Transitions in genetic toggle switches driven by dynamic disorder in rate coefficients

Area of Science:

• Biochemistry
• Systems Biology
• Statistical Mechanics

Background:

• Biochemical systems often exhibit intrinsic noise, leading to state switching.
• Bistable networks possess two stable states, with transitions influenced by kinetic parameters.

Purpose of the Study:

• To investigate the impact of dynamic disorder (fluctuating rate coefficients) on kinetic switching in bistable networks.
• To analyze how different stochastic processes governing dynamic disorder affect transition pathways and probabilities.

Main Methods:

• Geometric minimum action method applied to a genetic toggle switch model.
• Analysis of discrete and continuous probability distributions for rate coefficients.
• Modeling dynamic disorder using discrete Markov processes and continuous Langevin dynamics.

Main Results:

• Optimal transition paths and minimum actions were determined for discrete and continuous disorder models.
• Dynamic disorder significantly influences transition path statistics and probabilities.
• Regulation of parameters modulating dynamic disorder is crucial for network behavior.

Conclusions:

• Dynamic disorder plays a critical role in the switching dynamics of bistable biochemical networks.
• Allosteric control mechanisms can be leveraged to modulate dynamic disorder and thus network stability.
• Understanding these dynamics is essential for predicting and controlling biochemical system behavior.