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  Global, quantitative and dynamic mapping of protein subcellular localization

Itzhak, D. N., Tyanova, S., Cox, J., & Borner, G. H. H. (2016). Global, quantitative and dynamic mapping of protein subcellular localization. eLife, 5: e16950. doi:10.7554/eLife.16950.

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 Creators:
Itzhak, Daniel N.1, Author           
Tyanova, Stefka1, 2, Author           
Cox, Jürgen1, 2, Author           
Borner, Georg H. H.1, Author           
Affiliations:
1Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565159              
2Cox, Jürgen / Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Max Planck Society, ou_2063284              

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 Abstract: Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

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Language(s): eng - English
 Dates: 2016-06-09
 Publication Status: Published online
 Pages: 36
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.7554/eLife.16950
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Title: eLife
Source Genre: Journal
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Publ. Info: Cambridge : eLife Sciences Publications
Pages: - Volume / Issue: 5 Sequence Number: e16950 Start / End Page: - Identifier: ISSN: 2050-084X
CoNE: https://pure.mpg.de/cone/journals/resource/2050-084X