cryo-EM Images Research Articles

Review of Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs

Review of Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs

Fast Cryo-EM Image Alignment Algorithm Using Power Spectrum Features

Cryo-electron microscopy (cryo-EM) single-particle image analysis is a powerful technique to resolve structures of biomacromolecules, while the challenge is that the cryo-EM image is of a low signal-to-noise ratio. For both two-dimensional image analysis and three-dimensional density map analysis, image alignment is an important step to improve the precision of the image distance calculation. In this paper, we introduce a new algorithm for performing two-dimensional pairwise alignment for cryo-EM particle images, which is based on the Fourier transform and power spectrum analysis. Compared to the existing heuristic iterative alignment methods, our method utilizes the signal distribution and signal feature on images' power spectrum to directly compute the alignment parameters. It does not require iterative computations and is robust against the cryo-EM image noise. Both theoretical analysis and experimental results suggest that our power-spectrum-feature-based alignment method is highly computational-efficient and is capable of offering effective alignment results. This new alignment algorithm is publicly available at: www.csbio.sjtu.edu.cn/bioinf/EMAF/for academic use.

Cryo-EM density maps adjustment for subtraction, consensus and sharpening

Electron cryomicroscopy (cryo-EM) has emerged as a powerful structural biology instrument to solve near-atomic three-dimensional structures. Despite the fast growth in the number of density maps generated from cryo-EM data, comparison tools among these reconstructions are still lacking. Current proposals to compare cryo-EM data derived volumes perform map subtraction based on adjustment of each volume grey level to the same scale. We present here a more sophisticated way of adjusting the volumes before comparing, which implies adjustment of grey level scale and spectrum energy, but keeping phases intact inside a mask and imposing the results to be strictly positive. The adjustment that we propose leaves the volumes in the same numeric frame, allowing to perform operations among the adjusted volumes in a more reliable way. This adjustment can be a preliminary step for several applications such as comparison through subtraction, map sharpening, or combination of volumes through a consensus that selects the best resolved parts of each input map. Our development might also be used as a sharpening method using an atomic model as a reference. We illustrate the applicability of this algorithm with the reconstructions derived of several experimental examples. This algorithm is implemented in Xmipp software package and its applications are user-friendly accessible through the cryo-EM image processing framework Scipion.

Remodeling and activation mechanisms of outer arm dyneins revealed by cryo-EM.

Cilia are thin microtubule-based protrusions of eukaryotic cells. The swimming of ciliated protists and sperm cells is propelled by the beating of cilia. Cilia propagate the flow of mucus in the trachea and protect the human body from viral infections. The main force generators of ciliary beating are the outer dynein arms (ODAs) which attach to the doublet microtubules. The bending of cilia is driven by the ODAs' conformational changes caused by ATP hydrolysis. Here, we report the native ODA complex structure attaching to the doublet microtubule by cryo-electron microscopy. The structure reveals how the ODA complex is attached to the doublet microtubule via the docking complex in its native state. Combined with coarse-grained molecular dynamic simulations, we present a model of how the attachment of the ODA to the doublet microtubule induces remodeling and activation of the ODA complex.

Statistical estimation of spatially resolved heterogeneity from cryo-EM images

Statistical estimation of spatially resolved heterogeneity from cryo-EM images

RAMI – Rapid Alignment with Moment of Inertia for Cryo-EM Image Processing

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Continuous heterogeneity analysis of CryoEM images through Zernike polynomials and spherical harmonics

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What is a single cryo-EM image worth? A survey of high-resolution cryo-EM model system datasets

What is a single cryo-EM image worth? A survey of high-resolution cryo-EM model system datasets

A Bayesian approach to extracting free-energy profiles from cryo-electron microscopy experiments

Cryo-electron microscopy (cryo-EM) extracts single-particle density projections of individual biomolecules. Although cryo-EM is widely used for 3D reconstruction, due to its single-particle nature it has the potential to provide information about a biomolecule’s conformational variability and underlying free-energy landscape. However, treating cryo-EM as a single-molecule technique is challenging because of the low signal-to-noise ratio (SNR) in individual particles. In this work, we propose the cryo-BIFE method (cryo-EM Bayesian Inference of Free-Energy profiles), which uses a path collective variable to extract free-energy profiles and their uncertainties from cryo-EM images. We test the framework on several synthetic systems where the imaging parameters and conditions were controlled. We found that for realistic cryo-EM environments and relevant biomolecular systems, it is possible to recover the underlying free energy, with the pose accuracy and SNR as crucial determinants. We then use the method to study the conformational transitions of a calcium-activated channel with real cryo-EM particles. Interestingly, we recover not only the most probable conformation (used to generate a high-resolution reconstruction of the calcium-bound state) but also a metastable state that corresponds to the calcium-unbound conformation. As expected for turnover transitions within the same sample, the activation barriers are on the order of k_BT. We expect our tool for extracting free-energy profiles from cryo-EM images to enable more complete characterization of the thermodynamic ensemble of biomolecules.

Full-Length Computational Model of the SARS-CoV-2 Spike Protein and Its Implications for a Viral Membrane Fusion Mechanism.

The SARS-CoV-2 virus has now become one of the greatest causes of infectious death and morbidity since the 1918 flu pandemic. Substantial and unprecedented progress has been made in the elucidation of the viral infection process in a short time; however, our understanding of the structure–function dynamics of the spike protein during the membrane fusion process and viral uptake remains incomplete. Employing computational approaches, we use full-length structural models of the SARS-CoV-2 spike protein integrating Cryo-EM images and biophysical properties, which fill the gaps in our understanding. We propose a membrane fusion model incorporating structural transitions associated with the proteolytic processing of the spike protein, which initiates and regulates a series of events to facilitate membrane fusion and viral genome uptake. The membrane fusion mechanism highlights the notable role of the S1 subunit and eventual mature spike protein uptake through the host membrane. Our comprehensive view accounts for distinct neutralizing antibody binding effects targeting the spike protein and the enhanced infectivity of the SARS-CoV-2 variant.

Biochemical Society 2022 Award winners

Biochemical Society 2022 Award winners

On the asymptotic normality and efficiency of Kronecker envelope principal component analysis

Dimension reduction methods for matrix or tensor data have been an active research field in recent years. Li et al. (2010) introduced the notion of the Kronecker envelope and proposed dimension folding estimators for supervised dimension reduction. In a data analysis of cryogenic electron microscopy (cryo-EM) images (Chen et al., 2014), Kronecker envelope principal component analysis (PCA) was used to reduce the dimension of cryo-EM images. Kronecker envelope PCA is a two-step procedure, which consists of projecting data onto a multilinear envelope subspace as the first step, followed by ordinary PCA on the projected core tensor. The multilinear envelope subspace preserves the natural Kronecker product structure of observations when searching for the leading principal subspace. The main advantage of preserving the Kronecker product structure is the parsimonious usage of parameters in specifying the leading principal subspace, which mitigates the adverse influence of high-dimensionality. The method of PCA will convert possibly correlated variables to uncorrelated ones and further reduce the dimension of the projected core tensor. In this article we derive the asymptotic normality of Kronecker envelope PCA and compare it with ordinary PCA. Utilizing majorization theory, we show that Kronecker envelope PCA is asymptotically more efficient than ordinary PCA in the sense that the asymptotic total stochastic variation of Kronecker envelope PCA is smaller than that of ordinary PCA. A motivating real data example of cryo-EM image clustering and simulation studies are presented to show the merits of Kronecker envelope PCA.

Automated picking of amyloid fibrils from cryo-EM images for helical reconstruction with RELION

Cryogenic electron microscopy (cryo-EM) is an important tool for determining the molecular structure of proteins and protein assemblies, including helical assemblies such as amyloid fibrils. In reconstruction of amyloid fibril structures from cryo-EM images, an important early step is the selection of fibril locations. This fibril picking step is typically done by hand, a tedious process when thousands of images need to be analyzed. Here we present a computer program called FibrilFinder that identifies the locations and directions of fibril segments in cryo-EM images, by using the properties that the fibrils should be linear objects and have widths within a specified range. The program outputs the fibril locations in text files compatible with the RELION density reconstruction program. After RELION is used to extract the particle image boxes contained in the fibril segments identified by FibrilFinder, a second program called FibrilFixer removes boxes that contain more than one fibril, for instance because two fibrils cross each other. As concrete and realistic examples, we describe the application of the two programs to cryo-EM images of two different amyloid fibrils, namely 40-residue amyloid-β fibrils derived from human brain tissue by seeded growth and fibrils formed by the C-terminal half of the low-complexity domain of the RNA-binding protein FUS. Both examples of amyloid fibrils can be picked from cryo-EM images using the same set of FibrilFinder and FibrilFixer parameters, showing that this software does not require re-optimization for each sample. A set of 1337 cryo-EM images was analyzed in 17 min with one multi-core computer. The new fibril picking software should enable the rapid analysis and comparison of more helical structures using cryo-EM, and perhaps serve as part of the greater automation of the entire structure determination process.

Split conformation of Chaetomium thermophilum Hsp104 disaggregase

Hsp104 and its bacterial homolog ClpB form hexameric ring structures and mediate protein disaggregation. The disaggregated polypeptide is thought to thread through the central channel of the ring. However, the dynamic behavior of Hsp104 during disaggregation remains unclear. Here, we reported the stochastic conformational dynamics and a split conformation of Hsp104 disaggregase from Chaetomium thermophilum (CtHsp104) in the presence of ADP by X-ray crystallography, cryo-electron microscopy (EM), and high-speed atomic force microscopy (AFM). ADP-bound CtHsp104 assembles into a 65 left-handed spiral filament in the crystal structure at a resolution of 2.7Å. The unit of the filament is a hexamer of the split spiral structure. In the cryo-EM images, staggered and split hexameric rings were observed. Further, high-speed AFM observations showed that a substrate addition enhanced the conformational change and increased the split structure's frequency. Our data suggest that split conformation is an off-pathway state of CtHsp104 during disaggregation.

Clustering polymorphs of tau and IAPP fibrils with the CHEP algorithm

Recent steps towards automation have improved the quality and efficiency of the entire cryo-electron microscopy workflow, from sample preparation to image processing. Most of the image processing steps are now quite automated, but there are still a few steps which need the specific intervention of researchers. One such step is the identification and separation of helical protein polymorphs at early stages of image processing. Here, we tested and evaluated our recent clustering approach on three datasets containing amyloid fibrils, demonstrating that the proposed unsupervised clustering method automatically and effectively identifies the polymorphs from cryo-EM images. As an automated polymorph separation method, it has the potential to complement automated helical picking, which typically cannot easily distinguish between polymorphs with subtle differences in morphology, and is therefore a useful tool for the image processing and structure determination of helical proteins.

A New Standard for Membrane Structure? Investigating Factors that Influence Measured Bilayer Thickness in Cryo-EM Images

Cryogenic electron microscopy (cryo-EM) is a promising tool for the analysis of lipid bilayer structure. We recently showed that cryo-EM can be used to measure the bilayer thickness of lipid vesicles and biological membranes with sub-angstrom precision (Heberle et al. 2020 PNAS 117:19943). Despite the great potential of cryo-EM for bilayer structural studies, factors that influence the primary data have not been systematically evaluated. Here, we investigate the influence of energy filtering, contrast transfer function corrections, and instrument defocus length on the primary image data. We report on how these parameters influence such measurements as distributions of membrane thickness, average radial intensity profiles across the bilayer, and spatial autocorrelation of the bilayer thickness. Experimental measurements were correlated with images calculated from two-dimensional projections of atomistic molecular simulations of lipid bilayers, convolved with a contrast transfer function to mimic primary cyro-EM data. This approach yields insights into the molecular origins of measurements quantified from images. We also explored the influence of membrane curvature on thickness using DOPC vesicles of varying diameter prepared via sonication or extrusion through pore sizes ranging from 30-200 nm in diameter. The smallest vesicles exhibited bilayer thinning consistent with curvature stress. The practical implications of instrument settings on the analysis of single and multicomponent lipid membranes and how membrane curvature differs depending on observed size are discussed. These efforts demonstrate how data collection can be systematically optimized to maximize the potential of cryo-EM for resolving variation in membrane thickness within biological membranes.

Effects of cryo-EM Freezing on Structural Ensembles

The recent revolution in cryo-electron microscopy (cryo-EM) allows the determination of structures of macromolecular complexes at atomic resolution. Cryo-EM also provides information on structural heterogeneity and ensembles of macromolecules. To obtain cryo-EM images of macromolecules, the samples are first rapidly cooled down to liquid nitrogen temperatures. The rapid cooling preserves some information of the room temperature ensemble. However, to what extent the structural ensemble is perturbed by the cooling is currently unknown.

CDAE: A Cascade of Denoising Autoencoders for Noise Reduction in the Clustering of Single-Particle Cryo-EM Images.

As an emerging technology, cryo-electron microscopy (cryo-EM) has attracted more and more research interests from both structural biology and computer science, because many challenging computational tasks are involved in the processing of cryo-EM images. An important image processing step is to cluster the 2D cryo-EM images according to their projection angles, then the cluster mean images are used for the subsequent 3D reconstruction. However, cryo-EM images are quite noisy and denoising them is not easy, because the noise is a complicated mixture from samples and hardware. In this study, we design an effective cryo-EM image denoising model, CDAE, i.e., a cascade of denoising autoencoders. The new model comprises stacked blocks of deep neural networks to reduce noise in a progressive manner. Each block contains a convolutional autoencoder, pre-trained by simulated data of different SNRs and fine-tuned by target data set. We assess this new model on three simulated test sets and a real data set. CDAE achieves very competitive PSNR (peak signal-to-noise ratio) in the comparison of the state-of-the-art image denoising methods. Moreover, the denoised images have significantly enhanced clustering results compared to original image features or high-level abstraction features obtained by other deep neural networks. Both quantitative and visualized results demonstrate the good performance of CDAE for the noise reduction in clustering single-particle cryo-EM images.

Molecular structure of a prevalent amyloid-β fibril polymorph from Alzheimer's disease brain tissue

Amyloid-β (Aβ) fibrils exhibit self-propagating, molecular-level polymorphisms that may contribute to variations in clinical and pathological characteristics of Alzheimer's disease (AD). We report the molecular structure of a specific fibril polymorph, formed by 40-residue Aβ peptides (Aβ40), that is derived from cortical tissue of an AD patient by seeded fibril growth. The structure is determined from cryogenic electron microscopy (cryoEM) images, supplemented by mass-per-length (MPL) measurements and solid-state NMR (ssNMR) data. Previous ssNMR studies with multiple AD patients had identified this polymorph as the most prevalent brain-derived Aβ40 fibril polymorph from typical AD patients. The structure, which has 2.8-Å resolution according to standard criteria, differs qualitatively from all previously described Aβ fibril structures, both in its molecular conformations and its organization of cross-β subunits. Unique features include twofold screw symmetry about the fibril growth axis, despite an MPL value that indicates three Aβ40 molecules per 4.8-Å β-sheet spacing, a four-layered architecture, and fully extended conformations for molecules in the central two cross-β layers. The cryoEM density, ssNMR data, and MPL data are consistent with β-hairpin conformations for molecules in the outer cross-β layers. Knowledge of this brain-derived fibril structure may contribute to the development of structure-specific amyloid imaging agents and aggregation inhibitors with greater diagnostic and therapeutic utility.

Where in the cell is my protein?

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