Implementation of Nano Flow Chromatography Coupled to Mass Spectrometry as a Reliable and Sensitive Discovery Lipidomics Platform

RATIONALE: Untargeted lipidomics is commonly performed at analytical flow rates, which consume more solvent and may require higher on-column sample loads when sensitivity is limited by analyte abundance. Nano flow separations use lower flow rates and sample loads, reducing solvent consumption and facilitating improved electrospray ionization. We present here practical considerations for implementing a routine nano flow lipidomics workflow. METHODS: Bovine liver total lipid extract was spiked with SPLASH Lipidomix internal standards and analyzed by nano flow and high flow liquid chromatography coupled to a high-resolution accurate mass Orbitrap-based mass spectrometer. Full-scan polarity switching was used for untargeted profiling, and the AcquireX Deep Scan workflow was applied to support data-dependent MS/MS acquisition in the complex matrix. A SPLASH dilution series was analyzed in triplicate injections to compare analytical response across on-column loads between the two workflows. RESULTS: At 25 ng on-column, nano flow yielded 1266 total lipid annotations and 835 high-quality annotations, compared with 919 total and 518 high-quality annotations for high flow at 100 ng. Unintentional fragmentation decreased under nano flow conditions by 21%-31% across the representative lipid species evaluated. The use of nano flow allowed for the detection of lower on-column loads across several standards, extending the lower end of the response range by up to 40-fold compared with high flow analyses. CONCLUSIONS: Nano flow lipidomics improved sensitivity for untargeted analysis by increasing the number of lipid annotations, reducing unintentional fragmentation, and extending the analytical response to lower on-column loads. Together with practical guidance around sample preparation, injection volume, washing, and equilibration, these results support nano flow chromatography as a sensitive and reliable approach for sample-limited untargeted lipidomics.