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

Abstract

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 .