Extending the scope of isotope mapping models becomes increasingly important in order to analyze strains and drive improved product yields as more complex pathways are engineered into strains and as secondary metabolites are used as starting points for new products. The elementary metabolite unit (EMU) framework and flux coupling significantly decrease the computational burden of metabolic flux analysis (MFA) when applied to large-scale metabolic models. We find that the combined use of EMU and flux coupling analysis leads to a ten-fold decrease in the number of variables in comparison to the original isotope distribution vector (IDV) version of the imPS1485 model.
Related Publications: Gopalakrishnan S., Maranas C.D. (2015), "13C metabolic flux analysis at a genome-scale", Metabolic Engineering, 32:12-22. PMID: 26358840.  Suthers, P.F., Y.J. Chang and C.D. Maranas (2009), "Improved computational performance of MFA using elementary metabolite units and flux coupling," Metab Eng, 12(2): 123.
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