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A draft map of the mouse pluripotent stem cell spatial proteome

Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/o...

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Autores principales: Christoforou, Andy, Mulvey, Claire M., Breckels, Lisa M., Geladaki, Aikaterini, Hurrell, Tracey, Hayward, Penelope C., Naake, Thomas, Gatto, Laurent, Viner, Rosa, Arias, Alfonso Martinez, Lilley, Kathryn S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4729960/
https://www.ncbi.nlm.nih.gov/pubmed/26754106
http://dx.doi.org/10.1038/ncomms9992
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author Christoforou, Andy
Mulvey, Claire M.
Breckels, Lisa M.
Geladaki, Aikaterini
Hurrell, Tracey
Hayward, Penelope C.
Naake, Thomas
Gatto, Laurent
Viner, Rosa
Arias, Alfonso Martinez
Lilley, Kathryn S.
author_facet Christoforou, Andy
Mulvey, Claire M.
Breckels, Lisa M.
Geladaki, Aikaterini
Hurrell, Tracey
Hayward, Penelope C.
Naake, Thomas
Gatto, Laurent
Viner, Rosa
Arias, Alfonso Martinez
Lilley, Kathryn S.
author_sort Christoforou, Andy
collection PubMed
description Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and post-translational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data.
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spelling pubmed-47299602016-03-04 A draft map of the mouse pluripotent stem cell spatial proteome Christoforou, Andy Mulvey, Claire M. Breckels, Lisa M. Geladaki, Aikaterini Hurrell, Tracey Hayward, Penelope C. Naake, Thomas Gatto, Laurent Viner, Rosa Arias, Alfonso Martinez Lilley, Kathryn S. Nat Commun Article Knowledge of the subcellular distribution of proteins is vital for understanding cellular mechanisms. Capturing the subcellular proteome in a single experiment has proven challenging, with studies focusing on specific compartments or assigning proteins to subcellular niches with low resolution and/or accuracy. Here we introduce hyperLOPIT, a method that couples extensive fractionation, quantitative high-resolution accurate mass spectrometry with multivariate data analysis. We apply hyperLOPIT to a pluripotent stem cell population whose subcellular proteome has not been extensively studied. We provide localization data on over 5,000 proteins with unprecedented spatial resolution to reveal the organization of organelles, sub-organellar compartments, protein complexes, functional networks and steady-state dynamics of proteins and unexpected subcellular locations. The method paves the way for characterizing the impact of post-transcriptional and post-translational modification on protein location and studies involving proteome-level locational changes on cellular perturbation. An interactive open-source resource is presented that enables exploration of these data. Nature Publishing Group 2016-01-12 /pmc/articles/PMC4729960/ /pubmed/26754106 http://dx.doi.org/10.1038/ncomms9992 Text en Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Christoforou, Andy
Mulvey, Claire M.
Breckels, Lisa M.
Geladaki, Aikaterini
Hurrell, Tracey
Hayward, Penelope C.
Naake, Thomas
Gatto, Laurent
Viner, Rosa
Arias, Alfonso Martinez
Lilley, Kathryn S.
A draft map of the mouse pluripotent stem cell spatial proteome
title A draft map of the mouse pluripotent stem cell spatial proteome
title_full A draft map of the mouse pluripotent stem cell spatial proteome
title_fullStr A draft map of the mouse pluripotent stem cell spatial proteome
title_full_unstemmed A draft map of the mouse pluripotent stem cell spatial proteome
title_short A draft map of the mouse pluripotent stem cell spatial proteome
title_sort draft map of the mouse pluripotent stem cell spatial proteome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4729960/
https://www.ncbi.nlm.nih.gov/pubmed/26754106
http://dx.doi.org/10.1038/ncomms9992
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