Uncovering the complexity of the yeast lipidome by means of nLC/NSI-MS/MS.

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.

Nano-LC/NSI MS Refines Lipidomics by Enhancing Lipid Coverage, Measurement Sensitivity, and Linear Dynamic Range.

Nano-liquid chromatography (nLC)-nanoelectrospray (NSI) is one of the cornerstones of mass-spectrometry-based bioanalytics. Nevertheless, the application of nLC is not yet prevalent in lipid analyses. In this study, we established a reproducible nLC separation for global lipidomics and describe the merits of using such a miniaturized system for lipid analyses. In order to enable comprehensive lipid analyses that is not restricted to specific lipid classes, we particularly optimized sample preparation conditions and reversed-phase separation parameters. We further benchmarked the developed nLC system to a commonly used high flow HPLC/ESI MS system in terms of lipidome coverage and sensitivity. The comparison revealed an intensity gain between 2 and 3 orders of magnitude for individual lipid classes and an increase in the linear dynamic range of up to 2 orders of magnitude. Furthermore, the analysis of the yeast lipidome using nLC/NSI resulted in more than a 3-fold gain in lipid identifications. All in all, we identified 447 lipids from the core phospholipid lipid classes (PA, PE, PC, PS, PG, and PI) in Saccharomyces cerevisiae.