期刊
NATURE COMMUNICATIONS
卷 12, 期 1, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41467-021-23667-y
关键词
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资金
- European Commission [GA-2013-609409, 2017-389, ALTF 1595-2014]
- Kirsten & Freddy Johansen Foundation
- Novo Nordisk Foundation (Novo Nordisk Foundation Centre for Stem Cell Biology, DanStem) [NNF17CC0027852]
- Novo Nordisk Foundation as part of the Copenhagen Bioscience Ph.D. Programme [NNF19SA0035442]
- Novo Nordisk Foundation Young Investigator Award [NNF16OC0020670]
- Kirsten & Freddy Johansen International Prize
- Princess Margaret Cancer Centre Foundation
- Ontario Institute for Cancer Research
- Province of Ontario
- Canadian Institutes for Health Research
- Canadian Cancer Society Research Institute
- Terry Fox Foundation
- Genome Canada through the Ontario Genomics Institute
- Canada Research Chair
- PRO-MS: Danish National Mass Spectrometry Platform for Functional Proteomics [5072-00007B]
- Independent Research Fund Denmark
- Svend Andersen Foundation
- Candys Foundation
The study demonstrates a comprehensive experimental and computational workflow that establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses, enabling the exploration of cellular heterogeneity. The approach presented is capable of consistently quantifying around 1000 proteins per cell within limited instrument time.
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 similar to 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.
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