Single particle tomography in EMAN2

Automatic detection of alignment errors in cryo-electron tomography

Cryo-electron tomography is an imaging technique that allows the study of the three-dimensional structure of a wide range of biological samples, from entire cellular environments to purified specimens. This technique collects a series of images from different views of the specimen by tilting the sample stage in the microscope. Subsequently, this information is combined into a three-dimensional reconstruction. To obtain reliable representations of the specimen of study, it is mandatory to define the acquisition geometry accurately. This is achieved by aligning all tilt images to a standard reference scheme. Errors in this step introduce artifacts into the final reconstructed tomograms, leading to loss of resolution and making them unsuitable for detailed sample analysis. This publication presents algorithms for automatically assessing the alignment quality of the tilt series and their classification based on the residual errors provided by the alignment algorithms. If no alignment information is available, a set of algorithms for calculating the residual vectors focused on fiducial markers is also presented. This software is accessible as part of the Xmipp software package and the Scipion framework.

CryoVesNet: A dedicated framework for synaptic vesicle segmentation in cryo-electron tomograms

Cryo-electron tomography (cryo-ET) has the potential to reveal cell structure down to atomic resolution. Nevertheless, cellular cryo-ET data is highly complex, requiring image segmentation for visualization and quantification of subcellular structures. Due to noise and anisotropic resolution in cryo-ET data, automatic segmentation based on classical computer vision approaches usually does not perform satisfactorily. Communication between neurons relies on neurotransmitter-filled synaptic vesicle (SV) exocytosis. Cryo-ET study of the spatial organization of SVs and their interconnections allows a better understanding of the mechanisms of exocytosis regulation. Accurate SV segmentation is a prerequisite to obtaining a faithful connectivity representation. Hundreds of SVs are present in a synapse, and their manual segmentation is a bottleneck. We addressed this by designing a workflow consisting of a convolutional network followed by post-processing steps. Alongside, we provide an interactive tool for accurately segmenting spherical vesicles. Our pipeline can in principle segment spherical vesicles in any cell type as well as extracellular and in vitro spherical vesicles.

Streamlining segmentation of cryo-electron tomography datasets with Ais

Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible, and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available on GitHub. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature segmentations of cellular architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at aiscryoet.org, we hope that Ais will help accelerate research and dissemination of data involving cryoET.

Virion morphology and on-virus spike protein structures of diverse SARS-CoV-2 variants

The evolution of SARS-CoV-2 variants with increased fitness has been accompanied by structural changes in the spike (S) proteins, which are the major target for the adaptive immune response. Single-particle cryo-EM analysis of soluble S protein from SARS-CoV-2 variants has revealed this structural adaptation at high resolution. The analysis of S trimers in situ on intact virions has the potential to provide more functionally relevant insights into S structure and virion morphology. Here, we characterized B.1, Alpha, Beta, Gamma, Delta, Kappa, and Mu variants by cryo-electron microscopy and tomography, assessing S cleavage, virion morphology, S incorporation, "in-situ" high-resolution S structures, and the range of S conformational states. We found no evidence for adaptive changes in virion morphology, but describe multiple different positions in the S protein where amino acid changes alter local protein structure. Taken together, our data are consistent with a model where amino acid changes at multiple positions from the top to the base of the spike cause structural changes that can modulate the conformational dynamics of the S protein.

Structure and organization of full-length Epidermal Growth Factor Receptor in extracellular vesicles by cryo-electron tomography

We report here transport of the Epidermal Growth Factor Receptor (EGFR), Insulin Receptor, 7-pass transmembrane receptor Smoothened, and 13-pass Sodium-iodide symporter to extracellular vesicles (EVs) for structural and functional studies. Mass spectrometry confirmed the transported proteins as the most abundant in EV membranes, and the presence of many receptor-interacting proteins demonstrates the utility of EVs for characterizing membrane protein interactomes. Cryo-electron tomography of EGFR-containing EVs reveals that EGFR forms clusters in the presence of EGF with a ∼3 nm gap between the inner membrane and cytoplasmic density. EGFR extracellular regions do not form regular arrays, suggesting that clustering is mediated by the intracellular region. Subtomogram averaging of the EGFR extracellular region (ECR) yielded a 15 Å map into which the crystal structure of the ligand-bound EGFR ECR dimer fits well. These findings refine our understanding of EGFR activation, clustering, and signaling, and they establish EVs as a versatile platform for structural and functional characterization of human membrane proteins in a native-like environment.

Significance Statement

Atomic or near-atomic resolution structural studies of proteins embedded in cell membranes have proven challenging. We show that transporting integral membrane proteins to cell-derived extracellular vesicles enables structural and functional studies of human membrane proteins in a native membrane environment. We have used this approach to visualize an active form of full-length Epidermal Growth Factor Receptor (EGFR) and show that it forms clusters in the membrane and projects its cytoplasmic signaling domains ∼3 nm away from the membrane surface. EGFR is essential for normal development, but abnormal EGFR activity is associated with several human cancers and is the target of many anticancer therapies. Our studies refine current models of how ligand binding to EGFR transmits signals across cell membranes.

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. Here, we present an image processing pipeline for electron tomography data in RELION-5, with functionality ranging from the import of unprocessed movies to the automated building of atomic models in the final maps. Our explicit definition of metadata items that describe the steps of our pipeline has been designed for interoperability with other software tools and provides a framework for further standardisation.

Automated fiducial-based alignment of cryo-electron tomography tilt series in Dynamo

With the advent of modern technologies for cryo-electron tomography (cryo-ET), high-quality tilt series are more rapidly acquired than processed and analyzed. Thus, a robust and fast-automated alignment for batch processing in cryo-ET is needed. While different software packages have made available several approaches for automated marker-based alignment of tilt series, manual user intervention remains necessary for many datasets, thus preventing high-throughput tomography. We have developed a MATLAB-based framework integrated into the Dynamo software package for automatic detection of fiducial markers that generates a robust alignment model with minimal input parameters. This approach allows high-throughput, unsupervised volume reconstruction. This new module extends Dynamo with a large repertory of tools for tomographic alignment and reconstruction, as well as specific visualization browsers to rapidly assess the biological relevance of the dataset. Our approach has been successfully tested on a broad range of datasets that include diverse biological samples and cryo-ET modalities.

Molecular architecture of the mammalian 2-oxoglutarate dehydrogenase complex

The 2-oxoglutarate dehydrogenase complex (OGDHc) orchestrates a critical reaction regulating the TCA cycle. Although the structure of each OGDHc subunit has been solved, the architecture of the intact complex and inter-subunit interactions still remain unknown. Here we report the assembly of native, intact OGDHc from Sus scrofa heart tissue using cryo-electron microscopy (cryo-EM), cryo-electron tomography (cryo-ET), and subtomogram averaging (STA) to discern native structures of the whole complex and each subunit. Our cryo-EM analyses revealed the E2o cubic core structure comprising eight homotrimers at 3.3-Å resolution. More importantly, the numbers, positions and orientations of each OGDHc subunit were determined by cryo-ET and the STA structures of the core were resolved at 7.9-Å with the peripheral subunits reaching nanometer resolution. Although the distribution of the peripheral subunits E1o and E3 vary among complexes, they demonstrate a certain regularity within the position and orientation. Moreover, we analyzed and validated the interactions between each subunit, and determined the flexible binding mode for E1o, E2o and E3, resulting in a proposed model of Sus scrofa OGDHc. Together, our results reveal distinctive factors driving the architecture of the intact, native OGDHc.

The advent of preventive high-resolution structural histopathology by artificial-intelligence-powered cryogenic electron tomography

Advances in cryogenic electron microscopy (cryoEM) single particle analysis have revolutionized structural biology by facilitating the in vitro determination of atomic- and near-atomic-resolution structures for fully hydrated macromolecular complexes exhibiting compositional and conformational heterogeneity across a wide range of sizes. Cryogenic electron tomography (cryoET) and subtomogram averaging are rapidly progressing toward delivering similar insights for macromolecular complexes in situ, without requiring tags or harsh biochemical purification. Furthermore, cryoET enables the visualization of cellular and tissue phenotypes directly at molecular, nanometric resolution without chemical fixation or staining artifacts. This forward-looking review covers recent developments in cryoEM/ET and related technologies such as cryogenic focused ion beam milling scanning electron microscopy and correlative light microscopy, increasingly enhanced and supported by artificial intelligence algorithms. Their potential application to emerging concepts is discussed, primarily the prospect of complementing medical histopathology analysis. Machine learning solutions are poised to address current challenges posed by "big data" in cryoET of tissues, cells, and macromolecules, offering the promise of enabling novel, quantitative insights into disease processes, which may translate into the clinic and lead to improved diagnostics and targeted therapeutics.

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3-20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3 - 20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

Blik is an extensible 3D visualisation tool for the annotation and analysis of cryo-electron tomography data

Powerful, workflow-agnostic and interactive visualisation is essential for the ad hoc, human-in-the-loop workflows typical of cryo-electron tomography (cryo-ET). While several tools exist for visualisation and annotation of cryo-ET data, they are often integrated as part of monolithic processing pipelines, or focused on a specific task and offering limited reusability and extensibility. With each software suite presenting its own pros and cons and tools tailored to address specific challenges, seamless integration between available pipelines is often a difficult task. As part of the effort to enable such flexibility and move the software ecosystem towards a more collaborative and modular approach, we developed blik, an open-source napari plugin for visualisation and annotation of cryo-ET data (source code: https://github.com/brisvag/blik). blik offers fast, interactive, and user-friendly 3D visualisation thanks to napari, and is built with extensibility and modularity at the core. Data is handled and exposed through well-established scientific Python libraries such as numpy arrays and pandas dataframes. Reusable components (such as data structures, file read/write, and annotation tools) are developed as independent Python libraries to encourage reuse and community contribution. By easily integrating with established image analysis tools-even outside of the cryo-ET world-blik provides a versatile platform for interacting with cryo-ET data. On top of core visualisation features-interactive and simultaneous visualisation of tomograms, particle picks, and segmentations-blik provides an interface for interactive tools such as manual, surface-based and filament-based particle picking, and image segmentation, as well as simple filtering tools. Additional self-contained napari plugins developed as part of this work also implement interactive plotting and selection based on particle features, and label interpolation for easier segmentation. Finally, we highlight the differences with existing software and showcase blik's applicability in biological research.

Complement is activated by elevated IgG3 hexameric platforms and deposits C4b onto distinct antibody domains

IgG3 is unique among the IgG subclasses due to its extended hinge, allotypic diversity and enhanced effector functions, including highly efficient pathogen neutralisation and complement activation. It is also underrepresented as an immunotherapeutic candidate, partly due to a lack of structural information. Here, we use cryoEM to solve structures of antigen-bound IgG3 alone and in complex with complement components. These structures reveal a propensity for IgG3-Fab clustering, which is possible due to the IgG3-specific flexible upper hinge region and may maximise pathogen neutralisation by forming high-density antibody arrays. IgG3 forms elevated hexameric Fc platforms that extend above the protein corona to maximise binding to receptors and the complement C1 complex, which here adopts a unique protease conformation that may precede C1 activation. Mass spectrometry reveals that C1 deposits C4b directly onto specific IgG3 residues proximal to the Fab domains. Structural analysis shows this to be caused by the height of the C1-IgG3 complex. Together, these data provide structural insights into the role of the unique IgG3 extended hinge, which will aid the development and design of upcoming immunotherapeutics based on IgG3.

Morphological Diversity of Dps Complex with Genomic DNA

In response to adverse environmental factors, Escherichia coli cells actively produce Dps proteins which form ordered complexes (biocrystals) with bacterial DNA to protect the genome. The effect of biocrystallization has been described extensively in the scientific literature; furthermore, to date, the structure of the Dps-DNA complex has been established in detail in vitro using plasmid DNA. In the present work, for the first time, Dps complexes with E. coli genomic DNA were studied in vitro using cryo-electron tomography. We demonstrate that genomic DNA forms one-dimensional crystals or filament-like assemblies which transform into weakly ordered complexes with triclinic unit cells, similar to what is observed for plasmid DNA. Changing such environmental factors as pH and KCl and MgCl₂ concentrations leads to the formation of cylindrical structures.

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.

Previously uncharacterized rectangular bacterial structures in the dolphin mouth

Much remains to be explored regarding the diversity of uncultured, host-associated microbes. Here, we describe rectangular bacterial structures (RBSs) in the mouths of bottlenose dolphins. DNA staining revealed multiple paired bands within RBSs, suggesting the presence of cells dividing along the longitudinal axis. Cryogenic transmission electron microscopy and tomography showed parallel membrane-bound segments that are likely cells, encapsulated by an S-layer-like periodic surface covering. RBSs displayed unusual pilus-like appendages with bundles of threads splayed at the tips. We present multiple lines of evidence, including genomic DNA sequencing of micromanipulated RBSs, 16S rRNA gene sequencing, and fluorescence in situ hybridization, suggesting that RBSs are bacterial and distinct from the genera Simonsiella and Conchiformibius (family Neisseriaceae), with which they share similar morphology and division patterning. Our findings highlight the diversity of novel microbial forms and lifestyles that await characterization using tools complementary to genomics such as microscopy.

High-throughput cryo-ET structural pattern mining by unsupervised deep iterative subtomogram clustering

Cryoelectron tomography directly visualizes heterogeneous macromolecular structures in their native and complex cellular environments. However, existing computer-assisted structure sorting approaches are low throughput or inherently limited due to their dependency on available templates and manual labels. Here, we introduce a high-throughput template-and-label-free deep learning approach, Deep Iterative Subtomogram Clustering Approach (DISCA), that automatically detects subsets of homogeneous structures by learning and modeling 3D structural features and their distributions. Evaluation on five experimental cryo-ET datasets shows that an unsupervised deep learning based method can detect diverse structures with a wide range of molecular sizes. This unsupervised detection paves the way for systematic unbiased recognition of macromolecular complexes in situ.

Commercial influenza vaccines vary in HA-complex structure and in induction of cross-reactive HA antibodies

Influenza virus infects millions of people annually and can cause global pandemics. Hemagglutinin (HA) is the primary component of commercial influenza vaccines (CIV), and antibody titer to HA is a primary correlate of protection. Continual antigenic variation of HA requires that CIVs are reformulated yearly. Structural organization of HA complexes have not previously been correlated with induction of broadly reactive antibodies, yet CIV formulations vary in how HA is organized. Using electron microscopy to study four current CIVs, we find structures including: individual HAs, starfish structures with up to 12 HA molecules, and novel spiked-nanodisc structures that display over 50 HA molecules along the complex's perimeter. CIV containing these spiked nanodiscs elicit the highest levels of heterosubtypic cross-reactive antibodies in female mice. Here, we report that HA structural organization can be an important CIV parameter and can be associated with the induction of cross-reactive antibodies to conserved HA epitopes.

Molecular architecture of the Chikungunya virus replication complex

To better understand how positive-strand (+) RNA viruses assemble membrane-associated replication complexes (RCs) to synthesize, process, and transport viral RNA in virus-infected cells, we determined both the high-resolution structure of the core RNA replicase of chikungunya virus and the native RC architecture in its cellular context at subnanometer resolution, using in vitro reconstitution and in situ electron cryotomography, respectively. Within the core RNA replicase, the viral polymerase nsP4, which is in complex with nsP2 helicase-protease, sits in the central pore of the membrane-anchored nsP1 RNA-capping ring. The addition of a large cytoplasmic ring next to the C terminus of nsP1 forms the holo-RNA-RC as observed at the neck of spherules formed in virus-infected cells. These results represent a major conceptual advance in elucidating the molecular mechanisms of RNA virus replication and the principles underlying the molecular architecture of RCs, likely to be shared with many pathogenic (+) RNA viruses.

Multivalent S2-based vaccines provide broad protection against SARS-CoV-2 variants of concern and pangolin coronaviruses

BACKGROUND

The COVID-19 pandemic continues to cause morbidity and mortality worldwide. Most approved COVID-19 vaccines generate a neutralizing antibody response that primarily targets the highly variable receptor-binding domain (RBD) of the SARS-CoV-2 spike (S) protein. SARS-CoV-2 "variants of concern" have acquired mutations in this domain allowing them to evade vaccine-induced humoral immunity. Recent approaches to improve the breadth of protection beyond SARS-CoV-2 have required the use of mixtures of RBD antigens from different sarbecoviruses. It may therefore be beneficial to develop a vaccine in which the protective immune response targets a more conserved region of the S protein.

METHODS

Here we have developed a vaccine based on the conserved S2 subunit of the S protein and optimized the adjuvant and immunization regimen in Syrian hamsters and BALB/c mice. We have characterized the efficacy of the vaccine against SARS-CoV-2 variants and other coronaviruses.

FINDINGS

Immunization with S2-based constructs elicited a broadly cross-reactive IgG antibody response that recognized the spike proteins of not only SARS-CoV-2 variants, but also SARS-CoV-1, and the four endemic human coronaviruses. Importantly, immunization reduced virus titers in respiratory tissues in vaccinated animals challenged with SARS-CoV-2 variants B.1.351 (beta), B.1.617.2 (delta), and BA.1 (omicron) as well as a pangolin coronavirus.

INTERPRETATION

These results suggest that S2-based constructs can elicit a broadly cross-reactive antibody response resulting in limited virus replication, thus providing a framework for designing vaccines that elicit broad protection against coronaviruses.

FUNDING

NIH, Japan Agency for Medical Research and Development, Garry Betty/ V Foundation Chair Fund, and NSF.

Reconstruction of 3D density from solution scattering

Ab initio modeling methods have proven to be powerful means of interpreting solution scattering data. In the absence of atomic models, or complementary to them, ab initio modeling approaches can be used for generating low-resolution particle envelopes using only solution scattering profiles. Recently, a new ab initio reconstruction algorithm has been introduced to the scientific community, called DENSS. DENSS is unique among ab initio modeling algorithms in that it solves the inverse scattering problem, i.e., the 1D scattering intensities are directly used to determine the 3D particle density. The reconstruction of particle density has several advantages over conventional uniform density modeling approaches, including the ability to reconstruct a much wider range of particle types and the ability to visualize low-resolution density fluctuations inside the particle envelope. In this chapter we will discuss the theory behind this new approach, how to use DENSS, and how to interpret the results. Several examples with experimental and simulated data will be provided.

Efficient manual annotation of cryogenic electron tomograms using IMOD

Annotation highlights and segmentation isolates features in cryogenic electron tomograms to improve visualization and quantification of features (for example, their size and abundance, and spatial relationships with other features), facilitating phenotypic structural analyses of cellular tomograms. Here, we present a manual annotation protocol using the open-source software IMOD and describe segmentation of three types of common cellular features: membranes, large globules, and filaments. IMOD's interpolation function can improve the speed of manual annotation up to an order of magnitude.

ACE2-containing defensosomes serve as decoys to inhibit SARS-CoV-2 infection

Extracellular vesicles of endosomal origin, exosomes, mediate intercellular communication by transporting substrates with a variety of functions related to tissue homeostasis and disease. Their diagnostic and therapeutic potential has been recognized for diseases such as cancer in which signaling defects are prominent. However, it is unclear to what extent exosomes and their cargo inform the progression of infectious diseases. We recently defined a subset of exosomes termed defensosomes that are mobilized during bacterial infection in a manner dependent on autophagy proteins. Through incorporating protein receptors on their surface, defensosomes mediated host defense by binding and inhibiting pore-forming toxins secreted by bacterial pathogens. Given this capacity to serve as decoys that interfere with surface protein interactions, we investigated the role of defensosomes during infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of Coronavirus Disease 2019 (COVID-19). Consistent with a protective function, exosomes containing high levels of the viral receptor ACE2 in bronchoalveolar lavage fluid (BALF) from critically ill COVID-19 patients was associated with reduced intensive care unit (ICU) and hospitalization times. We found ACE2+ exosomes were induced by SARS-CoV-2 infection and activation of viral sensors in cell culture, which required the autophagy protein ATG16L1, defining these as defensosomes. We further demonstrate that ACE2+ defensosomes directly bind and block viral entry. These findings suggest that defensosomes may contribute to the antiviral response against SARS-CoV-2 and expand our knowledge on the regulation and effects of extracellular vesicles during infection.

Autophagy proteins mediate the production of extracellular vesicles termed defensosomes in response to innate immune ligands. This study reveals that ACE2-containing defensosomes bind and inhibit SARS-CoV-2 infection, and are associated with reduced length of hospital stay for patients with COVID-19.

Cryo-electron Tomography Remote Data Collection and Subtomogram Averaging

Cryo-electron tomography (cryo-ET) has been gaining momentum in recent years, especially since the introduction of direct electron detectors, improved automated acquisition strategies, preparative techniques that expand the possibilities of what the electron microscope can image at high-resolution using cryo-ET and new subtomogram averaging software. Additionally, data acquisition has become increasingly streamlined, making it more accessible to many users. The SARS-CoV-2 pandemic has further accelerated remote cryo-electron microscopy (cryo-EM) data collection, especially for single-particle cryo-EM, in many facilities globally, providing uninterrupted user access to state-of-the-art instruments during the pandemic. With the recent advances in Tomo5 (software for 3D electron tomography), remote cryo-ET data collection has become robust and easy to handle from anywhere in the world. This article aims to provide a detailed walk-through, starting from the data collection setup in the tomography software for the process of a (remote) cryo-ET data collection session with detailed troubleshooting. The (remote) data collection protocol is further complemented with the workflow for structure determination at near-atomic resolution by subtomogram averaging with emClarity, using apoferritin as an example.

Data-driven determination of number of discrete conformations in single-particle cryo-EM

BACKGROUND AND OBJECTIVE

One of the strengths of single-particle cryo-EM compared to other structural determination techniques is its ability to image heterogeneous samples containing multiple molecular species, different oligomeric states or distinct conformations. This is achieved using routines for in-silico 3D classification that are now well established in the field and have successfully been used to characterize the structural heterogeneity of important biomolecules. These techniques, however, rely on expert-user knowledge and trial-and-error experimentation to determine the correct number of conformations, making it a labor intensive, subjective, and difficult to reproduce procedure.

METHODS

We propose an approach to address the problem of automatically determining the number of discrete conformations present in heterogeneous single-particle cryo-EM datasets. We do this by systematically evaluating all possible partitions of the data and selecting the result that maximizes the average variance of similarities measured between particle images and the corresponding 3D reconstructions.

RESULTS

Using this strategy, we successfully analyzed datasets of heterogeneous protein complexes, including: 1) in-silico mixtures obtained by combining closely related antibody-bound HIV-1 Env trimers and other important membrane channels, and 2) naturally occurring mixtures from diverse and dynamic protein complexes representing varying degrees of structural heterogeneity and conformational plasticity.

CONCLUSIONS

The availability of unsupervised strategies for 3D classification combined with existing approaches for fully automatic pre-processing and 3D refinement, represents an important step towards converting single-particle cryo-EM into a high-throughput technique.

A feature-guided, focused 3D signal permutation method for subtomogram averaging

Advances in electron microscope instrumentation, cryo-electron tomography data collection, and subtomogram averaging have allowed for the in-situ visualization of molecules and their complexes in their native environment. Current data processing pipelines commonly extract subtomograms as a cubic subvolume with the key assumption that the selected object of interest is discrete from its surroundings. However, in instances when the object is in its native environment, surrounding densities may negatively affect the subsequent alignment and refinement processes, leading to loss of information due to misalignment. For example, the strong densities from surrounding membranes may dominate the alignment process for membrane proteins. Here, we developed methods for feature-guided subtomogram alignment and 3D signal permutation for subtomogram averaging. Our 3D signal permutation method randomizes and filters voxels outside a mask of any shape and blurs the boundary of the mask that encapsulates the object of interest. The randomization preserves global statistical properties such as mean density and standard deviation of voxel density values, effectively producing a featureless background surrounding the object of interest. This signal permutation process can be repeatedly applied with intervening alignments of the 3D signal-permuted subvolumes, recentering of the mask, and optional adjustments of the shape of the mask. We have implemented these methods in a new processing pipeline which starts from tomograms, contains feature-guided subtomogram extraction and alignment, 3D signal-permutation, and subtomogram visualization tools. As an example, feature-guided alignment and 3D signal permutation leads to improved subtomogram average maps for a dataset of synaptic protein complexes in their native environment.

High-resolution in situ structure determination by cryo-electron tomography and subtomogram averaging using emClarity

Cryo-electron tomography and subtomogram averaging (STA) has developed rapidly in recent years. It provides structures of macromolecular complexes in situ and in cellular context at or below subnanometer resolution and has led to unprecedented insights into the inner working of molecular machines in their native environment, as well as their functional relevant conformations and spatial distribution within biological cells or tissues. Given the tremendous potential of cryo-electron tomography STA in in situ structural cell biology, we previously developed emClarity, a graphics processing unit-accelerated image-processing software that offers STA and classification of macromolecular complexes at high resolution. However, the workflow remains challenging, especially for newcomers to the field. In this protocol, we describe a detailed workflow, processing and parameters associated with each step, from initial tomography tilt-series data to the final 3D density map, with several features unique to emClarity. We use four different samples, including human immunodeficiency virus type 1 Gag assemblies, ribosome and apoferritin, to illustrate the procedure and results of STA and classification. Following the processing steps described in this protocol, along with a comprehensive tutorial and guidelines for troubleshooting and parameter optimization, one can obtain density maps up to 2.8 Å resolution from six tilt series by cryo-electron tomography STA.

Cryo-EM structures of GroEL:ES2 with RuBisCO visualize molecular contacts of encapsulated substrates in a double-cage chaperonin

The GroEL/GroES chaperonin system assists the folding of many proteins, through conformational transitions driven by ATP hydrolysis. Although structural information about bullet-shaped GroEL:ES₁ complexes has been extensively reported, the substrate interactions of another functional complex, the football-shaped GroEL:ES₂, remain elusive. Here, we report single-particle cryo-EM structures of reconstituted wild-type GroEL:ES₂ complexes with a chemically denatured substrate, ribulose-1,5-bisphosphate carboxylase oxygenase (RuBisCO). Our structures demonstrate that native-like folded RuBisCO density is captured at the lower part of the GroEL chamber and that GroEL's bulky hydrophobic residues Phe281, Tyr360, and Phe44 contribute to direct contact with RuBisCO density. In addition, our analysis found that GroEL:ES₂ can be occupied by two substrates simultaneously, one in each chamber. Together, these observations provide insights to the football-shaped GroEL:ES₂ complex as a functional state to assist the substrate folding with visualization.

Compressed sensing for electron cryotomography and high-resolution subtomogram averaging of biological specimens

Cryoelectron tomography (cryo-ET) and subtomogram averaging (STA) allow direct visualization and structural studies of biological macromolecules in their native cellular environment, in situ. Often, low signal-to-noise ratios in tomograms, low particle abundance within the cell, and low throughput in typical cryo-ET workflows severely limit the obtainable structural information. To help mitigate these limitations, here we apply a compressed sensing approach using 3D second-order total variation (CS-TV²) to tomographic reconstruction. We show that CS-TV² increases the signal-to-noise ratio in tomograms, enhancing direct visualization of macromolecules, while preserving high-resolution information up to the secondary structure level. We show that, particularly with small datasets, CS-TV² allows improvement of the resolution of STA maps. We further demonstrate that the CS-TV² algorithm is applicable to cellular specimens, leading to increased visibility of molecular detail within tomograms. This work highlights the potential of compressed sensing-based reconstruction algorithms for cryo-ET and in situ structural biology.

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Compressed sensing (CS-TV²) for cryo-ET using 3D second-order total variation

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CS-TV² increases signal contrast while retaining high-resolution information

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Improved subtomogram averaging from CS-TV² reconstructions of small datasets

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Increased contrast and detail in CS-TV² reconstructions of cellular specimens

ACE2-containing defensosomes serve as decoys to inhibit SARS-CoV-2 infection

Extracellular vesicles of endosomal origin, exosomes, mediate intercellular communication by transporting substrates with a variety of functions related to tissue homeostasis and disease. Their diagnostic and therapeutic potential has been recognized for diseases such as cancer in which signaling defects are prominent. However, it is unclear to what extent exosomes and their cargo inform the progression of infectious diseases. We recently defined a subset of exosomes termed defensosomes that are mobilized during bacterial infection in a manner dependent on autophagy proteins. Through incorporating protein receptors on their surface, defensosomes mediated host defense by binding and inhibiting pore-forming toxins secreted by bacterial pathogens. Given this capacity to serve as decoys that interfere with surface protein interactions, we investigated the role of defensosomes during infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of COVID-19. Consistent with a protective function, exosomes containing high levels of the viral receptor ACE2 in bronchioalveolar lavage fluid from critically ill COVID-19 patients was associated with reduced ICU and hospitalization times. We found ACE2+ exosomes were induced by SARS-CoV-2 infection and activation of viral sensors in cell culture, which required the autophagy protein ATG16L1, defining these as defensosomes. We further demonstrate that ACE2+ defensosomes directly bind and block viral entry. These findings suggest that defensosomes may contribute to the antiviral response against SARS-CoV-2 and expand our knowledge on the regulation and effects of extracellular vesicles during infection.

Perspective: Emerging strategies for determining atomic-resolution structures of macromolecular complexes within cells

In principle, electron cryo-tomography (cryo-ET) of thin portions of cells provides high-resolution images of the three-dimensional spatial arrangement of all members of the proteome. In practice, however, radiation damage creates a tension between recording images at many different tilt angles, but at correspondingly reduced exposure levels, versus limiting the number of tilt angles in order to improve the signal-to-noise ratio (SNR). Either way, it is challenging to read the available information out at the level of atomic structure. Here, we first review work that explores the optimal strategy for data collection, which currently seems to favor the use of a limited angular range for tilting the sample or even the use of a single image to record the high-resolution information. Looking then to the future, we point to the alternative of so-called “deconvolution microscopy”, which may be applied to tilt-series or optically-sectioned, focal series data. Recording data as a focal series has the advantage that little or no translational alignment of frames might be needed, and a three-dimensional reconstruction might require only 2/3 the number of images as does standard tomography. We also point to the unexploited potential of phase plates to increase the contrast, and thus to reduce the electron exposure levels while retaining the ability align and merge the data. In turn, using much lower exposures per image could have the advantage that high-resolution information is retained throughout the full data-set, whether recorded as a tilt series or a focal series of images.

Weakly Supervised 3D Semantic Segmentation Using Cross-Image Consensus and Inter-Voxel Affinity Relations

We propose a novel weakly supervised approach for 3D semantic segmentation on volumetric images. Unlike most existing methods that require voxel-wise densely labeled training data, our weakly-supervised CIVA-Net is the first model that only needs image-level class labels as guidance to learn accurate volumetric segmentation. Our model learns from cross-image co-occurrence for integral region generation, and explores inter-voxel affinity relations to predict segmentation with accurate boundaries. We empirically validate our model on both simulated and real cryo-ET datasets. Our experiments show that CIVA-Net achieves comparable performance to the state-of-the-art models trained with stronger supervision.

Towards Visual Proteomics at High Resolution

Traditionally, structural biologists approach the complexity of cellular proteomes in a reductionist manner. Proteomes are fractionated, their molecular components purified and studied one-by-one using the experimental methods for structure determination at their disposal. Visual proteomics aims at obtaining a holistic picture of cellular proteomes by studying them in situ, ideally in unperturbed cellular environments. The method that enables doing this at highest resolution is cryo-electron tomography. It allows to visualize cellular landscapes with molecular resolution generating maps or atlases revealing the interaction networks which underlie cellular functions in health and in disease states. Current implementations of cryo ET do not yet realize the full potential of the method in terms of resolution and interpretability. To this end, further improvements in technology and methodology are needed. This review describes the state of the art as well as measures which we expect will help overcoming current limitations.

Cryo-electron tomography provides topological insights into mutant huntingtin exon 1 and polyQ aggregates

Huntington disease (HD) is a neurodegenerative trinucleotide repeat disorder caused by an expanded poly-glutamine (polyQ) tract in the mutant huntingtin (mHTT) protein. The formation and topology of filamentous mHTT inclusions in the brain (hallmarks of HD implicated in neurotoxicity) remain elusive. Using cryo-electron tomography and subtomogram averaging, here we show that mHTT exon 1 and polyQ-only aggregates in vitro are structurally heterogenous and filamentous, similar to prior observations with other methods. Yet, we find filaments in both types of aggregates under ~2 nm in width, thinner than previously reported, and regions forming large sheets. In addition, our data show a prevalent subpopulation of filaments exhibiting a lumpy slab morphology in both aggregates, supportive of the polyQ core model. This provides a basis for future cryoET studies of various aggregated mHTT and polyQ constructs to improve their structure-based modeling as well as their identification in cells without fusion tags.

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).

Multivalent nanoparticle-based vaccines protect hamsters against SARS-CoV-2 after a single immunization

The COVID-19 pandemic continues to wreak havoc as worldwide SARS-CoV-2 infection, hospitalization, and death rates climb unabated. Effective vaccines remain the most promising approach to counter SARS-CoV-2. Yet, while promising results are emerging from COVID-19 vaccine trials, the need for multiple doses and the challenges associated with the widespread distribution and administration of vaccines remain concerns. Here, we engineered the coat protein of the MS2 bacteriophage and generated nanoparticles displaying multiple copies of the SARS-CoV-2 spike (S) protein. The use of these nanoparticles as vaccines generated high neutralizing antibody titers and protected Syrian hamsters from a challenge with SARS-CoV-2 after a single immunization with no infectious virus detected in the lungs. This nanoparticle-based vaccine platform thus provides protection after a single immunization and may be broadly applicable for protecting against SARS-CoV-2 and future pathogens with pandemic potential.

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.

Cryogenic Super-Resolution Fluorescence and Electron Microscopy Correlated at the Nanoscale

We review the emerging method of super-resolved cryogenic correlative light and electron microscopy (srCryoCLEM). Super-resolution (SR) fluorescence microscopy and cryogenic electron tomography (CET) are both powerful techniques for observing subcellular organization, but each approach has unique limitations. The combination of the two brings the single-molecule sensitivity and specificity of SR to the detailed cellular context and molecular scale resolution of CET. The resulting correlative data is more informative than the sum of its parts. The correlative images can be used to pinpoint the positions of fluorescently labeled proteins in the high-resolution context of CET with nanometer-scale precision and/or to identify proteins in electron-dense structures. The execution of srCryoCLEM is challenging and the approach is best described as a method that is still in its infancy with numerous technical challenges. In this review, we describe state-of-the-art srCryoCLEM experiments, discuss the most pressing challenges, and give a brief outlook on future applications.

Tools for visualizing and analyzing Fourier space sampling in Cryo-EM

A complete understanding of how an orientation distribution contributes to a cryo-EM reconstruction remains lacking. It is necessary to begin critically assessing the set of views to gain an understanding of its effect on experimental reconstructions. Toward that end, we recently suggested that the type of orientation distribution may alter resolution measures in a systematic manner. We introduced the sampling compensation factor (SCF), which incorporates how the collection geometry might change the spectral signal-to-noise ratio (SSNR), irrespective of the other experimental aspects. We show here that knowledge of the sampling restricted to spherical surfaces of sufficiently large radii in Fourier space is equivalent to knowledge of the set of projection views. Moreover, the SCF geometrical factor may be calculated from one such surface. To aid cryo-EM practitioners, we developed a graphical user interface (GUI) tool that evaluates experimental orientation distributions. The GUI returns plots of projection directions, sampling constrained to the surface of a sphere, the SCF value, the fraction of the empty region of Fourier space, and a histogram of the sampling values over the points on a sphere. Finally, a fixed tilt angle may be incorporated to determine how tilting the grid during collection may improve the distribution of views and Fourier space sampling. We advocate this simple conception of sampling and the use of such tools as a complement to the distribution of views to capture the different aspects of the effect of projection directions on cryo-EM reconstructions.

Ordered Clusters of the Complete Oxidative Phosphorylation System in Cardiac Mitochondria

The existence of a complete oxidative phosphorylation system (OXPHOS) supercomplex including both electron transport system and ATP synthases has long been assumed based on functional evidence. However, no structural confirmation of the docking between ATP synthase and proton pumps has been obtained. In this study, cryo-electron tomography was used to reveal the supramolecular architecture of the rat heart mitochondria cristae during ATP synthesis. Respirasome and ATP synthase structure in situ were determined using subtomogram averaging. The obtained reconstructions of the inner mitochondrial membrane demonstrated that rows of respiratory chain supercomplexes can dock with rows of ATP synthases forming oligomeric ordered clusters. These ordered clusters indicate a new type of OXPHOS structural organization. It should ensure the quickness, efficiency, and damage resistance of OXPHOS, providing a direct proton transfer from pumps to ATP synthase along the lateral pH gradient without energy dissipation.

Functional refolding of the penetration protein on a non-enveloped virus

A non-enveloped virus requires a membrane lesion to deliver its genome into a target cell¹. For rotaviruses, membrane perforation is a principal function of the viral outer-layer protein, VP4^2,3. Here we describe the use of electron cryomicroscopy to determine how VP4 performs this function and show that when activated by cleavage to VP8* and VP5*, VP4 can rearrange on the virion surface from an 'upright' to a 'reversed' conformation. The reversed structure projects a previously buried 'foot' domain outwards into the membrane of the host cell to which the virion has attached. Electron cryotomograms of virus particles entering cells are consistent with this picture. Using a disulfide mutant of VP4, we have also stabilized a probable intermediate in the transition between the two conformations. Our results define molecular mechanisms for the first steps of the penetration of rotaviruses into the membranes of target cells and suggest similarities with mechanisms postulated for other viruses.

In Situ Imaging and Structure Determination of Biomolecular Complexes Using Electron Cryo-Tomography

Electron cryo-tomography (cryo-ET) is a technique that allows the investigation of intact macromolecular complexes while they are in their cellular milieu. Over the years, cryo-ET has had a huge impact on our understanding of how large biomolecular complexes look like, how they assemble, disassemble, function, and evolve(d). Recent hardware and software developments and combining cryo-ET with other techniques, e.g., focused ion beam milling (FIB-milling) and cryo-light microscopy, has extended the realm of cryo-ET to include transient molecular complexes embedded deep in thick samples (like eukaryotic cells) and enhanced the resolution of structures obtained by cryo-ET. In this chapter, we will present an outline of how to perform cryo-ET studies on a wide variety of biological samples including prokaryotic and eukaryotic cells and biological plant tissues. This outline will include sample preparation, data collection, and data processing as well as hybrid approaches like FIB-milling, cryosectioning, and cryo-correlated light and electron microscopy (cryo-CLEM).

Structures and distributions of SARS-CoV-2 spike proteins on intact virions

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virions are surrounded by a lipid bilayer from which spike (S) protein trimers protrude1. Heavily glycosylated S trimers bind to the angiotensin-converting enzyme 2 receptor and mediate entry of virions into target cells2-6. S exhibits extensive conformational flexibility: it modulates exposure of its receptor-binding site and subsequently undergoes complete structural rearrangement to drive fusion of viral and cellular membranes2,7,8. The structures and conformations of soluble, overexpressed, purified S proteins have been studied in detail using cryo-electron microscopy2,7,9-12, but the structure and distribution of S on the virion surface remain unknown. Here we applied cryo-electron microscopy and tomography to image intact SARS-CoV-2 virions and determine the high-resolution structure, conformational flexibility and distribution of S trimers in situ on the virion surface. These results reveal the conformations of S on the virion, and provide a basis from which to understand interactions between S and neutralizing antibodies during infection or vaccination.

The promise and the challenges of cryo-electron tomography

Structural biologists have traditionally approached cellular complexity in a reductionist manner in which the cellular molecular components are fractionated and purified before being studied individually. This 'divide and conquer' approach has been highly successful. However, awareness has grown in recent years that biological functions can rarely be attributed to individual macromolecules. Most cellular functions arise from their concerted action, and there is thus a need for methods enabling structural studies performed in situ, ideally in unperturbed cellular environments. Cryo-electron tomography (Cryo-ET) combines the power of 3D molecular-level imaging with the best structural preservation that is physically possible to achieve. Thus, it has a unique potential to reveal the supramolecular architecture or 'molecular sociology' of cells and to discover the unexpected. Here, we review state-of-the-art Cryo-ET workflows, provide examples of biological applications, and discuss what is needed to realize the full potential of Cryo-ET.

Gum-Net: Unsupervised Geometric Matching for Fast and Accurate 3D Subtomogram Image Alignment and Averaging

We propose a Geometric unsupervised matching Network (Gum-Net) for finding the geometric correspondence between two images with application to 3D subtomogram alignment and averaging. Subtomogram alignment is the most important task in cryo-electron tomography (cryo-ET), a revolutionary 3D imaging technique for visualizing the molecular organization of unperturbed cellular landscapes in single cells. However, subtomogram alignment and averaging are very challenging due to severe imaging limits such as noise and missing wedge effects. We introduce an end-to-end trainable architecture with three novel modules specifically designed for preserving feature spatial information and propagating feature matching information. The training is performed in a fully unsupervised fashion to optimize a matching metric. No ground truth transformation information nor category-level or instance-level matching supervision information is needed. After systematic assessments on six real and nine simulated datasets, we demonstrate that Gum-Net reduced the alignment error by 40 to 50% and improved the averaging resolution by 10%. Gum-Net also achieved 70 to 110 times speedup in practice with GPU acceleration compared to state-of-the-art subtomogram alignment methods. Our work is the first 3D unsupervised geometric matching method for images of strong transformation variation and high noise level. The training code, trained model, and datasets are available in our open-source software AITom.

Unravelling the Stability and Capsid Dynamics of the Three Virions of Brome Mosaic Virus Assembled Autonomously In Vivo

Viral capsids are dynamic assemblies that undergo controlled conformational transitions to perform various biological functions. The replication-derived four-molecule RNA progeny of Brome mosaic virus (BMV) is packaged by a single capsid protein (CP) into three types of morphologically indistinguishable icosahedral virions with T=3 quasisymmetry. Type 1 (B1^V) and type 2 (B2^V) virions package genomic RNA1 and RNA2, respectively, while type 3 (B3+4^V) virions copackage genomic RNA3 (B3) and its subgenomic RNA4 (sgB4). In this study, the application of a robust Agrobacterium-mediated transient expression system allowed us to assemble each virion type separately in planta Experimental approaches analyzing the morphology, size, and electrophoretic mobility failed to distinguish between the virion types. Thermal denaturation analysis and protease-based peptide mass mapping experiments were used to analyze stability and the conformational dynamics of the individual virions, respectively. The crystallographic structure of the BMV capsid shows four trypsin cleavage sites (K⁶⁵, R¹⁰³, K¹¹¹, and K¹⁶⁵ on the CP subunits) exposed on the exterior of the capsid. Irrespective of the digestion time, while retaining their capsid structural integrity, B1^V and B2^V released a single peptide encompassing amino acids 2 to 8 of the N-proximal arginine-rich RNA binding motif. In contrast, B3+4^V capsids were unstable with trypsin, releasing several peptides in addition to the peptides encompassing four predicted sites exposed on the capsid exterior. These results, demonstrating qualitatively different dynamics for the three types of BMV virions, suggest that the different RNA genes they contain may have different translational timing and efficiency and may even impart different structures to their capsids.IMPORTANCE The majority of viruses contain RNA genomes protected by a shell of capsid proteins. Although crystallographic studies show that viral capsids are static structures, accumulating evidence suggests that, in solution, virions are highly dynamic assemblies. The three genomic RNAs (RNA1, -2, and -3) and a single subgenomic RNA (RNA4) of Brome mosaic virus (BMV), an RNA virus pathogenic to plants, are distributed among three physically homogeneous virions. This study examines the thermal stability by differential scanning fluorimetry (DSF) and capsid dynamics by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) analyses following trypsin digestion of the three virions assembled separately in vivo using the Agrobacterium-mediated transient expression approach. The results provide compelling evidence that virions packaging genomic RNA1 and -2 are distinct from those copackaging RNA3 and -4 in their stability and dynamics, suggesting that RNA-dependent capsid dynamics play an important biological role in the viral life cycle.

Investigating eukaryotic cells with cryo-ET

The interior of eukaryotic cells is mysterious. How do the large communities of macromolecular machines interact with each other? How do the structures and positions of these nanoscopic entities respond to new stimuli? Questions like these can now be answered with the help of a method called electron cryotomography (cryo-ET). Cryo-ET will ultimately reveal the inner workings of a cell at the protein, secondary structure, and perhaps even side-chain levels. Combined with genetic or pharmacological perturbation, cryo-ET will allow us to answer previously unimaginable questions, such as how structure, biochemistry, and forces are related in situ. Because it bridges structural biology and cell biology, cryo-ET is indispensable for structural cell biology-the study of the 3-D macromolecular structure of cells. Here we discuss some of the key ideas, strategies, auxiliary techniques, and innovations that an aspiring structural cell biologist will consider when planning to ask bold questions.