岩藻糖基化
化学
糖基化
聚糖
计算生物学
生物化学
糖蛋白
生物
作者
Xin Guo,Xiaoyan Liu,Changrui Zhao,Zheng Fang,Da Sun,Feng Tang,Taiheng Ma,Lei Liu,He Zhu,Yan Wang,Zhongyu Wang,Yanan Li,Hongqiang Qin,Wei Huang,Mingming Dong,Mingliang Ye,Lingyun Jia
标识
DOI:10.1021/acs.analchem.4c00330
摘要
Dysregulation of protein core-fucosylation plays a pivotal role in the onset, progression, and immunosuppression of cancer. However, analyzing core-fucosylation, especially the accurate determination of the core-fucosylation (CF) site occupancy ratio, remains challenging. To address these problems, we developed a truncation strategy that efficiently converts intact glycopeptides with hundreds of different glycans into two truncated forms, i.e., a monosaccharide HexNAc and a disaccharide HexNAc+core-fucose. Further combination with data-independent analysis to form an integrated platform allowed the measurement of site-specific core-fucosylation abundances and the determination of the CF occupancy ratio with high reproducibility. Notably, three times CF sites were identified using this strategy compared to conventional methods based on intact glycopeptides. Application of this platform to characterize protein core-fucosylation in two breast cancer cell lines, i.e., MDA-MB-231 and MCF7, yields a total of 1615 unique glycosites and about 900 CF sites from one single LC-MS/MS analysis. Differential analysis unraveled the distinct glycosylation pattern for over 201 cell surface drug targets between breast cancer subtypes and provides insights into developing new therapeutic strategies to aid precision medicine. Given the robust performance of this platform, it would have broad application in discovering novel biomarkers based on the CF glycosylation pattern, investigating cancer mechanisms, as well as detecting new intervention targets.
科研通智能强力驱动
Strongly Powered by AbleSci AI