Nontargeted Identification of Tracer Incorporation in High-Resolution Mass Spectrometry

“Fluxomics”
refers to the systematic analysis of
metabolic fluxes in a biological system and may uncover novel dynamic
properties of metabolism that remain undetected in conventional metabolomic
approaches. In labeling experiments, tracer molecules are used to
track changes in the isotopologue distribution of metabolites, which
allows one to estimate fluxes in the metabolic network. Because unidentified
compounds cannot be mapped on pathways, they are often neglected in
labeling experiments. However, using recent developments in de novo
annotation may allow to harvest the information present in these compounds
if they can be identified. Here, we present a novel tool (HiResTEC)
to detect tracer incorporation in high-resolution mass spectrometry
data sets. The software automatically extracts a comprehensive, nonredundant
list of all compounds showing more than 1% tracer incorporation in
a nontargeted fashion. We explain and show in an example data set
how mass precision and other filter heuristics, calculated on the
raw data, can efficiently be used to reduce redundancy and noninformative
signals by 95%. Ultimately, this allows to quickly investigate any
labeling experiment for a complete set of labeled compounds (here
149) with acceptable false positive rates. We further re-evaluate
a published data set from liquid chromatography-electrospray ionization
(LC-ESI) to demonstrate broad applicability of our tool and emphasize
importance of quality control (QC) tests. HiResTEC is provided as
a package in the open source software framework R and is freely available
on CRAN.