Balancing sensitivity and throughput in single-cell proteomics using low-nanoflow LC-MS

Significance of the Topic

Profiling the proteome of individual cells and sub-nanogram samples is critical for uncovering cellular heterogeneity and understanding complex biological processes. Nano-flow liquid chromatography-mass spectrometry (nLC-MS) at flow rates below 300 nL/min greatly improves ionization efficiency and detection sensitivity. However, traditional low-flow workflows suffer from limited sample throughput, constraining large-scale or high-frequency analyses. This study addresses the sensitivity–throughput trade-off by developing and benchmarking high-throughput nLC-MS methods suited for single-cell and ultra-limited sample proteomics.

Objectives and Study Overview

This work presents seven optimized nanoLC-MS workflows for label-free quantitation (LFQ) of limited material, including single-cell proteomics. The goals were to balance deep proteome coverage with high sample throughput, compare data acquisition strategies (DDA, wide-window DDA, DIA), implement a trap-and-elute (T&E) approach to accelerate loading, and assess the impact of advanced mass analyzers on sensitivity and throughput.

Methodology and Instrumentation

The experimental strategy combined precise sample preparation, varied LC-MS configurations, and multiple acquisition modes:

• Sample Preparation: HeLa digest aliquots (0.25–10 µL injections, 250 pg–5 ng) spiked with PRTC standard; single-cell samples processed in 384-well plates by a one-pot, label-free protocol; TMTpro 18-plex labeled HeLa for multiplex single-cell assays.
• Chromatography: Thermo Vanquish Neo UHPLC with 50 µm × 15 cm C18 column at 100 nL/min; direct injection and trap-and-elute workflows using a 300 µm × 5 mm trap in backward-flush mode; 10 µm emitter at 50 °C.
• Mass Spectrometry: Thermo Orbitrap Exploris 480 or Orbitrap Astral with FAIMS Pro interface; MS1 resolution 120 k, MS2 resolution 6 k; DIA isolation windows varied from 20 m/z to 100 m/z.
• Data Acquisition: Data-dependent acquisition (DDA), wide-window DDA (WW-DDA), library-free DIA; optimized MS2 injection times and scan speeds.
• Data Analysis: Proteome Discoverer 2.5 with SEQUEST HT and INFERYS rescoring; CHIMERYS in Proteome Discoverer 3.0 for chimeric DDA spectra; Spectronaut 17 for DIA processing; FDR < 1% at peptide and protein levels.

Main Results and Discussion

Throughput and cycle times varied by workflow:

• Direct Injection: 24–72 samples per day (SPD) with 20–30 min cycles; MS utilization 55–70%.
• Trap-and-Elute: 100 SPD (14.4 min cycle) and 120 SPD (12 min cycle); MS utilization up to 78%.

Proteome coverage at 250 pg HeLa digest:

• DDA (2-step SEQUEST + INFERYS): ~1,500 protein groups.
• WW-DDA (CHIMERYS): >1,800 protein groups.
• DIA (SN17): >2,600 protein groups.
• Trap-and-Elute at 100 SPD: ~2,200 protein groups; as little as 60 pg yielded >1,100 proteins.
• Orbitrap Astral with pulled-tip column: >5,000 proteins at 100 SPD from 250 pg.
• WW-DIA open MS1 window: ~3,000 proteins in 20 min, covering >4 orders of magnitude dynamic range.

Single-cell performance:

• LFQ-DIA QC across labs: >1,200 protein IDs per cell; individual HeLa cells: ~1,700 proteins.
• TMTpro 18-plex SCoPE-MS: >800 cells/day with >1,100 protein IDs.
• TMTpro 35-plex potential: up to 864 cells/day and projected >1,600 cells/day.

Benefits and Practical Applications

The optimized platform enables high-sensitivity analysis of picogram-level samples and high-throughput profiling of single cells or small populations. It supports both label-free and multiplexed workflows, facilitating quantitative studies in cell biology, clinical research, QA/QC, and industrial analytics. The trap-and-elute design reduces cycle times without compromising proteome depth.

Future Trends and Opportunities

Further integration of advanced mass analyzers, refined microfluidics, and higher-plex isobaric tagging strategies (e.g., TMTpro 35-plex) will push throughput beyond 2,000 cells/day. Automation of sample preparation, real-time data acquisition adjustments, and improved bioinformatics will drive single-cell proteomics toward routine large-scale applications in systems biology and precision medicine.

Conclusion

This study delivers a versatile nanoLC-MS framework that successfully balances sensitivity and throughput for proteomics of minute samples. By comparing acquisition modes and introducing a trap-and-elute workflow, the platform achieves up to 120 SPD with deep proteome coverage. Advanced instrumentation further elevates sensitivity, supporting robust single-cell and sub-nanogram analyses.

References

1. Manuel Matzinger et al., Analytical Chemistry, 2023, 95(9), 4435–4445
2. Karel Stejskal et al., Analytical Chemistry, 2021, 93(25), 8704–8710
3. Runsheng Zheng et al., Analytical Chemistry, 2023, 95(51), 18673–18678