Data from: Development, characterization and comparisons of targeted and non-targeted metabolomics methods

The potential of a metabolomics method to detect statistically significant
perturbations in the metabolome of an organism is enhanced by excellent
analytical precision, unequivocal identification, and broad metabolomic
coverage. While the former two metrics are usually associated with
targeted metabolomics and the latter with non-targeted metabolomics, a
systematic comparison of the performance of both approaches has not yet
been carried out. The present work reports on the development and
performance evaluation of separate targeted and non-targeted metabolomics
methods. The targeted approach facilitated determination of 181
metabolites (quantitative analysis of 18 amino acids, 10 biogenic amines,
5 neurotransmitters, 5 nucleobases and semi-quantitative analysis of 50
carnitines, 83 phosphotidylcholines, and 9 sphingomyelins) using
ultra-performance liquid chromatography-tandem mass spectrometry
(UPLC-MS/MS) and flow injection-tandem mass spectrometry (FI-MS/MS).
Method accuracy and/or precision were assessed using replicate samples of
NIST SRM1950 as well as fish liver and brain tissue from Gilthead Bream
(Sparus aurata). The non-target approach involved UPLC-high resolution
(Orbitrap) mass spectrometry (UPLC-HRMS). Testing of ionization mode and
stationary phase revealed that a combination of positive electrospray
ionization and HILIC chromatography produced the largest number of
chromatographic features during non-target analysis. Furthermore, an
evaluation of 4 different sequence drift correction algorithms, and
combinations thereof, revealed that batchCorr produced the best precision
in almost every test. However, even following correction of non-target
data for signal drift, the precision of targeted data was better,
confirming our existing assumptions about the strengths of targeted
metabolomics. Finally, the accuracy of the online MS2-library mzCloud was
evaluated using reference standards for 38 different metabolites. This is
among the few studies that have systematically evaluated the performance
of targeted and non-targeted metabolomics and provides new insight into
the advantages and disadvantages of each approach.