Bidirectional reaction steps in metabolic networks: IV. Optimal design of isotopomer labeling experiments

This article generalizes the statistical tools for the evaluation of carbon -labeling experiments that have been developed for the case of positional e nrichment: systems in part It of this series to the general case of isotopo mer systems. For this purpose, a new generalized measurement equation is in troduced that can describe all kinds of measured data, like positional enri chments, relative C-13 nuclear magnetic resonance (C-13 NMR) multiplet inte nsities, or mass isotopomer fractions produced with mass spectroscopy (MS) instruments. Then, to facilitate the specification of the various measureme nt procedures available, a new flexible textual notation is introduced from which the complicated generalized measurement equations are generated auto matically. Based on these measurement equations, a statistically optimal fl ux estimator is established and parameter covariance matrices for the flux estimation are computed. Having implemented these tools, different kinds of labeling experiments can be compared by using statistical quality measures . A general framework for the optimal design of carbon-labeling experiments is established on the basis of this method. As an example it is applied to the Corynebacterium network from part II extended by various NMR and MS me asurements. In particular, the positional enrichment, multiplet, or mass is otopomer measurements with the greatest information content for flux estima tion are computed (measurement design) and various differently labeled inpu t substrates are compared with respect to flux estimation (input design), i t is examined in detail how the measurement procedure influences the estima tion quality of specific fluxes like the pentose phosphate pathway influx. (C) 1999 John Wiley tk Sons, Inc.