Controlling reversible cell differentiation for labor division in microbial consortia

Abstract

We address the problem of regulating and keeping at a desired balance the relative numbers between cells exhibiting a different phenotype within a monostrain microbial consortium. We propose a strategy based on the use of external control inputs, assuming each cell in the community is endowed with a reversible, bistable memory mechanism. Specifically, we provide a general analytical framework to guide the design of external feedback control strategies aimed at balancing the ratio between cells whose memory is stabilized at either one of two equilibria associated to different cell phenotypes. We demonstrate the stability and robustness properties of the control laws proposed and validate them in silico implementing the memory element via a genetic toggle-switch. The proposed control framework may be used to allow long term coexistence of different populations, with both industrial and biotechnological applications. Examples include consortia where each population produces a compound of interest or where one population supports the growth of the other which has the role of producing a desired molecule. As a representative example we consider the realistic agent-based implementation of our control strategy to enable cooperative bioproduction in microbial consortia.

Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback

“…Nevertheless, introducing multiplexing methods 57 and focusing external control on key driver species within interacting communities 58 could provide a way forward. Previous attempts to stabilize microbial co-cultures have relied largely on self-limiting populations 29,30 , harnessing phenotypic switches in the co-cultured populations [59][60][61] , engineered interactions between strains and emergent behaviors 6,21,31,32,34 . Methods for ensuring co-existance in a chemostat through control of the dilution rate have also been proposed 62 .…”

Control-Based Continuation: A New Approach to Prototype Synthetic Gene Networks

“…As previously done in Shannon et al 22 and Salzano et al, 49 the simulation environment has been complemented with the SDE solver based on the Euler–Maruyama method eq 4 .…”

Control-based continuation: a new approach to prototype synthetic gene networks

“…As previously done in Shannon et al [22] and Salzano et al [49], the simulation environment has been complemented with the SDE solver based on the Euler-Maruyama method (4).…”

“…The CBC algorithm was implemented by adding to the simulation environment both the proportional and the MPC controllers. As previously done Shannon et al [22] and Salzano et al [49], the simulation environment has been complemented with the SDE solver based on the Euler-Maruyama method (4). BSim simulates experiments via a microfluidic-based system composed by a microfluidic device, a microscopy, a computer and an actuation system.…”