Cellular Cryo-electron Tomography Research Articles

RNA genome packaging and capsid assembly of bluetongue virus visualized in host cells

Unlike those of double-stranded DNA (dsDNA), single-stranded DNA (ssDNA), and ssRNA viruses, the mechanism of genome packaging of dsRNA viruses is poorly understood. Here, we combined the techniques of high-resolution cryoelectron microscopy (cryo-EM), cellular cryoelectron tomography (cryo-ET), and structure-guided mutagenesis to investigate genome packaging and capsid assembly of bluetongue virus (BTV), a member of the Reoviridae family of dsRNA viruses. A total of eleven assembly states of BTV capsid were captured, with resolutions up to 2.8Å, with most visualized in the host cytoplasm. ATPase VP6 was found underneath the vertices of capsid shell protein VP3 as an RNA-harboring pentamer, facilitating RNA packaging. RNA packaging expands the VP3 shell, which then engages middle- and outer-layer proteins to generate infectious virions. These revealed "duality" characteristics of the BTV assembly mechanism reconcile previous contradictory co-assembly and core-filling models and provide insights into the mysterious RNA packaging and capsid assembly of Reoviridae members and beyond.

ColabSeg: An interactive tool for editing, processing, and visualizing membrane segmentations from cryo-ET data

Cellular cryo-electron tomography (cryo-ET) has emerged as a key method to unravel the spatial and structural complexity of cells in their near-native state at unprecedented molecular resolution. To enable quantitative analysis of the complex shapes and morphologies of lipid membranes, the noisy three-dimensional (3D) volumes must be segmented. Despite recent advances, this task often requires considerable user intervention to curate the resulting segmentations. Here, we present ColabSeg, a Python-based tool for processing, visualizing, editing, and fitting membrane segmentations from cryo-ET data for downstream analysis. ColabSeg makes many well-established algorithms for point-cloud processing easily available to the broad community of structural biologists for applications in cryo-ET through its graphical user interface (GUI). We demonstrate the usefulness of the tool with a range of use cases and biological examples. Finally, for a large Mycoplasma pneumoniae dataset of 50 tomograms, we show how ColabSeg enables high-throughput membrane segmentation, which can be used as valuable training data for fully automated convolutional neural network (CNN)-based segmentation.

Structures and Efflux Mechanisms of the AcrAB-TolC Pump.

The global emergence of multidrug resistance (MDR) in gram-negative bacteria has become a matter of worldwide concern. MDR in these pathogens is closely linked to the overexpression of certain efflux pumps, particularly the resistance-nodulation-cell division (RND) efflux pumps. Inhibition of these pumps presents an attractive and promising strategy to combat antibiotic resistance, as the efflux pump inhibitors can effectively restore the potency of existing antibiotics. AcrAB-TolC is one well-studied RND efflux pump, which transports a variety of substrates, therefore providing resistance to a broad spectrum of antibiotics. To develop effective pump inhibitors, a comprehensive understanding of the structural aspect of the AcrAB-TolC efflux pump is imperative. Previous studies on this pump's structure have been limited to individual components or in vitro determination of fully assembled pumps. Recent advancements in cellular cryo-electron tomography (cryo-ET) have provided novel insights into this pump's assembly and functional mechanism within its native cell membrane environment. Here, we present a summary of the structural data regarding the AcrAB-TolC efflux pump, shedding light on its assembly pathway and operational mechanism.

De novo protein identification in mammalian sperm using in situ cryoelectron tomography and AlphaFold2 docking

To understand the molecular mechanisms of cellular pathways, contemporary workflows typically require multiple techniques to identify proteins, track their localization, and determine their structures invitro. Here, we combined cellular cryoelectron tomography (cryo-ET) and AlphaFold2 modeling to address these questions and understand how mammalian sperm are built in situ. Our cellular cryo-ET and subtomogram averaging provided 6.0-Å reconstructions of axonemal microtubule structures. The well-resolved tertiary structures allowed us to unbiasedly match sperm-specific densities with 21,615 AlphaFold2-predicted protein models of the mouse proteome. We identified Tektin 5, CCDC105, and SPACA9 as novel microtubule-associated proteins. These proteins form an extensive interaction network crosslinking the lumen of axonemal doublet microtubules, suggesting their roles in modulating the mechanical properties of the filaments. Indeed, Tekt5-/- sperm possess more deformed flagella with 180° bends. Together, our studies presented a cellular visual proteomics workflow and shed light on the invivo functions of Tektin 5.

Quantifying organellar ultrastructure in cryo-electron tomography using a surface morphometrics pipeline.

Cellular cryo-electron tomography (cryo-ET) enables three-dimensional reconstructions of organelles in their native cellular environment at subnanometer resolution. However, quantifying ultrastructural features of pleomorphic organelles in three dimensions is challenging, as is defining the significance of observed changes induced by specific cellular perturbations. To address this challenge, we established a semiautomated workflow to segment organellar membranes and reconstruct their underlying surface geometry in cryo-ET. To complement this workflow, we developed an open-source suite of ultrastructural quantifications, integrated into a single pipeline called the surface morphometrics pipeline. This pipeline enables rapid modeling of complex membrane structures and allows detailed mapping of inter- and intramembrane spacing, curvedness, and orientation onto reconstructed membrane meshes, highlighting subtle organellar features that are challenging to detect in three dimensions and allowing for statistical comparison across many organelles. To demonstrate the advantages of this approach, we combine cryo-ET with cryo-fluorescence microscopy to correlate bulk mitochondrial network morphology (i.e., elongated versus fragmented) with membrane ultrastructure of individual mitochondria in the presence and absence of endoplasmic reticulum (ER) stress. Using our pipeline, we demonstrate ER stress promotes adaptive remodeling of ultrastructural features of mitochondria including spacing between the inner and outer membranes, local curvedness of the inner membrane, and spacing between mitochondrial cristae. We show that differences in membrane ultrastructure correlate to mitochondrial network morphologies, suggesting that these two remodeling events are coupled. Our pipeline offers opportunities for quantifying changes in membrane ultrastructure on a single-cell level using cryo-ET, opening new opportunities to define changes in ultrastructural features induced by diverse types of cellular perturbations.

Direct Cryo-ET observation of platelet deformation induced by SARS-CoV-2 spike protein

SARS-CoV-2 is a novel coronavirus responsible for the COVID-19 pandemic. Its high pathogenicity is due to SARS-CoV-2 spike protein (S protein) contacting host-cell receptors. A critical hallmark of COVID-19 is the occurrence of coagulopathies. Here, we report the direct observation of the interactions between S protein and platelets. Live imaging shows that the S protein triggers platelets to deform dynamically, in some cases, leading to their irreversible activation. Cellular cryo-electron tomography reveals dense decorations of S protein on the platelet surface, inducing filopodia formation. Hypothesizing that S protein binds to filopodia-inducing integrin receptors, we tested the binding to RGD motif-recognizing platelet integrins and find that S protein recognizes integrin αvβ3. Our results infer that the stochastic activation of platelets is due to weak interactions of S protein with integrin, which can attribute to the pathogenesis of COVID-19 and the occurrence of rare but severe coagulopathies.

Structure and activity of particulate methane monooxygenase arrays in methanotrophs

Methane-oxidizing bacteria play a central role in greenhouse gas mitigation and have potential applications in biomanufacturing. Their primary metabolic enzyme, particulate methane monooxygenase (pMMO), is housed in copper-induced intracytoplasmic membranes (ICMs), of which the function and biogenesis are not known. We show by serial cryo-focused ion beam (cryoFIB) milling/scanning electron microscope (SEM) volume imaging and lamellae-based cellular cryo-electron tomography (cryoET) that these ICMs are derived from the inner cell membrane. The pMMO trimer, resolved by cryoET and subtomogram averaging to 4.8 Å in the ICM, forms higher-order hexagonal arrays in intact cells. Array formation correlates with increased enzymatic activity, highlighting the importance of studying the enzyme in its native environment. These findings also demonstrate the power of cryoET to structurally characterize native membrane enzymes in the cellular context.

Volumetric macromolecule identification in cryo-electron tomograms using capsule networks

BackgroundDespite recent advances in cellular cryo-electron tomography (CET), developing automated tools for macromolecule identification in submolecular resolution remains challenging due to the lack of annotated data and high structural complexities. To date, the extent of the deep learning methods constructed for this problem is limited to conventional Convolutional Neural Networks (CNNs). Identifying macromolecules of different types and sizes is a tedious and time-consuming task. In this paper, we employ a capsule-based architecture to automate the task of macromolecule identification, that we refer to as 3D-UCaps. In particular, the architecture is composed of three components: feature extractor, capsule encoder, and CNN decoder. The feature extractor converts voxel intensities of input sub-tomograms to activities of local features. The encoder is a 3D Capsule Network (CapsNet) that takes local features to generate a low-dimensional representation of the input. Then, a 3D CNN decoder reconstructs the sub-tomograms from the given representation by upsampling.ResultsWe performed binary and multi-class localization and identification tasks on synthetic and experimental data. We observed that the 3D-UNet and the 3D-UCaps had an F_1-score mostly above 60% and 70%, respectively, on the test data. In both network architectures, we observed degradation of at least 40% in the F_1-score when identifying very small particles (PDB entry 3GL1) compared to a large particle (PDB entry 4D8Q). In the multi-class identification task of experimental data, 3D-UCaps had an F_1-score of 91% on the test data in contrast to 64% of the 3D-UNet. The better F_1-score of 3D-UCaps compared to 3D-UNet is obtained by a higher precision score. We speculate this to be due to the capsule network employed in the encoder. To study the effect of the CapsNet-based encoder architecture further, we performed an ablation study and perceived that the F_1-score is boosted as network depth is increased which is in contrast to the previously reported results for the 3D-UNet. To present a reproducible work, source code, trained models, data as well as visualization results are made publicly available.ConclusionQuantitative and qualitative results show that 3D-UCaps successfully perform various downstream tasks including identification and localization of macromolecules and can at least compete with CNN architectures for this task. Given that the capsule layers extract both the existence probability and the orientation of the molecules, this architecture has the potential to lead to representations of the data that are better interpretable than those of 3D-UNet.

In situ cryo-electron tomography reveals local cellular machineries for axon branch development

Neurons are highly polarized cells forming an intricate network of dendrites and axons. They are shaped by the dynamic reorganization of cytoskeleton components and cellular organelles. Axon branching allows the formation of new paths and increases circuit complexity. However, our understanding of branch formation is sparse due to the lack of direct in-depth observations. Using in situ cellular cryo-electron tomography on primary mouse neurons, we directly visualized the remodeling of organelles and cytoskeleton structures at axon branches. Strikingly, branched areas functioned as hotspots concentrating organelles to support dynamic activities. Unaligned actin filaments assembled at the base of premature branches accompanied by filopodia-like protrusions. Microtubules and ER comigrated into preformed branches to support outgrowth together with accumulating compact, ∼500-nm mitochondria and locally clustered ribosomes. We obtained a roadmap of events supporting the hypothesis of local protein synthesis selectively taking place at axon branches, allowing them to serve as unique control hubs for axon development and downstream neural network formation.

Genetically encoded labels for cellular cryo-electron tomography

Cellular cryo-electron tomography is a label-free imaging approach that allows us to visualise the macromolecular landscape inside cells in its near-native state. However, in-depth understanding of the visualised landscapes has been hampered by our inability to identify specific macromolecules without extensive data collection and image processing. Genetically encoded multimeric particles (GEMs) provide a physical, intracellular solution that can be used as visual landmarks for localising a protein of interest.

Cellular cryo-electron tomography reveals drastic mitochondrial membrane remodeling in response to endoplasmic reticulum stress

Mitochondria are important stress sensing organelles that can adapt the metabolic needs of the cell. Cellular stress associated with the accumulation of misfolded proteins in the endoplasmic reticulum (ER Stress) is signaled to mitochondria through the PERK arm of the unfolded protein response (UPR). This leads to stress induced mitochondrial hyperfusion (SIMH) coupled with changes to mitochondrial metabolic function. Imbalances in PERK signaling is linked to mitochondrial dysfunction associated with neurodegenerative disease.

A modular platform for automated cryo-FIB workflows.

Lamella micromachining by focused ion beam milling at cryogenic temperature (cryo-FIB) has matured into a preparation method widely used for cellular cryo-electron tomography. Due to the limited ablation rates of low Ga+ ion beam currents required to maintain the structural integrity of vitreous specimens, common preparation protocols are time-consuming and labor intensive. The improved stability of new-generation cryo-FIB instruments now enables automated operations. Here, we present an open-source software tool, SerialFIB, for creating automated and customizable cryo-FIB preparation protocols. The software encompasses a graphical user interface for easy execution of routine lamellae preparations, a scripting module compatible with available Python packages, and interfaces with three-dimensional correlative light and electron microscopy (CLEM) tools. SerialFIB enables the streamlining of advanced cryo-FIB protocols such as multi-modal imaging, CLEM-guided lamella preparation and in situ lamella lift-out procedures. Our software therefore provides a foundation for further development of advanced cryogenic imaging and sample preparation protocols.

UNSUPERVISED DOMAIN ALIGNMENT BASED OPEN SET STRUCTURAL RECOGNITION OF MACROMOLECULES CAPTURED BY CRYO-ELECTRON TOMOGRAPHY.

Cellular cryo-Electron Tomography (cryo-ET) provides three-dimensional views of structural and spatial information of various macromolecules in cells in a near-native state. Subtomogram classification is a key step for recognizing and differentiating these macromolecular structures. In recent years, deep learning methods have been developed for high-throughput subtomogram classification tasks; however, conventional supervised deep learning methods cannot recognize macromolecular structural classes that do not exist in the training data. This imposes a major weakness since most native macromolecular structures in cells are unknown and consequently, cannot be included in the training data. Therefore, open set learning which can recognize unknown macromolecular structures is necessary for boosting the power of automatic subtomogram classification. In this paper, we propose a method called Margin-based Loss for Unsupervised Domain Alignment (MLUDA) for open set recognition problems where only a few categories of interest are shared between cross-domain data. Through extensive experiments, we demonstrate that MLUDA performs well at cross-domain open-set classification on both public datasets and medical imaging datasets. So our method is of practical importance.

Correlative cryo-ET identifies actin/tropomyosin filaments that mediate cell-substrate adhesion in cancer cells and mechanosensitivity of cell proliferation.

The actin cytoskeleton is the primary driver of cellular adhesion and mechanosensing due to its ability to generate force and sense the stiffness of the environment. At the cell's leading edge, severing of the protruding Arp2/3 actin network generates a specific actin/tropomyosin (Tpm) filament population that controls lamellipodial persistence. The interaction between these filaments and adhesion to the environment is unknown. Using cellular cryo-electron tomography we resolve the ultrastructure of the Tpm/actin copolymers and show that they specifically anchor to nascent adhesions and are essential for focal adhesion assembly. Re-expression of Tpm1.8/1.9 in transformed and cancer cells is sufficient to restore cell-substrate adhesions. We demonstrate that knock-out of Tpm1.8/1.9 disrupts the formation of dorsal actin bundles, hindering the recruitment of α-actinin and non-muscle myosin IIa, critical mechanosensors. This loss causes a force-generation and proliferation defect that is notably reversed when cells are grown on soft surfaces. We conclude that Tpm1.8/1.9 suppress the metastatic phenotype, which may explain why transformed cells naturally downregulate this Tpm subset during malignant transformation.

Lattice micropatterning for cryo-electron tomography studies of cell-cell contacts

Cryo-electron tomography is the highest resolution tool available for structural analysis of macromolecular complexes within their native cellular environments. At present, data acquisition suffers from low throughput, in part due to the low probability of positioning a cell such that the subcellular structure of interest is on a region of the electron microscopy (EM) grid that is suitable for imaging. Here, we photo-micropatterned EM grids to optimally position endothelial cells so as to enable high-throughput imaging of cell-cell contacts. Lattice micropatterned grids increased the average distance between intercellular contacts and thicker cell nuclei such that the regions of interest were sufficiently thin for direct imaging. We observed a diverse array of membranous and cytoskeletal structures at intercellular contacts, demonstrating the utility of this technique in enhancing the rate of data acquisition for cellular cryo-electron tomography studies.

Micropatterning of electron microscopy grids for improved cellular cryo-electron tomography throughput

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Lattice Micropatterning of Electron Microscopy Grids for Improved Cellular Cryo-Electron Tomography Throughput

Cryo-electron tomography is the highest resolution tool available for structural analysis of macromolecular complexes within their native cellular environment. At present, data acquisition suffers from low throughput, in part due to the low probability of positioning a cell such that the subcellular structure of interest is on a region of the electron microscopy (EM) grid that is suitable for imaging. Here, we leverage photo-micropatterning of EM grids to optimally position endothelial cells to enable high-throughput imaging of cell-cell contacts.

Practical Approaches for Cryo-FIB Milling and Applications for Cellular Cryo-Electron Tomography.

Cryo-electron tomography (cryo-ET) is a powerful technique to examine cellular structures as they exist in situ. However, direct imaging by TEM for cryo-ET is limited to specimens up to ∼400nm in thickness, narrowing its applicability to areas such as cellular projections or small bacteria and viruses. Cryo-focused ion beam (cryo-FIB) milling has emerged in recent years as a method to generate thin specimens from cellular samples in preparation for cryo-ET. In this technique, specimens are thinned with a beam of gallium ions to gradually ablate cellular material in order to leave a thin, electron-transparent section (a lamella) through the bulk material. The lamella can be used for high-resolution cryo-ET to visualize cells in 3D in a near-native state. This approach has proved to be robust and relatively simple for new users and exhibits minimal sectioning artifacts. In this chapter, we describe a general approach to cryo-FIB milling for users with prior cryo-EM experience, with extensive notes on operation and troubleshooting.

Indirect Bacterial Transcription-Translation Coupling Mechanism Revealed by In Situ Integrative Structural Biology

In situ structural biology aims to resolve macromolecular structures and collective behaviors of macromolecular machineries within the cell. In bacteria, transcription mediated by RNA polymerase is known to be functionally coupled to the leading ribosome, a process crucial for efficient gene expression. Direct ribosome-RNA polymerase interaction has been demonstrated in vitro, but how these two gigantic molecular machines coordinate is yet unclear, especially within the context of crowded and complex cellular environments. Using Mycoplasma pneumonia as model system, we integrated cellular cryo-electron tomography followed by sub-tomogram analysis (STA) and in-cell crosslinking mass spectrometry (CLMS) to investigate the coupling in native cells, without resorting to labelling or cell disruption. By averaging sub-tomograms extracted in silico from cellular volumes, we solved the 70S ribosome structure at 6.4 Å resolution, so far the highest resolution reported for in-cell cryo-ET. After large-scale classification, we determined the structure of a super-complex consisting of ribosome, RNA polymerase and other auxiliary proteins. Protein-protein interaction networks revealed by in-cell CLMS indicated an essential transcription elongation factor bridging RNA polymerase and the translating ribosome. Integrative modelling suggests a novel, indirect transcription-translation coupling mechanism, which advances our understanding of key machineries of the central dogma of molecular biology in bacteria. Methodology wise, our work demonstrates the feasibility and superiority of integrative structural biology performed directly inside cells. Integration of two approaches, cryo-ET/STA and in-cell CLMS, holds great potential to delineate cellular processes in a quantitative and structural view.

Tailoring cryo-electron microscopy grids by photo-micropatterning for in-cell structural studies.

Spatially-controlled cell adhesion on electron microscopy (EM) supports remains a bottleneck in specimen preparation for cellular cryo-electron tomography. Here, we describe contactless and mask-free photo-micropatterning of EM grids for site-specific deposition of extracellular matrix (ECM)-related proteins. We attained refined cell positioning for micromachining by cryo-focused ion beam milling. Complex micropatterns generated predictable intracellular organization, allowing direct correlation between cell architecture and in-cell 3D-structural characterization of the underlying molecular machinery.