Expansion Microscopy

By Fei Chen, Paul W. Tillberg, Ed Boyden. Science, 2015

1,039 citations recorded by the source corpus.

Overcoming the limits of the microscope The resolution of a light microscope is limited. Physicists have long since worked out what these limits are and which parameters determine the spatial resolution. Many groups have nevertheless made numerous attempts to overcome these resolution limits. Rather than improving the power and quality of the microscope, Chen et al. instead expanded the biological specimens under study (see the Perspective by Dodt). They introduced a polymer gel into fixed cells and tissues and chemically induced swelling of the polymer by almost two orders of magnitude. They could then produce much higher-resolution images of their samples, which included the mouse hippocampus. Science, this issue p. 543; see also p. 474 A new approach to image fixed biological samples by expanding the specimen under study reveals mouse brain substructures. [Also see Perspective by Dodt] In optical microscopy, fine structural details are resolved by using refraction to magnify images of a specimen. We discovered that by synthesizing a swellable polymer network within a specimen, it can be physically expanded, resulting in physical magnification. By covalently anchoring specific labels located within the specimen directly to the polymer network, labels spaced closer than the optical diffraction limit can be isotropically separated and optically resolved, a process we call expansion microscopy (ExM). Thus, this process can be used to perform scalable superresolution microscopy with diffraction-limited microscopes. We demonstrate ExM with apparent ~70-nanometer lateral resolution in both cultured cells and brain tissue, performing three-color superresolution imaging of ~107 cubic micrometers of the mouse hippocampus with a conventional confocal microscope.

Subfields: Biophysics, Structural Biology

View Paper: https://www.semanticscholar.org/paper/e3a04565f01c8e18d4a1fbf7cdbe18bf5323442a

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Citations in the corpus

In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus (2016, positive): “Although merFISH can tolerate 2 errors in the barcodes, it requires 16 rounds of hybridization to code 140 genes (Chen et al. 2015).”
Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images (2018, methodology): “Increasing the resolution of images, either during acquisition (51) or with computational methods such as resizing images to make objects look bigger, may help fix these errors.”
The Human Cell Atlas (2017, methodology): “Some strategies for RNA detection, such as MERFISH (Chen et al., 2015c; Moffitt et al., 2016b) or Seq-FISH (Shah et al., 2016), combine multiplex hybridization with microscopy-based quantification to assess distributions at both the cellular and subcellular level; other early studies have performed ”
Museum of spatial transcriptomics (2020, methodology): “This can be mitigated by expansion microscopy (ExM) [84], only imaging a subset of probes at a time and using computational super-resolution [75], imaging highly expressed genes without combinatorial barcoding [52], and computationally resolving over-lapping spots [85].”