Department of Chemical and Physical Sciences and Institute for Optical Sciences, University of Toronto at Mississauga, Mississauga, Ontario, Canada.
Biophys J. 2013 Jan 22;104(2):505-15. doi: 10.1016/j.bpj.2012.12.015.
Synthetic biology includes an effort to use design-based approaches to create novel controllers, biological systems aimed at regulating the output of other biological processes. The design of such controllers can be guided by results from control theory, including the strategy of integral feedback control, which is central to regulation, sensory adaptation, and long-term robustness. Realization of integral control in a synthetic network is an attractive prospect, but the nature of biochemical networks can make the implementation of even basic control structures challenging. Here we present a study of the general challenges and important constraints that will arise in efforts to engineer biological integral feedback controllers or to analyze existing natural systems. Constraints arise from the need to identify target output values that the combined process-plus-controller system can reach, and to ensure that the controller implements a good approximation of integral feedback control. These constraints depend on mild assumptions about the shape of input-output relationships in the biological components, and thus will apply to a variety of biochemical systems. We summarize our results as a set of variable constraints intended to provide guidance for the design or analysis of a working biological integral feedback controller.
合成生物学包括利用基于设计的方法来创建新型控制器的努力,这些生物系统旨在调节其他生物过程的输出。此类控制器的设计可以通过控制理论的结果来指导,包括积分反馈控制策略,这是调节、感官适应和长期鲁棒性的核心。在合成网络中实现积分控制是一个吸引人的前景,但生化网络的性质使得即使是基本控制结构的实现也具有挑战性。在这里,我们研究了在设计生物积分反馈控制器或分析现有自然系统时将出现的一般挑战和重要约束。约束源于需要确定组合过程加控制器系统可以达到的目标输出值,并确保控制器实现良好的积分反馈控制近似值。这些约束取决于对生物组成部分输入输出关系形状的一些温和假设,因此将适用于各种生化系统。我们将结果总结为一组变量约束,旨在为设计或分析工作的生物积分反馈控制器提供指导。