Abstract
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.
Highlights
In complex engineering networks such as transportation systems, power grids, irrigation networks, etc, the presence of external perturbations can have serious adverse effects on the functioning of the overall system
Several modelling formalisms are available for the representation of gene regulatory networks, the question of their suitability for the design of synthetic feedback control systems has so far received little attention in the literature
We propose the use of the S-System modelling formalism
Summary
In complex engineering networks such as transportation systems, power grids, irrigation networks, etc, the presence of external perturbations can have serious adverse effects on the functioning of the overall system. These undesirable effects include gridlock in the movement of vehicles, major power outages in residential and industrial areas, and unreliable water supply to farming areas. The ability to control the dynamics of gene regulatory networks using feedback, especially in the presence of perturbations, has many potential applications in the field of synthetic biology, where synthetic circuits can be developed to implement the proposed controllers and curb the effect of external perturbations due to disease or environmental changes. We design a feedback controller that can be implemented genetically in order to mitigate the effect of perturbations that enter the network
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