An image processing pipeline for electron cryo-tomography in RELION-5.

Electron tomography of frozen, hydrated samples allows structure determination of macromolecular complexes that are embedded in complex environments. Provided that the target complexes may be localised in noisy, three-dimensional tomographic reconstructions, averaging images of multiple instances of these molecules can lead to structures with sufficient resolution for de novo atomic modelling. Although many research groups have contributed image processing tools for these tasks, a lack of standardisation and interoperability represents a barrier for newcomers to the field.

DynaMight: estimating molecular motions with improved reconstruction from cryo-EM images.

How to deal with continuously flexing molecules is one of the biggest outstanding challenges in single-particle analysis of proteins from cryogenic-electron microscopy (cryo-EM) images. Here, we present DynaMight, a software tool that estimates a continuous space of conformations in a cryo-EM dataset by learning three-dimensional deformations of a Gaussian pseudo-atomic model of a consensus structure for every particle image. Inversion of the learned deformations is then used to obtain an improved reconstruction of the consensus structure.

Phage anti-CRISPR control by an RNA- and DNA-binding helix-turn-helix protein.

In all organisms, regulation of gene expression must be adjusted to meet cellular requirements and frequently involves helix-turn-helix (HTH) domain proteins. For instance, in the arms race between bacteria and bacteriophages, rapid expression of phage anti-CRISPR (acr) genes upon infection enables evasion from CRISPR-Cas defence; transcription is then repressed by an HTH-domain-containing anti-CRISPR-associated (Aca) protein, probably to reduce fitness costs from excessive expression. However, how a single HTH regulator adjusts anti-CRISPR production to cope with increasing phage genome copies and accumulating acr mRNA is unknown.

Data-driven regularization lowers the size barrier of cryo-EM structure determination.

Macromolecular structure determination by electron cryo-microscopy (cryo-EM) is limited by the alignment of noisy images of individual particles. Because smaller particles have weaker signals, alignment errors impose size limitations on its applicability. Here, we explore how image alignment is improved by the application of deep learning to exploit prior knowledge about biological macromolecular structures that would otherwise be difficult to express mathematically.

Confronting heterogeneity in cryogenic electron microscopy data: Innovative strategies and future perspectives with data-driven methods.

The surge in the influx of data from cryogenic electron microscopy (cryo-EM) experiments has intensified the demand for robust algorithms capable of autonomously managing structurally heterogeneous datasets. This presents a wealth of exciting opportunities from a data science viewpoint, inspiring the development of numerous innovative, application-specific methods, many of which leverage contemporary data-driven techniques. However, addressing the challenges posed by heterogeneous datasets remains a paramount yet unresolved issue in the field.

Ghostbuster: A phase retrieval diffraction tomography algorithm for cryo-EM.

Ewald sphere curvature correction, which extends beyond the projection approximation, stretches the shallow depth of field in cryo-EM reconstructions of thick particles. Here we show that even for previously assumed thin particles, reconstruction artifacts which we refer to as ghosts can appear. By retrieving the lost phases of the electron exitwaves and accounting for the first Born approximation scattering within the particle, we show that these ghosts can be effectively eliminated.

Automated model building and protein identification in cryo-EM maps.

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts.

Disease-specific tau filaments assemble via polymorphic intermediates.

Intermediate species in the assembly of amyloid filaments are believed to play a central role in neurodegenerative diseases and may constitute important targets for therapeutic intervention. However, structural information about intermediate species has been scarce and the molecular mechanisms by which amyloids assemble remain largely unknown. Here we use time-resolved cryogenic electron microscopy to study the in vitro assembly of recombinant truncated tau (amino acid residues 297-391) into paired helical filaments of Alzheimer's disease or into filaments of chronic traumatic encephalopathy.

Automated model building and protein identification in cryo-EM maps.

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention. We present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality as those generated by human experts.

New tools for automated cryo-EM single-particle analysis in RELION-4.0.

We describe new tools for the processing of electron cryo-microscopy (cryo-EM) images in the fourth major release of the RELION software. In particular, we introduce VDAM, a variable-metric gradient descent algorithm with adaptive moments estimation, for image refinement; a convolutional neural network for unsupervised selection of 2D classes; and a flexible framework for the design and execution of multiple jobs in pre-defined workflows. In addition, we present a stand-alone utility called MDCatch that links the execution of jobs within this framework with metadata gathering during microscope data acquisition.

Structure of the SARS-CoV-2 RNA-dependent RNA polymerase in the presence of favipiravir-RTP.

The RNA polymerase inhibitor favipiravir is currently in clinical trials as a treatment for infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), despite limited information about the molecular basis for its activity. Here we report the structure of favipiravir ribonucleoside triphosphate (favipiravir-RTP) in complex with the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) bound to a template:primer RNA duplex, determined by electron cryomicroscopy (cryoEM) to a resolution of 2.5 Å.

Exploiting prior knowledge about biological macromolecules in cryo-EM structure determination.

Three-dimensional reconstruction of the electron-scattering potential of biological macromolecules from electron cryo-microscopy (cryo-EM) projection images is an ill-posed problem. The most popular cryo-EM software solutions to date rely on a regularization approach that is based on the prior assumption that the scattering potential varies smoothly over three-dimensional space. Although this approach has been hugely successful in recent years, the amount of prior knowledge that it exploits compares unfavorably with the knowledge about biological structures that has been accumulated over decades of research in structural biology.

New tools for automated high-resolution cryo-EM structure determination in RELION-3.

Here, we describe the third major release of RELION. CPU-based vector acceleration has been added in addition to GPU support, which provides flexibility in use of resources and avoids memory limitations. Reference-free autopicking with Laplacian-of-Gaussian filtering and execution of jobs from python allows non-interactive processing during acquisition, including 2D-classification, model generation and 3D-classification.

Publisher Correction: Structure of the chloroplast ribosome with chl-RRF and hibernation-promoting factor.

In the version of this Article originally published, the name of co-author Annemarie Perez Boerema was coded wrongly, resulting in it being incorrect when exported to citation databases. This has been corrected, though no visible changes will be apparent.

Characterisation of molecular motions in cryo-EM single-particle data by multi-body refinement in RELION.

Macromolecular complexes that exhibit continuous forms of structural flexibility pose a challenge for many existing tools in cryo-EM single-particle analysis. We describe a new tool, called multi-body refinement, which models flexible complexes as a user-defined number of rigid bodies that move independently from each other. Using separate focused refinements with iteratively improved partial signal subtraction, the new tool generates improved reconstructions for each of the defined bodies in a fully automated manner.

Structure of the chloroplast ribosome with chl-RRF and hibernation-promoting factor.

Oxygenic photosynthesis produces oxygen and builds a variety of organic compounds, changing the chemistry of the air, the sea and fuelling the food chain on our planet. The photochemical reactions underpinning this process in plants take place in the chloroplast. Chloroplasts evolved ~1.

Cryo-EM reconstruction of the chlororibosome to 3.2 Å resolution within 24 h.

The introduction of direct detectors and the automation of data collection in cryo-EM have led to a surge in data, creating new opportunities for advancing computational processing. In particular, on-the-fly workflows that connect data collection with three-dimensional reconstruction would be valuable for more efficient use of cryo-EM and its application as a sample-screening tool. Here, accelerated on-the-fly analysis is reported with optimized organization of the data-processing tools, image acquisition and particle alignment that make it possible to reconstruct the three-dimensional density of the 70S chlororibosome to 3.

Structures of the human mitochondrial ribosome in native states of assembly.

Mammalian mitochondrial ribosomes (mitoribosomes) have less rRNA content and 36 additional proteins compared with the evolutionarily related bacterial ribosome. These differences make the assembly of mitoribosomes more complex than the assembly of bacterial ribosomes, but the molecular details of mitoribosomal biogenesis remain elusive. Here, we report the structures of two late-stage assembly intermediates of the human mitoribosomal large subunit (mt-LSU) isolated from a native pool within a human cell line and solved by cryo-EM to ∼3-Å resolution.

Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2.

By reaching near-atomic resolution for a wide range of specimens, single-particle cryo-EM structure determination is transforming structural biology. However, the necessary calculations come at large computational costs, which has introduced a bottleneck that is currently limiting throughput and the development of new methods. Here, we present an implementation of the RELION image processing software that uses graphics processors (GPUs) to address the most computationally intensive steps of its cryo-EM structure determination workflow.

SAXS-Guided Metadynamics.

The small-angle X-ray scattering (SAXS) methodology enables structural characterization of biological macromolecules in solution. However, because SAXS provides low-dimensional information, several potential structural configurations can reproduce the experimental scattering profile, which severely complicates the structural refinement process. Here, we present a bias-exchange metadynamics refinement protocol that incorporates SAXS data as collective variables and therefore tags all possible configurations with their corresponding free energies, which allows identification of a unique structural solution.