| Autor: |
Jasenko Zivanov, Joaquín Otón, Zunlong Ke, Andriko von Kügelgen, Euan Pyle, Kun Qu, Dustin Morado, Daniel Castaño-Díez, Giulia Zanetti, Tanmay AM Bharat, John AG Briggs, Sjors HW Scheres |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
eLife, Vol 11 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2050-084X |
| DOI: |
10.7554/eLife.83724 |
| Popis: |
We present a new approach for macromolecular structure determination from multiple particles in electron cryo-tomography (cryo-ET) data sets. Whereas existing subtomogram averaging approaches are based on 3D data models, we propose to optimise a regularised likelihood target that approximates a function of the 2D experimental images. In addition, analogous to Bayesian polishing and contrast transfer function (CTF) refinement in single-particle analysis, we describe the approaches that exploit the increased signal-to-noise ratio in the averaged structure to optimise tilt-series alignments, beam-induced motions of the particles throughout the tilt-series acquisition, defoci of the individual particles, as well as higher-order optical aberrations of the microscope. Implementation of our approaches in the open-source software package RELION aims to facilitate their general use, particularly for those researchers who are already familiar with its single-particle analysis tools. We illustrate for three applications that our approaches allow structure determination from cryo-ET data to resolutions sufficient for de novo atomic modelling. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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