Development of a Liquid Chromatography–High Resolution Mass Spectrometry Metabolomics Method with High Specificity for Metabolite Identification Using All Ion Fragmentation Acquisition

High-resolution
mass spectrometry (HRMS)-based metabolomics approaches
have made significant advances. However, metabolite identification
is still a major challenge with significant bottleneck in translating
metabolomics data into biological context. In the current study, a
liquid chromatography (LC)–HRMS metabolomics method was developed
using an all ion fragmentation (AIF) acquisition approach. To increase
the specificity in metabolite annotation, four criteria were considered:
(i) accurate mass (AM), (ii) retention time (RT), (iii) MS/MS spectrum,
and (iv) product/precursor ion intensity ratios. We constructed an
in-house mass spectral library of 408 metabolites containing AMRT
and MS/MS spectra information at four collision energies. The percent
relative standard deviations between ion ratios of a metabolite in
an analytical standard vs sample matrix were used as an additional
metric for establishing metabolite identity. A data processing method
for targeted metabolite screening was then created, merging m/z, RT, MS/MS, and ion ratio information
for each of the 413 metabolites. In the data processing method, the
precursor ion and product ion were considered as the quantifier and
qualifier ion, respectively. We also included a scheme to distinguish
coeluting isobaric compounds by selecting a specific product ion as
the quantifier ion instead of the precursor ion. An advantage of the
current AIF approach is the concurrent collection of full scan data,
enabling identification of metabolites not included in the database.
Our data acquisition strategy enables a simultaneous mixture of database-dependent
targeted and nontargeted metabolomics in combination with improved
accuracy in metabolite identification, increasing the quality of the
biological information acquired in a metabolomics experiment.