Fast Top-Down Analysis via Orbitrap and Astral Analyzers

Significance of the Topic

The accurate and rapid analysis of intact proteins is critical in biopharmaceutical development, proteomics research, and quality control applications. Traditional top-down approaches using Orbitrap analyzers deliver high resolution but are constrained by slow acquisition rates and complex spectra at high m/z values. The integration of a parallel Astral analyzer offers a path to accelerate top-down experiments while preserving spectral detail, enabling more efficient characterization of protein structure, post-translational modifications, and complex assemblies.

Objectives and Study Overview

This study evaluates the performance of the Thermo Scientific Orbitrap Astral mass spectrometer for top-down protein analysis. Key aims include:

• Demonstrating intact mass measurement of protein standards and monoclonal antibodies.
• Comparing fragmentation quality between Orbitrap and Astral analyzers.
• Implementing a hybrid data-dependent acquisition (DDA) workflow to accelerate MS/MS experiments.

Methodology and Instrumentation

An ‘Intact Protein’ mode was developed combining optimized ion processor pressures and advanced peak deconvolution algorithms. Protein samples (myoglobin, carbonic anhydrase, Humira, NISTmAb) were infused or separated via a Vanquish Neo UHPLC system with a MAbPac Capillary RP column (0.15 × 150 mm). A 22-minute Top10 DDA method triggered Orbitrap Full-MS scans and Astral MS/MS acquisitions in parallel. Instrument parameters tuned included lower collisional scatter pressures in the dual-pressure ion trap and IRM regions, ensuring high transmission of high m/z ions.

Main Results and Discussion

Infusion of myoglobin (17 kDa) and carbonic anhydrase (29 kDa) produced highly populated Astral spectra with resolved charge state distributions. Averaging 50–100 scans was required to overcome background noise at higher masses. Top-down MS/MS of carbonic anhydrase at m/z 854.7 showed comparable fragmentation patterns between Orbitrap and Astral, with Astral yielding 79 matching fragments (28% residue cleavages) versus 65 fragments (25% cleavages) in the Orbitrap. The hybrid DDA workflow generated numerous high-quality MS/MS spectra in a single run of a six-protein standard mix. Antibody infusions (144–150 kDa) resolved glycoforms, demonstrating Astral compatibility with large proteins, although peak-picking software currently struggles with dense data streams.

Benefits and Practical Applications

• Accelerated top-down workflows: Parallel acquisition doubles throughput compared to Orbitrap-only methods.
• High-resolution intact mass: Enables confident assignment of proteoforms and glycoforms in biopharma QC.
• Robust MS/MS fragmentation: Astral produces spectra suitable for sequence mapping and modification localization.
• Scalability: Compatible with LC separation and complex sample mixtures for proteomics studies.

Future Trends and Opportunities

To fully exploit Astral capabilities, software enhancements for peak picking and data reduction are needed. Binning strategies or adaptive digitizer rates could manage data volume without sacrificing resolution. Integration with real-time search algorithms may enable intelligent MS/MS targeting, further boosting throughput. In the long term, combined Orbitrap-Astral platforms may support automated proteoform workflows in pharmaceutical and clinical laboratories.

Conclusion

The Orbitrap Astral mass spectrometer successfully measures intact proteins up to ~150 kDa and delivers high-quality top-down MS/MS spectra at enhanced acquisition rates. This parallel analyzer approach offers a promising route to faster, more comprehensive protein characterization in research and industrial settings.

References

1. Stewart H, Arrey T, Phlairaharn T, Damoc E, Hoek M, Hock C. Analytical Chemistry. 2023;95(42):15656–15664.
2. Stewart H, Arrey T, Phlairaharn T, Damoc E, Hoek M, Hock C. Journal of the American Society for Mass Spectrometry. 2023;35(1):74–81.
3. Viner J, et al. Proceedings of the 65th ASMS Conference; 2017: Indianapolis, Indiana.