d-OptCom: Dynamic multi-level and multi-objective metabolic modeling of microbial communities.

Area of Science:

• Microbial Ecology
• Computational Biology
• Systems Biology

Background:

• Microbial communities are dynamic and change in response to environmental shifts.
• Interspecies metabolic interactions are crucial for community structure and function.
• Existing models often lack the ability to capture temporal dynamics.

Purpose of the Study:

• To introduce d-OptCom, a novel dynamic metabolic modeling framework for microbial communities.
• To enable the simulation of temporal changes in biomass and metabolite concentrations.
• To integrate both species- and community-level fitness functions for comprehensive analysis.

Main Methods:

• d-OptCom extends the OptCom procedure for dynamic metabolic modeling.
• Models capture temporal dynamics of biomass and extracellular metabolites.
• Integrates species- and community-level fitness functions and uptake kinetics.

Main Results:

• Demonstrated d-OptCom's applicability using E. coli auxotrophic mutant pairs.
• Assessed the dynamics and composition of a uranium-reducing microbial community.
• Showcased the impact of nutrient (lactate vs. acetate) on community composition.

Conclusions:

• Simultaneous consideration of species- and community-level fitness is vital for accurate modeling.
• Incorporating uptake kinetics significantly enhances prediction of interspecies flux.
• d-OptCom facilitates dynamic, multi-level, and multi-objective analysis of microbial ecosystems.