Electron Cryo-microscopy Structure of Ebola Virus Nucleoprotein Reveals a Mechanism for Nucleocapsid-like Assembly.

Ebola virus nucleoprotein (eNP) assembles into higher-ordered structures that form the viral nucleocapsid (NC) and serve as the scaffold for viral RNA synthesis. However, molecular insights into the NC assembly process are lacking. Using a hybrid approach, we characterized the NC-like assembly of eNP, identified novel regulatory elements, and described how these elements impact function. We generated a three-dimensional structure of the eNP NC-like assembly at 5.8 Å using electron cryo-microscopy and identified a new regulatory role for eNP helices α22-α23. Biochemical, biophysical, and mutational analyses revealed that inter-eNP contacts within α22-α23 are critical for viral NC assembly and regulate viral RNA synthesis. These observations suggest that the N terminus and α22-α23 of eNP function as context-dependent regulatory modules (CDRMs). Our current study provides a framework for a structural mechanism for NC-like assembly and a new therapeutic target.

Structural Insights of Transcriptionally Active, Full-Length Androgen Receptor Coactivator Complexes.

Steroid receptors activate gene transcription by recruiting coactivators to initiate transcription of their target genes. For most nuclear receptors, the ligand-dependent activation function domain-2 (AF-2) is a primary contributor to the nuclear receptor (NR) transcriptional activity. In contrast to other steroid receptors, such as ERα, the activation function of androgen receptor (AR) is largely dependent on its ligand-independent AF-1 located in its N-terminal domain (NTD). It remains unclear why AR utilizes a different AF domain from other receptors despite that NRs share similar domain organizations. Here, we present cryoelectron microscopy (cryo-EM) structures of DNA-bound full-length AR and its complex structure with key coactivators, SRC-3 and p300. AR dimerization follows a unique head-to-head and tail-to-tail manner. Unlike ERα, AR directly contacts a single SRC-3 and p300. The AR NTD is the primary site for coactivator recruitment. The structures provide a basis for understanding assembly of the AR:coactivator complex and its domain contributions for coactivator assembly and transcriptional regulation.

Improving resolution and resolvability of single-particle cryoEM structures using Gaussian mixture models.

Cryogenic electron microscopy is widely used in structural biology, but its resolution is often limited by the dynamics of the macromolecule. Here we developed a refinement protocol based on Gaussian mixture models that integrates particle orientation and conformation estimation and improves the alignment for flexible domains of protein structures. We demonstrated this protocol on multiple datasets, resulting in improved resolution and resolvability, locally and globally, by visual and quantitative measures.

Cryo-ET of Toxoplasma parasites gives subnanometer insight into tubulin-based structures.

Tubulin is a conserved protein that polymerizes into different forms of filamentous structures in Toxoplasma gondii, an obligate intracellular parasite in the phylum Apicomplexa. Two key tubulin-containing cytoskeletal components are subpellicular microtubules (SPMTs) and conoid fibrils (CFs). The SPMTs help maintain shape and gliding motility, while the CFs are implicated in invasion. Here, we use cryogenic electron tomography to determine the molecular structures of the SPMTs and CFs in vitrified intact and detergent-extracted parasites. Subvolume densities from detergent-extracted parasites yielded averaged density maps at subnanometer resolutions, and these were related back to their architecture in situ. An intralumenal spiral lines the interior of the 13-protofilament SPMTs, revealing a preferred orientation of these microtubules relative to the parasite's long axis. Each CF is composed of nine tubulin protofilaments that display a comma-shaped cross-section, plus additional associated components. Conoid protrusion, a crucial step in invasion, is associated with an altered pitch of each CF. The use of basic building blocks of protofilaments and different accessory proteins in one organism illustrates the versatility of tubulin to form two distinct types of assemblies, SPMTs and CFs.

Deep learning-based mixed-dimensional Gaussian mixture model for characterizing variability in cryo-EM.

Structural flexibility and/or dynamic interactions with other molecules is a critical aspect of protein function. Cryogenic electron microscopy (cryo-EM) provides direct visualization of individual macromolecules sampling different conformational and compositional states. While numerous methods are available for computational classification of discrete states, characterization of continuous conformational changes or large numbers of discrete state without human supervision remains challenging. Here we present e2gmm, a machine learning algorithm to determine a conformational landscape for proteins or complexes using a three-dimensional Gaussian mixture model mapped onto two-dimensional particle images in known orientations. Using a deep neural network architecture, e2gmm can automatically resolve the structural heterogeneity within the protein complex and map particles onto a small latent space describing conformational and compositional changes. This system presents a more intuitive and flexible representation than other manifold methods currently in use. We demonstrate this method on both simulated data and three biological systems to explore compositional and conformational changes at a range of scales. The software is distributed as part of EMAN2.

A complete data processing workflow for cryo-ET and subtomogram averaging.

Electron cryotomography is currently the only method capable of visualizing cells in three dimensions at nanometer resolutions. While modern instruments produce massive amounts of tomography data containing extremely rich structural information, data processing is very labor intensive and the results are often limited by the skills of the personnel rather than the data. We present an integrated workflow that covers the entire tomography data processing pipeline, from automated tilt series alignment to subnanometer resolution subtomogram averaging. Resolution enhancement is made possible through the use of per-particle per-tilt contrast transfer function correction and alignment. The workflow greatly reduces human bias, increases throughput and more closely approaches data-limited resolution for subtomogram averaging in both purified macromolecules and cells.

Structural and functional analyses of photosystem II in the marine diatom Phaeodactylum tricornutum.

A descendant of the red algal lineage, diatoms are unicellular eukaryotic algae characterized by thylakoid membranes that lack the spatial differentiation of stroma and grana stacks found in green algae and higher plants. While the photophysiology of diatoms has been studied extensively, very little is known about the spatial organization of the multimeric photosynthetic protein complexes within their thylakoid membranes. Here, using cryo-electron tomography, proteomics, and biophysical analyses, we elucidate the macromolecular composition, architecture, and spatial distribution of photosystem II complexes in diatom thylakoid membranes. Structural analyses reveal 2 distinct photosystem II populations: loose clusters of complexes associated with antenna proteins and compact 2D crystalline arrays of dimeric cores. Biophysical measurements reveal only 1 photosystem II functional absorption cross section, suggesting that only the former population is photosynthetically active. The tomographic data indicate that the arrays of photosystem II cores are physically separated from those associated with antenna proteins. We hypothesize that the islands of photosystem cores are repair stations, where photodamaged proteins can be replaced. Our results strongly imply convergent evolution between the red and the green photosynthetic lineages toward spatial segregation of dynamic, functional microdomains of photosystem II supercomplexes.

Flagellum couples cell shape to motility in Trypanosoma brucei.

In the unicellular parasite Trypanosoma brucei, the causative agent of human African sleeping sickness, complex swimming behavior is driven by a flagellum laterally attached to the long and slender cell body. Using microfluidic assays, we demonstrated that T. brucei can penetrate through an orifice smaller than its maximum diameter. Efficient motility and penetration depend on active flagellar beating. To understand how active beating of the flagellum affects the cell body, we genetically engineered T. brucei to produce anucleate cytoplasts (zoids and minis) with different flagellar attachment configurations and different swimming behaviors. We used cryo-electron tomography (cryo-ET) to visualize zoids and minis vitrified in different motility states. We showed that flagellar wave patterns reflective of their motility states are coupled to cytoskeleton deformation. Based on these observations, we propose a mechanism for how flagellum beating can deform the cell body via a flexible connection between the flagellar axoneme and the cell body. This mechanism may be critical for T. brucei to disseminate in its host through size-limiting barriers.

Convolutional neural networks for automated annotation of cellular cryo-electron tomograms.

Cellular electron cryotomography offers researchers the ability to observe macromolecules frozen in action in situ, but a primary challenge with this technique is identifying molecular components within the crowded cellular environment. We introduce a method that uses neural networks to dramatically reduce the time and human effort required for subcellular annotation and feature extraction. Subsequent subtomogram classification and averaging yield in situ structures of molecular components of interest. The method is available in the EMAN2.2 software package.

Automation and assessment of de novo modeling with Pathwalking in near atomic resolution cryoEM density maps.

With the rapidly growing number of macromolecular structures solved to near-atomic resolution using electron cryomicroscopy (cryoEM), map interpretation and model building directly from the density without the use of structural templates has become increasingly important. As part of the 2015/2016 Map and Model Challenge, we attempted to assess our latest de novo modeling tool, Pathwalking, in terms of performance and usability, as well as identify areas for future improvements. In total, we applied Pathwalking to six density maps between 3 and 4.5 Šresolution selected from the challenge data sets. In five of the six cases, Pathwalking was able to accurately determine the protein fold and in three of these cases, the final all atom model had less than 1.6 ŠRMSD when compared to the known structure. Model building and refinement was nearly completely automated, used default parameters and took less than 30 min to complete a refined all atom model. A direct outgrowth of this work was a more streamlined automated command line Pathwalking utility, as well as a novel sequence assignment and optimization routine, which attempts to register sidechain density with expected side chain volume. In total, Pathwalking offers a nearly complete, robust and efficient method for constructing atomistic protein structures directly from a density map without the aid of a template.

New software tools in EMAN2 inspired by EMDatabank map challenge.

EMAN2 is an extensible software suite with complete workflows for performing high-resolution single particle analysis, 2-D and 3-D heterogeneity analysis, and subtomogram averaging, among other tasks. Participation in the recent CryoEM Map Challenge sponsored by the EMDatabank led to a number of significant improvements to the single particle analysis process in EMAN2. A new convolutional neural network particle picker was developed, which dramatically improves particle picking accuracy for difficult data sets. A new particle quality metric capable of accurately identifying "bad" particles with a high degree of accuracy, no human input, and a negligible amount of additional computation, has been introduced, and this now serves as a replacement for earlier human-biased methods. The way 3-D single particle reconstructions are filtered has been altered to be more comparable to the filter applied in several other popular software packages, dramatically improving the appearance of sidechains in high-resolution structures. Finally, an option has been added to perform local resolution-based iterative filtration, resulting in local resolution improvements in many maps.

High resolution single particle refinement in EMAN2.1.

EMAN2.1 is a complete image processing suite for quantitative analysis of grayscale images, with a primary focus on transmission electron microscopy, with complete workflows for performing high resolution single particle reconstruction, 2-D and 3-D heterogeneity analysis, random conical tilt reconstruction and subtomogram averaging, among other tasks. In this manuscript we provide the first detailed description of the high resolution single particle analysis pipeline and the philosophy behind its approach to the reconstruction problem. High resolution refinement is a fully automated process, and involves an advanced set of heuristics to select optimal algorithms for each specific refinement task. A gold standard FSC is produced automatically as part of refinement, providing a robust resolution estimate for the final map, and this is used to optimally filter the final CTF phase and amplitude corrected structure. Additional methods are in-place to reduce model bias during refinement, and to permit cross-validation using other computational methods.

De Novo modeling in cryo-EM density maps with Pathwalking.

As electron cryo-microscopy (cryo-EM) can now frequently achieve near atomic resolution, accurate interpretation of these density maps in terms of atomistic detail has become paramount in deciphering macromolecular structure and function. However, there are few software tools for modeling protein structure from cryo-EM density maps in this resolution range. Here, we present an extension of our original Pathwalking protocol, which can automatically trace a protein backbone directly from a near-atomic resolution (3-6Å) density map. The original Pathwalking approach utilized a Traveling Salesman Problem solver for backbone tracing, but manual adjustment was still required during modeling. In the new version, human intervention is minimized and we provide a more robust approach for backbone modeling. This includes iterative secondary structure identification, termini detection and the ability to model multiple subunits without prior segmentation. Overall, the new Pathwalking procedure provides a more complete and robust tool for annotating protein structure function in near-atomic resolution density maps.

Rendering protein structures inside cells at the atomic level with Unreal Engine.

While the recent development of cryogenic electron tomography (CryoET) makes it possible to identify various macromolecules inside cells and determine their structure at near-atomic resolution, it remains challenging to visualize the complex cellular environment at the atomic level. One of the main hurdles in cell visualization is to render the millions of molecules in real time computationally. Here, using a video game engine, we demonstrate the capability of rendering massive biological macromolecules at the atomic level within their native environment. To facilitate the visualization, we also provide tools that help the interactive navigation inside the cells, as well as software that converts protein structures identified using CryoET to a scene that can be explored with the game engine.

Centriole and transition zone structures in photoreceptor cilia revealed by cryo-electron tomography.

Primary cilia mediate sensory signaling in multiple organisms and cell types but have structures adapted for specific roles. Structural defects in them lead to devastating diseases known as ciliopathies in humans. Key to their functions are structures at their base: the basal body, the transition zone, the "Y-shaped links," and the "ciliary necklace." We have used cryo-electron tomography with subtomogram averaging and conventional transmission electron microscopy to elucidate the structures associated with the basal region of the "connecting cilia" of rod outer segments in mouse retina. The longitudinal variations in microtubule (MT) structures and the lumenal scaffold complexes connecting them have been determined, as well as membrane-associated transition zone structures: Y-shaped links connecting MT to the membrane, and ciliary beads connected to them that protrude from the cell surface and form a necklace-like structure. These results represent a clearer structural scaffold onto which molecules identified by genetics, proteomics, and superresolution fluorescence can be placed in our emerging model of photoreceptor sensory cilia.

Cryogenic electron microscopy and tomography reveal imperfect icosahedral symmetry in alphaviruses.

Alphaviruses are spherical, enveloped RNA viruses with two-layered icosahedral architecture. The structures of many alphaviruses have been studied using cryogenic electron microscopy (cryo-EM) reconstructions, which impose icosahedral symmetry on the viral particles. Using cryogenic electron tomography (cryo-ET), we revealed a polarized symmetry defect in the icosahedral lattice of Chikungunya virus (CHIKV) in situ, similar to the late budding particles, suggesting the inherent imperfect symmetry originates from the final pinch-off of assembled virions. We further demonstrated this imperfect symmetry is also present in in vitro purified CHIKV and Mayaro virus, another arthritogenic alphavirus. We employed a subparticle-based single-particle analysis protocol to circumvent the icosahedral imperfection and boosted the resolution of the structure of the CHIKV to ∼3 Šresolution, which revealed detailed molecular interactions between glycoprotein E1-E2 heterodimers in the transmembrane region and multiple lipid-like pocket factors located in a highly conserved hydrophobic pocket. This complementary use of in situ cryo-ET and single-particle cryo-EM approaches provides a more precise structural description of near-icosahedral viruses and valuable insights to guide the development of structure-based antiviral therapies against alphaviruses.

Correction: Jiménez-Ortigosa et al. Cryo-Electron Tomography of Candida glabrata Plasma Membrane Proteins. J. Fungi 2021, 7, 120.

The authors wish to update the article title to "Cryo-Electron Tomography of Candida glabrata Plasma Membrane Proteins" [...].

Angiotensin II downregulates ACE2-mediated enhancement of MMP-2 activity in human cardiofibroblasts.

Angiotensin converting enzyme II (ACE2) is a component of the renin-angiotensin system (RAS) that negatively regulates angiotensin II (Ang II). Ang II, in turn, affects the expression of matrix metalloproteinases (MMPs) to induce heart remodeling. The specific mechanisms by which ACE2 regulates MMP-2, however, remain unclear. The aim of this study was to investigate the regulatory relationships between Ang II, ACE2, and MMP-2. ACE2 expression was upregulated and downregulated in human cardiofibroblasts (HCFs) by lentiviral infection. Effects on MMP-2 activity, shed ACE2 activity, extracellular signal-regulated kinase (ERK) signaling pathway, and ADAM metallopeptidase domain 17 (ADAM17) expression were assessed. ACE2 increased MMP-2 activity, and Ang II inhibited this effect through the Ang II type-1 receptor (AT1R) and ERK1/2 signaling pathway. Ang II also reduced the effect of ACE2 on ERK1/2 levels, the activity of shed ACE2, and adam17 expression in HCFs. Additionally, these Ang II-mediated reductions could be attenuated by AT1R antagonist valsartan. In conclusion, these data help to clarify how ACE2 and Ang II interact to regulate MMP-2 and control tissue remodeling in heart disease.

Integrating Molecular Models Into CryoEM Heterogeneity Analysis Using Scalable High-resolution Deep Gaussian Mixture Models.

Resolving the structural variability of proteins is often key to understanding the structure-function relationship of those macromolecular machines. Single particle analysis using Cryogenic electron microscopy (CryoEM), combined with machine learning algorithms, provides a way to reveal the dynamics within the protein system from noisy micrographs. Here, we introduce an improved computational method that uses Gaussian mixture models for protein structure representation and deep neural networks for conformation space embedding. By integrating information from molecular models into the heterogeneity analysis, we can analyze continuous protein conformational changes using structural information at the frequency of 1/3 Å-1, and present the results in a more interpretable form.

Improving Resolution and Resolvability of Single Particle CryoEM using Gaussian Mixture Models.

Cryogenic electron microscopy is widely used in structural biology, but its resolution is often limited by the dynamics of the macromolecule. Here, we developed a refinement protocol based on Gaussian mixture models that integrates particle orientation and conformation estimation, and improves the alignment for flexible domains of protein structures. We demonstrated this protocol on multiple datasets, resulting in improved resolution and resolvability, locally and globally, by visual and quantitative measures.