Untargeted Profiling of Tracer-Derived MetabolitesUsing Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS

摘要

An untargeted metabolomics workflow for the detection of metabolites derived from endogenous or exogenous tracer substances is presented. To this end, a recently developed stable isotope-assisted LC–HRMS-based metabolomics workflow for the global annotation of biological samples has been further developed and extended. For untargeted detection of metabolites arising from labeled tracer substances, isotope pattern recognition has been adjusted to account for nonlabeled moieties conjugated to the native and labeled tracer molecules. Furthermore, the workflow has been extended by (i) an optional ion intensity ratio check, (ii) the automated combination of positive and negative ionization mode mass spectra derived from fast polarity switching, and (iii) metabolic feature annotation. These extensions enable the automated, unbiased, and global detection of tracer-derived metabolites in complex biological samples. The workflow is demonstrated with the metabolism of ¹³C9-phenylalanine in wheat cell suspension cultures in the presence of the mycotoxin deoxynivalenol (DON). In total, 341 metabolic features (150 in positive and 191 in negative ionizationmode) corresponding to 139 metabolites were detected. The benefitof fast polarity switching was evident, with 32 and 58 of these metaboliteshaving exclusively been detected in the positive and negative modes,respectively. Moreover, for 19 of the remaining 49 phenylalanine-derivedmetabolites, the assignment of ion species and, thus, molecular weightwas possible only by the use of complementary features of the twoion polarity modes. Statistical evaluation showed that treatment withDON increased or decreased the abundances of many detected metabolites.