Non-Targeted Mass Isotopolome Analysis Using Stable Isotope Patterns to Identify Metabolic Changes.

Abstract

Gas chromatography coupled with mass spectrometry can provide an extensive overview of the metabolic state of a biological system. Analysis of raw mass spectrometry data requires powerful data processing software to generate interpretable results. Here we describe a data processing workflow to generate metabolite levels, mass isotopomer distribution, similarity and variability analysis of metabolites in a nontargeted manner, using stable isotope labeling. Using our data analysis software, no bioinformatic or programming background is needed to generate results from raw mass spectrometry data.