Control-Based Continuation: A New Approach to Prototype Synthetic Gene Networks.

Area of Science:

• Systems Biology
• Biophysics
• Control Theory

Background:

• Bifurcation analysis is crucial for understanding complex system dynamics.
• Traditional methods rely on mathematical models, introducing uncertainty.
• Model-free approaches are needed for robust experimental analysis.

Purpose of the Study:

• To introduce and validate Control-Based Continuation (CBC) for bifurcation analysis in physical experiments.
• To demonstrate CBC's applicability to biochemical processes, including noisy systems.
• To showcase CBC's utility in complex, in vivo-like conditions and for parameter estimation.

Main Methods:

• Control-Based Continuation (CBC) applied to a biochemical toggle switch model.
• Comparison of model-free and model-based CBC control strategies.
• Implementation of CBC within an agent-based simulator for in vivo conditions.

Main Results:

• CBC successfully tracked equilibrium curves, revealing bistability in a toggle switch system.
• Both model-free and model-based CBC strategies identified stable and unstable solutions.
• CBC demonstrated efficacy in a complex agent-based simulation mimicking in vivo environments.

Conclusions:

• CBC offers a model-independent approach for bifurcation analysis in physical experiments.
• The method accurately identifies system dynamics, including bistability, even with noise.
• CBC accelerates the design and prototyping of synthetic gene networks.