SIMPLE: Software for ab initio reconstruction of heterogeneous single-particles

Deep generative priors for biomolecular 3D heterogeneous reconstruction from cryo-EM projections

Cryo-electron microscopy has become a powerful tool to determine three-dimensional (3D) structures of rigid biological macromolecules from noisy micrographs with single-particle reconstruction. Recently, deep neural networks, e.g., CryoDRGN, have demonstrated conformational and compositional heterogeneity of complexes. However, the lack of ground-truth conformations poses a challenge to assess the performance of heterogeneity analysis methods. In this work, variational autoencoders (VAE) with three types of deep generative priors were learned for latent variable inference and heterogeneous 3D reconstruction via Bayesian inference. More specifically, VAEs with "Variational Mixture of Posteriors" priors (VampPrior-SPR), non-parametric exemplar-based priors (ExemplarPrior-SPR) and priors from latent score-based generative models (LSGM-SPR) were quantitatively compared with CryoDRGN. We built four simulated datasets composed of hypothetical continuous conformation or discrete states of the hERG K + channel. Empirical and quantitative comparisons of inferred latent representations were performed with affine-transformation-based metrics. These models with more informative priors gave better regularized, interpretable factorized latent representations with better conserved pairwise distances, less deformed latent distributions and lower within-cluster variances. They were also tested on experimental datasets to resolve compositional and conformational heterogeneity (50S ribosome assembly, cowpea chlorotic mottle virus, and pre-catalytic spliceosome) with comparable high resolution. Codes and data are available: https://github.com/benjamin3344/DGP-SPR.

A robust normalized local filter to estimate compositional heterogeneity directly from cryo-EM maps

Cryo electron microscopy (cryo-EM) is used by biological research to visualize biomolecular complexes in 3D, but the heterogeneity of cryo-EM reconstructions is not easily estimated. Current processing paradigms nevertheless exert great effort to reduce flexibility and heterogeneity to improve the quality of the reconstruction. Clustering algorithms are typically employed to identify populations of data with reduced variability, but lack assessment of remaining heterogeneity. Here we develope a fast and simple algorithm based on spatial filtering to estimate the heterogeneity of a reconstruction. In the absence of flexibility, this estimate approximates macromolecular component occupancy. We show that our implementation can derive reasonable input parameters, that composition heterogeneity can be estimated based on contrast loss, and that the reconstruction can be modified accordingly to emulate altered constituent occupancy. This stands to benefit conventionally employed maximum-likelihood classification methods, whereas we here limit considerations to cryo-EM map interpretation, quantification, and particle-image signal subtraction.

Advances in computational approaches to structure determination of alphaviruses and flaviviruses using cryo-electron microscopy

Advancements in the field of cryo-electron microscopy (cryo-EM) have greatly contributed to our current understanding of virus structures and life cycles. In this review, we discuss the application of single particle cryo-electron microscopy (EM) for the structure elucidation of small enveloped icosahedral viruses, namely, alpha- and flaviviruses. We focus on technical advances in cryo-EM data collection, image processing, three-dimensional reconstruction, and refinement strategies for obtaining high-resolution structures of these viruses. Each of these developments enabled new insights into the alpha- and flavivirus architecture, leading to a better understanding of their biology, pathogenesis, immune response, immunogen design, and therapeutic development.

Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy

Single particle cryo-electron microscopy (cryo-EM) has emerged as the prevailing method for near-atomic structure determination, shedding light on the important molecular mechanisms of biological macromolecules. However, the inherent dynamics and structural variability of biological complexes coupled with the large number of experimental images generated by a cryo-EM experiment make data processing nontrivial. In particular, ab initio reconstruction and atomic model building remain major bottlenecks that demand substantial computational resources and manual intervention. Approaches utilizing recent innovations in artificial intelligence (AI) technology, particularly deep learning, have the potential to overcome the limitations that cannot be adequately addressed by traditional image processing approaches. Here, we review newly proposed AI-based methods for ab initio volume generation, heterogeneous 3D reconstruction, and atomic model building. We highlight the advancements made by the implementation of AI methods, as well as discuss remaining limitations and areas for future development.

Accurate real space iterative reconstruction (RESIRE) algorithm for tomography

Tomography has made a revolutionary impact on the physical, biological and medical sciences. The mathematical foundation of tomography is to reconstruct a three-dimensional (3D) object from a set of two-dimensional (2D) projections. As the number of projections that can be measured from a sample is usually limited by the tolerable radiation dose and/or the geometric constraint on the tilt range, a main challenge in tomography is to achieve the best possible 3D reconstruction from a limited number of projections with noise. Over the years, a number of tomographic reconstruction methods have been developed including direct inversion, real-space, and Fourier-based iterative algorithms. Here, we report the development of a real-space iterative reconstruction (RESIRE) algorithm for accurate tomographic reconstruction. RESIRE iterates between the update of a reconstructed 3D object and the measured projections using a forward and back projection step. The forward projection step is implemented by the Fourier slice theorem or the Radon transform, and the back projection step by a linear transformation. Our numerical and experimental results demonstrate that RESIRE performs more accurate 3D reconstructions than other existing tomographic algorithms, when there are a limited number of projections with noise. Furthermore, RESIRE can be used to reconstruct the 3D structure of extended objects as demonstrated by the determination of the 3D atomic structure of an amorphous Ta thin film. We expect that RESIRE can be widely employed in the tomography applications in different fields. Finally, to make the method accessible to the general user community, the MATLAB source code of RESIRE and all the simulated and experimental data are available at  https://zenodo.org/record/7273314 .

Cryo-EM-based structural insights into supramolecular assemblies of γ-hemolysin from S. aureus reveal the pore formation mechanism

γ-Hemolysin (γ-HL) is a hemolytic and leukotoxic bicomponent β-pore-forming toxin (β-PFT), a potent virulence factor from the Staphylococcus aureus Newman strain. In this study, we performed single-particle cryoelectron microscopy (cryo-EM) of γ-HL in a lipid environment. We observed clustering and square lattice packing of octameric HlgAB pores on the membrane bilayer and an octahedral superassembly of octameric pore complexes that we resolved at resolution of 3.5 Å. Our atomic model further demonstrated the key residues involved in hydrophobic zipping between the rim domains of adjacent octameric complexes, providing additional structural stability in PFTs post oligomerization. We also observed extra densities at the octahedral and octameric interfaces, providing insights into the plausible lipid-binding residues involved for HlgA and HlgB components. Furthermore, the hitherto elusive N-terminal region of HlgA was also resolved in our cryo-EM map, and an overall mechanism of pore formation for bicomponent β-PFTs is proposed.

Cryo-EM reveals the membrane-binding phenomenon of EspB, a virulence factor of the Mycobacterial Type VII secretion system

Mycobacterium tuberculosis (Mtb) utilizes sophisticated machinery called the type VII secretion system to translocate virulence factors across its complex lipid membrane. EspB, a ∼36 kDa secreted substrate of the ESX-1 apparatus, was shown to cause ESAT-6-independent host cell death. Despite the current wealth of high-resolution structural information of the ordered N-terminal domain, the mechanism of EspB-mediated virulence remains poorly characterized. Here we document EspB interaction with phosphatidic acid (PA) and phosphatidylserine (PS) in the context of membranes, through a biophysical approach including TEM and cryo-EM. We were also able to show PA, PS-dependent conversion of monomers to oligomers at physiological pH. Our data suggest that EspB adheres to biological membranes with limited PA and PS. Electron microscopy of yeast mitochondria with EspB indicates a mitochondrial-membrane binding property of this ESX-1 substrate. Further, we determined the 3D structures of EspB with and without PA and observed plausible stabilization of the low complexity C-terminal domain in the presence of PA. Collectively, our cryo-EM-based structural and functional studies of EspB provide further insight into the host-Mtb interaction.

Neutralizing Efficacy of Encapsulin Nanoparticles against SARS-CoV2 Variants of Concern

Rapid emergence of the SARS-CoV-2 variants has dampened the protective efficacy of existing authorized vaccines. Nanoparticle platforms offer a means to improve vaccine immunogenicity by presenting multiple copies of desired antigens in a repetitive manner which closely mimics natural infection. We have applied nanoparticle display combined with the SpyTag-SpyCatcher system to design encapsulin-mRBD, a nanoparticle vaccine displaying 180 copies of the monomeric SARS-CoV-2 spike receptor-binding domain (RBD). Here we show that encapsulin-mRBD is strongly antigenic and thermotolerant for long durations. After two immunizations, squalene-in-water emulsion (SWE)-adjuvanted encapsulin-mRBD in mice induces potent and comparable neutralizing antibody titers of 105 against wild-type (B.1), alpha, beta, and delta variants of concern. Sera also neutralizes the recent Omicron with appreciable neutralization titers, and significant neutralization is observed even after a single immunization.

Structure of the malaria vaccine candidate Pfs48/45 and its recognition by transmission blocking antibodies

An effective malaria vaccine remains a global health priority and vaccine immunogens which prevent transmission of the parasite will have important roles in multi-component vaccines. One of the most promising candidates for inclusion in a transmission-blocking malaria vaccine is the gamete surface protein Pfs48/45, which is essential for development of the parasite in the mosquito midgut. Indeed, antibodies which bind Pfs48/45 can prevent transmission if ingested with the parasite as part of the mosquito bloodmeal. Here we present the structure of full-length Pfs48/45, showing its three domains to form a dynamic, planar, triangular arrangement. We reveal where transmission-blocking and non-blocking antibodies bind on Pfs48/45. Finally, we demonstrate that antibodies which bind across this molecule can be transmission-blocking. These studies will guide the development of future Pfs48/45-based vaccine immunogens.

Pfs48/45, a surface protein of Plasmodium falciparum, is a promising anti-malarial vaccine candidate whose structure is not entirely resolved. Here, the authors present the structure of the full-length molecule, and characterise the binding and activity of transmission blocking antibodies.

Quantitative mining of compositional heterogeneity in cryo-EM datasets of ribosome assembly intermediates

Single-particle cryoelectron microscopy (cryo-EM) offers a unique opportunity to characterize macromolecular structural heterogeneity by virtue of its ability to place distinct particle populations into different groups through computational classification. However, there is a dearth of tools for surveying the heterogeneity landscape, quantitatively analyzing heterogeneous particle populations after classification, deciding how many unique classes are represented by the data, and accurately cross-comparing reconstructions. Here, we develop a workflow that contains discovery and analysis modules to quantitatively mine cryo-EM data for sets of structures with maximal diversity. This workflow was applied to a dataset of E. coli 50S ribosome assembly intermediates, which are characterized by significant structural heterogeneity. We identified more detailed branchpoints in the assembly process and characterized the interactions of an assembly factor with immature intermediates. While the tools described here were developed for ribosome assembly, they should be broadly applicable to the analysis of other heterogeneous cryo-EM datasets.

3D reconstruction from cryo-EM projection images using two spherical embeddings

Single-particle analysis (SPA) in cryo-electron microscopy has become a powerful tool for determining and studying the macromolecular structure at an atomic level. However, since the SPA problem is a non-convex optimization problem with enormous search space and there is high level of noise in the input images, the existing methods may produce biased or even wrong final models. In this work, to deal with the problem, consistent constraints from the input data are explored in an embedding space, a 3D spherical surface. More specifically, the orientation of a projection image is represented by two intersection points of the normal vector and the local X-axis vector of the projection image on the unit spherical surface. To determine the orientations of the projection images, the global consistency constraints of the relative orientations of all the projection images are satisfied by two spherical embeddings which estimate the normal vectors and the local X-axis vectors of the projection images respectively. Compared to the traditional methods, the proposed method is shown to be able to rectify the initial computation errors and produce a more accurate estimation of the projection angles, which results in a better final model reconstruction from the noisy image data.

A 3D reconstruction method using two spherical embeddings to resolve projection angles of the cryo-EM images is shown to improve the initial model reconstruction for single-particle analysis.

Single-particle cryo-EM reveals conformational variability of the oligomeric VCC β-barrel pore in a lipid bilayer

Vibrio cholerae cytolysin (VCC) is a water-soluble, membrane-damaging, pore-forming toxin (PFT) secreted by pathogenic V. cholerae, which causes eukaryotic cell death by altering the plasma membrane permeability. VCC self-assembles on the cell surface and undergoes a dramatic conformational change from prepore to heptameric pore structure. Over the past few years, several high-resolution structures of detergent-solubilized PFTs have been characterized. However, high-resolution structural characterization of small β-PFTs in a lipid environment is still rare. Therefore, we used single-particle cryo-EM to characterize the structure of the VCC oligomer in large unilamellar vesicles, which is the first atomic-resolution cryo-EM structure of VCC. From our study, we were able to provide the first documented visualization of the rim domain amino acid residues of VCC interacting with lipid membrane. Furthermore, cryo-EM characterization of lipid bilayer–embedded VCC suggests interesting conformational variabilities, especially in the transmembrane channel, which could have a potential impact on the pore architecture and assist us in understanding the pore formation mechanism.

Protective Efficacy of Recombinant Influenza Hemagglutinin Ectodomain Fusions

In current seasonal influenza vaccines, neutralizing antibody titers directed against the hemagglutinin surface protein are the primary correlate of protection. These vaccines are, therefore, quantitated in terms of their hemagglutinin content. Adding other influenza surface proteins, such as neuraminidase and M2e, to current quadrivalent influenza vaccines would likely enhance vaccine efficacy. However, this would come with increased manufacturing complexity and cost. To address this issue, as a proof of principle, we have designed genetic fusions of hemagglutinin ectodomains from H3 and H1 influenza A subtypes. These recombinant H1-H3 hemagglutinin ectodomain fusions could be transiently expressed at high yield in mammalian cell culture using Expi293F suspension cells. Fusions were trimeric, and as stable in solution as their individual trimeric counterparts. Furthermore, the H1-H3 fusion constructs were antigenically intact based on their reactivity with a set of conformation-specific monoclonal antibodies. H1-H3 hemagglutinin ectodomain fusion immunogens, when formulated with the MF59 equivalent adjuvant squalene-in-water emulsion (SWE), induced H1 and H3-specific humoral immune responses equivalent to those induced with an equimolar mixture of individually expressed H1 and H3 ectodomains. Mice immunized with these ectodomain fusions were protected against challenge with heterologous H1N1 (Bel/09) and H3N2 (X-31) mouse-adapted viruses with higher neutralizing antibody titers against the H1N1 virus. Use of such ectodomain-fused immunogens would reduce the number of components in a vaccine formulation and allow for the inclusion of other protective antigens to increase influenza vaccine efficacy.

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.

Tyrosine in the hinge region of the pore-forming motif regulates oligomeric β-barrel pore formation by Vibrio cholerae cytolysin

β-barrel pore-forming toxins perforate cell membranes by forming oligomeric β-barrel pores. The most crucial step is the membrane-insertion of the pore-forming motifs that create the transmembrane β-barrel scaffold. Molecular mechanism that regulates structural reorganization of these pore-forming motifs during β-barrel pore-formation still remains elusive. Using Vibrio cholerae cytolysin as an archetypical example of the β-barrel pore-forming toxin, we show that a key tyrosine residue (Y321) in the hinge region of the pore-forming motif plays crucial role in this process. Mutation of Y321 abrogates oligomerization of the membrane-bound toxin protomers, and blocks subsequent steps of pore-formation. Our study suggests that the presence of Y321 in the hinge region of the pore-forming motif is crucial for the toxin molecule to sense membrane-binding, and to trigger essential structural rearrangements required for the subsequent oligomerization and pore-formation process. Such a regulatory mechanism of pore-formation by V. cholerae cytolysin has not been documented earlier in the structurally related β-barrel pore-forming toxins.

Point-group symmetry detection in three-dimensional charge density of biomolecules

MOTIVATION

No rigorous statistical tests for detecting point-group symmetry in three-dimensional (3D) charge density maps obtained by electron microscopy (EM) and related techniques have been developed.

RESULTS

We propose a method for determining the point-group symmetry of 3D charge density maps obtained by EM and related techniques. Our ab initio algorithm does not depend on atomic coordinates but utilizes the density map directly. We validate the approach for a range of publicly available single-particle cryo-EM datasets. In straightforward cases, our method enables fully automated single-particle 3D reconstruction without having to input an arbitrarily selected point-group symmetry. When pseudo-symmetry is present, our method provides statistics quantifying the degree to which the 3D density agrees with the different point-groups tested.

AVAILABILITY AND IMPLEMENTATION

The software is freely available at https://github.com/hael/SIMPLE3.0.

Structure of the PCBP2/stem-loop IV complex underlying translation initiation mediated by the poliovirus type I IRES

The poliovirus type I IRES is able to recruit ribosomal machinery only in the presence of host factor PCBP2 that binds to stem-loop IV of the IRES. When PCBP2 is cleaved in its linker region by viral proteinase 3CD, translation initiation ceases allowing the next stage of replication to commence. Here, we investigate the interaction of PCBP2 with the apical region of stem-loop IV (SLIVm) of poliovirus RNA in its full-length and truncated form. CryoEM structure reconstruction of the full-length PCBP2 in complex with SLIVm solved to 6.1 Å resolution reveals a compact globular complex of PCBP2 interacting with the cruciform RNA via KH domains and featuring a prominent GNRA tetraloop. SEC-SAXS, SHAPE and hydroxyl-radical cleavage establish that PCBP2 stabilizes the SLIVm structure, but upon cleavage in the linker domain the complex becomes more flexible and base accessible. Limited proteolysis and REMSA demonstrate the accessibility of the linker region in the PCBP2/SLIVm complex and consequent loss of affinity of PCBP2 for the SLIVm upon cleavage. Together this study sheds light on the structural features of the PCBP2/SLIV complex vital for ribosomal docking, and the way in which this key functional interaction is regulated following translation of the poliovirus genome.

Structure of the Inhibited State of the Sec Translocon

Protein secretion in eukaryotes and prokaryotes involves a universally conserved protein translocation channel formed by the Sec61 complex. Unrelated small-molecule natural products and synthetic compounds inhibit Sec61 with differential effects for different substrates or for Sec61 from different organisms, making this a promising target for therapeutic intervention. To understand the mode of inhibition and provide insight into the molecular mechanism of this dynamic translocon, we determined the structure of mammalian Sec61 inhibited by the Mycobacterium ulcerans exotoxin mycolactone via electron cryo-microscopy. Unexpectedly, the conformation of inhibited Sec61 is optimal for substrate engagement, with mycolactone wedging open the cytosolic side of the lateral gate. The inability of mycolactone-inhibited Sec61 to effectively transport substrate proteins implies that signal peptides and transmembrane domains pass through the site occupied by mycolactone. This provides a foundation for understanding the molecular mechanism of Sec61 inhibitors and reveals novel features of translocon function and dynamics.

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The inhibited Sec translocon adopts a conformation optimal for substrate engagement

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The inhibitor mycolactone wedges open the lateral gate of Sec61α

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Mycolactone blocks the path taken by the signal peptide during engagement

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Resistance mutations are likely to operate by modulating translocon dynamics

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/.

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.

The TAFs of TFIID Bind and Rearrange the Topology of the TATA-Less RPS5 Promoter

The general transcription factor TFIID is a core promoter selectivity factor that recognizes DNA sequence elements and nucleates the assembly of a pre-initiation complex (PIC). The mechanism by which TFIID recognizes the promoter is poorly understood. The TATA-box binding protein (TBP) is a subunit of the multi-protein TFIID complex believed to be key in this process. We reconstituted transcription from highly purified components on a ribosomal protein gene (RPS5) and discovered that TFIIDΔTBP binds and rearranges the promoter DNA topology independent of TBP. TFIIDΔTBP binds ~200 bp of the promoter and changes the DNA topology to a larger extent than the nucleosome core particle. We show that TBP inhibits the DNA binding activities of TFIIDΔTBP and conclude that the complete TFIID complex may represent an auto-inhibited state. Furthermore, we show that the DNA binding activities of TFIIDΔTBP are required for assembly of a PIC poised to select the correct transcription start site (TSS).

Dodecameric structure of a small heat shock protein from Mycobacterium marinum M

Small heat shock proteins (sHSPs) are ATP-independent molecular chaperones present ubiquitously in all kingdoms of life. Their low molecular weight subunits associate to form higher order structures. Under conditions of stress, sHSPs prevent aggregation of substrate proteins by undergoing rapid changes in their conformation or stoichiometry. Polydispersity and dynamic nature of these proteins have made structural investigations through crystallography a daunting task. In pathogens like Mycobacteria, sHSPs are immuno-dominant antigens, enabling survival of the pathogen within the host and contributing to disease persistence. We characterized sHSPs from Mycobacterium marinum M and determined the crystal structure of one of these. The protein crystallized in three different conditions as dodecamers, with dimers arranged in a tetrahedral fashion to form a closed cage-like architecture. Interestingly, we found a pentapeptide bound to the dodecamers revealing one of the modes of sHSP-substrate interaction. Further, we have observed that ATP inhibits the chaperoning activity of the protein.

Searching for 3D structural models from a library of biological shapes using a few 2D experimental images

Background

Advancements in biophysical experimental techniques have pushed the limits in terms of the types of phenomena that can be characterized, the amount of data that can be produced and the resolution at which we can visualize them. Single particle techniques such as Electron Microscopy (EM) and X-ray free electron laser (XFEL) scattering require a large number of 2D images collected to resolve three-dimensional (3D) structures. In this study, we propose a quick strategy to retrieve potential 3D shapes, as low-resolution models, from a few 2D experimental images by searching a library of 2D projection images generated from existing 3D structures.

Results

We developed the protocol to assemble a non-redundant set of 3D shapes for generating the 2D image library, and to retrieve potential match 3D shapes for query images, using EM data as a test. In our strategy, we disregard differences in volume size, giving previously unknown structures and conformations a greater number of 3D biological shapes as possible matches. We tested the strategy using images from three EM models as query images for searches against a library of 22750 2D projection images generated from 250 random EM models. We found that our ability to identify 3D shapes that match the query images depends on how complex the outline of the 2D shapes are and whether they are represented in the search image library.

Conclusions

Through our computational method, we are able to quickly retrieve a 3D shape from a few 2D projection images. Our approach has the potential for exploring other types of 2D single particle structural data such as from XFEL scattering experiments, for providing a tool to interpret low-resolution data that may be insufficient for 3D reconstruction, and for estimating the mixing of states or conformations that could exist in such experimental data.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2358-0) contains supplementary material, which is available to authorized users.

Rapid near-atomic resolution single-particle 3D reconstruction with SIMPLE

Cryogenic electron microscopy (cryo-EM) and single-particle analysis enables determination of near-atomic resolution structures of biological molecules. However, large computational requirements limit throughput and rapid testing of new image processing tools. We developed PRIME, an algorithm part of the SIMPLE software suite, for determination of the relative 3D orientations of single-particle projection images. PRIME has primarily found use for generation of an initial ab initio 3D reconstruction. Here we show that the strategy behind PRIME, iterative estimation of per-particle orientation distributions with stochastic hill climbing, provides a competitive approach to near-atomic resolution single-particle 3D reconstruction. A number of mathematical techniques for accelerating the convergence rate are introduced, leading to a speedup of nearly two orders of magnitude. We benchmarked our developments on numerous publicly available data sets and conclude that near-atomic resolution ab initio 3D reconstructions can be obtained with SIMPLE in a matter of hours, using standard over-the-counter CPU workstations.

Routine single particle CryoEM sample and grid characterization by tomography

Single particle cryo-electron microscopy (cryoEM) is often performed under the assumption that particles are not adsorbed to the air-water interfaces and in thin, vitreous ice. In this study, we performed fiducial-less tomography on over 50 different cryoEM grid/sample preparations to determine the particle distribution within the ice and the overall geometry of the ice in grid holes. Surprisingly, by studying particles in holes in 3D from over 1000 tomograms, we have determined that the vast majority of particles (approximately 90%) are adsorbed to an air-water interface. The implications of this observation are wide-ranging, with potential ramifications regarding protein denaturation, conformational change, and preferred orientation. We also show that fiducial-less cryo-electron tomography on single particle grids may be used to determine ice thickness, optimal single particle collection areas and strategies, particle heterogeneity, and de novo models for template picking and single particle alignment.

The translation elongation cycle-capturing multiple states by cryo-electron microscopy

During the work cycle of elongation, the ribosome, a molecular machine of vast complexity, exists in a large number of states distinguished by constellation of its subunits, its subunit domains and binding partners. Single-particle cryogenic electron microscopy (cryo-EM), developed over the past 40 years, is uniquely suited to determine the structure of molecular machines in their native states. With the emergence, 10 years ago, of unsupervised clustering techniques in the analysis of single-particle data, it has been possible to determine multiple structures from a sample containing ribosomes equilibrating in different thermally accessible states. In addition, recent advances in detector technology have made it possible to reach near-atomic resolution for some of these states. With these capabilities, single-particle cryo-EM has been at the forefront of exploring ribosome dynamics during its functional cycle, along with single-molecule fluorescence resonance energy transfer and molecular dynamics computations, offering insights into molecular architecture uniquely honed by evolution to capitalize on thermal energy in the ambient environment.This article is part of the themed issue 'Perspectives on the ribosome'.

Molecular architecture of potassium chloride co-transporter KCC2

KCC2 is a neuron specific K⁺-Cl⁻ co-transporter that controls neuronal chloride homeostasis, and is critically involved in many neurological diseases including brain trauma, epilepsies, autism and schizophrenia. Despite significant accumulating data on the biology and electrophysiological properties of KCC2, structure-function relationships remain poorly understood. Here we used calixarene detergent to solubilize and purify wild-type non-aggregated and homogenous KCC2. Specific binding of inhibitor compound VU0463271 was demonstrated using surface plasmon resonance (SPR). Mass spectrometry revealed glycosylations and phosphorylations as expected from functional KCC2. We show by electron microscopy (EM) that KCC2 exists as monomers and dimers in solution. Monomers are organized into “head” and “core” domains connected by a flexible “linker”. Dimers are asymmetrical and display a bent “S-shape” architecture made of four distinct domains and a flexible dimerization interface. Chemical crosslinking in reducing conditions shows that disulfide bridges are involved in KCC2 dimerization. Moreover, we show that adding a tag to the C-terminus is detrimental to KCC2 function. We postulate that the conserved KCC2 C-ter may be at the interface of dimerization. Taken together, our findings highlight the flexible multi-domain structure of KCC2 with variable anchoring points at the dimerization interface and an important C-ter extremity providing the first in-depth functional architecture of KCC2.

Common lines modeling for reference free Ab-initio reconstruction in cryo-EM

We consider the problem of estimating an unbiased and reference-free ab initio model for non-symmetric molecules from images generated by single-particle cryo-electron microscopy. The proposed algorithm finds the globally optimal assignment of orientations that simultaneously respects all common lines between all images. The contribution of each common line to the estimated orientations is weighted according to a statistical model for common lines' detection errors. The key property of the proposed algorithm is that it finds the global optimum for the orientations given the common lines. In particular, any local optima in the common lines energy landscape do not affect the proposed algorithm. As a result, it is applicable to thousands of images at once, very robust to noise, completely reference free, and not biased towards any initial model. A byproduct of the algorithm is a set of measures that allow to asses the reliability of the obtained ab initio model. We demonstrate the algorithm using class averages from two experimental data sets, resulting in ab initio models with resolutions of 20Å or better, even from class averages consisting of as few as three raw images per class.

Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy

The orientation distribution of a single-particle electron cryomicroscopy specimen limits the resolution of the reconstructed density map. Here we define a statistical quantity, the efficiency, E_od, which characterises the orientation distribution via its corresponding point spread function. The efficiency measures the ability of the distribution to provide uniform information and resolution in all directions of the reconstruction, independent of other factors. This metric allows rapid and rigorous evaluation of specimen preparation methods, assisting structure determination to high resolution with minimal data.

A number of parameters influence the resolution of a cryo-EM structure. Here the authors investigate the effects of specimen orientation in single particle cryo-EM and present open-source software for rapidly assessing orientation distributions to improve data collection.

Single-particle cryo-EM-Improved ab initio 3D reconstruction with SIMPLE/PRIME

Cryogenic electron microscopy (cryo-EM) and single-particle analysis now enables the determination of high-resolution structures of macromolecular assemblies that have resisted X-ray crystallography and other approaches. We developed the SIMPLE open-source image-processing suite for analysing cryo-EM images of single-particles. A core component of SIMPLE is the probabilistic PRIME algorithm for identifying clusters of images in 2D and determine relative orientations of single-particle projections in 3D. Here, we extend our previous work on PRIME and introduce new stochastic optimization algorithms that improve the robustness of the approach. Our refined method for identification of homogeneous subsets of images in accurate register substantially improves the resolution of the cluster centers and of the ab initio 3D reconstructions derived from them. We now obtain maps with a resolution better than 10 Å by exclusively processing cluster centers. Excellent parallel code performance on over-the-counter laptops and CPU workstations is demonstrated.

Addressing preferred specimen orientation in single-particle cryo-EM through tilting

We present a strategy for tackling preferred specimen orientation in single-particle cryogenic electron microscopy by employing tilts during data collection. We also describe a tool to quantify the resulting directional resolution using 3D Fourier shell correlation volumes. We applied these methods to determine the structures at near-atomic resolution of the influenza hemagglutinin trimer, which adopts a highly preferred specimen orientation, and of ribosomal biogenesis intermediates, which adopt moderately preferred orientations.

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.

Architectures of Lipid Transport Systems for the Bacterial Outer Membrane

How phospholipids are trafficked between the bacterial inner and outer membranes through the hydrophilic space of the periplasm is not known. We report that members of the mammalian cell entry (MCE) protein family form hexameric assemblies with a central channel capable of mediating lipid transport. The E. coli MCE protein, MlaD, forms a ring associated with an ABC transporter complex in the inner membrane. A soluble lipid-binding protein, MlaC, ferries lipids between MlaD and an outer membrane protein complex. In contrast, EM structures of two other E. coli MCE proteins show that YebT forms an elongated tube consisting of seven stacked MCE rings, and PqiB adopts a syringe-like architecture. Both YebT and PqiB create channels of sufficient length to span the periplasmic space. This work reveals diverse architectures of highly conserved protein-based channels implicated in the transport of lipids between the membranes of bacteria and some eukaryotic organelles.

cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination

Single-particle electron cryomicroscopy (cryo-EM) is a powerful method for determining the structures of biological macromolecules. With automated microscopes, cryo-EM data can often be obtained in a few days. However, processing cryo-EM image data to reveal heterogeneity in the protein structure and to refine 3D maps to high resolution frequently becomes a severe bottleneck, requiring expert intervention, prior structural knowledge, and weeks of calculations on expensive computer clusters. Here we show that stochastic gradient descent (SGD) and branch-and-bound maximum likelihood optimization algorithms permit the major steps in cryo-EM structure determination to be performed in hours or minutes on an inexpensive desktop computer. Furthermore, SGD with Bayesian marginalization allows ab initio 3D classification, enabling automated analysis and discovery of unexpected structures without bias from a reference map. These algorithms are combined in a user-friendly computer program named cryoSPARC (http://www.cryosparc.com).

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.

Accelerated cryo-EM structure determination with parallelisation using GPUs in RELION-2

By reaching near-atomic resolution for a wide range of specimens, single-particle cryo-EM structure determination is transforming structural biology. However, the necessary calculations come at large computational costs, which has introduced a bottleneck that is currently limiting throughput and the development of new methods. Here, we present an implementation of the RELION image processing software that uses graphics processors (GPUs) to address the most computationally intensive steps of its cryo-EM structure determination workflow. Both image classification and high-resolution refinement have been accelerated more than an order-of-magnitude, and template-based particle selection has been accelerated well over two orders-of-magnitude on desktop hardware. Memory requirements on GPUs have been reduced to fit widely available hardware, and we show that the use of single precision arithmetic does not adversely affect results. This enables high-resolution cryo-EM structure determination in a matter of days on a single workstation.

DOI:http://dx.doi.org/10.7554/eLife.18722.001

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.

While the revolution will not be crystallized, biochemistry reigns supreme

Single-particle cryo-electron microscopy (EM) is currently gaining attention for the ability to calculate structures that reach sub-5 Å resolutions; however, the technique is more than just an alternative approach to X-ray crystallography. Molecular machines work via dynamic conformational changes, making structural flexibility the hallmark of function. While the dynamic regions in molecules are essential, they are also the most challenging to structurally characterize. Single-particle EM has the distinct advantage of being able to directly visualize purified molecules without the formation of ordered arrays of molecules locked into identical conformations. Additionally, structures determined using single-particle EM can span resolution ranges from very low- to atomic-levels (>30-1.8 Å), sometimes even in the same structure. The ability to accommodate various resolutions gives single-particle EM the unique capacity to structurally characterize dynamic regions of biological molecules, thereby contributing essential structural information needed for the development of molecular models that explain function. Further, many important molecular machines are intrinsically dynamic and compositionally heterogeneous. Structures of these complexes may never reach sub-5 Å resolutions due to this flexibility required for function. Thus, the biochemical quality of the sample, as well as, the calculation and interpretation of low- to mid-resolution cryo-EM structures (30-8 Å) remains critical for generating insights into the architecture of many challenging biological samples that cannot be visualized using alternative techniques.

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.

A data set from flash X-ray imaging of carboxysomes

Ultra-intense femtosecond X-ray pulses from X-ray lasers permit structural studies on single particles and biomolecules without crystals. We present a large data set on inherently heterogeneous, polyhedral carboxysome particles. Carboxysomes are cell organelles that vary in size and facilitate up to 40% of Earth's carbon fixation by cyanobacteria and certain proteobacteria. Variation in size hinders crystallization. Carboxysomes appear icosahedral in the electron microscope. A protein shell encapsulates a large number of Rubisco molecules in paracrystalline arrays inside the organelle. We used carboxysomes with a mean diameter of 115±26 nm from Halothiobacillus neapolitanus. A new aerosol sample-injector allowed us to record 70,000 low-noise diffraction patterns in 12 min. Every diffraction pattern is a unique structure measurement and high-throughput imaging allows sampling the space of structural variability. The different structures can be separated and phased directly from the diffraction data and open a way for accurate, high-throughput studies on structures and structural heterogeneity in biology and elsewhere.

Single particle electron cryomicroscopy: trends, issues and future perspective

There has been enormous progress during the last few years in the determination of three-dimensional biological structures by single particle electron cryomicroscopy (cryoEM), allowing maps to be obtained with higher resolution and from fewer images than required previously. This is due principally to the introduction of a new type of direct electron detector that has 2- to 3-fold higher detective quantum efficiency than available previously, and to the improvement of the computational algorithms for image processing. In spite of the great strides that have been made, quantitative analysis shows that there are still significant gains to be made provided that the problems associated with image degradation can be solved, possibly by minimising beam-induced specimen movement and charge build up during imaging. If this can be achieved, it should be possible to obtain near atomic resolution structures of smaller single particles, using fewer images and resolving more conformational states than at present, thus realising the full potential of the method. The recent popularity of cryoEM for molecular structure determination also highlights the need for lower cost microscopes, so we encourage development of an inexpensive, 100 keV electron cryomicroscope with a high-brightness field emission gun to make the method accessible to individual groups or institutions that cannot afford the investment and running costs of a state-of-the-art 300 keV installation. A key requisite for successful high-resolution structure determination by cryoEM includes interpretation of images and optimising the biochemistry and grid preparation to obtain nicely distributed macromolecules of interest. We thus include in this review a gallery of cryoEM micrographs that shows illustrative examples of single particle images of large and small macromolecular complexes.

Structural Insights into the Niemann-Pick C1 (NPC1)-Mediated Cholesterol Transfer and Ebola Infection

Niemann-Pick disease type C (NPC) is associated with mutations in NPC1 and NPC2, whose gene products are key players in the endosomal/lysosomal egress of low-density lipoprotein-derived cholesterol. NPC1 is also the intracellular receptor for Ebola virus (EBOV). Here, we present a 4.4 Å structure of full-length human NPC1 and a low-resolution reconstruction of NPC1 in complex with the cleaved glycoprotein (GPcl) of EBOV, both determined by single-particle electron cryomicroscopy. NPC1 contains 13 transmembrane segments (TMs) and three distinct lumenal domains A (also designated NTD), C, and I. TMs 2–13 exhibit a typical resistance-nodulation-cell division fold, among which TMs 3–7 constitute the sterol-sensing domain conserved in several proteins involved in cholesterol metabolism and signaling. A trimeric EBOV-GPcl binds to one NPC1 monomer through the domain C. Our structural and biochemical characterizations provide an important framework for mechanistic understanding of NPC1-mediated intracellular cholesterol trafficking and Ebola virus infection.

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The cryo-EM structure of full-length human NPC1 was determined at 4.4 Å resolution

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Structure-guided biochemical analysis of cholesterol transfer from NPC2 to NPC1

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Low-resolution cryo-EM structure of NPC1 bound to GPcl of Ebola virus was obtained

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A trimeric GPcl binds to one NPC1 through the crystal structure-revealed interface

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.

Structural basis for therapeutic inhibition of complement C5

Activation of complement C5 generates the potent anaphylatoxin C5a and leads to pathogen lysis, inflammation and cell damage. The therapeutic potential of C5 inhibition has been demonstrated by eculizumab, one of the world's most expensive drugs. However, the mechanism of C5 activation by C5 convertases remains elusive, thus limiting development of therapeutics. Here we identify and characterize a new protein family of tick-derived C5 inhibitors. Structures of C5 in complex with the new inhibitors, the phase I and phase II inhibitor OmCI, or an eculizumab Fab reveal three distinct binding sites on C5 that all prevent activation of C5. The positions of the inhibitor-binding sites and the ability of all three C5-inhibitor complexes to competitively inhibit the C5 convertase conflict with earlier steric-inhibition models, thus suggesting that a priming event is needed for activation.

A saposin-lipoprotein nanoparticle system for membrane proteins

A limiting factor in membrane protein research is the ability to solubilize and stabilize such proteins. Detergents are used most often for solubilizing membrane proteins, but they are associated with protein instability and poor compatibility with structural and biophysical studies. Here we present a saposin-lipoprotein nanoparticle system, Salipro, which allows for the reconstitution of membrane proteins in a lipid environment that is stabilized by a scaffold of saposin proteins. We demonstrate the applicability of the method on two purified membrane protein complexes as well as by the direct solubilization and nanoparticle incorporation of a viral membrane protein complex from the virus membrane. Our approach facilitated high-resolution structural studies of the bacterial peptide transporter PeptTSo2 by single-particle cryo-electron microscopy (cryo-EM) and allowed us to stabilize the HIV envelope glycoprotein in a functional state.

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.

Structure of the human dimeric ATM kinase

DNA-double strand breaks activate the serine/threonine protein kinase ataxia-telangiectasia mutated (ATM) to initiate DNA damage signal transduction. This activation process involves autophosphorylation and dissociation of inert ATM dimers into monomers that are catalytically active. Using single-particle electron microscopy (EM), we determined the structure of dimeric ATM in its resting state. The EM map could accommodate the crystal structure of the N-terminal truncated mammalian target of rapamycin (mTOR), a closely related enzyme of the phosphatidylinositol 3-kinase-related protein kinase (PIKK) family, allowing for the localization of the N- and the C-terminal regions of ATM. In the dimeric structure, the actives sites are buried, restricting the access of the substrates to these sites. The unanticipated domain organization of ATM provides a basis for understanding its mechanism of inhibition.