Epoxidation-Enhanced Charge-Switch Derivatization for Rapid Profiling of Monounsaturated Fatty Acid Isomers
Year: 2025
Type: article
Abstract: Structural isomerism in monounsaturated fatty acids (MUFAs) presents a persistent challenge in lipidomics due to limited chromatographic resolution and indistinguishable mass spectral profiles. Moreover, many methods that overcome these limitations require specialized instruments or additional apparatus that are typically not available for those using standard lipidomics core facilities. We report a streamlined LC-MS/MS method that integrates N -(4-aminomethylphenyl)pyridinium (AMP)-based charge-switch derivatization with meta-chloroperoxybenzoic acid (mCPBA) epoxidation to enable rapid and sensitive profiling of MUFA double bond positional isomers. Charge-switching enables enhanced detection of fatty acids, while epoxidation improves chromatographic resolution and produces diagnostic fragmentation patterns upon collision-induced dissociation (CID), enabling precise localization of double bond positions. The optimized workflow achieves baseline separation of 16:1, 18:1, and 20:1 MUFA isomers within a 20 min gradient, with reproducible retention times and consistent epoxide yields. The method also supports partial resolution of polyunsaturated fatty acids (PUFA) and cis / trans isomers. Application to prostate cancer cell lines revealed distinct MUFA i s omer profiles associated with aberrant fatty acid desaturase 2 (FADS2) activity, including elevated n- 10 and n- 12 isomers in tumorigenic lines. These results align with prior studies using other isomer-resolving techniques, validating the method’s analytical performance. This accessible and robust strategy expands the toolkit for lipidomics research, providing a method that is compatible with conventional LC-MS/MS workflows, positioning it as a practical solution for high-resolution isomer analysis in complex biological samples
Source: Analytical Chemistry
Institutions: Victor Chang Cardiac Research Institute, UNSW Sydney
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4417444359