Modeling microbial communities using biochemical resource allocation analysis

To understand the functioning and dynamics of microbial communities remains a fundamental challenge at the forefront of current biology. To tackle this challenge, the construction of computational models of interacting microbes is an indispensable tool. Currently, however, there is a large chasm between ecologically-motivated descriptions of microbial growth used in ecosystems simulations, and detailed metabolic pathway and genome-based descriptions developed within systems and synthetic biology. Here, we seek to demonstrate how current biochemical resource allocation models of microbial growth offer the potential to advance ecosystem simulations and their parameterization. In particular, recent work on quantitative microbial growth and cellular resource allocation allow us to formulate mechanistic models of microbial growth that are physiologically meaningful while remaining computationally tractable. Biochemical resource allocation models go beyond Michaelis-Menten and Monod-type growth models, and allow to account for emergent properties that underlie the remarkable plasticity of microbial growth. We exemplify our approach using a coarse-grained model of cyanobacterial phototrophic growth, and demonstrate how the model allows us to represent physiological acclimation to different environments, co-limitation of growth by several nutrients, as well as emergent switches between alternative nutrient sources. Our approach has implications for building models of microbial communities to understand their interactions, dynamics and response to environmental changes.