cryo-EM Map Research Articles

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.

Structural and mechanistic basis of the central energy-converting methyltransferase complex of methanogenesis

Methanogenic archaea inhabiting anaerobic environments play a crucial role in the global biogeochemical material cycle. The most universal electrogenic reaction of their methane-producing energy metabolism is catalyzed by N    5-methyl-tetrahydromethanopterin: coenzyme M methyltransferase (MtrABCDEFGH), which couples the vectorial Na+ transport with a methyl transfer between the one-carbon carriers tetrahydromethanopterin and coenzyme M via a vitamin B12 derivative (cobamide) as prosthetic group. We present the 2.08 Å cryo-EM structure of Mtr(ABCDEFG)3 composed of the central Mtr(ABFG)3 stalk symmetrically flanked by three membrane-spanning MtrCDE globes. Tetraether glycolipids visible in the map fill gaps inside the multisubunit complex. Putative coenzyme M and Na+ were identified inside or in a side-pocket of a cytoplasmic cavity formed within MtrCDE. Its bottom marks the gate of the transmembrane pore occluded in the cryo-EM map. By integrating Alphafold2 information, functionally competent MtrA-MtrH and MtrA-MtrCDE subcomplexes could be modeled and thus the methyl-tetrahydromethanopterin demethylation and coenzyme M methylation half-reactions structurally described. Methyl-transfer-driven Na+ transport is proposed to be based on a strong and weak complex between MtrCDE and MtrA carrying vitamin B12, the latter being placed at the entrance of the cytoplasmic MtrCDE cavity. Hypothetically, strongly attached methyl-cob(III)amide (His-on) carrying MtrA induces an inward-facing conformation, Na+ flux into the membrane protein center and finally coenzyme M methylation while the generated loosely attached (or detached) MtrA carrying cob(I)amide (His-off) induces an outward-facing conformation and an extracellular Na+ outflux. Methyl-cob(III)amide (His-on) is regenerated in the distant active site of the methyl-tetrahydromethanopterin binding MtrH implicating a large-scale shuttling movement of the vitamin B12-carrying domain.

RNA as a component of scrapie fibrils

Recently, electron cryo-microscopy (cryo-EM) maps of fibrils from the brains of mice and hamsters with five infectious scrapie strains have been published and deposited in the electron microscopy data bank (EMDB). As noted by the primary authors, the fibrils contain a second component other than protein. The aim of the present study was to identify the nature of this second component in the published maps using an in silico approach. Extra densities (EDs) containing this component were continuous, straight, axial, at right angles to protein rungs and within hydrogen-bonding distance of protein, consistent with a structural role. EDs co-located with strips of basic residues, notably lysines, and formed a conspicuous cladding over parts of the N-terminal lobe of the protein. A Y-shaped polymer consistent with RNA was found, in places forming a single chain and at one location forming a duplex, comprising two antiparallel chains, and raising the intriguing possibility of replicative behaviour. To reflect the monotonous nature of the protein interface, it is suggested that the RNA may be a short tandem repeat. Fibrils from brains of patients with Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis and other neurodegenerations also contain EDs and may be of a similar aetiology.

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.

All-atom RNA structure determination from cryo-EM maps.

Many methods exist for determining protein structures from cryogenic electron microscopy maps, but this remains challenging for RNA structures. Here we developed EMRNA, a method for accurate, automated determination of full-length all-atom RNA structures from cryogenic electron microscopy maps. EMRNA integrates deep learning-based detection of nucleotides, three-dimensional backbone tracing and scoring with consideration of sequence and secondary structure information, and full-atom construction of the RNA structure. We validated EMRNA on 140 diverse RNA maps ranging from 37 to 423 nt at 2.0-6.0 Å resolutions, and compared EMRNA with auto-DRRAFTER, phenix.map_to_model and CryoREAD on a set of 71 cases. EMRNA achieves a median accuracy of 2.36 Å root mean square deviation and 0.86 TM-score for full-length RNA structures, compared with 6.66 Å and 0.58 for auto-DRRAFTER. EMRNA also obtains a high residue coverage and sequence match of 93.30% and 95.30% in the built models, compared with 58.20% and 42.20% for phenix.map_to_model and 56.45% and 52.3% for CryoREAD. EMRNA is fast and can build an RNA structure of 100 nt within 3 min.

Accurate global and local 3D alignment of cryo-EM density maps using local spatial structural features.

Advances in cryo-electron microscopy (cryo-EM) imaging technologies have led to a rapidly increasing number of cryo-EM density maps. Alignment and comparison of density maps play a crucial role in interpreting structural information, such as conformational heterogeneity analysis using global alignment and atomic model assembly through local alignment. Here, we present a fast and accurate global and local cryo-EM density map alignment method called CryoAlign, that leverages local density feature descriptors to capture spatial structure similarities. CryoAlign is a feature-based cryo-EM map alignment tool, in which the employment of feature-based architecture enables the rapid establishment of point pair correspondences and robust estimation of alignment parameters. Extensive experimental evaluations demonstrate the superiority of CryoAlign over the existing methods in terms of both alignment accuracy and speed.

Noncanonical interaction with microtubules via the N-terminal nonmotor domain is critical for the functions of a bidirectional kinesin.

Several kinesin-5 motors (kinesin-5s) exhibit bidirectional motility. The mechanism of such motility remains unknown. Bidirectional kinesin-5s share a long N-terminal nonmotor domain (NTnmd), absent in exclusively plus-end-directed kinesins. Here, we combined in vivo, in vitro, and cryo-electron microscopy (cryo-EM) studies to examine the impact of NTnmd mutations on the motor functions of the bidirectional kinesin-5, Cin8. We found that NTnmd deletion mutants exhibited cell viability and spindle localization defects. Using cryo-EM, we examined the structure of a microtubule (MT)-bound motor domain of Cin8, containing part of its NTnmd. Modeling and molecular dynamic simulations based on the cryo-EM map suggested that the NTnmd of Cin8 interacts with the C-terminal tail of β-tubulin. In vitro experiments on subtilisin-treated MTs confirmed this notion. Last, we showed that NTnmd mutants are defective in plus-end-directed motility in single-molecule and antiparallel MT sliding assays. These findings demonstrate that the NTnmd, common to bidirectional kinesin-5s, is critical for their bidirectional motility and intracellular functions.

Accurate protein fitting into cryo-EM maps using multiple conformers generated by AlphaFold2

Accurate protein fitting into cryo-EM maps using multiple conformers generated by AlphaFold2

Cryo-EM structure and B-factor refinement with ensemble representation

Cryo-EM experiments produce images of macromolecular assemblies that are combined to produce three-dimensional density maps. Typically, atomic models of the constituent molecules are fitted into these maps, followed by a density-guided refinement. We introduce TEMPy-ReFF, a method for atomic structure refinement in cryo-EM density maps. Our method represents atomic positions as components of a Gaussian mixture model, utilising their variances as B-factors, which are used to derive an ensemble description. Extensively tested on a substantial dataset of 229 cryo-EM maps from EMDB ranging in resolution from 2.1-4.9 Å with corresponding PDB and CERES atomic models, our results demonstrate that TEMPy-ReFF ensembles provide a superior representation of cryo-EM maps. On a single-model basis, it performs similarly to the CERES re-refinement protocol, although there are cases where it provides a better fit to the map. Furthermore, our method enables the creation of composite maps free of boundary artefacts. TEMPy-ReFF is useful for better interpretation of flexible structures, such as those involving RNA, DNA or ligands.

Exploiting the full potential of cryo-EM maps

The Coulomb potential maps generated by electron microscopy (EM) experiments contain not only information about the position but also about the charge state of the atom. This feature of EM maps allows the identification of specific ions and the protonation state of amino acid side chains in the sample. Here, we summarize qualitative observations of charges in EM maps, discuss the difficulties in interpreting the charge in Coulomb potential maps with respect to distinguishing it from radiation damage, and outline considerations to implement the correct charge in fitting algorithms.

DeepQs: Local quality assessment of cryo-EM density map by deep learning map-model fit score

Cryogenic electron microscopy maps are valuable for determining macromolecule structures. A proper quality assessment method is essential for cryo-EM map selection or revision. This article presents DeepQs, a novel approach to estimate local quality for 3D cryo-EM density maps, using a deep-learning algorithm based on map-model fit score. DeepQs is a parameter-free method for users and incorporates structural information between map and its related atomic model into well-trained models by deep learning. More specifically, the DeepQs approach leverages the interplay between map and atomic model through predefined map-model fit score, Q-score. DeepQs can get close results to the ground truth map-model fit scores with only cryo-EM map as input. In experiments, DeepQs demonstrates the lowest root mean square error with standard method Fourier shell correlation metric and high correlation with map-model fit score, Q-score, when compared with other local quality estimation methods in high-resolution dataset (<=5 Å). DeepQs can also be applied to evaluate the quality of the post-processed maps. In both cases, DeepQs runs faster by using GPU acceleration. Our program is available at http://www.csbio.sjtu.edu.cn/bioinf/DeepQs for academic use.

Elucidating the Structural Dynamics of Integrin α IIbβ 3 from Native Platelet Membranes By Cryo-EM Coupled with Build and Retrieve Data Processing Methodology

Background: Platelets play a critical role in physiological processes by sensing the extracellular environment through their membrane proteins. Changing the quantity or quality of these proteins can profoundly affect platelet physiology and impact health. The native membrane environment provides essential additional regulatory cues that impact the protein structure and mechanism of action. Single-particle cryogenic electron microscopy (cryo-EM) has transformed structural biology by allowing high-resolution structures of membrane proteins and large macromolecules to be solved from highly purified, homogeneous samples. Our recent breakthroughs in data processing make it feasible to obtain high-resolution protein structures from crude preparations in their native environments by integrating cryo-EM with the novel “Build and Retrieve” (BaR) data processing methodology. By performing in silico purification, image sorting, and model building from large heterogenous datasets, this iterative bottom-up methodology opens new avenues for an in-depth systems biology approach with structural biology that will uncover how the native environment, including lipid and metal binding, post-translational modifications, and co-factor associations regulate platelet function at the molecular level. Method: Whole blood was collected, and the platelet membrane proteins were solubilized by 1% n-Dodecyl-β-D-Maltoside (DDM) and incorporated into lipidic nanodisc MSP1E3D1 directly from the endogenous source. After being enriched by size exclusion chromatography, the mixture of proteins at ~200 kDa was directly applied on cryo-EM grids. Data were collected on Titan Krios G3i cryogenic transmission electron microscope equipped with a BioQuantum K3 camera. All data processing was done in cryoSPARC using the BaR protocol. The near-atomic-resolution cryo-EM maps were used for protein identification using the program phenix.sequence_from_map in the PHENIX suite. The final protein models were built by Coot and refined by PHENIX. Results: We have used using cryo-EM followed by the BaR method to solve the first unmodified integrin α IIbβ 3 structure directly from resting human platelet membranes in its inactivated and intermediate states at 2.76Å and 2.49Å, respectively. From these two structures, we observed the ion binding sites at the β1-domain and β-propeller domain in agreement with previous “classical” α IIbβ 3 structural studies using a purified sample. More importantly, we were able to assign endogenous N-linked glycan sites, which reflected how glycosylation naturally regulates α IIbβ 3 dynamic and function on resting human platelets. Finally, we also solved a novel third unique dimer conformation of α IIbβ 3 at 2.61Å formed by two intermediate-states of α IIbβ 3. This may indicate a previously unknown self-regulatory mechanism of α IIbβ 3 in its native environment. Conclusion: In conclusion, our data show the power of using cryo-EM with the BaR method to uncover novel structures directly from natural sources to identify unrecognized regulation mechanisms for proteins without artifacts due to purification processes. A distinct advantage of the BaR method is that it is an unbiased approach for solving multiple structures from raw samples, which highlights the potential of building a protein structural atlas from platelets. These data have the potential to enrich our understanding of platelet signaling circuitry and foster the development of higher-quality diagnoses and treatments for patients with platelet disorders.

LipIDens: simulation assisted interpretation of lipid densities in cryo-EM structures of membrane proteins

Cryo-electron microscopy (cryo-EM) enables the determination of membrane protein structures in native-like environments. Characterising how membrane proteins interact with the surrounding membrane lipid environment is assisted by resolution of lipid-like densities visible in cryo-EM maps. Nevertheless, establishing the molecular identity of putative lipid and/or detergent densities remains challenging. Here we present LipIDens, a pipeline for molecular dynamics (MD) simulation-assisted interpretation of lipid and lipid-like densities in cryo-EM structures. The pipeline integrates the implementation and analysis of multi-scale MD simulations for identification, ranking and refinement of lipid binding poses which superpose onto cryo-EM map densities. Thus, LipIDens enables direct integration of experimental and computational structural approaches to facilitate the interpretation of lipid-like cryo-EM densities and to reveal the molecular identities of protein-lipid interactions within a bilayer environment. We demonstrate this by application of our open-source LipIDens code to ten diverse membrane protein structures which exhibit lipid-like densities.

Product analog binding identifies the copper active site of particulate methane monooxygenase.

Nature's primary methane-oxidizing enzyme, the membrane-bound particulate methane monooxygenase (pMMO), catalyzes the oxidation of methane to methanol. pMMO activity requires copper, and decades of structural and spectroscopic studies have sought to identify the active site among three candidates: the CuB, CuC, and CuD sites. Challenges associated with the isolation of active pMMO have hindered progress toward locating its catalytic center. However, reconstituting pMMO into native lipid nanodiscs stabilizes its structure and recovers its activity. Here, these active samples were incubated with 2,2,2,-trifluoroethanol (TFE), a product analog that serves as a readily visualized active-site probe. Interactions of TFE with the CuD site were observed by both pulsed ENDOR spectroscopy and cryoEM, implicating CuD and the surrounding hydrophobic pocket as the likely site of methane oxidation. Use of these orthogonal techniques on parallel samples is a powerful approach that can circumvent difficulties in interpreting metalloenzyme cryoEM maps.

CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning.

DNA and RNA play fundamental roles in various cellular processes, where their three-dimensional structures provide information critical to understanding the molecular mechanisms of their functions. Although an increasing number of nucleic acid structures and their complexes with proteins are determined by cryogenic electron microscopy (cryo-EM), structure modeling for DNA and RNA remains challenging particularly when the map is determined at a resolution coarser than atomic level. Moreover, computational methods for nucleic acid structure modeling are relatively scarce. Here, we present CryoREAD, a fully automated de novo DNA/RNA atomic structure modeling method using deep learning. CryoREAD identifies phosphate, sugar and base positions in a cryo-EM map using deep learning, which are traced and modeled into a three-dimensional structure. When tested on cryo-EM maps determined at 2.0 to 5.0 Å resolution, CryoREAD built substantially more accurate models than existing methods. We also applied the method to cryo-EM maps of biomolecular complexes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

CryoREAD provides fully automated DNA-RNA structure modeling for cryo-EM maps.

CryoREAD provides fully automated DNA-RNA structure modeling for cryo-EM maps.

RyR2 Binding of an Antiarrhythmic Cyclic Depsipeptide Mapped Using Confocal Fluorescence Lifetime Detection of FRET.

Hyperactivity of cardiac sarcoplasmic reticulum (SR) ryanodine receptor (RyR2) Ca2+-release channels contributes to heart failure and arrhythmias. Reducing the RyR2 activity, particularly during cardiac relaxation (diastole), is a desirable therapeutic goal. We previously reported that the unnatural enantiomer (ent) of an insect-RyR activator, verticilide, inhibits porcine and mouse RyR2 at diastolic (nanomolar) Ca2+ and has in vivo efficacy against atrial and ventricular arrhythmia. To determine the ent-verticilide structural mode of action on RyR2 and guide its further development via medicinal chemistry structure-activity relationship studies, here, we used fluorescence lifetime (FLT)-measurements of Förster resonance energy transfer (FRET) in HEK293 cells expressing human RyR2. For these studies, we used an RyR-specific FRET molecular-toolkit and computational methods for trilateration (i.e., using distances to locate a point of interest). Multiexponential analysis of FLT-FRET measurements between four donor-labeled FKBP12.6 variants and acceptor-labeled ent-verticilide yielded distance relationships placing the acceptor probe at two candidate loci within the RyR2 cryo-EM map. One locus is within the Ry12 domain (at the corner periphery of the RyR2 tetrameric complex). The other locus is sandwiched at the interface between helical domain 1 and the SPRY3 domain. These findings document RyR2-target engagement by ent-verticilide, reveal new insight into the mechanism of action of this new class of RyR2-targeting drug candidate, and can serve as input in future computational determinations of the ent-verticilide binding site on RyR2 that will inform structure-activity studies for lead optimization.

Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps.

Interpretation of cryo-electron microscopy (cryo-EM) maps requires building and fitting 3D atomic models of biological molecules. AlphaFold-predicted models generate initial 3D coordinates; however, model inaccuracy and conformational heterogeneity often necessitate labor-intensive manual model building and fitting into cryo-EM maps. In this work, we designed a protein model-building workflow, which combines a deep-learning cryo-EM map feature enhancement tool, CryoFEM (Cryo-EM Feature Enhancement Model) and AlphaFold. A benchmark test using 36 cryo-EM maps shows that CryoFEM achieves state-of-the-art performance in optimizing the Fourier Shell Correlations between the maps and the ground truth models. Furthermore, in a subset of 17 datasets where the initial AlphaFold predictions are less accurate, the workflow significantly improves their model accuracy. Our work demonstrates that the integration of modern deep learning image enhancement and AlphaFold may lead to automated model building and fitting for the atomistic interpretation of cryo-EM maps.

A robust normalized local filter to estimate compositional heterogeneity directly from cryo-EM maps

Cryo electron microscopy (cryo-EM) is used by biological research to visualize biomolecular complexes in 3D, but the heterogeneity of cryo-EM reconstructions is not easily estimated. Current processing paradigms nevertheless exert great effort to reduce flexibility and heterogeneity to improve the quality of the reconstruction. Clustering algorithms are typically employed to identify populations of data with reduced variability, but lack assessment of remaining heterogeneity. Here we develope a fast and simple algorithm based on spatial filtering to estimate the heterogeneity of a reconstruction. In the absence of flexibility, this estimate approximates macromolecular component occupancy. We show that our implementation can derive reasonable input parameters, that composition heterogeneity can be estimated based on contrast loss, and that the reconstruction can be modified accordingly to emulate altered constituent occupancy. This stands to benefit conventionally employed maximum-likelihood classification methods, whereas we here limit considerations to cryo-EM map interpretation, quantification, and particle-image signal subtraction.

Cryo-EM captures a unique conformational rearrangement in 23S rRNA helices of the Mycobacterium 50S subunit

Structural investigations of the ribosomes isolated from pathogenic and non-pathogenic Mycobacterium species have identified several mycobacteria-specific structural features of ribosomal RNA and proteins. Here, we report structural evidence of a hitherto unknown conformational switch of mycobacterium 23S rRNA helices (H54a and H67-H71). Cryo-electron microscopy (cryo-EM) structures (~3–4 Å) of the M. smegmatis (Msm) log-phase 50S ribosomal subunit revealed conformational variability in H67-H71 region of the 23S rRNA, and manifested that, while H68 possesses the usual stretched conformation in one class of the maps, another one exhibits a bulge-out, fused density of H68-H69 at the inter-subunit surface, indicating an intrinsic dynamics of these rRNA helices. Remarkably, altered conformation of H68 forming a more prominent bulge-out structure at the inter-subunit surface of the 50S subunit due to the conformational rearrangements of 23S rRNA H67-H71 region was clearly visualized in a 3 Å cryo-EM map of the 50S subunit obtained from the stationary phase ribosome dataset. The Msm50S subunit having such bulge-out conformation at the intersubunit surface would be incompatible for associating with the 30S subunit due to its inability to form major inter-subunit bridges. Evidently, availability of active 70S ribosome pool can be modulated by stabilizing either one of the H68 conformation.