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A Mass Spectrometry-Based Approach for Mapping Protein Subcellular Localization Reveals the Spatial Proteome of Mouse Primary Neurons

MPG-Autoren
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Itzhak,  Daniel N.
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Tyanova,  Stefka
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Mishra,  Archana
Department: Molecules-Signaling-Development / Klein, MPI of Neurobiology, Max Planck Society;

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Cox,  Jürgen
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Borner,  Georg H. H.
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Volltexte (frei zugänglich)

PIIS2211124717311889.pdf
(Verlagsversion), 4MB

Ergänzendes Material (frei zugänglich)

Itzhak_mmc1.pdf
(Ergänzendes Material), 3MB

Itzhak_mmc2.xlsx
(Ergänzendes Material), 19MB

Itzhak_mmc3.xlsx
(Ergänzendes Material), 8MB

Itzhak_mmc4.xlsx
(Ergänzendes Material), 2MB

Zitation

Itzhak, D. N., Davies, C., Tyanova, S., Mishra, A., Williamson, J., Antrobus, R., et al. (2017). A Mass Spectrometry-Based Approach for Mapping Protein Subcellular Localization Reveals the Spatial Proteome of Mouse Primary Neurons. Cell Reports, 20(11), 2706-2718. doi:10.1016/j.celrep.2017.08.063.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-002E-0950-9
Zusammenfassung
We previously developed a mass spectrometry-based method, dynamic organellar maps, for the determination of protein subcellular localization and identification of translocation events in comparative experiments. The use of metabolic labeling for quantification (stable isotope labeling by amino acids in cell culture [SILAC]) renders the method best suited to cells grown in culture. Here, we have adapted the workflow to both label-free quantification (LFQ) and chemical labeling/multiplexing strategies (tandem mass tagging [TMT]). Both methods are highly effective for the generation of organellar maps and capture of protein translocations. Furthermore, application of label-free organellar mapping to acutely isolated mouse primary neurons provided subcellular localization and copy-number information for over 8,000 proteins, allowing a detailed analysis of organellar organization. Our study extends the scope of dynamic organellar maps to any cell type or tissue and also to high-throughput screening.