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. However, current mainstream methods for large-scale lipid analysis can only identify lipid classes and fatty acyl chains, leaving the C=C location and sn-position unidentified. In this study, we combine photochemistry and tandem MS to develop a simple but effective workflow that enables large-scale and near-complete lipid structure characterization with the powerful capability of identifying C=C locations and sn-positions 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.

• This study presents a PB-MS³ workflow combining photochemistry reaction and tandem MS to simultaneously identifying and quantifying of glycerophospholipids (GPs) with C=C and sn-specificities in a single experiment, achieved by selecting the appropriate PB reagents that promotes the generation of diagnostic ions specific to both sn-positions and C=C locations.
• In terms of biomedical applications, quantitative analysis both GP sn-position and C=C location isomers achieved by this methodology successfully discriminated four subtypes of human breast cancer cells and correctly distinguished NSCLC tissues from normal tissues.
• The developed methodology can be easily implemented for routine analysis, empowering the discovery of biomarkers with a tool revealing rich lipid structure details.