A092 - Single Molecule Localization Microscopy and use of calibration tools to unravel EVs composition and 3D morphology at a single-vesicle level

Daniele D\'arrigo (daniele.darrigo@u-paris.fr)

Single Molecule Localization Microscopy (SMLM) allows to overcome the light’s diffraction limit, offering typically a localization precision lower than 20 nm. This is particularly important for the imaging and the characterization of extracellular vesicles (EVs). These lipid nanovesicles play a crucial role in cell communication process and they have a typical size below 200 nm. Thanks to the use of large unilamellar vesicles (LUVs), synthetic nanometric vesicles with comparable size that mimic natural EVs, we optimized the 3D and dual-color imaging of the EVs. Currently, different techniques are used to characterize their size and concentration (light scattering, tunable resistive pulse sensing and electron microscopy), morphology (electron microscopy and atomic force microscopy) and surface markers (western blot, confocal and fluorescent microscopy, ELISA and flow cytometry). However, SMLM could own the potential to provide all these information, allowing to reduce the variability connected with the use of several analytical techniques. During this workshop, we show an SMLM approach to image and characterize both LUVs and EVs, including the size, the 3D morphology, and the surface markers. Our experimental set-up includes dedicated capture surfaces that enables both a targeted (tetraspanins) and an untargeted capture of LUVs and EVs isolated from human mesenchymal stem cells, their 3D and dual-color imaging (using the spectral demixing approach) with a super-resolution microscope and an optimized proprietary software to extract quantitative data. In particular, we will present the theoretical basis and the sample preparation approaches for the imaging of EVs with SMLM, then we will perform a practical demonstration about the optimization and the imaging process and, lastly, the analysis of the obtained data. After this demonstration, the participants will actively participate in the acquisition of super-resolved EV images and in the subsequent data analysis.