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Step-by-step guide to efficient subtomogram averaging of virus-like particles with Dynamo.
- Source :
-
PLoS Biology . 8/26/2021, Vol. 19 Issue 8, p1-22. 22p. 3 Color Photographs, 2 Diagrams, 3 Charts, 3 Graphs. - Publication Year :
- 2021
-
Abstract
- Subtomogram averaging (STA) is a powerful image processing technique in electron tomography used to determine the 3D structure of macromolecular complexes in their native environments. It is a fast growing technique with increasing importance in structural biology. The computational aspect of STA is very complex and depends on a large number of variables. We noticed a lack of detailed guides for STA processing. Also, current publications in this field often lack a documentation that is practical enough to reproduce the results with reasonable effort, which is necessary for the scientific community to grow. We therefore provide a complete, detailed, and fully reproducible processing protocol that covers all aspects of particle picking and particle alignment in STA. The command line–based workflow is fully based on the popular Dynamo software for STA. Within this workflow, we also demonstrate how large parts of the processing pipeline can be streamlined and automatized for increased throughput. This protocol is aimed at users on all levels. It can be used for training purposes, or it can serve as basis to design user-specific projects by taking advantage of the flexibility of Dynamo by modifying and expanding the given pipeline. The protocol is successfully validated using the Electron Microscopy Public Image Archive (EMPIAR) database entry 10164 from immature HIV-1 virus-like particles (VLPs) that describe a geometry often seen in electron tomography. This study presents a complete and detailed step-by-step guide for subtomogram averaging using Dynamo software, with a special focus on particle picking and particle averaging; this will enable efficient processing for all experience levels, and lays a foundation for user-specific projects. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15449173
- Volume :
- 19
- Issue :
- 8
- Database :
- Academic Search Index
- Journal :
- PLoS Biology
- Publication Type :
- Academic Journal
- Accession number :
- 152093525
- Full Text :
- https://doi.org/10.1371/journal.pbio.3001318