Speaker
Description
To understand the organization and dynamics of microbial communities is a fundamental challenge in current biology. To tackle this challenge, the construction of computational models of interacting microbes is an indispensable tool. There is, however, still a chasm between ecologically motivated descriptions of microbial growth used in typical ecosystems simulations, and the detailed metabolic pathway and genome-based descriptions developed in the context of systems and synthetic biology.
My contribution will outline how models of cellular resource allocation allow us to formulate mechanistic descriptions of microbial growth that are physiologically meaningful while remaining computationally tractable, and therefore offer the potential to advance ecosystem simulations. In particular, recent coarse-grained mechanistic models of microbial growth go beyond Monod-type growth models, and are capable to account for, and explain, several emergent properties of microbial physiology, such as catabolite repression, hierarchies of preferred nutrients, and the utilization of seemingly inefficient pathways.
Of particular interest are trade-offs that arise from limited cellular resources, for example between synthesis of storage compounds versus rapid instantaneous growth. The contribution will discuss the implications of such trade-offs for the organization of microbial community ecology and point out limits in our current understanding of microbial physiology. My main example will be quantitative models of cyanobacterial growth and the emergence of metabolic dependencies between photo- and heterotrophic microorganisms.
