A Novel, Automated, and Highly Selective Phosphopeptide Enrichment for Phosphopeptide Identification and Phosphosite Localization

Significance of the topic

Protein phosphorylation is a key regulatory mechanism in cellular signaling and disease. Reliable enrichment and analysis of phosphopeptides are essential for deep phosphoproteomic studies, but manual workflows often suffer from poor reproducibility, variable selectivity, and ion suppression during LC–MS analysis.

Objectives and study overview

This work addresses the HUPO Phosphopeptide Challenge by deploying an automated Fe(III)-based phosphopeptide enrichment protocol. Two sample sets were analyzed: a synthetic mixture of 89 human phosphopeptides and their nonphosphorylated counterparts, and the same set spiked into a trypsin-digested yeast lysate matrix. Goals included peptide identification, phosphosite localization, relative quantitation of phosphorylation occupancy, and evaluation of enrichment selectivity.

Instrumentation used

• Agilent AssayMAP Bravo platform with high-capacity Fe(III)-NTA cartridges for enrichment and C18 cartridges for desalting
• Agilent 1290 Infinity II LC system coupled to a Nanodapter for nanoflow operation, including InfinityLab deactivator additive to reduce metal ion interactions
• Agilent 6550 iFunnel Q-TOF mass spectrometer equipped with an electromagnetostatic (EMS) ECD cell for complementary fragmentation

Methodology and workflow

Samples were processed using dedicated AssayMAP Bravo applications: first binding phosphopeptides to Fe(III)-NTA resin under organic–acidic conditions, then eluting into formic acid before C18 desalting. Enriched fractions were dried, reconstituted, and analyzed by nano-LC–MS. Data-dependent acquisition (DDA) using CID provided broad peptide identification, while targeted ECD experiments confirmed site-specific phosphorylation. Data were processed with Spectrum Mill for peptide ID, Skyline for MS1-based quantitation, and Byonic for phosphosite assignment.

Main results and discussion

• DDA analysis of the synthetic sample yielded 437 distinct peptides, including 294 phosphopeptides (∼67% phosphorylation rate). In the yeast-spiked sample, enrichment produced 287 peptides with 264 phosphopeptides (∼92% selectivity).
• Targeted ECD localized 124 phosphosites across 94 targeted peptides, demonstrating the utility of higher charge states (+3) for robust backbone fragmentation and site confirmation.
• Extracted ion chromatograms enabled relative quantitation of phosphorylation at individual sites, revealing occupancy ratios spanning two orders of magnitude.

Benefits and practical applications

• Automation ensures high reproducibility and throughput for routine phosphoproteomic workflows.
• Selective enrichment reduces background interference and improves detection of low-abundance phosphopeptides.
• Combined CID and ECD fragmentation strategies deliver comprehensive sequence coverage and accurate site localization.

Future trends and potential applications

• Integration with high-throughput and multiplexing approaches to expand phosphoproteome coverage in large-scale studies.
• Application to clinical biomarker discovery, mechanistic signaling research, and quality control in biopharmaceutical development.
• Combination with stable isotope labeling or data-independent acquisition for improved quantitative accuracy.

Conclusion

The automated AssayMAP Bravo enrichment and LC–MS workflow achieves high selectivity, reproducibility, and depth in phosphopeptide profiling. It meets the stringent requirements of the HUPO Phosphopeptide Challenge by delivering extensive peptide identification, precise phosphosite localization, and reliable quantitative data, offering a robust platform for diverse phosphoproteomic applications.

References

1. Russell JD, Murphy S. Agilent AssayMAP Bravo Technology Enables Reproducible Automated Phosphopeptide Enrichment from Complex Mixtures Using High-Capacity Fe(III)-NTA Cartridges. Agilent Technologies Application Note. 2016;5991-6073EN.
2. Wu S, Wu L. Human Breast Cancer Cell Line Phosphoproteome Revealed by an Automated and Highly Selective Enrichment Workflow. Agilent Technologies Application Note. 2018;5994-0315EN.
3. Hsiao JJ, et al. Improved LC/MS Methods for the Analysis of Metal-Sensitive Analytes Using Medronic Acid as a Mobile Phase Additive. Anal Chem. 2018;90(15):9457–9464.