Abstract text (incl. figure legends and references)
Cryo-electron tomography (cryo-ET) is a powerful technique that allows researchers to obtain 3D structures at nano-meter resolution in their near-native state. In recent years the technique has gained popularity and a large number of complexes have been resolved. This has improved our understanding of the molecular foundation of viral infections1, skeletal muscles2 and Parkinson"s disease3.
To obtain such a high resolution 3D structure, 1000-2000 copies of a protein complex need to be averaged in a process called subtomogram averaging4,5. This means that a high number of high quality tomograms are needed. Unfortunately the workflow is very error-prone and this has limited the data output6. To acquire high quality tomograms there are two main challenges: keeping the sample ice contamination-free and targeting the region of interest (ROI).
At Delmic we developed two workflow solutions called CERES and METEOR to improve the entire cryo-ET sample preparation workflow. The CERES Ice Defence System is based on the tools developed by Tacke et al7 and consists of multiple innovative tools that are tailored to minimize ice contamination during sample handling (CERES Clean Station), transfer (CERES Vitri-Lock) and FIB milling (CERES Ice Shield). METEOR is an integrated fluorescence light microscope (FLM) that greatly enhances the ROI targeting inside the cryo-FIB/SEM while reducing the number of handling steps required.
We show that these innovative tools can lead to improved cryo-ET data quality and throughput.
Klein, S. et al. SARS-CoV-2 structure and replication characterized by in situ cryo-electron tomography. Nature Communications 2020 11:1 11, 1–10 (2020). Wang, Z. et al. The molecular basis for sarcomere organization in vertebrate skeletal muscle. Cell 184, 2135-2150.e13 (2021). Watanabe, R. et al. The In Situ Structure of Parkinson"s Disease-Linked LRRK2. Cell 182, 1508-1518.e16 (2020). Chen, M. et al. A complete data processing workflow for cryo-ET and subtomogram averaging. Nature Methods 2019 16:11 16, 1161–1168 (2019). Scaramuzza, S. & Castaño-Díez, D. Step-by-step guide to efficient subtomogram averaging of virus-like particles with Dynamo. PLoS Biol 19, e3001318 (2021). Lau, K., Jonker, C., Liu, J. & Smeets, M. The Undesirable Effects and Impacts of Ice Contamination Experienced in the Cryo-Electron Tomography Workflow and Available Solutions. Micros Today 30, 30–35 (2022). Tacke, S. et al. A streamlined workflow for automated cryo focused ion beam milling. J Struct Biol 213, 107743 (2021).