Journal Article

A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0

Bharat, Tanmay AM, Otón, Joaquín, von Kügelgen, Andriko, Briggs, John AG, Zivanov, Jasenko, Qu, Kun, Morado, Dustin, Ke, Zunlong, Pyle, Euan, Zanetti, Giulia, Castaño-Díez, Daniel, Scheres, Sjors HW

2022

Overview

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.

• Publisher: eLife Sciences Publications Ltd,eLife Sciences Publications, Ltd
• Subject: Algorithms / Bayes Theorem / Bayesian analysis / Cryoelectron Microscopy - methods / Electron Microscope Tomography - methods / electron tomography / Electrons / Fourier transforms / Image Processing, Computer-Assisted - methods / Macromolecules / Mathematical models / maximum likelihood / Structural Biology and Molecular Biophysics / subtomogram averaging / Tomography / Tools and Resources