title: In silico approaches to study mass and energy flows in microbial consortia: a syntrophic case study.
abstract: BACKGROUND
  Three methods were developed for the application of stoichiometry-based network analysis approaches including elementary mode analysis to the study of mass and energy flows in microbial communities. Each has distinct advantages and disadvantages suitable for analyzing systems with different degrees of complexity and a priori knowledge. These approaches were tested and compared using data from the thermophilic, phototrophic mat communities from Octopus and Mushroom Springs in Yellowstone National Park (USA). The models were based on three distinct microbial guilds: oxygenic phototrophs, filamentous anoxygenic phototrophs, and sulfate-reducing bacteria. Two phases, day and night, were modeled to account for differences in the sources of mass and energy and the routes available for their exchange.
  
  
  RESULTS
  The in silico models were used to explore fundamental questions in ecology including the prediction of and explanation for measured relative abundances of primary producers in the mat, theoretical tradeoffs between overall productivity and the generation of toxic by-products, and the relative robustness of various guild interactions.
  
  
  CONCLUSIONS
  The three modeling approaches represent a flexible toolbox for creating cellular metabolic networks to study microbial communities on scales ranging from cells to ecosystems. A comparison of the three methods highlights considerations for selecting the one most appropriate for a given microbial system. For instance, communities represented only by metagenomic data can be modeled using the pooled method which analyzes a community's total metabolic potential without attempting to partition enzymes to different organisms. Systems with extensive a priori information on microbial guilds can be represented using the compartmentalized technique, employing distinct control volumes to separate guild-appropriate enzymes and metabolites. If the complexity of a compartmentalized network creates an unacceptable computational burden, the nested analysis approach permits greater scalability at the cost of more user intervention through multiple rounds of pathway analysis.
authors.affiliation: Thermal Biology Institute, Montana State University, Bozeman, MT 59717, USA. rtaffs@erc.montana.edu
authors.forename: Reed
authors.initials: R
authors.lastname: Taffs
authors.forename: John E
authors.initials: JE
authors.lastname: Aston
authors.forename: Kristen
authors.initials: K
authors.lastname: Brileya
authors.forename: Zackary
authors.initials: Z
authors.lastname: Jay
authors.forename: Christian G
authors.initials: CG
authors.lastname: Klatt
authors.forename: Shawn
authors.initials: S
authors.lastname: McGlynn
authors.forename: Natasha
authors.initials: N
authors.lastname: Mallette
authors.forename: Scott
authors.initials: S
authors.lastname: Montross
authors.forename: Robin
authors.initials: R
authors.lastname: Gerlach
authors.forename: William P
authors.initials: WP
authors.lastname: Inskeep
authors.forename: David M
authors.initials: DM
authors.lastname: Ward
authors.forename: Ross P
authors.initials: RP
authors.lastname: Carlson
mesh_terms: D041861:Chloroflexus / Q000502:physiology*; D002940:Circadian Rhythm / Q000502:physiology; D017753:Ecosystem; D004734:Energy Metabolism / Q000502:physiology*; D053858:Metabolic Networks and Pathways / Q000502:physiology*; D008954:Models, Biological; D009586:Nitrogen Fixation / Q000502:physiology; D013045:Species Specificity; D046940:Synechococcus / Q000502:physiology*; D014959:Wyoming