Resolving macromolecular structures from electron cryo-tomography data using subtomogram averaging in RELION

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.

Characterization of the rotavirus assembly pathway in situ using cryoelectron tomography

Rotavirus assembly is a complex process that involves the stepwise acquisition of protein layers in distinct intracellular locations to form the fully assembled particle. Understanding and visualization of the assembly process has been hampered by the inaccessibility of unstable intermediates. We characterize the assembly pathway of group A rotaviruses observed in situ within cryo-preserved infected cells through the use of cryoelectron tomography of cellular lamellae. Our findings demonstrate that the viral polymerase VP1 recruits viral genomes during particle assembly, as revealed by infecting with a conditionally lethal mutant. Additionally, pharmacological inhibition to arrest the transiently enveloped stage uncovered a unique conformation of the VP4 spike. Subtomogram averaging provided atomic models of four intermediate states, including a pre-packaging single-layered intermediate, the double-layered particle, the transiently enveloped double-layered particle, and the fully assembled triple-layered virus particle. In summary, these complementary approaches enable us to elucidate the discrete steps involved in forming an intracellular rotavirus particle.

Cryo-electron tomography on focused ion beam lamellae transforms structural cell biology

Cryogenic electron microscopy and data processing enable the determination of structures of isolated macromolecules to near-atomic resolution. However, these data do not provide structural information in the cellular environment where macromolecules perform their native functions, and vital molecular interactions can be lost during the isolation process. Cryogenic focused ion beam (FIB) fabrication generates thin lamellae of cellular samples and tissues, enabling structural studies on the near-native cellular interior and its surroundings by cryogenic electron tomography (cryo-ET). Cellular cryo-ET benefits from the technological developments in electron microscopes, detectors and data processing, and more in situ structures are being obtained and at increasingly higher resolution. In this Review, we discuss recent studies employing cryo-ET on FIB-generated lamellae and the technological developments in ultrarapid sample freezing, FIB fabrication of lamellae, tomography, data processing and correlative light and electron microscopy that have enabled these studies. Finally, we explore the future of cryo-ET in terms of both methods development and biological application.

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.

In situ cryo-electron tomography reveals the asymmetric architecture of mammalian sperm axonemes

The flagella of mammalian sperm display non-planar, asymmetric beating, in contrast to the planar, symmetric beating of flagella from sea urchin sperm and unicellular organisms. The molecular basis of this difference is unclear. Here, we perform in situ cryo-electron tomography of mouse and human sperm, providing the highest-resolution structural information to date. Our subtomogram averages reveal mammalian sperm-specific protein complexes within the microtubules, the radial spokes and nexin-dynein regulatory complexes. The locations and structures of these complexes suggest potential roles in enhancing the mechanical strength of mammalian sperm axonemes and regulating dynein-based axonemal bending. Intriguingly, we find that each of the nine outer microtubule doublets is decorated with a distinct combination of sperm-specific complexes. We propose that this asymmetric distribution of proteins differentially regulates the sliding of each microtubule doublet and may underlie the asymmetric beating of mammalian sperm.

Multishot tomography for high-resolution in situ subtomogram averaging

Cryo-electron tomography (cryo-ET) and subtomogram averaging (STA) can resolve protein complexes at near atomic resolution, and when combined with focused ion beam (FIB) milling, macromolecules can be observed within their native context. Unlike single particle acquisition (SPA), cryo-ET can be slow, which may reduce overall project throughput. We here propose a fast, multi-position tomographic acquisition scheme based on beam-tilt corrected beam-shift imaging along the tilt axis, which yields sub-nanometer in situ STA averages.

Plasma FIB milling for the determination of structures in situ

Structural biology studies inside cells and tissues require methods to thin vitrified specimens to electron transparency. Until now, focused ion beams based on gallium have been used. However, ion implantation, changes to surface chemistry and an inability to access high currents limit gallium application. Here, we show that plasma-coupled ion sources can produce cryogenic lamellae of vitrified human cells in a robust and automated manner, with quality sufficient for pseudo-atomic structure determination. Lamellae were produced in a prototype microscope equipped for long cryogenic run times (> 1 week) and with multi-specimen support fully compatible with modern-day transmission electron microscopes. We demonstrate that plasma ion sources can be used for structural biology within cells, determining a structure in situ to 4.9 Å, and characterise the resolution dependence on particle distance from the lamella edge. We describe a workflow upon which different plasmas can be examined to further streamline lamella fabrication.

In Situ Structure Determination of Bacterial Surface Nanomachines Using Cryo-Electron Tomography

Bacterial surface nanomachines are often refractory to structural determination in their intact form due to their extensive association with the cell envelope preventing them from being properly purified for traditional structural biology methods. Cryo-electron tomography (cryo-ET) is an emerging branch of cryo-electron microscopy that can visualize supramolecular complexes directly inside frozen-hydrated cells in 3D at nanometer resolution, therefore posing a unique capability to study the intact structures of bacterial surface nanomachines in situ and reveal their molecular association with other cellular components. Furthermore, the resolution of cryo-ET is continually improving alongside methodological advancement. Here, using the type IV pilus machine in Myxococcus xanthus as an example, we describe a step-by-step workflow for in situ structure determination including sample preparation and screening, microscope and camera tuning, tilt series acquisition, data processing and tomogram reconstruction, subtomogram averaging, and structural analysis.

Integrated multimodality microscope for accurate and efficient target-guided cryo-lamellae preparation

Cryo-electron tomography (cryo-ET) is a revolutionary technique for resolving the structure of subcellular organelles and macromolecular complexes in their cellular context. However, the application of the cryo-ET is hampered by the sample preparation step. Performing cryo-focused ion beam milling at an arbitrary position on the sample is inefficient, and the target of interest is not guaranteed to be preserved when thinning the cell from several micrometers to less than 300 nm thick. Here, we report a cryogenic correlated light, ion and electron microscopy (cryo-CLIEM) technique that is capable of preparing cryo-lamellae under the guidance of three-dimensional confocal imaging. Moreover, we demonstrate a workflow to preselect and preserve nanoscale target regions inside the finished cryo-lamellae. By successfully preparing cryo-lamellae that contain a single centriole or contact sites between subcellular organelles, we show that this approach is generally applicable, and shall help in innovating more applications of cryo-ET.

Advanced imaging techniques: Microscopy

For decades, bacteria were thought of as "bags" of enzymes, lacking organelles and significant subcellular structures. This stood in sharp contrast with eukaryotes, where intracellular compartmentalization and the role of large-scale order had been known for a long time. However, the emerging field of Bacterial Cell Biology has established that bacteria are in fact highly organized, with most macromolecular components having specific subcellular locations that can change depending on the cell's physiological state (Barry & Gitai, 2011; Lenz & Søgaard-Andersen, 2011; Thanbichler & Shapiro, 2008). For example, we now know that many processes in bacteria are orchestrated by cytoskeletal proteins, which polymerize into surprisingly diverse superstructures, such as rings, sheets, and tread-milling rods (Pilhofer & Jensen, 2013). These superstructures connect individual proteins, macromolecular assemblies, and even two neighboring cells, to affect essential higher-order processes including cell division, DNA segregation, and motility. Understanding these processes requires resolving the in vivo dynamics and ultrastructure at different functional stages of the cell, at macromolecular resolution and in 3-dimensions (3D). Fluorescence light microscopy (fLM) of tagged proteins is highly valuable for investigating protein localization and dynamics, and the resolution power of transmission electron microscopy (TEM) is required to elucidate the structure of macromolecular complexes in vivo and in vitro. This chapter summarizes the most recent advances in LM and TEM approaches that have revolutionized our knowledge and understanding of the microbial world.

Structural investigation of eukaryotic cells: From the periphery to the interior by cryo-electron tomography

Cryo-electron tomography (cryo-ET) combines a close-to-life preservation of the cell with high-resolution three-dimensional (3D) imaging. This allows to study the molecular architecture of the cellular landscape and provides unprecedented views on biological processes and structures. In this review we mainly focus on the application of cryo-ET to visualize and structurally characterize eukaryotic cells - from the periphery to the cellular interior. We discuss strategies that can be employed to investigate the structure of challenging targets in their cellular environment as well as the application of complimentary approaches in conjunction with cryo-ET.

Convolutional networks for supervised mining of molecular patterns within cellular context

Cryo-electron tomograms capture a wealth of structural information on the molecular constituents of cells and tissues. We present DeePiCt (deep picker in context), an open-source deep-learning framework for supervised segmentation and macromolecular complex localization in cryo-electron tomography. To train and benchmark DeePiCt on experimental data, we comprehensively annotated 20 tomograms of Schizosaccharomyces pombe for ribosomes, fatty acid synthases, membranes, nuclear pore complexes, organelles, and cytosol. By comparing DeePiCt to state-of-the-art approaches on this dataset, we show its unique ability to identify low-abundance and low-density complexes. We use DeePiCt to study compositionally distinct subpopulations of cellular ribosomes, with emphasis on their contextual association with mitochondria and the endoplasmic reticulum. Finally, applying pre-trained networks to a HeLa cell tomogram demonstrates that DeePiCt achieves high-quality predictions in unseen datasets from different biological species in a matter of minutes. The comprehensively annotated experimental data and pre-trained networks are provided for immediate use by the community.

Polyribosomes of circular topology are prevalent in mammalian cells

Polyribosomes, the groups of ribosomes simultaneously translating a single mRNA molecule, are very common in both, prokaryotic and eukaryotic cells. Even in early EM studies, polyribosomes have been shown to possess various spatial conformations, including a ring-shaped configuration which was considered to be functionally important. However, a recent in situ cryo-ET analysis of predominant regular inter-ribosome contacts did not confirm the abundance of ring-shaped polyribosomes in a cell cytoplasm. To address this discrepancy, here we analyzed the cryo-ET structure of polyribosomes in diluted lysates of HeLa cells. It was shown that the vast majority of the ribosomes were combined into polysomes and were proven to be translationally active. Tomogram analysis revealed that circular polyribosomes are indeed very common in the cytoplasm, but they mostly possess pseudo-regular structures without specific inter-ribosomal contacts. Although the size of polyribosomes varied widely, most circular polysomes were relatively small in size (4-8 ribosomes). Our results confirm the recent data that it is cellular mRNAs with short ORF that most commonly form circular structures providing an enhancement of translation.

Direct observation of the conformational states of formin mDia1 at actin filament barbed ends and along the filament

The fine regulation of actin polymerization is essential to control cell motility and architecture and to perform essential cellular functions. Formins are key regulators of actin filament assembly, known to processively elongate filament barbed ends and increase their polymerization rate. Different models have been extrapolated to describe the molecular mechanism governing the processive motion of formin FH2 domains at polymerizing barbed ends. Using negative stain electron microscopy, we directly identified for the first time two conformations of the mDia1 formin FH2 domains in interaction with the barbed ends of actin filaments. These conformations agree with the speculated open and closed conformations of the "stair-stepping" model. We observed the FH2 dimers to be in the open conformation for 79% of the data, interacting with the two terminal actin subunits of the barbed end while they interact with three actin subunits in the closed conformation. In addition, we identified and characterized the structure of single FH2 dimers encircling the core of actin filaments, and reveal their ability to spontaneously depart from barbed ends.

Isotropic reconstruction for electron tomography with deep learning

Cryogenic electron tomography (cryoET) allows visualization of cellular structures in situ. However, anisotropic resolution arising from the intrinsic "missing-wedge" problem has presented major challenges in visualization and interpretation of tomograms. Here, we have developed IsoNet, a deep learning-based software package that iteratively reconstructs the missing-wedge information and increases signal-to-noise ratio, using the knowledge learned from raw tomograms. Without the need for sub-tomogram averaging, IsoNet generates tomograms with significantly reduced resolution anisotropy. Applications of IsoNet to three representative types of cryoET data demonstrate greatly improved structural interpretability: resolving lattice defects in immature HIV particles, establishing architecture of the paraflagellar rod in Eukaryotic flagella, and identifying heptagon-containing clathrin cages inside a neuronal synapse of cultured cells. Therefore, by overcoming two fundamental limitations of cryoET, IsoNet enables functional interpretation of cellular tomograms without sub-tomogram averaging. Its application to high-resolution cellular tomograms should also help identify differently oriented complexes of the same kind for sub-tomogram averaging.

Visualizing translation dynamics at atomic detail inside a bacterial cell

Translation is the fundamental process of protein synthesis and is catalysed by the ribosome in all living cells1. Here we use advances in cryo-electron tomography and sub-tomogram analysis2,3 to visualize the structural dynamics of translation inside the bacterium Mycoplasma pneumoniae. To interpret the functional states in detail, we first obtain a high-resolution in-cell average map of all translating ribosomes and build an atomic model for the M. pneumoniae ribosome that reveals distinct extensions of ribosomal proteins. Classification then resolves 13 ribosome states that differ in their conformation and composition. These recapitulate major states that were previously resolved in vitro, and reflect intermediates during active translation. On the basis of these states, we animate translation elongation inside native cells and show how antibiotics reshape the cellular translation landscapes. During translation elongation, ribosomes often assemble in defined three-dimensional arrangements to form polysomes4. By mapping the intracellular organization of translating ribosomes, we show that their association into polysomes involves a local coordination mechanism that is mediated by the ribosomal protein L9. We propose that an extended conformation of L9 within polysomes mitigates collisions to facilitate translation fidelity. Our work thus demonstrates the feasibility of visualizing molecular processes at atomic detail inside cells.

A transformation clustering algorithm and its application in polyribosomes structural profiling

Improvements in cryo-electron tomography sample preparation, electron-microscopy instrumentations, and image processing algorithms have advanced the structural analysis of macromolecules in situ. Beyond such analyses of individual macromolecules, the study of their interactions with functionally related neighbors in crowded cellular habitats, i.e. 'molecular sociology', is of fundamental importance in biology. Here we present a NEighboring Molecule TOpology Clustering (NEMO-TOC) algorithm. We optimized this algorithm for the detection and profiling of polyribosomes, which play both constitutive and regulatory roles in gene expression. Our results suggest a model where polysomes are formed by connecting multiple nonstochastic blocks, in which translation is likely synchronized.

MemBrain: A deep learning-aided pipeline for detection of membrane proteins in Cryo-electron tomograms

BACKGROUND AND OBJECTIVE

Cryo-electron tomography (cryo-ET) is an imaging technique that enables 3D visualization of the native cellular environment at sub-nanometer resolution, providing unpreceded insights into the molecular organization of cells. However, cryo-electron tomograms suffer from low signal-to-noise ratios and anisotropic resolution, which makes subsequent image analysis challenging. In particular, the efficient detection of membrane-embedded proteins is a problem still lacking satisfactory solutions.

METHODS

We present MemBrain - a new deep learning-aided pipeline that automatically detects membrane-bound protein complexes in cryo-electron tomograms. After subvolumes are sampled along a segmented membrane, each subvolume is assigned a score using a convolutional neural network (CNN), and protein positions are extracted by a clustering algorithm. Incorporating rotational subvolume normalization and using a tiny receptive field simplify the task of protein detection and thus facilitate the network training.

RESULTS

MemBrain requires only a small quantity of training labels and achieves excellent performance with only a single annotated membrane (F1 score: 0.88). A detailed evaluation shows that our fully trained pipeline outperforms existing classical computer vision-based and CNN-based approaches by a large margin (F1 score: 0.92 vs. max. 0.63). Furthermore, in addition to protein center positions, MemBrain can determine protein orientations, which has not been implemented by any existing CNN-based method to date. We also show that a pre-trained MemBrain program generalizes to tomograms acquired using different cryo-ET methods and depicting different types of cells.

CONCLUSIONS

MemBrain is a powerful and annotation-efficient tool for the detection of membrane protein complexes in cryo-ET data, with the potential to be used in a wide range of biological studies. It is generalizable to various kinds of tomograms, making it possible to use pretrained models for different tasks. Its efficiency in terms of required annotations also allows rapid training and fine-tuning of models. The corresponding code, pretrained models, and instructions for operating the MemBrain program can be found at: https://github.com/CellArchLab/MemBrain.

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.

A cytoskeletal vortex drives phage nucleus rotation during jumbo phage replication in E. coli

Nucleus-forming jumbo phages establish an intricate subcellular organization, enclosing phage genomes within a proteinaceous shell called the phage nucleus. During infection in Pseudomonas, some jumbo phages assemble a bipolar spindle of tubulin-like PhuZ filaments that positions the phage nucleus at midcell and drives its intracellular rotation. This facilitates the distribution of capsids on its surface for genome packaging. Here we show that the Escherichia coli jumbo phage Goslar assembles a phage nucleus surrounded by an array of PhuZ filaments resembling a vortex instead of a bipolar spindle. Expression of a mutant PhuZ protein strongly reduces Goslar phage nucleus rotation, demonstrating that the PhuZ cytoskeletal vortex is necessary for rotating the phage nucleus. While vortex-like cytoskeletal arrays are important in eukaryotes for cytoplasmic streaming and nucleus alignment, this work identifies a coherent assembly of filaments into a vortex-like structure driving intracellular rotation within the prokaryotic cytoplasm.

Computational methods for ultrastructural analysis of synaptic complexes

Electron microscopy (EM) provided fundamental insights about the ultrastructure of neuronal synapses. The large amount of information present in the contemporary EM datasets precludes a thorough assessment by visual inspection alone, thus requiring computational methods for the analysis of the data. Here, I review image processing software methods ranging from membrane tracing in large volume datasets to high resolution structures of synaptic complexes. Particular attention is payed to molecular level analysis provided by recent cryo-electron microscopy and tomography methods.

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.

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.

FSCC: Few-Shot Learning for Macromolecule Classification Based on Contrastive Learning and Distribution Calibration in Cryo-Electron Tomography

Cryo-electron tomography (Cryo-ET) is an emerging technology for three-dimensional (3D) visualization of macromolecular structures in the near-native state. To recover structures of macromolecules, millions of diverse macromolecules captured in tomograms should be accurately classified into structurally homogeneous subsets. Although existing supervised deep learning–based methods have improved classification accuracy, such trained models have limited ability to classify novel macromolecules that are unseen in the training stage. To adapt the trained model to the macromolecule classification of a novel class, massive labeled macromolecules of the novel class are needed. However, data labeling is very time-consuming and labor-intensive. In this work, we propose a novel few-shot learning method for the classification of novel macromolecules (named FSCC). A two-stage training strategy is designed in FSCC to enhance the generalization ability of the model to novel macromolecules. First, FSCC uses contrastive learning to pre-train the model on a sufficient number of labeled macromolecules. Second, FSCC uses distribution calibration to re-train the classifier, enabling the model to classify macromolecules of novel classes (unseen class in the pre-training). Distribution calibration transfers learned knowledge in the pre-training stage to novel macromolecules with limited labeled macromolecules of novel class. Experiments were performed on both synthetic and real datasets. On the synthetic datasets, compared with the state-of-the-art (SOTA) method based on supervised deep learning, FSCC achieves competitive performance. To achieve such performance, FSCC only needs five labeled macromolecules per novel class. However, the SOTA method needs 1100 ∼ 1500 labeled macromolecules per novel class. On the real datasets, FSCC improves the accuracy by 5% ∼ 16% when compared to the baseline model. These demonstrate good generalization ability of contrastive learning and calibration distribution to classify novel macromolecules with very few labeled macromolecules.

Structure of In Vitro-Synthesized Cellulose Fibrils Viewed by Cryo-Electron Tomography and 13C Natural-Abundance Dynamic Nuclear Polarization Solid-State NMR

Cellulose, the most abundant biopolymer, is a central source for renewable energy and functionalized materials. In vitro synthesis of cellulose microfibrils (CMFs) has become possible using purified cellulose synthase (CESA) isoforms from Physcomitrium patens and hybrid aspen. The exact nature of these in vitro fibrils remains unknown. Here, we characterize in vitro-synthesized fibers made by CESAs present in membrane fractions of P. patens over-expressing CESA5 by cryo-electron tomography and dynamic nuclear polarization (DNP) solid-state NMR. DNP enabled measuring two-dimensional 13C-13C correlation spectra without isotope-labeling of the fibers. Results show structural similarity between in vitro fibrils and native CMF in plant cell walls. Intensity quantifications agree with the 18-chain structural model for plant CMF and indicate limited fibrillar bundling. The in vitro system thus reveals insights into cell wall synthesis and may contribute to novel cellulosic materials. The integrated DNP and cryo-electron tomography methods are also applicable to structural studies of other carbohydrate-based biomaterials.

Gel-like inclusions of C-terminal fragments of TDP-43 sequester stalled proteasomes in neurons

Aggregation of the multifunctional RNA-binding protein TDP-43 defines large subgroups of amyotrophic lateral sclerosis and frontotemporal dementia and correlates with neurodegeneration in both diseases. In disease, characteristic C-terminal fragments of ~25 kDa ("TDP-25") accumulate in cytoplasmic inclusions. Here, we analyze gain-of-function mechanisms of TDP-25 combining cryo-electron tomography, proteomics, and functional assays. In neurons, cytoplasmic TDP-25 inclusions are amorphous, and photobleaching experiments reveal gel-like biophysical properties that are less dynamic than nuclear TDP-43. Compared with full-length TDP-43, the TDP-25 interactome is depleted of low-complexity domain proteins. TDP-25 inclusions are enriched in 26S proteasomes adopting exclusively substrate-processing conformations, suggesting that inclusions sequester proteasomes, which are largely stalled and no longer undergo the cyclic conformational changes required for proteolytic activity. Reporter assays confirm that TDP-25 impairs proteostasis, and this inhibitory function is enhanced by ALS-causing TDP-43 mutations. These findings support a patho-physiological relevance of proteasome dysfunction in ALS/FTD.

ScipionTomo: Towards cryo-electron tomography software integration, reproducibility, and validation

Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline.

The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project.

The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.

Capturing actin assemblies in cells using in situ cryo-electron tomography

Actin contributes to an exceptionally wide range of cellular processes through the assembly and disassembly of highly dynamic and ordered structures. Visualizing these structures in cells can help us understand how the molecular players of the actin machinery work together to produce force-generating systems. In recent years, cryo-electron tomography (cryo-ET) has become the method of choice for structural analysis of the cell interior at the molecular scale. Here we review advances in cryo-ET workflows that have enabled this transformation, especially the automation of sample preparation procedures, data collection, and processing. We discuss new structural analyses of dynamic actin assemblies in cryo-preserved cells, which have provided mechanistic insights into actin assembly and function at the nanoscale. Finally, we highlight the latest visual proteomics studies of actin filaments and their interactors reaching sub-nanometer resolutions in cells.

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.

VP-Detector: A 3D multi-scale dense convolutional neural network for macromolecule localization and classification in cryo-electron tomograms

BACKGROUND AND OBJECTIVE

Cryo-electron tomography (cryo-ET) with subtomogram averaging (STA) is indispensable when studying macromolecule structures and functions in their native environments. Due to the low signal-to-noise ratio, the missing wedge artifacts in tomographic reconstructions, and multiple macromolecules of varied shapes and sizes, macromolecule localization and classification remain challenging. To tackle this bottleneck problem for structural determination by STA, we design an accurate macromolecule localization and classification method named voxelwise particle detector (VP-Detector).

METHODS

VP-Detector is a two-stage particle detection method based on a 3D multiscale dense convolutional neural network (3D MSDNet). The proposed network uses 3D hybrid dilated convolution (3D HDC) to avoid the resolution loss caused by scaling operations. Meanwhile, it uses 3D dense connectivity to encourage the reuse of feature maps to reduce trainable parameters. In addition, the weighted focal loss is proposed to focus more attention on difficult samples and rare classes, which relieves the class imbalance caused by multiple particles of various sizes. The performance of VP-Detector is evaluated on both simulated and real-world tomograms, and it shows that VP-Detector outperforms state-of-the-art methods.

RESULTS

The experiments show that VP-Detector outperforms the state-of-the-art methods on particle localization with an F1-score of 0.951 and a precision of 0.978. In addition, VP-Detector can replace manual particle picking in experiment on the real-world tomograms. Furthermore, it performs well in classifying large-, medium-, and small-weight proteins with accuracies of 1, 0.95, and 0.82, respectively. Finally, ablation studies demonstrate the effectiveness of 3D HDC, 3D dense connectivity, weighted focal loss, and training on small training sets.

CONCLUSIONS

VP-Detector can achieve high accuracy in particle detection with few trainable parameters and support training on small datasets. It can also relieve the class imbalance caused by multiple particles with various shapes and sizes.

Subcellular organization of viral particles during maturation of nucleus-forming jumbo phage

Many eukaryotic viruses assemble mature particles within distinct subcellular compartments, but bacteriophages are generally assumed to assemble randomly throughout the host cell cytoplasm. Here, we show that viral particles of Pseudomonas nucleus-forming jumbo phage PhiPA3 assemble into a unique structure inside cells we term phage bouquets. We show that after capsids complete DNA packaging at the surface of the phage nucleus, tails assemble and attach to capsids, and these particles accumulate over time in a spherical pattern, with tails oriented inward and the heads outward to form bouquets at specific subcellular locations. Bouquets localize at the same fixed distance from the phage nucleus even when it is mispositioned, suggesting an active mechanism for positioning. These results mark the discovery of a pathway for organizing mature viral particles inside bacteria and demonstrate that nucleus-forming jumbo phages, like most eukaryotic viruses, are highly spatially organized during all stages of their lytic cycle.

Locations and in situ structure of the polymerase complex inside the virion of vesicular stomatitis virus

Unlike fellow nonsegmented negative-strand RNA viruses, exemplified by the devastating Nipah, Ebola, rabies, and measles viruses, vesicular stomatitis virus (VSV) can be considered beneficial, as it is widely used as a vector for anticancer therapy and vaccine development. In these RNA viruses, transcription and replication of the viral genome depend on an RNA-dependent RNA polymerase. Here, we determined the in situ structure of the VSV polymerase complex, consisting of a large protein (L) and a phosphoprotein (P), by cryo-electron tomography and subtomogram averaging. Approximately 55 polymerase complexes are packaged in each bullet-shaped virion through flexible interactions with nucleoproteins. Our results provide insights into the mechanism of L packaging during virus assembly and efficient initiation of transcription during infection.

The polymerase complex of nonsegmented negative-strand RNA viruses primarily consists of a large (L) protein and a phosphoprotein (P). L is a multifunctional enzyme carrying out RNA-dependent RNA polymerization and all other steps associated with transcription and replication, while P is the nonenzymatic cofactor, regulating the function and conformation of L. The structure of a purified vesicular stomatitis virus (VSV) polymerase complex containing L and associated P segments has been determined; however, the location and manner of the attachments of L and P within each virion are unknown, limiting our mechanistic understanding of VSV RNA replication and transcription and hindering engineering efforts of this widely used anticancer and vaccine vector. Here, we have used cryo-electron tomography to visualize the VSV virion, revealing the attachment of the ring-shaped L molecules to VSV nucleocapsid proteins (N) throughout the cavity of the bullet-shaped nucleocapsid. Subtomogram averaging and three-dimensional classification of regions containing N and the matrix protein (M) have yielded the in situ structure of the polymerase complex. On average, ∼55 polymerase complexes are packaged in each virion. The capping domain of L interacts with two neighboring N molecules through flexible attachments. P, which exists as a dimer, bridges separate N molecules and the connector and C-terminal domains of L. Our data provide the structural basis for recruitment of L to N by P in virus assembly and for flexible attachments between L and N, which allow a quick response of L in primary transcription upon cell entry.

Cryogenic electron microscopy approaches that combine images and tilt series

Cryogenic electron microscopy can be widely applied to biological specimens from the molecular to the cellular scale. In single-particle analysis, 3D structures may be obtained in high resolution by averaging 2D images of single particles in random orientations. For pleomorphic specimens, structures may be obtained by recording the tilt series of a single example of the specimen and calculating tomograms. Where many copies of a single structure such as a protein or nucleic acid assembly are present within the tomogram, averaging of the sub-volumes (subtomogram averaging) has been successfully applied. The choice of data collection method for any given specimen may depend on the structural question of interest and is determined by the radiation sensitivity of the specimen. Here, we survey some recent developments on the use of hybrid methods for recording and analysing data from radiation-sensitive biological specimens. These include single-particle reconstruction from 2D images where additional views are recorded at a single tilt angle of the specimen and methods where image tilt series, initially used for tomogram reconstruction, are processed as individual single-particle images. There is a continuum of approaches now available to maximize structural information obtained from the specimen.

Structures from intact myofibrils reveal mechanism of thin filament regulation through nebulin

In skeletal muscle, nebulin stabilizes and regulates the length of thin filaments, but the underlying mechanism remains nebulous. In this work, we used cryo-electron tomography and subtomogram averaging to reveal structures of native nebulin bound to thin filaments within intact sarcomeres. This in situ reconstruction provided high-resolution details of the interaction between nebulin and actin, demonstrating the stabilizing role of nebulin. Myosin bound to the thin filaments exhibited different conformations of the neck domain, highlighting its inherent structural variability in muscle. Unexpectedly, nebulin did not interact with myosin or tropomyosin, but it did interact with a troponin T linker through two potential binding motifs on nebulin, explaining its regulatory role. Our structures support the role of nebulin as a thin filament "molecular ruler" and provide a molecular basis for studying nemaline myopathies.

Cryo-ET of Env on intact HIV virions reveals structural variation and positioning on the Gag lattice

HIV-1 Env mediates viral entry into host cells and is the sole target for neutralizing antibodies. However, Env structure and organization in its native virion context has eluded detailed characterization. Here, we used cryo-electron tomography to analyze Env in mature and immature HIV-1 particles. Immature particles showed distinct Env positioning relative to the underlying Gag lattice, providing insights into long-standing questions about Env incorporation. A 9.1-Å sub-tomogram-averaged reconstruction of virion-bound Env in conjunction with structural mass spectrometry revealed unexpected features, including a variable central core of the gp41 subunit, heterogeneous glycosylation between protomers, and a flexible stalk that allows Env tilting and variable exposure of neutralizing epitopes. Together, our results provide an integrative understanding of HIV assembly and structural variation in Env antigen presentation.

Subtomogram analysis: The sum of a tomogram's particles reveals molecular structure in situ

Cryo-electron tomography is uniquely suited to provide insights into the molecular architecture of cells and tissue in the native state. While frozen hydrated specimens tolerate sufficient electron doses to distinguish different types of particles in a tomogram, the accumulating beam damage does not allow resolving their detailed molecular structure individually. Statistical methods for subtomogram averaging and classification that coherently enhance the signal of particles corresponding to copies of the same type of macromolecular allow obtaining much higher resolution insights into macromolecules. Here, I review the developments in subtomogram analysis at Wolfgang Baumeister's laboratory that make the dream of structural biology in the native cell become reality.

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.

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

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

We present a new approach for macromolecular structure determination from multiple particles in electron cryo-tomography (cryo-ET) data sets. Whereas existing subtomogram averaging approaches are based on 3D data models, we propose to optimise a regularised likelihood target that approximates a function of the 2D experimental images. In addition, analogous to Bayesian polishing and contrast transfer function (CTF) refinement in single-particle analysis, we describe the approaches that exploit the increased signal-to-noise ratio in the averaged structure to optimise tilt-series alignments, beam-induced motions of the particles throughout the tilt-series acquisition, defoci of the individual particles, as well as higher-order optical aberrations of the microscope. Implementation of our approaches in the open-source software package RELION aims to facilitate their general use, particularly for those researchers who are already familiar with its single-particle analysis tools. We illustrate for three applications that our approaches allow structure determination from cryo-ET data to resolutions sufficient for de novo atomic modelling.

Electron cryo-tomography structure of axonemal doublet microtubule from Tetrahymena thermophila

Doublet microtubules (DMTs) provide a scaffold for axoneme assembly in motile cilia. Aside from α/β tubulins, the DMT comprises a large number of non-tubulin proteins in the luminal wall of DMTs, collectively named the microtubule inner proteins (MIPs). We used cryoET to study axoneme DMT isolated from Tetrahymena We present the structures of DMT at nanometer and sub-nanometer resolution. The structures confirm that MIP RIB72A/B binds to the luminal wall of DMT by multiple DM10 domains. We found FAP115, an MIP-containing multiple EF-hand domains, located at the interface of four-tubulin dimers in the lumen of A-tubule. It contacts both lateral and longitudinal tubulin interfaces and playing a critical role in DMT stability. We observed substantial structure heterogeneity in DMT in an FAP115 knockout strain, showing extensive structural defects beyond the FAP115-binding site. The defects propagate along the axoneme. Finally, by comparing DMT structures from Tetrahymena and Chlamydomonas, we have identified a number of conserved MIPs as well as MIPs that are unique to each organism. This conservation and diversity of the DMT structures might be linked to their specific functions. Our work provides structural insights essential for understanding the roles of MIPs during motile cilium assembly and function, as well as their relationships to human ciliopathies.

Determinants shaping the nanoscale architecture of the mouse rod outer segment

The unique membrane organization of the rod outer segment (ROS), the specialized sensory cilium of rod photoreceptor cells, provides the foundation for phototransduction, the initial step in vision. ROS architecture is characterized by a stack of identically shaped and tightly packed membrane disks loaded with the visual receptor rhodopsin. A wide range of genetic aberrations have been reported to compromise ROS ultrastructure, impairing photoreceptor viability and function. Yet, the structural basis giving rise to the remarkably precise arrangement of ROS membrane stacks and the molecular mechanisms underlying genetically inherited diseases remain elusive. Here, cryo-electron tomography (cryo-ET) performed on native ROS at molecular resolution provides insights into key structural determinants of ROS membrane architecture. Our data confirm the existence of two previously observed molecular connectors/spacers which likely contribute to the nanometer-scale precise stacking of the ROS disks. We further provide evidence that the extreme radius of curvature at the disk rims is enforced by a continuous supramolecular assembly composed of peripherin-2 (PRPH2) and rod outer segment membrane protein 1 (ROM1) oligomers. We suggest that together these molecular assemblies constitute the structural basis of the highly specialized ROS functional architecture. Our Cryo-ET data provide novel quantitative and structural information on the molecular architecture in ROS and substantiate previous results on proposed mechanisms underlying pathologies of certain PRPH2 mutations leading to blindness.

Integrative structural modeling of macromolecular complexes using Assembline

Integrative modeling enables structure determination of macromolecular complexes by combining data from multiple experimental sources such as X-ray crystallography, electron microscopy or cross-linking mass spectrometry. It is particularly useful for complexes not amenable to high-resolution electron microscopy-complexes that are flexible, heterogeneous or imaged in cells with cryo-electron tomography. We have recently developed an integrative modeling protocol that allowed us to model multi-megadalton complexes as large as the nuclear pore complex. Here, we describe the Assembline software package, which combines multiple programs and libraries with our own algorithms in a streamlined modeling pipeline. Assembline builds ensembles of models satisfying data from atomic structures or homology models, electron microscopy maps and other experimental data, and provides tools for their analysis. Compared with other methods, Assembline enables efficient sampling of conformational space through a multistep procedure, provides new modeling restraints and includes a unique configuration system for setting up the modeling project. Our protocol achieves exhaustive sampling in less than 100-1,000 CPU-hours even for complexes in the megadalton range. For larger complexes, resources available in institutional or public computer clusters are needed and sufficient to run the protocol. We also provide step-by-step instructions for preparing the input, running the core modeling steps and assessing modeling performance at any stage.

TomoFlow: Analysis of Continuous Conformational Variability of Macromolecules in Cryogenic Subtomograms based on 3D Dense Optical Flow

Cryogenic Electron Tomography (cryo-ET) allows structural and dynamics studies of macromolecules in situ. Averaging different copies of imaged macromolecules is commonly used to obtain their structure at higher resolution and discrete classification to analyze their dynamics. Instrumental and data processing developments are progressively equipping cryo-ET studies with the ability to escape the trap of classification into a complete continuous conformational variability analysis. In this work, we propose TomoFlow, a method for analyzing macromolecular continuous conformational variability in cryo-ET subtomograms based on a three-dimensional dense optical flow (OF) approach. The resultant lower-dimensional conformational space allows generating movies of macromolecular motion and obtaining subtomogram averages by grouping conformationally similar subtomograms. The animations and the subtomogram group averages reveal accurate trajectories of macromolecular motion based on a novel mathematical model that makes use of OF properties. This paper describes TomoFlow with tests on simulated datasets generated using different techniques, namely Normal Mode Analysis and Molecular Dynamics Simulation. It also shows an application of TomoFlow on a dataset of nucleosomes in situ, which provided promising results coherent with previous findings using the same dataset but without imposing any prior knowledge on the analysis of the conformational variability. The method is discussed with its potential uses and limitations.

Complete atomic structure of a native archaeal cell surface

Many prokaryotic cells are covered by an ordered, proteinaceous, sheet-like structure called a surface layer (S-layer). S-layer proteins (SLPs) are usually the highest copy number macromolecules in prokaryotes, playing critical roles in cellular physiology such as blocking predators, scaffolding membranes, and facilitating environmental interactions. Using electron cryomicroscopy of two-dimensional sheets, we report the atomic structure of the S-layer from the archaeal model organism Haloferax volcanii. This S-layer consists of a hexagonal array of tightly interacting immunoglobulin-like domains, which are also found in SLPs across several classes of archaea. Cellular tomography reveal that the S-layer is nearly continuous on the cell surface, completed by pentameric defects in the hexagonal lattice. We further report the atomic structure of the SLP pentamer, which shows markedly different relative arrangements of SLP domains needed to complete the S-layer. Our structural data provide a framework for understanding cell surfaces of archaea at the atomic level.

Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms

Cryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present DeepFinder, a computational procedure that uses artificial neural networks to simultaneously localize multiple classes of macromolecules. Once trained, the inference stage of DeepFinder is faster than template matching and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (roughly 3.2 MDa), ribulose 1,5-bisphosphate carboxylase-oxygenase (roughly 560 kDa soluble complex) and photosystem II (roughly 550 kDa membrane complex) with an accuracy comparable to expert-supervised ground truth annotations. DeepFinder is therefore a promising algorithm for the semiautomated analysis of a wide range of molecular targets in cellular tomograms.

Structural analysis of receptors and actin polarity in platelet protrusions

During activation the platelet cytoskeleton is reorganized, inducing adhesion to the extracellular matrix and cell spreading. These processes are critical for wound healing and clot formation. Initially, this task relies on the formation of strong cellular-extracellular matrix interactions, exposed in subendothelial lesions. Despite the medical relevance of these processes, there is a lack of high-resolution structural information on the platelet cytoskeleton controlling cell spreading and adhesion. Here, we present in situ structural analysis of membrane receptors and the underlying cytoskeleton in platelet protrusions by applying cryoelectron tomography to intact platelets. We utilized three-dimensional averaging procedures to study receptors at the plasma membrane. Analysis of substrate interaction-free receptors yielded one main structural class resolved to 26 Å, resembling the α_IIbβ₃ integrin folded conformation. Furthermore, structural analysis of the actin network in pseudopodia indicates a nonuniform polarity of filaments. This organization would allow generation of the contractile forces required for integrin-mediated cell adhesion.

In situ cryo-electron tomography reveals gradient organization of ribosome biogenesis in intact nucleoli

Ribosomes comprise a large (LSU) and a small subunit (SSU) which are synthesized independently in the nucleolus before being exported into the cytoplasm, where they assemble into functional ribosomes. Individual maturation steps have been analyzed in detail using biochemical methods, light microscopy and conventional electron microscopy (EM). In recent years, single particle analysis (SPA) has yielded molecular resolution structures of several pre-ribosomal intermediates. It falls short, however, of revealing the spatiotemporal sequence of ribosome biogenesis in the cellular context. Here, we present our study on native nucleoli in Chlamydomonas reinhardtii, in which we follow the formation of LSU and SSU precursors by in situ cryo-electron tomography (cryo-ET) and subtomogram averaging (STA). By combining both positional and molecular data, we reveal gradients of ribosome maturation within the granular component (GC), offering a new perspective on how the liquid-liquid-phase separation of the nucleolus supports ribosome biogenesis.

Structural Basis for a Neutralizing Antibody Response Elicited by a Recombinant Hantaan Virus Gn Immunogen

Hantaviruses are a group of emerging pathogens capable of causing severe disease upon zoonotic transmission to humans. The mature hantavirus surface presents higher-order tetrameric assemblies of two glycoproteins, Gn and Gc, which are responsible for negotiating host cell entry and constitute key therapeutic targets. Here, we demonstrate that recombinantly derived Gn from Hantaan virus (HTNV) elicits a neutralizing antibody response (serum dilution that inhibits 50% infection [ID₅₀], 1:200 to 1:850) in an animal model. Using antigen-specific B cell sorting, we isolated monoclonal antibodies (mAbs) exhibiting neutralizing and non-neutralizing activity, termed mAb HTN-Gn1 and mAb nnHTN-Gn2, respectively. Crystallographic analysis reveals that these mAbs target spatially distinct epitopes at disparate sites of the N-terminal region of the HTNV Gn ectodomain. Epitope mapping onto a model of the higher order (Gn-Gc)₄ spike supports the immune accessibility of the mAb HTN-Gn1 epitope, a hypothesis confirmed by electron cryo-tomography of the antibody with virus-like particles. These data define natively exposed regions of the hantaviral Gn that can be targeted in immunogen design. IMPORTANCE The spillover of pathogenic hantaviruses from rodent reservoirs into the human population poses a continued threat to human health. Here, we show that a recombinant form of the Hantaan virus (HTNV) surface-displayed glycoprotein, Gn, elicits a neutralizing antibody response in rabbits. We isolated a neutralizing (HTN-Gn1) and a non-neutralizing (nnHTN-Gn2) monoclonal antibody and provide the first molecular-level insights into how the Gn glycoprotein may be targeted by the antibody-mediated immune response. These findings may guide rational vaccine design approaches focused on targeting the hantavirus glycoprotein envelope.

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.

TomoAlign: A novel approach to correcting sample motion and 3D CTF in CryoET

TomoAlign is a software package that integrates tools to mitigate two important resolution limiting factors in cryoET, namely the beam-induced sample motion and the contrast transfer function (CTF) of the microscope. The package is especially focused on cryoET of thick specimens where fiducial markers are required for accurate tilt-series alignment and sample motion estimation. TomoAlign models the beam-induced sample motion undergone during the tilt-series acquisition. The motion models are used to produce motion-corrected subtilt-series centered on the particles of interest. In addition, the defocus of each particle at each tilt image is determined and can be corrected, resulting in motion-corrected and CTF-corrected subtilt-series from which the subtomograms can be computed. Alternatively, the CTF information can be passed on so that CTF correction can be carried out entirely within external packages like Relion. TomoAlign serves as a versatile tool that can streamline the cryoET workflow from initial alignment of tilt-series to final subtomogram averaging during in situ structure determination.