Abstract
Gangliosides are specialized glycosphingolipids most abundant in the central nervous system. Their complex amphiphilic structure is essential to the formation of membrane lipid rafts and for molecular recognition. Dysfunction of lipid rafts and ganglioside metabolism has been linked to cancer, metabolic disorders, and neurodegenerative disorders. Changes in ganglioside concentration and diversity during the progression of disease have made them potential biomarkers for early detection and shed light on disease mechanisms. Chemical derivatization facilitates whole ion analysis of gangliosides while improving ionization, providing rich fragmentation spectra, and enabling multiplexed analysis schemes such as stable isotope labeling. In this work, we report improvement to our previously reported isobaric labeling methodology for ganglioside analysis by increasing buffer concentration and removing solid-phase extraction desalting for a more complete and quantitative reaction. Identification and quantification of gangliosides are automated through MS-DIAL with an in-house ganglioside derivatives library. We have applied the updated methodology to relative quantification of gangliosides in six mouse brain regions (cerebellum, pons/medulla, midbrain, thalamus/hypothalamus, cortex, and basal ganglia) with 2 mg tissue per sample, and region-specific distributions of 88 ganglioside molecular species are described with ceramide isomers resolved. This method is promising for application to comparative analysis of gangliosides in biological samples.
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Research reported in this publication was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under Award Number R01DK123499.
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Mouse tissues used in this work were collected under animal use protocol # 20025, which was approved by the Jackson Laboratory’s Bar Harbor Institutional Animal Care and Use Committee.
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Smith, R.A., Zhang, Q. Region-specific mouse brain ganglioside distribution revealed by an improved isobaric aminoxyTMT labeling strategy with automated data processing. Anal Bioanal Chem 415, 7269–7279 (2023). https://doi.org/10.1007/s00216-023-04995-y
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DOI: https://doi.org/10.1007/s00216-023-04995-y