(182a) Automated Generation of Complete Atom Mappings for MFA Using Genome-Scale Metabolic Reconstruction

Metabolic flux analysis (MFA) has so far been restricted to lumped networks lacking many important pathways, partly due to the difficulty in automatically generating isotope mapping matrices for genome-scale networks. Here we introduce a procedure for the largely automated generation of atom mappings for genome-scale metabolic reconstructions. The developed procedure uses a compound matching algorithm based on the graph theoretical concept of pattern recognition along with relevant reaction heuristics to automatically generate genome-scale atom mappings which trace the path of atoms from reactants to products for every reaction in any given reconstruction. When applied to the iAF1260 metabolic reconstruction of Escherichia coli, the genome-scale isotope mapping model imPR90068 is obtained. The model maps 90,068 non-hydrogen atoms, contains 1.37 x 10¹⁵⁷ distinct isotope forms and accounts for all 2,077 reactions present in iAF1260 (the previous largest mapping model included 238 reactions). The expanded scope of imPR90068 allows for tracking of labeled atoms through pathways such as cofactor and prosthetic group biosynthesis and histidine metabolism. We also discuss how using an elementary metabolite unit (EMU) representation of imPR90068 significantly reduces the number of variables during MFA.