Metabolic Flux Analysis in Isotope Labeling Experiments Using the Adjoint Approach

Area of Science:

• Systems Biology
• Metabolic Engineering
• Computational Biology

Background:

• Metabolic flux analysis (MFA) aids in understanding metabolic pathways through isotope labeling experiments.
• Complex balance equations in MFA necessitate computational efficiency for analysis.

Purpose of the Study:

• To accelerate the metabolic flux analysis identification process.
• To reduce computational cost and complexity in nonstationary MFA.

Main Methods:

• Utilized the adjoint approach to compute the gradient of the residual sum of squares.
• Compared the adjoint approach with the conventional direct approach for computational efficiency.

Main Results:

• The adjoint approach demonstrated significant improvements in complexity and computation time.
• Numerical results for Escherichia coli central metabolic pathways validated the approach against reference software.

Conclusions:

• The adjoint approach offers a more efficient method for metabolic flux analysis.
• The developed algorithms are integrated into the open-source sysmetab software package.