Principles of cryo-EM single-particle image processing

Automated model-free analysis of cryo-EM volume ensembles with SIREn

Cryogenic electron microscopy (cryo-EM) has the potential to capture snapshots of proteins in motion and generate hypotheses linking conformational states to biological function. This potential has been increasingly realized by the advent of machine learning models that allow 100s-1,000s of 3D density maps to be generated from a single dataset. How to identify distinct structural states within these volume ensembles and quantify their relative occupancies remain open questions. Here, we present an approach to inferring variable regions directly from a volume ensemble based on the statistical co-occupancy of voxels, as well as a 3D convolutional neural network that predicts binarization thresholds for volumes in an unbiased and automated manner. We show that these tools recapitulate known heterogeneity in a variety of simulated and real cryo-EM datasets and highlight how integrating these tools with existing data processing pipelines enables improved particle curation.

Artificial Intelligence: A New Tool for Structure-Based G Protein-Coupled Receptor Drug Discovery

Understanding protein structures can facilitate the development of therapeutic drugs. Traditionally, protein structures have been determined through experimental approaches such as X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy. While these methods are effective and are considered the gold standard, they are very resource-intensive and time-consuming, ultimately limiting their scalability. However, with recent developments in computational biology and artificial intelligence (AI), the field of protein prediction has been revolutionized. Innovations like AlphaFold and RoseTTAFold enable protein structure predictions to be made directly from amino acid sequences with remarkable speed and accuracy. Despite the enormous enthusiasm associated with these newly developed AI-approaches, their true potential in structure-based drug discovery remains uncertain. In fact, although these algorithms generally predict overall protein structures well, essential details for computational ligand docking, such as the exact location of amino acid side chains within the binding pocket, are not predicted with the necessary accuracy. Additionally, docking methodologies are considered more as a hypothesis generator rather than a precise predictor of ligand-target interactions, and thus, usually identify many false-positive hits among only a few correctly predicted interactions. In this paper, we are reviewing the latest development in this cutting-edge field with emphasis on the GPCR target class to assess the potential role of AI approaches in structure-based drug discovery.

Automated model-free analysis of cryo-EM volume ensembles with SIREn

Cryogenic electron microscopy (cryo-EM) has the potential to capture snapshots of proteins in motion and generate hypotheses linking conformational states to biological function. This potential has been increasingly realized by the advent of machine learning models that allow 100s-1,000s of 3D density maps to be generated from a single dataset. How to identify distinct structural states within these volume ensembles and quantify their relative occupancies remain open questions. Here, we present an approach to inferring variable regions directly from a volume ensemble based on the statistical co-occupancy of voxels, as well as a 3D-convolutional neural network that predicts binarization thresholds for volumes in an unbiased and automated manner. We show that these tools recapitulate known heterogeneity in a variety of simulated and real cryo-EM datasets, and highlight how integrating these tools with existing data processing pipelines enables improved particle curation and the construction of quantitative conformational landscapes.

A deep learning method for simultaneous denoising and missing wedge reconstruction in cryogenic electron tomography

Cryogenic electron tomography is a technique for imaging biological samples in 3D. A microscope collects a series of 2D projections of the sample, and the goal is to reconstruct the 3D density of the sample called the tomogram. Reconstruction is difficult as the 2D projections are noisy and can not be recorded from all directions, resulting in a missing wedge of information. Tomograms conventionally reconstructed with filtered back-projection suffer from noise and strong artefacts due to the missing wedge. Here, we propose a deep-learning approach for simultaneous denoising and missing wedge reconstruction called DeepDeWedge. The algorithm requires no ground truth data and is based on fitting a neural network to the 2D projections using a self-supervised loss. DeepDeWedge is simpler than current state-of-the-art approaches for denoising and missing wedge reconstruction, performs competitively and produces more denoised tomograms with higher overall contrast.

Mutation-induced shift of the photosystem II active site reveals insight into conserved water channels

Photosystem II (PSII) is the water-plastoquinone photo-oxidoreductase central to oxygenic photosynthesis. PSII has been extensively studied for its ability to catalyze light-driven water oxidation at a Mn4CaO5 cluster called the oxygen-evolving complex (OEC). Despite these efforts, the complete reaction mechanism for water oxidation by PSII is still heavily debated. Previous mutagenesis studies have investigated the roles of conserved amino acids, but these studies have lacked a direct structural basis that would allow for a more meaningful interpretation. Here, we report a 2.14-Å resolution cryo-EM structure of a PSII complex containing the substitution Asp170Glu on the D1 subunit. This mutation directly perturbs a bridging carboxylate ligand of the OEC, which alters the spectroscopic properties of the OEC without fully abolishing water oxidation. The structure reveals that the mutation shifts the position of the OEC within the active site without markedly distorting the Mn4CaO5 cluster metal-metal geometry, instead shifting the OEC as a rigid body. This shift disturbs the hydrogen-bonding network of structured waters near the OEC, causing disorder in the conserved water channels. This mutation-induced disorder appears consistent with previous FTIR spectroscopic data. We further show using quantum mechanics/molecular mechanics methods that the mutation-induced structural changes can affect the magnetic properties of the OEC by altering the axes of the Jahn-Teller distortion of the Mn(III) ion coordinated to D1-170. These results offer new perspectives on the conserved water channels, the rigid body property of the OEC, and the role of D1-Asp170 in the enzymatic water oxidation mechanism.

Designing Rigid DNA Origami Templates for Molecular Visualization Using Cryo-EM

DNA origami, a method for constructing nanostructures from DNA, offers potential for diverse scientific and technological applications due to its ability to integrate various molecular functionalities in a programmable manner. In this study, we examined the impact of internal crossover distribution and the compositional uniformity of staple strands on the structure of multilayer DNA origami using cryogenic electron microscopy (cryo-EM) single-particle analysis. A refined DNA object was utilized as an alignment framework in a host-guest model, where we successfully resolved an 8 kDa thrombin binding aptamer (TBA) linked to the host object. Our results broaden the spectrum of DNA in structural applications.

Enabling cryo-EM density interpretation from yeast native cell extracts by proteomics data and AlphaFold structures

In the cellular context, proteins participate in communities to perform their function. The detection and identification of these communities as well as in-community interactions has long been the subject of investigation, mainly through proteomics analysis with mass spectrometry. With the advent of cryogenic electron microscopy and the "resolution revolution," their visualization has recently been made possible, even in complex, native samples. The advances in both fields have resulted in the generation of large amounts of data, whose analysis requires advanced computation, often employing machine learning approaches to reach the desired outcome. In this work, we first performed a robust proteomics analysis of mass spectrometry (MS) data derived from a yeast native cell extract and used this information to identify protein communities and inter-protein interactions. Cryo-EM analysis of the cell extract provided a reconstruction of a biomolecule at medium resolution (∼8 Å (FSC = 0.143)). Utilizing MS-derived proteomics data and systematic fitting of AlphaFold-predicted atomic models, this density was assigned to the 2.6 MDa complex of yeast fatty acid synthase. Our proposed workflow identifies protein complexes in native cell extracts from Saccharomyces cerevisiae by combining proteomics, cryo-EM, and AI-guided protein structure prediction.

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.

Recent advances and current trends in cryo-electron microscopy

All steps of cryogenic electron-microscopy (cryo-EM) workflows have rapidly evolved over the last decade. Advances in both single-particle analysis (SPA) cryo-EM and cryo-electron tomography (cryo-ET) have facilitated the determination of high-resolution biomolecular structures that are not tractable with other methods. However, challenges remain. For SPA, these include improved resolution in an additional dimension: time. For cryo-ET, these include accessing difficult-to-image areas of a cell and finding rare molecules. Finally, there is a need for automated and faster workflows, as many projects are limited by throughput. Here, we review current developments in SPA cryo-EM and cryo-ET that push these boundaries. Collectively, these advances are poised to propel our spatial and temporal understanding of macromolecular processes.

Structures of multisubunit membrane complexes with the CRYO ARM 200

Progress in structural membrane biology has been significantly accelerated by the ongoing 'Resolution Revolution' in cryo-electron microscopy (cryo-EM). In particular, structure determination by single-particle analysis has evolved into the most powerful method for atomic model building of multisubunit membrane protein complexes. This has created an ever-increasing demand in cryo-EM machine time, which to satisfy is in need of new and affordable cryo-electron microscopes. Here, we review our experience in using the JEOL CRYO ARM 200 prototype for the structure determination by single-particle analysis of three different multisubunit membrane complexes: the Thermus thermophilus V-type ATPase VO complex, the Thermosynechococcus elongatus photosystem I monomer and the flagellar motor lipopolysaccharide peptidoglycan ring (LP ring) from Salmonella enterica.

Membranes under the Magnetic Lens: A Dive into the Diverse World of Membrane Protein Structures Using Cryo-EM

Membrane proteins are highly diverse in both structure and function and can, therefore, present different challenges for structure determination. They are biologically important for cells and organisms as gatekeepers for information and molecule transfer across membranes, but each class of membrane proteins can present unique obstacles to structure determination. Historically, many membrane protein structures have been investigated using highly engineered constructs or using larger fusion proteins to improve solubility and/or increase particle size. Other strategies included the deconstruction of the full-length protein to target smaller soluble domains. These manipulations were often required for crystal formation to support X-ray crystallography or to circumvent lower resolution due to high noise and dynamic motions of protein subdomains. However, recent revolutions in membrane protein biochemistry and cryo-electron microscopy now provide an opportunity to solve high resolution structures of both large, >1 megadalton (MDa), and small, <100 kDa (kDa), drug targets in near-native conditions, routinely reaching resolutions around or below 3 Å. This review provides insights into how the recent advances in membrane biology and biochemistry, as well as technical advances in cryo-electron microscopy, help us to solve structures of a large variety of membrane protein groups, from small receptors to large transporters and more complex machineries.

Ab-initio contrast estimation and denoising of cryo-EM images

BACKGROUND AND OBJECTIVE

The contrast of cryo-EM images varies from one to another, primarily due to the uneven thickness of the ice layer. This contrast variation can affect the quality of 2-D class averaging, 3-D ab-initio modeling, and 3-D heterogeneity analysis. Contrast estimation is currently performed during 3-D iterative refinement. As a result, the estimates are not available at the earlier computational stages of class averaging and ab-initio modeling. This paper aims to solve the contrast estimation problem directly from the picked particle images in the ab-initio stage, without estimating the 3-D volume, image rotations, or class averages.

METHODS

The key observation underlying our analysis is that the 2-D covariance matrix of the raw images is related to the covariance of the underlying clean images, the noise variance, and the contrast variability between images. We show that the contrast variability can be derived from the 2-D covariance matrix and we apply the existing Covariance Wiener Filtering (CWF) framework to estimate it. We also demonstrate a modification of CWF to estimate the contrast of individual images.

RESULTS

Our method improves the contrast estimation by a large margin, compared to the previous CWF method. Its estimation accuracy is often comparable to that of an oracle that knows the ground truth covariance of the clean images. The more accurate contrast estimation also improves the quality of image restoration as demonstrated in both synthetic and experimental datasets.

CONCLUSIONS

This paper proposes an effective method for contrast estimation directly from noisy images without using any 3-D volume information. It enables contrast correction in the earlier stage of single particle analysis, and may improve the accuracy of downstream processing.

Cryo-electron tomography related radiation-damage parameters for individual-molecule 3D structure determination

To understand the dynamic structure-function relationship of soft- and biomolecules, the determination of the three-dimensional (3D) structure of each individual molecule (nonaveraged structure) in its native state is sought-after. Cryo-electron tomography (cryo-ET) is a unique tool for imaging an individual object from a series of tilted views. However, due to radiation damage from the incident electron beam, the tolerable electron dose limits image contrast and the signal-to-noise ratio (SNR) of the data, preventing the 3D structure determination of individual molecules, especially at high-resolution. Although recently developed technologies and techniques, such as the direct electron detector, phase plate, and computational algorithms, can partially improve image contrast/SNR at the same electron dose, the high-resolution structure, such as tertiary structure of individual molecules, has not yet been resolved. Here, we review the cryo-electron microscopy (cryo-EM) and cryo-ET experimental parameters to discuss how these parameters affect the extent of radiation damage. This discussion can guide us in optimizing the experimental strategy to increase the imaging dose or improve image SNR without increasing the radiation damage. With a higher dose, a higher image contrast/SNR can be achieved, which is crucial for individual-molecule 3D structure. With 3D structures determined from an ensemble of individual molecules in different conformations, the molecular mechanism through their biochemical reactions, such as self-folding or synthesis, can be elucidated in a straightforward manner.

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.

Applications of deep learning in electron microscopy

We review the growing use of machine learning in electron microscopy (EM) driven in part by the availability of fast detectors operating at kiloHertz frame rates leading to large data sets that cannot be processed using manually implemented algorithms. We summarize the various network architectures and error metrics that have been applied to a range of EM-related problems including denoising and inpainting. We then provide a review of the application of these in both physical and life sciences, highlighting how conventional networks and training data have been specifically modified for EM.

Label-free visual proteomics: Coupling MS- and EM-based approaches in structural biology

Combining diverse experimental structural and interactomic methods allows for the construction of comprehensible molecular encyclopedias of biological systems. Typically, this involves merging several independent approaches that provide complementary structural and functional information from multiple perspectives and at different resolution ranges. A particularly potent combination lies in coupling structural information from cryoelectron microscopy or tomography (cryo-EM or cryo-ET) with interactomic and structural information from mass spectrometry (MS)-based structural proteomics. Cryo-EM/ET allows for sub-nanometer visualization of biological specimens in purified and near-native states, while MS provides bioanalytical information for proteins and protein complexes without introducing additional labels. Here we highlight recent achievements in protein structure and interactome determination using cryo-EM/ET that benefit from additional MS analysis. We also give our perspective on how combining cryo-EM/ET and MS will continue bridging gaps between molecular and cellular studies by capturing and describing 3D snapshots of proteomes and interactomes.

It's noisy out there! A review of denoising techniques in cryo-electron tomography

Cryo-electron tomography is the only technique that can provide sub-nanometer resolved images of cell regions or even whole cells, without the need of labeling or staining methods. Technological advances over the past decade in electron microscope stability, cameras, stage precision and software have resulted in faster acquisition speeds and considerably improved resolution. In pursuit of even better image resolution, researchers seek to reduce noise - a crucial factor affecting the reliability of the tomogram interpretation and ultimately limiting the achieved resolution. Sub-tomogram averaging is the method of choice for reducing noise in repetitive objects. However, when averaging is not applicable, a trade-off between reducing noise and conserving genuine image details must be achieved. Thus, denoising is an important process that improves the interpretability of the tomogram not only directly but also by facilitating other downstream tasks, such as segmentation and 3D visualization. Here, I review contemporary denoising techniques for cryo-electron tomography by taking into account noise-specific properties of both reconstruction and detector noise. The outcomes of different techniques are compared, in order to help researchers select the most appropriate for each dataset and to achieve better and more reliable interpretation of the tomograms.

Structural heterogeneity of cellular K5/K14 filaments as revealed by cryo-electron microscopy

Keratin intermediate filaments are an essential and major component of the cytoskeleton in epithelial cells. They form a stable yet dynamic filamentous network extending from the nucleus to the cell periphery, which provides resistance to mechanical stresses. Mutations in keratin genes are related to a variety of epithelial tissue diseases. Despite their importance, the molecular structure of keratin filaments remains largely unknown. In this study, we analyzed the structure of keratin 5/keratin 14 filaments within ghost mouse keratinocytes by cryo-electron microscopy and cryo-electron tomography. By averaging a large number of keratin segments, we have gained insights into the helical architecture of the filaments. Two-dimensional classification revealed profound variations in the diameter of keratin filaments and their subunit organization. Computational reconstitution of filaments of substantial length uncovered a high degree of internal heterogeneity along single filaments, which can contain regions of helical symmetry, regions with less symmetry and regions with significant diameter fluctuations. Cross-section views of filaments revealed that keratins form hollow cylinders consisting of multiple protofilaments, with an electron dense core located in the center of the filament. These findings shed light on the complex and remarkable heterogenic architecture of keratin filaments, suggesting that they are highly flexible, dynamic cytoskeletal structures.

Routine sub-2.5 Å cryo-EM structure determination of GPCRs

Cryo-electron microscopy (cryo-EM) of small membrane proteins, such as G protein-coupled receptors (GPCRs), remains challenging. Pushing the performance boundaries of the technique requires quantitative knowledge about the contribution of multiple factors. Here, we present an in-depth analysis and optimization of the main experimental parameters in cryo-EM. We combined actual structural studies with methods development to quantify the effects of the Volta phase plate, zero-loss energy filtering, objective lens aperture, defocus magnitude, total exposure, and grid type. By using this information to carefully maximize the experimental performance, it is now possible to routinely determine GPCR structures at resolutions better than 2.5 Å. The improved fidelity of such maps enables the building of better atomic models and will be crucial for the future expansion of cryo-EM into the structure-based drug design domain. The optimization guidelines given here are not limited to GPCRs and can be applied directly to other small proteins.

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.

Centering Noisy Images with Application to Cryo-EM

We target the problem of estimating the center of mass of objects in noisy two-dimensional images. We assume that the noise dominates the image, and thus many standard approaches are vulnerable to estimation errors, e.g., the direct computation of the center of mass and the geometric median which is a robust alternative to the center of mass. In this paper, we define a novel surrogate function to the center of mass. We present a mathematical and numerical analysis of our method and show that it outperforms existing methods for estimating the center of mass of an object in various realistic scenarios. As a case study, we apply our centering method to data from single-particle cryo-electron microscopy (cryo-EM), where the goal is to reconstruct the three-dimensional structure of macromolecules. We show how to apply our approach for a better translational alignment of molecule images picked from experimental data. In this way, we facilitate the succeeding steps of reconstruction and streamline the entire cryo-EM pipeline, saving computational time and supporting resolution enhancement.

2.5 Å-resolution structure of human CDK-activating kinase bound to the clinical inhibitor ICEC0942

The human CDK-activating kinase (CAK), composed of CDK7, cyclin H, and MAT1, is involved in the control of transcription initiation and the cell cycle. Because of these activities, it has been identified as a promising target for cancer chemotherapy. A number of CDK7 inhibitors have entered clinical trials, among them ICEC0942 (also known as CT7001). Structural information can aid in improving the affinity and specificity of such drugs or drug candidates, reducing side effects in patients. Here, we have determined the structure of the human CAK in complex with ICEC0942 at 2.5 Å-resolution using cryogenic electron microscopy. Our structure reveals conformational differences of ICEC0942 compared with previous X-ray crystal structures of the CDK2-bound complex, and highlights the critical ability of cryogenic electron microscopy to resolve structures of drug-bound protein complexes without the need to crystalize the protein target.

CryoDRGN: reconstruction of heterogeneous cryo-EM structures using neural networks

Cryo-electron microscopy (cryo-EM) single-particle analysis has proven powerful in determining the structures of rigid macromolecules. However, many imaged protein complexes exhibit conformational and compositional heterogeneity that poses a major challenge to existing three-dimensional reconstruction methods. Here, we present cryoDRGN, an algorithm that leverages the representation power of deep neural networks to directly reconstruct continuous distributions of 3D density maps and map per-particle heterogeneity of single-particle cryo-EM datasets. Using cryoDRGN, we uncovered residual heterogeneity in high-resolution datasets of the 80S ribosome and the RAG complex, revealed a new structural state of the assembling 50S ribosome, and visualized large-scale continuous motions of a spliceosome complex. CryoDRGN contains interactive tools to visualize a dataset's distribution of per-particle variability, generate density maps for exploratory analysis, extract particle subsets for use with other tools and generate trajectories to visualize molecular motions. CryoDRGN is open-source software freely available at http://cryodrgn.csail.mit.edu .

Structural Heterogeneities of the Ribosome: New Frontiers and Opportunities for Cryo-EM

The extent of ribosomal heterogeneity has caught increasing interest over the past few years, as recent studies have highlighted the presence of structural variations of the ribosome. More precisely, the heterogeneity of the ribosome covers multiple scales, including the dynamical aspects of ribosomal motion at the single particle level, specialization at the cellular and subcellular scale, or evolutionary differences across species. Upon solving the ribosome atomic structure at medium to high resolution, cryogenic electron microscopy (cryo-EM) has enabled investigating all these forms of heterogeneity. In this review, we present some recent advances in quantifying ribosome heterogeneity, with a focus on the conformational and evolutionary variations of the ribosome and their functional implications. These efforts highlight the need for new computational methods and comparative tools, to comprehensively model the continuous conformational transition pathways of the ribosome, as well as its evolution. While developing these methods presents some important challenges, it also provides an opportunity to extend our interpretation and usage of cryo-EM data, which would more generally benefit the study of molecular dynamics and evolution of proteins and other complexes.

Deep-learning with synthetic data enables automated picking of cryo-EM particle images of biological macromolecules

MOTIVATION

Single-particle cryo-electron microscopy (cryo-EM) has become a powerful technique for determining 3D structures of biological macromolecules at near-atomic resolution. However, this approach requires picking huge numbers of macromolecular particle images from thousands of low-contrast, high-noisy electron micrographs. Although machine-learning methods were developed to get rid of this bottleneck, it still lacks universal methods that could automatically picking the noisy cryo-EM particles of various macromolecules.

RESULTS

Here, we present a deep-learning segmentation model that employs fully convolutional networks trained with synthetic data of known 3D structures, called PARSED (PARticle SEgmentation Detector). Without using any experimental information, PARSED could automatically segment the cryo-EM particles in a whole micrograph at a time, enabling faster particle picking than previous template/feature-matching and particle-classification methods. Applications to six large public cryo-EM datasets clearly validated its universal ability to pick macromolecular particles of various sizes. Thus, our deep-learning method could break the particle-picking bottleneck in the single-particle analysis, and thereby accelerates the high-resolution structure determination by cryo-EM.

AVAILABILITY AND IMPLEMENTATION

The PARSED package and user manual for noncommercial use are available as Supplementary Material (in the compressed file: parsed_v1.zip).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The cryoelectron microscopy structure of the human CDK-activating kinase

The human CDK-activating kinase (CAK), a complex composed of cyclin-dependent kinase (CDK) 7, cyclin H, and MAT1, is a critical regulator of transcription initiation and the cell cycle. It acts by phosphorylating the C-terminal heptapeptide repeat domain of the RNA polymerase II (Pol II) subunit RPB1, which is an important regulatory event in transcription initiation by Pol II, and it phosphorylates the regulatory T-loop of CDKs that control cell cycle progression. Here, we have determined the three-dimensional (3D) structure of the catalytic module of human CAK, revealing the structural basis of its assembly and providing insight into CDK7 activation in this context. The unique third component of the complex, MAT1, substantially extends the interaction interface between CDK7 and cyclin H, explaining its role as a CAK assembly factor, and it forms interactions with the CDK7 T-loop, which may contribute to enhancing CAK activity. We have also determined the structure of the CAK in complex with the covalently bound inhibitor THZ1 in order to provide insight into the binding of inhibitors at the CDK7 active site and to aid in the rational design of therapeutic compounds.

WITHDRAWN: Structural studies of vitrified biological proteins and macromolecules - A review on the microimaging aspects of cryo-electron microscopy

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Mitochondrial F-ATP synthase as the permeability transition pore

The current state of research on the mitochondrial permeability transition pore (PTP) can be described in terms of three major problems: molecular identity, atomic structure and gating mechanism. In this review these three problems are discussed in the light of recent findings with special emphasis on the discovery that the PTP is mitochondrial F-ATP synthase (mtF_oF₁). Novel features of the mitochondrial F-ATP synthase emerging from the success of single particle cryo electron microscopy (cryo-EM) to determine F-ATP synthase structures are surveyed along with their possible involvement in pore formation. Also, current findings from the gap junction field concerning the involvement of lipids in channel closure are examined. Finally, an earlier proposal denoted as the 'Death Finger' is discussed as a working model for PTP gating.

Arrangement of the Polymerase Complexes inside a Nine-Segmented dsRNA Virus

Members of the family Reoviridae package several copies of the viral polymerase complex into their capsid to carry out replication and transcription within viral particles. Classical single-particle reconstruction encounters difficulties resolving structures such as the intraparticle polymerase complex because refinement can converge to an incorrect map and because the map could depict a nonrepresentative subset of particles or an average of heterogeneous particles. Using the nine-segmented Fako virus, we tested hypotheses for the arrangement and number of polymerase complexes within the virion by measuring how well each hypothesis describes the set of cryoelectron microscopy images of individual viral particles. We find that the polymerase complex in Fako virus binds at ten possible sites despite having only nine genome segments. A single asymmetric configuration describes the arrangement of these complexes in both virions and genome-free capsids. Similarities between the arrangements of Reoviridae with 9, 10, and 11 segments indicate the generalizability of this architecture.

POLARIS: Path of Least Action Analysis on Energy Landscapes

Free-energy landscapes are a powerful tool for analyzing dynamical processes - capable of providing a complete mapping of a system's configurations in state space while articulating its energetics topologically in the form of sprawling hills and valleys. Within this mapping, the path of least action can be derived - representing the most probable sequence of transitions taken between any two states in the landscape. In this article, POLARIS (Path of Least Action Recursive Survey) is presented as a dynamic, global approach that efficiently automates the discovery of the least action path on previously determined 2D energy landscapes. Important built-in features of this program include plotting of landscape trajectories and transition state theory diagrams, generation of text files with least action coordinates and respective energies, and bifurcation analysis tools that provide downstream versatility for comparing most probable paths and reaction rates.

Cryo-Electron microscopy for the study of self-assembled poly(ionic liquid) nanoparticles and protein supramolecular structures

Cryo-electron microscopy (cryo-EM) is a powerful structure determination technique that is well-suited to the study of protein and polymer self-assembly in solution. In contrast to conventional transmission electron microscopy (TEM) sample preparation, which often times involves drying and staining, the frozen-hydrated sample preparation allows the specimens to be kept and imaged in a state closest to their native one. Here, we give a short overview of the basic principles of Cryo-EM and review our results on applying it to the study of different protein and polymer self-assembled nanostructures. More specifically, we show how we have applied cryo-electron tomography (cryo-ET) to visualize the internal morphology of self-assembled poly(ionic liquid) nanoparticles and cryo-EM single particle analysis (SPA) to determine the three-dimensional (3D) structures of artificial protein microtubules.

Fast and accurate defocus modulation for improved tunability of cryo-EM experiments

Current data collection strategies in electron cryo-microscopy (cryo-EM) record multiframe movies with static optical settings. This limits the number of adjustable parameters that can be used to optimize the experiment. Here, a method for fast and accurate defocus (FADE) modulation during movie acquisition is proposed. It uses the objective lens aperture as an electrostatic pole that locally modifies the electron beam potential. The beam potential variation is converted to defocus change by the typically undesired chromatic aberration of the objective lens. The simplicity, electrostatic principle and low electrical impedance of the device allow fast switching speeds that will enable per-frame defocus modulation of cryo-EM movies. Researchers will be able to define custom defocus 'recipes' and tailor the experiment for optimal information extraction from the sample. The FADE method could help to convert the microscope into a more dynamic and flexible optical platform that delivers better performance in cryo-EM single-particle analysis and electron cryo-tomography.

Joint Angular Refinement and Reconstruction for Single-Particle Cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) reconstructs the three-dimensional (3D) structure of biomolecules from a large set of 2D projection images with random and unknown orientations. A crucial step in the single-particle cryo-EM pipeline is 3D refinement, which resolves a highresolution 3D structure from an initial approximate volume by refining the estimation of the orientation of each projection. In this work, we propose a new approach that refines the projection angles on the continuum. We formulate the optimization problem over the density map and the orientations jointly. The density map is updated using the efficient alternating-direction method of multipliers, while the orientations are updated through a semicoordinate- wise gradient descent for which we provide an explicit derivation of the gradient. Our method eliminates the requirement for a fine discretization of the orientation space and does away with the classical but computationally expensive templatematching step. Numerical results demonstrate the feasibility and performance of our approach compared to several baselines.

A Technical Introduction to Transmission Electron Microscopy for Soft-Matter: Imaging, Possibilities, Choices, and Technical Developments

With a significant role in material sciences, physics, (soft matter) chemistry, and biology, the transmission electron microscope is one of the most widely applied structural analysis tool to date. It has the power to visualize almost everything from the micrometer to the angstrom scale. Technical developments keep opening doors to new fields of research by improving aspects such as sample preservation, detector performance, computational power, and workflow automation. For more than half a century, and continuing into the future, electron microscopy has been, and is, a cornerstone methodology in science. Herein, the technical considerations of imaging with electrons in terms of optics, technology, samples and processing, and targeted soft materials are summarized. Furthermore, recent advances and their potential for application to soft matter chemistry are highlighted.

Hyper-Molecules: on the Representation and Recovery of Dynamical Structures for Applications in Flexible Macro-Molecules in Cryo-EM

Cryo-electron microscopy (cryo-EM), the subject of the 2017 Nobel Prize in Chemistry, is a technology for obtaining 3-D reconstructions of macromolecules from many noisy 2-D projections of instances of these macromolecules, whose orientations and positions are unknown. These molecules are not rigid objects, but flexible objects involved in dynamical processes. The different conformations are exhibited by different instances of the macromolecule observed in a cryo-EM experiment, each of which is recorded as a particle image. The range of conformations and the conformation of each particle are not known a priori; one of the great promises of cryo-EM is to map this conformation space. Remarkable progress has been made in reconstructing rigid molecules based on homogeneous samples of molecules in spite of the unknown orientation of each particle image and significant progress has been made in recovering a few distinct states from mixtures of rather distinct conformations, but more complex heterogeneous samples remain a major challenge. We introduce the "hyper-molecule" theoretical framework for modeling structures across different states of heterogeneous molecules, including continuums of states. The key idea behind this framework is representing heterogeneous macromolecules as high-dimensional objects, with the additional dimensions representing the conformation space. This idea is then refined to model properties such as localized heterogeneity. In addition, we introduce an algorithmic framework for reconstructing such heterogeneous objects from experimental data using a Bayesian formulation of the problem and Markov chain Monte Carlo (MCMC) algorithms to address the computational challenges in recovering these high dimensional hyper-molecules. We demonstrate these ideas in a preliminary prototype implementation, applied to synthetic data.

In situ structure determination at nanometer resolution using TYGRESS

The resolution of subtomogram averages calculated from cryo-electron tomograms (cryo-ET) of crowded cellular environments is often limited owing to signal loss in, and misalignment of, the subtomograms. By contrast, single-particle cryo-electron microscopy (SP-cryo-EM) routinely reaches near-atomic resolution of isolated complexes. We report a method called 'tomography-guided 3D reconstruction of subcellular structures' (TYGRESS) that is a hybrid of cryo-ET and SP-cryo-EM, and is able to achieve close-to-nanometer resolution of complexes inside crowded cellular environments. TYGRESS combines the advantages of SP-cryo-EM (images with good signal-to-noise ratio and contrast, as well as minimal radiation damage) and subtomogram averaging (three-dimensional alignment of macromolecules in a complex sample). Using TYGRESS, we determined the structure of the intact ciliary axoneme with up to resolution of 12 Å. These results reveal many structural details that were not visible by cryo-ET alone. TYGRESS is generally applicable to cellular complexes that are amenable to subtomogram averaging.

Filling Adeno-Associated Virus Capsids: Estimating Success by Cryo-Electron Microscopy

Adeno-associated viruses (AAVs) have been employed successfully as gene therapy vectors in treating various genetic diseases for almost two decades. However, transgene packaging is usually imperfect, and developing a rapid and accurate method for measuring the proportion of DNA encapsidation is an important step for improving the downstream process of large scale vector production. In this study, we used two-dimensional class averages and three-dimensional classes, intermediate outputs in the single particle cryo-electron microscopy (cryo-EM) image reconstruction pipeline, to determine the proportion of DNA-packaged and empty capsid populations. Two different preparations of AAV3 were analyzed to estimate the minimum number of particles required to be sampled by cryo-EM in order for robust calculation of the proportion of the full versus empty capsids in any given sample. Cost analysis applied to the minimum amount of data required for a valid ratio suggests that cryo-EM is an effective approach to analyze vector preparations.

Structure Determination by Single-Particle Cryo-Electron Microscopy: Only the Sky (and Intrinsic Disorder) is the Limit

Traditionally, X-ray crystallography and NMR spectroscopy represent major workhorses of structural biologists, with the lion share of protein structures reported in protein data bank (PDB) being generated by these powerful techniques. Despite their wide utilization in protein structure determination, these two techniques have logical limitations, with X-ray crystallography being unsuitable for the analysis of highly dynamic structures and with NMR spectroscopy being restricted to the analysis of relatively small proteins. In recent years, we have witnessed an explosive development of the techniques based on Cryo-electron microscopy (Cryo-EM) for structural characterization of biological molecules. In fact, single-particle Cryo-EM is a special niche as it is a technique of choice for the structural analysis of large, structurally heterogeneous, and dynamic complexes. Here, sub-nanometer atomic resolution can be achieved (i.e., resolution below 10 Å) via single-particle imaging of non-crystalline specimens, with accurate 3D reconstruction being generated based on the computational averaging of multiple 2D projection images of the same particle that was frozen rapidly in solution. We provide here a brief overview of single-particle Cryo-EM and show how Cryo-EM has revolutionized structural investigations of membrane proteins. We also show that the presence of intrinsically disordered or flexible regions in a target protein represents one of the major limitations of this promising technique.

"Differential Visual Proteomics": Enabling the Proteome-Wide Comparison of Protein Structures of Single-Cells

Proteins are involved in all tasks of life, and their characterization is essential to understand the underlying mechanisms of biological processes. We present a method called "differential visual proteomics" geared to study proteome-wide structural changes of proteins and protein-complexes between a disturbed and an undisturbed cell or between two cell populations. To implement this method, the cells are lysed and the lysate is prepared in a lossless manner for single-particle electron microscopy (EM). The samples are subsequently imaged in the EM. Individual particles are computationally extracted from the images and pooled together, while keeping track of which particle originated from which specimen. The extracted particles are then aligned and classified. A final quantitative analysis of the particle classes found identifies the particle structures that differ between positive and negative control samples. The algorithm and a graphical user interface developed to perform the analysis and to visualize the results were tested with simulated and experimental data. The results are presented, and the potential and limitations of the current implementation are discussed. We envisage the method as a tool for the untargeted profiling of the structural changes in the proteome of single-cells as a response to a disturbing force.

3D Conformations of Thick Synthetic Polymer Chains Observed by Cryogenic Electron Microscopy

The backbone conformations of individual, unperturbed synthetic macromolecules have so far not been observed directly in spite of their fundamental importance to polymer physics. Here we report the dilute solution conformations of two types of linear dendronized polymers, obtained by cryogenic transmission electron stereography and tomography. The three-dimensional trajectories show that the wormlike chain model fails to adequately describe the scaling of these thick macromolecules already beyond a few nanometers in chain length, in spite of large apparent persistence lengths and long before a signature of self-avoidance appears. This insight is essential for understanding the limitations of polymer physical models, and it motivated us to discuss the advantages and disadvantages of this approach in comparison to the commonly applied scattering techniques.

Towards structural biology with super-resolution microscopy

Fluorescence resonance energy transfer (FRET) has been instrumental in determining the structure and dynamics of biomolecules but distances above 8 nanometers are not accessible. However, with the advent and rapid development of super-resolution (SR) microscopy, distances between two fluorescent dyes below 20 nanometers can be resolved, which hitherto has been inaccessible for fluorescence microscopy approaches due to the limited resolving power of an optical imaging system that is determined by the fundamental laws of light diffraction (referred to as the diffraction limit). Therefore, the question arises whether SR microscopy can ultimately close the resolution gap between FRET and the diffraction limit and whether SR microscopy can be employed for the structural interrogation of proteins in the sub-20 nm range? Here, we show that the combination of DNA nanotechnology and single-molecule biochemistry allows the first step towards the investigation of the structural organization of a protein via SR microscopy. Limiting factors and possible future directions for the full implementation of SR microscopy as a structural tool are discussed.

Dawning of a new era in TRP channel structural biology by cryo-electron microscopy

Cryo-electron microscopy (cryo-EM) permits the determination of atomic protein structures by averaging large numbers of individual projection images recorded at cryogenic temperatures-a method termed single-particle analysis. The cryo-preservation traps proteins within a thin glass-like ice layer, making literally a freeze image of proteins in solution. Projections of randomly adopted orientations are merged to reconstruct a 3D density map. While atomic resolution for highly symmetric viruses was achieved already in 2009, the development of new sensitive and fast electron detectors has enabled cryo-EM for smaller and asymmetrical proteins including fragile membrane proteins. As one of the most important structural biology methods at present, cryo-EM was awarded in October 2017 with the Nobel Prize in Chemistry. The molecular understanding of Transient-Receptor-Potential (TRP) channels has been boosted tremendously by cryo-EM single-particle analysis. Several near-atomic and atomic structures gave important mechanistic insights, e.g., into ion permeation and selectivity, gating, as well as into the activation of this enigmatic and medically important membrane protein family by various chemical and physical stimuli. Lastly, these structures have set the starting point for the rational design of TRP channel-targeted therapeutics to counteract life-threatening channelopathies. Here, we attempt a brief introduction to the method, review the latest advances in cryo-EM structure determination of TRP channels, and discuss molecular insights into the channel function based on the wealth of TRP channel cryo-EM structures.