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

Zivanov, J.; Oton, J.; Ke, Z.; Qu, K.; Morado, D.; Castano-Diez, D.; von Kügelgen, A.; Bharat, T.; Briggs, J.; Scheres, S.

doi:10.1101/2022.02.28.482229

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bioRxiv · 10.1101/2022.02.28.482229

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

Zivanov, J.·Oton, J.·Ke, Z.·Qu, K.·Morado, D.·Castano-Diez, D.·von Kügelgen, A.·Bharat, T.·Briggs, J.·Scheres, S.

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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 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.

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Zivanov, J., Oton, J., Ke, Z., Qu, K., Morado, D., Castano-Diez, D., von Kügelgen, A., Bharat, T., Briggs, J., Scheres, S.. 2022-02-28. A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0. https://doi.org/10.1101/2022.02.28.482229

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