1. Lipid Discovery by Combinatorial Screening and Untargeted LC-MS/MS
- Author
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Mauro Maccarrone, Suzanne Eaton, André Nadler, Mesut Bilgin, Filomena Fezza, Petra Born, Matthias Wilm, Carsten Schultz, Nicolai Wagner, Michael Heimes, Andrej Shevchenko, and Nicolina Mastrangelo
- Subjects
0301 basic medicine ,Animals ,Chromatography, Liquid ,Endocannabinoids ,Kidney ,Lipids ,Rats ,Software ,Tandem Mass Spectrometry ,Rat kidney ,Endogeny ,Tandem mass spectrometry ,01 natural sciences ,Article ,03 medical and health sciences ,Peptide mass fingerprinting ,Lc ms ms ,Settore BIO/10 ,Chromatogram correlation ,Chromatography ,Liquid ,Multidisciplinary ,Mass spectrometry ,Chemistry ,010401 analytical chemistry ,Chromatography liquid ,Endocannabinoid system ,Hedgehog signaling pathway ,0104 chemical sciences ,All ion fragmentation ,030104 developmental biology ,Biochemistry ,Screening ,lipids (amino acids, peptides, and proteins) - Abstract
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. Italian Ministry of Education, University and Research Deutsche Forschungsgemeinschaft (DFG)
- Published
- 2016
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