Buffering variability in cell regulation motifs close to criticality

Area of Science:

• Systems biology
• Theoretical biology
• Biophysics

Background:

• Bistable biological systems require noise management for precise function near critical points.
• Stochastic noise can destabilize biological systems, leading to unpredictable state changes.

Purpose of the Study:

• To investigate the stability of bistable biological systems operating near bifurcation points under stochastic noise.
• To determine how cooperative interactions influence system variability and noise resilience.
• To identify reliable methods for detecting impending regime shifts in such systems.

Main Methods:

• Analysis of generic systems using minimal models.
• Mathematical modeling of cooperative interactions and stochastic noise.
• Statistical analysis of distributional data to identify early warning signals.

Main Results:

• Cooperative interactions were shown to buffer system variability, thereby reducing the likelihood of noise-induced regime shifts.
• A specific range of cooperativity was identified where system variability is effectively managed.
• Statistical early warning signals derived from distributional data can reliably detect approaching regime shifts within this cooperativity range.

Conclusions:

• Cooperative interactions are crucial for maintaining stability in bistable biological systems subject to noise.
• The developed generic framework provides a method to assess robustness and variability in complex biological models and data.
• Early detection of critical transitions is feasible using statistical methods, aiding in understanding biological system dynamics.