Combining the Data-driven and Hypothesis-driven Approaches in One Go via a Novel Intelligent Data Acquisition Hybrid-DIA Mass Spectrometry Strategy

Significance of the Topic

Proteome profiling underpins biomarker discovery and clinical decision-making by revealing protein expression patterns across complex biological samples. Traditional data independent acquisition (DIA) workflows offer broad coverage but lack the sensitivity needed for low-abundance targets. Conversely, targeted methods such as parallel reaction monitoring (PRM) deliver high sensitivity but at the expense of throughput and proteome scale. Bridging this gap is vital for high-throughput biomarker validation and precision medicine applications.

Objectives and Overview of the Study

This work introduces Hybrid-DIA, an intelligent mass spectrometry acquisition strategy that seamlessly integrates high-resolution MS1-driven DIA with on-the-fly triggered multiplexed PRM scans. The goal is to achieve comprehensive proteome digitization while simultaneously quantifying selected isotope-labeled biomarkers with enhanced sensitivity and accuracy in a single LC-MS run.

Used Instrumentation

• Thermo Scientific UltiMate 3000 nanoLC system with Acclaim PepMap trap and analytical columns
• Thermo Scientific Orbitrap Exploris 480 or Orbitrap Fusion Lumos Tribrid mass spectrometers
• C#-based iAPI integration for real-time control of acquisition modes
• Spectronaut v.15 and Skyline software for DIA and PRM data processing

Methodology

• Hela digest samples spiked with six sets of five isotopologue peptides (Promega) across four concentration decades.
• Depleted human plasma spiked with reference peptides (Biognosys) for targeted biomarker quantitation.
• Hybrid-DIA cycle comprising a full MS1 scan, multiplexed DIA MS/MS windows, and real-time triggered (msx)PRM scans upon isotope signal detection.
• Optimized ion injection times and narrow isolation windows for PRM to maximize signal-to-noise and limit of detection.
• LC gradients ranging from 25 to 60 minutes evaluated for coverage and quantitation performance.

Main Results and Discussion

Hybrid-DIA matched standard DIA in global protein and peptide identifications (around 6,000 protein groups from Hela in 60 min) while reducing median CVs below 10%. On-the-fly PRM enhanced signal-to-noise ratios, improved limits of detection by orders of magnitude for targeted peptides, and minimized interferences in complex plasma matrices. Single-shot 60 min analyses quantified over 500 plasma proteins alongside up to 60 biomarkers with high confidence.

Benefits and Practical Applications of the Method

• Simultaneous broad proteome coverage and sensitive quantitation of specific targets in one run.
• Reduced sample consumption and analysis time compared to separate DIA and PRM workflows.
• Enhanced throughput for large clinical cohorts and high-value biomarker validation.
• Robust quantitation with median CVs <10% across gradients and sample types.

Future Trends and Potential Applications

Hybrid-DIA paves the way for adaptive acquisition schemes that respond to evolving sample complexity in real time. Integration with machine learning could further refine trigger thresholds and expand targeted panels dynamically. Broader adoption in clinical and industrial laboratories will accelerate large-scale proteotype mapping, quality control workflows, and personalized medicine studies.

Conclusion

The Hybrid-DIA strategy successfully combines data-driven proteome profiling with hypothesis-driven targeted quantitation, achieving comprehensive coverage and sensitive biomarker measurement in a single LC-MS experiment. This approach streamlines workflows, reduces resource use, and supports advanced clinical proteomics applications.

References

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.