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

Mesut Bilgin, Petra Born, Filomena Fezza, Michael Heimes, Nicolina Mastrangelo, Nicolai Wagner, Carsten Schultz, Mauro Maccarrone, Suzanne Eaton, André Nadler, Matthias Wilm, Andrej Shevchenko

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6 Scopus citations

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.

Original languageEnglish (US)
Article number27920
JournalScientific Reports
Volume6
DOIs
Publication statusPublished - Jun 17 2016
Externally publishedYes

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Cite this

Bilgin, M., Born, P., Fezza, F., Heimes, M., Mastrangelo, N., Wagner, N., ... Shevchenko, A. (2016). Lipid Discovery by Combinatorial Screening and Untargeted LC-MS/MS. Scientific Reports, 6, [27920]. https://doi.org/10.1038/srep27920