Abstract
Microbial communities, which are assemblies of interacting microbes, affect our health and environment. They can be harmful by causing infections or beneficial by degrading toxins. Controlling harmful or beneficial communities requires predictive models that adequately capture microbial interactions.
Following the historical tradition of community ecology, researchers often model microbial communities as a superposition of pairwise fitness effects between species (for example, by using Lotka-Volterra equations). However, it is unclear under what conditions such models are suitable for representing microbial communities.
We show that common microbial interactions mediated by chemical compounds (called mediators) often cannot be adequately captured by using a pairwise fitness model. We build a simple model of interactions by explicitly incorporating chemical mediators. We explore how interaction mechanisms influence the mathematical representation in such a model. We use this model to investigate how interactions among species can lead to coexistence in a microbial community.
Our results suggest that we need to be cautious when extrapolating and generalizing conclusions obtained from pairwise fitness models to communities with diverse interaction mechanisms. We advocate a transition to models that incorporate interaction mechanisms at the appropriate level of abstraction.
ABOUT THE SPEAKER
Babak Momeni joined the department of biology at Boston College in 2015 as an assistant professor. He received his doctoral training in Photonics Research Group (Electrical Engineering) at Georgia Tech, where he designed and implemented compact on-chip photonic demultiplexers. He continued his work at Georgia Tech as a postdoctoral fellow, making spectrometers for biosensing applications. Intrigued by biological systems, he joined the Shou lab at Fred Hutchinson Cancer Research Center, and studied stability and spatial organization of microbial communities in synthetic communities.
Host: Sam Brown
]]>