Ratiometric control of cell phenotypes in monostrain 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 with 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. As a representative example, we consider the realistic agent-based implementation of our control strategy to enable cooperative bioproduction of a dimer in a monostrain microbial consortium.

Multicellular PD Control in Microbial Consortia

“…We chose values of the control gains β P and β D that were shown in Matlab (see Figure 1) to guarantee e ∞ < 20% when Y d = 60 nM and to also satisfy condition (16). We ran 10 agent-based simulations, each time randomly selecting the control gains with uniform distribution and evaluating the performance.…”

“…For the PD architecture we also imposed condition (16). The reference signal Q d = µY d /θ is depicted as a dashed line.…”

“…The blue lines are obtained using a Proportional controller and the purple ones using a PD controller. Control gains were drawn with uniform distribution from the region of the parameter space (β P , β D ) in Figure2in which ē% < 20%.For the PD architecture we also imposed condition(16). The reference signal Q d = µY d /θ is depicted as a dashed line.…”

Pinning Control of Hypergraphs

“…However, due to limitations on sensing and actuation, in several applications it is not possible to measure the state of a given node, but rather a function of the state of a group of nodes. For instance, in feedback control of microbial consortia, fluorescence cannot always be measured at the level of the single node (i.e., the single cell) but rather an aggregated measurement of the fluorescence of groups of cells is obtained [29]. Similarly, limits on the actuation imply that the same control signal has to be injected on more nodes (i.e., more cells).…”

Structural Identifiability and Observability of Microbial Community Models

“…Despite their abundance, detailed information on the composition and function of microbial communities (both within humans and Earth-wide) has been obtained only in the last few decades [ 6 ], thanks to experimental advances in molecular biology. Likewise, the application of control-theoretic techniques to their analysis is largely unexplored, despite a number of recent examples [ 7 , 8 , 9 ]. The development of accurate and informative mathematical models is a key tool for understanding, predicting, and controlling the behaviour of microbial consortia [ 10 , 11 ].…”