Identifying lipidomic key species in MS-data, applied to hepatocyte lipid droplets from stressed mouse models

Lipid droplets are considered to be the hub for storage and metabolism of cellular lipids. In previous work we have phenotyped the lipidome of murine hepatocyte lipid droplets using liquid chromatography-mass spectrometry (UHPLC-MS) plus integrated MS/MS, followed by automatic analysis of the MS data. The organelles were isolated after intervention studies involving nutritional stress (extended feeding of a high fat diet or short term fasting), genetic stress due to knock-out of adipocyte triglyceride lipase, or by combined application of nutritional and genetic stress together (‘super stress’). Lipidomics at the level of lipid species (profiling of lipid classes) and lipid molecular species (structural analysis in parallel) has unraveled clear lipid droplet phenotypes as judged by patterns seen best in triacylglycerol (TG) lipidomes, but also in diacylglycerol and phosphatidylcholine lipidomes. The combined view of these data presented here validates the methods used and provides high quality lipidomic data for further bioinformatic inspections. Examples are given for identification of TG species subsets considered surrogates for whole TG lipidomes.