Using isotopomer path tracing to quantify metabolic fluxes in pathway models containing reversible reactions

As a more complete picture of the genetic and enzymatic composition of cell s becomes available, there is a growing need to describe how cellular regul atory elements interact with the cellular environment to affect cell physio logy. One means for describing intracellular regulatory mechanisms is concu rrent measurement of multiple metabolic pathways and their interactions by metabolic flux analysis. Flux of carbon through a metabolic pathway respond s to all cellular regulatory systems, including changes in enzyme and subst rate concentrations, enzyme activation or inhibition, and ultimately generi c control. The extent to which metabolic flux analysis can describe cellula r physiology depends on the number of pathways in the model and the quality of the data. Intracellular information is obtainable from isotopic tracer experiments, the most extensive being the determination of the isotopomer d istribution, or specific labeling pattern, of intracellular metabolites. We present a rapid and novel solution method that determines the flux of carb on through complex pathway models using isotopomer data. This time-consumin g problem was solved with the introduction of isotopomer path tracing, whic h drastically reduces the number of isotopomer variables to the number of i sotopomers observed experimentally. We propose a partitioned solution metho d that takes advantage of the nearly linear relationship between fluxes and isotopomers. Whereas the stoichiometric matrix and the isotopomer matrix a re invertible, simulated annealing and the Newton-Raphson method are used f or the nonlinear components. Reversible reactions are described by a new pa rameter, the association factor, which scales hyperbolically with the rate of metabolite exchange. Automating the solution method permits a variety of models to be compared, thus enhancing the accuracy of results. A simplifie d example that contains all of the complexities of a comprehensive pathway model is presented. (C) John Wiley & Sons, Inc.