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Combination of Chemical Genetics and Phosphoproteomics for Kinase Signaling Analysis Enables Confident Identification of Cellular Downstream Targets

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Oppermann,  Felix S.
Ullrich, Axel / Molecular Biology, Max Planck Institute of Biochemistry, Max Planck Society;

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Grundner-Culemann,  Kathrin
Ullrich, Axel / Molecular Biology, Max Planck Institute of Biochemistry, Max Planck Society;

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Kumar,  Chanchal
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Daub,  Henrik
Ullrich, Axel / Molecular Biology, Max Planck Institute of Biochemistry, Max Planck Society;

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Citation

Oppermann, F. S., Grundner-Culemann, K., Kumar, C., Gruss, O. J., Jallepalli, P. V., & Daub, H. (2012). Combination of Chemical Genetics and Phosphoproteomics for Kinase Signaling Analysis Enables Confident Identification of Cellular Downstream Targets. Molecular and Cellular Proteomics, 11.4. doi:10.1074/mcp.O111.012351.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000E-E40F-E
Abstract
Delineation of phosphorylation-based signaling networks requires reliable data about the underlying cellular kinasesubstrate interactions. We report a chemical genetics and quantitative phosphoproteomics approach that encompasses cellular kinase activation in combination with comparative replicate mass spectrometry analyses of cells expressing either inhibitor-sensitive or resistant kinase variant. We applied this workflow to Plk1 (Polo-like kinase 1) in mitotic cells and induced cellular Plk1 activity by wash-out of the bulky kinase inhibitor 3-MB-PP1, which targets a mutant kinase version with an enlarged catalytic pocket while not interfering with wild-type Plk1. We quantified more than 20,000 distinct phosphorylation sites by SILAC, approximately half of which were measured in at least two independent experiments in cells expressing mutant and wild-type Plk1. Based on replicate phosphorylation site quantifications in both mutant and wild-type Plk1 cells, our chemical genetic proteomics concept enabled stringent comparative statistics by significance analysis of microarrays, which unveiled more than 350 cellular downstream targets of Plk1 validated by full concordance of both statistical and experimental data. Our data point to hitherto poorly characterized aspects in Plk1-controlled mitotic progression and provide a largely extended resource for functional studies. We anticipate the described strategies to be of general utility for systematic and confident identification of cellular protein kinase substrates.