title: Model-based media selection to minimize the cost of metabolic cooperation in microbial ecosystems.
abstract: 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.
authors.affiliation: Department of Biology, Institute for Molecular Systems Biology, Zurich 8093, Switzerland.
authors.forename: Mattia
authors.initials: M
authors.lastname: Zampieri
authors.affiliation: Department of Biology, Institute for Molecular Systems Biology, Zurich 8093, Switzerland.
authors.forename: Uwe
authors.initials: U
authors.lastname: Sauer
mesh_terms: D000465:Algorithms; D017753:Ecosystem; D008954:Models, Biological; D008962:Models, Theoretical; D011382:Programming, Linear