Moment-based analysis of biochemical feedback circuits in a population of chemically interacting cells
Cells utilize chemical communication to exchange information and coordinate their behavior in noisy environments. Depending on the scenario, communication can reduce variability and shape a collective response, or amplify variability to generate distinct phenotypic subpopulations. Here we use a moment-based approach to study how cell-cell communication affects noise in biochemical networks that arises from both intrinsic and extrinsic sources. Based on a recently proposed model reduction technique, we derive a system of differential equations that captures lower-order moments of a population of cells, which communicate by secreting and sensing a diffusing molecule. Importantly, the number of equations that we obtain in this way is independent of the number of considered cells such that the method scales to arbitrary population sizes. Based on this approach, we analyze how cell-cell communication affects noise in several biochemical circuits.