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A0A0H3C8J1_CAUVN
Publication Abstract from PubMed
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 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, in particular 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.
A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0.,Zivanov J, Oton J, Ke Z, von Kugelgen A, Pyle E, Qu K, Morado D, Castano-Diez D, Zanetti G, Bharat TAM, Briggs JAG, Scheres SHW Elife. 2022 Dec 5;11:e83724. doi: 10.7554/eLife.83724. PMID:36468689[1]
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.
References
- ↑ Zivanov J, Oton J, Ke Z, von Kugelgen A, Pyle E, Qu K, Morado D, Castano-Diez D, Zanetti G, Bharat TAM, Briggs JAG, Scheres SHW. A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0. Elife. 2022 Dec 5;11:e83724. doi: 10.7554/eLife.83724. PMID:36468689 doi:http://dx.doi.org/10.7554/eLife.83724