Toward high-resolution in situ structural biology with cryo-electron tomography and subtomogram averaging

Navigating the unstructured by evaluating alphafold's efficacy in predicting missing residues and structural disorder in proteins

The study investigated regions with undefined structures, known as "missing" segments in X-ray crystallography and cryo-electron microscopy (Cryo-EM) data, by assessing their predicted structural confidence and disorder scores. Utilizing a comprehensive dataset from the Protein Data Bank (PDB), residues were categorized as "modeled", "hard missing" and "soft missing" based on their visibility in structural datasets. Key features were determined, including a confidence score predicted local distance difference test (pLDDT) from AlphaFold2, an advanced structural prediction tool, and a disorder score from IUPred, a traditional disorder prediction method. To enhance prediction performance for unstructured residues, we employed a Long Short-Term Memory (LSTM) model, integrating both scores with amino acid sequences. Notable patterns such as composition, region lengths and prediction scores were observed in unstructured residues and regions identified through structural experiments over our studied period. Our findings also indicate that "hard missing" residues often align with low confidence scores, whereas "soft missing" residues exhibit dynamic behavior that can complicate predictions. The incorporation of pLDDT, IUPred scores, and sequence data into the LSTM model has improved the differentiation between structured and unstructured residues, particularly for shorter unstructured regions. This research elucidates the relationship between established computational predictions and experimental structural data, enhancing our ability to target structurally significant areas for research and guiding experimental designs toward functionally relevant regions.

Macromolecular and cytological changes in fission yeast G0 nuclei

When starved of nitrogen, cells of the fission yeast Schizosaccharomyces pombe enter a quiescent 'G0' state with smaller nuclei and transcriptional repression. The genomics of S. pombe G0 cells has been well studied, but much of its nuclear cell biology remains unknown. Here, we use confocal microscopy, immunoblots and electron cryotomography to investigate the cytological, biochemical and ultrastructural differences between S. pombe proliferating, G1-arrested and G0 cell nuclei, with an emphasis on the histone acetylation, RNA polymerase II fates and macromolecular complex packing. Compared to proliferating cells, G0 cells have lower levels of histone acetylation, nuclear RNA polymerase II and active transcription. The G0 nucleus has similar macromolecular crowding yet fewer chromatin-associated multi-megadalton globular complexes. Induced histone hyperacetylation during nitrogen starvation results in cells that have larger nuclei and therefore chromatin that is less compact. However, these histone-hyperacetylated cells remain transcriptionally repressed with similar nuclear crowding. Canonical nucleosomes - those that resemble the crystal structure - are rare in proliferating, G1-arrested and G0 cells. Our study therefore shows that extreme changes in nucleus physiology are possible without extreme reorganization at the macromolecular level.

Advances in Axial Resolution Strategies for Super-Resolution Imaging Systems

3D fluorescence super-resolution imaging technology can reconstruct the 3D structure of biological cells in space, which is crucial for observing the intricate internal structures of cells and studying the organization and function of tissues and organs. However, even with super-resolution imaging techniques that surpass the diffraction limit, the axial resolution typically only reaches one-third to one-half of the lateral resolution. Achieving true axial or 3D super-resolution imaging of samples remains a significant challenge. In light of this, this review summarizes the research progress in axial super-resolution imaging techniques, with a focus on the principles, developments, and characteristics of these techniques, and provides an outlook on their future development directions. This paper aims to provide valuable reference material for researchers in the field.

Rapid structural analysis of bacterial ribosomes in situ

Rapid structural analysis of purified proteins and their complexes has become increasingly common thanks to key methodological advances in cryo-electron microscopy (cryo-EM) and associated data processing software packages. In contrast, analogous structural analysis in cells via cryo-electron tomography (cryo-ET) remains challenging due to critical technical bottlenecks, including low-throughput sample preparation and imaging, and laborious data processing methods. Here, we describe a rapid in situ cryo-ET sample preparation and data analysis workflow that results in the routine determination of sub-nm resolution ribosomal structures. We apply this workflow to E. coli, producing a 5.8 Å structure of the 70S ribosome from cells in less than 10 days and facilitating the discovery of a minor population of 100S-like disomes. We envision our approach to be widely applicable to related bacterial samples.

Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix

The extracellular matrix (ECM) serves as a scaffold for cells and plays an essential role in regulating numerous cellular processes, including cell migration and proliferation. Due to limitations in specimen preparation for conventional room-temperature electron microscopy, we lack structural knowledge on how ECM components are secreted, remodeled, and interact with surrounding cells. We have developed a 3D-ECM platform compatible with sample thinning by cryo-focused ion beam milling, the lift-out extraction procedure, and cryo-electron tomography. Our workflow implements cell-derived matrices (CDMs) grown on EM grids, resulting in a versatile tool closely mimicking ECM environments. This allows us to visualize ECM for the first time in its hydrated, native context. Our data reveal an intricate network of extracellular fibers, their positioning relative to matrix-secreting cells, and previously unresolved structural entities. Our workflow and results add to the structural atlas of the ECM, providing novel insights into its secretion and assembly.

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

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

Monitoring Drug-Protein Interactions in the Bacterial Periplasm by Solution Nuclear Magnetic Resonance Spectroscopy

The rapid spread of antimicrobial resistance across bacterial pathogens poses a serious risk to the efficacy and sustainability of available treatments. This puts pressure on research concerning the development of new drugs. Here, we present an in-cell NMR-based research strategy to monitor the activity of the enzymes located in the periplasmic space delineated by the inner and outer membranes of Gram-negative bacteria. We demonstrate its unprecedented analytical power in monitoring in situ and in real time (i) the hydrolysis of β-lactams by β-lactamases, (ii) the interaction of drugs belonging to the β-lactam family with their essential targets, and (iii) the binding of inhibitors to these enzymes. We show that in-cell NMR provides a powerful analytical tool for investigating new drugs targeting the molecular components of the bacterial periplasm.

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

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

Rapid structural analysis of bacterial ribosomes in situ

Rapid structural analysis of purified proteins and their complexes has become increasingly common thanks to key methodological advances in cryo-electron microscopy (cryo-EM) and associated data processing software packages. In contrast, analogous structural analysis in cells via cryo-electron tomography (cryo-ET) remains challenging due to critical technical bottlenecks, including low-throughput sample preparation and imaging, and laborious data processing methods. Here, we describe the development of a rapid in situ cryo-ET sample preparation and data analysis workflow that results in the routine determination of sub-nm resolution ribosomal structures. We apply this workflow to E. coli, producing a 5.8 Å structure of the 70S ribosome from cells in less than 10 days, and we expect this workflow will be widely applicable to related bacterial samples.

Advanced Techniques for Detecting Protein Misfolding and Aggregation in Cellular Environments

Protein misfolding and aggregation, a key contributor to the progression of numerous neurodegenerative diseases, results in functional deficiencies and the creation of harmful intermediates. Detailed visualization of this misfolding process is of paramount importance for improving our understanding of disease mechanisms and for the development of potential therapeutic strategies. While in vitro studies using purified proteins have been instrumental in delivering significant insights into protein misfolding, the behavior of these proteins in the complex milieu of living cells often diverges significantly from such simplified environments. Biomedical imaging performed in cell provides cellular-level information with high physiological and pathological relevance, often surpassing the depth of information attainable through in vitro methods. This review highlights a variety of methodologies used to scrutinize protein misfolding within biological systems. This includes optical-based methods, strategies leaning on mass spectrometry, in-cell nuclear magnetic resonance, and cryo-electron microscopy. Recent advancements in these techniques have notably deepened our understanding of protein misfolding processes and the features of the resulting misfolded species within living cells. The progression in these fields promises to catalyze further breakthroughs in our comprehension of neurodegenerative disease mechanisms and potential therapeutic interventions.

Correlative montage parallel array cryo-tomography for in situ structural cell biology

Imaging large fields of view while preserving high-resolution structural information remains a challenge in low-dose cryo-electron tomography. Here we present robust tools for montage parallel array cryo-tomography (MPACT) tailored for vitrified specimens. The combination of correlative cryo-fluorescence microscopy, focused-ion-beam milling, substrate micropatterning, and MPACT supports studies that contextually define the three-dimensional architecture of cells. To further extend the flexibility of MPACT, tilt series may be processed in their entirety or as individual tiles suitable for sub-tomogram averaging, enabling efficient data processing and analysis.

Finding Nano-Ötzi: Cryo-Electron Tomography Visualization Guided by Learned Segmentation

Cryo-electron tomography (cryo-ET) is a new 3D imaging technique with unprecedented potential for resolving submicron structural details. Existing volume visualization methods, however, are not able to reveal details of interest due to low signal-to-noise ratio. In order to design more powerful transfer functions, we propose leveraging soft segmentation as an explicit component of visualization for noisy volumes. Our technical realization is based on semi-supervised learning, where we combine the advantages of two segmentation algorithms. First, the weak segmentation algorithm provides good results for propagating sparse user-provided labels to other voxels in the same volume and is used to generate dense pseudo-labels. Second, the powerful deep-learning-based segmentation algorithm learns from these pseudo-labels to generalize the segmentation to other unseen volumes, a task that the weak segmentation algorithm fails at completely. The proposed volume visualization uses deep-learning-based segmentation as a component for segmentation-aware transfer function design. Appropriate ramp parameters can be suggested automatically through frequency distribution analysis. Furthermore, our visualization uses gradient-free ambient occlusion shading to further suppress the visual presence of noise, and to give structural detail the desired prominence. The cryo-ET data studied in our technical experiments are based on the highest-quality tilted series of intact SARS-CoV-2 virions. Our technique shows the high impact in target sciences for visual data analysis of very noisy volumes that cannot be visualized with existing techniques.

Big data in contemporary electron microscopy: challenges and opportunities in data transfer, compute and management

The second decade of the twenty-first century witnessed a new challenge in the handling of microscopy data. Big data, data deluge, large data, data compliance, data analytics, data integrity, data interoperability, data retention and data lifecycle are terms that have introduced themselves to the electron microscopy sciences. This is largely attributed to the booming development of new microscopy hardware tools. As a result, large digital image files with an average size of one terabyte within one single acquisition session is not uncommon nowadays, especially in the field of cryogenic electron microscopy. This brings along numerous challenges in data transfer, compute and management. In this review, we will discuss in detail the current state of international knowledge on big data in contemporary electron microscopy and how big data can be transferred, computed and managed efficiently and sustainably. Workflows, solutions, approaches and suggestions will be provided, with the example of the latest experiences in Australia. Finally, important principles such as data integrity, data lifetime and the FAIR and CARE principles will be considered.

Selecting optimal support grids for super-resolution cryogenic correlated light and electron microscopy

Cryogenic transmission electron microscopy (cryo-TEM) and super-resolution fluorescence microscopy are two popular and ever improving methods for high-resolution imaging of biological samples. In recent years, the combination of these two techniques into one correlated workflow has gained attention as a promising route towards contextualizing and enriching cryo-TEM imagery. A problem that is often encountered in the combination of these methods is that of light-induced damage to the sample during fluorescence imaging that renders the sample structure unsuitable for TEM imaging. In this paper, we describe how absorption of light by TEM sample support grids leads to sample damage, and we systematically explore the importance of parameters of grid design. We explain how, by changing the grid geometry and materials, one can increase the maximum illumination power density in fluorescence microscopy by up to an order of magnitude. Finally, we demonstrate the significant improvements in super-resolution image quality that are enabled by the selection of support grids that are optimally suited for correlated cryo-microscopy.

Site-Specific Fluorescent Labeling of Hemagglutinin-Specific Antigen Binding Fragment through Amine Chemistry Revealed by Mass Spectrometry

To capture the structure of assembled hemagglutinin (HA) nanoparticles at single-particle resolution, HA-specific antigen binding fragments (Fabs) were labeled by fluorescent (FLR) dyes as probes to highlight the HA trimers displayed on the assembled tetravalent HA nanoparticles for a qualitative localization microscopic study. The FLR dyes were conjugated to the Fabs through N-hydroxysuccinimide (NHS) ester mediated amine coupling chemistry. The labeling profile, including labeling ratio, distribution, and site-specific labeling occupancy, can affect the imaging results and introduce inconsistency. To evaluate the labeling profile so as to evaluate the labeling efficiency, a combination of intact mass measurement by MALDI-MS and peptide mapping through LC-MS/MS was implemented. At the intact molecular level, the labeling ratio and distribution were determined. Through peptide mapping, the labeled residues were identified and the corresponding site-specific labeling occupancy was measured. A systematic comparative investigation of four different FLR-labeled 1H01-Fabs (generated from H1 strain HA specific mAb 1H01) allowed accurate profiling of the labeling pattern. The data indicate that the labeling was site-specific and semiquantitative. This warrants the consistency of single-particle fluorescent imaging experiments and allows a further imaging characterization of the single nanoparticles.

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.

Are extraordinary nucleosome structures more ordinary than we thought?

The nucleosome is a DNA-protein assembly that is the basic unit of chromatin. A nucleosome can adopt various structures. In the canonical nucleosome structure, 145-147 bp of DNA is wrapped around a histone heterooctamer. The strong histone-DNA interactions cause the DNA to be inaccessible for nuclear processes such as transcription. Therefore, the canonical nucleosome structure has to be altered into different, non-canonical structures to increase DNA accessibility. While it is recognised that non-canonical structures do exist, these structures are not well understood. In this review, we discuss both the evidence for various non-canonical nucleosome structures in the nucleus and the factors that are believed to induce these structures. The wide range of non-canonical structures is likely to regulate the amount of accessible DNA, and thus have important nuclear functions.

Graph identification of proteins in tomograms (GRIP-Tomo)

In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases for refinement. We hypothesized that the topological connectivity of protein structures is invariant, and they are distinctive for the purpose of protein identification from distorted data presented in volume densities. Three-dimensional densities of a protein or a complex from simulated tomographic volumes were transformed into mathematical graphs as observables. We systematically introduced data distortion or defects such as missing fullness of data, the tumbling effect, and the missing wedge effect into the simulated volumes, and varied the distance cutoffs in pixels to capture the varying connectivity between the density cluster centroids in the presence of defects. A similarity score between the graphs from the simulated volumes and the graphs transformed from the physical protein structures in point data was calculated by comparing their network theory order parameters including node degrees, betweenness centrality, and graph densities. By capturing the essential topological features defining the heterogeneous morphologies of a network, we were able to accurately identify proteins and homo-multimeric complexes from 10 topologically distinctive samples without realistic noise added. Our approach empowers future developments of tomogram processing by providing pattern mining with interpretability, to enable the classification of single-domain protein native topologies as well as distinct single-domain proteins from multimeric complexes within noisy volumes.

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.

Poxvirus under the eyes of electron microscope

Zoonotic poxvirus infections pose significant threat to human health as we have witnessed recent spread of monkeypox. Therefore, insights into molecular mechanism behind poxvirus replication cycle are needed for the development of efficient antiviral strategies. Virion assembly is one of the key steps that determine the fate of replicating poxviruses. However, in-depth understanding of poxvirus assembly is challenging due to the complex nature of multi-step morphogenesis and heterogeneous virion structures. Despite these challenges, decades of research have revealed virion morphologies at various maturation stages, critical protein components and interactions with host cell compartments. Transmission electron microscopy has been employed as an indispensable tool for the examination of virion morphology, and more recently for the structure determination of protein complexes. In this review, we describe some of the major findings in poxvirus morphogenesis and the contributions of continuously advancing electron microscopy techniques.

Strategies for picking membrane-associated particles within subtomogram averaging workflows

Cryo-electron tomography (cryo-ET) with subtomogram averaging (STA) has emerged as a key tool for determining macromolecular structure(s) in vitro and in situ. However, processing cryo-ET data with STA currently requires significant user expertise. Recent efforts have streamlined several steps in STA workflows; however, particle picking remains a time-consuming bottleneck for many projects and requires considerable user input. Here, we present several strategies for the time-efficient and accurate picking of membrane-associated particles using the COPII inner coat as a case study. We also discuss a range of particle cleaning solutions to remove both poor quality and false-positive particles from STA datasets. We provide a step-by-step guide and the necessary scripts for users to independently carry out the particle picking and cleaning strategies discussed.

Artificial Intelligence in Cryo-Electron Microscopy

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

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

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

Revealing bacterial cell biology using cryo-electron tomography

Visualizing macromolecules inside bacteria at a high spatial resolution has remained a challenge owing to their small size and limited resolution of optical microscopy techniques. Recent advances in cryo-electron tomography (cryo-ET) imaging methods have revealed the spatial and temporal assemblies of many macromolecules involved in different cellular processes in bacteria at a resolution of a few nanometers in their native milieu. Specifically, the application of cryo-focused ion beam (cryo-FIB) milling to thin bacterial specimens makes them amenable for high-resolution cryo-ET data collection. In this review, we highlight recent research in three emerging areas of bacterial cell biology that have benefited from the cryo-FIB-ET technology - cytoskeletal filament assembly, intracellular organelles, and multicellularity.

Reconstitution of kinetochore motility and microtubule dynamics reveals a role for a kinesin-8 in establishing end-on attachments

During mitosis, individual microtubules make attachments to chromosomes via a specialized protein complex called the kinetochore to faithfully segregate the chromosomes to daughter cells. Translocation of kinetochores on the lateral surface of the microtubule has been proposed to contribute to high fidelity chromosome capture and alignment at the mitotic midzone, but has been difficult to observe in vivo because of spatial and temporal constraints. To overcome these barriers, we used total internal reflection fluorescence (TIRF) microscopy to track the interactions between microtubules, kinetochore proteins, and other microtubule-associated proteins in lysates from metaphase-arrested Saccharomyces cerevisiae. TIRF microscopy and cryo-correlative light microscopy and electron tomography indicated that we successfully reconstituted interactions between intact kinetochores and microtubules. These kinetochores translocate on the lateral microtubule surface toward the microtubule plus end and transition to end-on attachment, whereupon microtubule depolymerization commences. The directional kinetochore movement is dependent on the highly processive kinesin-8, Kip3. We propose that Kip3 facilitates stable kinetochore attachment to microtubule plus ends through its abilities to move the kinetochore laterally on the surface of the microtubule and to regulate microtubule plus end dynamics.

Exploring high-resolution cryo-ET and subtomogram averaging capabilities of contemporary DEDs

The potential of energy filtering and direct electron detection for cryo-electron microscopy (cryo-EM) has been well documented. Here, we assess the performance of recently introduced hardware for cryo-electron tomography (cryo-ET) and subtomogram averaging (STA), an increasingly popular structural determination method for complex 3D specimens. We acquired cryo-ET datasets of EIAV virus-like particles (VLPs) on two contemporary cryo-EM systems equipped with different energy filters and direct electron detectors (DED), specifically a Krios G4, equipped with a cold field emission gun (CFEG), Thermo Fisher Scientific Selectris X energy filter, and a Falcon 4 DED; and a Krios G3i, with a Schottky field emission gun (XFEG), a Gatan Bioquantum energy filter, and a K3 DED. We performed constrained cross-correlation-based STA on equally sized datasets acquired on the respective systems. The resulting EIAV CA hexamer reconstructions show that both systems perform comparably in the 4-6 Å resolution range based on Fourier-Shell correlation (FSC). In addition, by employing a recently introduced multiparticle refinement approach, we obtained a reconstruction of the EIAV CA hexamer at 2.9 Å. Our results demonstrate the potential of the new generation of energy filters and DEDs for STA, and the effects of using different processing pipelines on their STA outcomes.

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.

Microscopic Visualization of Cell-Cell Adhesion Complexes at Micro and Nanoscale

Considerable progress has been made in our knowledge of the morphological and functional varieties of anchoring junctions. Cell-cell adhesion contacts consist of discrete junctional structures responsible for the mechanical coupling of cytoskeletons and allow the transmission of mechanical signals across the cell collective. The three main adhesion complexes are adherens junctions, tight junctions, and desmosomes. Microscopy has played a fundamental role in understanding these adhesion complexes on different levels in both physiological and pathological conditions. In this review, we discuss the main light and electron microscopy techniques used to unravel the structure and composition of the three cell-cell contacts in epithelial and endothelial cells. It functions as a guide to pick the appropriate imaging technique(s) for the adhesion complexes of interest. We also point out the latest techniques that have emerged. At the end, we discuss the problems investigators encounter during their cell-cell adhesion research using microscopic techniques.

Interface refinement of low- to medium-resolution Cryo-EM complexes using HADDOCK2.4

A wide range of cellular processes requires the formation of multimeric protein complexes. The rise of cryo-electron microscopy (cryo-EM) has enabled the structural characterization of these protein assemblies. The density maps produced can, however, still suffer from limited resolution, impeding the process of resolving structures at atomic resolution. In order to solve this issue, monomers can be fitted into low- to medium-resolution maps. Unfortunately, the models produced frequently contain atomic clashes at the protein-protein interfaces (PPIs), as intermolecular interactions are typically not considered during monomer fitting. Here, we present a refinement approach based on HADDOCK2.4 to remove intermolecular clashes and optimize PPIs. A dataset of 14 cryo-EM complexes was used to test eight protocols. The best-performing protocol, consisting of a semi-flexible simulated annealing refinement with centroid restraints on the monomers, was able to decrease intermolecular atomic clashes by 98% without significantly deteriorating the quality of the cryo-EM density fit.

Structure Determination of Microtubules and Pili: Past, Present, and Future Directions

Historically proteins that form highly polymeric and filamentous assemblies have been notoriously difficult to study using high resolution structural techniques. This has been due to several factors that include structural heterogeneity, their large molecular mass, and available yields. However, over the past decade we are now seeing a major shift towards atomic resolution insight and the study of more complex heterogenous samples and in situ/ex vivo examination of multi-subunit complexes. Although supported by developments in solid state nuclear magnetic resonance spectroscopy (ssNMR) and computational approaches, this has primarily been due to advances in cryogenic electron microscopy (cryo-EM). The study of eukaryotic microtubules and bacterial pili are good examples, and in this review, we will give an overview of the technical innovations that have enabled this transition and highlight the advancements that have been made for these two systems. Looking to the future we will also describe systems that remain difficult to study and where further technical breakthroughs are required.

Nanometer-Scale Molecular Mapping by Super-resolution Fluorescence Microscopy

The structural organization of macromolecules and their association in assemblies and organelles is key to understand cellular function. Super-resolution fluorescence microscopy has expanded our toolbox for examining such nanometer-scale cellular structures, by enabling positional mapping of proteins in situ. Here, we detail the workflow to build nanometer-scale maps focusing on two complementary super-resolution modalities: structured illumination microscopy (SIM) and stochastic optical reconstruction microscopy (STORM).

Elusive structure of mammalian DGKs

Mammalian diacylglycerol kinases (DGKs) are a group of enzymes that catalyze the ATP-dependent phosphorylation of diacylglycerol (DAG) to produce phosphatidic acid (PtdOH). In doing so, they modulate the levels of these two important signaling lipids. Currently, ten mammalian DGKs are organized into five classes that vary with respect to domain organization, regulation, and cellular/subcellular distribution. As lipids play critical roles in cells, it is not surprising that there is increasing interest in understanding the mechanism underlying the catalysis and regulation of lipid modulating enzymes such as DGKs. However, there are no solved 3D structures for any of the eukaryotic DGKs. In this review, we summarize what is known and the current challenges in determining the structures of these important enzymes. In addition to gain critical insights into their mechanisms of catalysis and regulation, DGK structures will provide a platform for the design of isoform specific inhibitors.

Leveraging crosslinking mass spectrometry in structural and cell biology

Crosslinking mass spectrometry (crosslinking-MS) is a versatile tool providing structural insights into protein conformation and protein-protein interactions. Its medium-resolution residue-residue distance restraints have been used to validate protein structures proposed by other methods and have helped derive models of protein complexes by integrative structural biology approaches. The use of crosslinking-MS in integrative approaches is underpinned by progress in estimating error rates in crosslinking-MS data and in combining these data with other information. The flexible and high-throughput nature of crosslinking-MS has allowed it to complement the ongoing resolution revolution in electron microscopy by providing system-wide residue-residue distance restraints, especially for flexible regions or systems. Here, we review how crosslinking-MS information has been leveraged in structural model validation and integrative modeling. Crosslinking-MS has also been a key technology for cell biology studies and structural systems biology where, in conjunction with cryoelectron tomography, it can provide structural and mechanistic insights directly in situ.

Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data

A precise quantitative description of the ultrastructural characteristics underlying biological mechanisms is often key to their understanding. This is particularly true for dynamic extra- and intracellular filamentous assemblies, playing a role in cell motility, cell integrity, cytokinesis, tissue formation and maintenance. For example, genetic manipulation or modulation of actin regulatory proteins frequently manifests in changes of the morphology, dynamics, and ultrastructural architecture of actin filament-rich cell peripheral structures, such as lamellipodia or filopodia. However, the observed ultrastructural effects often remain subtle and require sufficiently large datasets for appropriate quantitative analysis. The acquisition of such large datasets has been enabled by recent advances in high-throughput cryo-electron tomography (cryo-ET) methods. This also necessitates the development of complementary approaches to maximize the extraction of relevant biological information. We have developed a computational toolbox for the semi-automatic quantification of segmented and vectorized filamentous networks from pre-processed cryo-electron tomograms, facilitating the analysis and cross-comparison of multiple experimental conditions. GUI-based components simplify the processing of data and allow users to obtain a large number of ultrastructural parameters describing filamentous assemblies. We demonstrate the feasibility of this workflow by analyzing cryo-ET data of untreated and chemically perturbed branched actin filament networks and that of parallel actin filament arrays. In principle, the computational toolbox presented here is applicable for data analysis comprising any type of filaments in regular (i.e. parallel) or random arrangement. We show that it can ease the identification of key differences between experimental groups and facilitate the in-depth analysis of ultrastructural data in a time-efficient manner.

Approximating deformation fields for the analysis of continuous heterogeneity of biological macromolecules by 3D Zernike polynomials

Structural biology has evolved greatly due to the advances introduced in fields like electron microscopy. This image-capturing technique, combined with improved algorithms and current data processing software, allows the recovery of different conformational states of a macromolecule, opening new possibilities for the study of its flexibility and dynamic events. However, the ensemble analysis of these different conformations, and in particular their placement into a common variable space in which the differences and similarities can be easily recognized, is not an easy matter. To simplify the analysis of continuous heterogeneity data, this work proposes a new automatic algorithm that relies on a mathematical basis defined over the sphere to estimate the deformation fields describing conformational transitions among different structures. Thanks to the approximation of these deformation fields, it is possible to describe the forces acting on the molecules due to the presence of different motions. It is also possible to represent and compare several structures in a low-dimensional mapping, which summarizes the structural characteristics of different states. All these analyses are integrated into a common framework, providing the user with the ability to combine them seamlessly. In addition, this new approach is a significant step forward compared with principal component analysis and normal mode analysis of cryo-electron microscopy maps, avoiding the need to select components or modes and producing localized analysis.

End-to-end robust joint unsupervised image alignment and clustering

Computing dense pixel-to-pixel image correspondences is a fundamental task of computer vision. Often, the objective is to align image pairs from the same semantic category for manipulation or segmentation purposes. Despite achieving superior performance, existing deep learning alignment methods cannot cluster images; consequently, clustering and pairing images needed to be a separate laborious and expensive step. Given a dataset with diverse semantic categories, we propose a multi-task model, Jim-Net, that can directly learn to cluster and align images without any pixel-level or image-level annotations. We design a pair-matching alignment unsupervised training algorithm that selectively matches and aligns image pairs from the clustering branch. Our unsupervised Jim-Net achieves comparable accuracy with state-of-the-art supervised methods on benchmark 2D image alignment dataset PF-PASCAL. Specifically, we apply Jim-Net to cryo-electron tomography, a revolutionary 3D microscopy imaging technique of native subcellular structures. After extensive evaluation on seven datasets, we demonstrate that Jim-Net enables systematic discovery and recovery of representative macromolecular structures in situ, which is essential for revealing molecular mechanisms underlying cellular functions. To our knowledge, Jim-Net is the first end-to-end model that can simultaneously align and cluster images, which significantly improves the performance as compared to performing each task alone.

A Structural Perspective of the Role of IP6 in Immature and Mature Retroviral Assembly

The small cellular molecule inositol hexakisphosphate (IP6) has been known for ~20 years to promote the in vitro assembly of HIV-1 into immature virus-like particles. However, the molecular details underlying this effect have been determined only recently, with the identification of the IP6 binding site in the immature Gag lattice. IP6 also promotes formation of the mature capsid protein (CA) lattice via a second IP6 binding site, and enhances core stability, creating a favorable environment for reverse transcription. IP6 also enhances assembly of other retroviruses, from both the Lentivirus and the Alpharetrovirus genera. These findings suggest that IP6 may have a conserved function throughout the family Retroviridae. Here, we discuss the different steps in the viral life cycle that are influenced by IP6, and describe in detail how IP6 interacts with the immature and mature lattices of different retroviruses.

Structure and dynamics of photoreceptor sensory cilia

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

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

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

Cryo-Focused Ion Beam Lamella Preparation Protocol for in Situ Structural Biology

The advances in electron cryo-microscopy have enabled high-resolution structural studies of vitrified macromolecular complexes in situ by cryo-electron tomography (cryo-ET). Since utilization of cryo-ET is generally limited to the specimens with thickness < 500 nm, a complex sample preparation protocol to study larger samples such as single eukaryotic cells by cryo-ET was developed and optimized over the last decade. The workflow is based on the preparation of a thin cellular lamella by cryo-focused ion beam milling (cryo-FIBM) from the vitrified cells. The sample preparation protocol is a multi-step process which includes utilization of several high-end instruments and comprises sample manipulation prone to sample deterioration. Here, we present a workflow for preparation of three different model specimens that was optimized to provide high-quality lamellae for cryo-ET or electron diffraction tomography with high reproducibility. Preparation of lamellae from large adherent mammalian cells, small suspension eukaryotic cell line, and protein crystals of intermediate size is described which represents examples of the most frequently studied samples used for cryo-FIBM in life sciences.

A flexible framework for multi-particle refinement in cryo-electron tomography

Cryo-electron tomography (cryo-ET) and subtomogram averaging (STA) are increasingly used for macromolecular structure determination in situ. Here, we introduce a set of computational tools and resources designed to enable flexible approaches to STA through increased automation and simplified metadata handling. We create a bidirectional interface between the Dynamo software package and the Warp-Relion-M pipeline, providing a framework for ab initio and geometrical approaches to multiparticle refinement in M. We illustrate the power of working within this framework by applying it to EMPIAR-10164, a publicly available dataset containing immature HIV-1 virus-like particles (VLPs), and a challenging in situ dataset containing chemosensory arrays in bacterial minicells. Additionally, we provide a comprehensive, step-by-step guide to obtaining a 3.4-Å reconstruction from EMPIAR-10164. The guide is hosted on https://teamtomo.org/, a collaborative online platform we establish for sharing knowledge about cryo-ET.

Patterns in Nature—S-Layer Lattices of Bacterial and Archaeal Cells

Bacterial surface layers (S-layers) have been observed as the outermost cell envelope component in a wide range of bacteria and most archaea. S-layers are monomolecular lattices composed of a single protein or glycoprotein species and have either oblique, square or hexagonal lattice symmetry with unit cell dimensions ranging from 3 to 30 nm. They are generally 5 to 10 nm thick (up to 70 nm in archaea) and represent highly porous protein lattices (30–70% porosity) with pores of uniform size and morphology in the range of 2 to 8 nm. Since S-layers can be considered as one of the simplest protein lattices found in nature and the constituent units are probably the most abundantly expressed proteins on earth, it seems justified to briefly review the different S-layer lattice types, the need for lattice imperfections and the discussion of S-layers from the perspective of an isoporous protein network in the ultrafiltration region. Finally, basic research on S-layers laid the foundation for applications in biotechnology, synthetic biology, and biomimetics.

Assessing the Role of Lipids in the Molecular Mechanism of Membrane Proteins

Membrane proteins have evolved to work optimally within the complex environment of the biological membrane. Consequently, interactions with surrounding lipids are part of their molecular mechanism. Yet, the identification of lipid-protein interactions and the assessment of their molecular role is an experimental challenge. Recently, biophysical approaches have emerged that are compatible with the study of membrane proteins in an environment closer to the biological membrane. These novel approaches revealed specific mechanisms of regulation of membrane protein function. Lipids have been shown to play a role in oligomerization, conformational transitions or allosteric coupling. In this review, we summarize the recent biophysical approaches, or combination thereof, that allow to decipher the role of lipid-protein interactions in the mechanism of membrane proteins.

Where in the cell is my protein?

The application of cryo-correlative light and cryo-electron microscopy (cryo-CLEM) gives us a way to locate structures of interest in the electron microscope. In brief, the structures of interest are fluorescently tagged, and images from the cryo-fluorescent microscope (cryo-FM) maps are superimposed on those from the cryo-electron microscope (cryo-EM). By enhancing cryo-FM to include single-molecule localization microscopy (SMLM), we can achieve much better localization. The introduction of cryo-SMLM increased the yield of photons from fluorophores, which can benefit localization efforts. Dahlberg and Moerner (2021, Annual Review of Physical Chemistry, 72, 253-278) have a recent broad and elegant review of super-resolution cryo-CLEM. This paper focuses on cryo(F)PALM/STORM for the cryo-electron tomography community. I explore the current challenges to increase the accuracy of localization by SMLM and the mapping of those positions onto cryo-EM images and maps. There is much to consider: we need to know if the excitation of fluorophores damages the structures we seek to visualize. We need to determine if higher numerical aperture (NA) objectives, which add complexity to image analysis but increase resolution and the efficiency of photon collection, are better than lower NA objectives, which pose fewer problems. We need to figure out the best way to determine the axial position of fluorophores. We need to have better ways of aligning maps determined by FM with those determined by EM. We need to improve the instrumentation to be easier to use, more accurate, and ice-contamination free. The bottom line is that we have more work to do.

Current data processing strategies for cryo-electron tomography and subtomogram averaging

Cryo-electron tomography (cryo-ET) can be used to reconstruct three-dimensional (3D) volumes, or tomograms, from a series of tilted two-dimensional images of biological objects in their near-native states in situ or in vitro. 3D subvolumes, or subtomograms, containing particles of interest can be extracted from tomograms, aligned, and averaged in a process called subtomogram averaging (STA). STA overcomes the low signal to noise ratio within the individual subtomograms to generate structures of the particle(s) of interest. In recent years, cryo-ET with STA has increasingly been capable of reaching subnanometer resolution due to improvements in microscope hardware and data processing strategies. There has also been an increase in the number and quality of software packages available to process cryo-ET data with STA. In this review, we describe and assess the data processing strategies available for cryo-ET data and highlight the recent software developments which have enabled the extraction of high-resolution information from cryo-ET datasets.

Challenges in solving structures from radiation-damaged tomograms of protein nanocrystals assessed by simulation

Structure-determination methods are needed to resolve the atomic details that underlie protein function. X-ray crystallography has provided most of our knowledge of protein structure, but is constrained by the need for large, well ordered crystals and the loss of phase information. The rapidly developing methods of serial femtosecond crystallography, micro-electron diffraction and single-particle reconstruction circumvent the first of these limitations by enabling data collection from nanocrystals or purified proteins. However, the first two methods also suffer from the phase problem, while many proteins fall below the molecular-weight threshold required for single-particle reconstruction. Cryo-electron tomography of protein nanocrystals has the potential to overcome these obstacles of mainstream structure-determination methods. Here, a data-processing scheme is presented that combines routines from X-ray crystallography and new algorithms that have been developed to solve structures from tomograms of nanocrystals. This pipeline handles image-processing challenges specific to tomographic sampling of periodic specimens and is validated using simulated crystals. The tolerance of this workflow to the effects of radiation damage is also assessed. The simulations indicate a trade-off between a wider tilt range to facilitate merging data from multiple tomograms and a smaller tilt increment to improve phase accuracy. Since phase errors, but not merging errors, can be overcome with additional data sets, these results recommend distributing the dose over a wide angular range rather than using a finer sampling interval to solve the protein structure.

Membrane imaging in the plant endomembrane system

Recent studies on membrane imaging in the plant endomembrane system by 2-D/3-D CLSM and TEM provide future perspectives of whole-cell ET and cryo-FIB-aided cryo-ET analysis.

Assessment of scoring functions to rank the quality of 3D subtomogram clusters from cryo-electron tomography

Cryo-electron tomography provides the opportunity for unsupervised discovery of endogenous complexes in situ. This process usually requires particle picking, clustering and alignment of subtomograms to produce an average structure of the complex. When applied to heterogeneous samples, template-free clustering and alignment of subtomograms can potentially lead to the discovery of structures for unknown endogenous complexes. However, such methods require scoring functions to measure and accurately rank the quality of aligned subtomogram clusters, which can be compromised by contaminations from misclassified complexes and alignment errors. Here, we provide the first study to assess the effectiveness of more than 15 scoring functions for evaluating the quality of subtomogram clusters, which differ in the amount of structural misalignments and contaminations due to misclassified complexes. We assessed both experimental and simulated subtomograms as ground truth data sets. Our analysis showed that the robustness of scoring functions varies largely. Most scores were sensitive to the signal-to-noise ratio of subtomograms and often required Gaussian filtering as preprocessing for improved performance. Two scoring functions, Spectral SNR-based Fourier Shell Correlation and Pearson Correlation in the Fourier domain with missing wedge correction, showed a robust ranking of subtomogram clusters without any preprocessing and irrespective of SNR levels of subtomograms. Of these two scoring functions, Spectral SNR-based Fourier Shell Correlation was fastest to compute and is a better choice for handling large numbers of subtomograms. Our results provide a guidance for choosing an accurate scoring function for template-free approaches to detect complexes from heterogeneous samples.

Cryo-EM as a tool to study bacterial efflux systems and the membrane proteome

Antibiotic resistance is an emerging threat to global health. Current treatment regimens for these types of bacterial infections are becoming increasingly inadequate. Thus, new innovative technologies are needed to help identify and characterize novel drugs and drug targets which are critical in order to combat multidrug-resistant bacterial strains. Bacterial efflux systems have emerged as an attractive target for drug design, as blocking their export function significantly increases the potency of administered antibiotics. However, in order to develop potent and tolerable efflux pump inhibitors with high efficacy, detailed structural information is required for both the apo- and substrate-bound forms of these membrane proteins. The emergence of cryo-electron microscopy (cryo-EM) has greatly advanced the field of membrane protein structural biology. It has significantly enhanced the ability to solve large multi-protein complexes as well as extract meaningful data from a heterogeneous sample, such as identification of several assembly states of the bacterial ribosome, from a single data set. This technique can be expanded to solve the structures of substrate-bound efflux pumps and entire efflux systems from previously unusable membrane protein sample preparations. Subsequently, cryo-EM combined with other biophysical techniques has the potential to markedly advance the field of membrane protein structural biology. The ability to discern complete transport machineries, enzymatic signal transduction pathways, and other membrane-associated complexes will help us fully understand the complexities of the membrane proteome.

Integrative approaches in cryogenic electron microscopy: Recent advances in structural biology and future perspectives

Cellular factories engage numerous highly complex "molecular machines" to perform pivotal biological functions. 3D structural visualization is an effective way to understand the functional mechanisms of these biomacromolecules. The "resolution revolution" has established cryogenic electron microscopy (cryo-EM) as a preferred structural biology tool. In parallel with the advances in cryo-EM methodologies aiming at atomic resolution, several innovative approaches have started emerging where other techniques are sensibly integrated with cryo-EM to obtain additional insights into the biological processes. For example, combining the time-resolved technique with high-resolution cryo-EM enables discerning structures of short-lived intermediates in the functional pathway of a biomolecule. Likewise, integrating mass spectrometry (MS) techniques with cryo-EM allows deciphering structural organizations of large molecular assemblies. Here, we discuss how the data generated upon combining either time resolve or MS techniques with cryo-EM supplement structural elucidations with in-depth understanding of the function of cellular macromolecules when they participate in fundamental biological processes.