Utilizing MS/MS data for fragmentation pattern analysis within a stable isotope tracer workflow

Abstract

Stable isotope labeling (SIL) coupled with liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is a powerful method for elucidating metabolic pathways and identifying metabolite transformations. However, analysis of untargeted SIL-LC-HRMS data remains challenging due to the complexity and volume of data, as well as difficulties in confidently identifying labeled metabolites. We previously developed SIL tracer software that programmatically identifies and validates stable isotope-labeled metabolites through a novel linear regression strategy, but it lacked the capacity to handle associated tandem mass spectrometry data for fragmentation pattern analysis, which can provide valuable structural information to the found features. I have now developed a unique integration strategy with the SIRIUS mass spectrometry software package to leverage its MS/MS-based structure prediction within our SIL-LC-HRMS data workflow, further enhancing our abilities to elucidate novel metabolic pathways.