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Dense, continuous membrane labeling and expansion microscopy visualization of ultrastructure in tissues

Author

Listed:
  • Tay Won Shin

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Hao Wang

    (Massachusetts Institute of Technology
    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
    Massachusetts Institute of Technology)

  • Panagiotis Symvoulidis

    (Massachusetts Institute of Technology)

  • Shoh Asano

    (Massachusetts Institute of Technology
    Pfizer Inc)

  • Leanne Lin

    (Massachusetts Institute of Technology)

  • Emma K. Costa

    (Massachusetts Institute of Technology
    Stanford University)

  • Adam H. Marblestone

    (Massachusetts Institute of Technology
    Convergent Research)

  • Narayanan Kasthuri

    (Argonne National Laboratory
    University of Chicago)

  • Li-Huei Tsai

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

  • Edward S. Boyden

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

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.

Suggested Citation

  • 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 & Lean, 2025. "Dense, continuous membrane labeling and expansion microscopy visualization of ultrastructure in tissues," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
  • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-56641-z
    DOI: 10.1038/s41467-025-56641-z
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    References listed on IDEAS

    as
    1. Yunfeng Hua & Philip Laserstein & Moritz Helmstaedter, 2015. "Large-volume en-bloc staining for electron microscopy-based connectomics," Nature Communications, Nature, vol. 6(1), pages 1-7, November.
    2. Fred Y. Shen & Margaret M. Harrington & Logan A. Walker & Hon Pong Jimmy Cheng & Edward S. Boyden & Dawen Cai, 2020. "Light microscopy based approach for mapping connectivity with molecular specificity," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
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