Protocol

Hydrocarbon and Lipid Microbiology Protocols

Part of the series Springer Protocols Handbooks pp 247-273

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Constructing and Analyzing Metabolic Flux Models of Microbial Communities

  • José P. FariaAffiliated withComputation Institute, University of ChicagoComputing, Environment and Life Sciences, Argonne National Laboratory 
  • , Tahmineh KhazaeiAffiliated withDivision of Biology and Biological Engineering, California Institute of Technology 
  • , Janaka N. EdirisingheAffiliated withComputation Institute, University of ChicagoMathematics and Computer Science Division, Argonne National Laboratory
  • , Pamela WeisenhornAffiliated withMathematics and Computer Science Division, Argonne National LaboratoryBiosciences, Argonne National Laboratory
  • , Samuel M. D. SeaverAffiliated withComputation Institute, University of ChicagoMathematics and Computer Science Division, Argonne National Laboratory
  • , Neal ConradAffiliated withMathematics and Computer Science Division, Argonne National Laboratory
  • , Nomi HarrisAffiliated withLawrence Berkley National Lab
  • , Matthew DeJonghAffiliated withComputer Science Department, Hope College
  • , Christopher S. HenryAffiliated withComputation Institute, University of ChicagoMathematics and Computer Science Division, Argonne National Laboratory Email author 

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Abstract

Here we provide a broad overview of current research in modeling the growth and behavior of microbial communities, while focusing primarily on metabolic flux modeling techniques, including the reconstruction of individual species models, reconstruction of mixed-bag models, and reconstruction of multi-species models. We describe how flux balance analysis may be applied with these various model types to explore the interactions of a microbial community with its environment, as well as the interactions of individual species with each other. We demonstrate all discussed model reconstruction and analysis approaches using the Department of Energy’s Systems Biology Knowledgebase (KBase), constructing and importing genome-scale metabolic models of Bacteroides thetaiotaomicron and Faecalibacterium prausnitzii, and subsequently combining them into a community model of the gut microbiome. We also use KBase to explore how these species interact with each other and with the gut environment, exploring the trade-offs in information provided by applying each metabolic flux modeling approach. Overall, we conclude that no single approach is better than the others, and often there is much to be gained by applying multiple approaches synergistically when exploring the ecology of a microbial community.

Keywords:

Bacteroides thetaiotaomicron Ecology Faecalibacterium prausnitzii Flux balance analysis Genome-scale modeling Microbial communities