High dynamic range proteome analysis with BoxCar DIA and super-resolution Orbitrap mass spectrometry

Significance of the Topic

Proteomics demands broad dynamic range and high throughput to quantify thousands of proteins reliably. Traditional data independent acquisition (DIA) workflows can be limited by either resolution or scan speed, affecting sensitivity and quantitative accuracy. Integrating BoxCar DIA with super-resolution Orbitrap technology overcomes these constraints by expanding dynamic range while preserving rapid analysis rates. This advancement supports comprehensive proteome profiling in complex biological matrices, such as human plasma.

Objectives and Study Overview

This study evaluates the performance of real-time phase-constrained spectrum deconvolution (ΦSDM) combined with BoxCar DIA on an Orbitrap Exploris 480 mass spectrometer. The primary goals are to assess improvements in mass resolution, scan speed, and dynamic range coverage, and to demonstrate feasibility in high-throughput proteomic workflows. Benchmarking experiments include analysis of HeLa cell digests at 100 samples per day and human blood samples at 30 samples per day.

Methodology

Trypsin/LysC-digested whole-cell lysates and human plasma samples were analyzed in single injections. Full-range MS spectra were acquired using BoxCar DIA, followed by real-time ΦSDM signal processing implemented on Nvidia TITAN X GPUs via CUDA C++. Quantitative data were extracted and validated using Spectronaut software to ensure accurate protein identification and quantification.

Used Instrumentation

• Thermo Scientific Orbitrap Exploris 480 mass spectrometer with FAIMS (CV –45 V)
• Evosep One liquid chromatography system
• Nvidia TITAN X GPUs for accelerated ΦSDM processing
• Spectronaut software (Biognosys) for DIA data analysis

Key Results and Discussion

ΦSDM processing at 32 ms transient achieved resolution comparable to or better than eFT at 64 ms, effectively doubling scan speed without compromising mass accuracy. BoxCar DIA enabled deep proteome coverage of human plasma, quantifying hundreds of proteins across 30 samples per day. In HeLa digest experiments, the combined workflow processed 100 samples per day while maintaining robust identification rates. Enhanced dynamic range and throughput underscore the method’s suitability for large-scale proteomic studies.

Benefits and Practical Applications of the Method

This workflow delivers significant gains in throughput and sensitivity for quantitative proteomics, making it ideal for clinical biomarker discovery and large cohort studies. Real-time ΦSDM minimizes acquisition time and computational load, while BoxCar DIA extends dynamic range for low-abundance protein detection. Existing Orbitrap platforms can be leveraged to implement this high-efficiency proteome profiling strategy in core facilities and industrial laboratories.

Future Trends and Applications

Advances in GPU-accelerated deconvolution will further enhance real-time processing, enabling complex DIA schemes and deeper proteome coverage. Integration with machine learning algorithms may improve identification speed and quantitative precision. Scalability to diverse sample types and automation will drive broader adoption in clinical diagnostics and pharmaceutical research.

Conclusion

The combination of BoxCar DIA and real-time ΦSDM on an Orbitrap Exploris 480 mass spectrometer achieves high dynamic range, accelerated scan rates, and robust quantitative performance. This workflow offers a powerful solution for high-throughput proteomic analyses and comprehensive proteome investigation.

References

1. D. Grinfeld et al., Anal. Chem., 89 (2), 1202–1211, 2017.
2. C. D. Kelstrup et al., J. Proteome Res., 17 (11), 4008–4016, 2018.
3. F. Meier et al., Nat. Methods, 15, 440–448, 2018.