基于质谱技术的肿瘤血清O-糖组学研究

【作者】 吴刚；

【导师】 白晨；

【作者基本信息】 复旦大学 ， 生物化学与分子生物学， 2009， 硕士

【摘要】 通过对接种和未接种B16黑色素瘤细胞的C57小鼠血清进行O-糖链的比较糖组学研究,寻找黑色素瘤血清特异性O-糖链。为筛选出最适合AXIMA QIT质谱仪的糖组学实验条件,分别对血清用量、质谱点样方式、质谱激光强度、石墨化炭黑小柱纯化方法等实验条件进行了比较研究。发现10 ul血清用量、0.5 ul糖链样品+0.5 ul阳离子供体(0.01 M NaCl)+0.5ul基质(溶于乙醇中50 mg/ml 2,5-DHB)的质谱点样方式、及pow 20-40的激光强度可以得到最佳的质谱分析结果,改进后的GCC小柱较市售GCC小柱能够大幅度地降低填料用量(填料为商业化小柱的1/15)和提取时间(由30分钟减少到10分钟),同时提高了实验结果的再现性。将优化后的方法用于寻找黑色素瘤血清特异性O-糖链,用Launchpad software(Kratos Analytical,Manchester,UK,Version 2.4.1 Build)采集和输出质谱数据,MATLAB(Version R2008b)进行数据分析,找到了10个稳定出现的差异糖链质谱峰。通过串联质谱对5种主要差异糖链质谱峰进行了结构分析,发现差异糖链都带有动物中少见的HexHexA二糖重复结构。首次探索了SDS-PAGE和GCC SPE连用的血清糖组学研究新方法。与常规方法相比,本方法血清用量低(2.5 ul)、鉴定到的糖链多、检测灵敏度高,同时还能检测到同一糖链连接在不同的蛋白质上的糖基化改变。结合糖链在CID过程中的碎裂规律,用MATLAB编写了相应的计算机程序:首先计算串联质谱数据中两峰间的差值,然后用xyl、Fuc、Hex、HexA、HexNac,和NeuAc穷举出所有可能符合该差值的单糖组成,输出这两个质谱峰的质荷比、峰间差和所差的单糖组分,分析预测糖链结构。程序能处理相差132 Da—1015 Da的质谱峰,并能自由设定误差允许范围,大大提高了对串联质谱数据的解析速度。更多还原

【Abstract】 Serum O-glycans were compared between C57 mouse with and without B16 melanoma implanted. In order to find out best glycomics protocol for AXIMA QIT MS, the serum volume, MS spotting method, laser power and GCC SPE purification were evaluated. Finally, 10 ul serum was chosen as the best volume, 0.5 ul sample+0.5 ul 0.01 M NaCl+0.5ul matrix (50 mg/ml 2,5-DHB in EtOH) as spotting method, and pow 20-40 for laser power. In addition, we modified commercial GCC and developed a mini-GCC column which needed less graphitized carbon (1/15 compared to the commercial type), cost less time (from 30 min to less than 10 min), and most of all yielded more stable result. The advanced method was then applied to the search for melanoma related serum O-glycans. MS raw data was first acquired and exported by Launchpad software (Kratos Analytical, Manchester, UK, Version 2.4.1 Build). MATLAB (Version R2008b) was then applied for further data analysis. 10 glycan mass peaks were considered to be firmly changed after B16 implantation, 5 of which were continued MS/MS for structure analysis. Surprisingly, we found the 5 glycans had HexHexA repeats, which were rarely found in mammals. And also, for the first time, we tried a new method that combined both SDS-PAGE and GCC SPE for serum glycomics analysis. The updated method needed 2.5 ul serum sample, more sensitive and able to detect more glycans than common glycomics methods. Most of all, it could tell the glycosylation which involved the same glycan attached to different proteins. Last but not least, according to CID fragmentation rules of glycans, a MATLAB program was devised. The program first computed the differences between fragment masses and estimated all possible loss of glycan moieties with candidate monosaccharide including Xyl, Fuc, Hex, HexA, HexNAc and NeuAc. If glycan moieties were found between the two peaks, their m/z, delta peaks, moiety composition were exported. The program could afford peaks spacing from 132 Da to 1015 Da. The set of mass tolerance was available. It greatly facilitated MS/MS data analysis.更多还原