In situ structure determination by subtomogram averaging

TomoNet: A streamlined cryogenic electron tomography software pipeline with automatic particle picking on flexible lattices

Cryogenic electron tomography (cryoET) is capable of determining in situ biological structures of molecular complexes at near-atomic resolution by averaging half a million subtomograms. While abundant complexes/particles are often clustered in arrays, precisely locating and seamlessly averaging such particles across many tomograms present major challenges. Here, we developed TomoNet, a software package with a modern graphical user interface to carry out the entire pipeline of cryoET and subtomogram averaging to achieve high resolution. TomoNet features built-in automatic particle picking and three-dimensional (3D) classification functions and integrates commonly used packages to streamline high-resolution subtomogram averaging for structures in 1D, 2D, or 3D arrays. Automatic particle picking is accomplished in two complementary ways: one based on template matching and the other using deep learning. TomoNet's hierarchical file organization and visual display facilitate efficient data management as required for large cryoET datasets. Applications of TomoNet to three types of datasets demonstrate its capability of efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures: virus-like particles, bacterial surface layers within cellular lamellae, and membranes decorated with nuclear egress protein complexes. These results demonstrate TomoNet's potential for broad applications to various cryoET projects targeting high-resolution in situ structures.

TOMOMAN: a software package for large scale cryo-electron tomography data preprocessing, community data sharing, and collaborative computing

Cryo-electron tomography (cryo-ET) and subtomogram averaging (STA) are becoming the preferred methodologies for investigating subcellular and macromolecular structures in native or near-native environments. While cryo-ET is amenable to a wide range of biological problems, these problems often have data processing requirements that need to be individually optimized, precluding the notion of a one-size-fits-all processing pipeline. Cryo-ET data processing is also becoming progressively more complex due to an increasing number of packages for each processing step. Though each package has its own strengths and weaknesses, independent development and different data formats makes them difficult to interface with one another. TOMOMAN (TOMOgram MANager) is an extensible package for streamlining the interoperability of packages, enabling users to develop project-specific processing workflows. TOMOMAN does this by maintaining an internal metadata format and wrapping external packages to manage and perform preprocessing, from raw tilt-series data to reconstructed tomograms. TOMOMAN can also export this metadata between various STA packages. TOMOMAN also includes tools for archiving projects to data repositories; allowing subsequent users to download TOMOMAN projects and directly resume processing where it was previously left off. By tracking essential metadata, TOMOMAN streamlines data sharing, which improves reproducibility of published results, reduces computational costs by minimizing reprocessing, and enables distributed cryo-ET projects between multiple groups and institutions. TOMOMAN provides a way for users to test different software packages to develop processing workflows that meet the specific needs of their biological questions and to distribute their results with the broader scientific community.

STOPGAP: an open-source package for template matching, subtomogram alignment and classification

Cryo-electron tomography (cryo-ET) enables molecular-resolution 3D imaging of complex biological specimens such as viral particles, cellular sections and, in some cases, whole cells. This enables the structural characterization of molecules in their near-native environments, without the need for purification or separation, thereby preserving biological information such as conformational states and spatial relationships between different molecular species. Subtomogram averaging is an image-processing workflow that allows users to leverage cryo-ET data to identify and localize target molecules, determine high-resolution structures of repeating molecular species and classify different conformational states. Here, STOPGAP, an open-source package for subtomogram averaging that is designed to provide users with fine control over each of these steps, is described. In providing detailed descriptions of the image-processing algorithms that STOPGAP uses, this manuscript is also intended to serve as a technical resource to users as well as for further community-driven software development.

Learning structural heterogeneity from cryo-electron sub-tomograms with tomoDRGN

Cryo-electron tomography (cryo-ET) enables observation of macromolecular complexes in their native, spatially contextualized cellular environment. Cryo-ET processing software to visualize such complexes at nanometer resolution via iterative alignment and averaging are well developed but rely upon assumptions of structural homogeneity among the complexes of interest. Recently developed tools allow for some assessment of structural diversity but have limited capacity to represent highly heterogeneous structures, including those undergoing continuous conformational changes. Here we extend the highly expressive cryoDRGN (Deep Reconstructing Generative Networks) deep learning architecture, originally created for single-particle cryo-electron microscopy analysis, to cryo-ET. Our new tool, tomoDRGN, learns a continuous low-dimensional representation of structural heterogeneity in cryo-ET datasets while also learning to reconstruct heterogeneous structural ensembles supported by the underlying data. Using simulated and experimental data, we describe and benchmark architectural choices within tomoDRGN that are uniquely necessitated and enabled by cryo-ET. We additionally illustrate tomoDRGN's efficacy in analyzing diverse datasets, using it to reveal high-level organization of human immunodeficiency virus (HIV) capsid complexes assembled in virus-like particles and to resolve extensive structural heterogeneity among ribosomes imaged in situ.

Cool-contacts: Cryo-Electron Microscopy of Membrane Contact Sites and Their Components

Electron microscopy has played a pivotal role in elucidating the ultrastructure of membrane contact sites between cellular organelles. The advent of cryo-electron microscopy has ushered in the ability to determine atomic models of constituent proteins or protein complexes within sites of membrane contact through single particle analysis. Furthermore, it enables the visualization of the three-dimensional architecture of membrane contact sites, encompassing numerous copies of proteins, whether in vitro reconstituted or directly observed in situ using cryo-electron tomography. Nevertheless, there exists a scarcity of cryo-electron microscopy studies focused on the site of membrane contact and their constitutive proteins. This review provides an overview of the contributions made by cryo-electron microscopy to our understanding of membrane contact sites, outlines the associated limitations, and explores prospects in this field.

Computational methods for in situ structural studies with cryogenic electron tomography

Cryo-electron tomography (cryo-ET) plays a critical role in imaging microorganisms in situ in terms of further analyzing the working mechanisms of viruses and drug exploitation, among others. A data processing workflow for cryo-ET has been developed to reconstruct three-dimensional density maps and further build atomic models from a tilt series of two-dimensional projections. Low signal-to-noise ratio (SNR) and missing wedge are two major factors that make the reconstruction procedure challenging. Because only few near-atomic resolution structures have been reconstructed in cryo-ET, there is still much room to design new approaches to improve universal reconstruction resolutions. This review summarizes classical mathematical models and deep learning methods among general reconstruction steps. Moreover, we also discuss current limitations and prospects. This review can provide software and methods for each step of the entire procedure from tilt series by cryo-ET to 3D atomic structures. In addition, it can also help more experts in various fields comprehend a recent research trend in cryo-ET. Furthermore, we hope that more researchers can collaborate in developing computational methods and mathematical models for high-resolution three-dimensional structures from cryo-ET datasets.

MDTOMO method for continuous conformational variability analysis in cryo electron subtomograms based on molecular dynamics simulations

Cryo electron tomography (cryo-ET) allows observing macromolecular complexes in their native environment. The common routine of subtomogram averaging (STA) allows obtaining the three-dimensional (3D) structure of abundant macromolecular complexes, and can be coupled with discrete classification to reveal conformational heterogeneity of the sample. However, the number of complexes extracted from cryo-ET data is usually small, which restricts the discrete-classification results to a small number of enough populated states and, thus, results in a largely incomplete conformational landscape. Alternative approaches are currently being investigated to explore the continuity of the conformational landscapes that in situ cryo-ET studies could provide. In this article, we present MDTOMO, a method for analyzing continuous conformational variability in cryo-ET subtomograms based on Molecular Dynamics (MD) simulations. MDTOMO allows obtaining an atomic-scale model of conformational variability and the corresponding free-energy landscape, from a given set of cryo-ET subtomograms. The article presents the performance of MDTOMO on a synthetic ABC exporter dataset and an in situ SARS-CoV-2 spike dataset. MDTOMO allows analyzing dynamic properties of molecular complexes to understand their biological functions, which could also be useful for structure-based drug discovery.

Learning structural heterogeneity from cryo-electron sub-tomograms with tomoDRGN

Cryo-electron tomography (cryo-ET) allows one to observe macromolecular complexes in their native, spatially contextualized environment. Tools to visualize such complexes at nanometer resolution via iterative alignment and averaging are well-developed but rely on assumptions of structural homogeneity among the complexes under consideration. Recently developed downstream analysis tools allow for some assessment of macromolecular diversity but have limited capacity to represent highly heterogeneous macromolecules, including those undergoing continuous conformational changes. Here, we extend the highly expressive cryoDRGN deep learning architecture, originally created for cryo-electron microscopy single particle analysis, to sub-tomograms. Our new tool, tomoDRGN, learns a continuous low-dimensional representation of structural heterogeneity in cryo-ET datasets while also learning to reconstruct a large, heterogeneous ensemble of structures supported by the underlying data. Using simulated and experimental data, we describe and benchmark architectural choices within tomoDRGN that are uniquely necessitated and enabled by cryo-ET data. We additionally illustrate tomoDRGN's efficacy in analyzing an exemplar dataset, using it to reveal extensive structural heterogeneity among ribosomes imaged in situ.

Computational Methods Toward Unbiased Pattern Mining and Structure Determination in Cryo-Electron Tomography Data

Cryo-electron tomography can uniquely probe the native cellular environment for macromolecular structures. Tomograms feature complex data with densities of diverse, densely crowded macromolecular complexes, low signal-to-noise, and artifacts such as the missing wedge effect. Post-processing of this data generally involves isolating regions or particles of interest from tomograms, organizing them into related groups, and rendering final structures through subtomogram averaging. Template-matching and reference-based structure determination are popular analysis methods but are vulnerable to biases and can often require significant user input. Most importantly, these approaches cannot identify novel complexes that reside within the imaged cellular environment. To reliably extract and resolve structures of interest, efficient and unbiased approaches are therefore of great value. This review highlights notable computational software and discusses how they contribute to making automated structural pattern discovery a possibility. Perspectives emphasizing the importance of features for user-friendliness and accessibility are also presented.

How Membrane Contact Sites Shape the Phagophore

During macroautophagy, phagophores establish multiple membrane contact sites (MCSs) with other organelles that are pivotal for proper phagophore assembly and growth. In S. cerevisiae, phagophore contacts have been observed with the vacuole, the ER, and lipid droplets. In situ imaging studies have greatly advanced our understanding of the structure and function of these sites. Here, we discuss how in situ structural methods like cryo-CLEM can give unprecedented insights into MCSs, and how they help to elucidate the structural arrangements of MCSs within cells. We further summarize the current knowledge of the contact sites in autophagy, focusing on autophagosome biogenesis in the model organism S. cerevisiae.

Studying membrane modulation mechanisms by electron cryo-tomography

Membrane modulation is a key part of cellular life. Critical to processes like energy production, cell division, trafficking, migration and even pathogen entry, defects in membrane modulation are often associated with diseases. Studying the molecular mechanisms of membrane modulation is challenging due to the highly dynamic nature of the oligomeric assemblies involved, which adopt multiple conformations depending on the precise event they are participating in. With the development of electron cryo-tomography and subtomogram averaging, many of these challenges are being resolved as it is now possible to observe complex macromolecular assemblies inside a cell at nanometre to sub-nanometre resolutions. Here, we review the different ways electron cryo-tomography is being used to help uncover the molecular mechanisms used by cells to shape their membranes.

In-cell NMR: Why and how?

NMR spectroscopy has been applied to cells and tissues analysis since its beginnings, as early as 1950. We have attempted to gather here in a didactic fashion the broad diversity of data and ideas that emerged from NMR investigations on living cells. Covering a large proportion of the periodic table, NMR spectroscopy permits scrutiny of a great variety of atomic nuclei in all living organisms non-invasively. It has thus provided quantitative information on cellular atoms and their chemical environment, dynamics, or interactions. We will show that NMR studies have generated valuable knowledge on a vast array of cellular molecules and events, from water, salts, metabolites, cell walls, proteins, nucleic acids, drugs and drug targets, to pH, redox equilibria and chemical reactions. The characterization of such a multitude of objects at the atomic scale has thus shaped our mental representation of cellular life at multiple levels, together with major techniques like mass-spectrometry or microscopies. NMR studies on cells has accompanied the developments of MRI and metabolomics, and various subfields have flourished, coined with appealing names: fluxomics, foodomics, MRI and MRS (i.e. imaging and localized spectroscopy of living tissues, respectively), whole-cell NMR, on-cell ligand-based NMR, systems NMR, cellular structural biology, in-cell NMR… All these have not grown separately, but rather by reinforcing each other like a braided trunk. Hence, we try here to provide an analytical account of a large ensemble of intricately linked approaches, whose integration has been and will be key to their success. We present extensive overviews, firstly on the various types of information provided by NMR in a cellular environment (the "why", oriented towards a broad readership), and secondly on the employed NMR techniques and setups (the "how", where we discuss the past, current and future methods). Each subsection is constructed as a historical anthology, showing how the intrinsic properties of NMR spectroscopy and its developments structured the accessible knowledge on cellular phenomena. Using this systematic approach, we sought i) to make this review accessible to the broadest audience and ii) to highlight some early techniques that may find renewed interest. Finally, we present a brief discussion on what may be potential and desirable developments in the context of integrative studies in biology.

Artificial Intelligence in Cryo-Electron Microscopy

Cryo-electron microscopy (cryo-EM) has become an unrivaled tool for determining the structure of macromolecular complexes. The biological function of macromolecular complexes is inextricably tied to the flexibility of these complexes. Single particle cryo-EM can reveal the conformational heterogeneity of a biochemically pure sample, leading to well-founded mechanistic hypotheses about the roles these complexes play in biology. However, the processing of increasingly large, complex datasets using traditional data processing strategies is exceedingly expensive in both user time and computational resources. Current innovations in data processing capitalize on artificial intelligence (AI) to improve the efficiency of data analysis and validation. Here, we review new tools that use AI to automate the data analysis steps of particle picking, 3D map reconstruction, and local resolution determination. We discuss how the application of AI moves the field forward, and what obstacles remain. We also introduce potential future applications of AI to use cryo-EM in understanding protein communities in cells.

Model building of protein complexes from intermediate-resolution cryo-EM maps with deep learning-guided automatic assembly

Advances in microscopy instruments and image processing algorithms have led to an increasing number of cryo-electron microscopy (cryo-EM) maps. However, building accurate models into intermediate-resolution EM maps remains challenging and labor-intensive. Here, we propose an automatic model building method of multi-chain protein complexes from intermediate-resolution cryo-EM maps, named EMBuild, by integrating AlphaFold structure prediction, FFT-based global fitting, domain-based semi-flexible refinement, and graph-based iterative assembling on the main-chain probability map predicted by a deep convolutional network. EMBuild is extensively evaluated on diverse test sets of 47 single-particle EM maps at 4.0-8.0 Å resolution and 16 subtomogram averaging maps of cryo-ET data at 3.7-9.3 Å resolution, and compared with state-of-the-art approaches. We demonstrate that EMBuild is able to build high-quality complex structures that are comparably accurate to the manually built PDB structures from the cryo-EM maps. These results demonstrate the accuracy and reliability of EMBuild in automatic model building.

In-Cell Structural Biology by NMR: The Benefits of the Atomic Scale

In-cell structural biology aims at extracting structural information about proteins or nucleic acids in their native, cellular environment. This emerging field holds great promise and is already providing new facts and outlooks of interest at both fundamental and applied levels. NMR spectroscopy has important contributions on this stage: It brings information on a broad variety of nuclei at the atomic scale, which ensures its great versatility and uniqueness. Here, we detail the methods, the fundamental knowledge, and the applications in biomedical engineering related to in-cell structural biology by NMR. We finally propose a brief overview of the main other techniques in the field (EPR, smFRET, cryo-ET, etc.) to draw some advisable developments for in-cell NMR. In the era of large-scale screenings and deep learning, both accurate and qualitative experimental evidence are as essential as ever to understand the interior life of cells. In-cell structural biology by NMR spectroscopy can generate such a knowledge, and it does so at the atomic scale. This review is meant to deliver comprehensive but accessible information, with advanced technical details and reflections on the methods, the nature of the results, and the future of the field.

In silico reconstitution of DNA replication. Lessons from single-molecule imaging and cryo-tomography applied to single-particle cryo-EM

DNA replication has been reconstituted in vitro with yeast proteins, and the minimal system requires the coordinated assembly of 16 distinct replication factors, consisting of 42 polypeptides. To understand the molecular interplay between these factors at the single residue level, new structural biology tools are being developed. Inspired by advances in single-molecule fluorescence imaging and cryo-tomography, novel single-particle cryo-EM experiments have been used to characterise the structural mechanism for the loading of the replicative helicase. Here, we discuss how in silico reconstitution of single-particle cryo-EM data can help describe dynamic systems that are difficult to approach with conventional three-dimensional classification tools.

Entropy-regularized deconvolution of cellular cryotransmission electron tomograms

Cellular cryo-electron tomography suffers from severely compromised Z resolution due to the missing wedges of information not collected during the acquisition of tilt series. This paper shows that application of entropy-regularized deconvolution to transmission electron tomography substantially fills in this missing information, allowing for improved Z resolution and better interpretation of cellular structures.

Cryo-electron tomography (cryo-ET) allows for the high-resolution visualization of biological macromolecules. However, the technique is limited by a low signal-to-noise ratio (SNR) and variance in contrast at different frequencies, as well as reduced Z resolution. Here, we applied entropy-regularized deconvolution (ER-DC) to cryo-ET data generated from transmission electron microscopy (TEM) and reconstructed using weighted back projection (WBP). We applied deconvolution to several in situ cryo-ET datasets and assessed the results by Fourier analysis and subtomogram analysis (STA).

Architects of their own environment: How membrane proteins shape the Gram-negative cell envelope

Gram-negative bacteria are surrounded by a complex multilayered cell envelope, consisting of an inner and an outer membrane, and separated by the aqueous periplasm, which contains a thin peptidoglycan cell wall. These bacteria employ an arsenal of highly specialized membrane protein machineries to ensure the correct assembly and maintenance of the membranes forming the cell envelope. Here, we review the diverse protein systems, which perform these functions in Escherichia coli, such as the folding and insertion of membrane proteins, the transport of lipoproteins and lipopolysaccharide within the cell envelope, the targeting of phospholipids, and the regulation of mistargeted envelope components. Some of these protein machineries have been known for a long time, yet still hold surprises. Others have only recently been described and some are still missing pieces or yet remain to be discovered.

Challenges and triumphs in cryo-electron tomography

Cryo-electron tomography has stepped fully into the spotlight. Enthusiasm is high. Fortunately for us, this is an exciting time to be a cryotomographer, but there is still a way to go before declaring victory. Despite its potential, cryo-electron tomography possesses many inherent challenges. How do we image through thick cell samples, and possibly even tissue? How do we identify a protein of interest amidst the noisy, crowded environment of the cytoplasm? How do we target specific moments of a dynamic cellular process for tomographic imaging? In this review, we cover the history of cryo-electron tomography and how it came to be, roughly speaking, as well as the many approaches that have been developed to overcome its intrinsic limitations.

Structure and dynamics of photoreceptor sensory cilia

The rod and cone photoreceptor cells of the vertebrate retina have highly specialized structures that enable them to carry out their function of light detection over a broad range of illumination intensities with optimized spatial and temporal resolution. Most prominent are their unusually large sensory cilia, consisting of outer segments packed with photosensitive disc membranes, a connecting cilium with many features reminiscent of the primary cilium transition zone, and a pair of centrioles forming a basal body which serves as the platform upon which the ciliary axoneme is assembled. These structures form a highway through which an enormous flux of material moves on a daily basis to sustain the continual turnover of outer segment discs and the energetic demands of phototransduction. After decades of study, the details of the fine structure and distribution of molecular components of these structures are still incompletely understood, but recent advances in cellular imaging techniques and animal models of inherited ciliary defects are yielding important new insights. This knowledge informs our understanding both of the mechanisms of trafficking and assembly and of the pathophysiological mechanisms of human blinding ciliopathies.

Step-by-step guide to efficient subtomogram averaging of virus-like particles with Dynamo

Subtomogram averaging (STA) is a powerful image processing technique in electron tomography used to determine the 3D structure of macromolecular complexes in their native environments. It is a fast growing technique with increasing importance in structural biology. The computational aspect of STA is very complex and depends on a large number of variables. We noticed a lack of detailed guides for STA processing. Also, current publications in this field often lack a documentation that is practical enough to reproduce the results with reasonable effort, which is necessary for the scientific community to grow. We therefore provide a complete, detailed, and fully reproducible processing protocol that covers all aspects of particle picking and particle alignment in STA. The command line-based workflow is fully based on the popular Dynamo software for STA. Within this workflow, we also demonstrate how large parts of the processing pipeline can be streamlined and automatized for increased throughput. This protocol is aimed at users on all levels. It can be used for training purposes, or it can serve as basis to design user-specific projects by taking advantage of the flexibility of Dynamo by modifying and expanding the given pipeline. The protocol is successfully validated using the Electron Microscopy Public Image Archive (EMPIAR) database entry 10164 from immature HIV-1 virus-like particles (VLPs) that describe a geometry often seen in electron tomography.

In situ ultrastructures of two evolutionarily distant apicomplexan rhoptry secretion systems

Parasites of the phylum Apicomplexa cause important diseases including malaria, cryptosporidiosis and toxoplasmosis. These intracellular pathogens inject the contents of an essential organelle, the rhoptry, into host cells to facilitate invasion and infection. However, the structure and mechanism of this eukaryotic secretion system remain elusive. Here, using cryo-electron tomography and subtomogram averaging, we report the conserved architecture of the rhoptry secretion system in the invasive stages of two evolutionarily distant apicomplexans, Cryptosporidium parvum and Toxoplasma gondii. In both species, we identify helical filaments, which appear to shape and compartmentalize the rhoptries, and an apical vesicle (AV), which facilitates docking of the rhoptry tip at the parasite’s apical region with the help of an elaborate ultrastructure named the rhoptry secretory apparatus (RSA); the RSA anchors the AV at the parasite plasma membrane. Depletion of T. gondii Nd9, a protein required for rhoptry secretion, disrupts the RSA ultrastructure and AV-anchoring. Moreover, T. gondii contains a line of AV-like vesicles, which interact with a pair of microtubules and accumulate towards the AV, leading to a working model for AV-reloading and discharging of multiple rhoptries. Together, our analyses provide an ultrastructural framework to understand how these important parasites deliver effectors into host cells.

The rhoptry is an apical secretory organelle of apicomplexan parasites that is essential for host cell invasion. Here, Mageswaran et al. provide in situ ultrastructures of rhoptries from two pathogens, revealing a conserved architecture including luminal filaments and a distinct docking mechanism.

HEMNMA-3D: Cryo Electron Tomography Method Based on Normal Mode Analysis to Study Continuous Conformational Variability of Macromolecular Complexes

Cryogenic electron tomography (cryo-ET) allows structural determination of biomolecules in their native environment (in situ). Its potential of providing information on the dynamics of macromolecular complexes in cells is still largely unexploited, due to the challenges of the data analysis. The crowded cell environment and continuous conformational changes of complexes make difficult disentangling the data heterogeneity. We present HEMNMA-3D, which is, to the best of our knowledge, the first method for analyzing cryo electron subtomograms in terms of continuous conformational changes of complexes. HEMNMA-3D uses a combination of elastic and rigid-body 3D-to-3D iterative alignments of a flexible 3D reference (atomic structure or electron microscopy density map) to match the conformation, orientation, and position of the complex in each subtomogram. The elastic matching combines molecular mechanics simulation (Normal Mode Analysis of the 3D reference) and experimental, subtomogram data analysis. The rigid-body alignment includes compensation for the missing wedge, due to the limited tilt angle of cryo-ET. The conformational parameters (amplitudes of normal modes) of the complexes in subtomograms obtained through the alignment are processed to visualize the distribution of conformations in a space of lower dimension (typically, 2D or 3D) referred to as space of conformations. This allows a visually interpretable insight into the dynamics of the complexes, by calculating 3D averages of subtomograms with similar conformations from selected (densest) regions and by recording movies of the 3D reference's displacement along selected trajectories through the densest regions. We describe HEMNMA-3D and show its validation using synthetic datasets. We apply HEMNMA-3D to an experimental dataset describing in situ nucleosome conformational variability. HEMNMA-3D software is available freely (open-source) as part of ContinuousFlex plugin of Scipion V3.0 (http://scipion.i2pc.es).

An overview of the recent advances in cryo-electron microscopy for life sciences

Cryo-electron microscopy (CryoEM) has superseded X-ray crystallography and NMR to emerge as a popular and effective tool for structure determination in recent times. It has become indispensable for the characterization of large macromolecular assemblies, membrane proteins, or samples that are limited, conformationally heterogeneous, and recalcitrant to crystallization. Besides, it is the only tool capable of elucidating high-resolution structures of macromolecules and biological assemblies in situ. A state-of-the-art electron microscope operable at cryo-temperature helps preserve high-resolution details of the biological sample. The structures can be determined, either in isolation via single-particle analysis (SPA) or helical reconstruction, electron diffraction (ED) or within the cellular environment via cryo-electron tomography (cryoET). All the three streams of SPA, ED, and cryoET (along with subtomogram averaging) have undergone significant advancements in recent times. This has resulted in breaking the boundaries with respect to both the size of the macromolecules/assemblies whose structures could be determined along with the visualization of atomic details at resolutions unprecedented for cryoEM. In addition, the collection of larger datasets combined with the ability to sort and process multiple conformational states from the same sample are providing the much-needed link between the protein structures and their functions. In overview, these developments are helping scientists decipher the molecular mechanism of critical cellular processes, solve structures of macromolecules that were challenging targets for structure determination until now, propelling forward the fields of biology and biomedicine. Here, we summarize recent advances and key contributions of the three cryo-electron microscopy streams of SPA, ED, and cryoET.

Multiscale Electron Microscopy for the Study of Viral Replication Organelles

During infection with positive-strand RNA viruses, viral RNA synthesis associates with modified intracellular membranes that form unique and captivating structures in the cytoplasm of the infected cell. These viral replication organelles (ROs) play a key role in the replicative cycle of important human pathogens like coronaviruses, enteroviruses, or flaviviruses. From their discovery to date, progress in our understanding of viral ROs has closely followed new developments in electron microscopy (EM). This review gives a chronological account of this progress and an introduction to the different EM techniques that enabled it. With an ample repertoire of imaging modalities, EM is nowadays a versatile technique that provides structural and functional information at a wide range of scales. Together with well-established approaches like electron tomography or labeling methods, we examine more recent developments, such as volume scanning electron microscopy (SEM) and in situ cryotomography, which are only beginning to be applied to the study of viral ROs. We also highlight the first cryotomography analyses of viral ROs, which have led to the discovery of macromolecular complexes that may serve as RO channels that control the export of newly-made viral RNA. These studies are key first steps towards elucidating the macromolecular complexity of viral ROs.

Fake It 'Till You Make It-The Pursuit of Suitable Membrane Mimetics for Membrane Protein Biophysics

Membrane proteins evolved to reside in the hydrophobic lipid bilayers of cellular membranes. Therefore, membrane proteins bridge the different aqueous compartments separated by the membrane, and furthermore, dynamically interact with their surrounding lipid environment. The latter not only stabilizes membrane proteins, but directly impacts their folding, structure and function. In order to be characterized with biophysical and structural biological methods, membrane proteins are typically extracted and subsequently purified from their native lipid environment. This approach requires that lipid membranes are replaced by suitable surrogates, which ideally closely mimic the native bilayer, in order to maintain the membrane proteins structural and functional integrity. In this review, we survey the currently available membrane mimetic environments ranging from detergent micelles to bicelles, nanodiscs, lipidic-cubic phase (LCP), liposomes, and polymersomes. We discuss their respective advantages and disadvantages as well as their suitability for downstream biophysical and structural characterization. Finally, we take a look at ongoing methodological developments, which aim for direct in-situ characterization of membrane proteins within native membranes instead of relying on membrane mimetics.

Complete structure of the chemosensory array core signalling unit in an E. coli minicell strain

Motile bacteria sense chemical gradients with transmembrane receptors organised in supramolecular signalling arrays. Understanding stimulus detection and transmission at the molecular level requires precise structural characterisation of the array building block known as a core signalling unit. Here we introduce an Escherichia coli strain that forms small minicells possessing extended and highly ordered chemosensory arrays. We use cryo-electron tomography and subtomogram averaging to provide a three-dimensional map of a complete core signalling unit, with visible densities corresponding to the HAMP and periplasmic domains. This map, combined with previously determined high resolution structures and molecular dynamics simulations, yields a molecular model of the transmembrane core signalling unit and enables spatial localisation of its individual domains. Our work thus offers a solid structural basis for the interpretation of a wide range of existing data and the design of further experiments to elucidate signalling mechanisms within the core signalling unit and larger array.