Comprehensive Plasma N-Glycoproteome Profiling Based on EThcD-sceHCD-MS/MS

Author:

Mao Yonghong,Su Tao,Lin Tianhai,Yang Hao,Zhao Yang,Zhang Yong,Dai Xinhua

Abstract

Glycoproteins are involved in a variety of biological processes. More than one-third of the plasma protein biomarkers of tumors approved by the FDA are glycoproteins, and could improve the diagnostic specificity and/or sensitivity. Therefore, it is of great significance to perform the systematic characterization of plasma N-glycoproteome. In previous studies, we developed an integrated method based on the combinatorial peptide ligand library (CPLL) and stepped collision energy/higher energy collisional dissociation (sceHCD) for comprehensive plasma N-glycoproteome profiling. Recently, we presented a new fragmentation method, EThcD-sceHCD, which outperformed sceHCD in the accuracy of identification. Herein, we integrated the combinatorial peptide ligand library (CPLL) into EThcD-sceHCD and compared the performance of different mass spectrometry dissociation methods (EThcD-sceHCD, EThcD, and sceHCD) in the intact N-glycopeptide analysis of prostate cancer plasma. The results illustrated that EThcD-sceHCD was better than EThcD and sceHCD in the number of identified intact N-glycopeptides (two-folds). A combination of sceHCD and EThcD-sceHCD methods can cover almost all glycoproteins (96.4%) and intact N-glycopeptides (93.6%), indicating good complementarity between the two. Our study has great potential for medium- and low-abundance plasma glycoprotein biomarker discovery.

Funder

National Natural Science Foundation of China

Department of Science and Technology of Sichuan Province

Publisher

Frontiers Media SA

Subject

General Chemistry

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3