Estimation of variance in single-particle reconstruction using the bootstrap technique

Visualizing Conformational Space of Functional Biomolecular Complexes by Deep Manifold Learning

The cellular functions are executed by biological macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving the conformational continuum of important biomolecular complexes at the atomic level is essential to understanding their functional mechanisms and guiding structure-based drug discovery. Here, we introduce a deep manifold learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy (cryo-EM) reconstructions that approximately visualize the conformational space of biomolecular complexes of interest. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of pseudo-energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. In blind assessments using simulated heterogeneous datasets, AlphaCryo4D achieved 3D classification accuracy three times those of alternative methods and reconstructed continuous conformational changes of a 130-kDa protein at sub-3 Å resolution. By applying this approach to analyze several experimental datasets of the proteasome, ribosome and spliceosome, we demonstrate its potential generality in exploring hidden conformational space or transient states of macromolecular complexes that remain hitherto invisible. Integration of this approach with time-resolved cryo-EM further allows visualization of conformational continuum in a nonequilibrium regime at the atomic level, thus potentially enabling therapeutic discovery against highly dynamic biomolecular targets.

Recovery of Conformational Continuum From Single-Particle Cryo-EM Images: Optimization of ManifoldEM Informed by Ground Truth

This work is based on the manifold-embedding approach to study biological molecules exhibiting continuous conformational changes. Previous work established a method-now termed ManifoldEM-capable of reconstructing 3D movies and accompanying free-energy landscapes from single-particle cryo-EM images of macromolecules exercising multiple conformational degrees of freedom. While ManifoldEM has proven its viability in several experimental studies, critical limitations and uncertainties have been found throughout its extended development and use. Guided by insights from studies with cryo-EM ground-truth data, simulated from atomic structures undergoing conformational changes, we have built a novel framework, ESPER, able to retrieve the free-energy landscape and respective 3D Coulomb potential maps for all states simulated. As shown by a direct comparison of ground truth vs. recovered maps, and analysis of experimental data from the 80S ribosome and ryanodine receptor, ESPER offers substantial improvements relative to the previous work.

Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review

Recently, single-particle cryo-electron microscopy (cryo-EM) has become an indispensable method for determining macromolecular structures at high resolution to deeply explore the relevant molecular mechanism. Its recent breakthrough is mainly because of the rapid advances in hardware and image processing algorithms, especially machine learning. As an essential support of single-particle cryo-EM, machine learning has powered many aspects of structure determination and greatly promoted its development. In this article, we provide a systematic review of the applications of machine learning in this field. Our review begins with a brief introduction of single-particle cryo-EM, followed by the specific tasks and challenges of its image processing. Then, focusing on the workflow of structure determination, we describe relevant machine learning algorithms and applications at different steps, including particle picking, 2-D clustering, 3-D reconstruction, and other steps. As different tasks exhibit distinct characteristics, we introduce the evaluation metrics for each task and summarize their dynamics of technology development. Finally, we discuss the open issues and potential trends in this promising field.

Principal component analysis is limited to low-resolution analysis in cryoEM

Principal component analysis (PCA) has been widely proposed to analyze flexibility and heterogeneity in cryo-electron microscopy (cryoEM). In this paper, it is argued that (i) PCA is an excellent technique to describe continuous flexibility at low resolution (but not so much at high resolution) and (ii) PCA components should be analyzed in a concerted manner (and not independently).

Computational Methods for Single-Particle Electron Cryomicroscopy

Single-particle electron cryomicroscopy (cryo-EM) is an increasingly popular technique for elucidating the three-dimensional structure of proteins and other biologically significant complexes at near-atomic resolution. It is an imaging method that does not require crystallization and can capture molecules in their native states. In single-particle cryo-EM, the three-dimensional molecular structure needs to be determined from many noisy two-dimensional tomographic projections of individual molecules, whose orientations and positions are unknown. The high level of noise and the unknown pose parameters are two key elements that make reconstruction a challenging computational problem. Even more challenging is the inference of structural variability and flexible motions when the individual molecules being imaged are in different conformational states. This review discusses computational methods for structure determination by single-particle cryo-EM and their guiding principles from statistical inference, machine learning, and signal processing that also play a significant role in many other data science applications.

Confidence maps: statistical inference of cryo-EM maps

Confidence maps provide complementary information for interpreting cryo-EM densities as they indicate statistical significance with respect to background noise. They can be thresholded by specifying the expected false-discovery rate (FDR), and the displayed volume shows the parts of the map that have the corresponding level of significance. Here, the basic statistical concepts of confidence maps are reviewed and practical guidance is provided for their interpretation and usage inside the CCP-EM suite. Limitations of the approach are discussed and extensions towards other error criteria such as the family-wise error rate are presented. The observed map features can be rendered at a common isosurface threshold, which is particularly beneficial for the interpretation of weak and noisy densities. In the current article, a practical guide is provided to the recommended usage of confidence maps.

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.

Need for Cross-Validation of Single Particle Cryo-EM

Cross-validation is used to determine the validity of a model on unseen data by assessing if the model is overfitted to noise. It is widely used in many fields, from artificial intelligence to structural biology in X-ray crystallography and nuclear magnetic resonance. Although there are concerns of map overfitting in cryo-electron microscopy (cryo-EM), cross-validation is rarely used. The problem is that establishing a performance metric of the maps over unseen data (given by 2D-projection images) is difficult due to the low signal-to-noise ratios in the individual particles. Here, I present recent advances for cryo-EM map reconstruction. I highlight that the gold-standard procedure can fail to detect map overfitting in certain cases, showing the necessity of assessing the map quality on unbiased data. Finally, I describe the challenges and advantages of developing a robust cross-validation methodology for cryo-EM.

Cryo-EM reconstruction of continuous heterogeneity by Laplacian spectral volumes

Single-particle electron cryomicroscopy is an essential tool for high-resolution 3D reconstruction of proteins and other biological macromolecules. An important challenge in cryo-EM is the reconstruction of non-rigid molecules with parts that move and deform. Traditional reconstruction methods fail in these cases, resulting in smeared reconstructions of the moving parts. This poses a major obstacle for structural biologists, who need high-resolution reconstructions of entire macromolecules, moving parts included. To address this challenge, we present a new method for the reconstruction of macromolecules exhibiting continuous heterogeneity. The proposed method uses projection images from multiple viewing directions to construct a graph Laplacian through which the manifold of three-dimensional conformations is analyzed. The 3D molecular structures are then expanded in a basis of Laplacian eigenvectors, using a novel generalized tomographic reconstruction algorithm to compute the expansion coefficients. These coefficients, which we name spectral volumes, provide a high-resolution visualization of the molecular dynamics. We provide a theoretical analysis and evaluate the method empirically on several simulated data sets.

The structure and oxidation of the eye lens chaperone αA-crystallin

The small heat shock protein αA-crystallin is a molecular chaperone important for the optical properties of the vertebrate eye lens. It forms heterogeneous oligomeric ensembles. We determined the structures of human αA-crystallin oligomers by combining cryo-electron microscopy, cross-linking/mass spectrometry, NMR spectroscopy and molecular modeling. The different oligomers can be interconverted by the addition or subtraction of tetramers, leading to mainly 12-, 16- and 20-meric assemblies in which interactions between N-terminal regions are important. Cross-dimer domain-swapping of the C-terminal region is a determinant of αA-crystallin heterogeneity. Human αA-crystallin contains two cysteines, which can form an intramolecular disulfide in vivo. Oxidation in vitro requires conformational changes and oligomer dissociation. The oxidized oligomers, which are larger than reduced αA-crystallin and destabilized against unfolding, are active chaperones and can transfer the disulfide to destabilized substrate proteins. The insight into the structure and function of αA-crystallin provides a basis for understanding its role in the eye lens.

Reconstruction of Stochastic 3D Signals With Symmetric Statistics From 2D Projection Images Motivated by Cryo-Electron Microscopy

Cryo-electron microscopy provides 2D projection images of the 3D electron scattering intensity of many instances of the particle under study (e.g., a virus). Both symmetry (rotational point groups) and heterogeneity are important aspects of biological particles and both aspects can be combined by describing the electron scattering intensity of the particle as a stochastic process with a symmetric probability law and, therefore, symmetric moments. A maximum likelihood estimator implemented by an expectation-maximization algorithm is described, which estimates the unknown statistics of the electron scattering intensity stochastic process from the images of instances of the particle. The algorithm is demonstrated on the bacteriophage HK97 and the virus [Formula: see text]. The results are contrasted with the existing algorithms, which assume that each instance of the particle has the symmetry rather than the less restrictive assumption that the probability law has the symmetry.

Thresholding of cryo-EM density maps by false discovery rate control

Cryo-EM now commonly generates close-to-atomic resolution as well as intermediate resolution maps from macromolecules observed in isolation and in situ. Interpreting these maps remains a challenging task owing to poor signal in the highest resolution shells and the necessity to select a threshold for density analysis. In order to facilitate this process, a statistical framework for the generation of confidence maps by multiple hypothesis testing and false discovery rate (FDR) control has been developed. In this way, three-dimensional confidence maps contain signal separated from background noise in the form of local detection rates of EM density values. It is demonstrated that confidence maps and FDR-based thresholding can be used for the interpretation of near-atomic resolution single-particle structures as well as lower resolution maps determined by subtomogram averaging. Confidence maps represent a conservative way of interpreting molecular structures owing to minimized noise. At the same time they provide a detection error with respect to background noise, which is associated with the density and is particularly beneficial for the interpretation of weaker cryo-EM densities in cases of conformational flexibility and lower occupancy of bound molecules and ions in the structure.

Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy

Single-particle analysis by electron microscopy is a well established technique for analyzing the three-dimensional structures of biological macromolecules. Besides its ability to produce high-resolution structures, it also provides insights into the dynamic behavior of the structures by elucidating their conformational variability. Here, the different image-processing methods currently available to study continuous conformational changes are reviewed.

Structural Variability from Noisy Tomographic Projections

In cryo-electron microscopy, the three-dimensional (3D) electric potentials of an ensemble of molecules are projected along arbitrary viewing directions to yield noisy two-dimensional images. The volume maps representing these potentials typically exhibit a great deal of structural variability, which is described by their 3D covariance matrix. Typically, this covariance matrix is approximately low rank and can be used to cluster the volumes or estimate the intrinsic geometry of the conformation space. We formulate the estimation of this covariance matrix as a linear inverse problem, yielding a consistent least-squares estimator. For n images of size N-by-N pixels, we propose an algorithm for calculating this covariance estimator with computational complexity O ( n N 4 + κ N 6 log N ) , where the condition number κ is empirically in the range 10-200. Its efficiency relies on the observation that the normal equations are equivalent to a deconvolution problem in six dimensions. This is then solved by the conjugate gradient method with an appropriate circulant preconditioner. The result is the first computationally efficient algorithm for consistent estimation of the 3D covariance from noisy projections. It also compares favorably in runtime with respect to previously proposed nonconsistent estimators. Motivated by the recent success of eigenvalue shrinkage procedures for high-dimensional covariance matrix estimation, we incorporate a shrinkage procedure that improves accuracy at lower signal-to-noise ratios. We evaluate our methods on simulated datasets and achieve classification results comparable to state-of-the-art methods in shorter running time. We also present results on clustering volumes in an experimental dataset, illustrating the power of the proposed algorithm for practical determination of structural variability.

Allosteric effects in bacteriophage HK97 procapsids revealed directly from covariance analysis of cryo EM data

The information content of cryo EM data sets exceeds that of the electron scattering potential (cryo EM) density initially derived for structure determination. Previously we demonstrated the power of data variance analysis for characterizing regions of cryo EM density that displayed functionally important variance anomalies associated with maturation cleavage events in Nudaurelia Omega Capensis Virus and the presence or absence of a maturation protease in bacteriophage HK97 procapsids. Here we extend the analysis in two ways. First, instead of imposing icosahedral symmetry on every particle in the data set during the variance analysis, we only assume that the data set as a whole has icosahedral symmetry. This change removes artifacts of high variance along icosahedral symmetry axes, but retains all of the features previously reported in the HK97 data set. Second we present a covariance analysis that reveals correlations in structural dynamics (variance) between the interior of the HK97 procapsid with the protease and regions of the exterior (not seen in the absence of the protease). The latter analysis corresponds well with hydrogen deuterium exchange studies previously published that reveal the same correlation.

Structural Study of Heterogeneous Biological Samples by Cryoelectron Microscopy and Image Processing

In living organisms, biological macromolecules are intrinsically flexible and naturally exist in multiple conformations. Modern electron microscopy, especially at liquid nitrogen temperatures (cryo-EM), is able to visualise biocomplexes in nearly native conditions and in multiple conformational states. The advances made during the last decade in electronic technology and software development have led to the revelation of structural variations in complexes and also improved the resolution of EM structures. Nowadays, structural studies based on single particle analysis (SPA) suggests several approaches for the separation of different conformational states and therefore disclosure of the mechanisms for functioning of complexes. The task of resolving different states requires the examination of large datasets, sophisticated programs, and significant computing power. Some methods are based on analysis of two-dimensional images, while others are based on three-dimensional studies. In this review, we describe the basic principles implemented in the various techniques that are currently used in the analysis of structural conformations and provide some examples of successful applications of these methods in structural studies of biologically significant complexes.

Computational methods for analyzing conformational variability of macromolecular complexes from cryo-electron microscopy images

Thanks to latest technical advances in cryo-electron microscopy (cryo-EM), structures of macromolecular complexes (viruses, ribosomes, etc.) are now often obtained at near-atomic resolution. Also, studies of conformational changes of complexes, in connection with their function, are gaining ground. Conformational variability analysis is usually done by classifying images in a number of discrete classes supposedly representing all conformational states present in the specimen. However, discrete classes cannot be meaningfully defined when the conformational change is continuous (the specimen contains a continuum of states instead of a few discrete states). For such cases, first image analysis methods that explicitly consider continuous conformational changes were recently developed. The latest developments in cryo-EM image analysis methods for conformational variability analysis are the focus of this review.

Cryo-electron Microscopy Analysis of Structurally Heterogeneous Macromolecular Complexes

Cryo-electron microscopy (cryo-EM) has for a long time been a technique of choice for determining structure of large and flexible macromolecular complexes that were difficult to study by other experimental techniques such as X-ray crystallography or nuclear magnetic resonance. However, a fast development of instruments and software for cryo-EM in the last decade has allowed that a large range of complexes can be studied by cryo-EM, and that their structures can be obtained at near-atomic resolution, including the structures of small complexes (e.g., membrane proteins) whose size was earlier an obstacle to cryo-EM. Image analysis to identify multiple coexisting structures in the same specimen (multiconformation reconstruction) is now routinely done both to solve structures at near-atomic resolution and to study conformational dynamics. Methods for multiconformation reconstruction and latest examples of their applications are the focus of this review.

Cryo-EM in the study of challenging systems: the human transcription pre-initiation complex

Single particle cryo-Electron Microscopy (cryo-EM) is a technique that allows the structural characterization of macromolecules without the need for crystallization. For certain type of samples that are ideally suited for cryo-EM studies it has been possible to reach high-resolution structures following relatively standard procedures. Other biological systems remain highly challenging, even for cryo-EM. Challenges may involve the scarcity of the sample, poor stability of the complexes, and most often, the intrinsic flexibility of biological molecules. Among these challenging samples are large eukaryotic transcription complexes, which suffer from all such shortcomings. Here we report how we have recently tried to overcome those challenges in order to improve our structural understanding of the human transcription pre-initiation complex assembly and the transcription initiation process. Parallel efforts have also been carried out for budding yeast transcription initiation complexes, allowing comparisons that establish both the overall conservation and the specific structural differences between the two systems.

Single-Particle Refinement and Variability Analysis in EMAN2.1

CryoEM single-particle reconstruction has been growing rapidly over the last 3 years largely due to the development of direct electron detectors, which have provided data with dramatic improvements in image quality. It is now possible in many cases to produce near-atomic resolution structures, and yet 2/3 of published structures remain at substantially lower resolutions. One important cause for this is compositional and conformational heterogeneity, which is both a resolution-limiting factor and presenting a unique opportunity to better relate structure to function. This manuscript discusses the canonical methods for high-resolution refinement in EMAN2.12, and then considers the wide range of available methods within this package for resolving structural variability, targeting both improved resolution and additional knowledge about particle dynamics.

Local analysis of strains and rotations for macromolecular electron microscopy maps

Macromolecular complexes perform their physiological functions by local rearrangements of their constituents and biochemically interacting with their reaction partners. These rearrangements may involve local rotations and the induction of local strains causing different mechanical efforts and stretches at the different areas of the protein. The analysis of these local deformations may reveal important insight into the way proteins perform their tasks. In this paper we introduce a method to perform this kind of local analysis using Electron Microscopy volumes in a fully objective and automatic manner. For doing so, we exploit the continuous nature of the result of an elastic image registration using B-splines as its basis functions. We show that the results obtained by the new automatic method are consistent with previous observations on these macromolecules.

Evaluation of reconstruction errors and identification of artefacts for JET gamma and neutron tomography

The Joint European Torus (JET) neutron profile monitor ensures 2D coverage of the gamma and neutron emissive region that enables tomographic reconstruction. Due to the availability of only two projection angles and to the coarse sampling, tomographic inversion is a limited data set problem. Several techniques have been developed for tomographic reconstruction of the 2-D gamma and neutron emissivity on JET, but the problem of evaluating the errors associated with the reconstructed emissivity profile is still open. The reconstruction technique based on the maximum likelihood principle, that proved already to be a powerful tool for JET tomography, has been used to develop a method for the numerical evaluation of the statistical properties of the uncertainties in gamma and neutron emissivity reconstructions. The image covariance calculation takes into account the additional techniques introduced in the reconstruction process for tackling with the limited data set (projection resampling, smoothness regularization depending on magnetic field). The method has been validated by numerically simulations and applied to JET data. Different sources of artefacts that may significantly influence the quality of reconstructions and the accuracy of variance calculation have been identified.

Principles of cryo-EM single-particle image processing

Single-particle reconstruction is the process by which 3D density maps are obtained from a set of low-dose cryo-EM images of individual macromolecules. This review considers the fundamental principles of this process and the steps in the overall workflow for single-particle image processing. Also considered are the limits that image signal-to-noise ratio places on resolution and the distinguishing of heterogeneous particle populations.

A local-optimization refinement algorithm in single particle analysis for macromolecular complex with multiple rigid modules

Single particle analysis, which can be regarded as an average of signals from thousands or even millions of particle projections, is an efficient method to study the three-dimensional structures of biological macromolecules. An intrinsic assumption in single particle analysis is that all the analyzed particles must have identical composition and conformation. Thus specimen heterogeneity in either composition or conformation has raised great challenges for high-resolution analysis. For particles with multiple conformations, inaccurate alignments and orientation parameters will yield an averaged map with diminished resolution and smeared density. Besides extensive classification approaches, here based on the assumption that the macromolecular complex is made up of multiple rigid modules whose relative orientations and positions are in slight fluctuation around equilibriums, we propose a new method called as local optimization refinement to address this conformational heterogeneity for an improved resolution. The key idea is to optimize the orientation and shift parameters of each rigid module and then reconstruct their three-dimensional structures individually. Using simulated data of 80S/70S ribosomes with relative fluctuations between the large (60S/50S) and the small (40S/30S) subunits, we tested this algorithm and found that the resolutions of both subunits are significantly improved. Our method provides a proof-of-principle solution for high-resolution single particle analysis of macromolecular complexes with dynamic conformations.

Efficient estimation of three-dimensional covariance and its application in the analysis of heterogeneous samples in cryo-electron microscopy

Single-particle cryogenic electron microscopy (cryo-EM) is a powerful tool for the study of macromolecular structures at high resolution. Classification allows multiple structural states to be extracted and reconstructed from the same sample. One classification approach is via the covariance matrix, which captures the correlation between every pair of voxels. Earlier approaches employ computing-intensive resampling and estimate only the eigenvectors of the matrix, which are then used in a separate fast classification step. We propose an iterative scheme to explicitly estimate the covariance matrix in its entirety. In our approach, the flexibility in choosing the solution domain allows us to examine a part of the molecule in greater detail. Three-dimensional covariance maps obtained in this way from experimental data (cryo-EM images of the eukaryotic pre-initiation complex) prove to be in excellent agreement with conclusions derived by using traditional approaches, revealing in addition the interdependencies of ligand bindings and structural changes.

Architecture of the RNA polymerase II-Mediator core initiation complex

The conserved co-activator complex Mediator enables regulated transcription initiation by RNA polymerase (Pol) II. Here we reconstitute an active 15-subunit core Mediator (cMed) comprising all essential Mediator subunits from Saccharomyces cerevisiae. The cryo-electron microscopic structure of cMed bound to a core initiation complex was determined at 9.7 Å resolution. cMed binds Pol II around the Rpb4-Rpb7 stalk near the carboxy-terminal domain (CTD). The Mediator head module binds the Pol II dock and the TFIIB ribbon and stabilizes the initiation complex. The Mediator middle module extends to the Pol II foot with a 'plank' that may influence polymerase conformation. The Mediator subunit Med14 forms a 'beam' between the head and middle modules and connects to the tail module that is predicted to bind transcription activators located on upstream DNA. The Mediator 'arm' and 'hook' domains contribute to a 'cradle' that may position the CTD and TFIIH kinase to stimulate Pol II phosphorylation.

Covariance Matrix Estimation for the Cryo-EM Heterogeneity Problem

In cryo-electron microscopy (cryo-EM), a microscope generates a top view of a sample of randomly oriented copies of a molecule. The problem of single particle reconstruction (SPR) from cryo-EM is to use the resulting set of noisy two-dimensional projection images taken at unknown directions to reconstruct the three-dimensional (3D) structure of the molecule. In some situations, the molecule under examination exhibits structural variability, which poses a fundamental challenge in SPR. The heterogeneity problem is the task of mapping the space of conformational states of a molecule. It has been previously suggested that the leading eigenvectors of the covariance matrix of the 3D molecules can be used to solve the heterogeneity problem. Estimating the covariance matrix is challenging, since only projections of the molecules are observed, but not the molecules themselves. In this paper, we formulate a general problem of covariance estimation from noisy projections of samples. This problem has intimate connections with matrix completion problems and high-dimensional principal component analysis. We propose an estimator and prove its consistency. When there are finitely many heterogeneity classes, the spectrum of the estimated covariance matrix reveals the number of classes. The estimator can be found as the solution to a certain linear system. In the cryo-EM case, the linear operator to be inverted, which we term the projection covariance transform, is an important object in covariance estimation for tomographic problems involving structural variation. Inverting it involves applying a filter akin to the ramp filter in tomography. We design a basis in which this linear operator is sparse and thus can be tractably inverted despite its large size. We demonstrate via numerical experiments on synthetic datasets the robustness of our algorithm to high levels of noise.

Cryo-EM of ribosomal 80S complexes with termination factors reveals the translocated cricket paralysis virus IRES

The cricket paralysis virus (CrPV) uses an internal ribosomal entry site (IRES) to hijack the ribosome. In a remarkable RNA-based mechanism involving neither initiation factor nor initiator tRNA, the CrPV IRES jumpstarts translation in the elongation phase from the ribosomal A site. Here, we present cryoelectron microscopy (cryo-EM) maps of 80S⋅CrPV-STOP ⋅ eRF1 ⋅ eRF3 ⋅ GMPPNP and 80S⋅CrPV-STOP ⋅ eRF1 complexes, revealing a previously unseen binding state of the IRES and directly rationalizing that an eEF2-dependent translocation of the IRES is required to allow the first A-site occupation. During this unusual translocation event, the IRES undergoes a pronounced conformational change to a more stretched conformation. At the same time, our structural analysis provides information about the binding modes of eRF1 ⋅ eRF3 ⋅ GMPPNP and eRF1 in a minimal system. It shows that neither eRF3 nor ABCE1 are required for the active conformation of eRF1 at the intersection between eukaryotic termination and recycling.

Regulation of the mammalian elongation cycle by subunit rolling: a eukaryotic-specific ribosome rearrangement

The extent to which bacterial ribosomes and the significantly larger eukaryotic ribosomes share the same mechanisms of ribosomal elongation is unknown. Here, we present subnanometer resolution cryoelectron microscopy maps of the mammalian 80S ribosome in the posttranslocational state and in complex with the eukaryotic eEF1A⋅Val-tRNA⋅GMPPNP ternary complex, revealing significant differences in the elongation mechanism between bacteria and mammals. Surprisingly, and in contrast to bacterial ribosomes, a rotation of the small subunit around its long axis and orthogonal to the well-known intersubunit rotation distinguishes the posttranslocational state from the classical pretranslocational state ribosome. We term this motion "subunit rolling." Correspondingly, a mammalian decoding complex visualized in substates before and after codon recognition reveals structural distinctions from the bacterial system. These findings suggest how codon recognition leads to GTPase activation in the mammalian system and demonstrate that in mammalia subunit rolling occurs during tRNA selection.

Hepatitis-C-virus-like internal ribosome entry sites displace eIF3 to gain access to the 40S subunit

Hepatitis C virus (HCV) and classical swine fever virus (CSFV) messenger RNAs contain related (HCV-like) internal ribosome entry sites (IRESs) that promote 5'-end independent initiation of translation, requiring only a subset of the eukaryotic initiation factors (eIFs) needed for canonical initiation on cellular mRNAs. Initiation on HCV-like IRESs relies on their specific interaction with the 40S subunit, which places the initiation codon into the P site, where it directly base-pairs with eIF2-bound initiator methionyl transfer RNA to form a 48S initiation complex. However, all HCV-like IRESs also specifically interact with eIF3 (refs 2, 5-7, 9-12), but the role of this interaction in IRES-mediated initiation has remained unknown. During canonical initiation, eIF3 binds to the 40S subunit as a component of the 43S pre-initiation complex, and comparison of the ribosomal positions of eIF3 and the HCV IRES revealed that they overlap, so that their rearrangement would be required for formation of ribosomal complexes containing both components. Here we present a cryo-electron microscopy reconstruction of a 40S ribosomal complex containing eIF3 and the CSFV IRES. Remarkably, although the position and interactions of the CSFV IRES with the 40S subunit in this complex are similar to those of the HCV IRES in the 40S-IRES binary complex, eIF3 is completely displaced from its ribosomal position in the 43S complex, and instead interacts through its ribosome-binding surface exclusively with the apical region of domain III of the IRES. Our results suggest a role for the specific interaction of HCV-like IRESs with eIF3 in preventing ribosomal association of eIF3, which could serve two purposes: relieving the competition between the IRES and eIF3 for a common binding site on the 40S subunit, and reducing formation of 43S complexes, thereby favouring translation of viral mRNAs.

Visualizing GroEL/ES in the act of encapsulating a folding protein

The GroEL/ES chaperonin system is required for the assisted folding of many proteins. How these substrate proteins are encapsulated within the GroEL-GroES cavity is poorly understood. Using symmetry-free, single-particle cryo-electron microscopy, we have characterized a chemically modified mutant of GroEL (EL43Py) that is trapped at a normally transient stage of substrate protein encapsulation. We show that the symmetric pattern of the GroEL subunits is broken as the GroEL cis-ring apical domains reorient to accommodate the simultaneous binding of GroES and an incompletely folded substrate protein (RuBisCO). The collapsed RuBisCO folding intermediate binds to the lower segment of two apical domains, as well as to the normally unstructured GroEL C-terminal tails. A comparative structural analysis suggests that the allosteric transitions leading to substrate protein release and folding involve concerted shifts of GroES and the GroEL apical domains and C-terminal tails.

One number does not fit all: mapping local variations in resolution in cryo-EM reconstructions

The resolution of density maps from single particle analysis is usually measured in terms of the highest spatial frequency to which consistent information has been obtained. This calculation represents an average over the entire reconstructed volume. In practice, however, substantial local variations in resolution may occur, either from intrinsic properties of the specimen or for technical reasons such as a non-isotropic distribution of viewing orientations. To address this issue, we propose the use of a space-frequency representation, the short-space Fourier transform, to assess the quality of a density map, voxel-by-voxel, i.e. by local resolution mapping. In this approach, the experimental volume is divided into small subvolumes and the resolution determined for each of them. It is illustrated in applications both to model data and to experimental density maps. Regions with lower-than-average resolution may be mobile components or ones with incomplete occupancy or result from multiple conformational states. To improve the interpretability of reconstructions, we propose an adaptive filtering approach that reconciles the resolution to which individual features are calculated with the results of the local resolution map.

Structure of the mammalian ribosomal 43S preinitiation complex bound to the scanning factor DHX29

Eukaryotic translation initiation begins with assembly of a 43S preinitiation complex. First, methionylated initiator methionine transfer RNA (Met-tRNAi(Met)), eukaryotic initiation factor (eIF) 2, and guanosine triphosphate form a ternary complex (TC). The TC, eIF3, eIF1, and eIF1A cooperatively bind to the 40S subunit, yielding the 43S preinitiation complex, which is ready to attach to messenger RNA (mRNA) and start scanning to the initiation codon. Scanning on structured mRNAs additionally requires DHX29, a DExH-box protein that also binds directly to the 40S subunit. Here, we present a cryo-electron microscopy structure of the mammalian DHX29-bound 43S complex at 11.6 Å resolution. It reveals that eIF2 interacts with the 40S subunit via its α subunit and supports Met-tRNAi(Met) in an unexpected P/I orientation (eP/I). The structural core of eIF3 resides on the back of the 40S subunit, establishing two principal points of contact, whereas DHX29 binds around helix 16. The structure provides insights into eukaryote-specific aspects of translation, including the mechanism of action of DHX29.

The ribosome triggers the stringent response by RelA via a highly distorted tRNA

The bacterial stringent response links nutrient starvation with the transcriptional control of genes. This process is initiated by the stringent factor RelA, which senses the presence of deacylated tRNA in the ribosome as a symptom of amino-acid starvation to synthesize the alarmone (p)ppGpp. Here we report a cryo-EM study of RelA bound to ribosomes bearing cognate, deacylated tRNA in the A-site. The data show that RelA on the ribosome stabilizes an unusual distorted form of the tRNA, with the acceptor arm making contact with RelA and far from its normal location in the peptidyl transferase centre.

Likelihood-based classification of cryo-EM images using FREALIGN

We describe an implementation of maximum likelihood classification for single particle electron cryo-microscopy that is based on the FREALIGN software. Particle alignment parameters are determined by maximizing a joint likelihood that can include hierarchical priors, while classification is performed by expectation maximization of a marginal likelihood. We test the FREALIGN implementation using a simulated dataset containing computer-generated projection images of three different 70S ribosome structures, as well as a publicly available dataset of 70S ribosomes. The results show that the mixed strategy of the new FREALIGN algorithm yields performance on par with other maximum likelihood implementations, while remaining computationally efficient.

High-resolution cryo-electron microscopy structure of the Trypanosoma brucei ribosome

Ribosomes, the protein factories of living cells, translate genetic information carried by messenger RNAs into proteins, and are thus involved in virtually all aspects of cellular development and maintenance. The few available structures of the eukaryotic ribosome reveal that it is more complex than its prokaryotic counterpart, owing mainly to the presence of eukaryote-specific ribosomal proteins and additional ribosomal RNA insertions, called expansion segments. The structures also differ among species, partly in the size and arrangement of these expansion segments. Such differences are extreme in kinetoplastids, unicellular eukaryotic parasites often infectious to humans. Here we present a high-resolution cryo-electron microscopy structure of the ribosome of Trypanosoma brucei, the parasite that is transmitted by the tsetse fly and that causes African sleeping sickness. The atomic model reveals the unique features of this ribosome, characterized mainly by the presence of unusually large expansion segments and ribosomal-protein extensions leading to the formation of four additional inter-subunit bridges. We also find additional rRNA insertions, including one large rRNA domain that is not found in other eukaryotes. Furthermore, the structure reveals the five cleavage sites of the kinetoplastid large ribosomal subunit (LSU) rRNA chain, which is known to be cleaved uniquely into six pieces, and suggests that the cleavage is important for the maintenance of the T. brucei ribosome in the observed structure. We discuss several possible implications of the large rRNA expansion segments for the translation-regulation process. The structure could serve as a basis for future experiments aimed at understanding the functional importance of these kinetoplastid-specific ribosomal features in protein-translation regulation, an essential step towards finding effective and safe kinetoplastid-specific drugs.

Dynamics in cryo EM reconstructions visualized with maximum-likelihood derived variance maps

CryoEM data capture the dynamic character associated with biological macromolecular assemblies by preserving the various conformations of the individual specimens at the moment of flash freezing. Regions of high variation in the data set are apparent in the image reconstruction due to the poor density that results from the lack of superposition of these regions. These observations are qualitative and, to date, only preliminary efforts have been made to quantitate the heterogeneity in the ensemble of particles that are individually imaged. We developed and tested a quantitative method for simultaneously computing a reconstruction of the particle and a map of the space-varying heterogeneity of the particle based on an entire data set. The method uses a maximum likelihood algorithm that explicitly takes into account the continuous variability from one instance to another instance of the particle. The result describes the heterogeneity of the particle as a variance to be plotted at every voxel of the reconstructed density. The test, employing time resolved data sets of virus maturation, not only recapitulated local variations obtained with difference map analysis, but revealed a remarkable time dependent reduction in the overall particle dynamics that was unobservable with classical methods of analysis.

Multiscale natural moves refine macromolecules using single-particle electron microscopy projection images

The method presented here refines molecular conformations directly against projections of single particles measured by electron microscopy. By optimizing the orientation of the projection at the same time as the conformation, the method is well-suited to two-dimensional class averages from cryoelectron microscopy. Such direct use of two-dimensional images circumvents the need for a three-dimensional density map, which may be difficult to reconstruct from projections due to structural heterogeneity or preferred orientations of the sample on the grid. Our refinement protocol exploits Natural Move Monte Carlo to model a macromolecule as a small number of segments connected by flexible loops, on multiple scales. After tests on artificial data from lysozyme, we applied the method to the Methonococcus maripaludis chaperonin. We successfully refined its conformation from a closed-state initial model to an open-state final model using just one class-averaged projection. We also used Natural Moves to iteratively refine against heterogeneous projection images of Methonococcus maripaludis chaperonin in a mix of open and closed states. Our results suggest a general method for electron microscopy refinement specially suited to macromolecules with significant conformational flexibility. The algorithm is available in the program Methodologies for Optimization and Sampling In Computational Studies.

The structure of human tripeptidyl peptidase II as determined by a hybrid approach

Tripeptidyl-peptidase II (TPPII) is a high molecular mass (∼5 MDa) serine protease, which is thought to act downstream of the 26S proteasome, cleaving peptides released by the latter. Here, the structure of human TPPII (HsTPPII) has been determined to subnanometer resolution by cryoelectron microscopy and single-particle analysis. The complex is built from two strands forming a quasihelical structure harboring a complex system of inner cavities. HsTPPII particles exhibit some polymorphism resulting in complexes consisting of nine or of eight dimers per strand. To obtain deeper insights into the architecture and function of HsTPPII, we have created a pseudoatomic structure of the HsTPPII spindle using a comparative model of HsTPPII dimers and molecular dynamics flexible fitting. Analyses of the resulting hybrid structure of the HsTPPII holocomplex provide new insights into the mechanism of maturation and activation.

Identifying conformational states of macromolecules by eigen-analysis of resampled cryo-EM images

We present the codimensional principal component analysis (PCA), a novel and straightforward method for resolving sample heterogeneity within a set of cryo-EM 2D projection images of macromolecular assemblies. The method employs PCA of resampled 3D structures computed using subsets of 2D data obtained with a novel hypergeometric sampling scheme. PCA provides us with a small subset of dominating "eigenvolumes" of the system, whose reprojections are compared with experimental projection data to yield their factorial coordinates constructed in a common framework of the 3D space of the macromolecule. Codimensional PCA is unique in the dramatic reduction of dimensionality of the problem, which facilitates rapid determination of both the plausible number of conformers in the sample and their 3D structures. We applied the codimensional PCA to a complex data set of Thermus thermophilus 70S ribosome, and we identified four major conformational states and visualized high mobility of the stalk base region.

Activator-mediator binding stabilizes RNA polymerase II orientation within the human mediator-RNA polymerase II-TFIIF assembly

The human Mediator complex controls RNA polymerase II (pol II) function in ways that remain incompletely understood. Activator-Mediator binding alters Mediator structure, and these activator-induced structural shifts appear to play key roles in regulating transcription. A recent cryo-electron microscopy (EM) analysis revealed that pol II adopted a stable orientation within a Mediator-pol II-TFIIF assembly in which Mediator was bound to the activation domain of viral protein 16 (VP16). Whereas TFIIF was shown to be important for orienting pol II within this assembly, the potential role of the activator was not assessed. To determine how activator binding might affect pol II orientation, we isolated human Mediator-pol II-TFIIF complexes in which Mediator was not bound to an activator. Cryo-EM analysis of this assembly, coupled with pol II crystal structure docking, revealed that pol II binds Mediator at the same general location; however, in contrast to VP16-bound Mediator, pol II does not appear to stably orient in the absence of an activator. Variability in pol II orientation might be important mechanistically, perhaps to enable sense and antisense transcription at human promoters. Because Mediator interacts extensively with pol II, these results suggest that Mediator structural shifts induced by activator binding help stably orient pol II prior to transcription initiation.

Structural insights into methyltransferase KsgA function in 30S ribosomal subunit biogenesis

The assembly of the ribosomal subunits is facilitated by ribosome biogenesis factors. The universally conserved methyltransferase KsgA modifies two adjacent adenosine residues in the 3'-terminal helix 45 of the 16 S ribosomal RNA (rRNA). KsgA recognizes its substrate adenosine residues only in the context of a near mature 30S subunit and is required for the efficient processing of the rRNA termini during ribosome biogenesis. Here, we present the cryo-EM structure of KsgA bound to a nonmethylated 30S ribosomal subunit. The structure reveals that KsgA binds to the 30S platform with the catalytic N-terminal domain interacting with substrate adenosine residues in helix 45 and the C-terminal domain making extensive contacts to helix 27 and helix 24. KsgA excludes the penultimate rRNA helix 44 from adopting its position in the mature 30S subunit, blocking the formation of the decoding site and subunit joining. We suggest that the activation of methyltransferase activity and subsequent dissociation of KsgA control conformational changes in helix 44 required for final rRNA processing and translation initiation.

Reconstructing virus structures from nanometer to near-atomic resolutions with cryo-electron microscopy and tomography

The past few decades have seen tremendous advances in single-particle electron -cryo-microscopy (cryo-EM). The field has matured to the point that near-atomic resolution density maps can be generated for icosahedral viruses without the need for crystallization. In parallel, substantial progress has been made in determining the structures of nonicosahedrally arranged proteins in viruses by employing either single-particle cryo-EM or cryo-electron tomography (cryo-ET). Implicit in this course have been the availability of a new generation of electron cryo-microscopes and the development of the computational tools that are essential for generating these maps and models. This methodology has enabled structural biologists to analyze structures in increasing detail for virus particles that are in different morphogenetic states. Furthermore, electron imaging of frozen, hydrated cells, in the process of being infected by viruses, has also opened up a new avenue for studying virus structures "in situ". Here we present the common techniques used to acquire and process cryo-EM and cryo-ET data and discuss their implications for structural virology both now and in the future.