An In-depth Plasma Proteomics Workflow Powered by Orbitrap Astral Mass Spectrometer

Importance of the Topic

Plasma proteomics enables the discovery of disease biomarkers, monitors therapeutic response and supports diagnostic and prognostic applications. High abundance proteins in plasma span a dynamic range of over seven orders of magnitude, presenting analytical challenges for bottom‐up workflows. A robust, label‐free, data‐independent acquisition solution that balances sample throughput and proteome coverage is essential to fully exploit large biobank collections and routine clinical samples.

Objectives and Study Overview

This work describes the development and evaluation of a high‐throughput plasma proteomics workflow using the Thermo Scientific Orbitrap Astral mass spectrometer. The main goals were to:

• Achieve deep proteome coverage without sacrificing sample throughput.
• Compare three sample preparation methods: neat plasma, depleted plasma and nanoparticle‐based enrichment.
• Test multiple LC gradient lengths to offer flexibility from highest throughput to highest depth.

Methodology and Instrumentation

Sample Preparation:

• Neat plasma: direct analysis of pooled healthy donor plasma.
• Depleted plasma: removal of abundant proteins using High Select depletion columns.
• Enriched plasma: nanoparticle‐based capture with the Seer Proteograph Product Suite on SP100 automation.

Liquid Chromatography:

• Multiple gradient methods ranging from ~8 to 80 min, accommodating 4 to 180 samples per day (SPD).
• Columns: EASY‐Spray PepMap and uPAC Neo C18 columns with trap cartridges for optimized peptide separation.

Mass Spectrometry:

• Orbitrap Astral detector with 240 000 resolution at m/z 200.
• DIA acquisition over 380–980 m/z with 2 m/z isolation windows and no overlap.
• Collision energy at 25% HCD, AGC target 500%, and experiment‐dependent maximum injection times.
• Data processed in Proteome Discoverer 3.1 using the CHIMERYS node with Inferys spectral prediction.

Main Results and Discussion

The Astral‐based workflow delivered:

• Neat plasma: highest throughput but limited depth, yet still identified thousands of protein groups across short and long gradients.
• Depleted plasma: approximately two‐fold increase in protein identifications compared to neat plasma.
• Nanoparticle‐enriched plasma: superior depth, yielding over 6 000 protein groups and nearly 50 000 unique peptides in the deepest protocol.

Dynamic range coverage exceeded seven orders of magnitude. Twenty‐four established clinical biomarkers were reliably quantified with two or more unique peptides. Between 5 and 255 FDA drug‐target proteins were detected depending on the method.

Benefits and Practical Applications

• Flexible trade‐off between throughput (up to 180 SPD) and depth (extensive protein group identification).
• Label‐free DIA removes the need for isotopic or isobaric labeling, simplifying sample handling.
• Compatibility with automated sample preparation and biobank workflows enhances reproducibility.
• High sensitivity and dynamic range allow detection of low‐abundance biomarkers.

Future Trends and Opportunities

Future developments may include:

• Integration of advanced AI‐driven spectral deconvolution and real‐time acquisition strategies.
• Expanded use of nanoparticle chemistries for targeted enrichment of low‐abundance protein classes.
• Higher multiplexing in DIA to further boost throughput without loss of coverage.
• Application to clinical and regulatory settings for companion diagnostics and personalized medicine.

Conclusion

The Orbitrap Astral mass spectrometer, combined with optimized sample preparation and LC gradient options, delivers unparalleled performance in plasma proteomics. This workflow achieves both high throughput and deep proteome coverage, positioning it as a powerful platform for biomarker discovery and routine clinical research.

References

• Hakimi A., Delanghe B., Arrey T.N., Flora A.K., Loziuk P.L., Horn D.M., Webb S., Damoc E. An In-depth Plasma Proteomics Workflow Powered by Orbitrap Astral Mass Spectrometer. Thermo Fisher Scientific; 2023.