Glycosylation is one of the most prevalent and crucial protein modifications. Quantitative site-specific characterization of glycosylation usually requires sophisticated intact glycopeptide analysis using glycoproteomics. Recent efforts have focused on the interrogation of intact glycopeptide analyses using tandem mass spectrometry. However, a systematic evaluation of the quantitative glycoproteomic workflow is still lacking. This study compared different strategies for glycopeptide enrichment alongside glycopeptide quantitation, as well as mass spectrometry and data analysis strategies, providing a comprehensive assessment of their efficacy. The ZIC-HILIC enrichment method demonstrated superior performance, representing a 26% improvement in identified glycopeptiudes compared to the MAX enrichment method. Quantification using TMT provided high precision and throughput with an average CV of 8%. Through systematic evaluation, this study established that the ZIC-HILIC enrichment method, quantification with TMT, and collision energies of 25, 35, and 45 using tandem mass spectrometry are the optimal workflow for higher-energy collisional dissociation (HCD) fragmentation, significantly enhancing the analysis of intact glycopeptides. Precise energy adjustment is crucial for the identification of certain glycans. Intact glycopeptides were analyzed using different software tools to investigate the identification and quantification of glycopeptides. By applying optimal settings, 5514 unique intact glycopeptides were in luminal and basal patient-derived xenograft (PDX) characterized models, highlighting distinct glycosylation profiles that may influence tumor behavior. This study offers a systematic approach to evaluate glycoproteomic analysis workflow.
Improving Glycoproteomic Analysis Workflow by Systematic Evaluation of Glycopeptide Enrichment, Quantification, Mass Spectrometry Approach, and Data Analysis Strategies.
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作者:Sun Zhenyu, Lih T Mamie, Woo Jongmin, Jiao Liyuan, Hu Yingwei, Wang Yuefan, Liu Hongyi, Zhang Hui
| 期刊: | Analytical Chemistry | 影响因子: | 6.700 |
| 时间: | 2024 | 起止号: | 2024 Dec 31; 96(52):20481-20490 |
| doi: | 10.1021/acs.analchem.4c04466 | ||
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