Metabolic Flux Analysis at the Genome-Scale Increases the Scope and Accuracy of Flux Estimations

Metabolic flux analysis (MFA) is considered to be the gold standard for determining the intracellular flux distribution of biological systems.  The majority of work using MFA has so far been limited to core models of metabolism.  In this work, the scope of MFA is expanded to the genome-scale through a combination of an improved analytical method and model generation workflow.  It is shown that a compromise between precision and accuracy exists when utilizing a core model or genome-scale model for MFA: the former offers greater precision of flux estimates of core metabolism, while the latter offers greater accuracy of flux estimates of core metabolism, and provides direct flux calculations of purine, pyrimidine, isoprenoid, methionine, riboflavin, CoA, folate, and other biosynthetic pathways.  It is also shown that the loss of precision of flux estimates of core metabolism when using the genome-scale model can be improved through additional measurements of mass isotopomer distributions of cofactors and peripheral metabolism metabolites.  Current applications of genome-scale MFA to understanding adaptive laboratory evolution (ALE) in E. coli will also be presented.