Population balance models of autonomous microbial oscillations

Area of Science:

• Microbial Physiology
• Biochemical Engineering
• Mathematical Modeling

Background:

• Autonomous oscillations are well-documented in continuous cultures of Saccharomyces cerevisiae (baker's yeast).
• These oscillations occur under various operating conditions and are crucial for understanding microbial population dynamics.

Purpose of the Study:

• To model autonomous microbial oscillations using unstructured population balance models.
• To investigate how cell cycle parameters, influenced by environmental conditions, drive dynamic behaviors in microbial cultures.

Main Methods:

• Development and simulation of unstructured population balance models.
• Analysis of model outputs to identify dynamic behaviors, including synchronized subpopulations.

Main Results:

• The models successfully replicate observed dynamic behaviors in yeast cultures.
• Budding yeasts, like S. cerevisiae, exhibit two synchronized subpopulations, consistent with experimental data.
• Complex periodic solutions with periods differing from the cell cycle length are predicted by the models.

Conclusions:

• Unstructured population balance models provide a simple yet powerful framework for describing yeast culture dynamics.
• These models accurately capture the complex oscillations observed in Saccharomyces cerevisiae, including synchronized subpopulations.
• The approach highlights the influence of environmental factors on cell cycle parameters and overall culture behavior.