Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering

Single-cell proteomics (scProteomics) promises to advance our understanding of cell functions within complex biological systems. However, a major challenge of current methods is their inability to identify and provide accurate quantitative information for low-abundance proteins. Herein, we describe an ion- mobilityenhanced mass spectrometry acquisition and peptide identification method, transferring identification based on FAIMS filtering (TIFF), to improve the sensitivity and accuracy of label-free scProteomics. TIFF extends the ion accumulation times for peptide ions by filtering out singly charged ions. The peptide identities are assigned by a three-dimensional MS1 feature matching approach (retention time, accurate mass, and FAIMS compensation voltage). The TIFF method enabled unbiased proteome analysis to a depth of >1,700 proteins in single HeLa cells, with >1,100 proteins consistently identified. As a demonstration, we applied the TIFF method to obtain temporal proteome profiles of >150 single murine macrophage cells during lipopolysaccharide stimulation and identified time-dependent proteome changes. A record of this paper's transparent peer review process is included in the supplemental information.

Automated summary

Single-cell proteomics (scProteomics) is a powerful tool for studying cell functions in complex biological systems. However, current methods face challenges in identifying and quantifying low-abundance proteins accurately. In this study, we present a method called transferring identification based on FAIMS filtering (TIFF), which combines ion mobility-enhanced mass spectrometry acquisition and peptide identification to improve the sensitivity and accuracy of label-free scProteomics. By filtering out singly charged ions, the TIFF method extends the ion accumulation times for peptide ions. Peptide identities are determined using a three-dimensional MS1 feature matching approach. Using TIFF, we achieved unbiased proteome analysis of over 1,700 proteins in single HeLa cells, with more than 1,100 proteins consistently identified. We also applied the TIFF method to study time-dependent proteome changes in single murine macrophage cells during lipopolysaccharide stimulation.