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

Author(s)
Bilgin, Mesut  
Born, Petra  
Fezza, Filomena  
Wilm, Matthias  
et al.  
Uri
http://hdl.handle.net/10197/7785
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
Subjects

Lipids

Mass spectrometry

Screening

Chromatogram correlat...

All ion fragmentation...

DOI
10.1038/srep27920
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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Lipid_Discovery_by_Combinatorial_Screening_-_designed.pdf

Size

997.37 KB

Format

Adobe PDF

Checksum (MD5)

4a700da9d2712aeea999951d688f6679

Owning collection
Conway Institute Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
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