Quantitative single-cell proteomics as a tool to characterize cellular hierarchies

Erwin M. Schoof (), Benjamin Furtwängler, Nil Üresin, Nicolas Rapin, Simonas Savickas, Coline Gentil, Eric Lechman, Ulrich auf dem Keller, John E. Dick and Bo T. Porse ()
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Erwin M. Schoof: University of Copenhagen
Benjamin Furtwängler: University of Copenhagen
Nil Üresin: University of Copenhagen
Nicolas Rapin: University of Copenhagen
Simonas Savickas: Technical University of Denmark
Coline Gentil: University of Copenhagen
Eric Lechman: Princess Margaret Cancer Centre, University Health Network
Ulrich auf dem Keller: Technical University of Denmark
John E. Dick: Princess Margaret Cancer Centre, University Health Network
Bo T. Porse: University of Copenhagen

Nature Communications, 2021, vol. 12, issue 1, 1-15

Abstract: Abstract 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.

Date: 2021
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DOI: 10.1038/s41467-021-23667-y

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