基于非天然糖代谢标记的分泌蛋白质糖基化精细分析新方法研究

The glycosylation of secreted proteins has been reported closely associated with the drug resistance of cancer cells. Yet, it is still a challenge for precise determination of the glycosylation, due to the low abundance of secreted proteins and the high complexity of glycosylation. In order to selectively enrich the secreted proteins, decrease the interference of highly abundant proteins in bovine serum, as well as improve the efficiency of site-specific glycoform determination, several methods are developed in this project in the following aspects: 1) Development of methods for specific enrichment of low abundance secreted proteins by combining unnatural sugar metabolic labeling and bio-orthogonal reactions, which could efficiently decrease the inference of high abundant proteins; 2) Development of methods for secreted protein digestion by combining in-situ digestion of proteins on beads by using combined-enzymes, which could enhance the coverage of protein identification, as well as the location of glycosites for the expression of secreted proteins and glycosite-occupancy; 3) Development of new MS dissociation methods and integrated software platforms for detection and interpretation of intact glycopeptides, as well as quantification of intact glycopeptides, which could display the site-specific glycoforms of secreted glycoproteins. Combined the above methods, the precise determination of glycosylation in secreted proteins could be performed on the levels of protein expressions, glycosite-occupancy, as well as site-specific glycoforms. Furthermore, the newly developed method is utilized to quantitative analysis of protein glycosylation in drug-resistance liver cancer cells, which could reveal the connections between glycosylation of secreted proteins and drug-resistance. Based on the above results, we will further investigate the relationship among secreted proteins and drug-resistance, which has great potential applications in the screening of efficiency drugs for chemotherapy in precise medicine.

分泌蛋白质糖基化与肿瘤细胞耐药性密切相关，然而受到分泌蛋白质低丰度和糖基化复杂性的双重制约，难以实现其糖基化位点占有率及位点特异性糖型的精细解析。本项目针对糖基化分泌蛋白质丰度低且培养基血清蛋白质干扰严重、完整糖肽离子化效率低和谱图解析困难的问题，拟从以下三个方面解决：1）发展基于非天然糖代谢标记-生物正交反应的分泌蛋白质富集方法，去除培养基中高丰度蛋白质的干扰，实现分泌蛋白质的特异性富集；2）发展基于组合酶的蛋白质原位酶解技术，降低样品损失，进行分泌蛋白质的高效酶解和糖基化位点的高覆盖分析，实现蛋白质表达量和糖基化位点占有率的高效表征；3）建立完整糖基化肽段的高效质谱检测方法及谱图解析算法，实现位点特异性糖型的高通量表征。将发展的方法用于含血清培养的肝癌亲本-耐药细胞的分泌蛋白质糖基化特征谱的精细解析，探讨糖基化水平与肿瘤耐药机制的关系，为肝癌肿瘤临床药物的筛选提供技术支撑和数据支持。

针对分泌蛋白质糖基化分析面临的丰度低、完整糖肽离子化效率低和谱图解析困难的挑战，本项目通过化学测量学、材料化学和化学生物学等多学科交叉融合，以糖肽富集新材料新技术、完整糖肽的质谱检测与解析技术和基于位点特异性糖基化的定量分析三个方向为突破口，通过发展基于多聚组氨酸修饰和亲水-亲和协同效应的高特异性糖基化分泌蛋白质富集新材料，克服了分泌蛋白质中N-和O-连接糖肽丰度低、干扰严重的挑战, 将N-连接唾液酸糖肽的富集特异性提高到94.5%，并且率先实现了0.1微升血清中超过300条O-GalNAc糖肽的高效捕获；通过发展酶促去糖基化和理论去糖基化的策略，分别提高N-和O-连接完整糖肽的质谱检测效率，实现了超过10000条位点特异性N-连接糖肽和2000条O-GalNAc糖肽的高覆盖度鉴定；在此基础上，结合非标记定量技术和质谱靶向检测模式，从糖基化蛋白质表达量、糖基化位点占有率和位点特异性糖型三个层次进行分泌蛋白质糖基化的精细解析，深入揭示其微观不均一性，发现血清免疫球蛋白中超过6个位点特异性糖型在肝癌和胰腺癌中存在显著变化，建立了基于完整糖肽靶向高通量定量的技术，进行了超过174个正常-肝癌样本的差异分析，实现了其不同病期的分型。本项目在蛋白质糖基化解析新方法研究方面取得了多项进展，相关研究成果发表包括Anal. Chem., J. Proteome Res., 共发表SCI学术论文11篇，涵盖了方法学和相关转化医学应用等多个研究领域；共申请及授权发明专利4项，顺利完成项目目标。通过本项目的实施，为恶性肿瘤的早期诊断和个性化治疗提供技术和基础数据支撑。