Cell size distribution of lineage data: analytic results and parameter inference

Area of Science:

• Cell biology
• Mathematical modeling
• Quantitative biology

Background:

• Single-cell technologies allow time-resolved measurements of cell size over multiple cell cycles.
• Understanding cell size homeostasis is crucial for comprehending normal cell growth and preventing abnormal proliferation.

Purpose of the Study:

• To formulate a mathematical model for cell size evolution across generations.
• To analyze the three main cell size homeostasis strategies: timer, sizer, and adder.
• To derive an analytical expression for non-Gaussian cell size distributions in cell lineages.

Main Methods:

• Development of a piecewise deterministic Markov model for cell size dynamics.
• Analytical solution of the model to obtain cell size distribution.
• Comparison of theoretical predictions with experimental E. coli lineage data.

Main Results:

• An analytical expression for non-Gaussian cell size distribution was derived.
• The model elucidates how cell cycle dynamics and tracking protocols influence distribution shape.
• The theoretical distribution closely matched experimental E. coli cell size data across various growth conditions.

Conclusions:

• The developed model provides a robust framework for studying cell size homeostasis.
• The findings offer insights into the mechanisms cells employ to correct size aberrations.
• The model's accuracy validates its utility in analyzing single-cell experimental data.