Controllability of non-linear biochemical systems

Area of Science:

• Systems Biology
• Biochemical Engineering
• Control Theory

Background:

• Mathematical analysis of biochemical pathways is advancing, enabling objective rationale for metabolic system design and manipulation.
• Current metabolic optimization techniques primarily focus on steady-state conditions or transition time minimization using linear or kinetic models within biochemical systems theory (BST).
• Controllability of non-linear biochemical systems, especially steering them to non-steady states, remains a significant challenge.

Purpose of the Study:

• To address the problem of controllability in non-linear biochemical systems.
• To develop a method for steering these systems from initial to target states within a specified time frame.
• To enable manipulation of metabolic systems beyond steady-state conditions.

Main Methods:

• Transformation of BST models in S-system form into affine non-linear control systems.
• Application of exact feedback linearization to enable controllability.
• Utilizing independent variables for precise system steering.

Main Results:

• The developed method allows for the exact feedback linearization of non-linear biochemical systems.
• Controllability is achieved through the manipulation of independent variables.
• The method's efficacy is demonstrated using a glycolytic-glycogenolytic pathway model.

Conclusions:

• The proposed method offers a robust approach to controlling non-linear biochemical systems.
• This technique facilitates steering metabolic pathways to desired target states, including non-steady states.
• The findings have implications for optimizing microbial product yields and advancing metabolic engineering strategies.