineering of microorganisms requires the introduction of heterologous pathways and dynamically rerouting metabolic flux towards products of interest. Transcriptional factor-based biosensors translate an internal cellular signal to a transcriptional output and drive the expression of the designed genetic/biomolecular circuits to compensate the activity loss of the engineered biosystem. Recent development of genetically-encoded malonyl-CoA sensor has stood out as a classical example to dynamically reprogram cell metabolism for various biotechnological applications. Here, we reviewed the design principles of constructing a transcriptional factor-based malonyl-CoA sensor with superior detection limit, high sensitivity and broad dynamic range. We discussed various synthetic biology strategies to remove pathway bottleneck and how genetically-encoded metabolite sensor could be deployed to improve pathway efficiency. Particularly, we emphasized that integration of malonyl-CoA sensing capability with biocatalytic function would be critical to engineer efficient microbial cell factory. Biosensors have also advanced beyond its classical function of a sensor actuator for in situ monitoring of intracellular metabolite concentration. Applications of malonyl-CoA biosensors as a sensor-invertor for negative feedback regulation of metabolic flux, a metabolic switch for oscillatory balancing of malonyl-CoA sink pathway and source pathway and a screening tool for engineering more efficient biocatalyst are also presented in this review. We envision the genetically-encoded malonyl-CoA sensor will be an indispensable tool to optimize cell metabolism and cost-competitively manufacture malonyl-CoA-derived compounds.
丙二酰辅酶 A 是合成一系列重要化合物的基本结构单元，包括脂肪酸、苯丙烷类、类黄酮和非核糖体聚酮化合物。以丙二酰辅酶 A 为中心，我们总结了最近用于调节和控制丙二酰辅酶 A 代谢和提高细胞生产力的各种代谢工程策略。有效代谢工程化微生物需要引入异源途径，并动态重新路由代谢通量以产生目标产物。基于转录因子的生物传感器将内部细胞信号转化为转录输出，并驱动设计的遗传/生物分子回路的表达，以补偿工程生物系统的活性损失。最近开发的遗传编码丙二酰辅酶 A 传感器作为一个经典的例子，突出了用于各种生物技术应用的动态重新编程细胞代谢的方法。在这里，我们综述了构建基于转录因子的丙二酰辅酶 A 传感器的设计原则，该传感器具有卓越的检测限、高灵敏度和宽动态范围。我们讨论了各种合成生物学策略来消除途径瓶颈，以及如何部署遗传编码代谢物传感器来提高途径效率。特别是，我们强调了将丙二酰辅酶 A 传感能力与生物催化功能集成对于工程高效微生物细胞工厂至关重要。生物传感器的应用已经超越了其作为原位监测细胞内代谢物浓度的传感器执行器的经典功能。本文还介绍了丙二酰辅酶 A 生物传感器作为代谢通量负反馈调节的传感器 - 反向器、丙二酰辅酶 A 汇途径和源途径的振荡平衡代谢开关以及用于工程更高效生物催化剂的筛选工具的应用。我们设想遗传编码的丙二酰辅酶 A 传感器将成为优化细胞代谢和具有成本竞争力地制造丙二酰辅酶 A 衍生化合物的不可或缺的工具。
