Dense, Continuous Membrane Labeling and Expansion Microscopy Visualization of Ultrastructure in Tissues

Tay Won Shin, Hao Wang*, Chi Zhang*, Bobae An, Yangning Lu, Elizabeth Zhang, Xiaotang Lu, Emmanouil D Karagiannis, Jeong Seuk Kang, Amauche Emenari, Panagiotis Symvoulidis, Shoh Asano, Leanne Lin, Emma K Costa; IMAXT Grand Challenge Consortium; Adam H Marblestone, Narayanan Kasthuri, Li-Huei Tsai, Edward S Boyden (2024) Dense, Continuous Membrane Labeling and Expansion Microscopy Visualization of Ultrastructure in Tissues, bioRxiv 2024.03.07.583776; doi: https://doi.org/10.1101/2024.03.07.583776 (*, equal contribution)

See PDF Publisher Link

Lipid membranes are key to the nanoscale compartmentalization of biological systems, but fluorescent visualization of them in intact tissues, with nanoscale precision, is challenging to do with high labeling density. Here, we report ultrastructural membrane expansion microscopy (umExM), which combines a novel membrane label and optimized expansion microscopy protocol, to support dense labeling of membranes in tissues for nanoscale visualization. We validated the high signal-to-background ratio, and uniformity and continuity, of umExM membrane labeling in brain slices, which supported the imaging of membranes and proteins at a resolution of ~60 nm on a confocal microscope. We demonstrated the utility of umExM for the segmentation and tracing of neuronal processes, such as axons, in mouse brain tissue. Combining umExM with optical fluctuation imaging, or iterating the expansion process, yielded ~35 nm resolution imaging, pointing towards the potential for electron microscopy resolution visualization of brain membranes on ordinary light microscopes.

Project

Tools for mapping the molecular architecture and wiring of the brain

View Project