Directing microbial co-culture composition using cybernetic control

We demonstrate a cybernetic approach to control the composition of a P. putida and E. coli co-culture that does not rely on genetic engineering to interface cells with computers. We first show how composition information can be extracted from different bioreactor measurements and then combined with a system model using an extended Kalman filter to generate accurate estimates of a noisy system. We then demonstrate that adjusting the culture temperature can drive the composition due to the species’ different optimal temperatures. Using a proportional-integral control algorithm, we are able to track dynamic references with real-time noise rejection and independence from starting conditions such as inoculation ratio. We stabilize the co-culture for 7 days (∼250 generations) with the experiment ending before the cells could adapt out of the control. This cybernetic framework is broadly applicable, with different microbes’ unique characteristics enabling robust control over diverse co-cultures.