A Molecular Communication model for cellular metabolism

Abstract

Understanding cellular engagement with its environment is essential to control and monitor metabolism. Molecular Communication theory (MC) offers a computational means to identify environmental perturbations that direct or signify cellular behaviors by quantifying the information about a molecular environment that is transmitted through a metabolic system. We developed an model that integrates conventional flux balance analysis metabolic modeling (FBA) and MC, and additionally defined several channels of metabolic communication through environmental information transfers through a metabolism, to uniquely blend mechanistic biology and information theory to understand how substrate consumption is captured reaction activity, metabolite excretion, and biomass growth. The information flow in bits calculated through this workflow further determines the upper limit of information flow -- the maximal effect of environmental perturbations on cellular metabolism and behaviors -- since FBA simulates maximal efficiency of the metabolic system. We exemplify this method on two intestinal symbionts -- Bacteroides thetaiotaomicron and Methanobrevibacter smithii -- and visually consolidated the results into constellation diagrams that facilitate interpretation towards actionable design of controllable biological systems. The unique confluence of metabolic modeling and information theory in this model advances basic understanding of cellular metabolism and has applied value for the Internet of Bio-Nano Things, synthetic biology, microbial ecology, and autonomous laboratories, where the calculable control of cellular behaviors from environmental perturbations is imperative.