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, multidimensional separation methods such as those integrating liquid chromatography, ion mobility spectrometry, collision induced dissociation and mass spectrometry (LC-IMS-CID-MS) are often employed. While the LC-IMS-CID-MS data offers 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 therefore essential. Here, we utilize the freely available, vendor-neutral, and open-source software Skyline to process and annotate the multidimensional lipidomic data. 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.

This protocol describes a workflow for data processing and annotation of LC-IMS-CID-MS lipidomics data. Skyline features including small molecule spectral libraries, ion mobility filtering, and indexed retention time are used. The library used in this protocol includes 854 lipid targets and 6149 transitions which correlates to 516 unique lipids spanning multiple classes from 5 of the 8 lipid categories. Each lipid in the library has stored information on its class or subclass, common name, molecular formula, m/z for one or more adducts, fragments and neutral losses, CCS, and indexed retention time. While the library was optimized for human plasma lipidomic analyses, it can be readily applied to any sample type.