IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v10y2019i1d10.1038_s41467-019-10007-4.html
   My bibliography  Save this article

A tessellation-based colocalization analysis approach for single-molecule localization microscopy

Author

Listed:
  • Florian Levet

    (University of Bordeaux
    Centre National de la Recherche Scientifique (CNRS) UMR 5297
    University of Bordeaux
    CNRS UMS 3420)

  • Guillaume Julien

    (University of Bordeaux
    Centre National de la Recherche Scientifique (CNRS) UMR 5297)

  • Rémi Galland

    (University of Bordeaux
    Centre National de la Recherche Scientifique (CNRS) UMR 5297)

  • Corey Butler

    (University of Bordeaux
    Centre National de la Recherche Scientifique (CNRS) UMR 5297)

  • Anne Beghin

    (University of Bordeaux
    Centre National de la Recherche Scientifique (CNRS) UMR 5297)

  • Anaël Chazeau

    (University of Bordeaux
    Centre National de la Recherche Scientifique (CNRS) UMR 5297)

  • Philipp Hoess

    (European Molecular Biology Laboratory (EMBL))

  • Jonas Ries

    (European Molecular Biology Laboratory (EMBL))

  • Grégory Giannone

    (University of Bordeaux
    Centre National de la Recherche Scientifique (CNRS) UMR 5297)

  • Jean-Baptiste Sibarita

    (University of Bordeaux
    Centre National de la Recherche Scientifique (CNRS) UMR 5297)

Abstract

Multicolor single-molecule localization microscopy (λSMLM) is a powerful technique to reveal the relative nanoscale organization and potential colocalization between different molecular species. While several standard analysis methods exist for pixel-based images, λSMLM still lacks such a standard. Moreover, existing methods only work on 2D data and are usually sensitive to the relative molecular organization, a very important parameter to consider in quantitative SMLM. Here, we present an efficient, parameter-free colocalization analysis method for 2D and 3D λSMLM using tessellation analysis. We demonstrate that our method allows for the efficient computation of several popular colocalization estimators directly from molecular coordinates and illustrate its capability to analyze multicolor SMLM data in a robust and efficient manner.

Suggested Citation

  • Florian Levet & Guillaume Julien & Rémi Galland & Corey Butler & Anne Beghin & Anaël Chazeau & Philipp Hoess & Jonas Ries & Grégory Giannone & Jean-Baptiste Sibarita, 2019. "A tessellation-based colocalization analysis approach for single-molecule localization microscopy," Nature Communications, Nature, vol. 10(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-10007-4
    DOI: 10.1038/s41467-019-10007-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-019-10007-4
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-019-10007-4?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. Aske L. Ejdrup & Matthew D. Lycas & Niels Lorenzen & Ainoa Konomi & Freja Herborg & Kenneth L. Madsen & Ulrik Gether, 2022. "A density-based enrichment measure for assessing colocalization in single-molecule localization microscopy data," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    2. Jonathan D. Worboys & Katherine N. Vowell & Roseanna K. Hare & Ashley R. Ambrose & Margherita Bertuzzi & Michael A. Conner & Florence P. Patel & William H. Zammit & Judit Gali-Moya & Khodor S. Hazime , 2023. "TIGIT can inhibit T cell activation via ligation-induced nanoclusters, independent of CD226 co-stimulation," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    3. Nario Tomishige & Maaz Nasim & Motohide Murate & Brigitte Pollet & Pascal Didier & Julien Godet & Ludovic Richert & Yasushi Sako & Yves Mély & Toshihide Kobayashi, 2023. "HIV-1 Gag targeting to the plasma membrane reorganizes sphingomyelin-rich and cholesterol-rich lipid domains," Nature Communications, Nature, vol. 14(1), pages 1-18, 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:10:y:2019:i:1:d:10.1038_s41467-019-10007-4. 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.