Automated model building and protein identification in cryo-EM maps.

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy to those built by humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will therefore remove bottlenecks and increase objectivity in cryo-EM structure determination.

MeasureIce: accessible on-the-fly measurement of ice thickness in cryo-electron microscopy.

Ice thickness is arguably one of the most important factors limiting the resolution of protein structures determined by cryo-electron microscopy (cryo-EM). The amorphous atomic structure of the ice that stabilizes and protects biological samples in cryo-EM grids also imprints some additional noise in cryo-EM images. Ice that is too thick jeopardizes the success of particle picking and reconstruction of the biomolecule in the worst case and, at best, deteriorates eventual map resolution. Minimizing the thickness of the ice layer and thus the magnitude of its noise contribution is thus imperative in cryo-EM grid preparation. In this paper we introduce MeasureIce, a simple, easy to use ice thickness measurement tool for screening and selecting acquisition areas of cryo-EM grids. We show that it is possible to simulate thickness-image intensity look-up tables, also usable in SerialEM and Leginon, using elementary scattering physics and thereby adapt the tool to any microscope without time consuming experimental calibration. We benchmark our approach using two alternative techniques: the "ice channel" technique and tilt-series tomography. We also demonstrate the utility of ice thickness measurement for selecting holes in gold grids containing an Equine apoferritin sample, achieving a 1.88 Ångstrom resolution in subsequent refinement of the atomic map.

Improving particle quality in cryo-EM analysis using a PEGylation method.

Cryo-electron microscopy (cryo-EM) is widely used for structural biology studies and has been developed extensively in recent years. However, its sample vitrification process is a major limitation because it causes severe particle aggregation and/or denaturation. This effect is thought to occur because particles tend to stick to the "deadly" air-water interface during vitrification. Here, we report a method for PEGylation of proteins that can efficiently protect particles against such problems during vitrification. This method alleviates the laborious process of fine-tuning the vitrification conditions, allowing for analysis of samples that would otherwise be discarded.

High-Resolution Cryo-EM Structure of the Cardiac Actomyosin Complex.

Heart contraction depends on a complicated array of interactions between sarcomeric proteins required to convert chemical energy into mechanical force. Cyclic interactions between actin and myosin molecules, controlled by troponin and tropomyosin, generate the sliding force between the actin-based thin and myosin-based thick filaments. Alterations in this sophisticated system due to missense mutations can lead to cardiovascular diseases. Numerous structural studies proposed pathological mechanisms of missense mutations at the myosin-myosin, actin-tropomyosin, and tropomyosin-troponin interfaces. However, despite the central role of actomyosin interactions a detailed structural description of the cardiac actomyosin interface remained unknown. Here, we report a cryo-EM structure of a cardiac actomyosin complex at 3.8 Å resolution. The structure reveals the molecular basis of cardiac diseases caused by missense mutations in myosin and actin proteins.

Low-Dose Data Collection and Radiation Damage in MicroED.

Microcrystal electron diffraction (MicroED) is a technique for structure determination that relies on the strong interaction of electrons with a minuscule, crystalline sample. While some of the electrons used to probe the crystal interact without altering the crystal, others deposit energy which changes the sample through a series of damage events. It follows that the sample cannot be observed without damaging it, and the frames obtained at the beginning of data collection reflect a crystal that differs from the one that yields the last frames of the dataset. Data acquisition at cryogenic temperatures has been found to reduce the rate of damage progression and is routinely used to increase the dose tolerance of the crystal, allowing more useful data to be obtained before the sample is destroyed. Low-dose data collection can further prolong the lifetime of the crystal, such that less damage is inflicted over the course of data acquisition. Ideally, lower doses increase the measurable volume of a single-crystal lattice by reducing the damage caused by probing electrons. However, the information that can be recovered from a diffraction image is directly related to the number of electrons used to probe the sample. The signal from a weakly exposed crystal runs the risk of being lost in the noise contributed by solvent, crystal disorder, and the electron detection process. This work focuses on obtaining the best possible data from a MicroED measurement, which requires considering several aspects such as sample, dose, and camera type.

Atomic-resolution protein structure determination by cryo-EM.

Single-particle electron cryo-microscopy (cryo-EM) is a powerful method for solving the three-dimensional structures of biological macromolecules. The technological development of transmission electron microscopes, detectors and automated procedures in combination with user-friendly image processing software and ever-increasing computational power have made cryo-EM a successful and expanding technology over the past decade1. At resolutions better than 4 Å, atomic model building starts to become possible, but the direct visualization of true atomic positions in protein structure determination requires much higher (better than 1.5 Å) resolution, which so far has not been attained by cryo-EM. The direct visualization of atom positions is essential for understanding the mechanisms of protein-catalysed chemical reactions, and for studying how drugs bind to and interfere with the function of proteins2. Here we report a 1.25 Å-resolution structure of apoferritin obtained by cryo-EM with a newly developed electron microscope that provides, to our knowledge, unprecedented structural detail. Our apoferritin structure has almost twice the 3D information content of the current world record reconstruction (at 1.54 Å resolution3). We can visualize individual atoms in a protein, see density for hydrogen atoms and image single-atom chemical modifications. Beyond the nominal improvement in resolution, we also achieve a substantial improvement in the quality of the cryo-EM density map, which is highly relevant for using cryo-EM in structure-based drug design.

Single-particle cryo-EM at atomic resolution.

The three-dimensional positions of atoms in protein molecules define their structure and their roles in biological processes. The more precisely atomic coordinates are determined, the more chemical information can be derived and the more mechanistic insights into protein function may be inferred. Electron cryo-microscopy (cryo-EM) single-particle analysis has yielded protein structures with increasing levels of detail in recent years1,2. However, it has proved difficult to obtain cryo-EM reconstructions with sufficient resolution to visualize individual atoms in proteins. Here we use a new electron source, energy filter and camera to obtain a 1.7 Å resolution cryo-EM reconstruction for a human membrane protein, the ß3 GABAA receptor homopentamer3. Such maps allow a detailed understanding of small-molecule coordination, visualization of solvent molecules and alternative conformations for multiple amino acids, and unambiguous building of ordered acidic side chains and glycans. Applied to mouse apoferritin, our strategy led to a 1.22 Å resolution reconstruction that offers a genuine atomic-resolution view of a protein molecule using single-particle cryo-EM. Moreover, the scattering potential from many hydrogen atoms can be visualized in difference maps, allowing a direct analysis of hydrogen-bonding networks. Our technological advances, combined with further approaches to accelerate data acquisition and improve sample quality, provide a route towards routine application of cryo-EM in high-throughput screening of small molecule modulators and structure-based drug discovery.

High-Throughput Cryo-EM Enabled by User-Free Preprocessing Routines.

Single-particle cryoelectron microscopy (cryo-EM) continues to grow into a mainstream structural biology technique. Recent developments in data collection strategies alongside new sample preparation devices herald a future where users will collect multiple datasets per microscope session. To make cryo-EM data processing more automatic and user-friendly, we have developed an automatic pipeline for cryo-EM data preprocessing and assessment using a combination of deep-learning and image-analysis tools. We have verified the performance of this pipeline on a number of datasets and extended its scope to include sample screening by the user-free assessment of the qualities of a series of datasets under different conditions. We propose that our workflow provides a decision-free solution for cryo-EM, making data preprocessing more generalized and robust in the high-throughput era as well as more convenient for users from a range of backgrounds.

Membrane Protein Cryo-EM: Cryo-Grid Optimization and Data Collection with Protein in Detergent.

Cryo-electron microscopy (cryo-EM) is a powerful tool for investigating the structure of macromolecules under near-native conditions. Especially in the context of membrane proteins, this technique has allowed researchers to obtain structural information at a previously unattainable level of detail. Specimen preparation remains the bottleneck of most cryo-EM research projects, with membrane proteins representing particularly challenging targets of investigation due to their universal requirement for detergents or other solubilizing agents. Here we describe preparation of negative staining and cryo-EM grids and downstream data collection of membrane proteins in detergent, by far the most common solubilization agent. This protocol outlines a quick and straightforward procedure for screening and determining the structure of a membrane protein of interest under biologically relevant conditions.

Benchmarking tomographic acquisition schemes for high-resolution structural biology.

Cryo electron tomography with subsequent subtomogram averaging is a powerful technique to structurally analyze macromolecular complexes in their native context. Although close to atomic resolution in principle can be obtained, it is not clear how individual experimental parameters contribute to the attainable resolution. Here, we have used immature HIV-1 lattice as a benchmarking sample to optimize the attainable resolution for subtomogram averaging. We systematically tested various experimental parameters such as the order of projections, different angular increments and the use of the Volta phase plate. We find that although any of the prominently used acquisition schemes is sufficient to obtain subnanometer resolution, dose-symmetric acquisition provides considerably better outcome. We discuss our findings in order to provide guidance for data acquisition. Our data is publicly available and might be used to further develop processing routines.

Experimental Phasing of MicroED Data Using Radiation Damage.

We previously demonstrated that microcrystal electron diffraction (MicroED) can be used to determine atomic-resolution structures from vanishingly small three-dimensional crystals. Here, we present an example of an experimentally phased structure using only MicroED data. The structure of a seven-residue peptide is solved starting from differences to the diffraction intensities induced by structural changes due to radiation damage. The same wedge of reciprocal space was recorded twice by continuous-rotation MicroED from a set of 11 individual crystals. The data from the first pass were merged to make a "low-dose dataset." The data from the second pass were similarly merged to form a "damaged dataset." Differences between these two datasets were used to identify a single heavy-atom site from a Patterson difference map, and initial phases were generated. Finally, the structure was completed by iterative cycles of modeling and refinement.

A Super-Clustering Approach for Fully Automated Single Particle Picking in Cryo-EM.

Structure determination of proteins and macromolecular complexes by single-particle cryo-electron microscopy (cryo-EM) is poised to revolutionize structural biology. An early challenging step in the cryo-EM pipeline is the detection and selection of particles from two-dimensional micrographs (particle picking). Most existing particle-picking methods require human intervention to deal with complex (irregular) particle shapes and extremely low signal-to-noise ratio (SNR) in cryo-EM images. Here, we design a fully automated super-clustering approach for single particle picking (SuperCryoEMPicker) in cryo-EM micrographs, which focuses on identifying, detecting, and picking particles of the complex and irregular shapes in micrographs with extremely low signal-to-noise ratio (SNR). Our method first applies advanced image processing procedures to improve the quality of the cryo-EM images. The binary mask image-highlighting protein particles are then generated from each individual cryo-EM image using the super-clustering (SP) method, which improves upon base clustering methods (i.e., k-means, fuzzy c-means (FCM), and intensity-based cluster (IBC) algorithm) via a super-pixel algorithm. SuperCryoEMPicker is tested and evaluated on micrographs of ß-galactosidase and 80S ribosomes, which are examples of cryo-EM data exhibiting complex and irregular particle shapes. The results show that the super-particle clustering method provides a more robust detection of particles than the base clustering methods, such as k-means, FCM, and IBC. SuperCryoEMPicker automatically and effectively identifies very complex particles from cryo-EM images of extremely low SNR. As a fully automated particle detection method, it has the potential to relieve researchers from laborious, manual particle-labeling work and therefore is a useful tool for cryo-EM protein structure determination.

Acceleration of cryo-EM Flexible Fitting for Large Biomolecular Systems by Efficient Space Partitioning.

Flexible fitting is a powerful technique to build the 3D structures of biomolecules from cryoelectron microscopy (cryo-EM) density maps. One popular method is a cross-correlation coefficient-based approach, where the molecular dynamics (MD) simulation is carried out with the biasing potential that includes the cross-correlation coefficient between the experimental and simulated density maps. Here, we propose efficient parallelization schemes for the calculation of the cross-correlation coefficient to accelerate flexible fitting. Our schemes are tested for small, medium, and large biomolecules using CPU and hybrid CPU + GPU architectures. The scheme for the atomic decomposition MD is suitable for small proteins such as Ca2+-ATPase with the all-atom Go model, while that for the domain decomposition MD is better for larger systems such as ribosome with the all-atom Go or the all-atom explicit solvent models. Our methods allow flexible fitting for various biomolecules with reasonable computational cost. This approach also connects high-resolution structure refinements with investigation of protein structure-function relationship.

Defocus and magnification dependent variation of TEM image astigmatism.

Daily alignment of the microscope is a prerequisite to reaching optimal lens conditions for high resolution imaging in cryo-EM. In this study, we have investigated how image astigmatism varies with the imaging conditions (e.g. defocus, magnification). We have found that the large change of defocus/magnification between visual correction of astigmatism and subsequent data collection tasks, or during data collection, will inevitably result in undesirable astigmatism in the final images. The dependence of astigmatism on the imaging conditions varies significantly from time to time, so that it cannot be reliably compensated by pre-calibration of the microscope. Based on these findings, we recommend that the same magnification and the median defocus of the intended defocus range for final data collection are used in the objective lens astigmatism correction task during microscope alignment and in the focus mode of the iterative low-dose imaging. It is also desirable to develop a fast, accurate method that can perform dynamic correction of the astigmatism for different intended defocuses during automated imaging. Our findings also suggest that the slope of astigmatism changes caused by varying defocuses can be used as a convenient measurement of objective lens rotation symmetry and potentially an acceptance test of new electron microscopes.

Cross-Validation of Data Compatibility Between Small Angle X-ray Scattering and Cryo-Electron Microscopy.

Cryo-electron microscopy (EM) and small angle X-ray scattering (SAXS) are two different data acquisition modalities often used to glean information about the structure of large biomolecular complexes in their native states. A SAXS experiment is generally considered fast and easy but unveils the structure at very low resolution, whereas a cryo-EM experiment needs more extensive preparation and postacquisition computation to yield a three-dimensional (3D) density map at higher resolution. In certain applications, we may need to verify whether the data acquired in the SAXS and cryo-EM experiments correspond to the same structure (e.g., before reconstructing the 3D density map in EM). In this article, a simple and fast method is proposed to verify the compatibility of the SAXS and EM experimental data. The method is based on averaging the two-dimensional correlation of EM images and the Abel transform of the SAXS data. Orientational preferences are known to exist in cryo-EM experiments, and we also consider these effects on our method. The results are verified on simulations of conformational states of large biomolecular complexes.

Unsupervised Cryo-EM Data Clustering through Adaptively Constrained K-Means Algorithm.

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.