Article ; Online: Enhancing the Signal-to-Noise of Diagnostic Fragment Ions of Unsaturated Glycerophospholipids via Precursor Exclusion Ultraviolet Photodissociation Mass Spectrometry (PEx-UVPD-MS).
2022 Volume 94, Issue 32, Page(s) 11352–11359
Abstract: Understanding and elucidating the diverse structures and functions of lipids has motivated the development of many innovative tandem mass spectrometry (MS/MS) strategies. Higher-energy activation methods, such as ultraviolet photodissociation (UVPD), ... ...
Abstract | Understanding and elucidating the diverse structures and functions of lipids has motivated the development of many innovative tandem mass spectrometry (MS/MS) strategies. Higher-energy activation methods, such as ultraviolet photodissociation (UVPD), generate unique fragment ions from glycerophospholipids that can be used to perform in-depth structural analysis and facilitate the deconvolution of isomeric lipid structures in complex samples. Although detailed characterization is central to the correlation of lipid structure to biological function, it is often impeded by the lack of sufficient instrument sensitivity for highly bioactive but low-abundance phospholipids. Here, we present precursor exclusion (PEx) UVPD, a simple yet powerful technique to enhance the signal-to-noise (S/N) of informative low-abundance fragment ions produced from UVPD of glycerophospholipids. Through the exclusion of the large population of undissociated precursor ions with an MS |
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MeSH term(s) | Animals ; Cattle ; Chromatography, Liquid/methods ; Glycerophospholipids/chemistry ; Ions ; Tandem Mass Spectrometry/methods ; Ultraviolet Rays |
Chemical Substances | Glycerophospholipids ; Ions |
Language | English |
Publishing date | 2022-08-02 |
Publishing country | United States |
Document type | Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't |
ZDB-ID | 1508-8 |
ISSN | 1520-6882 ; 0003-2700 |
ISSN (online) | 1520-6882 |
ISSN | 0003-2700 |
DOI | 10.1021/acs.analchem.2c02128 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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