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

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Abstract

Motivation: 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.

Results: 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.

Availability and implementation: The software is freely available as a matlab script in the Supplementary materials.

Contact:zampieri@imsb.biol.ethz.ch.

Supplementary information: Supplementary data are available at Bioinformatics online.

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