Fine-Tuning of Label-Free Single-Cell Proteomics Workflows

Area of Science:

• Proteomics
• Cellular Biology
• Analytical Chemistry

Background:

• Single-cell proteomics is crucial for understanding cellular heterogeneity.
• Current methods face limitations in robustness, reproducibility, and throughput, hindering large-scale studies.
• Analyzing large single-cell cohorts is essential for statistical confidence.

Purpose of the Study:

• To optimize mass spectrometry-based single-cell proteomics workflows.
• To improve robustness, reproducibility, and throughput for analyzing cellular heterogeneity.
• To establish a reliable method for quantifying thousands of proteins per single cell.

Main Methods:

• Benchmarking of three nanoElute2-compatible workflows with different sample supports.
• Comparison of optimized EVO96 workflow with Evosep-based separations at varying throughputs.
• Evaluation of enzyme/protein ratios for digestion efficiency and chromatographic setup refinement.

Main Results:

• Established a streamlined, automated sample preparation and direct injection protocol.
• Achieved quantification of up to 5000 proteins per single HeLa cell.
• Developed a robust workflow with a throughput of 55 samples per day at 10 min gradient time.

Conclusions:

• The optimized workflow significantly enhances the capabilities of single-cell proteomics.
• This advancement addresses key limitations, enabling more in-depth studies of cellular heterogeneity.
• The method provides a robust and high-throughput solution for large-scale single-cell proteome analysis.