Model-based process design for surfactin production with Bacillus subtilis.

Area of Science:

• Industrial Biotechnology
• Bioprocess Engineering
• Microbial Physiology

Background:

• Bacillus subtilis is a key industrial microorganism, but its fed-batch fermentation kinetics are poorly understood.
• Lack of biological performance indicators, like time-varying production yields, hinders optimization.
• Optimizing fed-batch processes requires a deep understanding of microbial kinetics and biological performance.

Purpose of the Study:

• To characterize fed-batch bioreactor kinetics of Bacillus subtilis BMV9 for surfactin production.
• To develop a kinetic model describing biomass, substrate, surfactin, and acetate dynamics.
• To utilize the kinetic model for designing and implementing an optimized, model-based fed-batch process.

Main Methods:

• Fed-batch bioreactor cultures of Bacillus subtilis BMV9 were used.
• A kinetic model using first-order ordinary differential equations was developed.
• The model integrated Monod kinetics for growth, substrate consumption, surfactin synthesis, and acetate formation.
• The model was parameterized using data from 12 fed-batch experiments.

Main Results:

• The kinetic model accurately described biomass accumulation, substrate consumption, and surfactin production rates.
• The model provided insights into overflow metabolism and acetate formation.
• A model-based process design, omitting the batch phase, achieved a product titre of 46.33 g/L.
• A space-time-yield of 2.11 g/(L*h) was attained.

Conclusions:

• The developed kinetic model significantly enhances process understanding for Bacillus subtilis fed-batch cultures.
• The model allows for the computation of non-analytically accessible process parameters.
• Sensitivity analysis identified key parameters influencing model outputs, guiding further optimization efforts.