A stochastic vs deterministic perspective on the timing of cellular events

Area of Science:

• Cellular and Molecular Biology
• Systems Biology
• Biophysics

Background:

• Cellular processes are initiated by molecular events reaching critical thresholds.
• Stochasticity, or noise, is inherent in molecular processes within cells.
• Understanding the impact of noise on cellular timing is crucial for predicting cell behavior.

Purpose of the Study:

• To investigate how molecular and cellular noise influence the time it takes for cells to reach critical molecular thresholds (first-passage time).
• To analyze scenarios where stochastic dynamics lead to altered average first-passage times compared to deterministic models.
• To provide theoretical insights into the role of noise in cellular event timing.

Main Methods:

• Development of a theoretical framework to analyze first-passage times in stochastic cellular systems.
• Modeling exemplar systems including gene expression, auto-regulatory feedback control, and enzyme-mediated catalysis.
• Quantifying the dependence of mean first-passage time on molecular noise levels.

Main Results:

• Molecular noise profoundly influences the first-passage time, the time to cross critical molecular thresholds.
• Stochastic dynamics can result in shorter or longer average first-passage times compared to noise-less dynamics.
• Deterministic predictions of cellular event timing can be inaccurate for systems with low molecule numbers.

Conclusions:

• Molecular noise significantly shifts mean first-passage times, particularly in auto-regulatory genetic feedback circuits.
• Accurate prediction of cellular event timing requires consideration of molecular noise, especially in systems with limited molecule counts.
• The study provides a theoretical foundation for understanding noise-driven dynamics in cellular decision-making.