(441g) Dynamic Metabolic Flux Analysis at Metabolic Non-Steady State

Metabolic flux analysis (MFA) using stable isotopes has been established as a practical tool for flux mapping in complex metabolic networks. At the present time, work involving MFA has been limited to systems at metabolic steady state (e.g. chemostats and batch cultures during exponential growth). In order to analyze dynamic systems (e.g. fed-batch cultures) we had to develop a new framework that describes time-dependent fluxes. In this paper, we present such a framework for dynamic metabolic flux analysis (DMFA) at metabolic non-steady state. The DMFA modeling framework was applied to a previously collected data set, consisting of concentration measurements and off-gas analysis data, from a fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol. The DMFA model was applied successfully and time-dependent flux profiles were generated. Statistical analysis of the model was conducted allowing, for the first time, determination of flux confidence intervals and parameter sensitivities under dynamic flux conditions. Having demonstrated the validity of the linear flux mappings, our current work involves the application of non-linear flux mapping (e.g. exponential flux mapping) and analysis of dynamic isotopic tracer experiments.