PID Control of Biochemical Reaction Networks
For synthetic biology and biochemical systems engineering, this work enables more precise feedback control by implementing derivative action in CRNs for the first time.
This work provides the first implementation of a derivative component in Biochemical Reaction Networks (CRNs), enabling a full PID controller in CRNs, and demonstrates its application to regulate protein expression in a microRNA-regulated gene expression model.
Principles of feedback control have been shown to naturally arise in biological systems and successfully applied to build synthetic circuits. In this work we consider Biochemical Reaction Networks (CRNs) as a paradigm for modelling biochemical systems and provide the first implementation of a derivative component in CRNs. That is, given an input signal represented by the concentration level of some species, we build a CRN that produces as output the concentration of two species whose difference is the derivative of the input signal. By relying on this component, we present a CRN implementation of a feedback control loop with Proportional-Integral-Derivative (PID) controller and apply the resulting control architecture to regulate the protein expression in a microRNA regulated gene expression model.