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Lipid Discovery by Combinatorial Screening and Untargeted LC-MS/MS
Date Issued
2016-06-17
Date Available
2016-07-25T12:28:18Z
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.
Other Sponsorship
Italian Ministry of Education, University and Research
Deutsche Forschungsgemeinschaft (DFG)
Type of Material
Journal Article
Publisher
Nature Publishing Group
Journal
Scientific Reports
Volume
6
Start Page
27920
End Page
27926
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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Lipid_Discovery_by_Combinatorial_Screening_-_designed.pdf
Size
997.37 KB
Format
Adobe PDF
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