High-confidence 3D template matching for cryo-electron tomography.

Visual proteomics attempts to build atlases of the molecular content of cells but the automated annotation of cryo electron tomograms remains challenging. Template matching (TM) and methods based on machine learning detect structural signatures of macromolecules. However, their applicability remains limited in terms of both the abundance and size of the molecular targets. Here we show that the performance of TM is greatly improved by using template-specific search parameter optimization and by including higher-resolution information. We establish a TM pipeline with systematically tuned parameters for the automated, objective and comprehensive identification of structures with confidence 10 to 100-fold above the noise level. We demonstrate high-fidelity and high-confidence localizations of nuclear pore complexes, vaults, ribosomes, proteasomes, fatty acid synthases, lipid membranes and microtubules, and individual subunits inside crowded eukaryotic cells. We provide software tools for the generic implementation of our method that is broadly applicable towards realizing visual proteomics.

Modeling and Simulation of the NMDA Receptor at Coarse-Grained and Atomistic Levels.

N-Methyl-D-aspartate (NMDA) receptors are glutamate-gated excitatory channels that play essential roles in brain functions. While high-resolution structures were solved for an allosterically inhibited form of functional NMDA receptor, other key functional states (particularly the active open-channel state) have not yet been resolved at atomic resolutions. To decrypt the molecular mechanism of the NMDA receptor activation, structural modeling and simulation are instrumental in providing detailed information about the dynamics and energetics of the receptor in various functional states. In this chapter, we describe coarse-grained modeling of the NMDA receptor using an elastic network model and related modeling/analysis tools (e.g., normal mode analysis, flexibility and hotspot analysis, cryo-EM flexible fitting, and transition pathway modeling) based on available structures. Additionally, we show how to build an atomistic model of the active-state receptor with targeted molecular dynamics (MD) simulation and explore its energetics and dynamics with conventional MD simulation. Taken together, these modeling and simulation can offer rich structural and dynamic information which will guide experimental studies of the activation of this key receptor.

How to apply the broad toolbox of correlative light and electron microscopy to address a specific biological question.

Correlative light and electron microscopy (CLEM) is an approach that combines the strength of multiple imaging techniques to obtain complementary information about a given specimen. The "toolbox" for CLEM is broad, making it sometimes difficult to choose an appropriate approach for a given biological question. In this chapter, we provide experimental details for three CLEM approaches that can help the interested reader in designing a personalized CLEM strategy for obtaining ultrastructural data by using transmission electron microscopy (TEM). First, we describe chemical fixation of cells grown on a solid support (broadest approach). Second, we apply high-pressure freezing/freeze substitution to describe cellular ultrastructure (cryo-immobilization approach). Third, we give a protocol for a ultrastructural labeling by immuno-electron microscopy (immuno-EM approach). In addition, we also describe how to overlay fluorescence and electron microscopy images, an approach that is applicable to each of the reported different CLEM strategies. Here we provide step-by step descriptions prior to discussing possible technical problems and variations of these three general schemes to suit different models or different biological questions. This chapter is written for electron microscopists that are new to CLEM and unsure how to begin. Therefore, our protocols are meant to provide basic information with further references that should help the reader get started with applying a tailored strategy for a specific CLEM experiment.

Building a super-resolution fluorescence cryomicroscope.

Correlated super-resolution fluorescence microscopy and cryo-electron microscopy enables imaging with both high labeling specificity and high resolution. Naturally, combining two sophisticated imaging techniques within one workflow also introduces new requirements on hardware, such as the need for a super-resolution fluorescence capable microscope that can be used to image cryogenic samples. In this chapter, we describe the design and use of the "cryoscope"; a microscope designed for single-molecule localization microscopy (SMLM) of cryoEM samples that fits right into established cryoEM workflows. We demonstrate the results that can be achieved with our microscope by imaging fluorescently labeled vimentin, an intermediate filament, within U2OS cells grown on EM grids, and we provide detailed 3d models that encompass the entire design of the microscope.

Imaging intracellular components in situ using super-resolution cryo-correlative light and electron microscopy.

Super-resolution cryo-correlative light and electron microscopy (SRcryoCLEM) is emerging as a powerful method to enable targeted in situ structural studies of biological samples. By combining the high specificity and localization accuracy of single-molecule localization microscopy (cryoSMLM) with the high resolution of cryo-electron tomography (cryoET), this method enables accurately targeted data acquisition and the observation and identification of biomolecules within their natural cellular context. Despite its potential, the adaptation of SRcryoCLEM has been hindered by the need for specialized equipment and expertise. In this chapter, we outline a workflow for cryoSMLM and cryoET-based SRcryoCLEM, and we demonstrate that, given the right tools, it is possible to incorporate cryoSMLM into an established cryoET workflow. Using Vimentin as an exemplary target of interest, we demonstrate all stages of an SRcryoCLEM experiment: performing cryoSMLM, targeting cryoET acquisition based on single-molecule localization maps, and correlation of cryoSMLM and cryoET datasets using scNodes, a software package dedicated to SRcryoCLEM. By showing how SRcryoCLEM enables the imaging of specific intracellular components in situ, we hope to facilitate adoption of the technique within the field of cryoEM.

Correlative cryo-microscopy pipelines for in situ cellular studies.

Correlative cryo-microscopy pipelines combining light and electron microscopy and tomography in cryogenic conditions (cryoCLEM) on the same sample are powerful methods for investigating the structure of specific cellular targets identified by a fluorescent tag within their unperturbed cellular environment. CryoCLEM approaches circumvent one of the inherent limitations of cryo EM, and specifically cryo electron tomography (cryoET), of identifying the imaged structures in the crowded 3D environment of cells. Whereas several cryoCLEM approaches are based on thinning the sample by cryo FIB milling, here we present detailed protocols of two alternative cryoCLEM approaches for in situ studies of adherent cells at the single-cell level without the need for such cryo-thinning. The first approach is a complete cryogenic pipeline in which both fluorescence and electronic imaging are performed on frozen-hydrated samples, the second is a hybrid cryoCLEM approach in which fluorescence imaging is performed at room temperature, followed by rapid freezing and subsequent cryoEM imaging. We provide a detailed description of the two methods we have employed for imaging fluorescently labeled cellular structures with thickness below 350-500nm, such as cell protrusions and organelles located in the peripheral areas of the cells.

Toward quantitative super-resolution methods for cryo-CLEM.

Cryogenic ultrastructural imaging techniques such as cryo-electron tomography have produced a revolution in how the structure of biological systems is investigated by enabling the determination of structures of protein complexes immersed in a complex biological matrix within vitrified cell and model organisms. However, so far, the portfolio of successes has been mostly limited to highly abundant complexes or to structures that are relatively unambiguous and easy to identify through electron microscopy. In order to realize the full potential of this revolution, researchers would have to be able to pinpoint lower abundance species and obtain functional annotations on the state of objects of interest which would then be correlated to ultrastructural information to build a complete picture of the structure-function relationships underpinning biological processes. Fluorescence imaging at cryogenic conditions has the potential to be able to meet these demands. However, wide-field images acquired at low numeric aperture (NA) using air immersion objective have a low resolving power and cannot provide accurate enough three-dimensional (3D) localization to enable the assignment of functional annotations to individual objects of interest or target sample debulking to ensure the preservation of the structures of interest. It is therefore necessary to develop super-resolved cryo-fluorescence workflows capable of fulfilling this role and enabling new biological discoveries. In this chapter, we present the current state of development of two super-resolution cryogenic fluorescence techniques, superSIL-STORM and astigmatism-based 3D STORM, show their application to a variety of biological systems and discuss their advantages and limitations. We further discuss the future applicability to cryo-CLEM workflows though examples of practical application to the study of membrane protein complexes both in mammalian cells and in Escherichia coli.

Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures.

The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structures of biological macromolecules and their complexes significantly expedite biomedical research and drug discovery. However, automatically and accurately building atomic models from high-resolution cryo-EM density maps is still time-consuming and challenging when template-based models are unavailable. Artificial intelligence (AI) methods such as deep learning trained on limited amount of labeled cryo-EM density maps generate inaccurate atomic models. To address this issue, we created a dataset called Cryo2StructData consisting of 7,600 preprocessed cryo-EM density maps whose voxels are labelled according to their corresponding known atomic structures for training and testing AI methods to build atomic models from cryo-EM density maps. Cryo2StructData is larger than existing, publicly available datasets for training AI methods to build atomic protein structures from cryo-EM density maps. We trained and tested deep learning models on Cryo2StructData to validate its quality showing that it is ready for being used to train and test AI methods for building atomic models.

Bridging structural and cell biology with cryo-electron microscopy.

Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.

New insights into the structure and dynamics of the TOM complex in mitochondria.

To date, there is no general physical model of the mechanism by which unfolded polypeptide chains with different properties are imported into the mitochondria. At the molecular level, it is still unclear how transit polypeptides approach, are captured by the protein translocation machinery in the outer mitochondrial membrane, and how they subsequently cross the entropic barrier of a protein translocation pore to enter the intermembrane space. This deficiency has been due to the lack of detailed structural and dynamic information about the membrane pores. In this review, we focus on the recently determined sub-nanometer cryo-EM structures and our current knowledge of the dynamics of the mitochondrial two-pore outer membrane protein translocation machinery (TOM core complex), which provide a starting point for addressing the above questions. Of particular interest are recent discoveries showing that the TOM core complex can act as a mechanosensor, where the pores close as a result of interaction with membrane-proximal structures. We highlight unusual and new correlations between the structural elements of the TOM complexes and their dynamic behavior in the membrane environment.

Determining Macromolecular Structures Using Cryo-Electron Microscopy.

Structural insights into macromolecular and protein complexes provide key clues about the molecular basis of the function. Cryogenic electron microscopy (cryo-EM) has emerged as a powerful structural biology method for studying protein and macromolecular structures at high resolution in both native and near-native states. Despite the ability to get detailed structural insights into the processes underlying protein function using cryo-EM, there has been hesitancy amongst plant biologists to apply the method for biomolecular interaction studies. This is largely evident from the relatively fewer structural depositions of proteins and protein complexes from plant origin in electron microscopy databank. Even though the progress has been slow, cryo-EM has significantly contributed to our understanding of the molecular biology processes underlying photosynthesis, energy transfer in plants, besides viruses infecting plants. This chapter introduces sample preparation for both negative-staining electron microscopy (NSEM) and cryo-EM for plant proteins and macromolecular complexes and data analysis using single particle analysis for beginners.

Swin-cryoEM: Multi-class cryo-electron micrographs single particle mixed detection method.

Cryo-electron micrograph images have various characteristics such as varying sizes, shapes, and distribution densities of individual particles, severe background noise, high levels of impurities, irregular shapes, blurred edges, and similar color to the background. How to demonstrate good adaptability in the field of image vision by picking up single particles from multiple types of cryo-electron micrographs is currently a challenge in the field of cryo-electron micrographs. This paper combines the characteristics of the MixUp hybrid enhancement algorithm, enhances the image feature information in the pre-processing stage, builds a feature perception network based on the channel self-attention mechanism in the forward network of the Swin Transformer model network, achieving adaptive adjustment of self-attention mechanism between different single particles, increasing the network's tolerance to noise, Incorporating PReLU activation function to enhance information exchange between pixel blocks of different single particles, and combining the Cross-Entropy function with the softmax function to construct a classification network based on Swin Transformer suitable for cryo-electron micrograph single particle detection model (Swin-cryoEM), achieving mixed detection of multiple types of single particles. Swin-cryoEM algorithm can better solve the problem of good adaptability in picking single particles of many types of cryo-electron micrographs, improve the accuracy and generalization ability of the single particle picking method, and provide high-quality data support for the three-dimensional reconstruction of a single particle. In this paper, ablation experiments and comparison experiments were designed to evaluate and compare Swin-cryoEM algorithms in detail and comprehensively on multiple datasets. The Average Precision is an important evaluation index of the evaluation model, and the optimal Average Precision reached 95.5% in the training stage Swin-cryoEM, and the single particle picking performance was also superior in the prediction stage. This model inherits the advantages of the Swin Transformer detection model and is superior to mainstream models such as Faster R-CNN and YOLOv5 in terms of the single particle detection capability of cryo-electron micrographs.

Thinner is not always better: Optimizing cryo-lamellae for subtomogram averaging.

Cryo-electron tomography (cryo-ET) is a powerful method to elucidate subcellular architecture and to structurally analyze biomolecules in situ by subtomogram averaging, yet data quality critically depends on specimen thickness. Cells that are too thick for transmission imaging can be thinned into lamellae by cryo-focused ion beam (cryo-FIB) milling. Despite being a crucial parameter directly affecting attainable resolution, optimal lamella thickness has not been systematically investigated nor the extent of structural damage caused by gallium ions used for FIB milling. We thus systematically determined how resolution is affected by these parameters. We find that ion-induced damage does not affect regions more than 30 nanometers from either lamella surface and that up to ~180-nanometer lamella thickness does not negatively affect resolution. This shows that there is no need to generate very thin lamellae and lamella thickness can be chosen such that it captures cellular features of interest, thereby opening cryo-ET also for studies of large complexes.

Rapid Freezing and Cryo-SEM-EDS Imaging of Foraminifera (Unicellular Eukaryotes) Using a Conductive Viscous Cryogenic Glue.

Spatial distribution of water-soluble molecules and ions in living organisms is still challenging to assess. Energy-dispersive X-ray spectroscopy (EDS) via cryogenic scanning electron microscopy (cryo-SEM) is one of the promising methods to study them without loss of dissolved contents. High-resolution cryo-SEM-EDS has challenges in sample preparation, including cross-section exposure and sample drift/charging due to insulative surrounding water. The former becomes problematic for large and inseparable organisms, such as benthic foraminifera, a unicellular eukaryote playing significant roles in marine ecosystems, which often exceed the size limit for the most reliable high-pressure freezing. Here we show graphite oxide dispersed in sucrose solution as a good glue to freeze, expose cross-section by cryo-ultramicrotome, and analyze elemental distribution owing to the glue's high viscosity, adhesion force, and electron conductivity. To demonstrate the effectiveness and applicability of the glue for cryo-SEM-EDS, deep-sea foraminifer Uvigerina akitaensis was sampled during a cruise and plunge frozen directly on the research vessel, where the liquid nitrogen supply is limited. The microstructures were preserved as faithfully in cryo-SEM images as those with the conventional resin-substituted transmission electron micrograph. We found elements colocalized within the cytoplasm originating from water-soluble compounds that can be lost with conventional dehydrative fixation.

Cryo-EM reveals a nearly complete PCNA loading process and unique features of the human alternative clamp loader CTF18-RFC.

The DNA sliding clamp PCNA is a multipurpose platform for DNA polymerases and many other proteins involved in DNA metabolism. The topologically closed PCNA ring needs to be cracked open and loaded onto DNA by a clamp loader, e.g., the well-studied pentameric ATPase complex RFC (RFC1-5). The CTF18-RFC complex is an alternative clamp loader found recently to bind the leading strand DNA polymerase ε and load PCNA onto leading strand DNA, but its structure and the loading mechanism have been unknown. By cryo-EM analysis of in vitro assembled human CTF18-RFC-DNA-PCNA complex, we have captured seven loading intermediates, revealing a detailed PCNA loading mechanism onto a 3'-ss/dsDNA junction by CTF18-RFC. Interestingly, the alternative loader has evolved a highly mobile CTF18 AAA+ module likely to lower the loading activity, perhaps to avoid competition with the RFC and to limit its role to leading strand clamp loading. To compensate for the lost stability due to the mobile AAA+ module, CTF18 has evolved a unique ß-hairpin motif that reaches across RFC2 to interact with RFC5, thereby stabilizing the pentameric complex. Further, we found that CTF18 also contains a separation pin to locally melt DNA from the 3'-end of the primer; this ensures its ability to load PCNA to any 3'-ss/dsDNA junction, facilitated by the binding energy of the E-plug to the major groove. Our study reveals unique structural features of the human CTF18-RFC and contributes to a broader understanding of PCNA loading by the alternative clamp loaders.

High-Resolution Cryo-Electron Microscopy Structure Determination of Haemophilus influenzae Tellurite-Resistance Protein A via 200 kV Transmission Electron Microscopy.

Membrane proteins constitute about 20% of the human proteome and play crucial roles in cellular functions. However, a complete understanding of their structure and function is limited by their hydrophobic nature, which poses significant challenges in purification and stabilization. Detergents, essential in the isolation process, risk destabilizing or altering the proteins' native conformations, thus affecting stability and functionality. This study leverages single-particle cryo-electron microscopy to elucidate the structural nuances of membrane proteins, focusing on the SLAC1 bacterial homolog from Haemophilus influenzae (HiTehA) purified with diverse detergents, including n-dodecyl ß-D-maltopyranoside (DDM), glycodiosgenin (GDN), ß-D-octyl-glucoside (OG), and lauryl maltose neopentyl glycol (LMNG). This research not only contributes to the understanding of membrane protein structures but also addresses detergent effects on protein purification. By showcasing that the overall structural integrity of the channel is preserved, our study underscores the intricate interplay between proteins and detergents, offering insightful implications for drug design and membrane biology.

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.

VitroJet: new features and case studies.

Single-particle cryo-electron microscopy has become a widely adopted method in structural biology due to many recent technological advances in microscopes, detectors and image processing. Before being able to inspect a biological sample in an electron microscope, it needs to be deposited in a thin layer on a grid and rapidly frozen. The VitroJet was designed with this aim, as well as avoiding the delicate manual handling and transfer steps that occur during the conventional grid-preparation process. Since its creation, numerous technical developments have resulted in a device that is now widely utilized in multiple laboratories worldwide. It features plasma treatment, low-volume sample deposition through pin printing, optical ice-thickness measurement and cryofixation of pre-clipped Autogrids through jet vitrification. This paper presents recent technical improvements to the VitroJet and the benefits that it brings to the cryo-EM workflow. A wide variety of applications are shown: membrane proteins, nucleosomes, fatty-acid synthase, Tobacco mosaic virus, lipid nanoparticles, tick-borne encephalitis viruses and bacteriophages. These case studies illustrate the advancement of the VitroJet into an instrument that enables accurate control and reproducibility, demonstrating its suitability for time-efficient cryo-EM structure determination.

Tomo Live: an on-the-fly reconstruction pipeline to judge data quality for cryo-electron tomography workflows.

Data acquisition and processing for cryo-electron tomography can be a significant bottleneck for users. To simplify and streamline the cryo-ET workflow, Tomo Live, an on-the-fly solution that automates the alignment and reconstruction of tilt-series data, enabling real-time data-quality assessment, has been developed. Through the integration of Tomo Live into the data-acquisition workflow for cryo-ET, motion correction is performed directly after each of the acquired tilt angles. Immediately after the tilt-series acquisition has completed, an unattended tilt-series alignment and reconstruction into a 3D volume is performed. The results are displayed in real time in a dedicated remote web platform that runs on the microscope hardware. Through this web platform, users can review the acquired data (aligned stack and 3D volume) and several quality metrics that are obtained during the alignment and reconstruction process. These quality metrics can be used for fast feedback for subsequent acquisitions to save time. Parameters such as Alignment Accuracy, Deleted Tilts and Tilt Axis Correction Angle are visualized as graphs and can be used as filters to export only the best tomograms (raw data, reconstruction and intermediate data) for further processing. Here, the Tomo Live algorithms and workflow are described and representative results on several biological samples are presented. The Tomo Live workflow is accessible to both expert and non-expert users, making it a valuable tool for the continued advancement of structural biology, cell biology and histology.

Analysis of the Conformational Landscape of the N-Domains of the AAA ATPase p97: Disentangling the Continuous Conformational Variability in Partially Symmetrical Complexes.

Single-particle cryo-electron microscopy (cryo-EM) has been shown to be effective in defining the structure of macromolecules, including protein complexes. Complexes adopt different conformations and compositions to perform their biological functions. In cryo-EM, the protein complexes are observed in solution, enabling the recording of images of the protein in multiple conformations. Various methods exist for capturing the conformational variability through analysis of cryo-EM data. Here, we analyzed the conformational variability in the hexameric AAA + ATPase p97, a complex with a six-fold rotational symmetric core surrounded by six flexible N-domains. We compared the performance of discrete classification methods with our recently developed method, MDSPACE, which uses 3D-to-2D flexible fitting of an atomic structure to images based on molecular dynamics (MD) simulations. Our analysis detected a novel conformation adopted by approximately 2% of the particles in the dataset and determined that the N-domains of p97 sway by up to 60° around a central position. This study demonstrates the application of MDSPACE in analyzing the continuous conformational changes in partially symmetrical protein complexes, systems notoriously difficult to analyze due to the alignment errors caused by their partial symmetry.