Saccharomyces cerevisiae is a eukaryotic model organism widely used for the investigation of fundamental cellular processes and disease mechanisms. Consequently, the lipid landscape of yeast has been extensively investigated and up to this day the lipidome is considered as rather basic. Here, we used a nLC/NSI-MS/MS method combined with a semi-autonomous data analysis workflow for an in-depth evaluation of the steady state yeast lipidome. We identified close to 900 lipid species across 26 lipid classes, including glycerophospholipids, sphingolipids, glycerolipids and sterol lipids. Most lipid classes are dominated by few high abundant species, with a multitude of lower abundant lipids contributing to the overall complexity of the yeast lipidome. Contrary to previously published datasets, odd-chain and diunsaturated fatty acyl moieties were found to be commonly incorporated in multiple lipid classes. Careful data evaluation furthermore revealed the presence of putative new lipid species such as MMPSs (mono-methylated phosphatidylserine), not yet described in yeast. Overall, our analysis achieved a more than 4-fold increase in lipid identifications compared to previous approaches, underscoring the use of nLC/NSI-MS/MS methods for the in-depth investigation of lipidomes.
Keywords: Lipidomics; Nano-liquid chromatography; Saccharomyces cerevisiae; Untargeted lipidomics; Yeast lipidome; nLC/NSI-MS/MS.
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