LipidHunter Identifies Phospholipids by High-Throughput Processing of LC-MS and Shotgun Lipidomics Datasets

Lipids
are dynamic constituents of biological systems, rapidly
responding to any changes in physiological conditions. Thus, there
is a large interest in lipid-derived markers for diagnostic and prognostic
applications, especially in translational and systems medicine research.
As lipid identification remains a bottleneck of modern untargeted
lipidomics, we developed LipidHunter, a new open source software for
the high-throughput identification of phospholipids in data acquired
by LC-MS and shotgun experiments. LipidHunter resembles a workflow
of manual spectra annotation. Lipid identification is based on MS/MS
data analysis in accordance with defined fragmentation rules for each
phospholipid (PL) class. The software tool matches product and neutral
loss signals obtained by collision-induced dissociation to a user-defined
white list of fatty acid residues and PL class-specific fragments.
The identified signals are tested against elemental composition and
bulk identification provided via LIPID MAPS search. Furthermore, LipidHunter
provides information-rich tabular and graphical reports allowing to
trace back key identification steps and perform data quality control.
Thereby, 202 discrete lipid species were identified in lipid extracts
from rat primary cardiomyocytes treated with a peroxynitrite donor.
Their relative quantification allowed the monitoring of dynamic reconfiguration
of the cellular lipidome in response to mild nitroxidative stress.
LipidHunter is available free for download at https://bitbucket.org/SysMedOs/lipidhunter.