All-in-one Complement Isobaric Mass Tag Enables Accurate Lipid Identification and Quantification with sn-Position, C=C Location and Configuration Isomer Resolution

Lipids are essential biomolecules that not only constitute the fundamental building blocks of cells but also act as critical energy reservoirs and signaling mediators. Dysregulation of lipid metabolism is closely associated with various diseases, including cardiovascular, neurodegenerative disorder, and cancer. Lipids display extraordinary structural diversity, with isomers arising from different subclasses, fatty acyl chain lengths, sn-position, and position and configuration of C=C. This structural complexity, combined with dynamic regulations of lipid metabolism, presents significant challenges to elucidating lipid reprogramming mechanism.
Here, we present a novel complement isobaric mass tag, tandem balance loss tag (TBLT), which enables simultaneous chemical structural characterizations and accurate relative quantification at the isomer level. TBLT is composed of a reactive group, a mass balancer, and a mass reporter unit, linked by a newly designed cleavable bond. Unsaturated lipids are first derivatized via aziridination, converting C=C bonds to aziridines, followed by TBLT labeling. Upon MS/MS, the balancer dissociates from TBLT-labeled lipids, generating complementary reporter ions in conjunction with different diagnostic ions that pinpoint C=C position, cis/trans configuration, and sn-position. Distinct reporter ions generated from different isobaric tag-labeled lipids allow accurate relative quantitation based on reporter ion ratios. Using this approach, we achieved identification and quantification across 10 lipid classes with high sensitivity, a wide dynamic range of two orders of magnitude, and excellent accuracy in resolving structurally similar lipids and isomers. With 4-plex TBLT tags, this platform enables high-throughput and quantitative lipidomic analyses of complex biological samples with deep isomer resolution, providing powerful opportunities for biomarker discovery in disease diagnosis as well as mechanistic insights into lipid metabolism.