IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v7y2016i1d10.1038_ncomms9992.html
   My bibliography  Save this article

A draft map of the mouse pluripotent stem cell spatial proteome

Author

Listed:
  • Andy Christoforou

    (Cambridge Centre for Proteomics, University of Cambridge
    University of Cambridge)

  • Claire M. Mulvey

    (Cambridge Centre for Proteomics, University of Cambridge
    University of Cambridge)

  • Lisa M. Breckels

    (Cambridge Centre for Proteomics, University of Cambridge
    Computational Proteomics Unit, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK.)

  • Aikaterini Geladaki

    (Cambridge Centre for Proteomics, University of Cambridge
    University of Cambridge)

  • Tracey Hurrell

    (Cambridge Centre for Proteomics, University of Cambridge
    University of Pretoria)

  • Penelope C. Hayward

    (University of Cambridge)

  • Thomas Naake

    (Cambridge Centre for Proteomics, University of Cambridge
    Computational Proteomics Unit, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK.)

  • Laurent Gatto

    (Cambridge Centre for Proteomics, University of Cambridge
    Computational Proteomics Unit, University of Cambridge, Tennis Court Road, Cambridge CB2 1QR, UK.)

  • Rosa Viner

    (Thermo Fisher Scientific)

  • Alfonso Martinez Arias

    (University of Cambridge)

  • Kathryn S. Lilley

    (Cambridge Centre for Proteomics, University of Cambridge)

Abstract

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.

Suggested Citation

  • Andy Christoforou & Claire M. Mulvey & Lisa M. Breckels & Aikaterini Geladaki & Tracey Hurrell & Penelope C. Hayward & Thomas Naake & Laurent Gatto & Rosa Viner & Alfonso Martinez Arias & Kathryn S. L, 2016. "A draft map of the mouse pluripotent stem cell spatial proteome," Nature Communications, Nature, vol. 7(1), pages 1-12, April.
    • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms9992
    DOI: 10.1038/ncomms9992
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/ncomms9992
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/ncomms9992?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Oliver M Crook & Aikaterini Geladaki & Daniel J H Nightingale & Owen L Vennard & Kathryn S Lilley & Laurent Gatto & Paul D W Kirk, 2020. "A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection," PLOS Computational Biology, Public Library of Science, vol. 16(11), pages 1-21, November.
    2. Ying Zhu & Kerem Can Akkaya & Julia Ruta & Nanako Yokoyama & Cong Wang & Max Ruwolt & Diogo Borges Lima & Martin Lehmann & Fan Liu, 2024. "Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topologies," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    3. Oliver M. Crook & Colin T. R. Davies & Lisa M. Breckels & Josie A. Christopher & Laurent Gatto & Paul D. W. Kirk & Kathryn S. Lilley, 2022. "Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
    4. Oliver M Crook & Claire M Mulvey & Paul D W Kirk & Kathryn S Lilley & Laurent Gatto, 2018. "A Bayesian mixture modelling approach for spatial proteomics," PLOS Computational Biology, Public Library of Science, vol. 14(11), pages 1-29, November.
    5. Nicola M. Moloney & Konstantin Barylyuk & Eelco Tromer & Oliver M. Crook & Lisa M. Breckels & Kathryn S. Lilley & Ross F. Waller & Paula MacGregor, 2023. "Mapping diversity in African trypanosomes using high resolution spatial proteomics," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    6. Lisa M Breckels & Sean B Holden & David Wojnar & Claire M Mulvey & Andy Christoforou & Arnoud Groen & Matthew W B Trotter & Oliver Kohlbacher & Kathryn S Lilley & Laurent Gatto, 2016. "Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics," PLOS Computational Biology, Public Library of Science, vol. 12(5), pages 1-26, May.
    7. Ana Martinez-Val & Dorte B. Bekker-Jensen & Sophia Steigerwald & Claire Koenig & Ole Østergaard & Adi Mehta & Trung Tran & Krzysztof Sikorski & Estefanía Torres-Vega & Ewa Kwasniewicz & Sólveig Hlín B, 2021. "Spatial-proteomics reveals phospho-signaling dynamics at subcellular resolution," Nature Communications, Nature, vol. 12(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms9992. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.