Abstract
Lipids have been analyzed in applications including drug discovery, disease etiology elucidation, and natural products. The chemical and structural diversity of lipids requires a tailored lipidomics workflow for each sample type. Therefore, every protocol in the lipidomics workflow, especially those involving sample preparation, should be optimized to avoid the introduction of bias. The coupling of ultra-high-performance liquid chromatography (UHPLC) with high-resolution mass spectrometry (HRMS) allows for the separation and identification of lipids based on class and fatty acid acyl chain. This work provides a comprehensive untargeted lipidomics workflow that was optimized for various sample types (mammalian cells, plasma, and tissue) to balance extensive lipid coverage and specificity with high sample throughput. For identification purposes, both data-dependent and data-independent tandem mass spectrometric approaches were incorporated, providing more extensive lipid coverage. Popular open-source feature detection, data processing, and identification software are also outlined.