Quantitative single-cell proteomics as a tool to characterize cellular hierarchies
Research output: Contribution to journal › Journal article › peer-review
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- s41467-021-23667-y
Final published version, 5.93 MB, PDF document
Large-scale single-cell analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems, but have largely been limited to RNA-based technologies. Here we present a comprehensive benchmarked experimental and computational workflow, which establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses. By exploiting a primary leukemia model system, we demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within this aberrant developmental hierarchy. Our approach is capable of consistently quantifying ~1000 proteins per cell across thousands of individual cells using limited instrument time. Furthermore, we develop a computational workflow (SCeptre) that effectively normalizes the data, integrates available FACS data and facilitates downstream analysis. The approach presented here lays a foundation for implementing global single-cell proteomics studies across the world.
Original language | English |
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Journal | Nature Communications |
Volume | 12 |
Issue number | 1 |
Pages (from-to) | 3341 |
ISSN | 2041-1723 |
DOIs | |
Publication status | Published - 7 Jun 2021 |
- Humans, Leukemia, Myeloid, Acute, Mass Spectrometry, Neoplastic Stem Cells, Proteome/metabolism, Proteomics/methods, RNA, Single-Cell Analysis/methods, Workflow
Research areas
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