Untargeted extraction of metabolites 13C labeling profiles from time course labeling switch experiment

ABSTRACT: Dynamic isotope labeling data provide crucial information about the operation of metabolic pathways, and are commonly generated via liquid chromatography mass spectrometry (LC-MS). Metabolome-wide analysis is challenging as it requires grouping of metabolite features over different samples. We developed DynaMet for fully automated investigations of isotope labeling experiments from LC-high resolution MS raw data. DynaMet enables untargeted extraction of metabolite labeling profiles and provides integrated tools for expressive data visualization. For this study we generated labeling data of the model strain Bacillus methanolicus from 13C methanol resulting in complex spectra in multi carbon compounds. Analysis of two biological replicates revealed high robustness and reproducibility of the pipeline. In total, DynaMet extracted 386 features showing dynamic labeling within ten minutes. Of these features, 357 could be fitted by implemented kinetic models. Feature identification against KEGG database resulted in 247 matches covering multiple pathways of core metabolism and major biosynthetic routes. The study results reported here are only a summary. To reproduce the complete results including plots, DynaMet software is required.

INSTRUMENT(S): LTQ Orbitrap Classic (Thermo Scientific)

SUBMITTER: Patrick Kiefer 

PROVIDER: MTBLS228 | MetaboLights | 2015-10-19

REPOSITORIES: MetaboLights