Journal of Structural Biology: X

Researchers using electron microscopy must often balance a trade-off between obtaining high-resolution structural information and preserving sufficient cellular context. At one end of this spectrum, single particle cryo-electron microscopy and cryo-electron tomography provide near-molecular detail but are typically limited to relatively small fields of view. At the other, volume electron microscopy approaches, such as scanning electron microscopy of resin-embedded specimens, capture large cellular volumes but generally at lower resolution. Consequently, linking nanoscale structural information to larger cellular architecture remains a significant challenge. To address this gap, we optimised a transmission electron tomography workflow for resin-embedded malaria parasites that allows us to visualise targeted regions of interest at nanometre-scale resolution while retaining several micrometres of surrounding cellular context. Here, we present our current best-practice pipeline for sample preparation, tomogram acquisition, and reconstruction. In addition, we introduce VolWeaver, a data-processing framework, that integrates high-resolution tomographic datasets into serial section volume reconstructions, enabling the visualisation and interpretation of ultrastructural features within their broader cellular environment.

Dinoflagellate chromosomes adopt a highly condensed and organized morphology, with periodic bands and arches observed by traditional Transmission Electron Microscopy (TEM). However, the limited two-dimensional field of view of TEM has prevented a precise characterization of the inherently three-dimensional organization of dinoflagellate chromosomes. Moreover, given the vast diversity among dinoflagellate species and the lack of a systematic comparison of their chromosomes, it remains unclear whether dinoflagellate chromosomes share common organizational features or instead exhibit significant cell- or species-specific differences. Here, we acquire three whole-nucleus 3D Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) datasets at 4 nm voxel size for each of four dinoflagellate species: Symbiodinium microadriaticum, Breviolum minutum, Fugacium kawagutii, and Crypthecodinium cohnii. We compile these data with previously published image volumes from four additional species and present an analysis of the largest collection of dinoflagellate FIB-SEM images to date. Common features observed across all eight species include the absence of physical confinement or spatial clustering of chromosomes in the nucleus. In addition, by decomposing each chromosome into a weighted sum of orthogonal shapes using Spherical Harmonics Expansion, we find a principal component encapsulating 88% of the total shape variance that is common to all species. However, our analysis also reveals differences in chromosome morphology across species. First, while many chromosomes exhibit surface ridges with left-handed helical twist, the proportion of chromosomes with such ridges varies extensively across species. Second, while chromosomes in most species are discrete and well-separated, chromosomes in F. kawagutii are interconnected in a single contiguous network. Lastly, to our knowledge, we report the first observation in eukaryotic cells of toroid-shaped DNA objects, whose numbers vary dramatically across cells and species. Overall, our results show that dinoflagellate chromosomes exhibit both shared organizational features and pronounced species-specific deviations.

Damage to biological specimens by the electron beam is the fundamental resolution-limiting factor in cryoelectron microscopy (cryo-EM) single particle analysis. There is, however, currently no method to accurately infer fluence-dependent changes to the specimen structure during electron irradiation. We develop a Bayesian framework to fit a sequence of atomic models to a series of cryo-EM reconstructions produced at increasing fluence. In particular, our algorithm is able to infer the ensemble average position and atomic displacement parameter of every atom in the macromolecule as a function of fluence. Application of the algorithm to cryo-EM datasets shows that the molecule expands during imaging and identifies environment-dependent variations in beam-induced damage. We use our results to propose a stochastic process model of this phenomenon. We envisage that our method will lead to a better mechanistic understanding of radiation damage to biological specimens and may contribute to efforts to mitigate its effects.

Visualizing macromolecules within their native cellular context by cryo-electron tomography (cryo-ET) is fundamentally limited by the trade-off between field of view and resolution: Capturing high-resolution information about biomolecules requires high magnification, which restricts the field of view and obscures the cellular context in which those biomolecules function. Collecting montage data by tiling the electron beam over the region of interest offers one solution, although traditional round electron beams cause excessive radiation damage across overlapping regions. We previously made electron beams square in shape, enabling montage collection with minimal overlap and thereby reducing excessive exposure and loss of high-resolution information. Here, we create a pipeline for collecting and processing montage cryo-ET data with square electron beams. We show that square beam montages retain high-resolution information by reconstructing virus-like particles to 3.5 [A] resolution using sub-tomogram averaging, and apply the workflow to imaging a glial cell and malaria parasite lamellae over fields of view up to 65 m2. We also provide a comprehensive protocol to make square beams accessible to the community.

Here, we present MC-Bayes, a Python-based script for processing cryo-electron microscopy EER movies on one or more GPUs using MotionCor3 in a user-friendly manner. Further, it generates the .star files necessary for RELION to perform Bayesian polishing (a.k.a.: reference-based motion correction) with EER movies. Until now, Bayesian polishing of EER data was only possible if the CPU-based "RELIONCor" implementation of MotionCor2 was used, which is sub-optimal on GPU-heavy cryo-EM processing systems. This wrapper was created for those facilities and/or users who may have (many) powerful GPUs, but for whatever reason have few CPU cores or less system RAM. Leveraging MotionCor3, MC-Bayes allows motion correction of EER data 2 or more times faster (depending on system) than the RELION CPU implementation, except in circumstances where dozens or hundreds of CPU cores with high quantities of system RAM can be utilised.

X-ray fiber diffraction patterns exhibit four-fold symmetry that can be exploited, through folding and averaging, to improve signal-to-noise ratio. Accurate folding requires a precise sub-pixel estimate of the symmetry center and precise orientation of the meridional pattern axis to the fiber axis: small center or angular errors blur diffraction features, reduce layer-line sharpness, and introduce errors in spacing measurements. A pixel-level estimate is often too imprecise for this purpose, and detector gaps further complicate the alignment objective. We formulate the masked quadrant-folding problem, define a four-quadrant symmetry loss that consistently excludes invalid pixels, and evaluate several refinement strategies: hierarchical coarse-to-fine grid search; ECC-based rigid registration with global center/orientation correction fitting; ECC registration followed by local gradient refinement; and a hybrid that appends a local grid search on a cropped pattern. Direct gradient optimization from the rough QF alignment was found to be unreliable. Grid search provides a robust, interpretable baseline that directly minimizes the folding objective but is substantially slower than registration; ECC gives a fast near-correct alignment, and the hybrid closes the accuracy gap to brute-force search at a fraction of its runtime. On real datasets with calibration data, applying a calibration center with optimized rotation is effectively optimal. The hybrid center-refinement method has been integrated into the MuscleX package.

The quality of single particle cryo-EM reconstructions can be severely degraded when an insufficient variety of 3D particle orientations is present in the image data, limiting downstream model building and interpretation. However, it is often difficult to ascertain whether or not a particular dataset suffers from such preferred orientation since the required orientation coverage depends on target geometry, alignment accuracy, and particle quality. To simplify diagnosis of preferred orientation, we present two complementary methods. First, the conical Fourier Shell Correlation Area Ratio (cFAR) compares the worst- and best-correlating conical regions of 3D Fourier space to quantify half-map anisotropy into a single, easily interpretable score ranging from zero to one. Second, Relative Signal, a companion to cFAR, directly relates signal content to viewing direction so that under-sampled views can be identified. We characterize our methods and compare them to existing anisotropy detection approaches on synthetic data and on 14 real datasets that span sundry molecular weights and structure types. Implementations of both cFAR and Relative Signal are included in CryoSPARC v4.5 and later versions.

Electron microscopy (EM) is essential for resolving cellular ultrastructure, yet quantitative analysis remains limited by labor-intensive segmentation and the scarcity of generalizable models. Here we present QuantEM, an open-source platform for segmentation and analysis of EM data across imaging modalities, tissues, and species. We assembled the largest curated collection of intracellular EM datasets to date, comprising over 15,000 two-dimensional images and 1,700 three-dimensional acquisitions from more than 600 datasets, including nearly 4,000 newly released acquisitions. Using this resource, we trained an EM-specific vision transformer foundation model and systematically optimized adaptation strategies for organelle segmentation. QuantEM provides pretrained models for mitochondria, endoplasmic reticulum, nuclei, and lipid droplets, integrated with interactive proofreading and downstream quantitative analyses through standalone and napari interfaces. Across diverse naive datasets, QuantEM consistently matches or exceeds existing models on zero-shot segmentation while requiring less data for finetuning. We further demonstrate its utility by revealing previously unrecognized subcellular compartmentation of hepatic glucokinase using immuno-electron microscopy.

Surface layers (S-layers) are paracrystalline protein lattices that form the outermost layer of the cell envelope in most archaea, providing structural support, protecting against external insults, and co-ordinating interactions with their environment. Despite their widespread occurrence, the molecular and structural details of S-layer architecture in hyperthermophilic archaea remain largely unknown. Here, we report the structure and cellular architecture of the S-layer from the hyperthermophilic archaeon Pyrobaculum arsenaticum by combining in situ electron cryotomography with single-particle electron cryomicroscopy, AlphaFold modelling, and peptide-fingerprinting mass spectrometry. We show that the S-layer is formed by an uncharacterised 292-kDa S-layer protein (SLP) extending 37 nm from the cytoplasmic membrane, making it, to our knowledge, the largest SLP structurally characterised to date. This SLP has a remarkable multidomain architecture comprising 19 immunoglobulin-like domains, 14 canonical and five non-canonical, organised into a lattice-forming core, a stalk, and a unique crown domain that stabilise the S-layer. Comparative genomic analyses unearthed homologous colossal SLP candidates across Thermoproteota, indicating that this distinctive architecture is conserved across diverse archaeal lineages. Together, our findings provide a structural framework for understanding the cell-surface organisation in hyperthermophilic archaea and suggest that these colossal S-layers represent a specialised adaptation to life at high temperatures.

Ammonia oxidation initiates nitrification and is closely linked to microbial N2O production. Ammonia monooxygenase (AMO) catalyzes the first and rate-limiting step of nitrification and is widespread across evolutionarily distinct ammonia-oxidizing archaea (AOA) and bacteria (AOB). The ocean is the largest biome for AOA and AOB, which have distinct ecological niches and markedly different sensitivities to nitrification inhibitors. However, the lack of archaeal AMO structures and inhibitor-bound AMO complexes has hindered mechanistic understanding of the architectural, catalytic, and inhibitory divergence between these two enzyme systems. Here, we report high-resolution cryo-electron microscopy (cryo-EM) structures of marine archaeal AMO captured in active and inactivated states within its native membrane environment, together with inhibitor-bound structures of estuarine bacterial AMO. Archaeal AMO forms an unexpected cup-shaped homotrimer composed of eight subunits per protomer and exhibits substantial architectural divergence from bacterial AMO. Integrated structural, biochemical, kinetic, and computational analyses reveal distinct periplasmic architectures, copper-center organization, and hydrophobic channels between archaeal and bacterial AMOs for ammonium acquisition, catalysis and inhibitor response. These findings provide a structural and mechanistic framework for understanding how archaeal and bacterial AMOs have diverged to distinct ammonia-oxidizing strategies and inhibitor susceptibilities across environmentally important ammonia oxidizers.

Accurate assessment of ligand coordinate-density consistency across different resolutions remains challenging in macromolecular crystallography. We introduce the atomic Box Correlation Coefficient (aBCC), an atom-level metric for evaluating the consistency between ligand atomic coordinates and electron density in a resolution-standardized framework. To predict aBCC values from electron-density maps, we developed QAEmap, a machine-learning model based on three-dimensional convolutional neural networks (3D-CNNs). The model was trained using Fourier-truncated electron-density maps and corresponding ligand coordinates generated from high-resolution structures in the Protein Data Bank. It was evaluated using both Fourier-truncated electron-density maps and experimentally determined PDB structures. was evaluated using both Fourier-truncated electron-density maps and experimentally determined PDB structures.The prediction accuracy gradually decreased with decreasing resolution, but remained reliable up to [~]3.5 [A]. These results demonstrate that aBCC enables resolution-standardized atom-wise evaluation of coordinate-density consistency across different resolutions and provide a foundation for further development and refinement of machine learning-based coordinate validation. SynopsisWe introduce the atomic box correlation coefficient (aBCC), a machine learning-based metric for the resolution-standardized atom-level evaluation of ligand coordinate-density consistency in crystallographic structures. aBCC provides a common framework for assessing and communicating the local coordinate reliability between structural biologists and researchers in structure-based drug discovery.

Solution X-ray scattering provides unique structural information on biomolecules under biological conditions, resolving conformational heterogeneity and time-resolved structural changes. The scattering profiles contain limited information, and interpretation largely relies on fitting candidate structures guided by priors. Direct reconstruction of electron density maps is desirable, but so far has been prevented by the difficulty of incorporating such prior knowledge. Here we propose XSSDense, a framework that couples a variational autoencoder trained on electron densities from predicted or simulated protein ensembles with a genetic algorithm to refine densities against scattering data. We validate XSSDense on synthetic data for crambin, recover the conformational heterogeneity of the unfolded state of Avena sativa light-oxygen-voltage sensing domain 2, resolve a de-novo density for the pre-unfolding state of the same protein, and provide a new structural description of the signalling-state ensemble of photoactive yellow protein. XSSDense enables structurally grounded electron density reconstructions that intrinsically capture conformational heterogeneity.

Ferritins are ubiquitous iron homeostasis proteins found across the tree of life that form conserved 24-subunit cages with octahedral (4-3-2) symmetry. New types of ferritins and ferritin-like proteins are being continuously discovered, such as mini-bacterioferritins, which form smaller shells of 12 subunits, and double-ferritin-fold proteins, which act as ferroxidases but do not form shells. Here, we describe double-ferritin-fold proteins from Asgard archaea, dubbed dFTNs, and determine Cryo-EM structure of a representative from Candidatus Heimdallarchaeum endolithica. The protein forms a dodecameric shell with tetrahedral (2-3) symmetry. N-terminal (NTD) and C-terminal (CTD) domains are bridged by an ordered linker and are related by two-fold rotational pseudosymmetry. C-terminal -helix (helix E) that forms the four-fold channel in classic ferritins is repositioned to be the helix 2 out of 5 ferritin domain -helices in dFTN, with two such helices from NTD and two helices from CTD forming a pseudo-four-fold symmetry structural element. Four three-fold channels are formed by NTDs, and four other such channels are formed by CTDs. The overall arrangement of dFTN ferritin domains is similar to that of protomers in classic ferritin shells. Altogether, our findings expand the range of known ferritin family proteins and provide insight into Asgard archaea iron metabolism.

Cation-proton antiporters (CPAs) are vital for the maintenance of ionic homeostasis and normal physiology among diverse cell types. Despite recent insights into K+/H+ exchange transporters, the diversity in their structural organization and regulatory mechanisms of K+-specific CPAs are minimally understood. Here, we explore the architecture of an E. coli CPA1 K+/H+ antiporter, YcgO and its inhibition by the unphosphorylated form of PtsN, the terminal protein of a regulatory phosphorelay, using cryoEM structures at 3.4 [A] and 3.2 [A] resolution, respectively. Homodimeric YcgO bound to K+ ions in the occluded conformation, harbors additional linked cytosolic domains, RCK and CorC, to regulate the movement of the transport helices within the YcgO dimer. These domains are the sites of interaction and efflux inhibition by unphosphorylated PtsN, which interacts with the CorC domains with high affinity and allosterically augments inhibitory interactions of CorC with transport helices of YcgO. Inhibition is relieved leading to constitutive activation, upon disrupting the CorC-transport conduit interface. This study illuminates the structural basis of K+ efflux mediated through regulation of a K+/H+ antiporter in E. coli and related prokaryotes via a metabolic network involving a regulatory phosphorelay.

Quorum sensing in Gram-positive bacteria commonly relies on posttranslationally modified peptide pheromones. In Bacillus subtilis, the prenyltransferase ComQ catalyzes tryptophan prenylation of the quorum-sensing peptide ComX, but the structural basis of this unique peptide modification has remained unclear. Here we identified a previously uncharacterized ComQ homolog, StheQ, and its cognate peptide substrate, StheX, from Sphaerobacter thermophilus and investigated their structural and functional relationship. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis demonstrated that StheQ catalyzes prenylation of the tryptophan residue located second from the C-terminus of StheX. Crystal structures of apo StheQ and its complexes with a farnesyl pyrophosphate analog revealed that StheQ adopts the all--helical fold of the trans-isoprenyl diphosphate synthase (IPPS) superfamily while possessing an active-site architecture adapted for peptide-based indole prenylation. The structures identified a single Mg2+-binding site associated with the first aspartic acid-rich motif and showed no evidence for metal coordination at the pseudo-second aspartic acid-rich motif. Site-directed mutagenesis, complex formation assays, and docking analyses identified a peptide-binding pocket adjacent to the active site and suggested that N215 contributes to productive positioning of the acceptor tryptophan. These findings establish the structural basis for peptide prenylation by a ComQ-family enzyme, providing insight into the evolution of peptide-based indole prenylation within the IPPS superfamily, and support the view that ComQ-family enzymes constitute a distinct functional branch specialized for peptide modification.

Preparing electron-transparent cryo-lamellae is inherently a serial, low-throughput process. During sample handling, milling, and transfer, cryo-fixed cells and their supporting films are subjected to mechanical forces as well as thermal stresses caused by temperature fluctuations. After milling, these extremely thin lamellae remain vulnerable to both mechanical and thermal stress, often leading to cracking or complete disintegration. Consequently, the loss of valuable lamellae is frequently an unavoidable aspect of working with such fragile specimens. In this work, we reconsider the conventional lamella geometry, which is typically a flat, thin cross-sectional slab. During milling, lamellae often become unintentionally bent, complicating the final polishing step required to achieve uniform thinning across their width. To address this limitation, we propose deliberately fabricating lamellae in a pre-bent configuration, i.e. specifically, adopting an arch-shaped profile instead of the traditional flat geometry. The arch shape is intrinsically more mechanically stable than a flat structure, thereby reducing lamella loss due to mechanical failure. Moreover, pre-bent milling patterns facilitate uniform thinning of bent lamellae, which is difficult to achieve using conventional flat milling approaches. In addition to the arch geometry, we investigate corrugated lamellae, characterised by a sinusoidal variation around the plane of a conventional flat lamella. Similarly to the arch shape, the corrugated design offers enhanced mechanical stability compared to traditional flat lamellae. We fabricated a series of test lamellae incorporating both arches and corrugations. High-resolution cryo-TEM imaging was performed to evaluate these structures, demonstrating that non-flat geometries do not compromise cryo-electron tomography performance. Furthermore, finite element method (FEM) simulations were conducted to provide insight into stress distributions within bent and corrugated lamellae.

Immunoglobulin light chain (LC) amyloidosis is a debilitating multiorgan disease with limited treatment options. Sequence and structural variability make LC amyloids particularly challenging for therapeutic targeting. We report four cryo-EM structures of lambda6-LC amyloid fibrils from four organs of two patients. Fibrils from different patients show different N-terminal conformations expanding known repertoire of lambda6-LC amyloid folds. These folds contain a planar beta-arch with a flexible linker containing the complementarity-determining region 2, flanked by N- and C-terminal segments in variable patient-specific conformations. The surface location of the structurally frustrated charged segment may contribute to the overrepresentation of the lambda6-LC family in amyloidosis. These and other lambda6-LC amyloid structures from different patients show different side chain packing. Conversely, cardiac, renal and splenic amyloids from the same patient exhibit similar structures with small peripheral organ-specific variations. Moreover, they show similar orphan densities, suggesting collagen-like triple helices bound to a tyrosine ladder along the fibril spine. Mass spectrometry detects collagen type-VI in tissue-extracted amyloids. Molecular dynamics simulations suggest amyloid binds collagen-VI triple helices via mixed interactions facilitated by the geometric complementarity between the layered amyloid structure and the triple helix. Similar interactions may drive formation of other amyloid-collagen complexes, influencing biological properties of amyloids.

The leukocyte-specific {beta}2-integrin receptor family exerts a wide range of functions: {beta}2-integrins are involved in leukocyte trafficking, where they mediate cell adhesion during inflammatory responses via binding to ICAM-1, ICAM-2, or JAM-C. Furthermore, they are essential for the recognition and phagocytosis of pathogens opsonized by complement. Accordingly, the {beta}2-integrin family is known to be involved in autoimmune and inflammatory diseases, such as systemic lupus erythematosus. Owing to their complex biology, involving multiple conformational transitions, different signaling pathways, and a broad spectrum of ligands, the development of {beta}2-integrin-targeted probes and therapeutics has remained challenging. We aimed to develop macrocyclic peptides, derived from phage display screening, which can be used to unravel ligand binding profiles of {beta}2-integrins with an emphasis on the I domain. The selection of suitable lead peptides, and the characterization of their interaction profiles with different I domains, was enabled by an established in-vitro assay platform. Various peptide sequences were enriched during several rounds of phage display against the I-domain of CR3, of which two peptides with particularly low micromolar binding affinity were further characterized. Both peptides showed direct binding to {beta}2-integrin I-domains and, in a competitive assay, dose-dependent inhibition of the I-domains interactions with their main ligands iC3b and ICAM-1, respectively. These ligand-interfering properties were confirmed in bead- and cell-based adhesion assays. The modulators developed here are expected to provide valuable insight into the (patho-)physiology of CR3 and the other members of the {beta}2-integrin family, as the two peptides were able to compete with different ligands. In the future, this may help to identify potential therapeutic approaches for autoimmune, inflammatory, and age-related diseases.

Single-particle cryo-electron microscopy (cryo-EM) pose estimation is traditionally solved anew for each dataset, where iterative refinement is done from scratch while the estimator learns to store the molecule in its weights. In this work, we show that pose inference is a generalizable, specimen-agnostic operation when conditioned explicitly on a reference volume. We introduce ARCHER, an amortized contrastive classifier that models the pose posterior over a discrete rotation grid. Trained across a variety of protein structures, it operates zero-shot without retraining per structure. This transferability is grounded in Fourier-space information mechanics, where all specimen dependence is captured by the reference structure's power spectrum and spatial extent. ARCHER achieves a median angular error of 5.0{degrees} on 100 held-out test structures and 2.5{degrees} on experimental particles, matching dedicated estimators within 0.16[A] in 3D reconstruction. Crucially, downstream conformational signal is preserved. The leading conformational coordinate correlates at 0.97 with deposited benchmarks, faithfully reconstructing free-energy basins and mobile domains. These results overall demonstrate that cryo-EM pose estimation can be generalized across different structures.

Members of the FAD-dependent oxidoreductase family (IPR050260) play diverse and key roles in maintaining cellular redox balance, yet the functions of many distinct subgroups within this family remain unknown. Here, we define the biochemical and physiological functions of the Haloferax volcanii flavin-dependent oxidoreductase HvFdR (HVO_2345; fdr), a haloarchaeal member of a previously uncharacterized IPR050260 subgroup. HvFdR binds FAD and catalyzes NAD(P)H oxidase, diaphorase and ferredoxin reductase activities, with a kinetic preference for NADPH over NADH and catalytic properties that are strongly influenced by oxygen availability. Under stoichiometric conditions, HvFdR mediates reverse electron transfer to NADP, suggesting that intracellular nicotinamide nucleotide pools regulate electron flow bidirectionally. Consistent with this reversibility, HvFdR bound-FAD exhibits a low midpoint redox potential (-413 mV), supporting its capacity to function as an electron donor. Deletion of fdr impairs growth and elevates intracellular NADPH levels, consistent with a role for HvFdR in maintaining NADP(H) homeostasis. Conserved residues K47 and Y323 are identified as determinants of HvFdR electron transfer activity and may function as a regulatory gate that modulates electron flow while limiting excessive H2O2 production under aerobic conditions. Together, these findings establish HvFdR as an oxygen-responsive flavin-dependent oxidoreductase that contributes to cellular redox homeostasis and provides functional insight into a previously uncharacterized subgroup of the IPR050260 family.