A guide to deciphering microbial interactions and metabolic fluxes in microbiome communities

Abstract

Microbiomes occupy nearly all environments on Earth. These communities of interacting microorganisms are highly complex, dynamic biological systems that impact and reshape the molecular composition of their habitats by performing complex biochemical transformations. The structure and function of microbiomes are influenced by local environmental stimuli and spatiotemporal changes. In order to control the dynamics and ultimately the function of microbiomes, we need to develop a mechanistic and quantitative understanding of the ecological, molecular, and evolutionary driving forces that govern these systems. Here, we describe recent advances in developing computational and experimental approaches that can promote a more fundamental understanding of microbial communities through comprehensive model-based analysis of heterogeneous data types across multiple scales, from intracellular metabolism, to metabolite cross-feeding interactions, to the emergent macroscopic behaviors. Ultimately, harnessing the full potential of microbiomes for practical applications will require developing new predictive modeling approaches and better tools to manipulate microbiome interactions.