Isotopic Ratio Outlier Analysis of the S. cerevisiae Metabolome Using Accurate Mass Gas Chromatography/Time-of-Flight Mass Spectrometry: A New Method for Discovery

Qiu, Y.; Moir, R.; Willis, I.; et al.

Analyte identification is a major bottleneck in metabolomics studies. The isotopic ratio outlier analysis (IROA) technique, which utilizes full metabolic ¹³C labeling to distinguish between two cell populations (i.e., experimental and control), has proven valuable in LC-MS analysis to discriminate between metabolites of biological and nonbiological (i.e., chemical artifacts and noise) origin. Here, Kurland, I. et al. demonstrates the application of the IROA labeling technology to GC-MS profiling (via electron impact and chemical ionization) of the yeast (S. cerevisiae) metabolome. Using accurate mass GC-MS data in combination with a newly developed algorithm for formula elucidation, the structure/identity of 126 yeast metabolites was characterized. This catalog represents a first step toward the creation of clean spectral libraries for improved metabolite identification of experimental samples.