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Glycomics-Guided Glycoproteomics Facilitates Comprehensive Profiling of the Glycoproteome in Complex Tumor Microenvironments
Published on: February 7, 2025
Recent advancements in sample pretreatment methods for glycoproteomics.
Wei Zhang1, Siyuan Kong1, Weiqian Cao1
1Shanghai Fifth People's Hospital and Institutes of Biomedical Sciences, NHC Key Laboratory of Glycoconjugates Research, Fudan University, Shanghai 200433, China.
Biophysics Reports
|June 29, 2026
Summary
Glycoprotein analysis is crucial for understanding biology and disease, but glycan complexity poses challenges. This review highlights advancements in sample preparation for bottom-up glycoproteomics (LC-MS) to improve efficiency and applications.
Area of Science:
- Biochemistry
- Analytical Chemistry
- Molecular Biology
Background:
- Protein glycosylation plays vital roles in biological processes and disease.
- The structural complexity and heterogeneity of glycans present significant analytical challenges.
- Bottom-up glycoproteomics using liquid chromatography-mass spectrometry (LC-MS) is a key technique for detailed glycoprotein analysis.
Purpose of the Study:
- To review current sample pretreatment workflows in glycoproteomics.
- To emphasize recent advancements in sample preparation and enrichment strategies over the last decade.
- To discuss challenges and future directions in glycoproteomic sample preparation.
Main Methods:
- Review of literature on glycoproteomics sample preparation techniques.
- Focus on liquid chromatography-mass spectrometry (LC-MS)-based methods.
- Analysis of advancements in enrichment strategies for glycopeptides.
Main Results:
- Sample pretreatment is a critical step influencing LC-MS-based glycoproteomics outcomes.
- Recent decade advancements have improved enrichment efficiency and high-throughput compatibility.
- Enhanced strategies show promise for diverse biological sample applications.
Conclusions:
- Optimized sample preparation is essential for robust glycoproteomics.
- Continued innovation in enrichment techniques is needed to address remaining challenges.
- Future directions include further improving efficiency, throughput, and applicability to complex biological systems.
