Advances in cryo-ET data processing: meeting the demands of visual proteomics.

Cryogenic electron tomography (cryo-ET), a method that enables the viewing of biomolecules in near-native environments at high resolution, is rising in accessibility and applicability. Over the past several years, once slow sample preparation and data collection procedures have seen innovations which enable rapid collection of the large datasets required for attaining high resolution structures. Increased data availability has provided a driving force for exciting improvements in cryo-ET data processing methodologies throughout the entire processing pipeline and the development of accessible graphical user interfaces (GUIs) that enable individuals inexperienced in computational fields to convert raw tilt series into 3D structures. These advances in data processing are enabling cryo-ET to attain higher resolution and extending its applicability to more complex samples.

Joint micrograph denoising and protein localization in cryo-electron microscopy.

Cryo-electron microscopy (cryo-EM) is an imaging technique that allows the visualization of proteins and macromolecular complexes at near-atomic resolution. The low electron doses used to prevent radiation damage to the biological samples result in images where the power of noise is 100 times stronger than that of the signal. Accurate identification of proteins from these low signal-to-noise ratio (SNR) images is a critical task, as the detected positions serve as inputs for the downstream 3D structure determination process. Current methods either fail to identify all true positives or result in many false positives, especially when analyzing images from smaller-sized proteins that exhibit extremely low contrast, or require manual labeling that can take days to complete. Acknowledging the fact that accurate protein identification is dependent upon the visual interpretability of micrographs, we propose a framework that can perform denoising and detection in a joint manner and enable particle localization under extremely low SNR conditions using self-supervised denoising and particle identification from sparsely annotated data. We validate our approach on three challenging single-particle cryo-EM datasets and projection images from one cryo-electron tomography dataset with extremely low SNR, showing that it outperforms existing state-of-the-art methods used for cryo-EM image analysis by a significant margin. We also evaluate the performance of our algorithm under decreasing SNR conditions and show that our method is more robust to noise than competing methods.

nextPYP: a comprehensive and scalable platform for characterizing protein variability in situ using single-particle cryo-electron tomography.

Single-particle cryo-electron tomography is an emerging technique capable of determining the structure of proteins imaged within the native context of cells at molecular resolution. While high-throughput techniques for sample preparation and tilt-series acquisition are beginning to provide sufficient data to allow structural studies of proteins at physiological concentrations, the complex data analysis pipeline and the demanding storage and computational requirements pose major barriers for the development and broader adoption of this technology. Here, we present a scalable, end-to-end framework for single-particle cryo-electron tomography data analysis from on-the-fly pre-processing of tilt series to high-resolution refinement and classification, which allows efficient analysis and visualization of datasets with hundreds of tilt series and hundreds of thousands of particles. We validate our approach using in vitro and cellular datasets, demonstrating its effectiveness at achieving high-resolution and revealing conformational heterogeneity in situ. The framework is made available through an intuitive and easy-to-use computer application, nextPYP ( http://nextpyp.app ).

Molecular architecture and conservation of an immature human endogenous retrovirus.

The human endogenous retrovirus K (HERV-K) is the most recently acquired endogenous retrovirus in the human genome and is activated and expressed in many cancers and amyotrophic lateral sclerosis. We present the immature HERV-K capsid structure at 3.2 Å resolution determined from native virus-like particles using cryo-electron tomography and subtomogram averaging. The structure shows a hexamer unit oligomerized through a 6-helix bundle, which is stabilized by a small molecule analogous to IP6 in immature HIV-1 capsid. The HERV-K immature lattice is assembled via highly conserved dimer and trimer interfaces, as detailed through all-atom molecular dynamics simulations and supported by mutational studies. A large conformational change mediated by the linker between the N-terminal and the C-terminal domains of CA occurs during HERV-K maturation. Comparison between HERV-K and other retroviral immature capsid structures reveals a highly conserved mechanism for the assembly and maturation of retroviruses across genera and evolutionary time.

Molecular architecture and conservation of an immature human endogenous retrovirus.

A significant part of the human genome consists of endogenous retroviruses sequences. Human endogenous retrovirus K (HERV-K) is the most recently acquired endogenous retrovirus, is activated and expressed in many cancers and amyotrophic lateral sclerosis and possibly contributes to the aging process. To understand the molecular architecture of endogenous retroviruses, we determined the structure of immature HERV-K from native virus-like particles (VLPs) using cryo-electron tomography and subtomogram averaging (cryoET STA). The HERV-K VLPs show a greater distance between the viral membrane and immature capsid lattice, correlating with the presence of additional peptides, SP1 and p15, between the capsid (CA) and matrix (MA) proteins compared to the other retroviruses. The resulting cryoET STA map of the immature HERV-K capsid at 3.2 Å resolution shows a hexamer unit oligomerized through a 6-helix bundle which is further stabilized by a small molecule in the same way as the IP6 in immature HIV-1 capsid. The HERV-K immature CA hexamer assembles into the immature lattice via highly conserved dimmer and trimer interfaces, whose interactions were further detailed through all-atom molecular dynamics simulations and supported by mutational studies. A large conformational change mediated by the flexible linker between the N-terminal and the C-terminal domains of CA occurs between the immature and the mature HERV-K capsid protein, analogous to HIV-1. Comparison between HERV-K and other retroviral immature capsid structures reveals a highly conserved mechanism for the assembly and maturation of retroviruses across genera and evolutionary time.

Structural basis for breadth development in the HIV-1 V3-glycan targeting DH270 antibody clonal lineage.

Antibody affinity maturation enables adaptive immune responses to a wide range of pathogens. In some individuals broadly neutralizing antibodies develop to recognize rapidly mutating pathogens with extensive sequence diversity. Vaccine design for pathogens such as HIV-1 and influenza has therefore focused on recapitulating the natural affinity maturation process. Here, we determine structures of antibodies in complex with HIV-1 Envelope for all observed members and ancestral states of the broadly neutralizing HIV-1 V3-glycan targeting DH270 antibody clonal B cell lineage. These structures track the development of neutralization breadth from the unmutated common ancestor and define affinity maturation at high spatial resolution. By elucidating contacts mediated by key mutations at different stages of antibody development we identified sites on the epitope-paratope interface that are the focus of affinity optimization. Thus, our results identify bottlenecks on the path to natural affinity maturation and reveal solutions for these that will inform immunogen design aimed at eliciting a broadly neutralizing immune response by vaccination.

Structure and dynamics of the Arabidopsis O-fucosyltransferase SPINDLY.

SPINDLY (SPY) in Arabidopsis thaliana is a novel nucleocytoplasmic protein O-fucosyltransferase (POFUT), which regulates diverse developmental processes. Sequence analysis indicates that SPY is distinct from ER-localized POFUTs and contains N-terminal tetratricopeptide repeats (TPRs) and a C-terminal catalytic domain resembling the O-linked-N-acetylglucosamine (GlcNAc) transferases (OGTs). However, the structural feature that determines the distinct enzymatic selectivity of SPY remains unknown. Here we report the cryo-electron microscopy (cryo-EM) structure of SPY and its complex with GDP-fucose, revealing distinct active-site features enabling GDP-fucose instead of UDP-GlcNAc binding. SPY forms an antiparallel dimer instead of the X-shaped dimer in human OGT, and its catalytic domain interconverts among multiple conformations. Analysis of mass spectrometry, co-IP, fucosylation activity, and cryo-EM data further demonstrates that the N-terminal disordered peptide in SPY contains trans auto-fucosylation sites and inhibits the POFUT activity, whereas TPRs 1-5 dynamically regulate SPY activity by interfering with protein substrate binding.

Structures of trehalose-6-phosphate synthase, Tps1, from the fungal pathogen Cryptococcus neoformans: a target for novel antifungals.

Invasive fungal diseases are a major threat to human health, resulting in more than 1.5 million deaths worldwide each year. Yet the arsenal of antifungal therapeutics remains limited and is in dire need of novel drugs that target additional fungal-specific biosynthetic pathways. One such pathway involves the biosynthesis of trehalose. Trehalose is a non-reducing disaccharide composed of two molecules of glucose that is required for pathogenic fungi, including Candida albicans and Cryptococcus neoformans, to survive in their human hosts. Trehalose biosynthesis is a two-step process in fungal pathogens. Trehalose-6-phosphate synthase (Tps1) converts UDP-glucose and glucose-6-phosphate to trehalose-6-phosphate (T6P). Subsequently, trehalose-6-phosphate phosphatase (Tps2) converts T6P to trehalose. The trehalose biosynthesis pathway has been identified as a top candidate for novel antifungal development based on quality, occurrence, specificity, and assay development. However, there are currently no known antifungal agents that target this pathway. As initial steps to develop Tps1 from Cryptococcus neoformans (CnTps1) as a drug target, we report the structures of full-length apo CnTps1 and CnTps1 in complex with uridine diphosphate (UDP) and glucose-6-phosphate (G6P). Both CnTps1 structures are tetramers and display D2 (222) molecular symmetry. Comparison of these two structures reveals significant movement towards the catalytic pocket by the N-terminus upon ligand binding and identifies key residues required for substrate-binding, which are conserved amongst other Tps1 enzymes, as well as residues that stabilize the tetramer. Intriguingly, an intrinsically disordered domain (IDD), encompassing residues M209 to I300, which is conserved amongst Cryptococcal species and closely related Basidiomycetes, extends from each subunit of the tetramer into the "solvent" but is not visible in the density maps. Although, activity assays revealed that the highly conserved IDD is not required for catalysis in vitro, we hypothesize that the IDD is required for C. neoformans Tps1-dependent thermotolerance and osmotic stress survival. Characterization of the substrate specificity of CnTps1 revealed that UDP-galactose, an epimer of UDP-glucose, is a very poor substrate and inhibitor of the enzyme and highlights the exquisite substrate specificity of Tps1. In toto, these studies expand our knowledge of trehalose biosynthesis in Cryptococcus and highlight the potential of developing antifungal therapeutics that disrupt the synthesis of this disaccharide or the formation of a functional tetramer and the use of cryo-EM in the structural characterization of CnTps1-ligand/drug complexes.

Multiple-image super-resolution of cryo-electron micrographs based on deep internal learning.

Single-particle cryo-electron microscopy (cryo-EM) is a powerful imaging modality capable of visualizing proteins and macromolecular complexes at near-atomic resolution. The low electron-doses used to prevent radiation damage to the biological samples, however, result in images where the power of the noise is 100 times greater than the power of the signal. To overcome these low signal-to-noise ratios (SNRs), hundreds of thousands of particle projections are averaged to determine the three-dimensional structure of the molecule of interest. The sampling requirements of high-resolution imaging impose limitations on the pixel sizes that can be used for acquisition, limiting the size of the field of view and requiring data collection sessions of several days to accumulate sufficient numbers of particles. Meanwhile, recent image super-resolution (SR) techniques based on neural networks have shown state-of-the-art performance on natural images. Building on these advances, here, we present a multiple-image SR algorithm based on deep internal learning designed specifically to work under low-SNR conditions. Our approach leverages the internal image statistics of cryo-EM movies and does not require training on ground-truth data. When applied to single-particle datasets of apoferritin and T20S proteasome, we show that the resolution of the 3D structure obtained from SR micrographs can surpass the limits imposed by the imaging system. Our results indicate that the combination of low magnification imaging with in silico image SR has the potential to accelerate cryo-EM data collection by virtue of including more particles in each exposure and doing so without sacrificing resolution.

Automated systematic evaluation of cryo-EM specimens with SmartScope.

Finding the conditions to stabilize a macromolecular target for imaging remains the most critical barrier to determining its structure by cryo-electron microscopy (cryo-EM). While automation has significantly increased the speed of data collection, specimens are still screened manually, a laborious and subjective task that often determines the success of a project. Here, we present SmartScope, the first framework to streamline, standardize, and automate specimen evaluation in cryo-EM. SmartScope employs deep-learning-based object detection to identify and classify features suitable for imaging, allowing it to perform thorough specimen screening in a fully automated manner. A web interface provides remote control over the automated operation of the microscope in real time and access to images and annotation tools. Manual annotations can be used to re-train the feature recognition models, leading to improvements in performance. Our automated tool for systematic evaluation of specimens streamlines structure determination and lowers the barrier of adoption for cryo-EM.

High-resolution structure determination using high-throughput electron cryo-tomography.

Tomographic reconstruction of frozen-hydrated specimens followed by extraction and averaging of sub-tomograms has successfully been used to determine the structure of macromolecules in their native environment at resolutions that are high enough to reveal molecular level interactions. The low throughput characteristic of tomographic data acquisition combined with the complex data-analysis pipeline that is required to obtain high-resolution maps, however, has limited the applicability of this technique to favorable samples or to resolutions that are too low to provide useful mechanistic information. Recently, beam image-shift electron cryo-tomography (BISECT), a strategy to significantly accelerate the acquisition of tilt series without sacrificing image quality, was introduced. The ability to produce thousands of high-quality tilt series during a single microscope session, however, introduces significant bottlenecks in the downstream data analysis, which has so far relied on specialized pipelines. Here, recent advances in accurate estimation of the contrast transfer function and self-tuning exposure-weighting routines that contribute to improving the resolution and streamlining the structure-determination process using sub-volume averaging are reviewed. Ultimately, the combination of automated data-driven techniques for image analysis together with high-throughput strategies for tilt-series acquisition will pave the way for tomography to become the technique of choice for in situ structure determination.

Structural basis of NPR1 in activating plant immunity.

NPR1 is a master regulator of the defence transcriptome induced by the plant immune signal salicylic acid1-4. Despite the important role of NPR1 in plant immunity5-7, understanding of its regulatory mechanisms has been hindered by a lack of structural information. Here we report cryo-electron microscopy and crystal structures of Arabidopsis NPR1 and its complex with the transcription factor TGA3. Cryo-electron microscopy analysis reveals that NPR1 is a bird-shaped homodimer comprising a central Broad-complex, Tramtrack and Bric-à-brac (BTB) domain, a BTB and carboxyterminal Kelch helix bundle, four ankyrin repeats and a disordered salicylic-acid-binding domain. Crystal structure analysis reveals a unique zinc-finger motif in BTB for interacting with ankyrin repeats and mediating NPR1 oligomerization. We found that, after stimulation, salicylic-acid-induced folding and docking of the salicylic-acid-binding domain onto ankyrin repeats is required for the transcriptional cofactor activity of NPR1, providing a structural explanation for a direct role of salicylic acid in regulating NPR1-dependent gene expression. Moreover, our structure of the TGA32-NPR12-TGA32 complex, DNA-binding assay and genetic data show that dimeric NPR1 activates transcription by bridging two fatty-acid-bound TGA3 dimers to form an enhanceosome. The stepwise assembly of the NPR1-TGA complex suggests possible hetero-oligomeric complex formation with other transcription factors, revealing how NPR1 reprograms the defence transcriptome.

Redox-sensitive E2 Rad6 controls cellular response to oxidative stress via K63-linked ubiquitination of ribosomes.

Protein ubiquitination is an essential process that rapidly regulates protein synthesis, function, and fate in dynamic environments. Within its non-proteolytic functions, we showed that K63-linked polyubiquitinated conjugates heavily accumulate in yeast cells exposed to oxidative stress, stalling ribosomes at elongation. K63-ubiquitinated conjugates accumulate mostly because of redox inhibition of the deubiquitinating enzyme Ubp2; however, the role and regulation of ubiquitin-conjugating enzymes (E2) in this pathway remained unclear. Here, we show that the E2 Rad6 associates and modifies ribosomes during stress. We further demonstrate that Rad6 and its human homolog UBE2A are redox regulated by forming a reversible disulfide with the E1 ubiquitin-activating enzyme (Uba1). This redox regulation is part of a negative feedback regulation, which controls the levels of K63 ubiquitination under stress. Finally, we show that Rad6 activity is necessary to regulate translation, antioxidant defense, and adaptation to stress, thus providing an additional physiological role for this multifunctional enzyme.

Data-driven determination of number of discrete conformations in single-particle cryo-EM.

BACKGROUND AND OBJECTIVE: One of the strengths of single-particle cryo-EM compared to other structural determination techniques is its ability to image heterogeneous samples containing multiple molecular species, different oligomeric states or distinct conformations. This is achieved using routines for in-silico 3D classification that are now well established in the field and have successfully been used to characterize the structural heterogeneity of important biomolecules. These techniques, however, rely on expert-user knowledge and trial-and-error experimentation to determine the correct number of conformations, making it a labor intensive, subjective, and difficult to reproduce procedure. METHODS: We propose an approach to address the problem of automatically determining the number of discrete conformations present in heterogeneous single-particle cryo-EM datasets. We do this by systematically evaluating all possible partitions of the data and selecting the result that maximizes the average variance of similarities measured between particle images and the corresponding 3D reconstructions. RESULTS: Using this strategy, we successfully analyzed datasets of heterogeneous protein complexes, including: 1) in-silico mixtures obtained by combining closely related antibody-bound HIV-1 Env trimers and other important membrane channels, and 2) naturally occurring mixtures from diverse and dynamic protein complexes representing varying degrees of structural heterogeneity and conformational plasticity. CONCLUSIONS: The availability of unsupervised strategies for 3D classification combined with existing approaches for fully automatic pre-processing and 3D refinement, represents an important step towards converting single-particle cryo-EM into a high-throughput technique.

Fab-dimerized glycan-reactive antibodies are a structural category of natural antibodies.

Natural antibodies (Abs) can target host glycans on the surface of pathogens. We studied the evolution of glycan-reactive B cells of rhesus macaques and humans using glycosylated HIV-1 envelope (Env) as a model antigen. 2G12 is a broadly neutralizing Ab (bnAb) that targets a conserved glycan patch on Env of geographically diverse HIV-1 strains using a unique heavy-chain (VH) domain-swapped architecture that results in fragment antigen-binding (Fab) dimerization. Here, we describe HIV-1 Env Fab-dimerized glycan (FDG)-reactive bnAbs without VH-swapped domains from simian-human immunodeficiency virus (SHIV)-infected macaques. FDG Abs also recognized cell-surface glycans on diverse pathogens, including yeast and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike. FDG precursors were expanded by glycan-bearing immunogens in macaques and were abundant in HIV-1-naive humans. Moreover, FDG precursors were predominately mutated IgM+IgD+CD27+, thus suggesting that they originated from a pool of antigen-experienced IgM+ or marginal zone B cells.

Beam image-shift accelerated data acquisition for near-atomic resolution single-particle cryo-electron tomography.

Tomographic reconstruction of cryopreserved specimens imaged in an electron microscope followed by extraction and averaging of sub-volumes has been successfully used to derive atomic models of macromolecules in their biological environment. Eliminating biochemical isolation steps required by other techniques, this method opens up the cell to in-situ structural studies. However, the need to compensate for errors in targeting introduced during mechanical navigation of the specimen significantly slows down tomographic data collection thus limiting its practical value. Here, we introduce protocols for tilt-series acquisition and processing that accelerate data collection speed by up to an order of magnitude and improve map resolution compared to existing approaches. We achieve this by using beam-image shift to multiply the number of areas imaged at each stage position, by integrating geometrical constraints during imaging to achieve high precision targeting, and by performing per-tilt astigmatic CTF estimation and data-driven exposure weighting to improve final map resolution. We validated our beam image-shift electron cryo-tomography (BISECT) approach by determining the structure of a low molecular weight target (~300 kDa) at 3.6 Å resolution where density for individual side chains is clearly resolved.

Structural Basis for Virulence Activation of Francisella tularensis.

The bacterium Francisella tularensis (Ft) is one of the most infectious agents known. Ft virulence is controlled by a unique combination of transcription regulators: the MglA-SspA heterodimer, PigR, and the stress signal, ppGpp. MglA-SspA assembles with the σ70-associated RNAP holoenzyme (RNAPσ70), forming a virulence-specialized polymerase. These factors activate Francisella pathogenicity island (FPI) gene expression, which is required for virulence, but the mechanism is unknown. Here we report FtRNAPσ70-promoter-DNA, FtRNAPσ70-(MglA-SspA)-promoter DNA, and FtRNAPσ70-(MglA-SspA)-ppGpp-PigR-promoter DNA cryo-EM structures. Structural and genetic analyses show MglA-SspA facilitates σ70 binding to DNA to regulate virulence and virulence-enhancing genes. Our Escherichia coli RNAPσ70-homodimeric EcSspA structure suggests this is a general SspA-transcription regulation mechanism. Strikingly, our FtRNAPσ70-(MglA-SspA)-ppGpp-PigR-DNA structure reveals ppGpp binding to MglA-SspA tethers PigR to promoters. PigR in turn recruits FtRNAP αCTDs to DNA UP elements. Thus, these studies unveil a unique mechanism for Ft pathogenesis involving a virulence-specialized RNAP that employs two (MglA-SspA)-based strategies to activate virulence genes.

Structural impact of K63 ubiquitin on yeast translocating ribosomes under oxidative stress.

Subpopulations of ribosomes are responsible for fine tuning the control of protein synthesis in dynamic environments. K63 ubiquitination of ribosomes has emerged as a new posttranslational modification that regulates protein synthesis during cellular response to oxidative stress. K63 ubiquitin, a type of ubiquitin chain that functions independently of the proteasome, modifies several sites at the surface of the ribosome, however, we lack a molecular understanding on how this modification affects ribosome structure and function. Using cryoelectron microscopy (cryo-EM), we resolved the first three-dimensional (3D) structures of K63 ubiquitinated ribosomes from oxidatively stressed yeast cells at 3.5-3.2 Å resolution. We found that K63 ubiquitinated ribosomes are also present in a polysome arrangement, similar to that observed in yeast polysomes, which we determined using cryoelectron tomography (cryo-ET). We further showed that K63 ubiquitinated ribosomes are captured uniquely at the rotated pretranslocation stage of translation elongation. In contrast, cryo-EM structures of ribosomes from mutant cells lacking K63 ubiquitin resolved at 4.4-2.7 Å showed 80S ribosomes represented in multiple states of translation, suggesting that K63 ubiquitin regulates protein synthesis at a selective stage of elongation. Among the observed structural changes, ubiquitin mediates the destabilization of proteins in the 60S P-stalk and in the 40S beak, two binding regions of the eukaryotic elongation factor eEF2. These changes would impact eEF2 function, thus, inhibiting translocation. Our findings help uncover the molecular effects of K63 ubiquitination on ribosomes, providing a model of translation control during oxidative stress, which supports elongation halt at pretranslocation.

Single-particle cryo-electron microscopy: Mathematical theory, computational challenges, and opportunities.

In recent years, an abundance of new molecular structures have been elucidated using cryo-electron microscopy (cryo-EM), largely due to advances in hardware technology and data processing techniques. Owing to these new exciting developments, cryo-EM was selected by Nature Methods as Method of the Year 2015, and the Nobel Prize in Chemistry 2017 was awarded to three pioneers in the field. The main goal of this article is to introduce the challenging and exciting computational tasks involved in reconstructing 3-D molecular structures by cryo-EM. Determining molecular structures requires a wide range of computational tools in a variety of fields, including signal processing, estimation and detection theory, high-dimensional statistics, convex and non-convex optimization, spectral algorithms, dimensionality reduction, and machine learning. The tools from these fields must be adapted to work under exceptionally challenging conditions, including extreme noise levels, the presence of missing data, and massively large datasets as large as several Terabytes. In addition, we present two statistical models: multi-reference alignment and multi-target detection, that abstract away much of the intricacies of cryo-EM, while retaining some of its essential features. Based on these abstractions, we discuss some recent intriguing results in the mathematical theory of cryo-EM, and delineate relations with group theory, invariant theory, and information theory.