Duplex Paternò-Büchi Isobaric Reagents for One-Step C═C-Resolved Lipid Isomer Quantification

Lipid isomeromics, the systematic structural and quantitative profiling of lipid isomers, is needed to determine how subtle variations in lipid structure contribute to metabolic regulation and disease. Carbon-carbon double-bond (C═C) positional isomers can have distinct biological functions despite sharing identical masses and sum compositions; however, their quantitative analysis remains challenging. Here, we introduce duplex Paternò-Büchi (PB)-derived isobaric mass tags, termed AMPE-tags, that integrate lipid derivatization, C═C positional-isomer identification, and relative quantification in a single photochemical step. The tags combine a PB-reactive ketone, an isotope-encoded methylpiperazine reporter, and a mass-balancing group within one molecular scaffold. Photoirradiation installs the tag directly at lipid C═C bonds to form oxetane-containing PB products. Higher-energy collisional dissociation of intact PB products generates reporter ions for total-level quantification, whereas collision-induced dissociation produces C═C position-specific diagnostic ions that retain the reporter-bearing tag. Subsequent MS3 fragmentation of these diagnostic ions releases reporter ions directly associated with individual positional isomers, enabling isomer-level quantification without chromatographic resolution of C═C positional isomers. The duplex tags provided accurate relative quantification of unsaturated fatty acids over a 200-fold concentration-ratio range and in structurally diverse mixtures containing PB regioisomers and minor photochemical byproducts. Application to visceral adipose tissue from mice fed chow or high-fat diets identified 18 unsaturated fatty acids and 37 C═C positional isomers, revealing diet-associated isomer remodeling that was masked at the total-fatty-acid level, including opposing changes among FA 18:1 positional isomers. These PB-derived isobaric reagents provide a chemical platform for duplex lipid isomeromics and enable biologically informative quantification beyond conventional sum-composition lipid analysis.