Assessment of potential false positives via orbitrap-based untargeted lipidomics from rat tissues

Abstract

Untargeted lipidomics is increasingly popular due to the broad coverage of lipid species. Data dependent MS/MS acquisition is commonly used in order to acquire sufficient information for confident lipid assignment. However, although lipids are identified based on MS/MS confirmation, a number of false positives are still observed. Here, we discuss several causes of introducing lipid false identifications in untargeted analysis. Phosphotidylcholines and cholesteryl esters generate in-source fragmentation to produce dimethylated phosphotidylethanolamine and free cholesterol. Dimerization of fatty acid results in false identification of fatty acid ester of hydroxyl fatty acid. Realizing these false positives is able to improve confidence of results acquired from untargeted analysis. Besides, thresholds are established for lipids identified using LipidSearch v4.1.16 software to reduce unreliable results.

Keywords: False identifications; LC-MS/MS; Orbitrap; Untargeted lipidomics.