2021Weis Strategies

From 3DEM-Methods
Revision as of 14:26, 15 April 2021 by WikiSysop (talk | contribs) (Created page with "== Citation == Weis, F.; Hagen, W. J.; Schorb, M. & Mattei, S. Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition. Journal of Visualized Experiment...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Citation

Weis, F.; Hagen, W. J.; Schorb, M. & Mattei, S. Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition. Journal of Visualized Experiments: Jove, 2021, e62383

Abstract

Cryogenic electron tomography (cryoET) is a powerful method to study the 3Dstructure of biological samples in a close-to-native state. Current state-of-the-artcryoET combined with subtomogram averaging analysis enables the high-resolutionstructural determination of macromolecular complexes that are present in multiplecopies within tomographic reconstructions. Tomographic experiments usually requirea vast amount of tilt series to be acquired by means of high-end transmission electronmicroscopes with important operational running-costs. Although the throughput andreliability of automated data acquisition routines have constantly improved over therecent years, the process of selecting regions of interest at which a tilt series willbe acquired cannot be easily automated and it still relies on the user's manualinput. Therefore, the set-up of a large-scale data collection session is a timeconsumingprocedure that can considerably reduce the remaining microscope timeavailable for tilt series acquisition. Here, the protocol describes the recently developedimplementations based on the SerialEM package and the PyEM software thatsignificantly improve the time-efficiency of grid screening and large-scale tilt seriesdata collection. The presented protocol illustrates how to use SerialEM scriptingfunctionalities to fully automate grid mapping, grid square mapping, and tilt seriesacquisition. Furthermore, the protocol describes how to use PyEM to select additionalacquisition targets in off-line mode after automated data collection is initiated. Toillustrate this protocol, its application in the context of high-end data collection ofSars-Cov-2 tilt series is described. The presented pipeline is particularly suited tomaximizing the time-efficiency of tomography experiments that require a carefulselection of acquisition targets and at the same time a large amount of tilt series tobe collected.

Keywords

Links

https://www.jove.com/t/62383/strategies-for-optimization-cryogenic-electron-tomography-data

Related software

Related methods

Comments