Maximizing sample throughput and sensitivity in nano- and capillary-LC-MS

Significance of the Topic

Nano- and capillary-flow liquid chromatography coupled to mass spectrometry (LC-MS) represents the benchmark for in-depth proteomic analyses due to its superior sensitivity and chromatographic resolution. However, the inherently slow sample loading, gradient migration, washing and equilibration steps of single-column, low-flow workflows lead to significant mass spectrometer idle time and limited sample throughput. Addressing these bottlenecks is critical for large-cohort studies, clinical applications and high-throughput screening assays.

Objectives and Overview

The primary goal of this study was to evaluate a novel tandem direct injection (TDI) LC-MS workflow designed to maximize MS utilization and sample throughput for both deep-dive and high-throughput proteomics. By employing two parallel analytical columns and binary pumps, offset gradients enable near-continuous sample introduction. The workflow was tested in data-dependent acquisition (DDA) and data-independent acquisition (DIA) modes for both label-free quantification (LFQ) and tandem mass tag (TMT) analyses.

Methodology and Instrumentation

Sample Preparation and Consumables:

• Thermo Scientific Pierce HeLa Digest/PRTC standard (10 µg/vial) reconstituted in 0.1 % formic acid/2 % ACN or 0.015 % n-dodecyl-D-maltoside.
• TMTpro 18-plex labeling reagent for multiplexed quantification.
• Optima LC/MS grade solvents: water, acetonitrile, isopropanol with 0.1 % formic acid.

Instrumentation Setup:

• Vanquish Neo UHPLC system with two Binary Pump N modules and a dual-barrel column compartment.
• Sonation double-barrel oven (DBO) housing two coiled nanoViper PepMap Neo columns (50–75 µm I.D., 15–75 cm length).
• Thermo Scientific Nanospray Flex ion source modified with the Sonation DBO and dual spray emitters.
• Orbitrap Exploris 480 MS or Orbitrap Astral MS for high-resolution DDA and DIA acquisitions.
• COControl software for independent oven temperature control and Vanquish User Interface scripts to automate fluidic configuration and column resistance measurement.

Method Configuration:

• Automatic method editor populates valve switching, pump pressures, flow rates and spray voltage timing based on user-defined flow, injection volume and gradient length.
• Gradient lengths ranged from 90 min to 360 min for deep profiling; short gradients (∼14 min) enabled 100–180 samples/day throughput.
• Column resistance measurements ensure optimal maximum flow rates for washing, equilibration and loading.

Main Results and Discussion

• Deep Proteome Profiling: Using a 75 µm × 75 cm column at 250 nL/min, MS utilization increased from 70 % (direct injection) to 93 % (TDI), raising throughput from 12 to 18 samples/day without loss in protein identification or quantification precision.
• TMTpro 18-plex: Single-shot DDA of 1 µg TMT-labeled HeLa digest in a 360-min gradient yielded >5,700 quantified proteins (SEQUEST HT), further boosted to >6,700 with CHIMERYS processing.
• High-Throughput Gradients: Short gradients on 75 µm × 15 cm columns at 500–1,000 nL/min delivered 100–180 samples/day throughputs with over 90 % MS utilization, identifying ~5,000–6,000 protein groups from 200 ng injections in DDA and >4,300 proteins in DIA from 40 ng injections.
• Low-Nanoflow Sensitivity: At 100 nL/min with a 75 µm × 15 cm column, 36–72 samples/day were achieved, identifying ~2,600 proteins from 5 ng HeLa digest in LFQ-DDA and quantifying 1,070–1,564 TMTpro proteins from as little as 2–10 ng total protein.
• Carryover Minimization: Automated trapezoidal wash cycles (up to eight column volumes) reduced carryover to below 0.02 % peak area and undetectable peptide IDs in high-load (1,000 ng) TMT and DIA workflows.
• Self-packed Column Support: Using 75 µm × 20 cm pulled-tip columns, 96 samples/day at 700 nL/min in DIA mode quantified ~10,000 protein groups from cell lysate with clear differentiation between biological conditions.

Benefits and Practical Applications

• Maximized MS utilization (up to 98 %) by eliminating idle time through offset gradients on parallel columns.
• Flexible throughput options (24–180 samples/day) adaptable to deep profiling or large-cohort studies.
• Robust quantification precision (<10 % CV for proteins and peptides) across a wide dynamic range of sample loads (2–1,000 ng).
• Significant sensitivity gains, enabling proteome analysis of limited and single-cell equivalent samples.
• Automated fluidic and method setup reduces hands-on time and risk of error, facilitating routine adoption in proteomics laboratories.

Future Trends and Applications

• Integration with emerging AI-driven data analysis platforms for real-time method optimization and sample prioritization.
• Extension to post-translational modification mapping and targeted assays using parallel reaction monitoring (PRM) or selected ion monitoring (SIM).
• Adaptation for single-cell proteomics via higher multiplexing, reduced flow rates and further miniaturized columns or emitter geometries.
• Application to clinical biomarker discovery and high-throughput drug screening where throughput and reproducibility are paramount.

Conclusion

The tandem direct injection workflow, combining a dual-column Vanquish Neo UHPLC configuration, Sonation double-barrel oven, and Orbitrap mass spectrometer, delivers a transformative increase in MS utilization and sample throughput for nano- and capillary-flow LC-MS. The approach harmonizes deep proteome coverage, high-throughput operation, sensitivity for limited samples and minimized carryover, enabling proteomics laboratories to achieve unprecedented efficiency and robustness in both discovery and quantitative applications.

References

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2. Stewart H. et al. Anal. Chem. 2023;95(42):15656–15664.
3. Sonation GmbH. Double barrel oven for Thermo Scientific NanoSpray Flex ion source ES071 and ES072. 2024.
4. Pynn C. et al. Thermo Fisher Scientific Technical Note 72899. 2019.
5. Zheng R. et al. Thermo Fisher Scientific Technical Note 73671. 2020.
6. Vanquish Neo System User Guide Revision 2.0. 2024.