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, T.A.M., Briggs, J.A.G., Scheres, S.H.W.(2022) Elife 11
- PubMed: 36468689 
- DOI: https://doi.org/10.7554/eLife.83724
- Primary Citation of Related Structures:  
8BQE, 8BSH - PubMed Abstract: 
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.
Organizational Affiliation: 
MRC Laboratory of Molecular Biology, Cambridge, United Kingdom.