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

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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
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    Cited by:

    1. 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.
    2. 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.
    3. 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.

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