Cryo-Electron Microscopy Methodology: Current Aspects and Future Directions

Super-Resolution Detection of DNA Nanostructures Using a Nanopore

High-resolution analysis of biomolecules has brought unprecedented insights into fundamental biological processes and dramatically advanced biosensing. Notwithstanding the ongoing resolution revolution in electron microscopy and optical imaging, only a few methods are presently available for high-resolution analysis of unlabeled single molecules in their native states. Here, label-free electrical sensing of structured single molecules with a spatial resolution down to single-digit nanometers is demonstrated. Using a narrow solid-state nanopore, the passage of a series of nanostructures attached to a freely translocating DNA molecule is detected, resolving individual nanostructures placed as close as 6 nm apart and with a surface-to-surface gap distance of only 2 nm. Such super-resolution ability is attributed to the nanostructure-induced enhancement of the electric field at the tip of the nanopore. This work demonstrates a general approach to improving the resolution of single-molecule nanopore sensing and presents a critical advance towards label-free, high-resolution DNA sequence mapping, and digital information storage independent of molecular motors.

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.

Phase Separation of Rubisco by the Folded SSUL Domains of CcmM in Beta-Carboxysome Biogenesis

Carboxysomes are large, cytosolic bodies present in all cyanobacteria and many proteobacteria that function as the sites of photosynthetic CO₂ fixation by the enzyme ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco). The carboxysome lumen is enriched with Rubisco and carbonic anhydrase (CA). The polyhedral proteinaceous shell allows the passage of HCO₃^- ions into the carboxysome, where they are converted to CO₂ by CA. Thus, the carboxysome functions as a CO₂-concentrating mechanism (CCM), enhancing the efficiency of Rubisco in CO₂ fixation. In β-cyanobacteria, carboxysome biogenesis first involves the aggregation of Rubisco by CcmM, a scaffolding protein that exists in two isoforms. Both isoforms contain a minimum of three Rubisco small subunit-like (SSUL) domains, connected by flexible linkers. Multivalent interaction between these linked SSUL domains with Rubisco results in phase separation and condensate formation. Here, we use Rubisco and the short isoform of CcmM (M35) of the β-cyanobacterium Synechococcus elongatus PCC7942 to describe the methods used for in vitro analysis of the mechanism of condensate formation driven by the SSUL domains. The methods include turbidity assays, bright-field and fluorescence microscopy, as well as transmission electron microscopy (TEM) in both negative staining and cryo-conditions.

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.

Maximum-likelihood model fitting for quantitative analysis of SMLM data

Quantitative data analysis is important for any single-molecule localization microscopy (SMLM) workflow to extract biological insights from the coordinates of the single fluorophores. However, current approaches are restricted to simple geometries or require identical structures. Here, we present LocMoFit (Localization Model Fit), an open-source framework to fit an arbitrary model to localization coordinates. It extracts meaningful parameters from individual structures and can select the most suitable model. In addition to analyzing complex, heterogeneous and dynamic structures for in situ structural biology, we demonstrate how LocMoFit can assemble multi-protein distribution maps of six nuclear pore components, calculate single-particle averages without any assumption about geometry or symmetry, and perform a time-resolved reconstruction of the highly dynamic endocytic process from static snapshots. We provide extensive simulation and visualization routines to validate the robustness of LocMoFit and tutorials to enable any user to increase the information content they can extract from their SMLM data.

Characterizing the resolution and throughput of the Apollo direct electron detector

Advances in electron detection have been essential to the success of high-resolution cryo-EM structure determination. A new generation of direct electron detector called the Apollo, has been developed by Direct Electron. The Apollo uses a novel event-based MAPS detector custom designed for ultra-fast electron counting. We have evaluated this new camera, finding that it delivers high detective quantum efficiency (DQE) and low coincidence loss, enabling high-quality electron counting data acquisition at up to nearly 80 input electrons per pixel per second. We further characterized the performance of Apollo for single particle cryo-EM on real biological samples. Using mouse apoferritin, Apollo yielded better than 1.9 Å resolution reconstructions at all three tested dose rates from a half-day data collection session each. With longer collection time and improved specimen preparation, mouse apoferritin was reconstructed to 1.66 Å resolution. Applied to a more challenging small protein aldolase, we obtained a 2.24 Å resolution reconstruction. The high quality of the map indicates that the Apollo has sufficiently high DQE to reconstruct smaller proteins and complexes with high-fidelity. Our results demonstrate that the Apollo camera performs well across a broad range of dose rates and is capable of capturing high quality data that produce high-resolution reconstructions for large and small single particle samples.

Stability and expression of SARS-CoV-2 spike-protein mutations

Protein fold stability likely plays a role in SARS-CoV-2 S-protein evolution, together with ACE2 binding and antibody evasion. While few thermodynamic stability data are available for S-protein mutants, many systematic experimental data exist for their expression. In this paper, we explore whether such expression levels relate to the thermodynamic stability of the mutants. We studied mutation-induced SARS-CoV-2 S-protein fold stability, as computed by three very distinct methods and eight different protein structures to account for method- and structure-dependencies. For all methods and structures used (24 comparisons), computed stability changes correlate significantly (99% confidence level) with experimental yeast expression from the literature, such that higher expression is associated with relatively higher fold stability. Also significant, albeit weaker, correlations were seen between stability and ACE2 binding effects. The effect of thermodynamic fold stability may be direct or a correlate of amino acid or site properties, notably the solvent exposure of the site. Correlation between computed stability and experimental expression and ACE2 binding suggests that functional properties of the SARS-CoV-2 S-protein mutant space are largely determined by a few simple features, due to underlying correlations. Our study lends promise to the development of computational tools that may ideally aid in understanding and predicting SARS-CoV-2 S-protein evolution.

Structural heterogeneity and precision of implications drawn from cryo-electron microscopy structures: SARS-CoV-2 spike-protein mutations as a test case

Protein structures may be used to draw functional implications at the residue level, but how sensitive are these implications to the exact structure used? Calculation of the effects of SARS-CoV-2 S-protein mutations based on experimental cryo-electron microscopy structures have been abundant during the pandemic. To understand the precision of such estimates, we studied three distinct methods to estimate stability changes for all possible mutations in 23 different S-protein structures (3.69 million ΔΔG values in total) and explored how random and systematic errors can be remedied by structure-averaged mutation group comparisons. We show that computational estimates have low precision, due to method and structure heterogeneity making results for single mutations uninformative. However, structure-averaged differences in mean effects for groups of substitutions can yield significant results. Illustrating this protocol, functionally important natural mutations, despite individual variations, average to a smaller stability impact compared to other possible mutations, independent of conformational state (open, closed). In summary, we document substantial issues with precision in structure-based protein modeling and recommend sensitivity tests to quantify these effects, but also suggest partial solutions to the problem in the form of structure-averaged “ensemble” estimates for groups of residues when multiple structures are available.

Integrative modeling of the cell

A whole-cell model represents certain aspects of the cell structure and/or function. Due to the high complexity of the cell, an integrative modeling approach is often taken to utilize all available information including experimental data, prior knowledge and prior models. In this review, we summarize an emerging workflow of whole-cell modeling into five steps: (i) gather information; (ii) represent the modeled system into modules; (iii) translate input information into scoring function; (iv) sample the whole-cell model; (v) validate and interpret the model. In particular, we propose the integrative modeling of the cell by combining available (whole-cell) models to maximize the accuracy, precision, and completeness. In addition, we list quantitative predictions of various aspects of cell biology from existing whole-cell models. Moreover, we discuss the remaining challenges and future directions, and highlight the opportunity to establish an integrative spatiotemporal multi-scale whole-cell model based on a community approach.

Three-dimensional electron ptychography of organic-inorganic hybrid nanostructures

Three dimensional scaffolded DNA origami with inorganic nanoparticles has been used to create tailored multidimensional nanostructures. However, the image contrast of DNA is poorer than those of the heavy nanoparticles in conventional transmission electron microscopy at high defocus so that the biological and non-biological components in 3D scaffolds cannot be simultaneously resolved using tomography of samples in a native state. We demonstrate the use of electron ptychography to recover high contrast phase information from all components in a DNA origami scaffold without staining. We further quantitatively evaluate the enhancement of contrast in comparison with conventional transmission electron microscopy. In addition, We show that for ptychography post-reconstruction focusing simplifies the workflow and reduces electron dose and beam damage.

The authors demonstrate electron ptychographic computed tomography by simultaneously recording high contrast data from both the organic- and inorganic components in a 3D DNA-origami framework hybrid nanostructure.

Neurons: The Interplay between Cytoskeleton, Ion Channels/Transporters and Mitochondria

Neurons are permanent cells whose key feature is information transmission via chemical and electrical signals. Therefore, a finely tuned homeostasis is necessary to maintain function and preserve neuronal lifelong survival. The cytoskeleton, and in particular microtubules, are far from being inert actors in the maintenance of this complex cellular equilibrium, and they participate in the mobilization of molecular cargos and organelles, thus influencing neuronal migration, neuritis growth and synaptic transmission. Notably, alterations of cytoskeletal dynamics have been linked to alterations of neuronal excitability. In this review, we discuss the characteristics of the neuronal cytoskeleton and provide insights into alterations of this component leading to human diseases, addressing how these might affect excitability/synaptic activity, as well as neuronal functioning. We also provide an overview of the microscopic approaches to visualize and assess the cytoskeleton, with a specific focus on mitochondrial trafficking.

Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction

Ion mobility (IM) mass spectrometry provides structural information about protein shape and size in the form of an orientationally-averaged collision cross-section (CCSIM). While IM data have been used with various computational methods, they have not yet been utilized to predict monomeric protein structure from sequence. Here, we show that IM data can significantly improve protein structure determination using the modelling suite Rosetta. We develop the Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm that allows for fast and accurate prediction of CCSIM from structure. Following successful testing of the PARCS algorithm, we use an integrative modelling approach to utilize IM data for protein structure prediction. Additionally, we propose a confidence metric that identifies near native models in the absence of a known structure. The results of this study demonstrate the ability of IM data to consistently improve protein structure prediction.

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

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

Recent advances in RNA structurome

RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes (e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.

Structural basis for the mechanisms of human presequence protease conformational switch and substrate recognition

Presequence protease (PreP), a 117 kDa mitochondrial M16C metalloprotease vital for mitochondrial proteostasis, degrades presequence peptides cleaved off from nuclear-encoded proteins and other aggregation-prone peptides, such as amyloid β (Aβ). PreP structures have only been determined in a closed conformation; thus, the mechanisms of substrate binding and selectivity remain elusive. Here, we leverage advanced vitrification techniques to overcome the preferential denaturation of one of two ~55 kDa homologous domains of PreP caused by air-water interface adsorption. Thereby, we elucidate cryoEM structures of three apo-PreP open states along with Aβ- and citrate synthase presequence-bound PreP at 3.3–4.6 Å resolution. Together with integrative biophysical and pharmacological approaches, these structures reveal the key stages of the PreP catalytic cycle and how the binding of substrates or PreP inhibitor drives a rigid body motion of the protein for substrate binding and catalysis. Together, our studies provide key mechanistic insights into M16C metalloproteases for future therapeutic innovations.

Presequence protease (PreP) is essential to mitochondrial proteostasis. This study leverages advanced vitrification techniques to solve cryoEM structures of apo- and substrate-bound PreP and integrates these data with other analysis to reveal key stages and mechanistic insights of the PreP catalytic cycle.

Hierarchical autoclassification of cryo-EM samples and macromolecular energy landscape determination

BACKGROUND AND OBJECTIVE

Cryo-electron microscopy using single particle analysis is a powerful technique for obtaining 3D reconstructions of macromolecules in near native conditions. One of its major advances is its capacity to reveal conformations of dynamic molecular complexes. Most popular and successful current approaches to analyzing heterogeneous complexes are founded on Bayesian inference. However, these 3D classification methods require the tuning of specific parameters by the user and the use of complicated 3D re-classification procedures for samples affected by extensive heterogeneity. Thus, the success of these approaches highly depends on the user experience. We introduce a robust approach to identify many different conformations presented in a cryo-EM dataset based on Bayesian inference through Relion classification methods that does not require tuning of parameters and reclassification strategies.

METHODS

The algorithm allows both 2D and 3D classification and is based on a hierarchical clustering approach that runs automatically without requiring typical inputs, such as the number of conformations present in the dataset or the required classification iterations. This approach is applied to robustly determine the energy landscapes of macromolecules.

RESULTS

We tested the performance of the methods proposed here using four different datasets, comprising structurally homogeneous and highly heterogeneous cases. In all cases, the approach provided excellent results. The routines are publicly available as part of the CryoMethods plugin included in the Scipion package.

CONCLUSIONS

Our results show that the proposed method can be used to align and classify homogeneous and heterogeneous datasets without requiring previous alignment information or any prior knowledge about the number of co-existing conformations. The approach can be used for both 2D and 3D autoclassification and only requires an initial volume. In addition, the approach is robust to the "attractor" problem providing many different conformations/views for samples affected by extensive heterogeneity. The obtained 3D classes can render high resolution 3D structures, while the obtained energy landscapes can be used to determine structural trajectories.

Heterogeneous cryo-EM projection image classification using a two-stage spectral clustering based on novel distance measures

Single-particle cryo-electron microscopy (cryo-EM) has become one of the mainstream technologies in the field of structural biology to determine the three-dimensional (3D) structures of biological macromolecules. Heterogeneous cryo-EM projection image classification is an effective way to discover conformational heterogeneity of biological macromolecules in different functional states. However, due to the low signal-to-noise ratio of the projection images, the classification of heterogeneous cryo-EM projection images is a very challenging task. In this paper, two novel distance measures between projection images integrating the reliability of common lines, pixel intensity and class averages are designed, and then a two-stage spectral clustering algorithm based on the two distance measures is proposed for heterogeneous cryo-EM projection image classification. In the first stage, the novel distance measure integrating common lines and pixel intensities of projection images is used to obtain preliminary classification results through spectral clustering. In the second stage, another novel distance measure integrating the first novel distance measure and class averages generated from each group of projection images is used to obtain the final classification results through spectral clustering. The proposed two-stage spectral clustering algorithm is applied on a simulated and a real cryo-EM dataset for heterogeneous reconstruction. Results show that the two novel distance measures can be used to improve the classification performance of spectral clustering, and using the proposed two-stage spectral clustering algorithm can achieve higher classification and reconstruction accuracy than using RELION and XMIPP.

Cryo-EM advances in RNA structure determination

Cryo-electron microscopy (cryo-EM) has emerged as an unprecedented tool to resolve protein structures at atomic resolution. Structural insights of biological samples not accessible by conventional X-ray crystallography and NMR can be explored with cryo-EM because measurements are carried out under near-native crystal-free conditions, and large protein complexes with conformational and compositional heterogeneity are readily resolved. RNA has remained underexplored in cryo-EM, despite its essential role in various biological processes. This review highlights current challenges and recent progress in using cryo-EM single-particle analysis to determine protein-free RNA structures, enabled by improvement in sample preparation and integration of multiple structural and biochemical methods.

Drug discovery in the era of cryo-electron microscopy

Structure-based drug discovery (SBDD) is an indispensable approach for the design and optimization of new therapeutic agents. Here, we highlight the rapid progress that has turned cryo-electron microscopy (cryoEM) into an exceptional SBDD tool, and the wealth of new structural information it is providing for high-value pharmacological targets. We review key advantages of a technique that directly images vitrified biomolecules without the need for crystallization; both in terms of a broader array of systems that can be studied and the different forms of information it can provide, including heterogeneity and dynamics. We discuss near- and far-future developments, working in concert towards achieving the resolution and throughput necessary for cryoEM to make a widespread impact on the SBDD pipeline.

Computational Methods for Single-Cell Imaging and Omics Data Integration

Integrating single cell omics and single cell imaging allows for a more effective characterisation of the underlying mechanisms that drive a phenotype at the tissue level, creating a comprehensive profile at the cellular level. Although the use of imaging data is well established in biomedical research, its primary application has been to observe phenotypes at the tissue or organ level, often using medical imaging techniques such as MRI, CT, and PET. These imaging technologies complement omics-based data in biomedical research because they are helpful for identifying associations between genotype and phenotype, along with functional changes occurring at the tissue level. Single cell imaging can act as an intermediary between these levels. Meanwhile new technologies continue to arrive that can be used to interrogate the genome of single cells and its related omics datasets. As these two areas, single cell imaging and single cell omics, each advance independently with the development of novel techniques, the opportunity to integrate these data types becomes more and more attractive. This review outlines some of the technologies and methods currently available for generating, processing, and analysing single-cell omics- and imaging data, and how they could be integrated to further our understanding of complex biological phenomena like ageing. We include an emphasis on machine learning algorithms because of their ability to identify complex patterns in large multidimensional data.

Structure and Mutations of SARS-CoV-2 Spike Protein: A Focused Overview

The spike protein (S-protein) of SARS-CoV-2, the protein that enables the virus to infect human cells, is the basis for many vaccines and a hotspot of concerning virus evolution. Here, we discuss the outstanding progress in structural characterization of the S-protein and how these structures facilitate analysis of virus function and evolution. We emphasize the differences in reported structures and that analysis of structure-function relationships is sensitive to the structure used. We show that the average residue solvent exposure in nearly complete structures is a good descriptor of open vs closed conformation states. Because of structural heterogeneity of functionally important surface-exposed residues, we recommend using averages of a group of high-quality protein structures rather than a single structure before reaching conclusions on specific structure-function relationships. To illustrate these points, we analyze some significant chemical tendencies of prominent S-protein mutations in the context of the available structures. In the discussion of new variants, we emphasize the selectivity of binding to ACE2 vs prominent antibodies rather than simply the antibody escape or ACE2 affinity separately. We note that larger chemical changes, in particular increased electrostatic charge or side-chain volume of exposed surface residues, are recurring in mutations of concern, plausibly related to adaptation to the negative surface potential of human ACE2. We also find indications that the fixated mutations of the S-protein in the main variants are less destabilizing than would be expected on average, possibly pointing toward a selection pressure on the S-protein. The richness of available structures for all of these situations provides an enormously valuable basis for future research into these structure-function relationships.

A case for glycerol as an acceptable additive for single-particle cryoEM samples

Buffer-composition and sample-preparation guidelines for cryo-electron microscopy are geared towards maximizing imaging contrast and reducing electron-beam-induced motion. These pursuits often involve the minimization or the complete removal of additives that are commonly used to facilitate proper protein folding and minimize aggregation. Among these admonished additives is glycerol, a widely used osmolyte that aids protein stability. In this work, it is shown that the inclusion of glycerol does not preclude high-resolution structure determination by cryoEM, as demonstrated by an ∼2.3 Å resolution reconstruction of mouse apoferritin (∼500 kDa) and an ∼3.3 Å resolution reconstruction of rabbit muscle aldolase (∼160 kDa) in the presence of 20%(v/v) glycerol. While it was found that generating thin ice that is amenable to high-resolution imaging requires long blot times, the addition of glycerol did not result in increased beam-induced motion or an inability to pick particles. Overall, these findings indicate that glycerol should not be discounted as a cryoEM sample-buffer additive, particularly for large, fragile complexes that are prone to disassembly or aggregation upon its removal.

A cryo-TSEM with temperature cycling capability allows deep sublimation of ice to uncover fine structures in thick cells

The scanning electron microscope (SEM) has been reassembled into a new type of cryo-electron microscope (cryo-TSEM) by installing a new cryo-transfer holder and anti-contamination trap, which allowed simultaneous acquisition of both transmission images (STEM images) and surface images (SEM images) in the frozen state. The ultimate temperatures of the holder and the trap reached − 190 °C and − 210 °C, respectively, by applying a liquid nitrogen slush. The STEM images at 30 kV were comparable to, or superior to, the images acquired with conventional transmission electron microscope (100 kV TEM) in contrast and sharpness. The unroofing method was used to observe membrane cytoskeletons instead of the frozen section and the FIB methods. Deep sublimation of ice surrounding unroofed cells by regulating temperature enabled to emerge intracellular fine structures in thick frozen cells. Hence, fine structures in the vicinity of the cell membrane such as the cytoskeleton, polyribosome chains and endoplasmic reticulum (ER) became visible. The ER was distributed as a wide, flat structure beneath the cell membrane, forming a large spatial network with tubular ER.

A Fast Image Alignment Approach for 2D Classification of Cryo-EM Images Using Spectral Clustering

Three-dimensional (3D) reconstruction in single-particle cryo-electron microscopy (cryo-EM) is a significant technique for recovering the 3D structure of proteins or other biological macromolecules from their two-dimensional (2D) noisy projection images taken from unknown random directions. Class averaging in single-particle cryo-EM is an important procedure for producing high-quality initial 3D structures, where image alignment is a fundamental step. In this paper, an efficient image alignment algorithm using 2D interpolation in the frequency domain of images is proposed to improve the estimation accuracy of alignment parameters of rotation angles and translational shifts between the two projection images, which can obtain subpixel and subangle accuracy. The proposed algorithm firstly uses the Fourier transform of two projection images to calculate a discrete cross-correlation matrix and then performs the 2D interpolation around the maximum value in the cross-correlation matrix. The alignment parameters are directly determined according to the position of the maximum value in the cross-correlation matrix after interpolation. Furthermore, the proposed image alignment algorithm and a spectral clustering algorithm are used to compute class averages for single-particle 3D reconstruction. The proposed image alignment algorithm is firstly tested on a Lena image and two cryo-EM datasets. Results show that the proposed image alignment algorithm can estimate the alignment parameters accurately and efficiently. The proposed method is also used to reconstruct preliminary 3D structures from a simulated cryo-EM dataset and a real cryo-EM dataset and to compare them with RELION. Experimental results show that the proposed method can obtain more high-quality class averages than RELION and can obtain higher reconstruction resolution than RELION even without iteration.

Assembly and recognition of keratins: A structural perspective

Keratins are one of the major components of cytoskeletal network and assemble into fibrous structures named intermediate filaments (IFs), which are important for maintaining the mechanical properties of cells and tissues. Over the past decades, evidence has shown that the functions of keratins go beyond providing mechanical support for cells, they interact with multiple cellular components and are widely involved in the pathways of cell proliferation, differentiation, motility and death. However, the structural details of keratins and IFs are largely missing and many questions remain regarding the mechanisms of keratin assembly and recognition. Here we briefly review the current structural models and assembly of keratins as well as the interactions of keratins with the binding partners, which may provide a structural view for understanding the mechanisms of keratins in the biological activities and the related diseases.

Cryo-EM single-particle structure refinement and map calculation using Servalcat

In 2020, cryo-EM single-particle analysis achieved true atomic resolution thanks to technological developments in hardware and software. The number of high-resolution reconstructions continues to grow, increasing the importance of the accurate determination of atomic coordinates. Here, a new Python package and program called Servalcat is presented that is designed to facilitate atomic model refinement. Servalcat implements a refinement pipeline using the program REFMAC5 from the CCP4 package. After the refinement, Servalcat calculates a weighted Fo - Fc difference map, which is derived from Bayesian statistics. This map helps manual and automatic model building in real space, as is common practice in crystallography. The Fo - Fc map helps in the visualization of weak features including hydrogen densities. Although hydrogen densities are weak, they are stronger than in the electron-density maps produced by X-ray crystallography, and some H atoms are even visible at ∼1.8 Å resolution. Servalcat also facilitates atomic model refinement under symmetry constraints. If point-group symmetry has been applied to the map during reconstruction, the asymmetric unit model is refined with the appropriate symmetry constraints.

Recent advancements in mass spectrometry for higher order structure characterization of protein therapeutics

Molecular characterization of higher order structure (HOS) in protein therapeutics is crucial to the selection of candidate molecules, understanding of structure-function relationships, formulation development, stability assessment, and comparability studies. Recent advances in mass spectrometry (MS), including native MS, hydrogen/deuterium exchange (HDX)-MS, and fast photochemical oxidation of proteins (FPOP) coupled with MS, have provided orthogonal ways to characterize HOS of protein therapeutics. In this review, we present the utility of native MS, HDX-MS and FPOP-MS in protein therapeutics discovery and development, with a focus on epitope mapping, aggregation assessment, and comparability studies. We also discuss future trends in the application of these MS methods to HOS characterization.

Biophysical applications in structural and molecular biology

The main objective of structural biology is to model proteins and other biological macromolecules and link the structural information to function and dynamics. The biological functions of protein molecules and nucleic acids are inherently dependent on their conformational dynamics. Imaging of individual molecules and their dynamic characteristics is an ample source of knowledge that brings new insights about mechanisms of action. The atomic-resolution structural information on most of the biomolecules has been solved by biophysical techniques; either by X-ray diffraction in single crystals or by nuclear magnetic resonance (NMR) spectroscopy in solution. Cryo-electron microscopy (cryo-EM) is emerging as a new tool for analysis of a larger macromolecule that couldn't be solved by X-ray crystallography or NMR. Now a day's low-resolution Cryo-EM is used in combination with either X-ray crystallography or NMR. The present review intends to provide updated information on applications like X-ray crystallography, cryo-EM and NMR which can be used independently and/or together in solving structures of biological macromolecules for our full comprehension of their biological mechanisms.

Practical considerations for using K3 cameras in CDS mode for high-resolution and high-throughput single particle cryo-EM

Detector technology plays a pivotal role in high-resolution and high-throughput cryo-EM structure determination. Compared with the first-generation, single-electron counting direct detection camera (Gatan K2), the latest K3 camera is faster, larger, and now offers a correlated-double sampling mode (CDS). Importantly this results in a higher DQE and improved throughput compared to its predecessor. In this study, we focused on optimizing camera data collection parameters for daily use within a cryo-EM facility and explored the balance between throughput and resolution. In total, eight data sets of murine heavy-chain apoferritin were collected at different dose rates and magnifications, using 9-hole image shift data collection strategies. The performance of the camera was characterized by the quality of the resultant 3D reconstructions. Our results demonstrated that the Gatan K3 operating in CDS mode outperformed standard (nonCDS) mode in terms of reconstruction resolution in all tested conditions with 8 electrons per pixel per second being the optimal dose rate. At low magnification (64kx) we were able to achieve reconstruction resolutions of 149% of the physical Nyquist limit (1.8 Å with a 1.346 Å physical pixel size). Low magnification allows more particles to be collected per image, aiding analysis of heterogeneous samples requiring large data sets. At moderate magnification (105kx, 0.834 Å physical pixel size) we achieved a resolution of 1.65 Å within 8-h of data collection, a condition optimal for achieving high-resolution on well behaved samples. Our results also show that for an optimal sample like apoferritin, one can achieve better than 2.5 Å resolution with 5 min of data collection. Together, our studies validate the most efficient ways of imaging protein complexes using the K3 direct detector and will greatly benefit the cryo-EM community.

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

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

Single-Particle Cryo-EM of Membrane Proteins

In the recent years, the protein databank has been fueled by the exponential growth of high-resolution electron cryo-microscopy (cryo-EM) structures. This trend will be further accelerated through the continuous software and method developments and the increasing availability of imaging centers, which will open cryo-EM to a wide array of researchers with their diverse scientific goals and questions. Especially for structural biology of membrane proteins, cryo-EM offers significant advantages as it can overcome multiple limitations of classical methods. Most importantly, in cryo-EM, the sample is prepared as a vitrified suspension, which abolishes the need for crystallization, reduces the required sample amount and allows usage of a wide arsenal of hydrophobic environments. Despite recent improvements, high-resolution cryo-EM still poses some significant challenges, and standardized procedures, especially for the characterization of membrane proteins, are missing. While there can be no ultimate recipe toward a high-resolution cryo-EM structure for every membrane protein, certain factors seem to be universally relevant. Here, we share the protocols that have been successfully used in our laboratory. We hope that this may be a useful resource to other researchers in the field and may increase their chances of success.

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.

Amphiphilic phospholipid-iodinated polymer conjugates for bioimaging

Amphiphilic phospholipid-iodinated polymer conjugates were designed and synthesized as new macromolecular probes for a highly radiopaque and biocompatible imaging technology. Bioconjugation of PEG 2000-phospholipids and iodinated polyesters by click chemistry created amphiphilic moieties with hydrophobic polyesters and hydrophilic PEG units, which allowed their self-assemblies into vesicles or spiked vesicles. More importantly, the conjugates exhibited high radiopacity and biocompatibility in in vitro X-ray and cell viability measurements. This new type of bioimaging contrast agent with a Mn value of 11 289 g mol-1 was found to have a significant X-ray signal at 3.13 mg mL-1 of iodine equivalent than baseline and no cytotoxicity after 48 hours incubation of with HEK and 3T3 cells at 20 μM (20 picomoles) concentration of conjugates per well. The potential of adopting the described macromolecular probes for bioimaging was demonstrated, which could further promote the development of a field-friendly and highly sensitive bioimaging contrast agent for point-of-care diagnostic applications.

Heteromeric TRP Channels in Lung Inflammation

Activation of Transient Receptor Potential (TRP) channels can disrupt endothelial barrier function, as their mediated Ca²⁺ influx activates the CaM (calmodulin)/MLCK (myosin light chain kinase)-signaling pathway, and thereby rearranges the cytoskeleton, increases endothelial permeability and thus can facilitate activation of inflammatory cells and formation of pulmonary edema. Interestingly, TRP channel subunits can build heterotetramers, whereas heteromeric TRPC1/4, TRPC3/6 and TRPV1/4 are expressed in the lung endothelium and could be targeted as a protective strategy to reduce endothelial permeability in pulmonary inflammation. An update on TRP heteromers and their role in lung inflammation will be provided with this review.

Sub-3 Å Cryo-EM Structures of Necrosis Virus Particles via the Use of Multipurpose TEM with Electron Counting Camera

During this global pandemic, cryo-EM has made a great impact on the structure determination of COVID-19 proteins. However, nearly all high-resolution results are based on data acquired on state-of-the-art microscopes where their availability is restricted to a number of centers across the globe with the studies on infectious viruses being further regulated or forbidden. One potential remedy is to employ multipurpose microscopes. Here, we investigated the capability of 200 kV multipurpose microscopes equipped with a direct electron camera in determining the structures of infectious particles. We used 30 nm particles of the grouper nerve necrosis virus as a test sample and obtained the cryo-EM structure with a resolution as high as ∼2.7 Å from a setting that used electron counting. For comparison, we tested a high-end cryo-EM (Talos Arctica) using a similar virus (Macrobrachium rosenbergii nodavirus) to obtain virtually the same resolution. Those results revealed that the resolution is ultimately limited by the depth of field. Our work updates the density maps of these viruses at the sub-3Å level to allow for building accurate atomic models from de novo to provide structural insights into the assembly of the capsids. Importantly, this study demonstrated that multipurpose TEMs are capable of the high-resolution cryo-EM structure determination of infectious particles and is thus germane to the research on pandemics.

Efficient Flexible Fitting Refinement with Automatic Error Fixing for De Novo Structure Modeling from Cryo-EM Density Maps

Structural modeling of proteins from cryo-electron microscopy (cryo-EM) density maps is one of the challenging issues in structural biology. De novo modeling combined with flexible fitting refinement (FFR) has been widely used to build a structure of new proteins. In de novo prediction, artificial conformations containing local structural errors such as chirality errors, cis peptide bonds, and ring penetrations are frequently generated and cannot be easily removed in the subsequent FFR. Moreover, refinement can be significantly suppressed due to the low mobility of atoms inside the protein. To overcome these problems, we propose an efficient scheme for FFR, in which the local structural errors are fixed first, followed by FFR using an iterative simulated annealing (SA) molecular dynamics protocol with the united atom (UA) model in an implicit solvent model; we call this scheme "SAUA-FFR". The best model is selected from multiple flexible fitting runs with various biasing force constants to reduce overfitting. We apply our scheme to the decoys obtained from MAINMAST and demonstrate an improvement of the best model of eight selected proteins in terms of the root-mean-square deviation, MolProbity score, and RWplus score compared to the original scheme of MAINMAST. Fixing the local structural errors can enhance the formation of secondary structures, and the UA model enables progressive refinement compared to the all-atom model owing to its high mobility in the implicit solvent. The SAUA-FFR scheme realizes efficient and accurate protein structure modeling from medium-resolution maps with less overfitting.

Gold nanoparticles and tilt pairs to assess protein flexibility by cryo-electron microscopy

A computational method was developed to recover the three-dimensional coordinates of gold nanoparticles specifically attached to a protein complex from tilt-pair images collected by electron microscopy. The program was tested on a simulated dataset and applied to a real dataset comprising tilt-pair images recorded by cryo electron microscopy of RNA polymerase II in a complex with four gold-labeled single-chain antibody fragments. The positions of the gold nanoparticles were determined, and comparison of the coordinates among the tetrameric particles revealed the range of motion within the protein complexes.

Improving particle quality in cryo-EM analysis using a PEGylation method

Cryo-electron microscopy (cryo-EM) is widely used for structural biology studies and has been developed extensively in recent years. However, its sample vitrification process is a major limitation because it causes severe particle aggregation and/or denaturation. This effect is thought to occur because particles tend to stick to the "deadly" air-water interface during vitrification. Here, we report a method for PEGylation of proteins that can efficiently protect particles against such problems during vitrification. This method alleviates the laborious process of fine-tuning the vitrification conditions, allowing for analysis of samples that would otherwise be discarded.

Cryo-EM Performance Testing of Hardware and Data Acquisition Strategies

The increasing popularity and adoption rate of cryo-electron microscopy is evidenced by a growing number of new microscope installations around the world. The quality and reliability of the instruments improved dramatically in recent years, but site-specific issues or unnoticed problems during installation could undermine productivity. Newcomers to the field may also have limited experience and/or low confidence in the capabilities of the equipment or their own skills. Therefore, it is recommended to perform an initial test of the complete cryo-EM workflow with an 'easy' test sample, such as apoferritin, before starting work with real and challenging samples. Analogous test experiments are also recommended for quantification of new data acquisition approaches or imaging hardware. Here, we present the results from our initial tests of a recently installed Krios G4 electron microscope equipped with two latest generation direct electron detector cameras-Gatan K3 and Falcon 4. Three beam-image shift-based data acquisition strategies were also tested. We detail the methodology and discuss the critical parameters and steps for performance testing. The two cameras performed equally, and the single and multi-shot per-hole acquisition schemes produced comparable results. We also evaluated the effects of environmental factors and optical flaws on data quality. Our results reaffirmed the exceptional performance of the software aberration correction in Relion in dealing with severe coma aberration. We hope that this work will help cryo-EM teams in their testing and troubleshooting of hardware and data collection approaches.

Below 3 Å structure of apoferritin using a multipurpose TEM with a side entry cryoholder

Recently, the structural analysis of protein complexes by cryo-electron microscopy (cryo-EM) single particle analysis (SPA) has had great impact as a biophysical method. Many results of cryo-EM SPA are based on data acquired on state-of-the-art cryo-electron microscopes customized for SPA. These are currently only available in limited locations around the world, where securing machine time is highly competitive. One potential solution for this time-competitive situation is to reuse existing multi-purpose equipment, although this comes with performance limitations. Here, a multi-purpose TEM with a side entry cryo-holder was used to evaluate the potential of high-resolution SPA, resulting in a 3 Å resolution map of apoferritin with local resolution extending to 2.6 Å. This map clearly showed two positions of an aromatic side chain. Further, examination of optimal imaging conditions depending on two different multi-purpose electron microscope and camera combinations was carried out, demonstrating that higher magnifications are not always necessary or desirable. Since automation is effectively a requirement for large-scale data collection, and augmenting the multi-purpose equipment is possible, we expanded testing by acquiring data with SerialEM using a β-galactosidase test sample. This study demonstrates the possibilities of more widely available and established electron microscopes, and their applications for cryo-EM SPA.

Using RELION software within the Scipion framework

Scipion is a modular image-processing framework that integrates several software packages under a unified interface while taking care of file formats and conversions. Here, new developments and capabilities of the Scipion plugin for the widely used RELION software package are presented and illustrated with an image-processing pipeline for published data. The user interfaces of Scipion and RELION are compared and the key differences are highlighted, allowing this manuscript to be used as a guide for both new and experienced users of this software. Different on-the-fly image-processing options are also discussed, demonstrating the flexibility of the Scipion framework.

A perspective on the PDB's impact on the field of glycobiology

Structures deposited in the Protein Data Bank (PDB) facilitate our understanding of many biological processes including those that fall under the general category of glycobiology. However, structure-based studies of how glycans affect protein structure, how they are synthesized, and how they regulate other biological processes remain challenging. Despite the abundant presence of glycans on proteins and the dense layers of glycans that surround most of our cells, structures containing glycans are underrepresented in the PDB. There are sound reasons for this, including difficulties in producing proteins with well-defined glycosylation and the tendency of mobile and heterogeneous glycans to inhibit crystallization. Nevertheless, the structures we do find in the PDB, even some of the earliest deposited structures, have had an impact on our understanding of function. I highlight a few examples in this review and point to some promises for the future. Promises include new structures from methodologies, such as cryo-EM, that are less affected by the presence of glycans and experiment-aided computational methods that build on existing structures to provide insight into the many ways glycans affect biological function.

Guidelines for Regulated Cell Death Assays: A Systematic Summary, A Categorical Comparison, A Prospective

Over the past few years, the field of regulated cell death continues to expand and novel mechanisms that orchestrate multiple regulated cell death pathways are being unveiled. Meanwhile, researchers are focused on targeting these regulated pathways which are closely associated with various diseases for diagnosis, treatment, and prognosis. However, the complexity of the mechanisms and the difficulties of distinguishing among various regulated types of cell death make it harder to carry out the work and delay its progression. Here, we provide a systematic guideline for the fundamental detection and distinction of the major regulated cell death pathways following morphological, biochemical, and functional perspectives. Moreover, a comprehensive evaluation of different assay methods is critically reviewed, helping researchers to make a reliable selection from among the cell death assays. Also, we highlight the recent events that have demonstrated some novel regulated cell death processes, including newly reported biomarkers (e.g., non-coding RNA, exosomes, and proteins) and detection techniques.