Metabolic modeling of microbial communities

Open Access
Islam, Mohammad Mazharul
Graduate Program:
Chemical Engineering
Master of Science
Document Type:
Master Thesis
Date of Defense:
February 21, 2014
Committee Members:
  • Costas D Maranas, Thesis Advisor
  • dynamic
  • microbial communities
  • modeling
  • d-OptCom
  • Uranium reduction
  • Auxotrophic mutants. metabolic modeling
Most microbial communities change with time in response to changes and/or perturbations in environmental conditions. The temporal variations in inter-species metabolic interactions within these communities can significantly affect their structure and function. Here, I introduce d-OptCom, an extension of the OptCom procedure, for the dynamic metabolic modeling of microbial communities. It enables capturing the temporal dynamics of biomass concentration of the community members and extracellular concentration of the shared metabolites, while integrating species- and community-level fitness functions. The applicability of d-OptCom was demonstrated by modeling the dynamic co-growth of a number of auxotrophic mutant pairs of E. coli and by computationally assessing the dynamics and composition of a uranium-reducing community comprised of Geobacter sulfurreducens, Rhodoferax ferireducens and Shewanella oneidensis. d-OptCom was also employed to examine the impact of lactate vs. acetate addition on the relative abundance of uranium reducing species. These studies highlight the importance of simultaneously accounting for both species- and community-level fitness functions when modeling microbial communities and demonstrate that the incorporation of uptake kinetic information can substantially improve the prediction of inter-species flux trafficking. Overall, this study paves the way for the dynamic multi-objective analysis of microbial ecosystems.