Ultra-sensitive LC/MS workflow for in-depth label-free analysis of single mammalian cells with nanodroplet sample processing

Importance of the Topic

Mass spectrometry–based single-cell proteomics is emerging as a crucial tool to characterize cellular heterogeneity at the protein level. Unlike transcriptomic approaches, proteomic workflows directly measure functional molecules, offering deeper insight into cell-to-cell variability in biological and clinical research. Ultra-sensitive, label-free analysis methods enable quantification of hundreds to thousands of proteins in individual mammalian cells, advancing our understanding of disease mechanisms, drug response, and complex tissue dynamics.

Objectives and Study Overview

This study presents an optimized liquid chromatography–mass spectrometry (LC-MS) workflow for label-free proteomic profiling of single mammalian cells. It combines nanodroplet sample processing with enhanced chromatographic separation and a novel FAIMS Pro interface coupled to the Thermo Scientific™ Orbitrap Eclipse™ Tribrid mass spectrometer. The goals were to improve proteome coverage, reduce chemical noise, and achieve robust quantification in low-attomole samples.

Methodology and Instrumentation

Sample Preparation

• Individual HeLa cells were isolated and processed on the nanoPOTS (nanodroplet Processing in One-pot for Trace Samples) platform, minimizing reaction volume (200 nL vs. 100 µL) and surface contact (0.8 mm² vs. 127 mm²) to reduce sample loss.
• Proteins underwent reduction, alkylation, Lys-C and trypsin digestion, and peptide collection in nanowells.

Separation and Detection

• Peptides were trapped and separated on 20–30 µm i.d. SPE and analytical columns using an UltiMate 3000 RSLCnano system.
• A Thermo Scientific™ FAIMS Pro™ interface provided gas-phase ion mobility filtering to remove singly charged ions and reduce matrix interferences.
• Mass analysis employed an Orbitrap Eclipse™ Tribrid MS with high-resolution MS and HCD fragmentation.

Data Processing

• Raw files were analyzed with Proteome Discoverer 2.4 and MaxQuant software, using match-between-runs to enhance identifications.

Main Results and Discussion

Using 0.5 ng HeLa digest standards, the optimized workflow identified 2 023 protein groups and 8 571 peptide groups (MS/MS at 1% FDR) with two FAIMS compensation voltages over a 2-hour gradient. From single HeLa cells, the method achieved:

• ~830 protein groups and ~3 000 peptides by MS/MS alone.
• ~1 300 protein groups and ~5 800 peptides with match-between-runs.

Compared to the initial nanoPOTS–Lumos setup (211/669 proteins with/without MBR), the Eclipse+FAIMS Pro approach yielded 829/1 300 protein IDs. FAIMS filtering significantly improved sensitivity and dynamic range by suppressing +1 ions and chemical noise.

Benefits and Practical Applications

This label-free, ultra-sensitive workflow enables reliable single-cell proteome coverage beyond 1 000 proteins without labeling. It offers:

• Reduced sample loss via miniaturized digestion volumes.
• Enhanced separation selectivity and noise reduction using FAIMS Pro.
• High quantitative accuracy suitable for QA/QC, biomedical research, and biomarker discovery.

Future Trends and Potential Uses

Advances in microfluidics, ion mobility, and data analysis are expected to further push single-cell proteomics depth and throughput. Integrating multiplexing strategies, real-time FAIMS control, and machine learning–driven data processing will expand applications in clinical diagnostics, drug screening, and systems biology.

Conclusion

The combined nanoPOTS sample preparation, low-nanoflow LC, FAIMS Pro interface, and Orbitrap Eclipse Tribrid MS deliver a robust, label-free single-cell proteomics platform with unprecedented depth and sensitivity. This workflow represents a significant step toward routine proteome profiling of individual mammalian cells.

References

• Zhu Y. et al. Nature Communications 9, 882 (2018).
• Schweppe D.K. et al. Analytical Chemistry 91(6):4010–4016 (2019).