Utilizing Skyline to analyze lipidomics data containing liquid chromatography, ion mobility spectrometry and mass spectrometry dimensions

Lipidomics studies suffer from analytical and annotation challenges due to the great structural similarity of many of the lipid species. To improve lipid characterization and annotation capabilities beyond those afforded by traditional mass spectrometry (MS)-based methods, multidimensional separation methods such as those integrating liquid chromatography, ion mobility spectrometry, collision induced dissociation and MS (LC-IMS-CID-MS) may be employed. While LC-IMS-CID-MS and other multidimensional methods offer valuable hydrophobicity, structural and mass information, the files are also complex and difficult to assess. Thus, the development of software tools to rapidly process and facilitate confident lipid annotations is essential. In this Protocol Extension, we utilize the freely available, vendor-neutral, and open-source software Skyline to process and annotate the multidimensional lipidomic data. While Skyline was established for targeted processing of LC-MS-based proteomics data, it has since been extended such that it can be used to analyze small molecule data as well as data containing the IMS dimension. This protocol utilizes Skylines’ recently expanded capabilities, including small molecule spectral libraries, indexed retention time (iRT), and ion mobility filtering, and provides a step-by-step description for importing data, predicting retention times, validating lipid annotations, exporting results, and editing our manually validated 500+ lipid library. While the time required to complete the steps outlined here varies based on multiple factors such as dataset size and familiarity with Skyline, this protocol takes approximately 5.5 hours to complete when annotations are rigorously verified for maximum confidence