The ribosome at improved resolution: new techniques for merging and orientation refinement in 3D cryo-electron microscopy of biological particles

Liquid-Electron Microscopy and the Real-Time Revolution

Advances in imaging technology enable striking views of life's most minute details. A missing piece of the puzzle, however, is the direct atomic observation of biomolecules in action. Liquid-phase transmission electron microscopy (liquid-EM) is the room-temperature correlate to cryo-electron microscopy, which is leading the resolution revolution in biophysics. This article reviews current challenges and opportunities in the liquid-EM field while discussing technical considerations for specimen enclosures, devices and systems, and scientific data management. Since liquid-EM is gaining traction in the life sciences community, cross talk among the disciplines of materials and life sciences is needed to disseminate knowledge of best practices along with high-level user engagement. How liquid-EM technology is inspiring the real-time revolution in molecular microscopy is also discussed. Looking ahead, the new movement can be better supported through open resource sharing and partnerships among academic, industry, and federal organizations, which may benefit from the scientific equity foundational to the technique.

The ribosome comes to life

The ribosome, together with its tRNA substrates, links genotype to phenotype by translating the genetic information carried by mRNA into protein. During the past half-century, the structure and mechanisms of action of the ribosome have emerged from mystery and confusion. It is now evident that the ribosome is an ancient RNA-based molecular machine of staggering structural complexity and that it is fundamentally similar in all living organisms. The three central functions of protein synthesis-decoding, catalysis of peptide bond formation, and translocation of mRNA and tRNA-are based on elegant mechanisms that evolved from the properties of RNA, the founding macromolecule of life. Moreover, all three of these functions (and even life itself) seem to proceed in defiance of entropy. Protein synthesis thus appears to exploit both the energy of GTP hydrolysis and peptide bond formation to constrain the directionality and accuracy of events taking place on the ribosome.

A predicted model-aided reconstruction algorithm for X-ray free-electron laser single-particle imaging

Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction.

Cryo-EM Map Anisotropy Can Be Attenuated by Map Post-Processing and a New Method for Its Estimation

One of the most important challenges in cryogenic electron microscopy (cryo-EM) is the substantial number of samples that exhibit preferred orientations, which leads to an uneven coverage of the projection sphere. As a result, the overall quality of the reconstructed maps can be severely affected, as manifested by the presence of anisotropy in the map resolution. Several methods have been proposed to measure the directional resolution of maps in tandem with experimental protocols to address the problem of preferential orientations in cryo-EM. Following these works, in this manuscript we identified one potential limitation that may affect most of the existing methods and we proposed an alternative approach to evaluate the presence of preferential orientations in cryo-EM reconstructions. In addition, we also showed that some of the most recently proposed cryo-EM map post-processing algorithms can attenuate map anisotropy, thus offering alternative visualization opportunities for cases affected by moderate levels of preferential orientations.

Cryo-electron microscopy-based drug design

Structure-based drug design (SBDD) has gained popularity owing to its ability to develop more potent drugs compared to conventional drug-discovery methods. The success of SBDD relies heavily on obtaining the three-dimensional structures of drug targets. X-ray crystallography is the primary method used for solving structures and aiding the SBDD workflow; however, it is not suitable for all targets. With the resolution revolution, enabling routine high-resolution reconstruction of structures, cryogenic electron microscopy (cryo-EM) has emerged as a promising alternative and has attracted increasing attention in SBDD. Cryo-EM offers various advantages over X-ray crystallography and can potentially replace X-ray crystallography in SBDD. To fully utilize cryo-EM in drug discovery, understanding the strengths and weaknesses of this technique and noting the key advancements in the field are crucial. This review provides an overview of the general workflow of cryo-EM in SBDD and highlights technical innovations that enable its application in drug design. Furthermore, the most recent achievements in the cryo-EM methodology for drug discovery are discussed, demonstrating the potential of this technique for advancing drug development. By understanding the capabilities and advancements of cryo-EM, researchers can leverage the benefits of designing more effective drugs. This review concludes with a discussion of the future perspectives of cryo-EM-based SBDD, emphasizing the role of this technique in driving innovations in drug discovery and development. The integration of cryo-EM into the drug design process holds great promise for accelerating the discovery of new and improved therapeutic agents to combat various diseases.

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.

Exploring the Structural Variability of Dynamic Biological Complexes by Single-Particle Cryo-Electron Microscopy

Biological macromolecules and assemblies precisely rearrange their atomic 3D structures to execute cellular functions. Understanding the mechanisms by which these molecular machines operate requires insight into the ensemble of structural states they occupy during the functional cycle. Single-particle cryo-electron microscopy (cryo-EM) has become the preferred method to provide near-atomic resolution, structural information about dynamic biological macromolecules elusive to other structure determination methods. Recent advances in cryo-EM methodology have allowed structural biologists not only to probe the structural intermediates of biochemical reactions, but also to resolve different compositional and conformational states present within the same dataset. This article reviews newly developed sample preparation and single-particle analysis (SPA) techniques for high-resolution structure determination of intrinsically dynamic and heterogeneous samples, shedding light upon the intricate mechanisms employed by molecular machines and helping to guide drug discovery efforts.

CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM Images

Cryo-electron microscopy (cryo-EM) has become a tool of fundamental importance in structural biology, helping us understand the basic building blocks of life. The algorithmic challenge of cryo-EM is to jointly estimate the unknown 3D poses and the 3D electron scattering potential of a biomolecule from millions of extremely noisy 2D images. Existing reconstruction algorithms, however, cannot easily keep pace with the rapidly growing size of cryo-EM datasets due to their high computational and memory cost. We introduce cryoAI, an ab initio reconstruction algorithm for homogeneous conformations that uses direct gradient-based optimization of particle poses and the electron scattering potential from single-particle cryo-EM data. CryoAI combines a learned encoder that predicts the poses of each particle image with a physics-based decoder to aggregate each particle image into an implicit representation of the scattering potential volume. This volume is stored in the Fourier domain for computational efficiency and leverages a modern coordinate network architecture for memory efficiency. Combined with a symmetrized loss function, this framework achieves results of a quality on par with state-of-the-art cryo-EM solvers for both simulated and experimental data, one order of magnitude faster for large datasets and with significantly lower memory requirements than existing methods.

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.

Artificial Intelligence in Cryo-Electron Microscopy

Cryo-electron microscopy (cryo-EM) has become an unrivaled tool for determining the structure of macromolecular complexes. The biological function of macromolecular complexes is inextricably tied to the flexibility of these complexes. Single particle cryo-EM can reveal the conformational heterogeneity of a biochemically pure sample, leading to well-founded mechanistic hypotheses about the roles these complexes play in biology. However, the processing of increasingly large, complex datasets using traditional data processing strategies is exceedingly expensive in both user time and computational resources. Current innovations in data processing capitalize on artificial intelligence (AI) to improve the efficiency of data analysis and validation. Here, we review new tools that use AI to automate the data analysis steps of particle picking, 3D map reconstruction, and local resolution determination. We discuss how the application of AI moves the field forward, and what obstacles remain. We also introduce potential future applications of AI to use cryo-EM in understanding protein communities in cells.

Liquid-EM goes viral - visualizing structure and dynamics

Liquid-electron microscopy (EM), the room temperature correlate to cryo-EM, is an exciting new technique delivering real-time data of dynamic reactions in solution. Here, we explain how liquid-EM gained popularity in recent years by examining key experiments conducted on viral assemblies and host-pathogen interactions. We describe developing workflows for specimen preparation, data collection, and computing processes that led to the first high-resolution virus structures in a liquid environment. Equally important, we review why liquid-electron tomography may become the next big thing in biomedical research due to its ability to monitor live viruses entering cells within seconds. Taken together, we pose the idea that liquid-EM can serve as a dynamic complement to current cryo-EM methods, inspiring the "real-time revolution" in nanoscale imaging.

Real space in cryo-EM: the future is local

Cryo-EM images have extremely low signal-to-noise levels because biological macromolecules are highly radiation-sensitive, requiring low-dose imaging, and because the molecules are poor in contrast. Confident recovery of the signal requires the averaging of many images, the iterative optimization of parameters and the introduction of much prior information. Poor parameter estimates, overfitting and variations in signal strength and resolution across the resulting reconstructions remain frequent issues. Because biological samples are real-space phenomena, exhibiting local variations, real-space measures can be both more reliable and more appropriate than Fourier-space measures. Real-space measures can be calculated separately over each differing region of an image or volume. Real-space filters can be applied according to the local need. Powerful prior information, not available in Fourier space, can be introduced in real space. Priors can be applied in real space in ways that Fourier space precludes. The treatment of biological phenomena remains highly dependent on spatial frequency, however, which would normally be handled in Fourier space. We believe that measures and filters based around real-space operations on extracted frequency bands, i.e. a series of band-pass filtered real-space volumes, and over real-space densities of striding (sequentially increasing or decreasing) resolution through Fourier space are the best way to address this and will perform better than global Fourier-space-based approaches. Future developments in image processing within the field are generally expected to be based on a mixture of both rationally designed and deep-learning approaches, and to incorporate novel prior information from developments such as AlphaFold. Regardless of approach, it is clear that `locality', through real-space measures, filters and processing, will become central to image processing.

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.

Automated Tools to Advance High-Resolution Imaging in Liquid

Liquid-electron microscopy (EM), the room-temperature correlate to cryo-EM, is a rapidly growing field providing high-resolution insights of macromolecules in solution. Here, we describe how liquid-EM experiments can incorporate automated tools to propel the field to new heights. We demonstrate fresh workflows for specimen preparation, data collection, and computing processes to assess biological structures in liquid. Adeno-associated virus (AAV) and the SARS-CoV-2 nucleocapsid (N) were used as model systems to highlight the technical advances. These complexes were selected based on their major differences in size and natural symmetry. AAV is a highly symmetric, icosahedral assembly with a particle diameter of ~25 nm. At the other end of the spectrum, N protein is an asymmetric monomer or dimer with dimensions of approximately 5–7 nm, depending upon its oligomerization state. Equally important, both AAV and N protein are popular subjects in biomedical research due to their high value in vaccine development and therapeutic efforts against COVID-19. Overall, we demonstrate how automated practices in liquid-EM can be used to decode molecules of interest for human health and disease.

The CRL4DCAF1 cullin-RING ubiquitin ligase is activated following a switch in oligomerization state

The cullin‐4‐based RING‐type (CRL4) family of E3 ubiquitin ligases functions together with dedicated substrate receptors. Out of the ˜29 CRL4 substrate receptors reported, the DDB1‐ and CUL4‐associated factor 1 (DCAF1) is essential for cellular survival and growth, and its deregulation has been implicated in tumorigenesis. We carried out biochemical and structural studies to examine the structure and mechanism of the CRL4^DCAF1 ligase. In the 8.4 Å cryo‐EM map of CRL4^DCAF1, four CUL4‐RBX1‐DDB1‐DCAF1 protomers are organized into two dimeric sub‐assemblies. In this arrangement, the WD40 domain of DCAF1 mediates binding with the cullin C‐terminal domain (CTD) and the RBX1 subunit of a neighboring CRL4^DCAF1 protomer. This renders RBX1, the catalytic subunit of the ligase, inaccessible to the E2 ubiquitin‐conjugating enzymes. Upon CRL4^DCAF1 activation by neddylation, the interaction between the cullin CTD and the neighboring DCAF1 protomer is broken, and the complex assumes an active dimeric conformation. Accordingly, a tetramerization‐deficient CRL4^DCAF1 mutant has higher ubiquitin ligase activity compared to the wild‐type. This study identifies a novel mechanism by which unneddylated and substrate‐free CUL4 ligases can be maintained in an inactive state.

Comparison of EMC and CM methods for orienting diffraction images in single-particle imaging experiments

In single-particle imaging (SPI) experiments, diffraction patterns of identical particles are recorded. The particles are injected into the X-ray free-electron laser (XFEL) beam in random orientations. The crucial step of the data processing of SPI is finding the orientations of the recorded diffraction patterns in reciprocal space and reconstructing the 3D intensity distribution. Here, two orientation methods are compared: the expansion maximization compression (EMC) algorithm and the correlation maximization (CM) algorithm. To investigate the efficiency, reliability and accuracy of the methods at various XFEL pulse fluences, simulated diffraction patterns of biological molecules are used.

Challenges in sample preparation and structure determination of amyloids by cryo-EM

Amyloids share a common architecture but play disparate biological roles in processes ranging from bacterial defense mechanisms to protein misfolding diseases. Their structures are highly polymorphic, which makes them difficult to study by X-ray diffraction or NMR spectroscopy. Our understanding of amyloid structures is due in large part to recent advances in the field of cryo-EM, which allows for determining the polymorphs separately. In this review, we highlight the main stepping stones leading to the substantial number of high-resolution amyloid fibril structures known today as well as recent developments regarding automation and software in cryo-EM. We discuss that sample preparation should move closer to physiological conditions to understand how amyloid aggregation and disease are linked. We further highlight new approaches to address heterogeneity and polymorphism of amyloid fibrils in EM image processing and give an outlook to the upcoming challenges in researching the structural biology of amyloids.

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.

Reliable cryo-EM resolution estimation with modified Fourier shell correlation

A modified Fourier shell correlation (mFSC) methodology is introduced that is aimed at addressing two fundamental problems that mar the use of the FSC: the strong influence of mask-induced artifacts on resolution estimation and the lack of assessment of FSC uncertainties stemming from the inability to determine the associated number of degrees of freedom. It is shown that by simply changing the order of the steps in which the FSC is computed, the correlations induced by masking of the input data can be eliminated. In addition, to further reduce artifacts, a smooth Gaussian window function is used to outline the regions of reciprocal space within which the mFSC is computed. Next, it is shown that the number of degrees of freedom (ndf) of the system is approximated well by combining the ndf associated with the Gaussian window in reciprocal space with further reduction of the ndf owing to the use of the mask in real space. It is demonstrated through the application of the mFSC to both single-particle and helical structures that the mFSC yields reliable, mask-induced artifact-free results as a result of the introduced modifications. Since the adverse effect of the mask is eliminated, it also becomes possible to compute robust local resolutions both per voxel of a 3D map as well as, in a newly developed approach, per functional subunit, segment or even larger secondary element of the studied complex.

Mitigating local over-fitting during single particle reconstruction with SIDESPLITTER

Single particle analysis has become a key structural biology technique. Experimental images are extremely noisy, and during iterative refinement it is possible to stably incorporate noise into the reconstruction. Such "over-fitting" can lead to misinterpretation of the structure and flawed biological results. Several strategies are routinely used to prevent over-fitting, the most common being independent refinement of two sides of a split dataset. In this study, we show that over-fitting remains an issue within regions of low local signal-to-noise, despite independent refinement of half datasets. We propose a modification of the refinement process through the application of a local signal-to-noise filter: SIDESPLITTER. We show that our approach can reduce over-fitting for both idealised and experimental data while maintaining independence between the two sides of a split refinement. SIDESPLITTER refinement leads to improved density, and can also lead to improvement of the final resolution in extreme cases where datasets are prone to severe over-fitting, such as small membrane proteins.

WITHDRAWN: Structural studies of vitrified biological proteins and macromolecules - A review on the microimaging aspects of cryo-electron microscopy

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Validation tests for cryo-EM maps using an independent particle set

Cryo-electron microscopy (cryo-EM) has revolutionized structural biology by providing 3D density maps of biomolecules at near-atomic resolution. However, map validation is still an open issue. Despite several efforts from the community, it is possible to overfit 3D maps to noisy data. Here, we develop a novel methodology that uses a small independent particle set (not used during the 3D refinement) to validate the maps. The main idea is to monitor how the map probability evolves over the control set during the 3D refinement. The method is complementary to the gold-standard procedure, which generates two reconstructions at each iteration. We low-pass filter the two reconstructions for different frequency cutoffs, and we calculate the probability of each filtered map given the control set. For high-quality maps, the probability should increase as a function of the frequency cutoff and the refinement iteration. We also compute the similarity between the densities of probability distributions of the two reconstructions. As higher frequencies are included, the distributions become more dissimilar. We optimized the BioEM package to perform these calculations, and tested it over systems ranging from quality data to pure noise. Our results show that with our methodology, it possible to discriminate datasets that are constructed from noise particles. We conclude that validation against a control particle set provides a powerful tool to assess the quality of cryo-EM maps.

Research journey of respirasome

Respirasome, as a vital part of the oxidative phosphorylation system, undertakes the task of transferring electrons from the electron donors to oxygen and produces a proton concentration gradient across the inner mitochondrial membrane through the coupled translocation of protons. Copious research has been carried out on this lynchpin of respiration. From the discovery of individual respiratory complexes to the report of the high-resolution structure of mammalian respiratory supercomplex I1III2IV1, scientists have gradually uncovered the mysterious veil of the electron transport chain (ETC). With the discovery of the mammalian respiratory mega complex I2III2IV2, a new perspective emerges in the research field of the ETC. Behind these advances glitters the light of the revolution in both theory and technology. Here, we give a short review about how scientists 'see' the structure and the mechanism of respirasome from the macroscopic scale to the atomic scale during the past decades.

Joint Angular Refinement and Reconstruction for Single-Particle Cryo-EM

Single-particle cryo-electron microscopy (cryo-EM) reconstructs the three-dimensional (3D) structure of biomolecules from a large set of 2D projection images with random and unknown orientations. A crucial step in the single-particle cryo-EM pipeline is 3D refinement, which resolves a highresolution 3D structure from an initial approximate volume by refining the estimation of the orientation of each projection. In this work, we propose a new approach that refines the projection angles on the continuum. We formulate the optimization problem over the density map and the orientations jointly. The density map is updated using the efficient alternating-direction method of multipliers, while the orientations are updated through a semicoordinate- wise gradient descent for which we provide an explicit derivation of the gradient. Our method eliminates the requirement for a fine discretization of the orientation space and does away with the classical but computationally expensive templatematching step. Numerical results demonstrate the feasibility and performance of our approach compared to several baselines.

Need for Cross-Validation of Single Particle Cryo-EM

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

Structural analysis of lecithin:cholesterol acyltransferase bound to high density lipoprotein particles

Lecithin:cholesterol acyltransferase (LCAT) catalyzes a critical step of reverse cholesterol transport by esterifying cholesterol in high density lipoprotein (HDL) particles. LCAT is activated by apolipoprotein A-I (ApoA-I), which forms a double belt around HDL, however the manner in which LCAT engages its lipidic substrates and ApoA-I in HDL is poorly understood. Here, we used negative stain electron microscopy, crosslinking, and hydrogen-deuterium exchange studies to refine the molecular details of the LCAT-HDL complex. Our data are consistent with LCAT preferentially binding to the edge of discoidal HDL near the boundary between helix 5 and 6 of ApoA-I in a manner that creates a path from the lipid bilayer to the active site of LCAT. Our results provide not only an explanation why LCAT activity diminishes as HDL particles mature, but also direct support for the anti-parallel double belt model of HDL, with LCAT binding preferentially to the helix 4/6 region.

Separating distinct structures of multiple macromolecular assemblies from cryo-EM projections

Single particle analysis for structure determination in cryo-electron microscopy is traditionally applied to samples purified to near homogeneity as current reconstruction algorithms are not designed to handle heterogeneous mixtures of structures from many distinct macromolecular complexes. We extend on long established methods and demonstrate that relating two-dimensional projection images by their common lines in a graphical framework is sufficient for partitioning distinct protein and multiprotein complexes within the same data set. The feasibility of this approach is first demonstrated on a large set of synthetic reprojections from 35 unique macromolecular structures spanning a mass range of hundreds to thousands of kilodaltons. We then apply our algorithm on cryo-EM data collected from a mixture of five protein complexes and use existing methods to solve multiple three-dimensional structures ab initio. Incorporating methods to sort single particle cryo-EM data from extremely heterogeneous mixtures will alleviate the need for stringent purification and pave the way toward investigation of samples containing many unique structures.

Cryo-EM structures of the human glutamine transporter SLC1A5 (ASCT2) in the outward-facing conformation

Alanine-serine-cysteine transporter 2 (ASCT2, SLC1A5) is the primary transporter of glutamine in cancer cells and regulates the mTORC1 signaling pathway. The SLC1A5 function involves finely tuned orchestration of two domain movements that include the substrate-binding transport domain and the scaffold domain. Here, we present cryo-EM structures of human SLC1A5 and its complex with the substrate, L-glutamine in an outward-facing conformation. These structures reveal insights into the conformation of the critical ECL2a loop which connects the two domains, thus allowing rigid body movement of the transport domain throughout the transport cycle. Furthermore, the structures provide new insights into substrate recognition, which involves conformational changes in the HP2 loop. A putative cholesterol binding site was observed near the domain interface in the outward-facing state. Comparison with the previously determined inward-facing structure of SCL1A5 provides a basis for a more integrated understanding of substrate recognition and transport mechanism in the SLC1 family.

Structure of the human frataxin-bound iron-sulfur cluster assembly complex provides insight into its activation mechanism

The core machinery for de novo biosynthesis of iron-sulfur clusters (ISC), located in the mitochondria matrix, is a five-protein complex containing the cysteine desulfurase NFS1 that is activated by frataxin (FXN), scaffold protein ISCU, accessory protein ISD11, and acyl-carrier protein ACP. Deficiency in FXN leads to the loss-of-function neurodegenerative disorder Friedreich's ataxia (FRDA). Here the 3.2 Å resolution cryo-electron microscopy structure of the FXN-bound active human complex, containing two copies of the NFS1-ISD11-ACP-ISCU-FXN hetero-pentamer, delineates the interactions of FXN with other component proteins of the complex. FXN binds at the interface of two NFS1 and one ISCU subunits, modifying the local environment of a bound zinc ion that would otherwise inhibit NFS1 activity in complexes without FXN. Our structure reveals how FXN facilitates ISC production through stabilizing key loop conformations of NFS1 and ISCU at the protein-protein interfaces, and suggests how FRDA clinical mutations affect complex formation and FXN activation.

Molecular Basis for poly(A) RNP Architecture and Recognition by the Pan2-Pan3 Deadenylase

The stability of eukaryotic mRNAs is dependent on a ribonucleoprotein (RNP) complex of poly(A)-binding proteins (PABPC1/Pab1) organized on the poly(A) tail. This poly(A) RNP not only protects mRNAs from premature degradation but also stimulates the Pan2-Pan3 deadenylase complex to catalyze the first step of poly(A) tail shortening. We reconstituted this process in vitro using recombinant proteins and show that Pan2-Pan3 associates with and degrades poly(A) RNPs containing two or more Pab1 molecules. The cryo-EM structure of Pan2-Pan3 in complex with a poly(A) RNP composed of 90 adenosines and three Pab1 protomers shows how the oligomerization interfaces of Pab1 are recognized by conserved features of the deadenylase and thread the poly(A) RNA substrate into the nuclease active site. The structure reveals the basis for the periodic repeating architecture at the 3′ end of cytoplasmic mRNAs. This illustrates mechanistically how RNA-bound Pab1 oligomers act as rulers for poly(A) tail length over the mRNAs’ lifetime.

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Oligomerization of PABP on the poly(A) tail creates a series of consecutive arches

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Pan2-Pan3 deadenylase recognizes the oligomerized state of poly(A)-bound PABP

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The dimerization interface of juxtaposed PABPs creates the Pan2-Pan3 docking site

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The poly(A) RNP arches are flexible and moldable by the interacting proteins

Joachim Frank's Binding with the Ribosome

With recent technological advancements, single-particle cryogenic electron microscopy (cryo-EM) is now the technique of choice to study structure and function of biological macromolecules at near-atomic resolution. Many single-particle EM reconstruction methods necessary for these advances were pioneered by Joachim Frank, and were optimized using the ribosome as a benchmark specimen. In doing so, he made several landmark contributions to the understanding of the structure and function of ribosomes. These include the first 3D visualization of ribosome-bound transfer RNAs, the first experimentally derived structures of the primary complexes formed during the bacterial translation elongation cycle, and the critical ribosomal conformational transitions required for translation. Over the years, his laboratory studied many important functional complexes of the ribosome from both eubacterial and eukaryotic systems, including ribosomes from pathogenic organisms. This article presents a brief account of the contributions made by Joachim Frank to the ribosome field.

Visualization of biological macromolecules at near-atomic resolution: cryo-electron microscopy comes of age

Structural biology is going through a revolution as a result of transformational advances in the field of cryo-electron microscopy (cryo-EM) driven by the development of direct electron detectors and ultrastable electron microscopes. High-resolution cryo-EM images of isolated biomolecules (single particles) suspended in a thin layer of vitrified buffer are subjected to powerful image-processing algorithms, enabling near-atomic resolution structures to be determined in unprecedented numbers. Prior to these advances, electron crystallography of two-dimensional crystals and helical assemblies of proteins had established the feasibility of atomic resolution structure determination using cryo-EM. Atomic resolution single-particle analysis, without the need for crystals, now promises to resolve problems in structural biology that were intractable just a few years ago.

Single-Particle cryo-EM as a Pipeline for Obtaining Atomic Resolution Structures of Druggable Targets in Preclinical Structure-Based Drug Design

Single-particle cryo-electron microscopy (cryo-EM) and three-dimensional (3D) image processing have gained importance in the last few years to obtain atomic structures of drug targets. Obtaining atomic-resolution 3D structure better than ~2.5 Å is a standard approach in pharma companies to design and optimize therapeutic compounds against drug targets like proteins. Protein crystallography is the main technique in solving the structures of drug targets at atomic resolution. However, this technique requires protein crystals which in turn is a major bottleneck. It was not possible to obtain the structure of proteins better than 2.5 Å resolution by any other methods apart from protein crystallography until 2015. Recent advances in single-particle cryo-EM and 3D image processing have led to a resolution revolution in the field of structural biology that has led to high-resolution protein structures, thus breaking the cryo-EM resolution barriers to facilitate drug discovery. There are 24 structures solved by single-particle cryo-EM with resolution 2.5 Å or better in the EMDataBank (EMDB) till date. Among these, five cryo-EM 3D reconstructions of proteins in the EMDB have their associated coordinates deposited in Protein Data Bank (PDB), with bound inhibitor/ ligand. Thus, for the first time, single-particle cryo-EM was included in the structure-based drug design (SBDD) pipeline for solving protein structures independently or where crystallography has failed to crystallize the protein. Further, this technique can be complementary and supplementary to protein crystallography field in solving 3D structures. Thus, single-particle cryo-EM can become a standard approach in pharmaceutical industry in the design, validation, and optimization of therapeutic compounds targeting therapeutically important protein molecules during preclinical drug discovery research. The present chapter will describe briefly the history and the principles of single-particle cryo-EM and 3D image processing to obtain atomic-resolution structure of proteins and their complex with their drug targets/ligands.

Fast multiscale reconstruction for Cryo-EM

We present a multiscale reconstruction framework for single-particle analysis (SPA). The representation of three-dimensional (3D) objects with scaled basis functions permits the reconstruction of volumes at any desired scale in the real-space. This multiscale approach generates interesting opportunities in SPA for the stabilization of the initial volume problem or the 3D iterative refinement procedure. In particular, we show that reconstructions performed at coarse scale are more robust to angular errors and permit gains in computational speed. A key component of the proposed iterative scheme is its fast implementation. The costly step of reconstruction, which was previously hindering the use of advanced iterative methods in SPA, is formulated as a discrete convolution with a cost that does not depend on the number of projection directions. The inclusion of the contrast transfer function inside the imaging matrix is also done at no extra computational cost. By permitting full 3D regularization, the framework is by itself a robust alternative to direct methods for performing reconstruction in adverse imaging conditions (e.g., heavy noise, large angular misassignments, low number of projections). We present reconstructions obtained at different scales from a dataset of the 2015/2016 EMDataBank Map Challenge. The algorithm has been implemented in the Scipion package.

Structure and Conformational Dynamics of a COMPASS Histone H3K4 Methyltransferase Complex

The methylation of histone 3 lysine 4 (H3K4) is carried out by an evolutionarily conserved family of methyltransferases referred to as complex of proteins associated with Set1 (COMPASS). The activity of the catalytic SET domain (su(var)3-9, enhancer-of-zeste, and trithorax) is endowed through forming a complex with a set of core proteins that are widely shared from yeast to humans. We obtained cryo-electron microscopy (cryo-EM) maps of the yeast Set1/COMPASS core complex at overall 4.0- to 4.4-Å resolution, providing insights into its structural organization and conformational dynamics. The Cps50 C-terminal tail weaves within the complex to provide a central scaffold for assembly. The SET domain, snugly positioned at the junction of the Y-shaped complex, is extensively contacted by Cps60 (Bre2), Cps50 (Swd1), and Cps30 (Swd3). The mobile SET-I motif of the SET domain is engaged by Cps30, explaining its key role in COMPASS catalytic activity toward higher H3K4 methylation states.

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.

Single-Particle Reconstruction of Biological Molecules-Story in a Sample (Nobel Lecture)

Pictures tell a thousand words: The development of single-particle cryo-electron microscopy set the stage for high-resolution structure determination of biological molecules. In his Nobel lecture, J. Frank describes the ground-breaking discoveries that have enabled the development of cryo-EM. The method has taken biochemistry into a new era.

Single-particle XFEL 3D reconstruction of ribosome-size particles based on Fourier slice matching: requirements to reach subnanometer resolution

Three-dimensional (3D) structures of biomolecules provide insight into their functions. Using X-ray free-electron laser (XFEL) scattering experiments, it was possible to observe biomolecules that are difficult to crystallize, under conditions that are similar to their natural environment. However, resolving 3D structure from XFEL data is not without its challenges. For example, strong beam intensity is required to obtain sufficient diffraction signal and the beam incidence angles to the molecule need to be estimated for diffraction patterns with significant noise. Therefore, it is important to quantitatively assess how the experimental conditions such as the amount of data and their quality affect the expected resolution of the resulting 3D models. In this study, as an example, the restoration of 3D structure of ribosome from two-dimensional diffraction patterns created by simulation is shown. Tests are performed using the diffraction patterns simulated for different beam intensities and using different numbers of these patterns. Guidelines for selecting parameters for slice-matching 3D reconstruction procedures are established. Also, the minimum requirements for XFEL experimental conditions to obtain diffraction patterns for reconstructing molecular structures to a high-resolution of a few nanometers are discussed.

Structure of the µ-opioid receptor-Gi protein complex

The μ-opioid receptor (μOR) is a G-protein-coupled receptor (GPCR) and the target of most clinically and recreationally used opioids. The induced positive effects of analgesia and euphoria are mediated by μOR signalling through the adenylyl cyclase-inhibiting heterotrimeric G protein Gi. Here we present the 3.5 Å resolution cryo-electron microscopy structure of the μOR bound to the agonist peptide DAMGO and nucleotide-free Gi. DAMGO occupies the morphinan ligand pocket, with its N terminus interacting with conserved receptor residues and its C terminus engaging regions important for opioid-ligand selectivity. Comparison of the μOR-Gi complex to previously determined structures of other GPCRs bound to the stimulatory G protein Gs reveals differences in the position of transmembrane receptor helix 6 and in the interactions between the G protein α-subunit and the receptor core. Together, these results shed light on the structural features that contribute to the Gi protein-coupling specificity of the µOR.

Architecture of an HIV-1 reverse transcriptase initiation complex

Reverse transcription of the HIV-1 RNA genome into double-stranded DNA is a central step in infection¹ and a common target of antiretrovirals². The reaction is catalyzed by viral reverse transcriptase (RT)^3,4 that is packaged in an infectious virion along with 2 copies of dimeric viral genomic RNA⁵ and host tRNA^Lys₃, which acts as a primer for initiation of reverse transcription^6,7. Upon viral entry, initiation is slow and non-processive compared to elongation^8,9. Despite extensive efforts, the structural basis for RT function during initiation has remained a mystery. Here we apply cryo-electron microscopy (cryo-EM) to determine a three-dimensional structure of the HIV-1 RT initiation complex. RT is in an inactive polymerase conformation with open fingers and thumb and with the nucleic acid primer-template complex shifted away from the active site. The primer binding site (PBS) helix formed between tRNA^Lys₃ and HIV-1 RNA lies in the cleft of RT and is extended by additional pairing interactions. The 5′ end of the tRNA refolds and stacks on the PBS to create a long helical structure, while the remaining viral RNA forms two helical stems positioned above the RT active site, with a linker that connects these helices to the RNase H region of the PBS. Our results illustrate how RNA structure in the initiation complex alters RT conformation to decrease activity, highlighting a potential target for drug action.

X-rays in the Cryo-Electron Microscopy Era: Structural Biology's Dynamic Future

Over the past several years, single-particle cryo-electron microscopy (cryo-EM) has emerged as a leading method for elucidating macromolecular structures at near-atomic resolution, rivaling even the established technique of X-ray crystallography. Cryo-EM is now able to probe proteins as small as hemoglobin (64 kDa) while avoiding the crystallization bottleneck entirely. The remarkable success of cryo-EM has called into question the continuing relevance of X-ray methods, particularly crystallography. To say that the future of structural biology is either cryo-EM or crystallography, however, would be misguided. Crystallography remains better suited to yield precise atomic coordinates of macromolecules under a few hundred kilodaltons in size, while the ability to probe larger, potentially more disordered assemblies is a distinct advantage of cryo-EM. Likewise, crystallography is better equipped to provide high-resolution dynamic information as a function of time, temperature, pressure, and other perturbations, whereas cryo-EM offers increasing insight into conformational and energy landscapes, particularly as algorithms to deconvolute conformational heterogeneity become more advanced. Ultimately, the future of both techniques depends on how their individual strengths are utilized to tackle questions at the frontiers of structural biology. Structure determination is just one piece of a much larger puzzle: a central challenge of modern structural biology is to relate structural information to biological function. In this perspective, we share insight from several leaders in the field and examine the unique and complementary ways in which X-ray methods and cryo-EM can shape the future of structural biology.

Structural Basis for Regulated Proteolysis by the α-Secretase ADAM10

Cleavage of membrane-anchored proteins by ADAM (a disintegrin and metalloproteinase) endopeptidases plays a key role in a wide variety of biological signal transduction and protein turnover processes. Among ADAM family members, ADAM10 stands out as particularly important because it is both responsible for regulated proteolysis of Notch receptors and catalyzes the non-amyloidogenic α-secretase cleavage of the Alzheimer's precursor protein (APP). We present here the X-ray crystal structure of the ADAM10 ectodomain, which, together with biochemical and cellular studies, reveals how access to the enzyme active site is regulated. The enzyme adopts an unanticipated architecture in which the C-terminal cysteine-rich domain partially occludes the enzyme active site, preventing unfettered substrate access. Binding of a modulatory antibody to the cysteine-rich domain liberates the catalytic domain from autoinhibition, enhancing enzymatic activity toward a peptide substrate. Together, these studies reveal a mechanism for regulation of ADAM activity and offer a roadmap for its modulation.

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.

Single-particle cryo-EM using alignment by classification (ABC): the structure of Lumbricus terrestris haemoglobin

Single-particle cryogenic electron microscopy (cryo-EM) can now yield near-atomic resolution structures of biological complexes. However, the reference-based alignment algorithms commonly used in cryo-EM suffer from reference bias, limiting their applicability (also known as the 'Einstein from random noise' problem). Low-dose cryo-EM therefore requires robust and objective approaches to reveal the structural information contained in the extremely noisy data, especially when dealing with small structures. A reference-free pipeline is presented for obtaining near-atomic resolution three-dimensional reconstructions from heterogeneous ('four-dimensional') cryo-EM data sets. The methodologies integrated in this pipeline include a posteriori camera correction, movie-based full-data-set contrast transfer function determination, movie-alignment algorithms, (Fourier-space) multivariate statistical data compression and unsupervised classification, 'random-startup' three-dimensional reconstructions, four-dimensional structural refinements and Fourier shell correlation criteria for evaluating anisotropic resolution. The procedures exclusively use information emerging from the data set itself, without external 'starting models'. Euler-angle assignments are performed by angular reconstitution rather than by the inherently slower projection-matching approaches. The comprehensive 'ABC-4D' pipeline is based on the two-dimensional reference-free 'alignment by classification' (ABC) approach, where similar images in similar orientations are grouped by unsupervised classification. Some fundamental differences between X-ray crystallography versus single-particle cryo-EM data collection and data processing are discussed. The structure of the giant haemoglobin from Lumbricus terrestris at a global resolution of ∼3.8 Å is presented as an example of the use of the ABC-4D procedure.

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.

Phase-plate cryo-EM structure of a class B GPCR-G-protein complex

Class B G-protein-coupled receptors are major targets for the treatment of chronic diseases, such as osteoporosis, diabetes and obesity. Here we report the structure of a full-length class B receptor, the calcitonin receptor, in complex with peptide ligand and heterotrimeric Gαsβγ protein determined by Volta phase-plate single-particle cryo-electron microscopy. The peptide agonist engages the receptor by binding to an extended hydrophobic pocket facilitated by the large outward movement of the extracellular ends of transmembrane helices 6 and 7. This conformation is accompanied by a 60° kink in helix 6 and a large outward movement of the intracellular end of this helix, opening the bundle to accommodate interactions with the α5-helix of Gαs. Also observed is an extended intracellular helix 8 that contributes to both receptor stability and functional G-protein coupling via an interaction with the Gβ subunit. This structure provides a new framework for understanding G-protein-coupled receptor function.