An intelligent Hybrid-DIA data acquisition strategy for cracking the clinical sample complexity challenge in translational proteotyping

Significance of the Topic

Mass spectrometry-based proteotyping plays a central role in biomarker discovery but faces challenges in clinical translation, including data missingness and limited sensitivity for specific protein markers. The Hybrid-DIA strategy addresses these obstacles by merging comprehensive proteome-wide profiling with targeted quantitation in a single workflow, enhancing assay robustness and accelerating clinical validation.

Objectives and Study Overview

This study aims to develop and evaluate a hybrid data acquisition method that integrates data independent acquisition (DIA) with on-the-fly, isotope-triggered multiplexed parallel reaction monitoring (msxPRM). The approach was tested on a mixture of 252 tumor-associated antigen peptides to assess improvements in sensitivity, quantitation accuracy, and reproducibility compared to standard DIA.

Methodology and Instrumentation

The Hybrid-DIA workflow consists of:

• Standard high-resolution MS1 scan followed by DIA MS/MS scans covering the full proteome.
• Detection of isotope-labeled reference peptides in MS1 triggers targeted msxPRM scans with narrow isolation windows and optimized ion injection times for endogenous peptides.
• The method is implemented in C# using the Exploris API on an Orbitrap Exploris 480 mass spectrometer.

Samples comprised heavy reference peptides at 100 fmol and light peptides in a dilution series (0.1 to 100 fmol). Data analysis was performed using Qual Browser, Spectronaut, and Skyline.

Main Results and Discussion

The Hybrid-DIA approach achieved:

• Lower limits of detection and quantitation for many peptides compared to standard DIA (peptides detected at 100 amol by Hybrid-DIA but not by DIA).
• Reduced coefficients of variation at low peptide concentrations, indicating improved reproducibility.
• Simultaneous acquisition of comprehensive proteomic data alongside enhanced targeted measurements, minimizing missing values in quantitative matrices.

These results demonstrate the ability of Hybrid-DIA to reliably detect and quantify clinically relevant peptides with high sensitivity and precision.

Benefits and Practical Applications

Hybrid-DIA offers:

• Enhanced sensitivity for low-abundance biomarkers within complex clinical samples.
• Streamlined workflows that combine discovery and targeted assays in one analysis.
• Reduced data missingness, facilitating robust biomarker validation and QA/QC in translational studies.

Future Trends and Applications

• Integration into multicenter clinical proteomics pipelines following standardization efforts.
• Expansion to post-translational modification–specific assays and complex matrix analyses.
• Real-time adaptive acquisition schemes driven by AI to further optimize data quality.
• Automation and high-throughput implementations for precision medicine applications.

Conclusion

The intelligent Hybrid-DIA method successfully combines broad-spectrum proteotyping with sensitive, targeted quantitation, outperforming standard DIA in detecting low-abundance clinical peptides. This approach holds promise for accelerating biomarker assay development and delivering actionable insights in translational proteomics.

References

• Xuan Y, et al. Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies. Nat Commun. 2020;11:5248.