Large-scale lipid analysis with C=C location and sn-position isomer resolving power
Lipids play a pivotal role in biological processes and lipid analysis by mass spectrometry (MS) has significantly advanced lipidomic studies. While the structure specificity of lipid analysis proves to be critical for studying the biological functions of lipids, current mainstream methods for large-...
Gespeichert in:
Veröffentlicht in: | Nature communications 2020-01, Vol.11 (1), p.375-375, Article 375 |
---|---|
Hauptverfasser: | , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Lipids play a pivotal role in biological processes and lipid analysis by mass spectrometry (MS) has significantly advanced lipidomic studies. While the structure specificity of lipid analysis proves to be critical for studying the biological functions of lipids, current mainstream methods for large-scale lipid analysis can only identify the lipid classes and fatty acyl chains, leaving the C=C location and
sn
-position unidentified. In this study, combining photochemistry and tandem MS we develop a simple but effective workflow to enable large-scale and near-complete lipid structure characterization with a powerful capability of identifying C=C location(s) and
sn
-position(s) simultaneously. Quantitation of lipid structure isomers at multiple levels of specificity is achieved and different subtypes of human breast cancer cells are successfully discriminated. Remarkably, human lung cancer tissues can only be distinguished from adjacent normal tissues using quantitative results of both lipid C=C location and
sn
-position isomers.
Coupling photochemical derivatization with tandem mass spectrometry enables C=C-isomer resolved lipidomics. Here, the authors further develop this approach into a shotgun lipidomics workflow that allows simultaneous characterization of lipid C=C locations and
sn
-positions in complex biological samples. |
---|---|
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-019-14180-4 |