Oral Presentation The 45th Lorne Conference on Protein Structure and Function 2020

chameleon: next generation sample preparation for cryo-EM (#35)

Paul Thaw 1 , John P Moore 1 , John Walker 1 , Klaus Doering 1 , Michele C Darrow 1 , Russell S King 1
  1. TTP Labtech, Melbourn, CAMBRIDGESHIRE, United Kingdom

In high-resolution structure determination for drug discovery, cryo-EM has witnessed dramatic improvements in microscope stability, direct detectors and image processing which have shifted the bottleneck to sample preparation. The process of obtaining a film of vitreous ice of an appropriate thickness, with evenly distributed particles is not straightforward. Many of the current vitrification methods are highly variable, necessitating the costly step of screening each grid in an electron microscope (EM). Additionally, relatively large sample volumes are required and then lost during the process of blotting, further grid losses are sustained during the manual handling steps required to transfer frozen grids into storage and there is poor traceability of samples throughout the workflow.

chameleon is a blot-free, pico-litre dispense instrument for rapid and robust freezing of samples for use in cryo-EM. The chameleon system was developed from Spotiton [1,2] and uses self-wicking copper nanowire grids to form the thin sample film [3]. This process occurs ‘on-the-fly’ as the grid passes in front of the dispenser on its way to the cryogen bowl, resulting in a stripe of sample across the frozen grid.

This method of grid freezing provides many benefits:

  • Blot-free high-speed plunging
  • Automated grid handling
  • Grid screening based on ice thickness
  • Intuitive automated workflows
  • Sample tracking and recording
  • Cryogen feedback and control
  • Potential impact on samples with air-water interface issues (preferred orientation, aggregation, denaturation)

In short, the chameleon is a sample vitrification system with walk-up usability that streamlines the flow of good grids to the microscope whilst capturing essential data to improve the repeatability of cryo-EM samples.

  1. [1] I Razinkov, et al. Journal of Structural Biology 195 (2016), p. 190-198
  2. [2] V Dandey, et al. Journal of Structural Biology 202 (2018), p. 161-169
  3. [3] H Wei, et al. Journal of Structural Biology 202 (2018), p. 170-174
  4. [4] A Noble, et al. Nature Methods 15 (2018), p. 793-795