Theoretical Basis for Dynamic Label Propagation in Stationary Metabolic Networks under Step and Periodic Inputs

Area of Science:

• Metabolic Engineering
• Systems Biology
• Biochemical Engineering

Background:

• Dynamic isotope labeling experiments provide insights into metabolic network topology, fluxes, and metabolite pool sizes.
• Current experimental and numerical methods face limitations in dynamic labeling studies.
• Addressing these limitations is crucial for advancing metabolic network analysis.

Purpose of the Study:

• To propose a novel method using periodic label inputs (sinusoidal or rectangular pulses) for dynamic labeling experiments.
• To address practical and numerical challenges associated with current dynamic labeling approaches.
• To provide a theoretical basis for interpreting label propagation curves and identifying limitations in dynamic labeling experiments.

Main Methods:

• Developed mathematical descriptions for label propagation in linear metabolic pathways under classical and periodic label inputs.
• Utilized theoretical developments and computer simulations to analyze label propagation dynamics.
• Applied the proposed strategy to estimate fluxes in a simulated central carbon metabolism network of Escherichia coli.

Main Results:

• Theoretical analysis and simulations demonstrate the advantages of rectangular periodic pulses over other input types.
• The proposed method shows practical and numerical benefits for dynamic labeling experiments.
• Successful flux estimation in a simulated complex metabolic network (E. coli central carbon metabolism) was achieved.

Conclusions:

• Periodic label inputs, particularly rectangular pulses, offer a viable solution to challenges in dynamic metabolic labeling.
• This approach enhances the ability to determine metabolic network topology, fluxes, and metabolite pool sizes.
• The study provides a foundation for rational interpretation of dynamic labeling data and development of numerical methods.