Metabolic engineering from a cybernetic perspective. 1. Theoretical preliminaries

Area of Science:

• Systems Biology
• Metabolic Engineering
• Computational Biology

Background:

• Metabolic networks are complex, and predicting responses to genetic changes is challenging.
• Existing models often lack a systematic way to represent metabolic regulation.
• Designing and analyzing metabolic networks requires robust theoretical frameworks.

Purpose of the Study:

• To present a theoretical framework for cybernetic metabolic network design and analysis.
• To develop a method for predicting system responses to genetic alterations.
• To integrate metabolic control analysis with a cybernetic approach.

Main Methods:

• A three-branched conceptual methodology: model realization, genetic alteration representation, and metabolic design.
• Postulates for modular construction of cybernetic models from elementary pathways.
• Application of metabolic control analysis to cybernetic models, incorporating regulatory functions.

Main Results:

• The framework allows for modular construction of complex metabolic network models.
• Genetic alterations are represented by changes in available physiological choices while maintaining system objectives.
• Sensitivity coefficients from cybernetic models explicitly include metabolic regulation, unlike purely kinetic models.

Conclusions:

• The cybernetic metabolic network framework provides a robust method for analysis and design.
• The approach enables prediction of system behavior under genetic perturbation.
• This methodology facilitates rational alteration of metabolic function through integrated design and simulation.