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

Reputable Mentor II
Reputable Mentor II
Mesut Bilgin1,† , Petra Born1, Filomena Fezza2,3, Michael Heimes4, Nicolina Mastrangelo5, NicolaiWagner1, Carsten Schultz4, Mauro Maccarrone3,5, Suzanne Eaton1, André Nadler1,4, MatthiasWilm6 & Andrej Shevchenko1
Scientific Reports 6, Article number: 27920 (2016) 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.
1Max Planck Institute for Cell Biology and Genetics, Pfotenhauerstraβe 108, 01307 Dresden, Germany. 2 Department of Experimental Medicine and Surgery, Tor Vergata University of Rome, via Montpellier 1, 00133, Rome, Italy. 3European Center for Brain Research/Fondazione Santa Lucia, via del Fosso di Fiorano 65, 00143 Rome, Italy. 4European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany. 5Department of Medicine, Campus Bio-Medico University of Rome, Via Alvaro del Portillo 21, 00128 Rome. 6Conway Institute of Biomolecular and Biomedical Research, University College Dublin, 4 Dublin, Ireland. † Present address: Unit for Cell Death and Metabolism, Center for Autophagy, Recycling and Disease, Danish Cancer Society Research Center, DK-2100, Copenhagen, Denmark.
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‎10-15-2021 07:41 AM
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