Ultrasensitive Detection of Tissue Lipids at the Femtomole Scale Using Low-Microflow Targeted Lipidomics

Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics is a widely adopted method for profiling and quantifying changes in cellular and tissue lipids in response to biological and pharmacological perturbations. Effective chromatographic separation is critical for lipid analysis, yet conventional LC flow rates often compromise either sensitivity (analytical flow) or throughput (nanoflow). Microflow chromatography has proven to be an effective intermediate option; however, few lipidomic methods have been developed on this scale. Here, we describe an optimized low-microflow (25 μL/min) LC method coupled to a triple-quadrupole mass spectrometer for sensitive targeted lipidomic analysis. A 0.5 mm inner diameter C12 column provides a stable and reproducible separation across 13 different lipid classes with femtomolar limits of detection and quantitation. Using four short (∼5 min) optimized gradients, we achieve detection of over 500 endogenous lipid molecular species across six mouse tissues, with a median CV of 13% across 36 biologically independent samples. The C12 stationary phase increases the coverage of monoacylglycerols and diacylglycerols (DAGs), the nonpolar lipid classes that are often underrepresented in existing workflows. We applied low-microflow targeted lipidomics to discover an unexpected decrease in polyunsaturated DAGs in tissues from DAG lipase-beta knockout compared with wild-type mice.