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dc.contributor.authorItzhak, DNen
dc.contributor.authorDavies, Colinen
dc.contributor.authorTyanova, Sen
dc.contributor.authorMishra, Aen
dc.contributor.authorWilliamson, Jamesen
dc.contributor.authorAtrobus, Ren
dc.contributor.authorCox, Jen
dc.contributor.authorWeekes, Michaelen
dc.contributor.authorBomer, GHHen
dc.date.accessioned2017-10-09T12:12:36Z
dc.date.available2017-10-09T12:12:36Z
dc.date.issued2017-09-12en
dc.identifier.issn2211-1247
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/267799
dc.description.abstractWe previously developed a mass spectrometry-based method, Dynamic Organellar Maps, for the determination of protein subcellular localisation, and the identification of translocation events in comparative experiments. The use of metabolic labelling for quantification (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 labelling/multiplexing strategies (Tandem Mass Tagging, TMT). Both new methods are highly effective for generation of organellar maps and capture of protein translocations. Furthermore, application of label-free organellar mapping to acutely isolated mouse primary neurons provided subcellular localisation and copy number information for over 8,000 proteins, allowing a detailed analysis of organellar organisation. Our study extends the scope of Dynamic Organellar Maps to any cell type or tissue, and also to high throughput screening.
dc.description.sponsorshipThis work was funded by the German Research Foundation (DFG/Gottfried Wilhelm Leibniz Prize MA 1764/2-1), the Louis-Jeantet Foundation, the Max Planck Society for the Advancement of Science, a Wellcome Trust Senior Clinical Research Fellowship 108070/Z/15/Z (to M.P.W.), and a strategic award to Cambridge Institute for Medical Research from the Wellcome Trust (100140).
dc.language.isoenen
dc.publisherElsevier
dc.rightsAttribution 4.0 International*
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleA Mass Spectrometry-Based Approach for Mapping Protein Subcellular Localization Reveals the Spatial Proteome of Mouse Primary Neuronsen
dc.typeArticle
prism.endingPage2718
prism.issueIdentifier11en
prism.publicationDate2017en
prism.publicationNameCell Reportsen
prism.startingPage2706
prism.volume20en
dc.identifier.doi10.17863/CAM.13728
dcterms.dateAccepted2017-08-18en
rioxxterms.versionofrecord10.1016/j.celrep.2017.08.063en
rioxxterms.versionVoRen
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/en
rioxxterms.licenseref.startdate2017-09-12en
dc.contributor.orcidWilliamson, James [0000-0002-2009-189X]
dc.contributor.orcidWeekes, Michael [0000-0003-3196-5545]
dc.identifier.eissn2211-1247
rioxxterms.typeJournal Article/Reviewen
pubs.funder-project-idWellcome Trust (100140/Z/12/Z)
pubs.funder-project-idWELLCOME TRUST (108070/Z/15/Z)
cam.issuedOnline2017-09-12en
cam.orpheus.successThu Jan 30 12:58:59 GMT 2020 - The item has an open VoR version.*
rioxxterms.freetoread.startdate2100-01-01


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International