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, Adam H. Marblestone, Narayanan Kasthuri, Li-Huei Tsai and Edward S. Boyden ()
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Tay Won Shin: Massachusetts Institute of Technology
Hao Wang: Massachusetts Institute of Technology
Chi Zhang: Massachusetts Institute of Technology
Bobae An: Massachusetts Institute of Technology
Yangning Lu: Massachusetts Institute of Technology
Elizabeth Zhang: Massachusetts Institute of Technology
Xiaotang Lu: Harvard University
Emmanouil D. Karagiannis: Massachusetts Institute of Technology
Jeong Seuk Kang: Massachusetts Institute of Technology
Amauche Emenari: Massachusetts Institute of Technology
Panagiotis Symvoulidis: Massachusetts Institute of Technology
Shoh Asano: Massachusetts Institute of Technology
Leanne Lin: Massachusetts Institute of Technology
Emma K. Costa: Massachusetts Institute of Technology
Adam H. Marblestone: Massachusetts Institute of Technology
Narayanan Kasthuri: Argonne National Laboratory
Li-Huei Tsai: Massachusetts Institute of Technology
Edward S. Boyden: Massachusetts Institute of Technology

Nature Communications, 2025, vol. 16, issue 1, 1-17

Abstract: Abstract 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 an innovative membrane label and optimized expansion microscopy protocol, to support dense labeling of membranes in tissues for nanoscale visualization. We validate the high signal-to-background ratio, and uniformity and continuity, of umExM membrane labeling in brain slices, which supports the imaging of membranes and proteins at a resolution of ~60 nm on a confocal microscope. We demonstrate 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, yields ~35 nm resolution imaging, pointing towards the potential for electron microscopy resolution visualization of brain membranes on ordinary light microscopes.

Date: 2025
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DOI: 10.1038/s41467-025-56641-z

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