Predicted steady-state cell size distributions for various growth models.

Area of Science:

• Microbiology
• Biophysics
• Mathematical Biology

Background:

• Bacterial cell growth mechanisms and size distributions are not fully understood.
• The Collins-Richmond equation offers a robust framework for analyzing bacterial growth kinetics.
• This equation relates cell size distributions to growth rates in steady-state conditions.

Purpose of the Study:

• To apply the Collins-Richmond equation in reverse to predict theoretical cell size distributions.
• To evaluate sophisticated bacterial growth hypotheses beyond simple deterministic models.
• To develop mathematical expressions for extant cell size distributions under steady-state exponential growth.

Main Methods:

• Utilized the Collins-Richmond equation in a reverse approach.
• Developed theoretical cell size distributions for two exponential and six linear growth models.
• Formulated rigorous mathematical expressions for predicting cell size distributions.

Main Results:

• Generated theoretical cell size distributions for various exponential and linear growth models.
• Models explored include those with minimal non-growing cell size and different timings for growth rate doubling.
• Mathematical expressions were derived to predict extant cell size distributions.

Conclusions:

• The reverse application of the Collins-Richmond equation allows for the evaluation of complex bacterial growth laws.
• This study provides theoretical predictions for cell size distributions under different growth scenarios.
• The derived mathematical expressions serve as a basis for experimental testing in subsequent research.