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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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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. |
format | Online Article Text |
id | pubmed-4729960 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
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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