Model-based media selection to minimize the cost of metabolic cooperation in microbial ecosystems

Simple forms of mutualism between microorganisms are widespread in nature. Nevertheless, the role played by the environmental nutrient composition in mediating cross-feeding in microbial ecosystems is still poorly understood.

Here, we use mixed-integer bilevel linear programming to investigate the cost of sharing metabolic resources in microbial communities. The algorithm infers an optimal combination of nutrients that can selectively sustain synergistic growth for a pair of species and guarantees minimum cost of cross-fed metabolites. To test model-based predictions, we selected a pair of Escherichia coli single gene knockouts auxotrophic, respectively, for arginine and leucine: ΔargB and ΔleuB and we experimentally verified that model-predicted medium composition significantly favors mutualism. Moreover, mass spectrometry profiling of exchanged metabolites confirmed the predicted cross-fed metabolites, supporting our constraint based modeling approach as a promising tool for engineering microbial consortia.

The software is freely available as a matlab script in the Supplementary materials.

zampieri@imsb.biol.ethz.ch

Supplementary data are available at Bioinformatics online.