(796g) Dynamic Multi-Level Analysis and Metabolic Modeling of Microbial Communities Using Optcom | AIChE

(796g) Dynamic Multi-Level Analysis and Metabolic Modeling of Microbial Communities Using Optcom


Zomorrodi, A. R. - Presenter, The Pennsylvania State Univeristy
Islam, M. M., Pennsylvania State University
Mahadevan, R., University of Toronto
Maranas, C. D., The Pennsylvania State University

The species within microbial communities communicate through unidirectional or bidirectional exchange of biochemical cues.  These inter-species interactions and their temporal changes in response to environmental stimuli are known to significantly affect the structure and function of microbial communities and play a pivotal role in species evolution. Despite the growing availability of high-throughput experimental techniques and data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of metabolic interactions among them. This calls for development of efficient modeling frameworks to elucidate less understood aspects of metabolism in microbial communities. We have recently developed a comprehensive framework, called OptCom, for the flux balance analysis of microbial communities using genome-scale metabolic models, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. Given that microbial communities change with time (e.g., day/night cycle) new approaches that would be able to capture temporal interspecies metabolic interactions and tradeoffs are needed. To this end, we extend the OptCom procedure for the dynamic metabolic modeling of microbial communities by combining it with the DMMM (Dynamic Multi-species Metabolic Modeling) framework previously proposed by Zhuang et al. This is done by replacing the separate FBA problems for each individual species in DMMM with the OptCom’s multi-level optimization structure to account for interspecies interactions and temporal driving forces. In addition, the OptCom procedure was further extended to incorporate the uptake kinetics whenever available. These approaches were used for modeling the competition between Rhodoferax and Geobacter in subsurface anaerobic environment, and to examine addition of a new member to this community in order to assess the newly formed inter-species metabolic interactions and driving forces, and their dynamics under different environmental conditions.