Effect of Error Propagation in Stable Isotope Tracer Studies: An Approach for Estimating Impact on Apparent Biochemical Flux

Abstract Stable isotope tracers are widely used to quantify metabolic rates, and yet a limited number of studies have considered the impact of analytical error on estimates of flux. For example, when estimating the contribution of de novo lipogenesis, one typically measures a minimum of four isotope ratios, i.e., the precursor and product labeling pre- and posttracer administration. This seemingly simple problem has 1 correct solution and 80 erroneous outcomes. In this report, we outline a methodology for evaluating the effect of error propagation on apparent physiological endpoints. We demonstrate examples of how to evaluate the influence of analytical error in case studies concerning lipid and protein synthesis; we have focused on 2 H 2 O as a tracer and contrast different mass spectrometry platforms including GC-quadrupole-MS, GC-pyrolysis-IRMS, LC-quadrupole-MS, and high-resolution FT-ICR-MS. The method outlined herein can be used to determine how to minimize variations in the apparent biology by altering the dose and/or the type of tracer. Likewise, one can facilitate biological studies by estimating the reduction in the noise of an outcome that is expected for a given increase in the number of replicate injections.