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Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering
- Source :
- Cell Systems; May 2022, Vol. 13 Issue: 5 p426-434.e4
- Publication Year :
- 2022
-
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, 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.
Details
- Language :
- English
- ISSN :
- 24054712
- Volume :
- 13
- Issue :
- 5
- Database :
- Supplemental Index
- Journal :
- Cell Systems
- Publication Type :
- Periodical
- Accession number :
- ejs59655821
- Full Text :
- https://doi.org/10.1016/j.cels.2022.02.003