Image optimisation for expansion microscopy gels

15:40 – 16:40 BST, 5 June 2024 ‐ 1 hour

Leica Microsystems

Emmanuelle Steib1, Lothar Schermelleh2

1Leica Microsystems, United Kingdom. 2Micron Facility, Department of Biochemistry, University of Oxford, United Kingdom

Workshop Room 11C

Super resolution (SR) microscopy has been a powerful tool to bridge the gaps between fluorescence and electron microscopy. However, SR microscopy requires specific optics and expertise that can be limiting in day-to-day applications for most biology laboratories. To bypass this issue, researchers have developed an approach based on sample optimisation. The idea behind expansion microscopy (ExM) is to physically increase the sample size to obtain SR-like images using conventional widefield or confocal microscopes. It involves embedding a fixed biological sample in a swellable polymer compatible with immunolabeling and light microscopy.

Still, the implementation of ExM has many challenges, some of which we will address in this workshop through hands-on demonstrations and sharing of tips and tricks with experts. The session will be led by Dr Emmanuelle Steib from Leica Microsystems, who has experience with expanding and imaging a wide variety of samples, ranging from isolated organelles to whole vertebrate embryos. Emmanuelle will be joined by super resolution expert Associate Professor Lothar Schermelleh from the Department of Biochemistry at The University of Oxford and head of the new Collaborative Centre of Excellence for Cutting-Edge Microscopy.

In this workshop, we will focus on optimising imaging modalities to accommodate the limits of ExM gels. We will discuss how to address the physical properties of gels, as well as fluorescence dilution compared to conventional immunofluorescence. We will use the versatility of the STELLARIS confocal platform to present a typical workflow to image samples across multiple scales. Making use of the Leica Navigator tool, we will also highlight how easy and fast it is to register large areas, then retrieve regions of interest for subcellular investigation. 

References

  1. Chen et al., Science, 2015 https://www.science.org/doi/10.1126/science.1260088
  2. Wassie et al., Nat Methods, 2019 https://www.nature.com/articles/s41592-018-0219-4
  3. Steib et al., Cell Rep Methods 2022 https://www.sciencedirect.com/science/article/pii/S2667237522001990