Automated HILIC-Enriched Glycopeptide Analysis of Plasma and Cell Lysates Using GlycoPASEF®on the timsTOF Ultra-2 with Real-Time Data Analysis Using GlycoScape

Importance of the Topic

Comprehensive glycoproteome profiling is essential for understanding protein function, disease biomarkers, and therapeutic development. Automated workflows that combine efficient enrichment and sensitive mass spectrometry accelerate discovery and improve reproducibility in both basic and applied research.

Objectives and Study Overview

This study presents an integrated workflow for automated HILIC-based glycopeptide enrichment on an AssayMAP Bravo platform, coupled with GlycoPASEF data acquisition on a timsTOF Ultra 2 mass spectrometer. The approach is evaluated on human plasma (citrate and EDTA anticoagulated) and cell lysates (HeLa and K562) to demonstrate improvements in glycopeptide identification, throughput, and reproducibility.

Methodology

The workflow consists of:

• Sample preparation: protein denaturation, reduction, alkylation, and tryptic digestion.
• Automated HILIC enrichment: using Agilent AssayMAP Bravo with hydrophilic interaction cartridges.
• LC-MS/MS analysis: nanoElute 2 chromatography coupled to timsTOF Ultra 2, employing GlycoPASEF for ion mobility separation and stepped-energy CID fragmentation.
• Data processing: real-time glycopeptide identification with GlycoScape and complementary offline analysis with MSFragger.

Instrumental Setup

• AssayMAP Bravo automated liquid handling system with CU HILIC cartridges
• nanoElute 2 nano-LC system
• timsTOF Ultra 2 mass spectrometer
• GlycoPASEF ion mobility acquisition mode
• Stepped-energy collisional induced dissociation (CID)
• GlycoScape real-time data analysis platform
• MSFragger for offline glycoproteomic evaluation

Main Results and Discussion

The combined workflow achieved:

• Up to 9-fold increase in glycopeptide identifications compared to unenriched samples.
• Identification of over 10 000 GlycoPSMs in enriched HeLa replicates, with consistent overlap across replicates (>2000 common glycopeptides).
• Enhanced fragmentation efficiency and oxonium ion evidence under stepped CID conditions.
• Distinct sialylation and fucosylation patterns observed in HeLa, K562, and plasma, highlighting species-specific glycosylation trends.
• Improved reproducibility across plasma and cell lysate replicates, supporting robust quantitative analysis.

Benefits and Practical Applications

The streamlined, automated HILIC–GlycoPASEF workflow offers:

• High throughput and sensitivity for large-scale glycoproteomic studies.
• Scalable sample preparation suitable for clinical and industrial laboratories.
• Real-time data analysis enabling rapid decision-making and method optimization.
• Comprehensive coverage of N-glycopeptides, facilitating biomarker discovery and quality control in biopharmaceuticals.

Future Trends and Opportunities

Emerging directions include:

1. Integration of machine learning for improved glycopeptide identification and glycan structure prediction.
2. Advanced ion mobility techniques to enhance separation of isomeric glycoforms.
3. Development of new affinity chemistries for targeted glycan classes.
4. Standardization of automated glycoproteomics protocols for regulatory compliance in clinical assays.

Conclusion

The presented automated HILIC enrichment combined with GlycoPASEF on timsTOF Ultra 2 delivers a robust, high-sensitivity glycoproteomic workflow. Significant gains in identification rates and reproducibility underscore its value for diverse research and quality control applications. Real-time analysis with GlycoScape enhances throughput and supports rapid method refinement.