Ergodic sets as cell phenotype of budding yeast cell cycle.

Area of Science:

• Systems Biology
• Computational Biology
• Cell Cycle Regulation

Background:

• Irreducible sets of states in Probabilistic Boolean Networks (PBNs) are hypothesized to represent stable cellular phenotypes.
• Understanding the regulatory logic governing the cell cycle is crucial for comprehending cell proliferation and development.

Purpose of the Study:

• To identify irreducible sets of states (ergodic sets) within the budding yeast cell cycle network.
• To investigate the role of these ergodic sets in regulating cyclin activity across different cell cycle phases.
• To analyze the emergent dynamics and robustness of the yeast cell cycle using a Boolean network model.

Main Methods:

• Identification of ergodic sets in the context of the budding yeast cell cycle.
• Analysis of cyclin activity levels in relation to identified ergodic sets.
• Dynamical simulations of the Boolean network model under stochastic external signals.
• Comparison of model results with experimental observations and differential equation models.

Main Results:

• Ergodic sets were identified for each phase of the budding yeast cell cycle.
• These ergodic sets were found to underlie cyclin activity levels throughout the cell cycle.
• The Boolean network model demonstrated emergent oscillating waves of cyclin activity and Cyclin-Dependent Kinase Inhibitors (CKIs) without requiring specific kinetic parameters.
• The model suggests robustness of the yeast cell cycle network to variations in cell size and external conditions.
• The irreversibility of the 'Start' signal was linked to the G1 regulon's logic.

Conclusions:

• Ergodic sets in PBNs provide a framework for understanding cellular phenotypes, specifically cyclin activity in the yeast cell cycle.
• Boolean network logic can generate complex oscillatory dynamics characteristic of the cell cycle, independent of detailed biochemical parameters.
• The yeast cell cycle network exhibits robustness, and its key regulatory signals, like 'Start', are governed by network structure and logic.