New Methods to Constrain Genome Scale Models with Stable Isotope Labeling Data

Here we present new methods to directly constrain genome scale models with 13C stable isotope labeling data. By reducing the assumptions required for flux modeling, these methods can infer fluxes in engineered organisms with unusual phenotypes. First, we present a method to systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation that carbon tends to flow outward from core metabolism. Second, we automatically identify an updated set of core reactions that can satisfy this approximation more efficiently via Simulated Annealing. Lastly, we present a workflow to quantify the uncertainty of fluxes constrained with stable isotope labeling data at the genome scale using Markov Chain Monte Carlo (MCMC).