Combining Isotopologue Workflows and Simultaneous Multidimensional Separations to Detect, Identify, and Validate Metabolites in Untargeted Analyses

While the combination of liquid chromatography
and tandem mass
spectrometry (LC-MS/MS) is commonly used for feature annotation in
untargeted omics experiments, ensuring these prioritized features
originate from endogenous metabolism remains challenging. Isotopologue
workflows, such as isotopic ratio outlier analysis (IROA), mass isotopomer
ratio analysis of U-13C labeled extracts (MIRACLE), and
credentialing incorporate isotopic labels directly into metabolic
precursors, guaranteeing that all features of interest are unequivocal
byproducts of cellular metabolism. Furthermore, comprehensive separation
and annotation of small molecules continue to challenge the metabolomics
field, particularly for isomeric systems. In this paper, we evaluate
the analytical utility of incorporating ion mobility spectrometry
(IMS) as an additional separation mechanism into standard LC-MS/MS
isotopologue workflows. Since isotopically labeled molecules codrift
in the IMS dimension with their 12C versions, LC-IMS-CID-MS
provides four dimensions (LC, IMS, MS, and MS/MS) to directly investigate
the metabolic activity of prioritized untargeted features. Here, we
demonstrate this additional selectivity by showcasing how a preliminary
data set of 30 endogeneous metabolites are putatively annotated from
isotopically labeled Escherichia coli cultures when analyzed by LC-IMS-CID-MS. Metabolite annotations
were based on several molecular descriptors, including accurate mass
measurement, carbon number, annotated fragmentation spectra, and collision
cross section (CCS), collectively illustrating the importance of incorporating
IMS into isotopologue workflows. Overall, our results highlight the
enhanced separation space and increased annotation confidence afforded
by IMS for metabolic characterization and provide a unique perspective
for future developments in isotopically labeled MS experiments.