Routine single particle CryoEM sample and grid characterization by tomography

Honeycomb gold specimen supports enabling orthogonal focussed ion beam-milling of elongated cells for cryo-ET

Cryo-focussed ion beam (FIB)-milling is a powerful technique that opens up thick, cellular specimens to high-resolution structural analysis by electron cryotomography (cryo-ET). FIB-milled lamellae can be produced from cells on grids, or cut from thicker, high-pressure frozen specimens. However, these approaches can put geometrical constraints on the specimen that may be unhelpful, particularly when imaging structures within the cell that have a very defined orientation. For example, plunge frozen rod-shaped bacteria orient parallel to the plane of the grid, yet the Z-ring, a filamentous structure of the tubulin-like protein FtsZ and the key organiser of bacterial division, runs around the circumference of the cell such that it is perpendicular to the imaging plane. It is therefore difficult or impractical to image many complete rings with current technologies. To circumvent this problem, we have fabricated monolithic gold specimen supports with a regular array of cylindrical wells in a honeycomb geometry, which trap bacteria in a vertical orientation. These supports, which we call "honeycomb gold discs", replace standard EM grids and when combined with FIB-milling enable the production of lamellae containing cross-sections through cells. The resulting lamellae are more stable and resistant to breakage and charging than conventional lamellae. The design of the honeycomb discs can be modified according to need and so will also enable cryo-ET and cryo-EM imaging of other specimens in otherwise difficult to obtain orientations.

Tuning ice thickness using the chameleon for high-quality cryoEM data collection

Advances in single-particle cryogenic electron microscopy (cryoEM) now allow for routine structure determination of well-behaved biological specimens to high-resolution. Despite advances in the electron microscope, direct electron detectors, and data processing software, the preparation of high-quality grids with thin layers of vitreous ice containing the specimen of interest in random orientations remains a critical bottleneck for many projects. Although numerous efforts have been dedicated to overcoming hurdles frequently encountered during specimen vitrification using traditional blot-and-plunge specimen preparation techniques, the development of blot-free grid preparation devices provide a unique opportunity to carefully tune ice thickness, particle density, and specimen behavior during the vitrification process for improvements in image quality. Here, we describe critical steps of high-quality grid preparation using a SPT Labtech chameleon, evaluation of grid quality/ice thickness using the chameleon software, high-throughput imaging in the electron microscope, and recommend steps for troubleshooting grid preparation when standard parameters fail to yield suitable specimen.

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.

Overcoming the preferred orientation problem in cryoEM with self-supervised deep-learning

While advances in single-particle cryoEM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the so-called "preferred" orientation problem) remains a complication for most specimens. Existing solutions have relied on biochemical and physical strategies applied to the specimen and are often complex and challenging. Here, we develop spIsoNet, an end-to-end self-supervised deep-learning-based software to address the preferred orientation problem. Using preferred-orientation views to recover molecular information in under-sampled views, spIsoNet improves both angular isotropy and particle alignment accuracy during 3D reconstruction. We demonstrate spIsoNet's capability of generating near-isotropic reconstructions from representative biological systems with limited views, including ribosomes, β-galactosidases, and a previously intractable hemagglutinin trimer dataset. spIsoNet can also be generalized to improve map isotropy and particle alignment of preferentially oriented molecules in subtomogram averaging. Therefore, without additional specimen-preparation procedures, spIsoNet provides a general computational solution to the preferred orientation problem.

Anaerobic cryoEM protocols for air-sensitive nitrogenase proteins

Single-particle cryo-electron microscopy (cryoEM) provides an attractive avenue for advancing our atomic resolution understanding of materials, molecules and living systems. However, the vast majority of published cryoEM methodologies focus on the characterization of aerobically purified samples. Air-sensitive enzymes and microorganisms represent important yet understudied systems in structural biology. We have recently demonstrated the success of an anaerobic single-particle cryoEM workflow applied to the air-sensitive nitrogenase enzymes. In this protocol, we detail the use of Schlenk lines and anaerobic chambers to prepare samples, including a protein tag for monitoring sample exposure to oxygen in air. We describe how to use a plunge freezing apparatus inside of a soft-sided vinyl chamber of the type we routinely use for anaerobic biochemistry and crystallography of oxygen-sensitive proteins. Manual control of the airlock allows for introduction of liquid cryogens into the tent. A custom vacuum port provides slow, continuous evacuation of the tent atmosphere to avoid accumulation of flammable vapors within the enclosed chamber. These methods allowed us to obtain high-resolution structures of both nitrogenase proteins using single-particle cryoEM. The procedures involved can be generally subdivided into a 4 d anaerobic sample generation procedure, and a 1 d anaerobic cryoEM sample preparation step, followed by conventional cryoEM imaging and processing steps. As nitrogen is a substrate for nitrogenase, the Schlenk lines and anaerobic chambers described in this procedure are operated under an argon atmosphere; however, the system and these procedures are compatible with other controlled gas environments.

Cryo-EM Map Anisotropy Can Be Attenuated by Map Post-Processing and a New Method for Its Estimation

One of the most important challenges in cryogenic electron microscopy (cryo-EM) is the substantial number of samples that exhibit preferred orientations, which leads to an uneven coverage of the projection sphere. As a result, the overall quality of the reconstructed maps can be severely affected, as manifested by the presence of anisotropy in the map resolution. Several methods have been proposed to measure the directional resolution of maps in tandem with experimental protocols to address the problem of preferential orientations in cryo-EM. Following these works, in this manuscript we identified one potential limitation that may affect most of the existing methods and we proposed an alternative approach to evaluate the presence of preferential orientations in cryo-EM reconstructions. In addition, we also showed that some of the most recently proposed cryo-EM map post-processing algorithms can attenuate map anisotropy, thus offering alternative visualization opportunities for cases affected by moderate levels of preferential orientations.

Architecture of full-length type I modular polyketide synthases revealed by X-ray crystallography, cryo-electron microscopy, and AlphaFold2

Covering: up to the end of 2023Type I modular polyketide synthases construct polyketide natural products in an assembly line-like fashion, where the growing polyketide chain attached to an acyl carrier protein is passed from catalytic domain to catalytic domain. These enzymes have immense potential in drug development since they can be engineered to produce non-natural polyketides by strategically adding, exchanging, and deleting individual catalytic domains. In practice, however, this approach frequently results in complete failures or dramatically reduced product yields. A comprehensive understanding of modular polyketide synthase architecture is expected to resolve these issues. We summarize the three-dimensional structures and the proposed mechanisms of three full-length modular polyketide synthases, Lsd14, DEBS module 1, and PikAIII. We also describe the advantages and limitations of using X-ray crystallography, cryo-electron microscopy, and AlphaFold2 to study intact type I polyketide synthases.

Cryo-electron microscopy-based drug design

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

Miffi: Improving the accuracy of CNN-based cryo-EM micrograph filtering with fine-tuning and Fourier space information

Efficient and high-accuracy filtering of cryo-electron microscopy (cryo-EM) micrographs is an emerging challenge with the growing speed of data collection and sizes of datasets. Convolutional neural networks (CNNs) are machine learning models that have been proven successful in many computer vision tasks, and have been previously applied to cryo-EM micrograph filtering. In this work, we demonstrate that two strategies, fine-tuning models from pretrained weights and including the power spectrum of micrographs as input, can greatly improve the attainable prediction accuracy of CNN models. The resulting software package, Miffi, is open-source and freely available for public use (https://github.com/ando-lab/miffi).

Miffi: Improving the accuracy of CNN-based cryo-EM micrograph filtering with fine-tuning and Fourier space information

Efficient and high-accuracy filtering of cryo-electron microscopy (cryo-EM) micrographs is an emerging challenge with the growing speed of data collection and sizes of datasets. Convolutional neural networks (CNNs) are machine learning models that have been proven successful in many computer vision tasks, and have been previously applied to cryo-EM micrograph filtering. In this work, we demonstrate that two strategies, fine-tuning models from pretrained weights and including the power spectrum of micrographs as input, can greatly improve the attainable prediction accuracy of CNN models. The resulting software package, Miffi, is open-source and freely available for public use (https://github.com/ando-lab/miffi).

Time resolution in cryo-EM using a PDMS-based microfluidic chip assembly and its application to the study of HflX-mediated ribosome recycling

The rapid kinetics of biological processes and associated short-lived conformational changes pose a significant challenge in attempts to structurally visualize biomolecules during a reaction in real time. Conventionally, on-pathway intermediates have been trapped using chemical modifications or reduced temperature, giving limited insights. Here, we introduce a time-resolved cryo-EM method using a reusable PDMS-based microfluidic chip assembly with high reactant mixing efficiency. Coating of PDMS walls with SiO2 virtually eliminates non-specific sample adsorption and ensures maintenance of the stoichiometry of the reaction, rendering it highly reproducible. In an operating range from 10 to 1,000 ms, the device allows us to follow in vitro reactions of biological molecules at resolution levels in the range of 3 Å. By employing this method, we show the mechanism of progressive HflX-mediated splitting of the 70S E. coli ribosome in the presence of the GTP via capture of three high-resolution reaction intermediates within 140 ms.

A web-based dashboard for RELION metadata visualization

Cryo-electron microscopy (cryo-EM) has witnessed radical progress in the past decade, driven by developments in hardware and software. While current software packages include processing pipelines that simplify the image-processing workflow, they do not prioritize the in-depth analysis of crucial metadata, limiting troubleshooting for challenging data sets. The widely used RELION software package lacks a graphical native representation of the underlying metadata. Here, two web-based tools are introduced: relion_live.py, which offers real-time feedback on data collection, aiding swift decision-making during data acquisition, and relion_analyse.py, a graphical interface to represent RELION projects by plotting essential metadata including interactive data filtration and analysis. A useful script for estimating ice thickness and data quality during movie pre-processing is also presented. These tools empower researchers to analyse data efficiently and allow informed decisions during data collection and processing.

SPOT-RASTR - a cryo-EM specimen preparation technique that overcomes problems with preferred orientation and the air/water interface

In cryogenic electron microscopy (cryo-EM), specimen preparation remains a bottleneck despite recent advancements. Classical plunge freezing methods often result in issues like aggregation and preferred orientations at the air/water interface. Many alternative methods have been proposed, but there remains a lack a universal solution, and multiple techniques are often required for challenging samples. Here, we demonstrate the use of lipid nanotubes with nickel NTA headgroups as a platform for cryo-EM sample preparation. His-tagged specimens of interest are added to the tubules, and they can be frozen by conventional plunge freezing. We show that the nanotubes protect samples from the air/water interface and promote a wider range of orientations. The reconstruction of average subtracted tubular regions (RASTR) method allows for the removal of the nanotubule signal from the cryo-EM images resulting in isolated images of specimens of interest. Testing with β-galactosidase validates the method's ability to capture particles at lower concentrations, overcome preferred orientations, and achieve near-atomic resolution reconstructions. Since the nanotubules can be identified and targeted automatically at low magnification, the method enables fully automated data collection. Furthermore, the particles on the tubes can be automatically identified and centered using 2D classification enabling particle picking without requiring prior information. Altogether, our approach that we call specimen preparation on a tube RASTR (SPOT-RASTR) holds promise for overcoming air-water interface and preferred orientation challenges and offers the potential for fully automated cryo-EM data collection and structure determination.

Overcoming resolution attenuation during tilted cryo-EM data collection

Structural biology efforts using cryogenic electron microscopy are frequently stifled by specimens adopting "preferred orientations" on grids, leading to anisotropic map resolution and impeding structure determination. Tilting the specimen stage during data collection is a generalizable solution but has historically led to substantial resolution attenuation. Here, we develop updated data collection and image processing workflows and demonstrate, using multiple specimens, that resolution attenuation is negligible or significantly reduced across tilt angles. Reconstructions with and without the stage tilted as high as 60° are virtually indistinguishable. These strategies allowed the reconstruction to 3 Å resolution of a bacterial RNA polymerase with preferred orientation, containing an unnatural nucleotide for studying novel base pair recognition. Furthermore, we present a quantitative framework that allows cryo-EM practitioners to define an optimal tilt angle during data acquisition. These results reinforce the utility of employing stage tilt for data collection and provide quantitative metrics to obtain isotropic maps.

Metallo-supramolecular branched polymer protects particles from air-water interface in single-particle cryo-electron microscopy

Recent technological breakthroughs in single-particle cryo-electron microscopy (cryo-EM) enable rapid atomic structure determination of biological macromolecules. A major bottleneck in the current single particle cryo-EM pipeline is the preparation of good quality frozen cryo-EM grids, which is mostly a trial-and-error process. Among many issues, preferred particle orientation and sample damage by air-water interface (AWI) are common practical problems. Here we report a method of applying metallo-supramolecular branched polymer (MSBP) in the cryo-sample preparation for high-resolution single-particle cryo-EM. Our data shows that MSBP keeps a majority of particles away from air-water interface and mitigates preferred orientation as verified by the analyses of apoferritin, hemagglutinin) trimer and various sample proteins. The use of MSBP is a simple method to improve particle distribution for high-resolution structure determination in single-particle cryo-EM.

From Fundamental Amyloid Protein Self-Assembly to Development of Bioplastics

Proteins can self-assemble into a range of nanostructures as a result of molecular interactions. Amyloid nanofibrils, as one of them, were first discovered with regard to the relevance of neurodegenerative diseases but now have been exploited as building blocks to generate multiscale materials with designed functions for versatile applications. This review interconnects the mechanism of amyloid fibrillation, the current approaches to synthesizing amyloid protein-based materials, and the application in bioplastic development. We focus on the fundamental structures of self-assembled amyloid fibrils and how external factors can affect protein aggregation to optimize the process. Protein self-assembly is essentially the autonomous congregation of smaller protein units into larger, organized structures. Since the properties of the self-assembly can be manipulated by changing intrinsic factors and external conditions, protein self-assembly serves as an excellent building block for bioplastic development. Building on these principles, general processing methods and pathways from raw protein sources to mature state materials are proposed, providing a guide for the development of large-scale production. Additionally, this review discusses the diverse properties of protein-based amyloid nanofibrils and how they can be utilized as bioplastics. The economic feasibility of the protein bioplastics is also compared to conventional plastics in large-scale production scenarios, supporting their potential as sustainable bioplastics for future applications.

CryoEM Data Analysis of Membrane Proteins. Practical Considerations on Amphipathic Belts, Ligands, and Variability Analysis

Membrane proteins data analysis by cryoEM shows some specificities, as can be found in other typical investigations such as biochemistry, biophysics, or X-ray crystallography. Membrane proteins are typically surrounded by an amphipathic belt that will have some degree of influence on the 3D reconstruction and analysis. In this chapter, we review our experience with the ABC transporter BmrA, as well as our statistical analysis of amphipathic belts around membrane proteins, to bring awareness on some particular features of membrane protein investigations by cryoEM.

Insights into protein structure using cryogenic light microscopy

Fluorescence microscopy has witnessed many clever innovations in the last two decades, leading to new methods such as structured illumination and super-resolution microscopies. The attainable resolution in biological samples is, however, ultimately limited by residual motion within the sample or in the microscope setup. Thus, such experiments are typically performed on chemically fixed samples. Cryogenic light microscopy (Cryo-LM) has been investigated as an alternative, drawing on various preservation techniques developed for cryogenic electron microscopy (Cryo-EM). Moreover, this approach offers a powerful platform for correlative microscopy. Another key advantage of Cryo-LM is the strong reduction in photobleaching at low temperatures, facilitating the collection of orders of magnitude more photons from a single fluorophore. This results in much higher localization precision, leading to Angstrom resolution. In this review, we discuss the general development and progress of Cryo-LM with an emphasis on its application in harnessing structural information on proteins and protein complexes.

Embracing Heterogeneity: Challenging the Paradigm of Replisomes as Deterministic Machines

The paradigm of cellular systems as deterministic machines has long guided our understanding of biology. Advancements in technology and methodology, however, have revealed a world of stochasticity, challenging the notion of determinism. Here, we explore the stochastic behavior of multi-protein complexes, using the DNA replication system (replisome) as a prime example. The faithful and timely copying of DNA depends on the simultaneous action of a large set of enzymes and scaffolding factors. This fundamental cellular process is underpinned by dynamic protein-nucleic acid assemblies that must transition between distinct conformations and compositional states. Traditionally viewed as a well-orchestrated molecular machine, recent experimental evidence has unveiled significant variability and heterogeneity in the replication process. In this review, we discuss recent advances in single-molecule approaches and single-particle cryo-EM, which have provided insights into the dynamic processes of DNA replication. We comment on the new challenges faced by structural biologists and biophysicists as they attempt to describe the dynamic cascade of events leading to replisome assembly, activation, and progression. The fundamental principles uncovered and yet to be discovered through the study of DNA replication will inform on similar operating principles for other multi-protein complexes.

Automated pipelines for rapid evaluation during cryoEM data acquisition

Cryo-electron microscopy (cryoEM) has become a popular method for determining high-resolution structures of biomolecules. However, data processing can be time-consuming, particularly for new researchers entering the field. To improve data quality and increase data collection efficiency, several software packages have been developed for on-the-fly data processing with various degrees of automation. These software packages allow researchers to perform tasks such as motion correction, CTF estimation, 2D classification, and 3D reconstruction in real-time, with minimal human input. On-the-fly data processing can not only improve data collection efficiency but also increase the productivity of instrumentation in high demand. However, the various software packages available differ in their performance, computational requirements, and levels of automation. In this review, we describe the minimal metrics used to assess data quality during data collection, outline the features of an ideal on-the-fly data processing software systems, and provide results from using three of these systems.

Time resolved applications for Cryo-EM; approaches, challenges and future directions

Developments within the cryo-EM field have allowed us to generate higher-resolution "static" structures and pull out different conformational states which exist at equilibrium within the sample. Moreover, to trap non-equilibrium states and determine conformations that are present after a defined period of time (typically in the ms time frame) new approaches have been developed for the application of time-resolved cryo-EM. Here we give an overview of these different approaches and the limitations and strengths of each whilst identifying some of the current challenges to achieve higher resolutions and trap states within faster time frames. Time-resolved applications may play an important role in the ever-expanding toolkit of cryo-EM and open up new possibilities in both single particle and tomographic studies.

Mass spectrometers as cryoEM grid preparation instruments

Structure determination by single-particle cryoEM has matured into a core structural biology technique. Despite many methodological advancements, most cryoEM grids are still prepared using the plunge-freezing method developed ∼40 years ago. Embedding samples in thin films and exposing them to the air-water interface often leads to sample damage and preferential orientation of the particles. Using native mass spectrometry to create cryoEM samples, potentially avoids these problems and allows the use of mass spectrometry sample isolation techniques during EM grid creation. We review the recent publications that have demonstrated protein complexes can be ionized, flown through the mass spectrometer, gently landed onto EM grids, imaged, and reconstructed in 3D. Although many uncertainties and challenges remain, the combination of cryoEM and MS has great potential.

Theoretical framework and experimental solution for the air-water interface adsorption problem in cryoEM

As cryogenic electron microscopy (cryoEM) gains traction in the structural biology community as a method of choice for determining atomic structures of biological complexes, it has been increasingly recognized that many complexes that behave well under conventional negative-stain electron microscopy tend to have preferential orientation, aggregate or simply mysteriously "disappear" on cryoEM grids, but the reasons for such misbehavior are not well understood, limiting systematic approaches to solving the problem. Here, we have developed a theoretical formulation that explains these observations. Our formulation predicts that all particles migrate to the air-water interface (AWI) to lower the total potential surface energy - rationalizing the use of surfactant, which is a direct solution to reducing the surface tension of the aqueous solution. By conducting cryogenic electron tomography (cryoET) with the widely-tested sample, GroEL, we demonstrate that, in a standard buffer solution, nearly all particles migrate to the AWI. Gradual reduction of the surface tension by introducing surfactants decreased the percentage of particles exposed to the surface. By conducting single-particle cryoEM, we confirm that applicable surfactants do not damage the biological complex, thus suggesting that they might offer a practical, simple, and general solution to the problem for high-resolution cryoEM. Application of this solution to a real-world AWI adsorption problem with a more challenging membrane protein, namely, the ClC-1 channel, has led to its first near-atomic structure using cryoEM.

Theoretical framework and experimental solution for the air-water interface adsorption problem in cryoEM

As cryogenic electron microscopy (cryoEM) gains traction in the structural biology community as a method of choice for determining atomic structures of biological complexes, it has been increasingly recognized that many complexes that behave well under conventional negative-stain electron microscopy tend to have preferential orientation, aggregate or simply mysteriously "disappear" on cryoEM grids. However, the reasons for such misbehavior are not well understood, which limits systematic approaches to solving the problem. Here, we have developed a theoretical formulation that explains these observations. Our formulation predicts that all particles migrate to the air-water interface (AWI) to lower the total potential surface energy-rationalizing the use of surfactant, which is a direct solution to reduce the surface tension of the aqueous solution. By performing cryogenic electron tomography (cryoET) on the widely-tested sample, GroEL, we demonstrate that, in a standard buffer solution, nearly all particles migrate to the AWI. Gradually reducing the surface tension by introducing surfactants decreased the percentage of particles exposed to the surface. By conducting single-particle cryoEM, we confirm that suitable surfactants do not damage the biological complex, thus suggesting that they might provide a practical, simple, and general solution to the problem for high-resolution cryoEM. Applying this solution to a real-world AWI adsorption problem involving a more challenging membrane protein, namely, the ClC-1 channel, has resulted in its near-atomic structure determination using cryoEM.

Challenges in making ideal cryo-EM samples

Recognizing that interaction with the air-water interface (AWI) is a major challenge for cryo-EM, we first review current approaches designed to avoid it. Of these, immobilizing particles on affinity grids is arguably the most promising. In addition, we review efforts to gain more reliable control of the sample thicknesses, not the least important reason being to prevent immobilized particles from coming in contact with the AWI of the remaining buffer. It is emphasized that avoiding such a contact is as important for cryo-ET as for single-particle cryo-EM. Finally, looking to the future, it is proposed that immobilized samples might be used to perform time-resolved biochemical experiments directly on EM grids rather than just in test tubes or cuvettes.

Heterogeneous non-canonical nucleosomes predominate in yeast cells in situ

Nuclear processes depend on the organization of chromatin, whose basic units are cylinder-shaped complexes called nucleosomes. A subset of mammalian nucleosomes in situ (inside cells) resembles the canonical structure determined in vitro 25 years ago. Nucleosome structure in situ is otherwise poorly understood. Using cryo-electron tomography (cryo-ET) and 3D classification analysis of budding yeast cells, here we find that canonical nucleosomes account for less than 10% of total nucleosomes expected in situ. In a strain in which H2A-GFP is the sole source of histone H2A, class averages that resemble canonical nucleosomes both with and without GFP densities are found ex vivo (in nuclear lysates), but not in situ. These data suggest that the budding yeast intranuclear environment favors multiple non-canonical nucleosome conformations. Using the structural observations here and the results of previous genomics and biochemical studies, we propose a model in which the average budding yeast nucleosome's DNA is partially detached in situ.

Overcoming Resolution Attenuation During Tilted Cryo-EM Data Collection

Structural biology efforts using cryogenic electron microscopy are frequently stifled by specimens adopting "preferred orientations" on grids, leading to anisotropic map resolution and impeding structure determination. Tilting the specimen stage during data collection is a generalizable solution but has historically led to substantial resolution attenuation. Here, we develop updated data collection and image processing workflows and demonstrate, using multiple specimens, that resolution attenuation is negligible or significantly reduced across tilt angles. Reconstructions with and without the stage tilted as high as 60° are virtually indistinguishable. These strategies allowed the reconstruction to 3 Å resolution of a bacterial RNA polymerase with preferred orientation. Furthermore, we present a quantitative framework that allows cryo-EM practitioners to define an optimal tilt angle for dataset acquisition. These data reinforce the utility of employing stage tilt for data collection and provide quantitative metrics to obtain isotropic maps.

A large expert-curated cryo-EM image dataset for machine learning protein particle picking

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining the structures of biological macromolecular complexes. Picking single-protein particles from cryo-EM micrographs is a crucial step in reconstructing protein structures. However, the widely used template-based particle picking process is labor-intensive and time-consuming. Though machine learning and artificial intelligence (AI) based particle picking can potentially automate the process, its development is hindered by lack of large, high-quality labelled training data. To address this bottleneck, we present CryoPPP, a large, diverse, expert-curated cryo-EM image dataset for protein particle picking and analysis. It consists of labelled cryo-EM micrographs (images) of 34 representative protein datasets selected from the Electron Microscopy Public Image Archive (EMPIAR). The dataset is 2.6 terabytes and includes 9,893 high-resolution micrographs with labelled protein particle coordinates. The labelling process was rigorously validated through 2D particle class validation and 3D density map validation with the gold standard. The dataset is expected to greatly facilitate the development of both AI and classical methods for automated cryo-EM protein particle picking.

Prospects and Limitations of High-Resolution Single-Particle Cryo-Electron Microscopy

Single particle cryo-electron microscopy (cryo-EM) has matured into a robust method for the determination of biological macromolecule structures in the past decade, complementing X-ray crystallography and nuclear magnetic resonance. Constant methodological improvements in both cryo-EM hardware and image processing software continue to contribute to an exponential growth in the number of structures solved annually. In this review, we provide a historical view of the many steps that were required to make cryo-EM a successful method for the determination of high-resolution protein complex structures. We further discuss aspects of cryo-EM methodology that are the greatest pitfalls challenging successful structure determination to date. Lastly, we highlight and propose potential future developments that would improve the method even further in the near future.

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.

The chemical landscape of the human ribosome at 1.67 Å resolution

The ability of ribosomes to translate the genetic code into protein requires a finely tuned ion and solvent ecosystem. However, the lack of high-resolution structures has precluded accurate positioning of all the functional elements of the ribosome and limited our understanding of the specific role of ribosomal RNA chemical modifications in modulating ribosome function in health and disease. Here, using a new sample preparation methodology based on functionalised pristine graphene-coated grids, we solve the cryo-EM structure of the human large ribosomal subunit to a resolution of 1.67 Å. The accurate assignment of water molecules, magnesium and potassium ions in our model highlights the fundamental biological role of ribosomal RNA methylation in harnessing unconventional carbon-oxygen hydrogen bonds to establish chemical interactions with the environment and fine-tune the functional interplay with tRNA. In addition, the structures of three translational inhibitors bound to the human large ribosomal subunit at better than 2 Å resolution provide mechanistic insights into how three key druggable pockets of the ribosome are targeted and illustrate the potential of this methodology to accelerate high-throughput structure-based design of anti-cancer therapeutics.

Structural consequences of turnover-induced homocitrate loss in nitrogenase

Nitrogenase catalyzes the ATP-dependent reduction of dinitrogen to ammonia during the process of biological nitrogen fixation that is essential for sustaining life. The active site FeMo-cofactor contains a [7Fe:1Mo:9S:1C] metallocluster coordinated with an R-homocitrate (HCA) molecule. Here, we establish through single particle cryoEM and chemical analysis of two forms of the Azotobacter vinelandii MoFe-protein - a high pH turnover inactivated species and a ∆NifV variant that cannot synthesize HCA - that loss of HCA is coupled to α-subunit domain and FeMo-cofactor disordering, and formation of a histidine coordination site. We further find a population of the ∆NifV variant complexed to an endogenous protein identified through structural and proteomic approaches as the uncharacterized protein NafT. Recognition by endogenous NafT demonstrates the physiological relevance of the HCA-compromised form, perhaps for cofactor insertion or repair. Our results point towards a dynamic active site in which HCA plays a role in enabling nitrogenase catalysis by facilitating activation of the FeMo-cofactor from a relatively stable form to a state capable of reducing dinitrogen under ambient conditions.

Addressing compressive deformation of proteins embedded in crystalline ice

For cryoelectron microscopy (cryo-EM), high cooling rates have been required for preparation of protein samples to vitrify the surrounding water and avoid formation of damaging crystalline ice. Whether and how crystalline ice affects single-particle cryo-EM is still unclear. Here, single-particle cryo-EM was used to analyze three-dimensional structures of various proteins and viruses embedded in crystalline ice formed at various cooling rates. Low cooling rates led to shrinkage deformation and density distortions on samples having loose structures. Higher cooling rates reduced deformations. Deformation-free proteins in crystalline ice were obtained by modifying the freezing conditions, and reconstructions from these samples revealed a marked improvement over vitreous ice. This procedure also increased the efficiency of cryo-EM structure determinations and was essential for high-resolution reconstructions.

A New Support Film for Cryo Electron Microscopy Protein Structure Analysis Based on Covalently Functionalized Graphene

Protein adsorption at the air-water interface is a serious problem in cryogenic electron microscopy (cryoEM) as it restricts particle orientations in the vitrified ice-film and promotes protein denaturation. To address this issue, the preparation of a graphene-based modified support film for coverage of conventional holey carbon transmission electron microscopy (TEM) grids is presented. The chemical modification of graphene sheets enables the universal covalent anchoring of unmodified proteins via inherent surface-exposed lysine or cysteine residues in a one-step reaction. Langmuir-Blodgett (LB) trough approach is applied for deposition of functionalized graphene sheets onto commercially available holey carbon TEM grids. The application of the modified TEM grids in single particle analysis (SPA) shows high protein binding to the surface of the graphene-based support film. Suitability for high resolution structure determination is confirmed by SPA of apoferritin. Prevention of protein denaturation at the air-water interface and improvement of particle orientations is shown using human 20S proteasome, demonstrating the potential of the support film for structural biology.

Measuring the effects of ice thickness on resolution in single particle cryo-EM

Ice thickness is a critical parameter in single particle cryo-EM - too thin ice can break during imaging or exclude the sample of interest, while ice that is too thick contributes to more inelastic scattering that precludes obtaining high resolution reconstructions. Here we present the practical effects of ice thickness on resolution, and the influence of energy filters, accelerating voltage, or detector mode. We collected apoferritin data with a wide range of ice thicknesses on three microscopes with different instrumentation and settings. We show that on a 300 kV microscope, using a 20 eV energy filter slit has a greater effect on improving resolution in thicker ice; that operating at 300 kV instead of 200 kV accelerating voltage provides significant resolution improvements at an ice thickness above 150 nm; and that on a 200 kV microscope using a detector operating in super resolution mode enables good reconstructions for up to 200 nm ice thickness, while collecting in counting instead of linear mode leads to improvements in resolution for ice of 50-150 nm thickness. Our findings can serve as a guide for users seeking to optimize data collection or sample preparation routines for both single particle and in situ cryo-EM. We note that most in situ data collection is done on samples in a range of ice thickness above 150 nm so these results may be especially relevant to that community.

Frozen in time: analyzing molecular dynamics with time-resolved cryo-EM

Molecular machines, such as polymerases, ribosomes, or proteasomes, fulfill complex tasks requiring the thermal energy of their environment. They achieve this by restricting random motion along a path of possible conformational changes. These changes are often directed through engagement with different cofactors, which can best be compared to a Brownian ratchet. Many molecular machines undergo three major steps throughout their functional cycles, including initialization, repetitive processing, and termination. Several of these major states have been elucidated by cryogenic electron microscopy (cryo-EM). However, the individual steps for these machines are unique and multistep processes themselves, and their coordination in time is still elusive. To measure these short-lived intermediate events by cryo-EM, the total reaction time needs to be shortened to enrich for the respective pre-equilibrium states. This approach is termed time-resolved cryo-EM (trEM). In this review, we sum up the methodological development of trEM and its application to a range of biological questions.

Fully automated multi-grid cryoEM screening using Smart Leginon

Single-particle cryo-electron microscopy (cryoEM) is a swiftly growing method for understanding protein structure. With increasing demand for high-throughput, high-resolution cryoEM services comes greater demand for rapid and automated cryoEM grid and sample screening. During screening, optimal grids and sample conditions are identified for subsequent high-resolution data collection. Screening is a major bottleneck for new cryoEM projects because grids must be optimized for several factors, including grid type, grid hole size, sample concentration, buffer conditions, ice thickness and particle behavior. Even for mature projects, multiple grids are commonly screened to select a subset for high-resolution data collection. Here, machine learning and novel purpose-built image-processing and microscope-handling algorithms are incorporated into the automated data-collection software Leginon, to provide an open-source solution for fully automated high-throughput grid screening. This new version, broadly called Smart Leginon, emulates the actions of an operator in identifying areas on the grid to explore as potentially useful for data collection. Smart Leginon Autoscreen sequentially loads and examines grids from an automated specimen-exchange system to provide completely unattended grid screening across a set of grids. Comparisons between a multi-grid autoscreen session and conventional manual screening by 5 expert microscope operators are presented. On average, Autoscreen reduces operator time from ∼6 h to <10 min and provides a percentage of suitable images for evaluation comparable to the best operator. The ability of Smart Leginon to target holes that are particularly difficult to identify is analyzed. Finally, the utility of Smart Leginon is illustrated with three real-world multi-grid user screening/collection sessions, demonstrating the efficiency and flexibility of the software package. The fully automated functionality of Smart Leginon significantly reduces the burden on operator screening time, improves the throughput of screening and recovers idle microscope time, thereby improving availability of cryoEM services.

Biophysical Characterization of Membrane Proteins

Membrane proteins are responsible for a large variety of tasks in organisms and of particular interesting as drug targets. At the same time, they are notoriously difficult to work with and require a thorough characterization before proceeding with structural studies. Here, we present a biophysical pipeline to characterize membrane proteins focusing on the optimization of stability, aggregation behavior, and homogeneity. The pipeline shown here is built on three biophysical techniques: differential scanning fluorimetry using native protein fluorescence (nano differential scanning fluorimetry), dynamic light scattering, and mass photometry. For each of these techniques, we provide detailed protocols for performing experiments and data analysis.

Learning to automate cryo-electron microscopy data collection with Ptolemy

Over the past decade, cryo-electron microscopy (cryoEM) has emerged as an important method for determining near-native, near-atomic resolution 3D structures of biological macromolecules. To meet the increasing demand for cryoEM, automated methods that improve throughput and efficiency of microscope operation are needed. Currently, the targeting algorithms provided by most data-collection software require time-consuming manual tuning of parameters for each grid, and, in some cases, operators must select targets completely manually. However, the development of fully automated targeting algorithms is non-trivial, because images often have low signal-to-noise ratios and optimal targeting strategies depend on a range of experimental parameters and macromolecule behaviors that vary between projects and collection sessions. To address this, Ptolemy provides a pipeline to automate low- and medium-magnification targeting using a suite of purpose-built computer vision and machine-learning algorithms, including mixture models, convolutional neural networks and U-Nets. Learned models in this pipeline are trained on a large set of images from real-world cryoEM data-collection sessions, labeled with locations selected by human operators. These models accurately detect and classify regions of interest in low- and medium-magnification images, and generalize to unseen sessions, as well as to images collected on different microscopes at another facility. This open-source, modular pipeline can be integrated with existing microscope control software to enable automation of cryoEM data collection and can serve as a foundation for future cryoEM automation software.

Towards automating single-particle cryo-EM data acquisition

Target selection for single-particle cryo-EM data acquisition sessions is mostly done manually by human operators, which is time consuming and leads to the inefficient use of instruments. The software toolbox Ptolemy [Kim et al. (2023). IUCrJ, 10, 90–102] provides solutions for automated target selection for cryo-EM imaging.

Temporal dynamics of charge buildup in cryo-electron microscopy

It is well known that insulating samples can accumulate electric charges from exposure to an electron beam. How the accumulation of charge affects imaging parameters and sample stability in transmission electron microscopy is poorly understood. To quantify these effects, it is important to know how the charge is distributed within the sample and how it builds up over time. In the present study, we determine the spatial distribution and temporal dynamics of charge accumulation on vitreous ice samples with embedded proteins through a combination of modeling and Fresnel diffraction experiments. Our data reveal a rapid evolution of the charge state on ice upon initial exposure to the electron beam accompanied by charge gradients at the interfaces between ice and carbon films. We demonstrate that ice film movement and charge state variations occur upon electron beam exposure and are dose-rate dependent. Both affect the image defocus through a combination of sample height changes and lensing effects. Our results may be used as a guide to improve sample preparation, data collection, and data processing for imaging of dose-sensitive samples.

Better Cryo-EM Specimen Preparation: How to Deal with the Air-Water Interface?

Cryogenic electron microscopy (cryo-EM) is now one of the most powerful and widely used methods to determine high-resolution structures of macromolecules. A major bottleneck of cryo-EM is to prepare high-quality vitrified specimen, which still faces many practical challenges. During the conventional vitrification process, macromolecules tend to adsorb at the air-water interface (AWI), which is known unfriendly to biological samples. In this review, we outline the nature of AWI and the problems caused by it, such as unpredictable or uneven particle distribution, protein denaturation, dissociation of complex and preferential orientation. We review and discuss the approaches and underlying mechanisms to deal with AWI: 1) Additives, exemplified by detergents, forming a protective layer at AWI and thus preserving the native folds of target macromolecules. 2) Fast vitrification devices based on the idea to freeze in-solution macromolecules before their touching of AWI. 3) Thin layer of continuous supporting films to adsorb macromolecules, and when functionalized with affinity ligands, to specifically anchor the target particles away from the AWI. Among these supporting films, graphene, together with its derivatives, with negligible background noise and mechanical robustness, has emerged as a new generation of support. These strategies have been proven successful in various cases and enable us a better handling of the problems caused by the AWI in cryo-EM specimen preparation.

Smart data collection for CryoEM

This report provides an overview of the discussions, presentations, and consensus thinking from the Workshop on Smart Data Collection for CryoEM held at the New York Structural Biology Center on April 6-7, 2022. The goal of the workshop was to address next generation data collection strategies that integrate machine learning and real-time processing into the workflow to reduce or eliminate the need for operator intervention.

Maintaining the momentum in cryoEM for biological discovery

Cryo-electron microscopy (cryoEM) has been transformed over the last decade, with continual new hardware and software tools coming online, pushing the boundaries of what is possible and the nature and complexity of projects that can be undertaken. Here we discuss some recent trends and new tools which are creating opportunities to make more effective use of the resources available within facilities (both staff and equipment). We present approaches for the stratification of projects based on risk and known information about the projects, and the impacts this might have on the allocation of microscope time. We show that allocating different resources (microscope time) based on this information can lead to a significant increase in 'successful' use of the microscope, and reduce lead time by enabling projects to 'fail faster'. This model results in more efficient and sustainable cryoEM facility operation.

Towards sub-millisecond cryo-EM grid preparation

Sample preparation is still a significant problem for many single particle cryo-EM workflows and our understanding and developments in the area lag behind that of image processing and microscope design. Over the last few years there has been growing evidence that many of the problems which occur during sample preparation are during the time the sample resides within the thin film created during the conventional blotting process. In parallel, faster grid preparation approaches have been developed for time-resolved cryo-EM experiments allowing for non-equilibrium intermediates to be captured on the ms timescale. Therefore, an important question is how fast can we prepare suitable grids for imaging by cryo-EM and how much does this mitigate the problems observed in sample preparation? Here we use a novel approach which has been developed for time-resolved studies to produce grids on an estimated sub-1 ms timescale. While the method comes with its own challenges, a 3.8 Å reconstruction of apoferritin prepared with the ultrafast method shows that good resolutions can be achieved. Although several orders of magnitude faster than conventional approaches we show using a ribosome sample, that interactions with the air-water interface cannot be avoided with preferred orientations still present. Therefore, the work shows that faster reactions can be captured but poses the question whether speed is the answer to problems with sample preparation.

Isotropic reconstruction for electron tomography with deep learning

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

The His-tag as a decoy modulating preferred orientation in cryoEM

The His-tag is a widely used affinity tag that facilitates purification by means of affinity chromatography of recombinant proteins for functional and structural studies. We show here that His-tag presence affects how coproheme decarboxylase interacts with the air-water interface during grid preparation for cryoEM. Depending on His-tag presence or absence, we observe significant changes in patterns of preferred orientation. Our analysis of particle orientations suggests that His-tag presence can mask the hydrophobic and hydrophilic patches on a protein’s surface that mediate the interactions with the air-water interface, while the hydrophobic linker between a His-tag and the coding sequence of the protein may enhance other interactions with the air-water interface. Our observations suggest that tagging, including rational design of the linkers between an affinity tag and a protein of interest, offer a promising approach to modulating interactions with the air-water interface.

DEEP ACTIVE LEARNING FOR CRYO-ELECTRON TOMOGRAPHY CLASSIFICATION

Cryo-Electron Tomography (cryo-ET) is an emerging 3D imaging technique which shows great potentials in structural biology research. One of the main challenges is to perform classification of macromolecules captured by cryo-ET. Recent efforts exploit deep learning to address this challenge. However, training reliable deep models usually requires a huge amount of labeled data in supervised fashion. Annotating cryo-ET data is arguably very expensive. Deep Active Learning (DAL) can be used to reduce labeling cost while not sacrificing the task performance too much. Nevertheless, most existing methods resort to auxiliary models or complex fashions (e.g. adversarial learning) for uncertainty estimation, the core of DAL. These models need to be highly customized for cryo-ET tasks which require 3D networks, and extra efforts are also indispensable for tuning these models, rendering a difficulty of deployment on cryo-ET tasks. To address these challenges, we propose a novel metric for data selection in DAL, which can also be leveraged as a regularizer of the empirical loss, further boosting the task model. We demonstrate the superiority of our method via extensive experiments on both simulated and real cryo-ET datasets. Our source Code and Appendix can be found at this URL.