Quantitative single-cell proteomics as a tool to characterize cellular hierarchies.
Quantitative single-cell proteomics as a tool to characterize cellular hierarchies.
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DOI:
10.1038/s41467-021-23667-y
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发表时间:
2021-06-07
影响因子:
16.6
通讯作者:
Porse BT
中科院分区:
文献类型:
--
作者:
Schoof EM;Furtwängler B;Üresin N;Rapin N;Savickas S;Gentil C;Lechman E;Keller UAD;Dick JE;Porse BT
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. Single-cell proteomics can provide insights into the molecular basis for cellular heterogeneity. Here, the authors develop a multiplexed single-cell proteomics and computational workflow, and show that their strategy captures the cellular hierarchies in an Acute Myeloid Leukemia culture model.
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DOI:
10.1126/science.1242379
发表时间:
2013-11-29
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
Khan Z;Ford MJ;Cusanovich DA;Mitrano A;Pritchard JK;Gilad Y
通讯作者:
Gilad Y
影响因子:
18.4
作者:
Levitin HM;Yuan J;Sims PA
通讯作者:
Sims PA
影响因子:
82.9
作者:
Eppert, Kolja;Takenaka, Katsuto;Dick, John E.
通讯作者:
Dick, John E.
影响因子:
12.3
作者:
Budnik B;Levy E;Harmange G;Slavov N
通讯作者:
Slavov N
影响因子:
50.3
作者:
Lechman ER;Gentner B;Ng SW;Schoof EM;van Galen P;Kennedy JA;Nucera S;Ciceri F;Kaufmann KB;Takayama N;Dobson SM;Trotman-Grant A;Krivdova G;Elzinga J;Mitchell A;Nilsson B;Hermans KG;Eppert K;Marke R;Isserlin R;Voisin V;Bader GD;Zandstra PW;Golub TR;Ebert BL;Lu J;Minden M;Wang JC;Naldini L;Dick JE
通讯作者:
Dick JE