275734 Rational Design of 13C-Labeling Experiments for Metabolic Flux Analysis Using Elementary Metabolite Unit-Basis Vectors (EMU-BV)

Wednesday, October 31, 2012: 3:33 PM
Somerset East (Westin )
Maciek R. Antoniewicz, Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE and Scott B. Crown, Chemical Engineering, University of Delaware, Newark

13C-Tracer selection is an important step in conducting 13C-metabolic flux analysis (13C-MFA) studies; however, current methods are restricted to trial-and-error approaches, which commonly focus on an arbitrary subset of the tracer design space. To effectively select optimal tracers, there is a pressing need for new rational approaches. Towards this end, we have introduced the concept of elementary metabolite unit basis vectors (EMU-BV). We demonstrate that any metabolite in a network model can be described as a linear combination of EMU-BVs, where the corresponding coefficients indicate the fractional contribution of the EMU-BV to the product metabolite. The strength of our approach is the decoupling of the substrate labeling, i.e. the EMU-BVs, from the dependence on free fluxes, i.e. the coefficients. We demonstrate that flux observability depends inherently on the number of independent EMU-BVs and the sensitivities of coefficients with respect to free fluxes.

The EMU-BV methodology was applied to design tracer experiments in microbial and mammalian systems of interest. First, we applied it to a model of HEK-293 metabolism to select optimal tracers for elucidating two key fluxes, the oxidative pentose phosphate pathway (oxPPP) and pyruvate carboxylase (PC) fluxes. Through efficient grouping of coefficient sensitivities, simple tracer selection rules were derived for high-resolution of the fluxes. The approach resulted in a significant reduction of the number of possible tracers and the feasible tracers were evaluated using numerical simulations. Two optimal, novel tracers were identified, specifically [2,3,4,5,6-13C]glucose for elucidating oxPPP flux and [3,4-13C]glucose for elucidating PC flux. The novel tracers improved confidence intervals of the estimated fluxes by 3- to 10-fold compared to currently used tracers. Secondly, we investigated flux branch points in microbial metabolism. In particular, we developed a high-precision method to estimate the oxidative PP pathway, Entner Doudoroff, and glycolysis fluxes with a single tracer experiment. Using glycolysis intermediates as measurements, candidate tracers were identified and numerical simulations narrowed the candidate list to a handful of optimal tracers. Experimental determination of the split ratios was conducted in two model organisms, E. coli and S. cerevisiae, to validate the modeling predictions. In summary, our work highlights the power of rational selection of isotopic tracers and provides a roadmap for high resolution flux measurements.

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