Single-cell proteomics (SCP) promises to revolutionize biomedicine by providing an unparalleled view of the proteome in individual cells. Here, we present a high-sensitivity SCP workflow named Chip-Tip, identifying >5,000 proteins in individual HeLa cells. It also facilitated direct detection of post-translational modifications in single cells, making the need for specific post-translational modification-enrichment unnecessary. Our study demonstrates the feasibility of processing up to 120 label-free SCP samples per day. An optimized tissue dissociation buffer enabled effective single-cell disaggregation of drug-treated cancer cell spheroids, refining overall SCP analysis. Analyzing nondirected human-induced pluripotent stem cell differentiation, we consistently quantified stem cell markers OCT4 and SOX2 in human-induced pluripotent stem cells and lineage markers such as GATA4 (endoderm), HAND1 (mesoderm) and MAP2 (ectoderm) in different embryoid body cells. Our workflow sets a benchmark in SCP for sensitivity and throughput, with broad applications in basic biology and biomedicine for identification of cell type-specific markers and therapeutic targets.
Enhanced sensitivity and scalability with a Chip-Tip workflow enables deep single-cell proteomics.
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作者:Ye Zilu, Sabatier Pierre, van der Hoeven Leander, Lechner Maico Y, Phlairaharn Teeradon, Guzman Ulises H, Liu Zhen, Huang Haoran, Huang Min, Li Xiangjun, Hartlmayr David, Izaguirre Fabiana, Seth Anjali, Joshi Hiren J, Rodin Sergey, Grinnemo Karl-Henrik, Hørning Ole B, Bekker-Jensen Dorte B, Bache Nicolai, Olsen Jesper V
| 期刊: | Nature Methods | 影响因子: | 32.100 |
| 时间: | 2025 | 起止号: | 2025 Mar;22(3):499-509 |
| doi: | 10.1038/s41592-024-02558-2 | ||
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