Isotopic Studies of Metabolic Systems by Mass Spectrometry: Using Pascal’s Triangle To Produce Biological Standards with Fully Controlled Labeling Patterns

Mass spectrometry (MS) is widely used for isotopic studies of metabolism in which detailed information about biochemical processes is obtained from the analysis of isotope incorporation into metabolites. The biological value of such experiments is dependent on the accuracy of the isotopic measurements. Using MS, isotopologue distributions are measured from the quantitative analysis of isotopic clusters. These measurements are prone to various biases, which can occur during the experimental workflow and/or MS analysis. The lack of relevant standards limits investigations of the quality of the measured isotopologue distributions. To meet that need, we developed a complete theoretical and experimental framework for the biological production of metabolites with fully controlled and predictable labeling patterns. This strategy is valid for different isotopes and different types of metabolisms and organisms, and was applied to two model microorganisms, Pichia augusta and Escherichia coli, cultivated on ¹³C-labeled methanol and acetate as sole carbon source, respectively. The isotopic composition of the substrates was designed to obtain samples in which the isotopologue distribution of all the metabolites should give the binomial coefficients found in Pascal’s triangle. The strategy was validated on a liquid chromatography–tandem mass spectrometry (LC-MS/MS) platform by quantifying the complete isotopologue distributions of different intracellular metabolites, which were in close agreement with predictions. This strategy can be used to evaluate entire experimental workflows (from sampling to data processing) or different analytical platforms in the context of isotope labeling experiments

Improved Isotopic Profiling by Pure Shift Heteronuclear 2D <i>J</i>‑Resolved NMR Spectroscopy

Quantitative information on the carbon isotope content of metabolites is essential for flux analysis. Whereas this information is in principle present in proton NMR spectra through both direct and long-range heteronuclear coupling constants, spectral overlap and homonuclear coupling constants both hinder its extraction. We demonstrate here how pure shift 2D <i>J</i>-resolved NMR spectroscopy can simultaneously remove the homonuclear couplings and separate the chemical shift information from the heteronuclear coupling patterns. We demonstrate the power of this method on cell lysates from different bacterial cultures and investigate in detail the branched chain amino acid biosynthesis