One of the key considerations in metabolic engineering is determining fluxes of metabolites within the cell, which provides an unambiguous description of metabolism before and/or after engineering interventions. Here, we present a computational framework that combines a constraint-based modeling framework with isotopic label tracing on a large-scale. This model includes 393 fluxes, 214 metabolites, and balances on cofactors such as ATP and NADH as well as the electron transport chain, full amino acid biosynthesis and degradation, and a detailed biomass equation. Experimental results are presented for an Escherichia coli strain engineered to produce amorphadiene, a precursor to the anti-malarial drug artemisinin. These include a statistical analysis of fluxes determined for the system such as the minimal and maximal values of the fluxes given measurement noise. We also introduce a degree of resolution calculation that quantifies how the isotope data restrict these fluxes within the ranges allowed by overall stoichiometry. We also address how labeled substrate choice and isotope measurements impact the elucidation of fluxes in large-scale metabolic reconstructions.

Subsequently, we discuss how these flux ranges can guide engineering of the system when improving product yields by using an optimization framework. For instance, if a product is increased by a certain percent, we identify the fluxes that must increase outside the ranges prescribed by the isotope data as potential targets of manipulation. We apply this approach to the production of amorphadiene and other bio-compounds of industrial interest.