IEEE/ACM Trans Comput Biol Bioinform. 2019 Mar-Apr;16(2):583-595. doi: 10.1109/TCBB.2017.2771775. Epub 2018 Jan 11.
Synthetic Biologists are increasingly interested in the idea of using synthetic feedback control circuits for the mitigation of perturbations to gene regulatory networks that may arise due to disease and/or environmental disturbances. Models employing Michaelis-Menten kinetics with Hill-type nonlinearities are typically used to represent the dynamics of gene regulatory networks. Here, we identify some fundamental problems with such models from the point of view of control system design, and argue that an alternative formalism, based on so-called S-System models, is more suitable. Using tools from system identification, we show how to build S-System models that capture the key dynamics of an example gene regulatory network, and design a genetic feedback controller with the objective of rejecting an external perturbation. Using a sine sweeping method, we show how the S-System model can be approximated by a linear transfer function and, based on this transfer function, we design our controller. Simulation results using the full nonlinear S-System model of the network show that the synthetic control circuit is able to mitigate the effect of external perturbations. Our study is the first to highlight the usefulness of the S-System modelling formalism for the design of synthetic control circuits for gene regulatory networks.
合成生物学家越来越感兴趣的是使用合成反馈控制电路来减轻由于疾病和/或环境干扰而可能对基因调控网络产生的干扰。采用米氏动力学和 Hill 型非线性的模型通常用于表示基因调控网络的动态。在这里，我们从控制系统设计的角度出发，指出了这些模型的一些基本问题，并认为基于所谓的 S 系统模型的替代形式更为合适。我们使用系统辨识工具，展示了如何构建能够捕捉示例基因调控网络关键动态的 S 系统模型，并设计了具有拒绝外部干扰目标的遗传反馈控制器。我们使用正弦扫描方法，展示了如何通过线性传递函数来逼近 S 系统模型，并基于此传递函数来设计我们的控制器。使用网络的完整非线性 S 系统模型进行的仿真结果表明，合成控制电路能够减轻外部干扰的影响。我们的研究首次强调了 S 系统建模形式对于设计基因调控网络合成控制电路的有用性。
