New standards for plasma proteomics—Balancing throughput for large sample cohorts and depth of analysis for biomarker discovery

Significance of the topic

Plasma proteomics plays a pivotal role in biomarker discovery, disease monitoring, and therapeutic evaluation due to the accessibility of blood samples and extensive biobank resources. However, the vast concentration range of plasma proteins challenges the detection of low-abundance biomarkers when abundant proteins dominate mass spectrometric signals.

Objectives and Overview of the Study

This study aimed to establish a high-throughput, label-free DIA workflow on the Thermo Scientific Orbitrap Astral mass spectrometer that does not compromise proteome depth. Four common plasma sample preparation methods—neat, immunodepleted, fractionated/enriched with engineered nanoparticles, and pooled fraction analysis—were compared for throughput and depth of coverage.

Methodology and Instrumentation

Sample preparation approaches:

• Neat plasma digestion using EasyPep kits without depletion.
• Immunodepletion of the 14 most abundant plasma proteins with High Select Depletion Spin Columns.
• Fractionation and enrichment via the Seer Proteograph Product Suite (five nanoparticle fractions and pooled fraction analysis).

UHPLC and MS platform:

• Thermo Scientific Vanquish Neo UHPLC with columns ranging from PepMap 15 cm to µPAC Neo 110 cm.
• Thermo Scientific Orbitrap Astral mass spectrometer operated in positive‐ion peptide mode, using DIA windows and CHIMERYS™ intelligent search in Proteome Discoverer 3.1.

LC-MS methods varied from 8 min (180 samples/day) to 107 min (14 samples/day) to balance speed versus depth.

Main Results and Discussion

Neat plasma (200 ng–2 µg load):

• 180 SPD (8 min) method identified ~643 protein groups (3,968 unique peptides).
• 24 SPD (50 min) method identified ~1,137 protein groups (7,720 unique peptides).

Depleted plasma (1 µg load, 80 min, 18 SPD):

• ~2,702 protein groups detected, a 1.5–2× increase over neat plasma.

Seer Proteograph enrichment:

• Individual fractions analyzed at 36 SPD (30 min each) yielded ~3,104 protein groups per fraction by capillary flow.
• Pooled fractions analyzed at 60 SPD (24 min) by nanoflow achieved ~3,285 protein groups.
• High-depth analysis at 14 SPD (107 min) identified up to ~5,036 protein groups (2 µg load) and with extended gradients up to ~6,341 protein groups.

The Orbitrap Astral’s high resolution, sensitivity, and speed enabled ~2× deeper proteome coverage per unit time compared to prior commercial platforms.

Benefits and Practical Applications

• Flexible workflows allow users to prioritize either large cohort throughput or maximal proteome depth without changing hardware.
• Label-free DIA quantitation delivers precise, reproducible data across hundreds of plasma samples per day.
• Enrichment with engineered nanoparticles expands the detectable dynamic range, facilitating discovery of low-abundance biomarkers.

Future Trends and Potential Applications

Ongoing developments will likely focus on:

• Automated, high-capacity sample processing combining depletion and nanoparticle enrichment.
• Integration of AI-driven acquisition strategies to further optimize window placement and duty cycle.
• Application of deep plasma workflows in longitudinal clinical trials and population-scale studies for precision medicine.

Conclusion

The Orbitrap Astral mass spectrometer, when paired with versatile plasma preparation strategies, achieves unprecedented balance between throughput and depth in plasma proteomics. This performance paves the way for large-scale biomarker discovery and robust clinical proteomic workflows.

Reference

1. Schiess R, et al. Targeted proteomic strategy for clinical biomarker discovery. Mol Oncol. 2009;3(1).
2. Shammel Baker E, et al. Mass spectrometry for translational proteomics: progress and clinical implications. Genome Med. 2012;4:63.
3. McArdle A, et al. Standardized workflow for precise mid- and high-throughput proteomics of blood biofluids. Clin Chem. 2022;68(3):450–460.
4. Geyer PE, et al. High-resolution serum proteome trajectories in COVID-19 reveal patient-specific seroconversion. EMBO Mol Med. 2021;13:e14167.
5. Viode A, et al. A simple, time- and cost-effective, high-throughput depletion strategy for deep plasma proteomics. Sci Adv. 2023;9(13):eadf9717.
6. Cao X, et al. Evaluation of spin columns for human plasma depletion to facilitate MS-based proteomics analysis of plasma. J Proteome Res. 2021;20(9):4610–4620.
7. Ferdosi S, et al. Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano–bio interactions. Proc Natl Acad Sci USA. 2022;119(11).