4.8 Article

Strategy for Comprehensive Profiling and Identification of Acidic Glycosphingolipids Using Ultra-High-Performance Liquid Chromatography Coupled with Quadrupole Time-of-Flight Mass Spectrometry

Journal

ANALYTICAL CHEMISTRY
Volume 89, Issue 14, Pages 7808-7816

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.7b02023

Keywords

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Funding

  1. National Natural Science Foundation [81273484]

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Acidic glycosphingolipids (AGSLs), which mainly consist of ganglioside and sulfatide moieties, are highly concentrated in the central nervous system. Comprehensive profiling of AGSLs has historically been challenging because of their high complexity and the lack of standards. In this study, a novel strategy was developed to comprehensively profile AGSLs using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Ganglioside isomers with different glycan chains such as GD1a/GD1b were completely separated on a C18 column for the first time to our knowledge, facilitated by the addition of formic acid in the mobile phase. A mathematical model was established to predict the retention times (RTs) of all theoretically possible AGSLs on the basis of the good logarithmic relationship between the ceramide carbon numbers of the AGSLs in the reference material and their RTs. A data set was created of 571 theoretically possible AGSLs, including the ceramide carbon numbers, RTs, and high-resolution quasi-molecular ions. A novel fast identification strategy was established for global AGSL profiling by comparing the high-resolution quasi-molecular ions and RTs of the tested peaks to those in the data set of 571 AGSLs. Using this strategy, 199 AGSL candidates were identified in rat brain tissue. MS/MS fragments were further collected for these 199 candidates to confirm their identity as AGSLs. This novel strategy was employed to profile AGSLs in brain tissue samples from control rats and model rats with bilateral common carotid artery (2-VO) cerebral ischemia. Forty AGSLs were significantly different between the control and model groups, and these differences were further interpreted.

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