Accelerating proteotyping transformation into clinical routine via an intelligent data acquisition Hybrid-DIA MS based proteomics solution

Significance of the Topic

The development of reliable and comprehensive proteomic assays is essential to translate biomarker discovery into routine clinical applications. Traditional MS workflows often compromise between breadth of proteome coverage and sensitivity for known markers, leading to missing data and limited validation capacity.

Objectives and Study Overview

This work presents an intelligent Hybrid-DIA data acquisition strategy that merges high-resolution MS1-based DIA and on-the-fly multiplexed PRM scans. The goal is to achieve deep, reproducible proteome digitization while simultaneously quantifying diagnostic marker panels in a single LC–MS run.

Methodology and Instrumentation

This workflow was implemented on a nanoLC EASY-nLC 1200 coupled to an Orbitrap Exploris 480 mass spectrometer. The Hybrid-DIA method, programmed in C# via the instrument API, combines three acquisition steps:

• High-resolution MS1 DIA scans covering the global proteome.
• Scheduled multiplexed PRM (msxPRM) scans triggered by internal reference peptides for targeted marker sensitivity.
• Integration of DIA and targeted scans in one experiment to reduce sample use and acquisition time.

Main Results and Discussion

Benchmarking against standard DIA and PRM protocols using HeLa digest spiked with isotope-labeled peptides demonstrated:

• Comparable proteome coverage: over 5 000 proteins identified at 1% FDR in both DIA and Hybrid-DIA.
• Enhanced sensitivity for 179 tumor-associated antigen peptides, with a limit of quantitation down to 100 attomole.
• Improved quantitation linearity (R² = 0.9995) and lower coefficient of variation, especially for low-abundance peptides.
• Reduced data missingness and interferences, yielding median CVs below 10% across technical replicates.

Benefits and Practical Applications

The Hybrid-DIA approach offers:

• Single-shot LC–MS for simultaneous global discovery and targeted validation.
• Higher throughput with reduced sample consumption.
• Enhanced confidence in marker quantitation for clinical decision-making.
• Potential for integration into routine translational and diagnostic workflows.

Future Trends and Potential Applications

Emerging opportunities include:

• Scaling Hybrid-DIA to large clinical cohorts for population proteomics.
• Combining real-time data interpretation and AI-driven biomarker pattern recognition.
• Increasing multiplexing capacity to track broader diagnostic panels.
• Adapting the workflow to novel instrumentation platforms and diverse sample types.

Conclusion

The intelligent Hybrid-DIA strategy successfully bridges comprehensive proteome profiling with sensitive, targeted quantitation in one automated experiment. This integrated solution streamlines biomarker research and paves the way for proteotype-based precision medicine.

Reference

1. Xuan Y., Bateman N.W., Gallien S. et al. Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies. Nat Commun. 2020;11:5248.