Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics

Thibault Lagache (1) , Alexandre Grassart (2) , Stéphane Dallongeville (1) , Orestis Faklaris (3) , Nathalie Sauvonnet (2) , Alexandre Dufour (1) , Lydia Danglot (4) , Jean-Christophe Olivo-Marin (1)

1 BIA - Analyse d'images biologiques - Biological Image Analysis
2 Pathogénie microbienne moléculaire
3 IJM (UMR_7592) - Institut Jacques Monod
4 U894 - Centre de Psychiatrie et Neurosciences

Elucidating protein functions and molecular organisation requires to localise precisely single or aggregated molecules and analyse their spatial distributions. We develop a statistical method SODA (Statistical Object Distance Analysis) that uses either micro- or nanoscopy to significantly improve on standard co-localisation techniques. Our method considers cellular geometry and densities of molecules to provide statistical maps of isolated and associated (coupled) molecules. We use SODA with three-colour structured-illumination microscopy (SIM) images of hippocampal neurons, and statistically characterise spatial organisation of thousands of synapses. We show that presynaptic synapsin is arranged in asymmetric triangle with the 2 postsynaptic markers homer and PSD95, indicating a deeper localisation of homer. We then determine stoichiometry and distance between localisations of two synaptic vesicle proteins with 3D-STORM. These findings give insights into the protein organisation at the synapse, and prove the efficiency of SODA to quantitatively assess the geometry of molecular assemblies.

Domaines: Biologie cellulaire; Traitement des images [eess.IV]

Thibault Lagache, Alexandre Grassart, Stéphane Dallongeville, Orestis Faklaris, Nathalie Sauvonnet, et al.. Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics. Nature Communications, 2018, 9 (1), pp.698. ⟨10.1038/s41467-018-03053-x⟩. ⟨pasteur-02168087⟩