Untargeted Profiling of Tracer-Derived Metabolites
Using Stable Isotopic Labeling and Fast Polarity-Switching LC–ESI-HRMS
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Abstract
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 <sup>13</sup>C<sub>9</sub>-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 ionization
mode) corresponding to 139 metabolites were detected. The benefit
of fast polarity switching was evident, with 32 and 58 of these metabolites
having exclusively been detected in the positive and negative modes,
respectively. Moreover, for 19 of the remaining 49 phenylalanine-derived
metabolites, the assignment of ion species and, thus, molecular weight
was possible only by the use of complementary features of the two
ion polarity modes. Statistical evaluation showed that treatment with
DON increased or decreased the abundances of many detected metabolites