Isotopomer Spectral Analysis: Utilizing Nonlinear Models in Isotopic Flux Studies.

We present the principles underlying the isotopomer spectral analysis (ISA) method for evaluating biosynthesis using stable isotopes. ISA addresses a classic conundrum encountered in the use of radioisotopes to estimate biosynthesis rates whereby the information available is insufficient to estimate biosynthesis. ISA overcomes this difficulty capitalizing on the additional information available from the mass isotopomer labeling profile of a polymer. ISA utilizes nonlinear regression to estimate the two unknown parameters of the model. A key parameter estimated by ISA represents the fractional contribution of the tracer to the precursor pool for the biosynthesis, D. By estimating D in cells synthesizing lipids, ISA quantifies the relative importance of two distinct pathways for flux of glutamine to lipid, reductive carboxylation, and glutaminolysis. ISA can also evaluate the competition between different metabolites, such as glucose and acetoacetate, as precursors for lipogenesis and thereby reveal regulatory properties of the biosynthesis pathway. The model is flexible and may be expanded to quantify sterol biosynthesis allowing tracer to enter the pathway at three different positions, acetyl CoA, acetoacetyl CoA, and mevalonate. The nonlinear properties of ISA provide a method of testing for the presence of gradients of precursor enrichment illustrated by in vivo sterol synthesis. A second ISA parameter provides the fraction of the polymer that is newly synthesized over the time course of the experiment. In summary, ISA is a flexible framework for developing models of polymerization biosynthesis providing insight into pools and pathway that are not easily quantified by other techniques.