Xmipp 3.0: An improved software suite for image processing in electron microscopy

Structure of the iminium reaction intermediate in an engineered aldolase explains the carboligation activity toward arylated ketones and aldehydes

Two structures of fructose 6-phosphate aldolase, the wild-type and an engineered variant containing five active-site mutations, have been solved by cryoelectron microscopy (cryo-EM). The engineered variant affords production of aldols from aryl substituted ketones and aldehydes. This structure was solved to a resolution of 3.1 Å and contains the critical iminium reaction intermediate trapped in the active site. This provides new information that rationalizes the acquired substrate scope and aids in formulating hypotheses of the chemical mechanism. A Tyr residue (Y131) is positioned for a role as catalytic acid/base during the aldol reaction and the different structures demonstrate mobility of this amino acid residue. Further engineering of this fructose 6-phosphate aldolase (FSA) variant, guided by this new structure, identified additional FSA variants that display improved carboligation activities with 2-hydroxyacetophenone and phenylacetaldehyde.

Human P2X4 receptor gating is modulated by a stable cytoplasmic cap and a unique allosteric pocket

P2X receptors (P2XRs) are a family of ATP-gated ion channels comprising homomeric and heteromeric trimers of seven subunits (P2X 1 - P2X 7 ) that confer different rates of desensitization. The helical recoil model of P2XR desensitization proposes the stability of the cytoplasmic cap sets the rate of desensitization, but timing of its formation is unclear for slow-desensitizing P2XRs. We report cryo-EM structures of full-length, wild-type human P2X 4 receptor in apo, antagonist-bound, and desensitized states. Because the apo and antagonist-bound structures of this slow-desensitizing P2XR include an intact cytoplasmic cap while the desensitized state structure does not, the cytoplasmic cap forms before agonist binding. Furthermore, structural and functional data suggests the cytoplasmic cap is stabilized by lipids to slow desensitization and that P2X 4 is further modified by glycosylation and palmitoylation. Finally, our antagonist-bound inhibited state structure reveals features specific to the allosteric ligand-binding pocket in human receptors that empower the development of small-molecule modulators.

Conformational Dynamics of Influenza A Virus Ribonucleoprotein Complexes during RNA Synthesis

Viral ribonucleoproteins (vRNPs) are the cornerstones of viral proliferation, as they form the macromolecular complexes that are responsible for the transcription and replication of most single-stranded RNA viruses. The influenza A virus (IAV) polymerase catalyzes RNA synthesis within the context of vRNPs where genomic viral RNA (vRNA) is packaged by the viral nucleoprotein (NP). We used high-speed atomic force microscopy and electron microscopy to study the conformational dynamics of individual IAV recombinant RNPs (rRNPs) during RNA synthesis. The rRNPs present an annular organization that allows for the real-time tracking of conformational changes in the NP-vRNA template caused by the advancing polymerase. We demonstrate that the rRNPs undergo a well-defined conformational cycle during RNA synthesis, which can be interpreted in light of previous transcription models. We also present initial estimations of the average RNA synthesis rate in the rRNP and its dependence on the nucleotide concentration and stability of the nascent RNA secondary structures. Furthermore, we provide evidence that rRNPs can perform consecutive cycles of RNA synthesis, accounting for their ability to recycle and generate multiple copies of RNA.

Molecular basis for different substrate-binding sites and chaperone functions of the BRICHOS domain

Proteins can misfold into fibrillar or amorphous aggregates and molecular chaperones act as crucial guardians against these undesirable processes. The BRICHOS chaperone domain, found in several otherwise unrelated proproteins that contain amyloidogenic regions, effectively inhibits amyloid formation and toxicity but can in some cases also prevent non-fibrillar, amorphous protein aggregation. Here, we elucidate the molecular basis behind the multifaceted chaperone activities of the BRICHOS domain from the Bri2 proprotein. High-confidence AlphaFold2 and RoseTTAFold predictions suggest that the intramolecular amyloidogenic region (Bri23) is part of the hydrophobic core of the proprotein, where it occupies the proposed amyloid binding site, explaining the markedly reduced ability of the proprotein to prevent an exogenous amyloidogenic peptide from aggregating. However, the BRICHOS-Bri23 complex maintains its ability to form large polydisperse oligomers that prevent amorphous protein aggregation. A cryo-EM-derived model of the Bri2 BRICHOS oligomer is compatible with surface-exposed hydrophobic motifs that get exposed and come together during oligomerization, explaining its effects against amorphous aggregation. These findings provide a molecular basis for the BRICHOS chaperone domain function, where distinct surfaces are employed against different forms of protein aggregation.

Secreted dengue virus NS1 from infection is predominantly dimeric and in complex with high-density lipoprotein

Severe dengue infections are characterized by endothelial dysfunction shown to be associated with the secreted nonstructural protein 1 (sNS1), making it an attractive vaccine antigen and biotherapeutic target. To uncover the biologically relevant structure of sNS1, we obtained infection-derived sNS1 (isNS1) from dengue virus (DENV)-infected Vero cells through immunoaffinity purification instead of recombinant sNS1 (rsNS1) overexpressed in insect or mammalian cell lines. We found that isNS1 appeared as an approximately 250 kDa complex of NS1 and ApoA1 and further determined the cryoEM structures of isNS1 and its complex with a monoclonal antibody/Fab. Indeed, we found that the major species of isNS1 is a complex of the NS1 dimer partially embedded in a high-density lipoprotein (HDL) particle. Crosslinking mass spectrometry studies confirmed that the isNS1 interacts with the major HDL component ApoA1 through interactions that map to the NS1 wing and hydrophobic domains. Furthermore, our studies demonstrated that the sNS1 in sera from DENV-infected mice and a human patient form a similar complex as isNS1. Our results report the molecular architecture of a biological form of sNS1, which may have implications for the molecular pathogenesis of dengue.

Structure-guided mutagenesis of OSCAs reveals differential activation to mechanical stimuli

The dimeric two-pore OSCA/TMEM63 family has recently been identified as mechanically activated ion channels. Previously, based on the unique features of the structure of OSCA1.2, we postulated the potential involvement of several structural elements in sensing membrane tension (Jojoa-Cruz et al., 2018). Interestingly, while OSCA1, 2, and 3 clades are activated by membrane stretch in cell-attached patches (i.e. they are stretch-activated channels), they differ in their ability to transduce membrane deformation induced by a blunt probe (poking). Here, in an effort to understand the domains contributing to mechanical signal transduction, we used cryo-electron microscopy to solve the structure of Arabidopsis thaliana (At) OSCA3.1, which, unlike AtOSCA1.2, only produced stretch- but not poke-activated currents in our initial characterization (Murthy et al., 2018). Mutagenesis and electrophysiological assessment of conserved and divergent putative mechanosensitive features of OSCA1.2 reveal a selective disruption of the macroscopic currents elicited by poking without considerable effects on stretch-activated currents (SAC). Our results support the involvement of the amphipathic helix and lipid-interacting residues in the membrane fenestration in the response to poking. Our findings position these two structural elements as potential sources of functional diversity within the family.

Alignment of density maps in Wasserstein distance

In this article, we propose an algorithm for aligning three-dimensional objects when represented as density maps, motivated by applications in cryogenic electron microscopy. The algorithm is based on minimizing the 1-Wasserstein distance between the density maps after a rigid transformation. The induced loss function enjoys a more benign landscape than its Euclidean counterpart and Bayesian optimization is employed for computation. Numerical experiments show improved accuracy and efficiency over existing algorithms on the alignment of real protein molecules. In the context of aligning heterogeneous pairs, we illustrate a potential need for new distance functions.

Structure-guided mutagenesis of OSCAs reveals differential activation to mechanical stimuli

The dimeric two-pore OSCA/TMEM63 family has recently been identified as mechanically activated ion channels. Previously, based on the unique features of the structure of OSCA1.2, we postulated the potential involvement of several structural elements in sensing membrane tension1. Interestingly, while OSCA1, 2, and 3 clades are activated by membrane stretch in cell-attached patches (i.e., they are stretch-activated channels), they differ in their ability to transduce membrane deformation induced by a blunt probe (poking). In an effort to understand the domains contributing to mechanical signal transduction, we used cryo-electron microscopy to solve the structure of Arabidopsis thaliana (At) OSCA3.1, which, unlike AtOSCA1.2, only produced stretch- but not poke-activated currents in our initial characterization2. Mutagenesis and electrophysiological assessment of conserved and divergent putative mechanosensitive features of OSCA1.2 reveal a selective disruption of the macroscopic currents elicited by poking without considerable effects on stretch-activated currents (SAC). Our results support the involvement of the amphipathic helix and lipid-interacting residues in the membrane fenestration in the response to poking. Our findings position these two structural elements as potential sources of functional diversity within the family.

A deep learning approach to the automatic detection of alignment errors in cryo-electron tomographic reconstructions

Electron tomography is an imaging technique that allows for the elucidation of three-dimensional structural information of biological specimens in a very general context, including cellular in situ observations. The approach starts by collecting a set of images at different projection directions by tilting the specimen stage inside the microscope. Therefore, a crucial preliminary step is to precisely define the acquisition geometry by aligning all the tilt images to a common reference. Errors introduced in this step will lead to the appearance of artifacts in the tomographic reconstruction, rendering them unsuitable for the sample study. Focusing on fiducial-based acquisition strategies, this work proposes a deep-learning algorithm to detect misalignment artifacts in tomographic reconstructions by analyzing the characteristics of these fiducial markers in the tomogram. In addition, we propose an algorithm designed to detect fiducial markers in the tomogram with which to feed the classification algorithm in case the alignment algorithm does not provide the location of the markers. This open-source software is available as part of the Xmipp software package inside of the Scipion framework, and also through the command-line in the standalone version of Xmipp.

Simcryocluster: a semantic similarity clustering method of cryo-EM images by adopting contrastive learning

BACKGROUND

Cryo-electron microscopy (Cryo-EM) plays an increasingly important role in the determination of the three-dimensional (3D) structure of macromolecules. In order to achieve 3D reconstruction results close to atomic resolution, 2D single-particle image classification is not only conducive to single-particle selection, but also a key step that affects 3D reconstruction. The main task is to cluster and align 2D single-grain images into non-heterogeneous groups to obtain sharper single-grain images by averaging calculations. The main difficulties are that the cryo-EM single-particle image has a low signal-to-noise ratio (SNR), cannot manually label the data, and the projection direction is random and the distribution is unknown. Therefore, in the low SNR scenario, how to obtain the characteristic information of the effective particles, improve the clustering accuracy, and thus improve the reconstruction accuracy, is a key problem in the 2D image analysis of single particles of cryo-EM.

RESULTS

Aiming at the above problems, we propose a learnable deep clustering method and a fast alignment weighted averaging method based on frequency domain space to effectively improve the class averaging results and improve the reconstruction accuracy. In particular, it is very prominent in the feature extraction and dimensionality reduction module. Compared with the classification method based on Bayesian and great likelihood, a large amount of single particle data is required to estimate the relative angle orientation of macromolecular single particles in the 3D structure, and we propose that the clustering method shows good results.

CONCLUSIONS

SimcryoCluster can use the contrastive learning method to perform well in the unlabeled high-noise cryo-EM single particle image classification task, making it an important tool for cryo-EM protein structure determination.

Structure of mechanically activated ion channel OSCA2.3 reveals mobile elements in the transmembrane domain

Members of the OSCA/TMEM63 family are mechanically activated ion channels and structures of some OSCA members have revealed the architecture of these channels and structural features that are potentially involved in mechanosensation. However, these structures are all in a similar state and information about the motion of different elements of the structure is limited, preventing a deeper understanding of how these channels work. Here, we used cryoelectron microscopy to determine high-resolution structures of Arabidopsis thaliana OSCA1.2 and OSCA2.3 in peptidiscs. The structure of OSCA1.2 matches previous structures of the same protein in different environments. Yet, in OSCA2.3, the TM6a-TM7 linker adopts a different conformation that constricts the pore on its cytoplasmic side. Furthermore, coevolutionary sequence analysis uncovered a conserved interaction between the TM6a-TM7 linker and the beam-like domain (BLD). Our results reveal conformational heterogeneity and differences in conserved interactions between the TMD and BLD among members of the OSCA family.

Structural Analysis of Protein Complexes by Cryo-Electron Microscopy

Structural studies of bio-complexes using single particle cryo-Electron Microscopy (cryo-EM) is nowadays a well-established technique in structural biology and has become competitive with X-ray crystallography. Development of digital registration systems for electron microscopy images and algorithms for the fast and efficient processing of the recorded images and their following analysis has facilitated the determination of structures at near-atomic resolution. The latest advances in EM have enabled the determination of protein complex structures at 1.4-3 Å resolution for an extremely broad range of sizes (from ~100 kDa up to hundreds of MDa (Bartesaghi et al., Science 348(6239):1147-1151, 2015; Herzik et al., Nat Commun 10:1032, 2019; Wu et al., J Struct Biol X 4:100020, 2020; Zhang et al., Nat Commun 10:5511, 2019; Zhang et al., Cell Res 30(12):1136-1139, 2020; Yip et al., Nature 587(7832):157-161, 2020; https://www.ebi.ac.uk/emdb/statistics/emdb_resolution_year )). In 2022, nearly 1200 structures deposited to the EMDB database were at a resolution of better than 3 Å ( https://www.ebi.ac.uk/emdb/statistics/emdb_resolution_year ).To date, the highest resolutions have been achieved for apoferritin, which comprises a homo-oligomer of high point group symmetry (O432) and has rigid organization together with high stability (Zhang et al., Cell Res 30(12):1136-1139, 2020; Yip et al., Nature 587(7832):157-161, 2020). It has been used as a test object for the assessments of modern cryo-microscopes and processing methods during the last 5 years. In contrast to apoferritin bacterial secretion systems are typical examples of multi protein complexes exhibiting high flexibility owing to their functions relating to the transportation of small molecules, proteins, and DNA into the extracellular space or target cells. This makes their structural characterization extremely challenging (Barlow, Methods Mol Biol 532:397-411, 2009; Costa et al., Nat Rev Microbiol 13:343-359, 2015). The most feasible approach to reveal their spatial organization and functional modification is cryo-electron microscopy (EM). During the last decade, structural cryo-EM has become broadly used for the analysis of the bio-complexes that comprise multiple components and are not amenable to crystallization (Lyumkis, J Biol Chem 294:5181-5197, 2019; Orlova and Saibil, Methods Enzymol 482:321-341, 2010; Orlova and Saibil, Chem Rev 111(12):7710-7748, 2011).In this review, we will describe the basics of sample preparation for cryo-EM, the principles of digital data collection, and the logistics of image analysis focusing on the common steps required for reconstructions of both small and large biological complexes together with refinement of their structures to nearly atomic resolution. The workflow of processing will be illustrated by examples of EM analysis of Type IV Secretion System.

Local defocus estimation in single particle analysis in cryo-electron microscopy

Single Particle analysis (SPA) aims to determine the three-dimensional structure of proteins and macromolecular complexes. The current state of the art has allowed us to achieve near-atomic and even atomic resolutions. To obtain high-resolution structures, a set of well-defined image processing steps is required. A critical one is the estimation of the Contrast Transfer Function (CTF), which considers the sample defocus and aberrations of the microscope. Defocus is usually globally estimated; in this case, it is the same for all the particles in each micrograph. But proteins are ice-embedded at different heights, suggesting that defocus should be measured in a local (per particle) manner. There are four state-of-the-art programs to estimate local defocus (Gctf, Relion, CryoSPARC, and Xmipp). In this work, we have compared the results of these software packages to check whether the resolution improves. We have used the Scipion framework and developed a specific program to analyze local defocus. The results produced by different programs do not show a clear consensus using the current test datasets in this study.

A new algorithm for particle weighted subtraction to decrease signals from unwanted components in single particle analysis

Single particle analysis (SPA) in cryo-electron microscopy (cryo-EM) is highly used to obtain the near-atomic structure of biological macromolecules. The current methods allow users to produce high-resolution maps from many samples. However, there are still challenging cases that require extra processing to obtain high resolution. This is the case when the macromolecule of the sample is composed of different components and we want to focus just on one of them. For example, if the macromolecule is composed of several flexible subunits and we are interested in a specific one, if it is embedded in a viral capsid environment, or if it has additional components to stabilize it, such as nanodiscs. The signal from these components, which in principle we are not interested in, can be removed from the particles using a projection subtraction method. Currently, there are two projection subtraction methods used in practice and both have some limitations. In fact, after evaluating their results, we consider that the problem is still open to new solutions, as they do not fully remove the signal of the components that are not of interest. Our aim is to develop a new and more precise projection subtraction method, improving the performance of state-of-the-art methods. We tested our algorithm with data from public databases and an in-house data set. In this work, we show that the performance of our algorithm improves the results obtained by others, including the localization of small ligands, such as drugs, whose binding location is unknown a priori.

Architecture and regulation of a GDNF-GFRα1 synaptic adhesion assembly

Glial-cell line derived neurotrophic factor (GDNF) bound to its co-receptor GFRα1 stimulates the RET receptor tyrosine kinase, promoting neuronal survival and neuroprotection. The GDNF-GFRα1 complex also supports synaptic cell adhesion independently of RET. Here, we describe the structure of a decameric GDNF-GFRα1 assembly determined by crystallography and electron microscopy, revealing two GFRα1 pentamers bridged by five GDNF dimers. We reconsitituted the assembly between adhering liposomes and used cryo-electron tomography to visualize how the complex fulfils its membrane adhesion function. The GFRα1:GFRα1 pentameric interface was further validated both in vitro by native PAGE and in cellulo by cell-clustering and dendritic spine assays. Finally, we provide biochemical and cell-based evidence that RET and heparan sulfate cooperate to prevent assembly of the adhesion complex by competing for the adhesion interface. Our results provide a mechanistic framework to understand GDNF-driven cell adhesion, its relationship to trophic signalling, and the central role played by GFRα1.

Scipion-EM-ProDy: A Graphical Interface for the ProDy Python Package within the Scipion Workflow Engine Enabling Integration of Databases, Simulations and Cryo-Electron Microscopy Image Processing

Macromolecular assemblies, such as protein complexes, undergo continuous structural dynamics, including global reconfigurations critical for their function. Two fast analytical methods are widely used to study these global dynamics, namely elastic network model normal mode analysis and principal component analysis of ensembles of structures. These approaches have found wide use in various computational studies, driving the development of complex pipelines in several software packages. One common theme has been conformational sampling through hybrid simulations incorporating all-atom molecular dynamics and global modes of motion. However, wide functionality is only available for experienced programmers with limited capabilities for other users. We have, therefore, integrated one popular and extensively developed software for such analyses, the ProDy Python application programming interface, into the Scipion workflow engine. This enables a wider range of users to access a complete range of macromolecular dynamics pipelines beyond the core functionalities available in its command-line applications and the normal mode wizard in VMD. The new protocols and pipelines can be further expanded and integrated into larger workflows, together with other software packages for cryo-electron microscopy image analysis and molecular simulations. We present the resulting plugin, Scipion-EM-ProDy, in detail, highlighting the rich functionality made available by its development.

Novel Artificial Intelligence-Based Approaches for Ab Initio Structure Determination and Atomic Model Building for Cryo-Electron Microscopy

Single particle cryo-electron microscopy (cryo-EM) has emerged as the prevailing method for near-atomic structure determination, shedding light on the important molecular mechanisms of biological macromolecules. However, the inherent dynamics and structural variability of biological complexes coupled with the large number of experimental images generated by a cryo-EM experiment make data processing nontrivial. In particular, ab initio reconstruction and atomic model building remain major bottlenecks that demand substantial computational resources and manual intervention. Approaches utilizing recent innovations in artificial intelligence (AI) technology, particularly deep learning, have the potential to overcome the limitations that cannot be adequately addressed by traditional image processing approaches. Here, we review newly proposed AI-based methods for ab initio volume generation, heterogeneous 3D reconstruction, and atomic model building. We highlight the advancements made by the implementation of AI methods, as well as discuss remaining limitations and areas for future development.

Cryo-EM structure of a plant photosystem II supercomplex with light-harvesting protein Lhcb8 and α-tocopherol

The heart of oxygenic photosynthesis is the water-splitting photosystem II (PSII), which forms supercomplexes with a variable amount of peripheral trimeric light-harvesting complexes (LHCII). Our knowledge of the structure of green plant PSII supercomplex is based on findings obtained from several representatives of green algae and flowering plants; however, data from a non-flowering plant are currently missing. Here we report a cryo-electron microscopy structure of PSII supercomplex from spruce, a representative of non-flowering land plants, at 2.8 Å resolution. Compared with flowering plants, PSII supercomplex in spruce contains an additional Ycf12 subunit, Lhcb4 protein is replaced by Lhcb8, and trimeric LHCII is present as a homotrimer of Lhcb1. Unexpectedly, we have found α-tocopherol (α-Toc)/α-tocopherolquinone (α-TQ) at the boundary between the LHCII trimer and the inner antenna CP43. The molecule of α-Toc/α-TQ is located close to chlorophyll a614 of one of the Lhcb1 proteins and its chromanol/quinone head is exposed to the thylakoid lumen. The position of α-Toc in PSII supercomplex makes it an ideal candidate for the sensor of excessive light, as α-Toc can be oxidized to α-TQ by high-light-induced singlet oxygen at low lumenal pH. The molecule of α-TQ appears to shift slightly into the PSII supercomplex, which could trigger important structure-functional modifications in PSII supercomplex. Inspection of the previously reported cryo-electron microscopy maps of PSII supercomplexes indicates that α-Toc/α-TQ can be present at the same site also in PSII supercomplexes from flowering plants, but its identification in the previous studies has been hindered by insufficient resolution.

Cooperation between bHLH transcription factors and histones for DNA access

The basic helix-loop-helix (bHLH) family of transcription factors recognizes DNA motifs known as E-boxes (CANNTG) and includes 108 members1. Here we investigate how chromatinized E-boxes are engaged by two structurally diverse bHLH proteins: the proto-oncogene MYC-MAX and the circadian transcription factor CLOCK-BMAL1 (refs. 2,3). Both transcription factors bind to E-boxes preferentially near the nucleosomal entry-exit sites. Structural studies with engineered or native nucleosome sequences show that MYC-MAX or CLOCK-BMAL1 triggers the release of DNA from histones to gain access. Atop the H2A-H2B acidic patch4, the CLOCK-BMAL1 Per-Arnt-Sim (PAS) dimerization domains engage the histone octamer disc. Binding of tandem E-boxes5-7 at endogenous DNA sequences occurs through direct interactions between two CLOCK-BMAL1 protomers and histones and is important for circadian cycling. At internal E-boxes, the MYC-MAX leucine zipper can also interact with histones H2B and H3, and its binding is indirectly enhanced by OCT4 elsewhere on the nucleosome. The nucleosomal E-box position and the type of bHLH dimerization domain jointly determine the histone contact, the affinity and the degree of competition and cooperativity with other nucleosome-bound factors.

New measures of anisotropy of cryo-EM maps

We propose two new measures of resolution anisotropy for cryogenic electron microscopy maps: Fourier shell occupancy (FSO), and the Bingham test (BT). FSO varies from 1 to 0, with 1 representing perfect isotropy, and lower values indicating increasing anisotropy. The threshold FSO = 0.5 occurs at Fourier shell correlation resolution. BT is a hypothesis test that complements the FSO to ensure the existence of anisotropy. FSO and BT allow visualization of resolution anisotropy. We illustrate their use with different experimental cryogenic electron microscopy maps.

Unsupervised Cryo-EM Images Denoising and Clustering Based on Deep Convolutional Autoencoder and K-Means+

Cryo-electron microscopy (cryo-EM) is a widely used structural determination technique. Because of the extremely low signal-to-noise ratio (SNR) of images captured by cryo-EM, clustering single-particle cryo-EM images with high accuracy is challenging. To address this, we proposed an iterative denoising and clustering method based on a deep convolutional variational autoencoder and K-means++. The proposed method contains two modules: a denoising ResNet variational autoencoder (DRVAE), and Balance size K-means++ (BSK-means++). First, the DRVAE is trained in a fully unsupervised manner to initialize the neural network and obtain preliminary denoised images. Second, BSK-means++ is built for clustering denoised images, and images closer to class centers are divided into reliable samples. Third, the training of DRVAE is continued, while the class-average images are used as pseudo supervision of reliable samples to reserve more detailed information of denoised images. Finally, the second and third steps mentioned above can be performed jointly and iteratively until convergence occurs. The experimental results showed that the proposed method can generate reliable class average images and achieve better clustering accuracy and normalized mutual information than current methods. This study confirmed that DRVAE with BSK-means++ could achieve a good denoise performance on single-particle cryo-EM images, which can help researchers obtain information such as symmetry and heterogeneity of the target particles. In addition, the proposed method avoids the extreme imbalance of class size, which improves the reliability of the clustering result.

ZART: A novel multiresolution reconstruction algorithm with motion-blur correction for single particle analysis

One of the main purposes of CryoEM Single Particle Analysis is to reconstruct the three-dimensional structure of a macromolecule thanks to the acquisition of many particle images representing different poses of the sample. By estimating the orientation of each projected particle, it is possible to recover the underlying 3D volume by multiple 3D reconstruction methods, usually working either in Fourier or in real space. However, the reconstruction from the projected images works under the assumption that all particles in the dataset correspond to the same conformation of the macromolecule. Although this requisite holds for some macromolecules, it is not true for flexible specimens, leading to motion-induced artefacts in the reconstructed CryoEM maps. In this work, we introduce a new Algebraic Reconstruction Technique called ZART, which is able to include continuous flexibility information during the reconstruction process to improve local resolution and reduce motion blurring. The conformational changes are modelled through Zernike3D polynomials. Our implementation allows for a multiresolution description of the macromolecule adapting itself to the local resolution of the reconstructed map. In addition, ZART has also proven to be a useful algorithm in cases where flexibility is not so dominant, as it improves the overall aspect of the reconstructed maps by improving their local and global resolution.

Septins and K63 ubiquitin chains are present in separate bacterial microdomains during autophagy of entrapped Shigella

During host cell invasion, Shigella escapes to the cytosol and polymerizes actin for cell-to-cell spread. To restrict cell-to-cell spread, host cells employ cell-autonomous immune responses including antibacterial autophagy and septin cage entrapment. How septins interact with the autophagy process to target Shigella for destruction is poorly understood. Here, we employed a correlative light and cryo-soft X-ray tomography (cryo-SXT) pipeline to study Shigella septin cage entrapment in its near-native state. Quantitative cryo-SXT showed that Shigella fragments mitochondria and enabled visualization of X-ray-dense structures (∼30 nm resolution) surrounding Shigella entrapped in septin cages. Using Airyscan confocal microscopy, we observed lysine 63 (K63)-linked ubiquitin chains decorating septin-cage-entrapped Shigella. Remarkably, septins and K63 chains are present in separate bacterial microdomains, indicating they are recruited separately during antibacterial autophagy. Cryo-SXT and live-cell imaging revealed an interaction between septins and LC3B-positive membranes during autophagy of Shigella. Together, these findings demonstrate how septin-caged Shigella are targeted for autophagy and provide fundamental insights into autophagy-cytoskeleton interactions.

Three-dimensional alignment of density maps in cryo-electron microscopy

A common task in cryo-electron microscopy data processing is to compare three-dimensional density maps of macromolecules. In this paper, we propose an algorithm for aligning three-dimensional density maps, which exploits common lines between projection images of the maps. The algorithm is fully automatic and handles rotations, reflections (handedness), and translations between the maps. In addition, the algorithm is applicable to any type of molecular symmetry without requiring any information regarding the symmetry of the maps. We evaluate our alignment algorithm on publicly available density maps, demonstrating its accuracy and efficiency. The algorithm is available at https://github.com/ShkolniskyLab/emalign.

Cryo-EM image alignment: From pair-wise to joint with deep unsupervised difference learning

Cryo-electron microscopy (cryo-EM) single-particle analysis is a revolutionary imaging technique to resolve and visualize biomacromolecules. Image alignment in cryo-EM is an important and basic step to improve the precision of the image distance calculation. However, it is a very challenging task due to high noise and low signal-to-noise ratio. Therefore, we propose a new deep unsupervised difference learning (UDL) strategy with novel pseudo-label guided learning network architecture and apply it to pair-wise image alignment in cryo-EM. The training framework is fully unsupervised. Furthermore, a variant of UDL called joint UDL (JUDL), is also proposed, which is capable of utilizing the similarity information of the whole dataset and thus further increase the alignment precision. Assessments on both real-world and synthetic cryo-EM single-particle image datasets suggest the new unsupervised joint alignment method can achieve more accurate alignment results. Our method is highly efficient by taking advantages of GPU devices. The source code of our methods is publicly available at "http://www.csbio.sjtu.edu.cn/bioinf/JointUDL/" for academic use.

Interaction of the periplasmic chaperone SurA with the inner membrane protein secretion (SEC) machinery

Gram-negative bacteria are surrounded by two protein-rich membranes with a peptidoglycan layer sandwiched between them. Together they form the envelope (or cell wall), crucial for energy production, lipid biosynthesis, structural integrity, and for protection against physical and chemical environmental challenges. To achieve envelope biogenesis, periplasmic and outer-membrane proteins (OMPs) must be transported from the cytosol and through the inner-membrane, via the ubiquitous SecYEG protein-channel. Emergent proteins either fold in the periplasm or cross the peptidoglycan (PG) layer towards the outer-membrane for insertion through the β-barrel assembly machinery (BAM). Trafficking of hydrophobic proteins through the periplasm is particularly treacherous given the high protein density and the absence of energy (ATP or chemiosmotic potential). Numerous molecular chaperones assist in the prevention and recovery from aggregation, and of these SurA is known to interact with BAM, facilitating delivery to the outer-membrane. However, it is unclear how proteins emerging from the Sec-machinery are received and protected from aggregation and proteolysis prior to an interaction with SurA. Through biochemical analysis and electron microscopy we demonstrate the binding capabilities of the unoccupied and substrate-engaged SurA to the inner-membrane translocation machinery complex of SecYEG-SecDF-YidC - aka the holo-translocon (HTL). Supported by AlphaFold predictions, we suggest a role for periplasmic domains of SecDF in chaperone recruitment to the protein translocation exit site in SecYEG. We propose that this immediate interaction with the enlisted chaperone helps to prevent aggregation and degradation of nascent envelope proteins, facilitating their safe passage to the periplasm and outer-membrane.

Equilibrium Dynamics of a Biomolecular Complex Analyzed at Single-amino Acid Resolution by Cryo-electron Microscopy

The biological function of macromolecular complexes depends not only on large-scale transitions between conformations, but also on small-scale conformational fluctuations at equilibrium. Information on the equilibrium dynamics of biomolecular complexes could, in principle, be obtained from local resolution (LR) data in cryo-electron microscopy (cryo-EM) maps. However, this possibility had not been validated by comparing, for a same biomolecular complex, LR data with quantitative information on equilibrium dynamics obtained by an established solution technique. In this study we determined the cryo-EM structure of the minute virus of mice (MVM) capsid as a model biomolecular complex. The LR values obtained correlated with crystallographic B factors and with hydrogen/deuterium exchange (HDX) rates obtained by mass spectrometry (HDX-MS), a gold standard for determining equilibrium dynamics in solution. This result validated a LR-based cryo-EM approach to investigate, with high spatial resolution, the equilibrium dynamics of biomolecular complexes. As an application of this approach, we determined the cryo-EM structure of two mutant MVM capsids and compared their equilibrium dynamics with that of the wild-type MVM capsid. The results supported a previously suggested linkage between mechanical stiffening and impaired equilibrium dynamics of a virus particle. Cryo-EM is emerging as a powerful approach for simultaneously acquiring information on the atomic structure and local equilibrium dynamics of biomolecular complexes.

Cryo-EM captures early ribosome assembly in action

Ribosome biogenesis is a fundamental multi-step cellular process in all domains of life that involves the production, processing, folding, and modification of ribosomal RNAs (rRNAs) and ribosomal proteins. To obtain insights into the still unexplored early assembly phase of the bacterial 50S subunit, we exploited a minimal in vitro reconstitution system using purified ribosomal components and scalable reaction conditions. Time-limited assembly assays combined with cryo-EM analysis visualizes the structurally complex assembly pathway starting with a particle consisting of ordered density for only ~500 nucleotides of 23S rRNA domain I and three ribosomal proteins. In addition, our structural analysis reveals that early 50S assembly occurs in a domain-wise fashion, while late 50S assembly proceeds incrementally. Furthermore, we find that both ribosomal proteins and folded rRNA helices, occupying surface exposed regions on pre-50S particles, induce, or stabilize rRNA folds within adjacent regions, thereby creating cooperativity.

Estimating conformational landscapes from Cryo-EM particles by 3D Zernike polynomials

The new developments in Cryo-EM Single Particle Analysis are helping us to understand how the macromolecular structure and function meet to drive biological processes. By capturing many states at the particle level, it is possible to address how macromolecules explore different conformations, information that is classically extracted through 3D classification. However, the limitations of classical approaches prevent us from fully understanding the complete conformational landscape due to the reduced number of discrete states accurately reconstructed. To characterize the whole structural spectrum of a macromolecule, we propose an extension of our Zernike3D approach, able to extract per-image continuous flexibility information directly from a particle dataset. Also, our method can be seamlessly applied to images, maps or atomic models, opening integrative possibilities. Furthermore, we introduce the ZART reconstruction algorithm, which considers the Zernike3D deformation fields to revert particle conformational changes during the reconstruction process, thus minimizing the blurring induced by molecular motions.

High-Resolution Structural Analysis of Dyneins by Cryo-electron Microscopy

Cryo-electron microscopy (cryo-EM) has become the mainstream technique for studying macromolecular structures. Determining the structures of protein complexes is more accessible to structural biologists than ever before. Nevertheless, obtaining high-resolution structures of molecular motors like dynein is still an extremely challenging goal due to their troublesome behaviors in ice, their exceedingly flexible conformations, and their intricate architectures. Dynein is a large molecular machine that drives the movement of many essential cellular cargos and is also the key force generator that powers ciliary motility. High-resolution structural information of dyneins in different states is critical for the in-depth mechanistic understanding of their roles in cells. Here, we summarize the cryo-EM approaches that we have used to study the structures of outer-arm dynein arrays bound to microtubule doublets. Our approaches can be applied to other similar structures and further optimized to deal with even more complicated targets.

Exploring the Structural Variability of Dynamic Biological Complexes by Single-Particle Cryo-Electron Microscopy

Biological macromolecules and assemblies precisely rearrange their atomic 3D structures to execute cellular functions. Understanding the mechanisms by which these molecular machines operate requires insight into the ensemble of structural states they occupy during the functional cycle. Single-particle cryo-electron microscopy (cryo-EM) has become the preferred method to provide near-atomic resolution, structural information about dynamic biological macromolecules elusive to other structure determination methods. Recent advances in cryo-EM methodology have allowed structural biologists not only to probe the structural intermediates of biochemical reactions, but also to resolve different compositional and conformational states present within the same dataset. This article reviews newly developed sample preparation and single-particle analysis (SPA) techniques for high-resolution structure determination of intrinsically dynamic and heterogeneous samples, shedding light upon the intricate mechanisms employed by molecular machines and helping to guide drug discovery efforts.

Engineering a Novel Self-Assembled Multi-siRNA Nanocaged Architecture with Controlled Enzyme-Mediated siRNA Release

The RNA interference (RNAi) chemical and structural design space has evolved since its original definitions. Although this has led to the development of RNAi molecules that are starting to address the issues of silencing efficiency and delivery to target organs and cells, there is an on-going interest to improve upon their properties to attain wider therapeutic applicability. Taking advantage of the flexibility given by DNA and RNA structural and chemical properties, we here investigated unconventional RNAi encoding structures, designated by caged-siRNA structures (CsiRNAs), to explore novel features that could translate into advantageous properties for cellular delivery and intracellular activity. Using the principles of controlled nucleic acid self-assembly, branched DNA-RNA hybrid intermediates were formed, ultimately leading to the assembly of a "closed" structure encompassing multiple RNAi units. The RNAi active regions are further triggered by an encoded RNAse H-mediated release mechanism, while the overall structure possesses easily addressable anchors for hybridization-based functionalization with active biological moieties. We confirmed the production of correct structures and demonstrated that the encoded RNAi sequences maintain gene silencing activity even within this novel unconventional nanoarchitecture, aided by the intracellularly triggered RNAse H release mechanism. With this design, functionalization is easily achieved with no negative effects on the silencing activity, warranting further development of these novel molecular structures as a multi-RNAi platform for therapeutic delivery.

Structural Studies Reveal that Endosomal Cations Promote Formation of Infectious Coxsackievirus A9 A-Particles, Facilitating RNA and VP4 Release

Coxsackievirus A9 (CVA9), an enterovirus, is a common cause of pediatric aseptic meningitis and neonatal sepsis. During cell entry, enterovirus capsids undergo conformational changes leading to expansion, formation of large pores, externalization of VP1 N termini, and loss of the lipid factor from VP1. Factors such as receptor binding, heat, and acidic pH can trigger capsid expansion in some enteroviruses. Here, we show that fatty acid-free bovine serum albumin or neutral endosomal ionic conditions can independently prime CVA9 for expansion and genome release. Our results showed that CVA9 treatment with albumin or endosomal ions generated a heterogeneous population of virions, which could be physically separated by asymmetric flow field flow fractionation and computationally by cryo-electron microscopy (cryo-EM) and image processing. We report cryo-EM structures of CVA9 A-particles obtained by albumin or endosomal ion treatment and a control nonexpanded virion to 3.5, 3.3, and 2.9 Å resolution, respectively. Whereas albumin promoted stable expanded virions, the endosomal ionic concentrations induced unstable CVA9 virions which easily disintegrated, losing their genome. Loss of most of the VP4 molecules and exposure of negatively charged amino acid residues in the capsid's interior after expansion created a repulsive viral RNA-capsid interface, aiding genome release. IMPORTANCE Coxsackievirus A9 (CVA9) is a common cause of meningitis and neonatal sepsis. The triggers and mode of action of RNA release into the cell unusually do not require receptor interaction. Rather, a slow process in the endosome, independent of low pH, is required. Here, we show by biophysical separation, cryogenic electron microscopy, and image reconstruction that albumin and buffers mimicking the endosomal ion composition can separately and together expand and prime CVA9 for uncoating. Furthermore, we show in these expanded particles that VP4 is present at only ~10% of the occupancy found in the virion, VP1 is externalized, and the genome is repelled by the negatively charged, repulsive inner surface of the capsid that occurs due to the expansion. Thus, we can now link observations from cell biology of infection with the physical processes that occur in the capsid to promote genome uncoating.

Tail proteins of phage SU10 reorganize into the nozzle for genome delivery

Escherichia coli phage SU10 belongs to the genus Kuravirus from the class Caudoviricetes of phages with short non-contractile tails. In contrast to other short-tailed phages, the tails of Kuraviruses elongate upon cell attachment. Here we show that the virion of SU10 has a prolate head, containing genome and ejection proteins, and a tail, which is formed of portal, adaptor, nozzle, and tail needle proteins and decorated with long and short fibers. The binding of the long tail fibers to the receptors in the outer bacterial membrane induces the straightening of nozzle proteins and rotation of short tail fibers. After the re-arrangement, the nozzle proteins and short tail fibers alternate to form a nozzle that extends the tail by 28 nm. Subsequently, the tail needle detaches from the nozzle proteins and five types of ejection proteins are released from the SU10 head. The nozzle with the putative extension formed by the ejection proteins enables the delivery of the SU10 genome into the bacterial cytoplasm. It is likely that this mechanism of genome delivery, involving the formation of the tail nozzle, is employed by all Kuraviruses.

E. coli phage SU10 has a short non-contractile tail. Here, the authors show that after cell binding, nozzle proteins and tail fibers of SU10 change conformation to form a nozzle that enables the delivery of the phage DNA into the bacterial cytoplasm.

SARS-CoV-2 Production, Purification Methods and UV Inactivation for Proteomics and Structural Studies

Severe acute respiratory syndrome coronavirus-2 is the causative agent of COVID-19. During the pandemic of 2019–2022, at least 500 million have been infected and over 6.3 million people have died from COVID-19. The virus is pleomorphic, and due to its pathogenicity is often handled in very restrictive biosafety containments laboratories. We developed two effective and rapid purification methods followed by UV inactivation that allow easy downstream handling of the virus. We monitored the purification through titering, sequencing, mass spectrometry and electron cryogenic microscopy. Although pelleting through a sucrose cushion, followed by gentle resuspension overnight gave the best particle recovery, infectivity decreased, and the purity was significantly worse than if using the size exclusion resin Capto Core. Capto Core can be used in batch mode, and was seven times faster than the pelleting method, obviating the need for ultracentrifugation in the containment laboratory, but resulting in a dilute virus. UV inactivation was readily optimized to allow handling of the inactivated samples under standard operating conditions. When containment laboratory space is limited, we recommend the use of Capto Core for purification and UV for inactivation as a simple, rapid workflow prior, for instance, to electron cryogenic microscopy or cell activation experiments.

Cryo-electron microscopy and image classification reveal the existence and structure of the coxsackievirus A6 virion

Coxsackievirus A6 (CV-A6) has recently overtaken enterovirus A71 and CV-A16 as the primary causative agent of hand, foot, and mouth disease worldwide. Virions of CV-A6 were not identified in previous structural studies, and it was speculated that the virus is unique among enteroviruses in using altered particles with expanded capsids to infect cells. In contrast, the virions of other enteroviruses are required for infection. Here we used cryo-electron microscopy (cryo-EM) to determine the structures of the CV-A6 virion, altered particle, and empty capsid. We show that the CV-A6 virion has features characteristic of virions of other enteroviruses, including a compact capsid, VP4 attached to the inner capsid surface, and fatty acid-like molecules occupying the hydrophobic pockets in VP1 subunits. Furthermore, we found that in a purified sample of CV-A6, the ratio of infectious units to virions is 1 to 500. Therefore, it is likely that virions of CV-A6 initiate infection, like those of other enteroviruses. Our results provide evidence that future vaccines against CV-A6 should target its virions instead of the antigenically distinct altered particles. Furthermore, the structure of the virion provides the basis for the rational development of capsid-binding inhibitors that block the genome release of CV-A6.

A cryo-EM structure for the three conformers of coxsackievirus A6 provides insight into the infection process of this enterovirus, which is responsible for numerous cases of hand, foot, and mouth disease.

Columnar structure of human telomeric chromatin

Telomeres, the ends of eukaryotic chromosomes, play pivotal parts in ageing and cancer and are targets of DNA damage and the DNA damage response^1-5. Little is known about the structure of telomeric chromatin at the molecular level. Here we used negative stain electron microscopy and single-molecule magnetic tweezers to characterize 3-kbp-long telomeric chromatin fibres. We also obtained the cryogenic electron microscopy structure of the condensed telomeric tetranucleosome and its dinucleosome unit. The structure displayed close stacking of nucleosomes with a columnar arrangement, and an unusually short nucleosome repeat  length that comprised about 132 bp DNA wound in a continuous superhelix around histone octamers. This columnar structure is primarily stabilized by the H2A carboxy-terminal and histone amino-terminal tails in a synergistic manner. The columnar conformation results in exposure of the DNA helix, which may make it susceptible to both DNA damage and the DNA damage response. The conformation also exists in an alternative open state, in which one nucleosome is unstacked and flipped out, which exposes the acidic patch of the histone surface. The structural features revealed in this work suggest mechanisms by which protein factors involved in telomere maintenance can access telomeric chromatin in its compact form.

Higher resolution in cryo-EM by the combination of macromolecular prior knowledge and image-processing tools

Single-particle cryo-electron microscopy has become a powerful technique for the 3D structure determination of biological molecules. The last decade has seen an astonishing development of both hardware and software, and an exponential growth of new structures obtained at medium-high resolution. However, the knowledge accumulated in this field over the years has hardly been utilized as feedback in the reconstruction of new structures. In this context, this article explores the use of the deep-learning approach deepEMhancer as a regularizer in the RELION refinement process. deepEMhancer introduces prior information derived from macromolecular structures, and contributes to noise reduction and signal enhancement, as well as a higher degree of isotropy. These features have a direct effect on image alignment and reduction of overfitting during iterative refinement. The advantages of this combination are demonstrated for several membrane proteins, for which it is especially useful because of their high disorder and flexibility.

Estimation of Projection Parameter Distribution and Initial Model Generation in Single-Particle Analysis

This study focused on the problem of projection parameter search in 3D reconstruction using single-particle analysis. We treated the sampling distribution for the parameter search as a prior distribution and designed a probabilistic model for efficient parameter estimation. Using our method, we showed that it is possible to perform 3D reconstruction from synthetic and actual electron microscope images using an initial model, and to generate the initial model itself. We also examined whether the optimization function used in the stochastic gradient descent method can be applied with loose constraints to improve the convergence of initial model generation and confirmed the effect. In order to investigate the advantage of generating a smooth sampling distribution from the stochastic model, we compared the distribution of estimated projection directions with the conventional method of performing a global search using spherical gridding. As a result, our method, which is simple in both mathematical model and implementation, showed no algorithmic artifacts.

Core and rod structures of a thermophilic cyanobacterial light-harvesting phycobilisome

Cyanobacteria, glaucophytes, and rhodophytes utilize giant, light-harvesting phycobilisomes (PBSs) for capturing solar energy and conveying it to photosynthetic reaction centers. PBSs are compositionally and structurally diverse, and exceedingly complex, all of which pose a challenge for a comprehensive understanding of their function. To date, three detailed architectures of PBSs by cryo-electron microscopy (cryo-EM) have been described: a hemiellipsoidal type, a block-type from rhodophytes, and a cyanobacterial hemidiscoidal-type. Here, we report cryo-EM structures of a pentacylindrical allophycocyanin core and phycocyanin-containing rod of a thermophilic cyanobacterial hemidiscoidal PBS. The structures define the spatial arrangement of protein subunits and chromophores, crucial for deciphering the energy transfer mechanism. They reveal how the pentacylindrical core is formed, identify key interactions between linker proteins and the bilin chromophores, and indicate pathways for unidirectional energy transfer.

Phycobilisome (PBS) absorbs solar energy and transfer the energy to photosynthetic membrane proteins. In this study, the structures of the pentacylindrical core and rod in PBS from a thermophilic cyanobacterium by cryo-electron microscopy.

ScipionTomo: Towards cryo-electron tomography software integration, reproducibility, and validation

Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline.

The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project.

The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.

Structural dynamics of SARS-CoV-2 nucleocapsid protein induced by RNA binding

The nucleocapsid (N) protein of the SARS-CoV-2 virus, the causal agent of COVID-19, is a multifunction phosphoprotein that plays critical roles in the virus life cycle, including transcription and packaging of the viral RNA. To play such diverse roles, the N protein has two globular RNA-binding modules, the N- (NTD) and C-terminal (CTD) domains, which are connected by an intrinsically disordered region. Despite the wealth of structural data available for the isolated NTD and CTD, how these domains are arranged in the full-length protein and how the oligomerization of N influences its RNA-binding activity remains largely unclear. Herein, using experimental data from electron microscopy and biochemical/biophysical techniques combined with molecular modeling and molecular dynamics simulations, we show that, in the absence of RNA, the N protein formed structurally dynamic dimers, with the NTD and CTD arranged in extended conformations. However, in the presence of RNA, the N protein assumed a more compact conformation where the NTD and CTD are packed together. We also provided an octameric model for the full-length N bound to RNA that is consistent with electron microscopy images of the N protein in the presence of RNA. Together, our results shed new light on the dynamics and higher-order oligomeric structure of this versatile protein.

The nucleocapsid (N) protein of the SARS-CoV-2 virus plays an essential role in virus particle assembly as it specifically binds to and wraps the virus genomic RNA into a well-organized structure known as the ribonucleoprotein. Understanding how the N protein wraps around the virus RNA is critical for the development of strategies to inhibit virus assembly within host cells. One of the limitations regarding the molecular structure of the ribonucleoprotein, however, is that the N protein has several unstructured and mobile regions that preclude the resolution of its full atomic structure. Moreover, the N protein can form higher-order oligomers, both in the presence and absence of RNA. Here we employed computational methods, supported by experimental data, to simulate the N protein structural dynamics in the absence and presence of RNA. Our data suggest that the N protein forms structurally dynamic dimers in the absence of RNA, with its structured N- and C-terminal domains oriented in extended conformations. In the presence of RNA, however, the N protein assumes a more compact conformation. Our model for the oligomeric structure of the N protein bound to RNA helps to understand how N protein dimers interact to each other to form the ribonucleoprotein.

Epitope-focused immunogen design based on the ebolavirus glycoprotein HR2-MPER region

The three human pathogenic ebolaviruses: Zaire (EBOV), Bundibugyo (BDBV), and Sudan (SUDV) virus, cause severe disease with high fatality rates. Epitopes of ebolavirus glycoprotein (GP) recognized by antibodies with binding breadth for all three ebolaviruses are of major interest for rational vaccine design. In particular, the heptad repeat 2 -membrane-proximal external region (HR2-MPER) epitope is relatively conserved between EBOV, BDBV, and SUDV GP and targeted by human broadly-neutralizing antibodies. To study whether this epitope can serve as an immunogen for the elicitation of broadly-reactive antibody responses, protein design in Rosetta was employed to transplant the HR2-MPER epitope identified from a co-crystal structure with the known broadly-reactive monoclonal antibody (mAb) BDBV223 onto smaller scaffold proteins. From computational analysis, selected immunogen designs were produced as recombinant proteins and functionally validated, leading to the identification of a sterile alpha motif (SAM) domain displaying the BDBV-HR2-MPER epitope near its C terminus as a promising candidate. The immunogen was fused to one component of a self-assembling, two-component nanoparticle and tested for immunogenicity in rabbits. Robust titers of cross-reactive serum antibodies to BDBV and EBOV GPs and moderate titers to SUDV GP were induced following immunization. To confirm the structural composition of the immunogens, solution NMR studies were conducted and revealed structural flexibility in the C-terminal residues of the epitope. Overall, our study represents the first report on an epitope-focused immunogen design based on the structurally challenging BDBV-HR2-MPER epitope.

Molecular Organisation of Tick-Borne Encephalitis Virus

Tick-borne encephalitis virus (TBEV) is a pathogenic, enveloped, positive-stranded RNA virus in the family Flaviviridae. Structural studies of flavivirus virions have primarily focused on mosquito-borne species, with only one cryo-electron microscopy (cryo-EM) structure of a tick-borne species published. Here, we present a 3.3 Å cryo-EM structure of the TBEV virion of the Kuutsalo-14 isolate, confirming the overall organisation of the virus. We observe conformational switching of the peripheral and transmembrane helices of M protein, which can explain the quasi-equivalent packing of the viral proteins and highlights their importance in stabilising membrane protein arrangement in the virion. The residues responsible for M protein interactions are highly conserved in TBEV but not in the structurally studied Hypr strain, nor in mosquito-borne flaviviruses. These interactions may compensate for the lower number of hydrogen bonds between E proteins in TBEV compared to the mosquito-borne flaviviruses. The structure reveals two lipids bound in the E protein which are important for virus assembly. The lipid pockets are comparable to those recently described in mosquito-borne Zika, Spondweni, Dengue, and Usutu viruses. Our results thus advance the understanding of tick-borne flavivirus architecture and virion-stabilising interactions.

Heterogeneous cryo-EM projection image classification using a two-stage spectral clustering based on novel distance measures

Single-particle cryo-electron microscopy (cryo-EM) has become one of the mainstream technologies in the field of structural biology to determine the three-dimensional (3D) structures of biological macromolecules. Heterogeneous cryo-EM projection image classification is an effective way to discover conformational heterogeneity of biological macromolecules in different functional states. However, due to the low signal-to-noise ratio of the projection images, the classification of heterogeneous cryo-EM projection images is a very challenging task. In this paper, two novel distance measures between projection images integrating the reliability of common lines, pixel intensity and class averages are designed, and then a two-stage spectral clustering algorithm based on the two distance measures is proposed for heterogeneous cryo-EM projection image classification. In the first stage, the novel distance measure integrating common lines and pixel intensities of projection images is used to obtain preliminary classification results through spectral clustering. In the second stage, another novel distance measure integrating the first novel distance measure and class averages generated from each group of projection images is used to obtain the final classification results through spectral clustering. The proposed two-stage spectral clustering algorithm is applied on a simulated and a real cryo-EM dataset for heterogeneous reconstruction. Results show that the two novel distance measures can be used to improve the classification performance of spectral clustering, and using the proposed two-stage spectral clustering algorithm can achieve higher classification and reconstruction accuracy than using RELION and XMIPP.

An anti-PD-1–GITR-L bispecific agonist induces GITR clustering-mediated T cell activation for cancer immunotherapy

Costimulatory receptors such as glucocorticoid-induced tumor necrosis factor receptor–related protein (GITR) play key roles in regulating the effector functions of T cells. In human clinical trials, however, GITR agonist antibodies have shown limited therapeutic effect, which may be due to suboptimal receptor clustering-mediated signaling. To overcome this potential limitation, a rational protein engineering approach is needed to optimize GITR agonist-based immunotherapies. Here we show a bispecific molecule consisting of an anti-PD-1 antibody fused with a multimeric GITR ligand (GITR-L) that induces PD-1-dependent and FcγR-independent GITR clustering, resulting in enhanced activation, proliferation and memory differentiation of primed antigen-specific GITR⁺PD-1⁺ T cells. The anti-PD-1–GITR-L bispecific is a PD-1-directed GITR-L construct that demonstrated dose-dependent, immunologically driven tumor growth inhibition in syngeneic, genetically engineered and xenograft humanized mouse tumor models, with a dose-dependent correlation between target saturation and Ki67 and TIGIT upregulation on memory T cells. Anti-PD-1–GITR-L thus represents a bispecific approach to directing GITR agonism for cancer immunotherapy.

Alvarez and colleagues develop a bispecific anti-PD-1–GITR-L agonist that activates T cells via a mechanism distinct from those found with individual PD-1 and GITR-L agonists and demonstrate its antitumor activity in mice and nonhuman primates.

RbgA ensures the correct timing in the maturation of the 50S subunits functional sites

RbgA is an essential protein for the assembly of the 50S subunit in Bacillus subtilis. Depletion of RbgA leads to the accumulation of the 45S intermediate. A strain expressing a RbgA variant with reduced GTPase activity generates spontaneous suppressor mutations in uL6. Each suppressor strain accumulates a unique 44S intermediate. We reasoned that characterizing the structure of these mutant 44S intermediates may explain why RbgA is required to catalyze the folding of the 50S functional sites. We found that in the 44S particles, rRNA helices H42 and H97, near the binding site of uL6, adopt a flexible conformation and allow the central protuberance and functional sites in the mutant 44S particles to mature in any order. Instead, the wild-type 45S particles exhibit a stable H42-H97 interaction and their functional sites always mature last. The dependence on RbgA was also less pronounced in the 44S particles. We concluded that the binding of uL6 pauses the maturation of the functional sites, but the central protuberance continues to fold. RbgA exclusively binds intermediates with a formed central protuberance and licenses the folding of the functional sites. Through this mechanism, RbgA ensures that the functional sites of the 50S mature last.

CR-I-TASSER: assemble protein structures from cryo-EM density maps using deep convolutional neural networks

Cryo-electron microscopy (cryo-EM) has become a leading approach for protein structure determination, but it remains challenging to accurately model atomic structures with cryo-EM density maps. We propose a hybrid method, CR-I-TASSER, which integrates deep neural-network learning with I-TASSER assembly simulations for automated cryo-EM structure determination. The method is benchmarked on 778 proteins with simulated and experimental density maps, where CR-I-TASSER constructs models with a correct fold (TM-score>0.5) for 643 targets that is 64% higher than the best of other de novo and refinement-based approaches on high-resolution data samples. Detailed data analyses showed that the major advantage of CR-I-TASSER lies in the deep-learning based Cα position prediction, which significantly improves the threading template quality and therefore boosts the accuracy of final models through optimized fragment assembly simulations. These results demonstrate a new avenue to determine cryo-EM protein structures with high accuracy and robustness covering various target types and density-map resolutions.

NMMD: Efficient cryo-EM flexible fitting based on simultaneous Normal Mode and Molecular Dynamics atomic displacements

Atomic models of cryo electron microscopy (cryo-EM) maps of biomolecular conformations are often obtained by flexible fitting of the maps with available atomic structures of other conformations (e.g., obtained by X-ray crystallography). This article presents a new flexible fitting method, NMMD, which combines normal mode analysis (NMA) and molecular dynamics simulation (MD). Given an atomic structure and a cryo-EM map to fit, NMMD simultaneously estimates global atomic displacements based on NMA and local displacements based on MD. NMMD was implemented by modifying EMfit, a flexible fitting method using MD only, in GENESIS 1.4. As EMfit, NMMD can be run with replica exchange umbrella sampling procedure. The new method was tested using a variety of EM maps (synthetic and experimental, with different noise levels and resolutions). The results of the tests show that adding normal modes to MD-based fitting makes the fitting faster (40% in average) and, in the majority of cases, more accurate.

Machine Learning for Structure Determination in Single-Particle Cryo-Electron Microscopy: A Systematic Review

Recently, single-particle cryo-electron microscopy (cryo-EM) has become an indispensable method for determining macromolecular structures at high resolution to deeply explore the relevant molecular mechanism. Its recent breakthrough is mainly because of the rapid advances in hardware and image processing algorithms, especially machine learning. As an essential support of single-particle cryo-EM, machine learning has powered many aspects of structure determination and greatly promoted its development. In this article, we provide a systematic review of the applications of machine learning in this field. Our review begins with a brief introduction of single-particle cryo-EM, followed by the specific tasks and challenges of its image processing. Then, focusing on the workflow of structure determination, we describe relevant machine learning algorithms and applications at different steps, including particle picking, 2-D clustering, 3-D reconstruction, and other steps. As different tasks exhibit distinct characteristics, we introduce the evaluation metrics for each task and summarize their dynamics of technology development. Finally, we discuss the open issues and potential trends in this promising field.