3Corresponding author:
alvaro.sanchez@cnb.csic.es
Abstract. 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.