The optimization of microbial community functions through rational environmental manipulations.

Microbial communities are gaining ground in biotechnology, as they offer many advantages over single-organism monocultures. To make microbial communities competitive as a biotechnological platform, it is essential that we develop strategies to engineering and optimizing their functionality. To this end, most efforts have focused on genetic manipulations. An alternative and also very promising strategy is to optimize the function of microbial communities by rationally engineering their environment and culture conditions. A major challenge is that the combinatorial space of environmental factors is enormous. Furthermore, environmental factors such as temperature, pH, nutrient composition, etc., generally combine their effects in complex, non-additive ways. In this piece, we overview the origins and consequences of these “interactions” between environmental factors, and discuss how they have been built into statistical models of microbial community function to identify optimal environmental conditions. We also overview alternative “top-down” approaches, such as genetic algorithms, to finding combinations of environmental factors that optimize the function of microbial consortia. By providing a brief summary of the state of this field, we hope to stimulate the development of novel methodologies to rationally manipulate and optimize microbial communities through their environment.