Model selection for microbial nutrient uptake using a cost-benefit approach.

Area of Science:

• Microbial Physiology
• Biochemistry
• Systems Biology

Background:

• Microbial nutrient uptake is crucial for growth and metabolism.
• Understanding substrate utilization dynamics is key to predicting microbial behavior.
• Existing models often simplify the complex regulatory mechanisms of nutrient uptake.

Purpose of the Study:

• To develop a mathematical model for microbial carbon source uptake based on fundamental assumptions.
• To identify distinct behavioral patterns in microbial substrate utilization when presented with multiple carbon sources.
• To validate the model's predictive capability using experimental data.

Main Methods:

• Formulated mathematical models based on four core assumptions: saturation kinetics, cost-benefit of processing, controlled uptake, and evolutionary optimization.
• Analyzed model predictions for two-substrate scenarios.
• Applied batch-culture and retentostat data from Geobacter metallireducens for model validation.

Main Results:

• Identified three distinct microbial substrate uptake patterns: simultaneous consumption, preferential consumption with repression (catabolite repression), and exclusive consumption leading to population specialization.
• Demonstrated that the model structure can quantitatively describe uptake dynamics.
• Showcased model applicability using experimental data for toluene, benzoate, and acetate uptake.

Conclusions:

• The developed mathematical framework provides a robust description of microbial carbon source uptake strategies.
• The model accurately predicts diverse substrate utilization behaviors, including catabolite repression and population specialization.
• Experimental validation confirms the model's utility for quantitative analysis of microbial metabolism.