How to extract significant information from clathrin SMLM data? Clathrin is a protein that plays a major role in the formation of coated vesicles, which play a key role in endocytosis.

The endocytic pathway can be hijacked by viruses and other pathogens in order to gain entry to the cell during infection. With Abbelight’s super-resolution nanoscopy solutions, clathrin light and heavy chains can be imaged at 20 nm resolution, almost resolving the triskellion, which is the base unit forming clathrin coated pits. Sophisticated analysis can also push this performance further.
In Single Molecule Localization Microscopy, data appears as a point cloud of localizations, each corresponding to the detection of a labeled site. The example of three-dimensional imaging of clathrin heavy chain is shown thereafter. Image is a 8×20 µm portion of a wider 100×100 µm² SMLM image.

Figure 1.a: 3D imaging of the heavy-chain of clathrin coated pits, where z position is color-encoded.

From this data, clustering algorithms can automatically extract individual structures and their associated relevant features.

The example of clathrin analysis is shown Figure 2. Clathrin cavities can take various sizes (Figure2.b), which can be distinguished thanks to clustering and made evident by color encoding each individual cluster (Figure2.a, Figure 1.b). [See 1] 

Specific analysis can then be performed to extract the most relevant parameters.

Here, by specifically extracting large cavities, the clathrin coated-pit structure can almost be resolved (Figure 2.c), a feature that is normally only accessible through electron microscopy. In other works, the precise geometry of clathrin coated pits at endocytic sites were also investigated through SMLM and statistical analysis [3].

Thus by combining SMLM with clustering, we can distinguish and analyze clathrin structures independently, a process which is also applicable to various samples, such as protein clusters, viruses, bacteria and cells. The relevance of these statistical data is strengthened by Abbelight’s ASTER uniform excitation scheme, which guarantees uniformity between data along the field of view.

Figure 1.b: Clustering of individual clathrin pits, where colors indicate various individual clusters.





Figure 2 : SMLM imaging and cluster analysis of COS-7 cells labeled for clathrin heavy-chain with AF647. (a) Final 140 µm × 140 µm image with scalebar 40 µm (top left) and close-up views of the highlighted regions. Colors encode cluster affiliation. Scalebars 1 µm. (b) Distribution of the diameter of clathrin clusters, highlighting four potential populations. Below are 250 nm × 250 nm images of individual clathrin related clusters, each group corresponding to a specific population. (c) specific images of large, hollow clathrin clusters likely corresponding to large clathrin-coated pits. Visible cavities are highlighted by arrows. See Mau et al. for further information.

References

1. Mau, A., Friedl, K., Leterrier, C. et al. Fast widefield scan provides tunable and uniform illumination optimizing super-resolution microscopy on large fields. Nat Commun 12, 3077 (2021). https://doi.org/10.1038/s41467-021-23405-4

2. Morris, K.L., Jones, J.R., Halebian, M. et al. Cryo-EM of multiple cage architectures reveals a universal mode of clathrin self-assembly. Nat Struct Mol Biol 26, 890–898 (2019). https://doi.org/10.1038/s41594-019-0292-0

3. Markus MundAline TschanzYu-Le WuFelix FreyJohanna L. MehlMarko KaksonenOri AvinoamUlrich S. SchwarzJonas Ries; Clathrin coats partially preassemble and subsequently bend during endocytosis. J Cell Biol 6 March 2023; 222 (3): e202206038. https://doi.org/10.1083/jcb.202206038