Lipid Discovery by Combinatorial Screening and Untargeted LC-MS/MS

• Published in: Scientific reports 2016-06, Vol.6 (1), p.27920-27920, Article 27920
• Main Authors: Bilgin, Mesut, Born, Petra, Fezza, Filomena, Heimes, Michael, Mastrangelo, Nicolina, Wagner, Nicolai, Schultz, Carsten, Maccarrone, Mauro, Eaton, Suzanne, Nadler, André, Wilm, Matthias, Shevchenko, Andrej
• Format: Article
• Language: English
• Subjects: 631/1647/296; 631/1647/320; 631/45/608; Amino acids; Animals; Chromatography, Liquid - methods; Endocannabinoids - analysis; Fatty acids; Glycerol; Humanities and Social Sciences; Kidney - chemistry; Lipids; Lipids - analysis; multidisciplinary; Rats; Science; Science (multidisciplinary); Software; Tandem Mass Spectrometry - methods
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/srep27920

We present a method for the systematic identification of picogram quantities of new lipids in total extracts of tissues and fluids. It relies on the modularity of lipid structures and applies all-ions fragmentation LC-MS/MS and Arcadiate software to recognize individual modules originating from the same lipid precursor of known or assumed structure. In this way it alleviates the need to recognize and fragment very low abundant precursors of novel molecules in complex lipid extracts. In a single analysis of rat kidney extract the method identified 58 known and discovered 74 novel endogenous endocannabinoids and endocannabinoid-related molecules, including a novel class of N -acylaspartates that inhibit Hedgehog signaling while having no impact on endocannabinoid receptors.