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

Florian Levet (1, 2) , Guillaume Julien (1) , Rémi Galland (1) , Corey Butler (1) , Anne Beghin (1) , Anaël Chazeau (1) , Philipp Hoess (3) , Jonas Ries (3) , Gregory Giannone (1) , Jean-Baptiste Sibarita (1)

1 IINS - Interdisciplinary Institute for Neuroscience [Bordeaux]
2 BIC - Bordeaux Imaging Center
3 EMBL - EMBL Cell Biology and Biophysics Unit

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.

Domaines: Bio-informatique [q-bio.QM]; Biologie cellulaire; Biotechnologies

Florian Levet, Guillaume Julien, Rémi Galland, Corey Butler, Anne Beghin, et al.. A tessellation-based colocalization analysis approach for single-molecule localization microscopy. Nature Communications, 2019, 10 (1), pp.2379. ⟨10.1038/s41467-019-10007-4⟩. ⟨hal-02361983⟩