A Method to Constrain Genome-Scale Models with 13C Labeling Data
Fig 2
Algorithm flow diagram for 2S-13C MFA showing a recursive procedure to achieve self-consistent results. The full model consists of a genome-scale model (iJR904 in this case) to which information on carbon transitions for the core sets of reactions is added (blue box on the left). The genome-scale model carries the measured extracellular fluxes information as upper and lower bounds (ubj and lbj). Carbon transitions (example line below the blue box) indicate the fate of each carbon atom in the reaction. The first step in the algorithm involves limiting the amount of flux that flows into the core set of metabolites and reactions, so as to enforce the two-scale approximation (i.e. that non-core contributions to labeling are negligible). The second step involves finding the set of fluxes that best fit the experimentally observed data, ignoring the non-core contributions. The final step tests that the error incurred by ignoring non-core reactions is negligible through External Labeling Variability Analysis (ELVA). If the ELVA does not indicate that the non-core contributions are negligible, the core set and the EMU model are expanded and the procedure repeated. When a self-consistent result is found, flux ranges compatible with the experimental data are obtained through 13C Flux Variability Analysis.