Modelling and parameter identification for batch fermentations with Streptomyces tendae under phosphate limitation

Area of Science:

• Biochemical Engineering
• Microbial Physiology
• Mathematical Modeling

Background:

• Phosphate availability critically impacts microbial growth and secondary metabolite production.
• Understanding intracellular phosphate dynamics is key to optimizing fermentation processes.
• Streptomyces tendae's phosphate metabolism involves complex regulatory pathways.

Purpose of the Study:

• To develop a simple structured model for phosphate-limited batch fermentations of Streptomyces tendae.
• To investigate the influence of intracellular phosphate storage on microbial growth.
• To elucidate internal regulatory processes in phosphate metabolism.

Main Methods:

• Development of a simplified model based on rate-limiting steps of phosphate metabolism.
• Parameter fitting using an identification program based on sequential quadratic programming.
• Iterative modeling and identification loops to refine model accuracy.
• Simulation analysis of batch fermentation data.

Main Results:

• A robust model was achieved that accurately fits experimental batch fermentation data.
• Simulations successfully interpret RNA measurements, linking them to intracellular state variables.
• Evidence suggests RNA acts as a significant intracellular phosphate reserve in Streptomyces tendae.

Conclusions:

• The developed model effectively captures the dynamics of phosphate-limited fermentations.
• Intracellular phosphate storage, potentially via RNA, plays a crucial role in regulating Streptomyces tendae growth.
• The model provides a valuable tool for understanding and optimizing microbial fermentation processes.