Improvement of cryo-EM maps by simultaneous local and non-local deep learning

Cryo-EM structure of flagellotropic bacteriophage Chi

The flagellotropic bacteriophage χ (Chi) infects bacteria via the flagellar filament. Despite years of study, its structural architecture remains partly characterized. Through cryo-EM, we unveil χ's nearly complete structure, encompassing capsid, neck, tail, and tail tip. While the capsid and tail resemble phage YSD1, the neck and tail tip reveal new proteins and their arrangement. The neck shows a unique conformation of the tail tube protein, forming a socket-like structure for attachment to the neck. The tail tip comprises four proteins, including distal tail protein (DTP), two baseplate hub proteins (BH1P and BH2P), and tail tip assembly protein (TAP) exhibiting minimal organization compared to other siphophages. Deviating from the consensus in other siphophages, DTP in χ forms a trimeric assembly, reducing tail symmetry from 6-fold to 3-fold at the tip. These findings illuminate the previously unexplored structural organization of χ's neck and tail tip.

Perturbed N-glycosylation of Halobacterium salinarum archaellum filaments leads to filament bundling and compromised cell motility

The swimming device of archaea-the archaellum-presents asparagine (N)-linked glycans. While N-glycosylation serves numerous roles in archaea, including enabling their survival in extreme environments, how this post-translational modification contributes to cell motility remains under-explored. Here, we report the cryo-EM structure of archaellum filaments from the haloarchaeon Halobacterium salinarum, where archaellins, the building blocks of the archaellum, are N-glycosylated, and the N-glycosylation pathway is well-resolved. We further determined structures of archaellum filaments from two N-glycosylation mutant strains that generate truncated glycans and analyzed their motility. While cells from the parent strain exhibited unidirectional motility, the N-glycosylation mutant strain cells swam in ever-changing directions within a limited area. Although these mutant strain cells presented archaellum filaments that were highly similar in architecture to those of the parent strain, N-linked glycan truncation greatly affected interactions between archaellum filaments, leading to dramatic clustering of both isolated and cell-attached filaments. We propose that the N-linked tetrasaccharides decorating archaellins act as physical spacers that minimize the archaellum filament aggregation that limits cell motility.

Factors affecting macromolecule orientations in thin films formed in cryo-EM

The formation of a vitrified thin film embedded with randomly oriented macromolecules is an essential prerequisite for cryogenic sample electron microscopy. Most commonly, this is achieved using the plunge-freeze method first described nearly 40 years ago. Although this is a robust method, the behaviour of different macromolecules shows great variation upon freezing and often needs to be optimized to obtain an isotropic, high-resolution reconstruction. For a macromolecule in such a film, the probability of encountering the air-water interface in the time between blotting and freezing and adopting preferred orientations is very high. 3D reconstruction using preferentially oriented particles often leads to anisotropic and uninterpretable maps. Currently, there are no general solutions to this prevalent issue, but several approaches largely focusing on sample preparation with the use of additives and novel grid modifications have been attempted. In this study, the effect of physical and chemical factors on the orientations of macromolecules was investigated through an analysis of selected well studied macromolecules, and important parameters that determine the behaviour of proteins on cryo-EM grids were revealed. These insights highlight the nature of the interactions that cause preferred orientations and can be utilized to systematically address orientation bias for any given macromolecule and to provide a framework to design small-molecule additives to enhance sample stability and behaviour.

TMPRSS2 and glycan receptors synergistically facilitate coronavirus entry

The entry of coronaviruses is initiated by spike recognition of host cellular receptors, involving proteinaceous and/or glycan receptors. Recently, TMPRSS2 was identified as the proteinaceous receptor for HCoV-HKU1 alongside sialoglycan as a glycan receptor. However, the underlying mechanisms for viral entry remain unknown. Here, we investigated the HCoV-HKU1C spike in the inactive, glycan-activated, and functionally anchored states, revealing that sialoglycan binding induces a conformational change of the NTD and promotes the neighboring RBD of the spike to open for TMPRSS2 recognition, exhibiting a synergistic mechanism for the entry of HCoV-HKU1. The RBD of HCoV-HKU1 features an insertion subdomain that recognizes TMPRSS2 through three previously undiscovered interfaces. Furthermore, structural investigation of HCoV-HKU1A in combination with mutagenesis and binding assays confirms a conserved receptor recognition pattern adopted by HCoV-HKU1. These studies advance our understanding of the complex viral-host interactions during entry, laying the groundwork for developing new therapeutics against coronavirus-associated diseases.

Structural insights into the GTP-driven monomerization and activation of a bacterial LRRK2 homolog using allosteric nanobodies

Roco proteins entered the limelight after mutations in human LRRK2 were identified as a major cause of familial Parkinson's disease. LRRK2 is a large and complex protein combining a GTPase and protein kinase activity, and disease mutations increase the kinase activity, while presumably decreasing the GTPase activity. Although a cross-communication between both catalytic activities has been suggested, the underlying mechanisms and the regulatory role of the GTPase domain remain unknown. Several structures of LRRK2 have been reported, but structures of Roco proteins in their activated GTP-bound state are lacking. Here, we use single-particle cryo-electron microscopy to solve the structure of a bacterial Roco protein (CtRoco) in its GTP-bound state, aided by two conformation-specific nanobodies: NbRoco1 and NbRoco2. This structure presents CtRoco in an active monomeric state, featuring a very large GTP-induced conformational change using the LRR-Roc linker as a hinge. Furthermore, this structure shows how NbRoco1 and NbRoco2 collaborate to activate CtRoco in an allosteric way. Altogether, our data provide important new insights into the activation mechanism of Roco proteins, with relevance to LRRK2 regulation, and suggest new routes for the allosteric modulation of their GTPase activity.

Machine learning approaches to cryoEM density modification differentially affect biomacromolecule and ligand density quality

The application of machine learning to cryogenic electron microscopy (cryoEM) data analysis has added a valuable set of tools to the cryoEM data processing pipeline. As these tools become more accessible and widely available, the implications of their use should be assessed. We noticed that machine learning map modification tools can have differential effects on cryoEM densities. In this perspective, we evaluate these effects to show that machine learning tools generally improve densities for biomacromolecules while generating unpredictable results for ligands. This unpredictable behavior manifests both in quantitative metrics of map quality and in qualitative investigations of modified maps. The results presented here highlight the power and potential of machine learning tools in cryoEM, while also illustrating some of the risks of their unexamined use.

Overcoming the preferred orientation problem in cryoEM with self-supervised deep-learning

While advances in single-particle cryoEM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the so-called "preferred" orientation problem) remains a complication for most specimens. Existing solutions have relied on biochemical and physical strategies applied to the specimen and are often complex and challenging. Here, we develop spIsoNet, an end-to-end self-supervised deep-learning-based software to address the preferred orientation problem. Using preferred-orientation views to recover molecular information in under-sampled views, spIsoNet improves both angular isotropy and particle alignment accuracy during 3D reconstruction. We demonstrate spIsoNet's capability of generating near-isotropic reconstructions from representative biological systems with limited views, including ribosomes, β-galactosidases, and a previously intractable hemagglutinin trimer dataset. spIsoNet can also be generalized to improve map isotropy and particle alignment of preferentially oriented molecules in subtomogram averaging. Therefore, without additional specimen-preparation procedures, spIsoNet provides a general computational solution to the preferred orientation problem.

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.

Structural basis for autoinhibition by the dephosphorylated regulatory domain of Ycf1

Yeast Cadmium Factor 1 (Ycf1) sequesters glutathione and glutathione-heavy metal conjugates into yeast vacuoles as a cellular detoxification mechanism. Ycf1 belongs to the C subfamily of ATP Binding Cassette (ABC) transporters characterized by long flexible linkers, notably the regulatory domain (R-domain). R-domain phosphorylation is necessary for activity, whereas dephosphorylation induces autoinhibition through an undefined mechanism. Because of its transient and dynamic nature, no structure of the dephosphorylated Ycf1 exists, limiting understanding of this R-domain regulation. Here, we capture the dephosphorylated Ycf1 using cryo-EM and show that the unphosphorylated R-domain indeed forms an ordered structure with an unexpected hairpin topology bound within the Ycf1 substrate cavity. This architecture and binding mode resemble that of a viral peptide inhibitor of an ABC transporter and the secreted bacterial WXG peptide toxins. We further reveal the subset of phosphorylation sites within the hairpin turn that drive the reorganization of the R-domain conformation, suggesting a mechanism for Ycf1 activation by phosphorylation-dependent release of R-domain mediated autoinhibition.

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.

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.

Structure of Escherichia coli exonuclease VII

Exonuclease VII (ExoVII) is a ubiquitous bacterial nuclease. Encoded by the xseA and xseB genes, ExoVII participates in multiple nucleic acid-dependent pathways including the processing of multicopy single-stranded DNA and the repair of covalent DNA-protein crosslinks (DPCs). Although many biochemical properties of ExoVII have been defined, little is known about its structure/function relationships. Here, we use cryoelectron microscopy (cryoEM) to determine that Escherichia coli ExoVII comprises a highly elongated XseA4·XseB24 holo-complex. Each XseA subunit dimerizes through a central extended α-helical segment decorated by six XseB subunits and a C-terminal, domain-swapped β-barrel element; two XseA2·XseB12 subcomplexes further associate using N-terminal OB (oligonucleotide/oligosaccharide-binding) folds and catalytic domains to form a spindle-shaped, catenated octaicosamer. The catalytic domains of XseA, which adopt a nuclease fold related to 3-dehydroquinate dehydratases, are sequestered in the center of the complex and accessible only through large pores formed between XseA tetramers. The architectural organization of ExoVII, combined with biochemical studies, indicate that substrate selectivity is controlled by steric access to its nuclease elements and that tetramer dissociation results from substrate DNA binding. Despite a lack of sequence and fold homology, the physical organization of ExoVII is reminiscent of Mre11·Rad50/SbcCD ATP (adenosine triphosphate)-dependent nucleases used in the repair of double-stranded DNA breaks, including those formed by DPCs through aberrant topoisomerase activity, suggesting that there may have been convergent evolutionary pressure to contend with such damage events.

Scaling up cryo-EM for biology and chemistry: The journey from niche technology to mainstream method

Cryoelectron microscopy (cryo-EM) methods have made meaningful contributions in a wide variety of scientific research fields. In structural biology, cryo-EM routinely elucidates molecular structure from isolated biological macromolecular complexes or in a cellular context by harnessing the high-resolution power of the electron in order to image samples in a frozen, hydrated environment. For structural chemistry, the cryo-EM method popularly known as microcrystal electron diffraction (MicroED) has facilitated atomic structure generation of peptides and small molecules from their three-dimensional crystal forms. As cryo-EM has grown from an emerging technology, it has undergone modernization to enable multimodal transmission electron microscopy (TEM) techniques becoming more routine, reproducible, and accessible to accelerate research across multiple disciplines. We review recent advances in modern cryo-EM and assess how they are contributing to the future of the field with an eye to the past.

Tad and toxin-coregulated pilus structures reveal unexpected diversity in bacterial type IV pili

Type IV pili (T4P) are ubiquitous in both bacteria and archaea. They are polymers of the major pilin protein, which has an extended and protruding N-terminal helix, α1, and a globular C-terminal domain. Cryo-EM structures have revealed key differences between the bacterial and archaeal T4P in their C-terminal domain structure and in the packing and continuity of α1. This segment forms a continuous α-helix in archaeal T4P but is partially melted in all published bacterial T4P structures due to a conserved helix breaking proline at position 22. The tad (tight adhesion) T4P are found in both bacteria and archaea and are thought to have been acquired by bacteria through horizontal transfer from archaea. Tad pilins are unique among the T4 pilins, being only 40 to 60 residues in length and entirely lacking a C-terminal domain. They also lack the Pro22 found in all high-resolution bacterial T4P structures. We show using cryo-EM that the bacterial tad pilus from Caulobacter crescentus is composed of continuous helical subunits that, like the archaeal pilins, lack the melted portion seen in other bacterial T4P and share the packing arrangement of the archaeal T4P. We further show that a bacterial T4P, the Vibrio cholerae toxin coregulated pilus, which lacks Pro22 but is not in the tad family, has a continuous N-terminal α-helix, yet its α1 s are arranged similar to those in other bacterial T4P. Our results highlight the role of Pro22 in helix melting and support an evolutionary relationship between tad and archaeal T4P.

Overview of Membrane Protein Sample Preparation for Single-Particle Cryo-Electron Microscopy Analysis

Single-particle cryo-electron microscopy (cryo-EM SPA) has recently emerged as an exceptionally well-suited technique for determining the structure of membrane proteins (MPs). Indeed, in recent years, huge increase in the number of MPs solved via cryo-EM SPA at a resolution better than 3.0 Å in the Protein Data Bank (PDB) has been observed. However, sample preparation remains a significant challenge in the field. Here, we evaluated the MPs solved using cryo-EM SPA deposited in the PDB in the last two years at a resolution below 3.0 Å. The most critical parameters for sample preparation are as follows: (i) the surfactant used for protein extraction from the membrane, (ii) the surfactant, amphiphiles, nanodiscs or other molecules present in the vitrification step, (iii) the vitrification method employed, and (iv) the type of grids used. The aim is not to provide a definitive answer on the optimal sample conditions for cryo-EM SPA of MPs but rather assess the current trends in the MP structural biology community towards obtaining high-resolution cryo-EM structures.