In situ architecture of the ciliary base reveals the stepwise assembly of intraflagellar transport trains.

The cilium is an antenna-like organelle that performs numerous cellular functions, including motility, sensing, and signaling. The base of the cilium contains a selective barrier that regulates the entry of large intraflagellar transport (IFT) trains, which carry cargo proteins required for ciliary assembly and maintenance. However, the native architecture of the ciliary base and the process of IFT train assembly remain unresolved. In this work, we used in situ cryo-electron tomography to reveal native structures of the transition zone region and assembling IFT trains at the ciliary base in Chlamydomonas. We combined this direct cellular visualization with ultrastructure expansion microscopy to describe the front-to-back stepwise assembly of IFT trains: IFT-B forms the backbone, onto which bind IFT-A, dynein-1b, and finally kinesin-2 before entry into the cilium.

MemBrain: A deep learning-aided pipeline for detection of membrane proteins in Cryo-electron tomograms.

BACKGROUND AND OBJECTIVE: Cryo-electron tomography (cryo-ET) is an imaging technique that enables 3D visualization of the native cellular environment at sub-nanometer resolution, providing unpreceded insights into the molecular organization of cells. However, cryo-electron tomograms suffer from low signal-to-noise ratios and anisotropic resolution, which makes subsequent image analysis challenging. In particular, the efficient detection of membrane-embedded proteins is a problem still lacking satisfactory solutions. METHODS: We present MemBrain - a new deep learning-aided pipeline that automatically detects membrane-bound protein complexes in cryo-electron tomograms. After subvolumes are sampled along a segmented membrane, each subvolume is assigned a score using a convolutional neural network (CNN), and protein positions are extracted by a clustering algorithm. Incorporating rotational subvolume normalization and using a tiny receptive field simplify the task of protein detection and thus facilitate the network training. RESULTS: MemBrain requires only a small quantity of training labels and achieves excellent performance with only a single annotated membrane (F1 score: 0.88). A detailed evaluation shows that our fully trained pipeline outperforms existing classical computer vision-based and CNN-based approaches by a large margin (F1 score: 0.92 vs. max. 0.63). Furthermore, in addition to protein center positions, MemBrain can determine protein orientations, which has not been implemented by any existing CNN-based method to date. We also show that a pre-trained MemBrain program generalizes to tomograms acquired using different cryo-ET methods and depicting different types of cells. CONCLUSIONS: MemBrain is a powerful and annotation-efficient tool for the detection of membrane protein complexes in cryo-ET data, with the potential to be used in a wide range of biological studies. It is generalizable to various kinds of tomograms, making it possible to use pretrained models for different tasks. Its efficiency in terms of required annotations also allows rapid training and fine-tuning of models. The corresponding code, pretrained models, and instructions for operating the MemBrain program can be found at: https://github.com/CellArchLab/MemBrain.

Membrane-anchored HDCR nanowires drive hydrogen-powered CO2 fixation.

Filamentous enzymes have been found in all domains of life, but the advantage of filamentation is often elusive1. Some anaerobic, autotrophic bacteria have an unusual filamentous enzyme for CO2 fixation-hydrogen-dependent CO2 reductase (HDCR)2,3-which directly converts H2 and CO2 into formic acid. HDCR reduces CO2 with a higher activity than any other known biological or chemical catalyst4,5, and it has therefore gained considerable interest in two areas of global relevance: hydrogen storage and combating climate change by capturing atmospheric CO2. However, the mechanistic basis of the high catalytic turnover rate of HDCR has remained unknown. Here we use cryo-electron microscopy to reveal the structure of a short HDCR filament from the acetogenic bacterium Thermoanaerobacter kivui. The minimum repeating unit is a hexamer that consists of a formate dehydrogenase (FdhF) and two hydrogenases (HydA2) bound around a central core of hydrogenase Fe-S subunits, one HycB3 and two HycB4. These small bacterial polyferredoxin-like proteins oligomerize through their C-terminal helices to form the backbone of the filament. By combining structure-directed mutagenesis with enzymatic analysis, we show that filamentation and rapid electron transfer through the filament enhance the activity of HDCR. To investigate the structure of HDCR in situ, we imaged T. kivui cells with cryo-electron tomography and found that HDCR filaments bundle into large ring-shaped superstructures attached to the plasma membrane. This supramolecular organization may further enhance the stability and connectivity of HDCR to form a specialized metabolic subcompartment within the cell.

Cryo-EM structure of native human thyroglobulin.

The thyroglobulin (TG) protein is essential to thyroid hormone synthesis, plays a vital role in the regulation of metabolism, development and growth and serves as intraglandular iodine storage. Its architecture is conserved among vertebrates. Synthesis of triiodothyronine (T3) and thyroxine (T4) hormones depends on the conformation, iodination and post-translational modification of TG. Although structural information is available on recombinant and deglycosylated endogenous human thyroglobulin (hTG) from patients with goiters, the structure of native, fully glycosylated hTG remained unknown. Here, we present the cryo-electron microscopy structure of native and fully glycosylated hTG from healthy thyroid glands to 3.2 Å resolution. The structure provides detailed information on hormonogenic and glycosylation sites. We employ liquid chromatography-mass spectrometry (LC-MS) to validate these findings as well as other post-translational modifications and proteolytic cleavage sites. Our results offer insights into thyroid hormonogenesis of native hTG and provide a fundamental understanding of clinically relevant mutations.

Deep learning improves macromolecule identification in 3D cellular cryo-electron tomograms.

Cryogenic electron tomography (cryo-ET) visualizes the 3D spatial distribution of macromolecules at nanometer resolution inside native cells. However, automated identification of macromolecules inside cellular tomograms is challenged by noise and reconstruction artifacts, as well as the presence of many molecular species in the crowded volumes. Here, we present DeepFinder, a computational procedure that uses artificial neural networks to simultaneously localize multiple classes of macromolecules. Once trained, the inference stage of DeepFinder is faster than template matching and performs better than other competitive deep learning methods at identifying macromolecules of various sizes in both synthetic and experimental datasets. On cellular cryo-ET data, DeepFinder localized membrane-bound and cytosolic ribosomes (roughly 3.2 MDa), ribulose 1,5-bisphosphate carboxylase-oxygenase (roughly 560 kDa soluble complex) and photosystem II (roughly 550 kDa membrane complex) with an accuracy comparable to expert-supervised ground truth annotations. DeepFinder is therefore a promising algorithm for the semiautomated analysis of a wide range of molecular targets in cellular tomograms.

Identification of a Dps contamination in Mitomycin-C-induced expression of Colicin Ia.

Colicins are bacterial toxins targeting Gram-negative bacteria, including E. coli and related Enterobacteriaceae strains. Some colicins form ion-gated pores in the inner membrane of attacked bacteria that are lethal to their target. Colicin Ia was the first pore-forming E. coli toxin, for which a high-resolution structure of the monomeric full-length protein was determined. It is so far also the only colicin, for which a low-resolution structure of its membrane-inserted pore was reported by negative-stain electron microscopy. Resolving this structure at the atomic level would allow an understanding of the mechanism of toxin pore formation. Here, we report an observation that we made during an attempt to determine the Colicin Ia pore structure at atomic resolution. Colicin Ia was natively expressed by mitomycin-C induction under a native SOS promotor and purified following published protocols. The visual appearance in the electron microscope of negatively stained preparations and the lattice parameters of 2D crystals obtained from the material were highly similar to those reported earlier resulting from the same purification protocol. However, a higher-resolution structural analysis revealed that the protein is Dps (DNA-binding protein from starved cells), a dodecameric E. coli protein. This finding suggests that the previously reported low-resolution structure of a "Colicin Ia oligomeric pore" actually shows Dps.

Author Correction: High-resolution cryo-EM structure of urease from the pathogen Yersinia enterocolitica.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-19845-z .

High-resolution cryo-EM structure of urease from the pathogen Yersinia enterocolitica.

Urease converts urea into ammonia and carbon dioxide and makes urea available as a nitrogen source for all forms of life except animals. In human bacterial pathogens, ureases also aid in the invasion of acidic environments such as the stomach by raising the surrounding pH. Here, we report the structure of urease from the pathogen Yersinia enterocolitica at 2 Å resolution from cryo-electron microscopy. Y. enterocolitica urease is a dodecameric assembly of a trimer of three protein chains, ureA, ureB and ureC. The high data quality enables detailed visualization of the urease bimetal active site and of the impact of radiation damage. The obtained structure is of sufficient quality to support drug development efforts.

Structural basis of Focal Adhesion Kinase activation on lipid membranes.

Focal adhesion kinase (FAK) is a key component of the membrane proximal signaling layer in focal adhesion complexes, regulating important cellular processes, including cell migration, proliferation, and survival. In the cytosol, FAK adopts an autoinhibited state but is activated upon recruitment into focal adhesions, yet how this occurs or what induces structural changes is unknown. Here, we employ cryo-electron microscopy to reveal how FAK associates with lipid membranes and how membrane interactions unlock FAK autoinhibition to promote activation. Intriguingly, initial binding of FAK to the membrane causes steric clashes that release the kinase domain from autoinhibition, allowing it to undergo a large conformational change and interact itself with the membrane in an orientation that places the active site toward the membrane. In this conformation, the autophosphorylation site is exposed and multiple interfaces align to promote FAK oligomerization on the membrane. We show that interfaces responsible for initial dimerization and membrane attachment are essential for FAK autophosphorylation and resulting cellular activity including cancer cell invasion, while stable FAK oligomerization appears to be needed for optimal cancer cell proliferation in an anchorage-independent manner. Together, our data provide structural details of a key membrane bound state of FAK that is primed for efficient autophosphorylation and activation, hence revealing the critical event in integrin mediated FAK activation and signaling at focal adhesions.

Retrieving high-resolution information from disordered 2D crystals by single-particle cryo-EM.

Electron crystallography can reveal the structure of membrane proteins within 2D crystals under close-to-native conditions. High-resolution structural information can only be reached if crystals are perfectly flat and highly ordered. In practice, such crystals are difficult to obtain. Available image unbending algorithms correct for disorder, but only perform well on images of non-tilted, flat crystals, while out-of-plane distortions are not addressed. Here, we present an approach that employs single-particle refinement procedures to locally unbend crystals in 3D. With this method, density maps of the MloK1 potassium channel with a resolution of 4 Å were obtained from images of 2D crystals that do not diffract beyond 10 Å. Furthermore, 3D classification allowed multiple structures to be resolved, revealing a series of MloK1 conformations within a single 2D crystal. This conformational heterogeneity explains the poor diffraction observed and is related to channel function. The approach is implemented in the FOCUS package.

Image processing techniques for high-resolution structure determination from badly ordered 2D crystals.

2D electron crystallography can be used to study small membrane proteins in their native environment. Obtaining highly ordered 2D crystals is difficult and time-consuming. However, 2D crystals diffracting to only 10-12 Šcan be prepared relatively conveniently in most cases. We have developed image-processing algorithms allowing to generate a high resolution 3D structure from cryo-electron crystallography images of badly ordered crystals. These include movie-mode unbending, refinement over sub-tiles of the images in order to locally refine the sample tilt geometry, implementation of different CTF correction schemes, and an iterative method to apply known constraints in the real and reciprocal space to approximate amplitudes and phases in the so-called missing cone regions. These algorithms applied to a dataset of the potassium channel MloK1 show significant resolution improvements to better than 5 Å.

Focus: The interface between data collection and data processing in cryo-EM.

We present a new software package called Focus that interfaces cryo-transmission electron microscopy (cryo-EM) data collection with computer image processing. Focus creates a user-friendly environment to import and manage data recorded by direct electron detectors and perform elemental image processing tasks in a high-throughput manner while new data is being acquired at the microscope. It provides the functionality required to remotely monitor the progress of data collection and data processing, which is essential now that automation in cryo-EM allows a steady flow of images of single particles, two-dimensional crystals, or electron tomography data to be recorded in overnight sessions. The rapid detection of any errors that may occur greatly increases the productivity of recording sessions at the electron microscope.

Assessment of a nanocrystal 3-D morphology by the analysis of single HAADF-HRSTEM images.

This work presents the morphological characterization of CeO2 nanocrystals by the analysis of single unfiltered high-angle annular dark-field (HAADF)-high-resolution scanning transmission electron microscopy (HRSTEM) images. The thickness of each individual atomic column is estimated by the classification of its HAADF integrated intensity using a Gaussian mixture model. The resulting thickness maps obtained from two example nanocrystals with distinct morphology were analyzed with aid of the symmetry from the CeO2 crystallographic structure, providing an approximation for their 3-D morphology with high spatial resolution. A confidence level of ±1 atom per atomic column along the viewing direction on the thickness estimation is indicated by the use of multislice image simulation. The described characterization procedure stands out as a simple approach for retrieving morphological parameters of individual nanocrystals, such as volume and specific surface areas for different crystalline planes. The procedure is an alternative to the tilt-series tomography technique for a number of nanocrystalline systems, since its application does not require the acquisition of multiple images from the same nanocrystal along different zone axes.

MEGACELL: a nanocrystal model construction software for HRTEM multislice simulation.

Image simulation has an invaluable importance for the accurate analysis of High Resolution Transmission Electron Microscope (HRTEM) results, especially due to its non-linear image formation mechanism. Because the as-obtained images cannot be interpreted in a straightforward fashion, the retrieval of both qualitative and quantitative information from HRTEM micrographs requires an iterative process including the simulation of a nanocrystal model and its comparison with experimental images. However most of the available image simulation software requires atom-by-atom coordinates as input for the calculations, which can be prohibitive for large finite crystals and/or low-symmetry systems and zone axis orientations. This paper presents an open source citation-ware tool named MEGACELL, which was developed to assist on the construction of nanocrystals models. It allows the user to build nanocrystals with virtually any convex polyhedral geometry and to retrieve its atomic positions either as a plain text file or as an output compatible with EMS (Electron Microscopy Software) input protocol. In addition to the description of this tool features, some construction examples and its application for scientific studies are presented. These studies show MEGACELL as a handy tool, which allows an easier construction of complex nanocrystal models and improves the quantitative information extraction from HRTEM images.