A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0
- MRC Laboratory of Molecular Biology, United Kingdom
- ALBA Synchrotron, Spain
- Birkbeck, University of London, United Kingdom
- University of Basel, Switzerland
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.
Data availability
We have only used previously published cryo-EM data sets for testing our software.Reconstructed maps and atomic models generated in this study have been submitted to the EMDB and PDB, with entry codes as indicated in Table 1.
Article and author information
Author details
Andriko von Kügelgen
Funding
UK Research and Innovation (MC_UP_A025_1013)
- Sjors HW Scheres
UK Research and Innovation (MC_UP_1201/16)
- John AG Briggs
European Research Council (ERC-CoG-2014 grant 648432)
- John AG Briggs
European Research Council (ERC-StG-2019 grant 852915)
- Giulia Zanetti
Swiss National Science Foundation (205321_179041/1)
- Daniel Castaño-Díez
UK Research and Innovation (BBSRC grant BB/T002670/1)
- Giulia Zanetti
European Research Council (ERC-AdG-2015 grant 692726)
- Jasenkio Zivanov
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Zivanov et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 4,530
- views
-
- 685
- downloads
-
- 209
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
A Bayesian approach to single-particle electron cryo-tomography in RELION-4.0
eLife 11:e83724.
https://doi.org/10.7554/eLife.83724
Further reading
-
- Biochemistry and Chemical Biology
- Structural Biology and Molecular Biophysics
African trypanosomes are the causative agents of neglected tropical diseases affecting both humans and livestock. Disease control is highly challenging due to an increasing number of drug treatment failures. African trypanosomes are extracellular, blood-borne parasites that mainly rely on glycolysis for their energy metabolism within the mammalian host. Trypanosomal glycolytic enzymes are therefore of interest for the development of trypanocidal drugs. Here, we report the serendipitous discovery of a camelid single-domain antibody (sdAb aka Nanobody) that selectively inhibits the enzymatic activity of trypanosomatid (but not host) pyruvate kinases through an allosteric mechanism. By combining enzyme kinetics, biophysics, structural biology, and transgenic parasite survival assays, we provide a proof-of-principle that the sdAb-mediated enzyme inhibition negatively impacts parasite fitness and growth.
-
- Structural Biology and Molecular Biophysics
The relationship between protein dynamics and function is essential for understanding biological processes and developing effective therapeutics. Functional sites within proteins are critical for activities such as substrate binding, catalysis, and structural changes. Existing computational methods for the predictions of functional residues are trained on sequence, structural, and experimental data, but they do not explicitly model the influence of evolution on protein dynamics. This overlooked contribution is essential as it is known that evolution can fine-tune protein dynamics through compensatory mutations either to improve the proteins’ performance or diversify its function while maintaining the same structural scaffold. To model this critical contribution, we introduce DyNoPy, a computational method that combines residue coevolution analysis with molecular dynamics simulations, revealing hidden correlations between functional sites. DyNoPy constructs a graph model of residue–residue interactions, identifies communities of key residue groups, and annotates critical sites based on their roles. By leveraging the concept of coevolved dynamical couplings—residue pairs with critical dynamical interactions that have been preserved during evolution—DyNoPy offers a powerful method for predicting and analysing protein evolution and dynamics. We demonstrate the effectiveness of DyNoPy on SHV-1 and PDC-3, chromosomally encoded β-lactamases linked to antibiotic resistance, highlighting its potential to inform drug design and address pressing healthcare challenges.
