De Paepe Brecht, Maertens Jo, Vanholme Bartel, De Mey Marjan
Centre for Synthetic Biology , Ghent University , Coupure Links 653 , B-9000 Ghent , Belgium.
Ghent University , Department of Plant Biotechnology and Bioinformatics , Technologiepark 927 , B-9052 Ghent , Belgium.
ACS Synth Biol. 2018 May 18;7(5):1303-1314. doi: 10.1021/acssynbio.7b00419. Epub 2018 May 4.
To monitor the intra- and extracellular environment of micro-organisms and to adapt their metabolic processes accordingly, scientists are reprogramming nature's myriad of transcriptional regulatory systems into transcriptional biosensors, which are able to detect small molecules and, in response, express specific output signals of choice. However, the naturally occurring response curve, the key characteristic of biosensor circuits, is typically not in line with the requirements for real-life biosensor applications. In this contribution, a natural LysR-type naringenin-responsive biosensor circuit is developed and characterized with Escherichia coli as host organism. Subsequently, this biosensor is dissected into a clearly defined detector and effector module without loss of functionality, and the influence of the expression levels of both modules on the biosensor response characteristics is investigated. Two collections of ten unique synthetic biosensors each are generated. Each collection demonstrates a unique diversity of response curve characteristics spanning a 128-fold change in dynamic and 2.5-fold change in operational ranges and 3-fold change in levels of Noise, fit for a wide range of applications, such as adaptive laboratory evolution, dynamic pathway control and high-throughput screening methods. The established biosensor engineering concepts, and the developed biosensor collections themselves, are of use for the future development and customization of biosensors in general, for the multitude of biosensor applications and as a compelling alternative for the commonly used LacI-, TetR- and AraC-based inducible circuits.
为了监测微生物的细胞内和细胞外环境,并相应地调整其代谢过程,科学家们正在将自然界无数的转录调控系统重新编程为转录生物传感器,这些传感器能够检测小分子,并相应地表达特定的输出信号。然而,生物传感器电路的关键特性——天然响应曲线,通常不符合实际生物传感器应用的要求。在本研究中,开发了一种天然的LysR型柚皮素响应生物传感器电路,并以大肠杆菌作为宿主进行了表征。随后,将该生物传感器分解为明确的检测器和效应器模块,且不损失功能,并研究了两个模块的表达水平对生物传感器响应特性的影响。生成了两个集合,每个集合包含十个独特的合成生物传感器。每个集合都展示了独特的响应曲线特征多样性,动态范围变化128倍,操作范围变化2.5倍,噪声水平变化3倍,适用于广泛的应用,如适应性实验室进化、动态途径控制和高通量筛选方法。所建立的生物传感器工程概念以及所开发的生物传感器集合本身,总体上对生物传感器的未来开发和定制、众多生物传感器应用均有用处,并且是常用的基于LacI、TetR和AraC的诱导电路的有力替代品。