TY - JOUR

T1 - Quantitative single-cell proteomics as a tool to characterize cellular hierarchies

AU - Schoof, Erwin M

AU - Furtwängler, Benjamin

AU - Üresin, Nil

AU - Rapin, Nicolas

AU - Savickas, Simonas

AU - Gentil, Coline

AU - Lechman, Eric

AU - Keller, Ulrich Auf dem

AU - Dick, John E

AU - Porse, Bo T

PY - 2021/6/7

Y1 - 2021/6/7

N2 - 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.

AB - 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.

KW - Humans

KW - Leukemia, Myeloid, Acute

KW - Mass Spectrometry

KW - Neoplastic Stem Cells

KW - Proteome/metabolism

KW - Proteomics/methods

KW - RNA

KW - Single-Cell Analysis/methods

KW - Workflow

U2 - 10.1038/s41467-021-23667-y

DO - 10.1038/s41467-021-23667-y

M3 - Journal article

C2 - 34099695

VL - 12

SP - 3341

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

IS - 1

ER -