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Related Experiment Video

Updated: Oct 29, 2025

Label-Retention Expansion Microscopy LR-ExM Enables Super-Resolution Imaging and High-Efficiency Labeling

Label-Retention Expansion Microscopy LR-ExM Enables Super-Resolution Imaging and High-Efficiency Labeling

Published on: October 11, 2022

Label-retention expansion microscopy.

Xiaoyu Shi^1,2, Qi Li^1,3, Zhipeng Dai⁴

¹Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA.

The Journal of Cell Biology

|July 6, 2021

Summary

This summary is machine-generated.

Label-retention expansion microscopy (LR-ExM) prevents fluorescence signal loss, enabling high-efficiency labeling. This technique achieves molecular resolution for visualizing subcellular structures, like clathrin-coated pits.

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Label-Retention Expansion Microscopy LR-ExM Enables Super-Resolution Imaging and High-Efficiency Labeling

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Area of Science:

Biophysics
Cell Biology
Microscopy

Background:

Expansion microscopy (ExM) enhances microscope resolution by hydrogel expansion.
ExM is widely used in cell, tissue, and animal studies.
Fluorescence signal loss during ExM limits molecular-scale imaging.

Purpose of the Study:

To develop a novel ExM technique that prevents fluorescence signal loss.
To enable high-efficiency labeling for improved molecular imaging.
To achieve molecular resolution in visualizing subcellular structures.

Main Methods:

Development of label-retention ExM (LR-ExM) using trifunctional anchors.
High-efficiency labeling with SNAP and CLIP tags.
Demonstration of multicolor LR-ExM on various subcellular structures.
Integration of LR-ExM with superresolution stochastic optical reconstruction microscopy (STORM).

Main Results:

LR-ExM effectively prevents fluorescence signal loss during polymerization and digestion.
High-efficiency labeling was achieved using SNAP and CLIP tags.
Multicolor LR-ExM successfully visualized diverse subcellular structures.
Combined LR-ExM and STORM achieved molecular resolution of clathrin-coated pits.

Conclusions:

LR-ExM overcomes the limitations of traditional ExM by retaining fluorescence signals.
This method significantly enhances labeling efficiency for detailed subcellular imaging.
LR-ExM coupled with STORM provides unprecedented molecular-level visualization capabilities.