February 15, 2024
Journal Article

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

Abstract

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 mobility-enhanced mass spectrometry acquisition and peptide identification method, TIFF (Transferring Identification based on FAIMS Filtering), 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). 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.

Published: February 15, 2024

Citation

Woo J., G. Clair, S.M. Williams, S. Feng, C. Tsai, R.J. Moore, and W.B. Chrisler, et al. 2022. Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering. Cell Systems 13, no. 5:426-434.e4. PNNL-SA-156470. doi:10.1016/j.cels.2022.02.003

Research topics