Modeling pH effects on microbial growth: a statistical thermodynamic approach.

Area of Science:

• Microbiology
• Biophysics
• Chemical Kinetics

Background:

• Microbial growth kinetics are significantly influenced by environmental factors, particularly pH.
• Existing models for pH-dependent microbial growth often struggle to capture diverse growth curve shapes.
• A robust theoretical framework is needed to unify the understanding of pH effects on microbial physiology.

Purpose of the Study:

• To develop a general equation based on statistical thermodynamics for microbial growth kinetics influenced by pH.
• To provide a theoretical foundation for existing pH-dependent microbial growth models.
• To evaluate the performance of the developed general equation against experimental data with varied curve shapes.

Main Methods:

• Application of a statistical thermodynamic approach to model microbial growth.
• Development of a general equation to describe specific growth rate as a function of pH.
• Testing the general equation using four diverse experimental data sets of microbial growth.

Main Results:

• The developed general equation provides a strong theoretical basis for existing pH models.
• The general equation successfully represented all four experimental data sets, including symmetrical and asymmetrical bell-shaped curves.
• Existing pH models only accurately represented one of the four data sets (the symmetrical case).

Conclusions:

• The novel statistical thermodynamic equation offers a more universally applicable model for pH-influenced microbial growth kinetics.
• This approach enhances the predictive capability for microbial responses to pH variations in diverse scenarios.
• The findings highlight the limitations of current models and the need for more comprehensive theoretical frameworks.