Low-flow On-line 2D LCMS Hyphenated with HRAM MS for Comprehensive Proteome Profiling

Significance of the Topic

This work addresses the fundamental challenge in bottom-up proteomics of balancing depth of coverage with throughput. The vast dynamic range and complexity of biological fluids such as plasma require multidimensional separations to reveal low-abundance proteins, yet traditional offline fractionation compromises throughput and reproducibility. An automated online 2D LC-MS approach promises deep proteome profiling within practical analysis times and minimal manual handling.

Objectives and Study Overview

The primary goal was to develop and demonstrate an online low-flow two-dimensional reversed-phase LC-MS/MS method coupled to high-resolution accurate-mass (HRAM) detection. The study focused on profiling complex samples—HeLa cell digest and crude plasma digest—using an automated high pH × low pH RP × RP configuration. Key performance metrics included proteome depth, chromatographic robustness, fraction overlap, and overall throughput.

Instrumental Setup

• UltiMate 3000 RSLCnano system equipped with NCS-3500RS micro-flow pump, NCP-3200RS nanopump, WPS-3000TPLRS autosampler, and VWD-3400RS detector modules.
• Two-position 10-port switching valve for seamless first- to second-dimension transfer.
• PepSwift monolithic capillary column (100 µm × 250 mm) for high-pH peptide fractionation.
• Two trap columns (75 µm × 20 mm) for enrichment of diluted fractions.
• EASY-Spray analytical column (75 µm × 150 mm, 3 µm particles) for low-pH separations.
• Thermo Scientific Q Exactive HF-X Hybrid Quadrupole-Orbitrap mass spectrometer operated in full MS/data-dependent acquisition mode.

Methodology and Instrumentation

First-dimension separations used 10 mM ammonium bicarbonate at pH 10 (mobile phase A) versus 80% acetonitrile at pH 10 (mobile phase B) at 0.3 µL/min. Eluate was mixed online with 0.05% TFA via micro-flow pump to acidify and direct peptides to the trap columns. The second dimension employed 0.1% formic acid in water (A) versus 80% acetonitrile with 0.1% FA (B) at 0.4 µL/min. Methods with 2, 4, or 8 fractions were tested (total run times 135, 225, and 405 min respectively), using HeLa digest (200 ng/µL or 1 µg/µL) and crude plasma digest without reduction/alkylation.

Main Results and Discussion

The high pH × low pH RP × RP approach yielded deep proteome coverage without peak broadening even at high sample loads. Key observations included:

• Symmetric and narrow peaks with retention time precision comparable to one-dimensional runs.
• Negligible overlap of selected proteotypic peptides across adjacent fractions, confirming effective orthogonality.
• Robust separation profiles across repeated injections, enabling reproducible data for both discovery and targeted workflows.
• Protein identifications in plasma increased from ~206 groups (2 fractions) to ~317 (4 fractions) and ~394 (8 fractions), with proportional gains in peptide spectrum matches.

Benefits and Practical Applications

The automated online 2D workflow minimizes manual fraction collection and transfer losses, enhancing reproducibility and throughput. It supports:

• Comprehensive profiling of complex biofluids and cell lysates in a routine laboratory setting.
• High-throughput experiments with minimal instrument downtime for column washing and equilibration.
• Potential integration into targeted proteomics assays with scheduled acquisition windows.

Future Trends and Opportunities

Further developments may include:

• Optimization of gradient schemes and column chemistries to enhance orthogonality and depth.
• Increased fraction numbers or variable segmentations driven by sample complexity.
• Integration with data-independent acquisition and real-time analytics for faster data processing.
• Applications in clinical biomarker discovery and quality-control workflows for regulated environments.

Conclusion

This study establishes a robust online low-flow 2D RP × RP LC-MS/MS platform coupled to HRAM detection as a new standard for deep, automated proteome profiling. The method delivers high reproducibility, scalable fractionation, and significant gains in protein identifications without manual intervention, offering an attractive alternative to traditional one-dimensional and offline workflows.

Reference

• RSLCnano pre-concentration nano LC kit (P/N 6720.0310) in the Ultimate 3000 RSLCnano Standard Applications Guide.
• Boychenko A., Pynn C., van den Berg B., Arrey T.N., Baynham M., Decrop R.; “High-throughput capillary-flow LC-MS proteomics with maximum MS utilization.” TN 72227.