A streamlined pipeline for multiplexed quantitative site-specific N-glycoproteomics.

Area of Science:

• Proteomics
• Glycomics
• Mass Spectrometry

Background:

• Protein N-glycosylation is crucial for human cellular functions.
• Accurate, site-specific quantification of glycosylation remains a significant analytical challenge.
• Existing methods lack the sensitivity and throughput for large-scale glycopeptide analysis.

Purpose of the Study:

• To introduce SugarQuant, an integrated pipeline for confident identification and quantification of intact glycopeptides.
• To overcome the technical challenges in large-scale, site-specific glycosylation analysis.
• To enable high-confidence determination of glycosylation changes in complex biological systems.

Main Methods:

• SugarQuant integrates protein aggregation capture (PAC) for rapid sample preparation.
• Multi-notch MS3 acquisition (Glyco-SPS-MS3) enhances signal detection and reduces interference.
• A data-processing tool (GlycoBinder) streamlines analysis and improves glycopeptide identification rates.

Main Results:

• PAC reduces sample handling time without compromising sensitivity.
• Glyco-SPS-MS3 improves reporter signal intensity and N-glycopeptide fragment detection.
• GlycoBinder increased glycopeptide identification rates by 22% compared to conventional methods.
• Over 5,000 unique glycoforms were identified and quantified in Burkitt's lymphoma cells.

Conclusions:

• SugarQuant provides a robust and efficient platform for comprehensive glycopeptide analysis.
• The pipeline enables high-confidence site-specific glycosylation profiling.
• SugarQuant facilitates the study of glycosylation changes in disease contexts, such as fucosylation inhibition.