Mass isotopomer distribution analysis at eight years: theoretical, analytic, and experimental considerations

1 Department of Nutritional Sciences, University of California at Berkeley, Berkeley 94720; and 2 Division of Endocrinology and Metabolism, Department of Medicine, University of California, San Francisco, California 94110 Mass isotopomer distribution analysis (MIDA) is a technique for measuring the synthesis of biological polymers. First developed approximately eight years ago, MIDA has been used for measuring the synthesis of lipids, carbohydrates, and proteins. The technique involves quantifying by mass spectrometry the relative abundances of molecular species of a polymer differing only in mass (mass isotopomers), after introduction of a stable isotope-labeled precursor. The mass isotopomer pattern, or distribution, is analyzed according to a combinatorial probability model by comparing measured abundances to theoretical distributions predicted from the binomial or multinomial expansion. For combinatorial probabilities to be applicable, a labeled precursor must therefore combine with itself in the form of two or more repeating subunits. MIDA allows dilution in the monomeric (precursor) and polymeric (product) pools to be determined. Kinetic parameters can then be calculated (e.g., replacement rate of the polymer, fractional contribution from the endogenous biosynthetic pathway, absolute rate of biosynthesis). Several issues remain unresolved, however. We consider here the impact of various deviations from the simple combinatorial probability model of biosynthesis and describe the analytic requirements for successful use of MIDA. A formal mathematical algorithm is presented for generating tables and equations (Appendix), on the basis of which effects of various confounding factors are simulated. These include variations in natural isotope abundances, isotopic disequilibrium in the precursor pool, more than one biosynthetic precursor pool, incorrect values for number of subunits present, and concurrent measurement of turnover from exogenously labeled polymers. We describe a strategy for testing whether isotopic inhomogeneity (e.g., an isotopic gradient or separate biosynthetic sites) is present in the precursor pool by comparing higher-mass (multiply labeled) to lower-mass (single- and double-labeled) isotopomer patterns. Also, an algebraic correction is presented for calculating fractional synthesis when an incomplete ion spectrum is monitored, and an approach for assessing the sensitivity of biosynthetic parameters to measurement error is described. T