Mass Spectrometry Based on Chemical Derivatization Has Brought Novel Discoveries to Lipidomics: A Comprehensive Review

AbstractLipids, as one of the most important organic compounds in organisms, are important components of cells and participate in energy storage and signal transduction of living organisms. As a rapidly rising field, lipidomics research involves the identification and quantification of multiple classes of lipid molecules, as well as the structure, function, dynamics, and interactions of lipids in living organisms. Due to its inherent high selectivity and high sensitivity, mass spectrometry (MS) is the “gold standard” analysis technique for small molecules in biological samples. The combination chemical derivatization with MS detection is a unique strategy that could improve MS ionization efficiency, facilitate structure identification and quantitative analysis. Herein, this review discusses derivatization-based MS strategies for lipidomic analysis over the past decade and focuses on all the reported lipid categories, including fatty acids and modified fatty acids, glycerolipids, glycerophospholipids, sterols and saccharolipids. The functional groups of lipids mainly involved in chemical derivatization include the C=C group, carboxyl group, hydroxyl group, amino group, carbonyl group. Furthermore, representative applications of these derivatization-based lipid profiling methods were summarized. Finally, challenges and countermeasures of lipid derivatization are mentioned and highlighted to guide future studies of derivatization-based MS strategy in lipidomics.Keywords: Lipidomicsderivatizationmass spectrometrystructure analysis Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThis work was supported by the National Natural Science Foundation of China (Grant No. U21A20274 and 22301313), National Key Research and Development Program Key Special Project (Grant No. 2021YFD1600103), Technology Innovation Project of Hubei Province (Grant No. 2021BEC021), and Agricultural Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences (CAAS-ASTIP-2013-OCRI).