Efficient initial volume determination from electron microscopy images of single particles

Structural recognition and stabilization of tyrosine hydroxylase by the J-domain protein DNAJC12

Pathogenic variants of the J-domain protein DNAJC12 cause parkinsonism, which is associated with a defective interaction of DNAJC12 with tyrosine hydroxylase (TH), the rate-limiting enzyme in dopamine biosynthesis. In this work, we characterize the formation of the TH:DNAJC12 complex, showing that DNAJC12 binding stabilizes both TH and the variant TH-p.R202H, associated with TH deficiency. This binding delays their time-dependent aggregation in an Hsp70-independent manner, while preserving TH activity and feedback regulatory inhibition by dopamine. DNAJC12 alone barely activates Hsc70 but synergistically stimulates Hsc70 ATPase activity when complexed with TH. Cryo-electron microscopy supported by crosslinking-mass spectroscopy reveals two DNAJC12 monomers bound per TH tetramer, each embracing one of the two regulatory domain dimers, leaving the active sites available for substrate, cofactor and inhibitory dopamine interaction. Our results also reveal the key role of the C-terminal region of DNAJC12 in TH binding, explaining the pathogenic mechanism of the DNAJC12 disease variant p.W175Ter.

The self-association equilibrium of DNAJA2 regulates its interaction with unfolded substrate proteins and with Hsc70

J-domain proteins tune the specificity of Hsp70s, engaging them in precise functions. Despite their essential role, the structure and function of many J-domain proteins remain largely unknown. We explore human DNAJA2, finding that it reversibly forms highly-ordered, tubular structures that can be dissociated by Hsc70, the constitutively expressed Hsp70 isoform. Cryoelectron microscopy and mutational studies reveal that different domains are involved in self-association. Oligomer dissociation into dimers potentiates its interaction with unfolded client proteins. The J-domains are accessible to Hsc70 within the tubular structure. They allow binding of closely spaced Hsc70 molecules that could be transferred to the unfolded substrate for its cooperative remodelling, explaining the efficient recovery of DNAJA2-bound clients. The disordered C-terminal domain, comprising the last 52 residues, regulates its holding activity and productive interaction with Hsc70. These in vitro findings suggest that the association equilibrium of DNAJA2 could regulate its interaction with client proteins and Hsc70.

Scipion3: A workflow engine for cryo-electron microscopy image processing and structural biology

Image-processing pipelines require the design of complex workflows combining many different steps that bring the raw acquired data to a final result with biological meaning. In the image-processing domain of cryo-electron microscopy single-particle analysis (cryo-EM SPA), hundreds of steps must be performed to obtain the three-dimensional structure of a biological macromolecule by integrating data spread over thousands of micrographs containing millions of copies of allegedly the same macromolecule. The execution of such complicated workflows demands a specific tool to keep track of all these steps performed. Additionally, due to the extremely low signal-to-noise ratio (SNR), the estimation of any image parameter is heavily affected by noise resulting in a significant fraction of incorrect estimates. Although low SNR and processing millions of images by hundreds of sequential steps requiring substantial computational resources are specific to cryo-EM, these characteristics may be shared by other biological imaging domains. Here, we present Scipion, a Python generic open-source workflow engine specifically adapted for image processing. Its main characteristics are: (a) interoperability, (b) smart object model, (c) gluing operations, (d) comparison operations, (e) wide set of domain-specific operations, (f) execution in streaming, (g) smooth integration in high-performance computing environments, (h) execution with and without graphical capabilities, (i) flexible visualization, (j) user authentication and private access to private data, (k) scripting capabilities, (l) high performance, (m) traceability, (n) reproducibility, (o) self-reporting, (p) reusability, (q) extensibility, (r) software updates, and (s) non-restrictive software licensing.

Unsupervised Cryo-EM Images Denoising and Clustering Based on Deep Convolutional Autoencoder and K-Means+

Cryo-electron microscopy (cryo-EM) is a widely used structural determination technique. Because of the extremely low signal-to-noise ratio (SNR) of images captured by cryo-EM, clustering single-particle cryo-EM images with high accuracy is challenging. To address this, we proposed an iterative denoising and clustering method based on a deep convolutional variational autoencoder and K-means++. The proposed method contains two modules: a denoising ResNet variational autoencoder (DRVAE), and Balance size K-means++ (BSK-means++). First, the DRVAE is trained in a fully unsupervised manner to initialize the neural network and obtain preliminary denoised images. Second, BSK-means++ is built for clustering denoised images, and images closer to class centers are divided into reliable samples. Third, the training of DRVAE is continued, while the class-average images are used as pseudo supervision of reliable samples to reserve more detailed information of denoised images. Finally, the second and third steps mentioned above can be performed jointly and iteratively until convergence occurs. The experimental results showed that the proposed method can generate reliable class average images and achieve better clustering accuracy and normalized mutual information than current methods. This study confirmed that DRVAE with BSK-means++ could achieve a good denoise performance on single-particle cryo-EM images, which can help researchers obtain information such as symmetry and heterogeneity of the target particles. In addition, the proposed method avoids the extreme imbalance of class size, which improves the reliability of the clustering result.

Emerging Themes in CryoEM─Single Particle Analysis Image Processing

Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.

On bias, variance, overfitting, gold standard and consensus in single-particle analysis by cryo-electron microscopy

Cryo-electron microscopy (cryoEM) has become a well established technique to elucidate the 3D structures of biological macromolecules. Projection images from thousands of macromolecules that are assumed to be structurally identical are combined into a single 3D map representing the Coulomb potential of the macromolecule under study. This article discusses possible caveats along the image-processing path and how to avoid them to obtain a reliable 3D structure. Some of these problems are very well known in the community. These may be referred to as sample-related (such as specimen denaturation at interfaces or non-uniform projection geometry leading to underrepresented projection directions). The rest are related to the algorithms used. While some have been discussed in depth in the literature, such as the use of an incorrect initial volume, others have received much less attention. However, they are fundamental in any data-analysis approach. Chiefly among them, instabilities in estimating many of the key parameters that are required for a correct 3D reconstruction that occur all along the processing workflow are referred to, which may significantly affect the reliability of the whole process. In the field, the term overfitting has been coined to refer to some particular kinds of artifacts. It is argued that overfitting is a statistical bias in key parameter-estimation steps in the 3D reconstruction process, including intrinsic algorithmic bias. It is also shown that common tools (Fourier shell correlation) and strategies (gold standard) that are normally used to detect or prevent overfitting do not fully protect against it. Alternatively, it is proposed that detecting the bias that leads to overfitting is much easier when addressed at the level of parameter estimation, rather than detecting it once the particle images have been combined into a 3D map. Comparing the results from multiple algorithms (or at least, independent executions of the same algorithm) can detect parameter bias. These multiple executions could then be averaged to give a lower variance estimate of the underlying parameters.

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.

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.

Structural mechanism for tyrosine hydroxylase inhibition by dopamine and reactivation by Ser40 phosphorylation

Tyrosine hydroxylase (TH) catalyzes the rate-limiting step in the biosynthesis of dopamine (DA) and other catecholamines, and its dysfunction leads to DA deficiency and parkinsonisms. Inhibition by catecholamines and reactivation by S40 phosphorylation are key regulatory mechanisms of TH activity and conformational stability. We used Cryo-EM to determine the structures of full-length human TH without and with DA, and the structure of S40 phosphorylated TH, complemented with biophysical and biochemical characterizations and molecular dynamics simulations. TH presents a tetrameric structure with dimerized regulatory domains that are separated 15 Å from the catalytic domains. Upon DA binding, a 20-residue α-helix in the flexible N-terminal tail of the regulatory domain is fixed in the active site, blocking it, while S40-phosphorylation forces its egress. The structures reveal the molecular basis of the inhibitory and stabilizing effects of DA and its counteraction by S40-phosphorylation, key regulatory mechanisms for homeostasis of DA and TH.

Tyrosine hydroxylase (TH) catalyzes the rate-limiting step in the synthesis of the catecholamine neurotransmitters and hormones dopamine (DA), adrenaline and noradrenaline. Here, the authors present the cryo-EM structures of full-length human TH in the apo form and bound with DA, as well as the structure of Ser40 phosphorylated TH, and discuss the inhibitory and stabilizing effects of DA on TH and its counteraction by Ser40-phosphorylation.

Cryo-EM structure of a tetrameric photosystem I from Chroococcidiopsis TS-821, a thermophilic, unicellular, non-heterocyst-forming cyanobacterium

Photosystem I (PSI) is one of two photosystems involved in oxygenic photosynthesis. PSI of cyanobacteria exists in monomeric, trimeric, and tetrameric forms, in contrast to the strictly monomeric form of PSI in plants and algae. The tetrameric organization raises questions about its structural, physiological, and evolutionary significance. Here we report the ∼3.72 Å resolution cryo-electron microscopy structure of tetrameric PSI from the thermophilic, unicellular cyanobacterium Chroococcidiopsis sp. TS-821. The structure resolves 44 subunits and 448 cofactor molecules. We conclude that the tetramer is arranged via two different interfaces resulting from a dimer-of-dimers organization. The localization of chlorophyll molecules permits an excitation energy pathway within and between adjacent monomers. Bioinformatics analysis reveals conserved regions in the PsaL subunit that correlate with the oligomeric state. Tetrameric PSI may function as a key evolutionary step between the trimeric and monomeric forms of PSI organization in photosynthetic organisms.

The molecular chaperone CCT sequesters gelsolin and protects it from cleavage by caspase-3

The actin filament severing and capping protein gelsolin plays an important role in modulation of actin filament dynamics by influencing the number of actin filament ends. During apoptosis, gelsolin becomes constitutively active due to cleavage by caspase-3. In non-apoptotic cells gelsolin is activated by the binding of Ca²⁺. This activated form of gelsolin binds to, but is not a folding substrate of the molecular chaperone CCT/TRiC. Here we demonstrate that in vitro, gelsolin is protected from cleavage by caspase-3 in the presence of CCT. Cryoelectron microscopy and single particle 3D reconstruction of the CCT:gelsolin complex reveals that gelsolin is located in the interior of the chaperonin cavity, with a placement distinct from that of the obligate CCT folding substrates actin and tubulin. In cultured mouse melanoma B16F1 cells, gelsolin co-localises with CCT upon stimulation of actin dynamics at peripheral regions during lamellipodia formation. These data indicate that localised sequestration of gelsolin by CCT may provide spatial control of actin filament dynamics.

Structural features of nucleosomes in interphase and metaphase chromosomes

Structural heterogeneity of nucleosomes in functional chromosomes is unknown. Here, we devise the template-, reference- and selection-free (TRSF) cryo-EM pipeline to simultaneously reconstruct cryo-EM structures of protein complexes from interphase or metaphase chromosomes. The reconstructed interphase and metaphase nucleosome structures are on average indistinguishable from canonical nucleosome structures, despite DNA sequence heterogeneity, cell-cycle-specific posttranslational modifications, and interacting proteins. Nucleosome structures determined by a decoy-classifying method and structure variability analyses reveal the nucleosome structural variations in linker DNA, histone tails, and nucleosome core particle configurations, suggesting that the opening of linker DNA, which is correlated with H2A C-terminal tail positioning, is suppressed in chromosomes. High-resolution (3.4-3.5 Å) nucleosome structures indicate DNA-sequence-independent stabilization of superhelical locations ±0-1 and ±3.5-4.5. The linker histone H1.8 preferentially binds to metaphase chromatin, from which chromatosome cryo-EM structures with H1.8 at the on-dyad position are reconstituted. This study presents the structural characteristics of nucleosomes in chromosomes.

Advances in Xmipp for Cryo-Electron Microscopy: From Xmipp to Scipion

Xmipp is an open-source software package consisting of multiple programs for processing data originating from electron microscopy and electron tomography, designed and managed by the Biocomputing Unit of the Spanish National Center for Biotechnology, although with contributions from many other developers over the world. During its 25 years of existence, Xmipp underwent multiple changes and updates. While there were many publications related to new programs and functionality added to Xmipp, there is no single publication on the Xmipp as a package since 2013. In this article, we give an overview of the changes and new work since 2013, describe technologies and techniques used during the development, and take a peek at the future of the package.

Image Processing in Cryo-Electron Microscopy of Single Particles: The Power of Combining Methods

Cryo-electron microscopy has established as a mature structural biology technique to elucidate the three-dimensional structure of biological macromolecules. The Coulomb potential of the sample is imaged by an electron beam, and fast semi-conductor detectors produce movies of the sample under study. These movies have to be further processed by a whole pipeline of image-processing algorithms that produce the final structure of the macromolecule. In this chapter, we illustrate this whole processing pipeline putting in value the strength of "meta algorithms," which are the combination of several algorithms, each one with different mathematical rationale, in order to distinguish correctly from incorrectly estimated parameters. We show how this strategy leads to superior performance of the whole pipeline as well as more confident assessments about the reconstructed structures. The "meta algorithms" strategy is common to many fields and, in particular, it has provided excellent results in bioinformatics. We illustrate this combination using the workflow engine, Scipion.

3D architecture and structural flexibility revealed in the subfamily of large glutamate dehydrogenases by a mycobacterial enzyme

Glutamate dehydrogenases (GDHs) are widespread metabolic enzymes that play key roles in nitrogen homeostasis. Large glutamate dehydrogenases composed of 180 kDa subunits (L-GDHs₁₈₀) contain long N- and C-terminal segments flanking the catalytic core. Despite the relevance of L-GDHs₁₈₀ in bacterial physiology, the lack of structural data for these enzymes has limited the progress of functional studies. Here we show that the mycobacterial L-GDH₁₈₀ (mL-GDH₁₈₀) adopts a quaternary structure that is radically different from that of related low molecular weight enzymes. Intersubunit contacts in mL-GDH₁₈₀ involve a C-terminal domain that we propose as a new fold and a flexible N-terminal segment comprising ACT-like and PAS-type domains that could act as metabolic sensors for allosteric regulation. These findings uncover unique aspects of the structure-function relationship in the subfamily of L-GDHs.

Lázaro et. al. report the first 3D structure of a large glutamate dehydrogenase (L-GDH), the one corresponding to the Mycobacterium smegmatis enzyme composed of 180 kDa subunits (mL-GDH₁₈₀), obtained by X-ray crystallography and cryo-electron microscopy. This structure reveals that mL-GDH₁₈₀ assembles as tetramers with the N- and C-terminal domains being involved in inter-subunit contacts and unveils unique features of the subfamily of L-GDHs.

Bayesian Random Tomography of Particle Systems

Random tomography is a common problem in imaging science and refers to the task of reconstructing a three-dimensional volume from two-dimensional projection images acquired in unknown random directions. We present a Bayesian approach to random tomography. At the center of our approach is a meshless representation of the unknown volume as a mixture of spherical Gaussians. Each Gaussian can be interpreted as a particle such that the unknown volume is represented by a particle cloud. The particle representation allows us to speed up the computation of projection images and to represent a large variety of structures accurately and efficiently. We develop Markov chain Monte Carlo algorithms to infer the particle positions as well as the unknown orientations. Posterior sampling is challenging due to the high dimensionality and multimodality of the posterior distribution. We tackle these challenges by using Hamiltonian Monte Carlo and a global rotational sampling strategy. We test the approach on various simulated and real datasets.

DeepAlign, a 3D alignment method based on regionalized deep learning for Cryo-EM

Cryo Electron Microscopy (Cryo-EM) is currently one of the main tools to reveal the structural information of biological specimens at high resolution. Despite the great development of the techniques involved to solve the biological structures with Cryo-EM in the last years, the reconstructed 3D maps can present lower resolution due to errors committed while processing the information acquired by the microscope. One of the main problems comes from the 3D alignment step, which is an error-prone part of the reconstruction workflow due to the very low signal-to-noise ratio (SNR) common in Cryo-EM imaging. In fact, as we will show in this work, it is not unusual to find a disagreement in the alignment parameters in approximately 20-40% of the processed images, when outputs of different alignment algorithms are compared. In this work, we present a novel method to align sets of single particle images in the 3D space, called DeepAlign. Our proposal is based on deep learning networks that have been successfully used in plenty of problems in image classification. Specifically, we propose to design several deep neural networks on a regionalized basis to classify the particle images in sub-regions and, then, make a refinement of the 3D alignment parameters only inside that sub-region. We show that this method results in accurately aligned images, improving the Fourier shell correlation (FSC) resolution obtained with other state-of-the-art methods while decreasing computational time.

Algorithmic robustness to preferred orientations in single particle analysis by CryoEM

The presence of preferred orientations in single particle analysis (SPA) by cryo-Electron Microscopy (cryoEM) is currently one of the hurdles preventing many structural analyses from yielding high-resolution structures. Although the existence of preferred orientations is mostly related to the grid preparation, in this technical note, we show that some image processing algorithms used for angular assignment and three-dimensional (3D) reconstruction are more robust than others to these detrimental conditions. We exemplify this argument with three different data sets in which the presence of preferred orientations hindered achieving a 3D reconstruction without artifacts or, even worse, a 3D reconstruction could never be achieved.

The Smc5/6 Core Complex Is a Structure-Specific DNA Binding and Compacting Machine

The structural organization of chromosomes is a crucial feature that defines the functional state of genes and genomes. The extent of structural changes experienced by genomes of eukaryotic cells can be dramatic and spans several orders of magnitude. At the core of these changes lies a unique group of ATPases-the SMC proteins-that act as major effectors of chromosome behavior in cells. The Smc5/6 proteins play essential roles in the maintenance of genome stability, yet their mode of action is not fully understood. Here we show that the human Smc5/6 complex recognizes unusual DNA configurations and uses the energy of ATP hydrolysis to promote their compaction. Structural analyses reveal subunit interfaces responsible for the functionality of the Smc5/6 complex and how mutations in these regions may lead to chromosome breakage syndromes in humans. Collectively, our results suggest that the Smc5/6 complex promotes genome stability as a DNA micro-compaction machine.

Arc self-association and formation of virus-like capsids are mediated by an N-terminal helical coil motif

Activity-regulated cytoskeleton-associated protein (Arc) is a protein interaction hub with diverse roles in intracellular neuronal signaling, and important functions in neuronal synaptic plasticity, memory, and postnatal cortical development. Arc has homology to retroviral Gag protein and is capable of self-assembly into virus-like capsids implicated in the intercellular transfer of RNA. However, the molecular basis of Arc self-association and capsid formation is largely unknown. Here, we identified a 28-amino-acid stretch in the mammalian Arc N-terminal (NT) domain that is necessary and sufficient for self-association. Within this region, we identified a 7-residue oligomerization motif, critical for the formation of virus-like capsids. Purified wild-type Arc formed capsids as shown by transmission and cryo-electron microscopy, whereas mutant Arc with disruption of the oligomerization motif formed homogenous dimers. An atomic-resolution crystal structure of the oligomerization region peptide demonstrated an antiparallel coiled-coil interface, strongly supporting NT-NT domain interactions in Arc oligomerization. The NT coil-coil interaction was also validated in live neurons using fluorescence lifetime FRET imaging, and mutation of the oligomerization motif disrupted Arc-facilitated endocytosis. Furthermore, using single-molecule photobleaching, we show that Arc mRNA greatly enhances higher-order oligomerization in a manner dependent on the oligomerization motif. In conclusion, a helical coil in the Arc NT domain supports self-association above the dimer stage, mRNA-induced oligomerization, and formation of virus-like capsids. DATABASE: The coordinates and structure factors for crystallographic analysis of the oligomerization region were deposited at the Protein Data Bank with the entry code 6YTU.

Validation of electron microscopy initial models via small angle X-ray scattering curves

MOTIVATION

Cryo electron microscopy (EM) is currently one of the main tools to reveal the structural information of biological macromolecules. The re-construction of three-dimensional (3D) maps is typically carried out following an iterative process that requires an initial estimation of the 3D map to be refined in subsequent steps. Therefore, its determination is key in the quality of the final results, and there are cases in which it is still an open issue in single particle analysis (SPA). Small angle X-ray scattering (SAXS) is a well-known technique applied to structural biology. It is useful from small nanostructures up to macromolecular ensembles for its ability to obtain low resolution information of the biological sample measuring its X-ray scattering curve. These curves, together with further analysis, are able to yield information on the sizes, shapes and structures of the analyzed particles.

RESULTS

In this paper, we show how the low resolution structural information revealed by SAXS is very useful for the validation of EM initial 3D models in SPA, helping the following refinement process to obtain more accurate 3D structures. For this purpose, we approximate the initial map by pseudo-atoms and predict the SAXS curve expected for this pseudo-atomic structure. The match between the predicted and experimental SAXS curves is considered as a good sign of the correctness of the EM initial map.

AVAILABILITY AND IMPLEMENTATION

The algorithm is freely available as part of the Scipion 1.2 software at http://scipion.i2pc.es/.

The Envelope-Based Fusion Antigen GP120C14K Forming Hexamer-Like Structures Triggers T Cell and Neutralizing Antibody Responses Against HIV-1

There is an urgent need for the development of potent vaccination regimens that are able to induce specific T and B cell responses against human immunodeficiency virus type 1 (HIV-1). Here, we describe the generation and characterization of a fusion antigen comprised of the HIV-1 envelope GP120 glycoprotein from clade C (GP120C) fused at its C-terminus, with the modified vaccinia virus (VACV) 14K protein (A27L gene) (termed GP120C14K). The design is directed toward improving the immunogenicity of the GP120C protein through its oligomerization facilitated by the fused VACV 14K protein that results in hexamer-like structures. Two different immunogens were generated: a recombinant GP120C14K fusion protein (purified from a stable CHO-K1 cell line) and a recombinant modified vaccinia virus Ankara (MVA) poxvirus vector expressing the GP120C14K fusion protein (termed MVA-GP120C14K). The GP120C14K fusion protein is recognized by broadly neutralizing antibodies (bNAbs) against HIV-1. In a murine model, a heterologous prime/boost immunization regimen with MVA-GP120C14K prime followed by adjuvanted GP120C14K protein boost generated stronger and polyfunctional HIV-1 Env-specific CD8 T cell responses when compared with the delivery of the monomeric GP120C form. Furthermore, the immunization protocol MVA-GP120C14K/GP120C14K elicited higher HIV-1 Env-specific T follicular helper cells, germinal center B cells and antibody responses than monomeric GP120. In addition, a similar MVA-GP120C14K prime/GP120C14K protein boost regimen performed in rabbits triggered high HIV-1-Env-specific IgG binding antibody titers that were capable of neutralizing HIV-1 pseudoviruses. The extent of HIV-1 neutralization was comparable to that elicited by the current standard GP140 SOSIP trimers from clades B and C when immunized as MVA-SOSIP prime/SOSIP protein boost regimen. Overall, the novel fusion antigen and the corresponding immunization scheme provided in this report can therefore be considered as potential vaccine strategies against HIV-1.

Role of Era in assembly and homeostasis of the ribosomal small subunit

Assembly factors provide speed and directionality to the maturation process of the 30S subunit in bacteria. To gain a more precise understanding of how these proteins mediate 30S maturation, it is important to expand on studies of 30S assembly intermediates purified from bacterial strains lacking particular maturation factors. To reveal the role of the essential protein Era in the assembly of the 30S ribosomal subunit, we analyzed assembly intermediates that accumulated in Era-depleted Escherichia coli cells using quantitative mass spectrometry, high resolution cryo-electron microscopy and in-cell footprinting. Our combined approach allowed for visualization of the small subunit as it assembled and revealed that with the exception of key helices in the platform domain, all other 16S rRNA domains fold even in the absence of Era. Notably, the maturing particles did not stall while waiting for the platform domain to mature and instead re-routed their folding pathway to enable concerted maturation of other structural motifs spanning multiple rRNA domains. We also found that binding of Era to the mature 30S subunit destabilized helix 44 and the decoding center preventing binding of YjeQ, another assembly factor. This work establishes Era’s role in ribosome assembly and suggests new roles in maintaining ribosome homeostasis.

Hybrid Electron Microscopy Normal Mode Analysis with Scipion

Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) method was introduced in 2014. HEMNMA computes normal modes of a reference model (an atomic structure or an electron microscopy map) of a molecular complex and uses this model and its normal modes to analyze single-particle images of the complex to obtain information on its continuous conformational changes, by determining the full distribution of conformational variability from the images. An advantage of HEMNMA is a simultaneous determination of all parameters of each image (particle conformation, orientation, and shift) through their iterative optimization, which allows applications of HEMNMA even when the effects of conformational changes dominate those of orientational changes. HEMNMA was first implemented in Xmipp and was using MATLAB for statistical analysis of obtained conformational distributions and for fitting of underlying trajectories of conformational changes. A HEMNMA implementation independent of MATLAB is now available as part of a plugin of Scipion V2.0 (http://scipion.i2pc.es). This plugin, named ContinuousFlex, can be installed by following the instructions at https://pypi.org/project/scipion-em-continuousflex. In this article, we present this new HEMNMA software, which is user-friendly, totally free, and open-source. STATEMENT FOR A BROADER AUDIENCE: This article presents Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) software that allows analyzing single-particle images of a complex to obtain information on continuous conformational changes of the complex, by determining the full distribution of conformational variability from the images. The HEMNMA software is user-friendly, totally free, open-source, and available as part of ContinuousFlex plugin (https://pypi.org/project/scipion-em-continuousflex) of Scipion V2.0 (http://scipion.i2pc.es).

Flexible workflows for on-the-fly electron-microscopy single-particle image processing using Scipion

Electron microscopy of macromolecular structures is an approach that is in increasing demand in the field of structural biology. The automation of image acquisition has greatly increased the potential throughput of electron microscopy. Here, the focus is on the possibilities in Scipion to implement flexible and robust image-processing workflows that allow the electron-microscope operator and the user to monitor the quality of image acquisition, assessing very simple acquisition measures or obtaining a first estimate of the initial volume, or the data resolution and heterogeneity, without any need for programming skills. These workflows can implement intelligent automatic decisions and they can warn the user of possible acquisition failures. These concepts are illustrated by analysis of the well known 2.2 Å resolution β-galactosidase data set.

A robust approach to ab initio cryo-electron microscopy initial volume determination

Structural information from macromolecules provides key insights into the way complexes perform their biological functions. The reconstruction process leading to the final three-dimensional (3D) map is iterative and requires an initial volume to prime the refinement procedure. Particle images are aligned to this first reference and subsequently a new map is calculated from these particles. The accurate determination of an ab initio initial volume is still a challenging and open problem in cryo-electron microscopy (cryo-EM). Different algorithms are available to estimate an initial volume from the dataset. Some of these methods provide multiple candidate initial maps and users looking for robustness typically run different approaches. In this case, users arbitrarily evaluate the different obtained candidate maps, as we lack robust methods to objectively assess the accuracy of initial references. This workflow is subjective and error-prone preventing implementation of high-throughput data processing procedures. In this work, we present a robust method to determine the best initial map or maps from a set of ab initio initial volumes obtained from one or multiple different approaches. The method is based on evaluating multiple small subsets of candidate initial volumes and particle images through reference-based 3D classifications. Obtained 3D classes of accurate initial maps will result majoritarian and the respective attracted particles will be aligned with high angular accuracies. We have tested the proposed approach with structurally homogeneous and heterogeneous datasets providing satisfactory results with both type of data.

Structural and functional analysis of the role of the chaperonin CCT in mTOR complex assembly

The mechanistic target of rapamycin (mTOR) kinase forms two multi-protein signaling complexes, mTORC1 and mTORC2, which are master regulators of cell growth, metabolism, survival and autophagy. Two of the subunits of these complexes are mLST8 and Raptor, β-propeller proteins that stabilize the mTOR kinase and recruit substrates, respectively. Here we report that the eukaryotic chaperonin CCT plays a key role in mTORC assembly and signaling by folding both mLST8 and Raptor. A high resolution (4.0 Å) cryo-EM structure of the human mLST8-CCT intermediate isolated directly from cells shows mLST8 in a near-native state bound to CCT deep within the folding chamber between the two CCT rings, and interacting mainly with the disordered N- and C-termini of specific CCT subunits of both rings. These findings describe a unique function of CCT in mTORC assembly and a distinct binding site in CCT for mLST8, far from those found for similar β-propeller proteins.

β-propeller domains are an important class of folding substrates for the eukaryotic cytosolic chaperonin CTT. Here the authors find that CTT contributes to the folding and assembly of two β-propeller proteins from mTOR complexes, mLST8 and Raptor, and determine the 4.0 Å cryoEM structure of a human mLST8-CCT intermediate that shows mLST8 in a near-native state.

Advances in image processing for single-particle analysis by electron cryomicroscopy and challenges ahead

Electron cryomicroscopy (cryoEM) is essential for the study and functional understanding of non-crystalline macromolecules such as proteins. These molecules cannot be imaged using X-ray crystallography or other popular methods. CryoEM has been successfully used to visualize macromolecular complexes such as ribosomes, viruses, and ion channels. Determination of structural models of these at various conformational states leads to insight on how these molecules function. Recent advances in imaging technology have given cryoEM a scientific rebirth. As a result of these technological advances image processing and analysis have yielded molecular structures at atomic resolution. Nevertheless there continue to be challenges in image processing, and in this article we will touch on the most essential in order to derive an accurate three-dimensional model from noisy projection images. Traditional approaches, such as k-means clustering for class averaging, will be provided as background. We will then highlight new approaches for each image processing subproblem, including a 3D reconstruction method for asymmetric molecules using just two projection images and deep learning algorithms for automated particle picking.

Likelihood-based structural analysis of electron microscopy images

Likelihood-based analysis of single-particle electron microscopy images has contributed much to the recent improvements in resolution. By treating particle orientations and classes probabilistically, uncertainties in the reconstruction process are explicitly accounted for, and the risk of bias towards the initial model is diminished. As a result, the quality and reliability of the reconstructions have greatly improved at manageable computational cost. Likelihood-based analysis of electron microscopy images also offers a route to direct coordinate refinement for dynamic systems, as an alternative to 3D density reconstruction. Here, we review recent developments in the algorithms used for reconstructions of high-resolution maps, and in the integrative framework of combining likelihood methods with simulations to address conformational variability in cryo-electron microscopy.

Cryo-EM reconstruction of Type VI secretion system baseplate and sheath distal end

The bacterial Type VI secretion system (T6SS) assembles from three major parts: a membrane complex that spans inner and outer membranes, a baseplate, and a sheath-tube polymer. The baseplate assembles around a tip complex with associated effectors and connects to the membrane complex by TssK. The baseplate assembly initiates sheath-tube polymerization, which in some organisms requires TssA. Here, we analyzed both ends of isolated non-contractile Vibrio cholerae sheaths by cryo-electron microscopy. Our analysis suggests that the baseplate, solved to an average 8.0 Å resolution, is composed of six subunits of TssE/F₂/G and the baseplate periphery is decorated by six TssK trimers. The VgrG/PAAR tip complex in the center of the baseplate is surrounded by a cavity, which may accommodate up to ~450 kDa of effector proteins. The distal end of the sheath, resolved to an average 7.5 Å resolution, shows sixfold symmetry; however, its protein composition is unclear. Our structures provide an important step toward an atomic model of the complete T6SS assembly.

Scipion web tools: Easy to use cryo-EM image processing over the web

Macromolecular structural determination by Electron Microscopy under cryogenic conditions is revolutionizing the field of structural biology, interesting a large community of potential users. Still, the path from raw images to density maps is complex, and sophisticated image processing suites are required in this process, often demanding the installation and understanding of different software packages. Here, we present Scipion Web Tools, a web-based set of tools/workflows derived from the Scipion image processing framework, specially tailored to nonexpert users in need of very precise answers at several key stages of the structural elucidation process.

A general mechanism of ribosome dimerization revealed by single-particle cryo-electron microscopy

Bacteria downregulate their ribosomal activity through dimerization of 70S ribosomes, yielding inactive 100S complexes. In Escherichia coli, dimerization is mediated by the hibernation promotion factor (HPF) and ribosome modulation factor. Here we report the cryo-electron microscopy study on 100S ribosomes from Lactococcus lactis and a dimerization mechanism involving a single protein: HPF^long. The N-terminal domain of HPF^long binds at the same site as HPF in Escherichia coli 100S ribosomes. Contrary to ribosome modulation factor, the C-terminal domain of HPF^long binds exactly at the dimer interface. Furthermore, ribosomes from Lactococcus lactis do not undergo conformational changes in the 30S head domains upon binding of HPF^long, and the Shine–Dalgarno sequence and mRNA entrance tunnel remain accessible. Ribosome activity is blocked by HPF^long due to the inhibition of mRNA recognition by the platform binding center. Phylogenetic analysis of HPF proteins suggests that HPF^long-mediated dimerization is a widespread mechanism of ribosome hibernation in bacteria.

When bacteria enter the stationary growth phase, protein translation is suppressed via the dimerization of 70S ribosomes into inactive complexes. Here the authors provide a structural basis for how the dual domain hibernation promotion factor promotes ribosome dimerization and hibernation in bacteria.

Pea PSII-LHCII supercomplexes form pairs by making connections across the stromal gap

In higher plant thylakoids, the heterogeneous distribution of photosynthetic protein complexes is a determinant for the formation of grana, stacks of membrane discs that are densely populated with Photosystem II (PSII) and its light harvesting complex (LHCII). PSII associates with LHCII to form the PSII-LHCII supercomplex, a crucial component for solar energy conversion. Here, we report a biochemical, structural and functional characterization of pairs of PSII-LHCII supercomplexes, which were isolated under physiologically-relevant cation concentrations. Using single-particle cryo-electron microscopy, we determined the three-dimensional structure of paired C2S2M PSII-LHCII supercomplexes at 14 Å resolution. The two supercomplexes interact on their stromal sides through a specific overlap between apposing LHCII trimers and via physical connections that span the stromal gap, one of which is likely formed by interactions between the N-terminal loops of two Lhcb4 monomeric LHCII subunits. Fast chlorophyll fluorescence induction analysis showed that paired PSII-LHCII supercomplexes are energetically coupled. Molecular dynamics simulations revealed that additional flexible physical connections may form between the apposing LHCII trimers of paired PSII-LHCII supercomplexes in appressed thylakoid membranes. Our findings provide new insights into how interactions between pairs of PSII-LHCII supercomplexes can link adjacent thylakoids to mediate the stacking of grana membranes.

Quantitative analysis of 3D alignment quality: its impact on soft-validation, particle pruning and homogeneity analysis

Single Particle Analysis using cryo-electron microscopy is a structural biology technique aimed at capturing the three-dimensional (3D) conformation of biological macromolecules. Projection images used to construct the 3D density map are characterized by a very low signal-to-noise ratio to minimize radiation damage in the samples. As a consequence, the 3D image alignment process is a challenging and error prone task which usually determines the success or failure of obtaining a high quality map. In this work, we present an approach able to quantify the alignment precision and accuracy of the 3D alignment process, which is then being used to help the reconstruction process in a number of ways, such as: (1) Providing quality indicators of the macromolecular map for soft validation, (2) Assessing the degree of homogeneity of the sample and, (3), Selecting subsets of representative images. We present experimental results in which the quality of the finally obtained 3D maps is clearly improved.

Three-dimensional reconstruction for coherent diffraction patterns obtained by XFEL

The three-dimensional (3D) structural analysis of single particles using an X-ray free-electron laser (XFEL) is a new structural biology technique that enables observations of molecules that are difficult to crystallize, such as flexible biomolecular complexes and living tissue in the state close to physiological conditions. In order to restore the 3D structure from the diffraction patterns obtained by the XFEL, computational algorithms are necessary as the orientation of the incident beam with respect to the sample needs to be estimated. A program package for XFEL single-particle analysis based on the Xmipp software package, that is commonly used for image processing in 3D cryo-electron microscopy, has been developed. The reconstruction program has been tested using diffraction patterns of an aerosol nanoparticle obtained by tomographic coherent X-ray diffraction microscopy.

Subunit and chlorophyll organization of the plant photosystem II supercomplex

Photosystem II (PSII) is a light-driven protein, involved in the primary reactions of photosynthesis. In plant photosynthetic membranes PSII forms large multisubunit supercomplexes, containing a dimeric core and up to four light-harvesting complexes (LHCs), which act as antenna proteins. Here we solved a three-dimensional (3D) structure of the C₂S₂M₂ supercomplex from Arabidopsis thaliana using cryo-transmission electron microscopy (cryo-EM) and single-particle analysis at an overall resolution of 5.3 Å. Using a combination of homology modelling and restrained refinement against the cryo-EM map, it was possible to model atomic structures for all antenna complexes and almost all core subunits. We located all 35 chlorophylls of the core region based on the cyanobacterial PSII structure, whose positioning is highly conserved, as well as all the chlorophylls of the LHCII S and M trimers. A total of 13 and 9 chlorophylls were identified in CP26 and CP24, respectively. Energy flow from LHC complexes to the PSII reaction centre is proposed to follow preferential pathways: CP26 and CP29 directly transfer to the core using several routes for efficient transfer; the S trimer is directly connected to CP43 and the M trimer can efficiently transfer energy to the core through CP29 and the S trimer.

Single-particle electron microscopy structure of UDP-glucose:glycoprotein glucosyltransferase suggests a selectivity mechanism for misfolded proteins

The enzyme UDP-glucose:glycoprotein glucosyltransferase (UGGT) mediates quality control of glycoproteins in the endoplasmic reticulum by attaching glucose to N-linked glycan of misfolded proteins. As a sensor, UGGT ensures that misfolded proteins are recognized by the lectin chaperones and do not leave the secretory pathway. The structure of UGGT and the mechanism of its selectivity for misfolded proteins have been unknown for 25 years. Here, we used negative-stain electron microscopy and small-angle X-ray scattering to determine the structure of UGGT from Drosophila melanogaster at 18-Å resolution. Three-dimensional reconstructions revealed a cage-like structure with a large central cavity. Particle classification revealed flexibility that precluded determination of a high-resolution structure. Introduction of biotinylation sites into a fungal UGGT expressed in Escherichia coli allowed identification of the catalytic and first thioredoxin-like domains. We also used hydrogen-deuterium exchange mass spectrometry to map the binding site of an accessory protein, Sep15, to the first thioredoxin-like domain. The UGGT structural features identified suggest that the central cavity contains the catalytic site and is lined with hydrophobic surfaces. This enhances the binding of misfolded substrates with exposed hydrophobic residues and excludes folded proteins with hydrophilic surfaces. In conclusion, we have determined the UGGT structure, which enabled us to develop a plausible functional model of the mechanism for UGGT's selectivity for misfolded glycoproteins.

Electron Microscopy Structural Insights into CPAP Oligomeric Behavior: A Plausible Assembly Process of a Supramolecular Scaffold of the Centrosome

Centrosomal P4.1-associated protein (CPAP) is a cell cycle regulated protein fundamental for centrosome assembly and centriole elongation. In humans, the region between residues 897–1338 of CPAP mediates interactions with other proteins and includes a homodimerization domain. CPAP mutations cause primary autosomal recessive microcephaly and Seckel syndrome. Despite of the biological/clinical relevance of CPAP, its mechanistic behavior remains unclear and its C-terminus (the G-box/TCP domain) is the only part whose structure has been solved. This situation is perhaps due in part to the challenges that represent obtaining the protein in a soluble, homogeneous state for structural studies. Our work constitutes a systematic structural analysis on multiple oligomers of HsCPAP^897−1338, using single-particle electron microscopy (EM) of negatively stained (NS) samples. Based on image classification into clearly different regular 3D maps (putatively corresponding to dimers and tetramers) and direct observation of individual images representing other complexes of HsCPAP^897−1338 (i.e., putative flexible monomers and higher-order multimers), we report a dynamic oligomeric behavior of this protein, where different homo-oligomers coexist in variable proportions. We propose that dimerization of the putative homodimer forms a putative tetramer which could be the structural unit for the scaffold that either tethers the pericentriolar material to centrioles or promotes procentriole elongation. A coarse fitting of atomic models into the NS 3D maps at resolutions around 20 Å is performed only to complement our experimental data, allowing us to hypothesize on the oligomeric composition of the different complexes. In this way, the current EM work represents an initial step toward the structural characterization of different oligomers of CPAP, suggesting further insights to understand how this protein works, contributing to the elucidation of control mechanisms for centriole biogenesis.

Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.

Designed proteins induce the formation of nanocage-containing extracellular vesicles

Complex biological processes are often performed by self-organizing nanostructures comprising multiple classes of macromolecules, such as ribosomes (proteins and RNA) or enveloped viruses (proteins, nucleic acids and lipids). Approaches have been developed for designing self-assembling structures consisting of either nucleic acids or proteins, but strategies for engineering hybrid biological materials are only beginning to emerge. Here we describe the design of self-assembling protein nanocages that direct their own release from human cells inside small vesicles in a manner that resembles some viruses. We refer to these hybrid biomaterials as 'enveloped protein nanocages' (EPNs). Robust EPN biogenesis requires protein sequence elements that encode three distinct functions: membrane binding, self-assembly, and recruitment of the endosomal sorting complexes required for transport (ESCRT) machinery. A variety of synthetic proteins with these functional elements induce EPN biogenesis, highlighting the modularity and generality of the design strategy. Biochemical analyses and cryo-electron microscopy reveal that one design, EPN-01, comprises small (~100 nm) vesicles containing multiple protein nanocages that closely match the structure of the designed 60-subunit self-assembling scaffold. EPNs that incorporate the vesicular stomatitis viral glycoprotein can fuse with target cells and deliver their contents, thereby transferring cargoes from one cell to another. These results show how proteins can be programmed to direct the formation of hybrid biological materials that perform complex tasks, and establish EPNs as a class of designed, modular, genetically-encoded nanomaterials that can transfer molecules between cells.

Foil-hole and data image quality assessment in 3DEM: Towards high-throughput image acquisition in the electron microscope

Automatic or semiautomatic data collection approaches on a transmission electron microscope (TEM) for Single Particle Analysis, capable of acquiring large datasets composed of only high quality images, are of great importance to obtain 3D density maps with the highest resolution possible. Typically, this task is performed by an experienced microscopist, who manually decides to keep or discard images according to subjective criteria. Therefore, this methodology is slow, intensive in human work and subjective. In this work, we propose a method to automatically or semiautomatically perform this image selection task. The approach is based on some simple, fast and effective image quality descriptors, which can be computed during acquisition, to characterize foil-hole and data images. The proposed approach has been used to evaluate the quality of different datasets consisting of foil-hole and data images obtained with a FEI Titan Krios electron microscope. The results show that the proposed method is very effective evaluating the quality of foil-hole and data images, as well as predicting the quality of the data images from the foil-hole images.

Structure of AP205 Coat Protein Reveals Circular Permutation in ssRNA Bacteriophages

AP205 is a single-stranded RNA bacteriophage that has a coat protein sequence not similar to any other known single-stranded RNA phage. Here, we report an atomic-resolution model of the AP205 virus-like particle based on a crystal structure of an unassembled coat protein dimer and a cryo-electron microscopy reconstruction of the assembled particle, together with secondary structure information from site-specific solid-state NMR data. The AP205 coat protein dimer adopts the conserved Leviviridae coat protein fold except for the N-terminal region, which forms a beta-hairpin in the other known single-stranded RNA phages. AP205 has a similar structure at the same location formed by N- and C-terminal beta-strands, making it a circular permutant compared to the other coat proteins. The permutation moves the coat protein termini to the most surface-exposed part of the assembled particle, which explains its increased tolerance to long N- and C-terminal fusions.

A Stochastic Hill Climbing Approach for Simultaneous 2D Alignment and Clustering of Cryogenic Electron Microscopy Images

A critical step in the analysis of novel cryogenic electron microscopy (cryo-EM) single-particle datasets is the identification of homogeneous subsets of images. Methods for solving this problem are important for data quality assessment, ab initio 3D reconstruction, and analysis of population diversity due to the heterogeneous nature of macromolecules. Here we formulate a stochastic algorithm for identification of homogeneous subsets of images. The purpose of the method is to generate improved 2D class averages that can be used to produce a reliable 3D starting model in a rapid and unbiased fashion. We show that our method overcomes inherent limitations of widely used clustering approaches and proceed to test the approach on six publicly available experimental cryo-EM datasets. We conclude that, in each instance, ab initio 3D reconstructions of quality suitable for initialization of high-resolution refinement are produced from the cluster centers.

Particle alignment reliability in single particle electron cryomicroscopy: a general approach

Electron Microscopy is reaching new capabilities thanks to the combined effect of new technologies and new image processing methods. However, the reconstruction process is still complex, requiring many steps and elaborated optimization procedures. Therefore, the possibility to reach a wrong structure exists, justifying the need of robust statistical tests. In this work, we present a conceptually simple alignment test, which does not require tilt-pair images, to evaluate the alignment consistency between a set of projection images with respect to a given 3D density map. We test the approach on a number of problems in 3DEM, especially the ranking and evaluation of initial 3D volumes and high resolution 3D maps, where we show its usefulness in providing an objective evaluation for maps that have recently been subject to a strong controversy in the field. Additionally, this alignment statistical test can be linked to the early stages of structure solving of new complexes, streamlining the whole process.

Bayesian inference of initial models in cryo-electron microscopy using pseudo-atoms

Single-particle cryo-electron microscopy is widely used to study the structure of macromolecular assemblies. Tens of thousands of noisy two-dimensional images of the macromolecular assembly viewed from different directions are used to infer its three-dimensional structure. The first step is to estimate a low-resolution initial model and initial image orientations. This is a challenging global optimization problem with many unknowns, including an unknown orientation for each two-dimensional image. Obtaining a good initial model is crucial for the success of the subsequent refinement step. We introduce a probabilistic algorithm for estimating an initial model. The algorithm is fast, has very few algorithmic parameters, and yields information about the precision of estimated model parameters in addition to the parameters themselves. Our algorithm uses a pseudo-atomic model to represent the low-resolution three-dimensional structure, with isotropic Gaussian components as moveable pseudo-atoms. This leads to a significant reduction in the number of parameters needed to represent the three-dimensional structure, and a simplified way of computing two-dimensional projections. It also contributes to the speed of the algorithm. We combine the estimation of the unknown three-dimensional structure and image orientations in a Bayesian framework. This ensures that there are very few parameters to set, and specifies how to combine different types of prior information about the structure with the given data in a systematic way. To estimate the model parameters we use Markov chain Monte Carlo sampling. The advantage is that instead of just obtaining point estimates of model parameters, we obtain an ensemble of models revealing the precision of the estimated parameters. We demonstrate the algorithm on both simulated and real data.

Electron Microscopy and Image Processing: Essential Tools for Structural Analysis of Macromolecules

Macromolecular electron microscopy typically depicts the structures of macromolecular complexes ranging from ∼200 kDa to hundreds of MDa. The amount of specimen required, a few micrograms, is typically 100 to 1000 times less than needed for X-ray crystallography or nuclear magnetic resonance spectroscopy. Micrographs of frozen-hydrated (cryogenic) specimens portray native structures, but the original images are noisy. Computational averaging reduces noise, and three-dimensional reconstructions are calculated by combining different views of free-standing particles ("single-particle analysis"). Electron crystallography is used to characterize two-dimensional arrays of membrane proteins and very small three-dimensional crystals. Under favorable circumstances, near-atomic resolutions are achieved. For structures at somewhat lower resolution, pseudo-atomic models are obtained by fitting high-resolution components into the density. Time-resolved experiments describe dynamic processes. Electron tomography allows reconstruction of pleiomorphic complexes and subcellular structures and modeling of macromolecules in their cellular context. Significant information is also obtained from metal-coated and dehydrated specimens.