Improved preanalytical workflow for pancreatic tissue lipidomics: insights into lipid stability and polar lipid recovery

Abstract

Tissue lipidomics is a rapidly advancing field in clinical and biomedical research that provides crucial information on the lipid-driven molecular mechanisms underlying physiological and pathological conditions. However, accurate MS-based analysis requires careful preanalytical handling due to the metabolic activity of tissue and analyte heterogeneity. Here, we introduce a robust tissue processing workflow with the pancreas as a model of a highly metabolically active organ. First, we evaluate lipid stability in porcine pancreatic tissue stored on ice, observing significant lysophospholipid formation after 60–120 min. Then, we compare sample handling using ice versus liquid nitrogen for both porcine and mouse pancreatic tissues, illustrating that processing temperature affects low-abundant lipid class levels, with liquid nitrogen providing better preservation. To enhance polar lipidome analysis, we optimize a hexane-methanol liquidliquid extraction protocol and find that the addition of 2% (v/v) water to methanol yields the most effective recovery and reproducibility. Finally, the workflow is applied to mouse pancreatic tissue samples, enabling the identification of 209 polar lipid species across 10 classes, with 124 species quantified. Among these, hexosylceramides show clear sex-specific variation.