Department of Chemistry & Biochemistry, University of North Carolina at Greensboro, Greensboro, NC, 27402, USA.
Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, 28081, USA.
Anal Bioanal Chem. 2023 Dec;415(29-30):7269-7279. doi: 10.1007/s00216-023-04995-y. Epub 2023 Oct 20.
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.
神经节苷脂是中枢神经系统中含量最丰富的特殊糖脂。它们复杂的两亲性结构对于膜脂筏的形成和分子识别至关重要。脂筏和神经节苷脂代谢功能障碍与癌症、代谢紊乱和神经退行性疾病有关。疾病进展过程中神经节苷脂浓度和多样性的变化使它们成为早期检测的潜在生物标志物，并揭示了疾病机制。化学衍生化促进了神经节苷脂的整体离子分析，同时改善了离子化，提供了丰富的碎片谱，并实现了多重分析方案，如稳定同位素标记。在这项工作中，我们通过增加缓冲液浓度和去除固相萃取脱盐来改进我们之前报道的神经节苷脂分析等排标记方法，以获得更完整和定量的反应。通过内部神经节苷脂衍生物库，MS-DIAL 可自动识别和定量神经节苷脂。我们已经将更新的方法应用于 6 个小鼠脑区（小脑、脑桥/延髓、中脑、丘脑/下丘脑、皮质和基底神经节）中神经节苷脂的相对定量，每个样本 2 毫克组织，并描述了 88 种神经节苷脂分子物种的区域特异性分布，解析了神经酰胺异构体。该方法有望应用于生物样本中神经节苷脂的比较分析。
