Fig. 6: Computational screening for optimal controller parameters and closed-loop control of co-culture composition.
From: Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback
a Schematic of closed-loop control experiment with a PID controller. b Computational screening for optimal PID gains. Sets of randomly sampled gains (Kp, Ki, Kd) are used to simulate the expected trajectory of the co-culture in a closed-loop setting with a defined target setpoint. Trajectories are scored according to their total deviation from the target strain ratio in the relevant time window. c–e Closed-loop control of co-cultures with the same initial strain ratio and different target setpoints. Both model predictions (Right) and experiments (Left) are shown. c Target photophilic fraction: \({\varphi }_{p}^{{{{{\mathrm{set}}}}}}=0.7\). d Target photophilic fraction: \({\varphi }_{p}^{{{{{\mathrm{set}}}}}}=0.3\). e The strain ratio is forced to track setpoints that change from a target photophilic fraction of \({\varphi }_{p}^{{{{{\mathrm{set}}}}}}=0.2\) to \({\varphi }_{p}^{{{{{\mathrm{set}}}}}}=0.8\) (t = 10 h) and to \({\varphi }_{p}^{{{{{\mathrm{set}}}}}}=0.4\) (t = 30 h).
