Journal of Structural Biology

Cryogenic-electron microscopy (cryo-EM) has revolutionized the field of protein structural biology. The structures of large membrane proteins are now routinely determined by cryo-EM to near atomic resolution. However, in the medium resolution range of cryo-EM maps (>[~]2 [A]), negatively charged sidechains of acidic residues are not well-resolved due to the negative electrostatic potential of the region. This may lead to incorrect sidechain models for residues like glutamic acid or aspartic acid that are central for proton transfer activity in various respiratory and photosynthetic enzymes. We previously proposed that the acidic residues with weak or non-existent cryo-EM density can be modeled to represent their low proton affinity conformations. Here, we tested this hypothesis on a larger data set of acidic amino acid residues in two high-resolution respiratory complex I structures. By using faster sidechain modeling and proton affinity prediction tools, we created a workflow that generates sidechain conformations of selected amino acid residues. We validated the sidechain conformation predictions by Q-score analysis and atomistic molecular dynamics simulations in different charged states. The proposed workflow provides a way to rapidly obtain sidechain conformations of acidic residues with weak cryo-EM densities and can be integrated into the existing cryo-EM modeling pipelines to speed up sidechain rotamer prediction.

Cryo-electron microscopy (cryo-EM) of biological specimens is limited by radiation damage and a low signal-to-noise ratio (SNR). Here, we show that reducing the illuminated area substantially slows the observed diffraction decay in protein microcrystals. We further show that narrow parallel-beam electron diffraction from thin non-crystalline biological specimens provides substantially higher reciprocal-space SNR than conventional cryo-EM imaging. We developed a multimodal scanning workflow, 4D-para-STEM, that records narrow-beam diffraction patterns together with corresponding images. Using viruses, peptide assemblies, and microtubules, we demonstrate interpretable diffraction signals from both crystalline and non-crystalline biological specimens. Together, these results show that narrow parallel-beam scanning reduces observed radiation damage and improves the SNR in cryo-EM.

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables the acquisition of diffraction patterns at every probe position in a dense array. For imaging applications this approach offers significant benefits in terms of spatial resolution and contrast enhancement. In this work, we present the development of a synchronous scan generator integrated with SerialEM software to enable automation of complex experimental protocols such as tomography. The proposed hardware functions as an interface between SerialEM, the scan controls of the microscope, a fast annular dark-field detector, and a synchronized trigger for a pixelated detector. Our previous implementation, named SavvyScan, relied on a dedicated computer equipped with a multichannel acquisition and signal-generation cards, as well as a separate microcontroller for synchronization. Here, we report a low-cost implementation based on a Red Pitaya board, utilizing direct programming of its embedded FPGA and Linux server components. We provide detailed instructions for system installation and operation, along with practical guidance for modifying the source code. System performance is validated through oscilloscope measurements and imaging of a replica grating sample. The utility of the approach is further demonstrated by generating a 3D electron tomogram of a cryogenic sample of mitochondria from a tilt series of shadow montage projections.

Cryogenic electron microscopy (cryoEM) is now routinely used for high-resolution structure determination of biological macromolecules. However, many biological specimens exhibit varying degrees of preferred orientation on cryoEM grids, resulting in uneven sampling of three-dimensional Fourier space. This orientation bias produces anisotropic reconstruction artifacts and, in severe cases, can exacerbate particle misalignment during iterative refinement, thereby limiting the success rate of near-atomic resolution cryoEM structure determination. This protocol provides a practical guide for applying spIsoNet, a self-supervised deep-learning method, to mitigate preferred-orientation issues in cryoEM reconstructions. We describe two complementary workflows: (1) map Anisotropy Correction to correct anisotropic artifacts of cryoEM maps and (2) particle Misalignment Correction, which integrates spIsoNet with RELION external reconstruction to improve particle-pose estimation. We demonstrate these workflows using two influenza hemagglutinin (HA) trimer datasets representing moderate and severe degrees of preferred-orientation bias. The protocol includes installation instructions, parameter-selection guidance, quality-control checkpoints and troubleshooting advice, and can typically be completed in ~7 hours on a workstation equipped with four NVIDIA A100 GPUs. Together, these workflows provide step-by-step guidance for using the open-source spIsoNet software to mitigate the preferred-orientation problem directly from experimental data.

Cryo-volume electron microscopy (cryo-vEM) enables near-native visualization of cellular ultrastructure, but its broad use is limited by low image contrast and the high cost of dense voxel-level annotation. Existing automated segmentation methods often generalize poorly across cell types, organelles, and imaging conditions. Here, we introduce SparseSeg, a target-conditioned, sparsity-driven segmentation framework that treats organelle segmentation as a discovery process rather than a closed-set classification task. SparseSeg uses a small number of context-specific exemplars to iteratively propagate reliable supervision through the volume. It combines sparse patch-based sampling, a multi-kernel U-Net, and geometry-consistent refinement to expand accurate segmentation while suppressing context-dependent false positives. Across serial cryo-FIB-SEM and conventional vEM datasets, SparseSeg achieves robust segmentation under extreme sparse annotation, including settings with less than 1% labeled slices. This framework reduces annotation burden while preserving morphological fidelity for quantitative cryo-vEM analysis.

Cryo-volume electron microscopy (CVEM) enables three-dimensional imaging of biological ultrastructure in a near-native state but has been limited by low image contrast and charging artifacts that hinder data interpretation and complicate automation of data acquisition. Here we present an experimental and computational workflow that combines orthogonal cryo-SEM imaging, spot-geometry optimized O+ plasma-FIB milling, dedicated acquisition-control routines, and dedicated image alignment procedure. The workflow enables autonomous acquisition of volumetric datasets from vitrified cells and tissues at [~]15-20 nm isotropic resolution. In addition, sub-volume averaging of 113 nuclear pore complexes extracted from CVEM dataset of Cos-7 cell yielded its reconstruction at 9.4 nm resolution. Together, these results establish CVEM as a robust platform for autonomous high-resolution volumetric imaging and structural analysis of vitrified biological specimens.

Images in the electron microscope are formed by electron scattering and focusing. The spherical geometry of these processes gives rise to two coherent, conjugate spherical wave fronts, known as Ewald spheres. These spheres are associated with the two halves of the contrast transfer function (CTF), and their widths are determined by the focal gradient through the specimen. To properly correct for the CTF, each half of the CTF must be applied to an image individually and integrated into the reconstruction into the corresponding Ewald sphere. Theory indicates that this dual Ewald sphere reconstruction method should recover the maximal amount of information possible. This method was compared to the other reconstruction methods commonly used: the projection approximation (ignoring the Ewald sphere), the simple insertion and the single sideband methods. In simulated reconstructions the dual Ewald sphere method recovered the most information when the correct half of the CTF is matched to the corresponding Ewald sphere. If the wrong half is matched, the result worse than the projection approximation method. Examining reconstructions from real data indicated that the dual Ewald sphere method performs at least as well as the simple insertion method, but not as good as in simulations. The likely reason is the two-fold ambiguity in the assigned orientations of the particle images, which remains an issue to pursue in further studies. In conclusion, the dual Ewald sphere reconstruction method may offer the best way to calculate very high resolution reconstructions when the micrograph quality warrants it. HighlightsO_LIThe dual Ewald sphere reconstruction corrects for the two halves of the CTF. C_LIO_LIThe signs of the two halves of the CTF must correspond to the focal gradient. C_LIO_LIDetermining the focal gradient for individual particle images remains unresolved. C_LIO_LIComplex reconstructions indicate any real space phases are artifacts. C_LI

The human sodium-citrate cotransporter NaCT imports various tri- and dicarboxylates into the cell as TCA cycle intermediates. This substrate uptake process is driven by an inward sodium gradient. The protein is a member of the Divalent Anion-Sodium Symporter (DASS) family. Whereas extensive biochemical and structural studies have been carried out for NaCT, how the substrate binding and translocation is coupled to the sodium gradient remains unclear. Here using single particle cryo-electron microscopy, we determined the structures of the human NaCT protein in three states: sodium-free, in the presence of sodium, and sodium- and substrate-bound. These structures suggest a simultaneous binding mechanism for sodium-substrate coupling, distinct from the sequential binding, conformational selection mechanism previously observed for the bacterial DASS protein VcINDY.

Cryo-correlative light and electron microscopy methods enable targeted structural analysis of fluorescently labelled features in vitrified specimens. However, correlative workflows on high-pressure frozen samples often remain challenging due to the lack of persistent landmarks for reliable sample tracking and image registration between different microscopes. Standard high-pressure freezing carriers provide little intrinsic reference information, as the exposed sample surface is often smooth and rotationally ambiguous, complicating localisation of regions of interest across imaging platforms. Here, we introduce PinCorr, a 3-mm high-pressure freezing carrier with an integrated coordinate system formed by four asymmetrically arranged pillars with distinct geometries. These built-in landmarks remain visible after freezing and provide a stable, sample-independent reference frame for orientation and correlation between cryo-fluorescence microscopy and electron microscopy. We show that PinCorr supports fluorescence-guided cryo-volume imaging, serial lift-out for cryo-electron tomography and freeze-substitution workflows followed by room-temperature on-section correlation. PinCorr thus provides a hardware-based approach to establishing a persistent spatial reference frame in HPF-based correlative imaging workflows for thick and multicellular specimens.

Vacuolar-type ATPases (V-ATPases) are evolutionarily conserved rotary proton pumps that play essential roles in the eukaryotic cell. By coupling ATP hydrolysis in their cytosolic V1 region to proton translocation through their membrane-embedded VO region, V-ATPases establish and maintain an acidic pH in the lumen of several different organelles. Functional diversity in the pump is enabled by multiple paralogous genes for the subunits of the complex, which are expressed in a tissue- and organelle-specific manner. Interactions between V-ATPase and TLDc domain-containing proteins have been shown to regulate the enzyme in yeast and mammals but their relevance in plants has remained unclear. We isolated the endogenous V-ATPase from Arabidopsis thaliana leaves and determined its structure by electron cryomicroscopy. Mass spectrometry showed that most of the enzyme originated from the tonoplast. The structural analysis revealed the full rotary catalytic cycle of the plant V-ATPase, and a combination of structural and biochemical experiments showed S-acylation of subunits AP1 and the tonoplast-specific subunit a3 isoform. A subpopulation of complexes derived from the trans-Golgi network/early endosome was identified and found to bind the TLDc protein OXR5. Together, these findings reveal plant-specific features in V-ATPase and suggest organelle-specific interactions with TLDc proteins, pointing to conserved but context-dependent V-ATPase regulation in eukaryotes.

The translocase of the outer mitochondrial membrane (TOM) complex is the main entry gate for mitochondrial proteins. Approximately 99 % of mitochondrial proteins are synthesized as precursor proteins (preproteins) in the cytosol and subsequently translocated into mitochondria through the TOM complex. The TOM complex exists in a dynamic equilibrium among multiple assembly states through spatial rearrangements of its subunits. The recent cryo-electron microscopy (cryo-EM) studies revealed near-atomic structures of the TOM core dimer, whereas previous biochemical studies indicated the TOM complex functions as a trimer in intact mitochondria. However, the relationship between the core dimer and the functional trimer remains unclear. In the present study, we analyzed the dynamics of the TOM complex using high-speed atomic force microscopy (HS-AFM) to investigate the assembly states and conformation transitions of the TOM complexes. We demonstrated that purified yeast TOM complexes predominantly adopt a trimeric organization but dynamically dissociate into dimeric and monomeric states during HS-AFM observation. The trimeric particles observed by HS-AFM exhibited spherical molecular shapes consistent with a trimeric structural model proposed from previous crosslinking analyses. In contrast, the dissociated dimeric particles closely resembled the dimensions of the TOM core-dimer structures determined by cryo-EM. Furthermore, HS-AFM analyses provided insight into the spatial arrangement of the Tom20 receptor, consistent with previous models of the trimeric TOM complex. These observations enabled characterization of the trimeric TOM complex in vitro and provide a foundation for future structural and functional analyses of TOM complex assembly.

In single particle cryo-EM, analysis of continuous conformational heterogeneity has always been challenging. Both linear and deep learning-based methods treat conformational heterogeneity as perturbations to the consensus average conformation, limiting their capability in analyzing large protein motions. While classic conformational classifications are capable of handling large domain motion, they bin continuous protein dynamics into discrete static substates. Here, we present cryoROLE, a computational tool that extracts the continuous conformational dynamics embedded in the static composite map constructed from multi-body refinement into a landscape of relative orientation between the moving domains. Depicted in real space, the landscape allows intuitive interpretations of domain motion and the population of poses in the conformational space. Applying it to various biological systems reveals hidden conformational dynamics that are relevant to protein functions.

Light scattering in scintillators is a pervasive problem and a key factor limiting X-ray imaging resolution. Here, we shift scintillator radioluminescence from the traditional visible range into the short-wave infrared (SWIR) or near-infrared II (NIR-II, 1000-3000 nm) window to mitigate light scattering and thereby enhance light penetration and X-ray imaging resolution. We present an NIR II MgGa2O4:Ni2+ scintillator with peak emission at 1340 nm, achieving a threefold improvement in X-ray imaging resolution compared with visible scintillators owing to reduced light scattering. This heavy-metal-free NIR-II scintillator exhibits intense radioluminescence comparable to that of conventional visible-emitting CsI:Tl, achieving a detection limit of 56 nanograys per second, ~100-fold lower than typical doses used in medical imaging. We show that this NIR-II scintillator enables high-resolution X-ray radiography of electronic circuit boards and biological tissues.

Soft X-ray tomography (SXT) is an emerging modality for whole-cell 3D imaging in near-native states. However, the effective spatial resolution is limited by optical artifacts characterized by the point spread function (PSF). To achieve optimal resolution via PSF inversion, we propose a measurement-supervised deep learning framework. Bypassing purely data-driven neural networks that are prone to hallucinations, we employ a measurement-supervised, instance-specific optimization strategy strictly constrained by a differentiable SXT formation forward model. The structural fidelity was validated using split-tilt Fourier ring correlation (FRC), ensuring the recovered high-frequency features reflect genuine specimen features rather than random artifacts. Our results demonstrate that this optimization consistently increases FRC resolution and enhances visual ultrastructural details across diverse biological structures. Furthermore, by recovering high-frequency features from sparse-angular projections, we show that spatial resolution can be maintained using only half the radiation exposure. This approach effectively compensates for the degradations caused by angular sparsity, providing a hardware-free computational solution to minimize radiation damage, maximize imaging speed, and overcome the optical and dosimetric limits of SXT.

Bovine ephemeral fever virus (BEFV), a member of the Rhabdoviridae family, is an arthropod-borne pathogen that causes acute febrile disease in cattle. The structural basis of its genome encapsidation and virion assembly remains unexplored, with the current knowledge largely limited to predictions derived from bioinformatic comparisons with other rhabdoviruses. Furthermore, the structural principles that permit the formation of variable-diameter nucleocapsids resulting in the distinctive bullet-shaped morphology of rhabdoviruses remain poorly understood. Here, we report the cryo-electron microscopy structure of the BEFV nucleoprotein (N) in complex with RNA, in the absence of other viral components. The complex predominantly forms circular decameric oligomers that we propose to act as nucleation intermediates during assembly of the bullet-shaped nucleocapsids. Direct subunit interactions are limited to a small polar surface area, with additional intersubunit links mediated by flexible N- and C-terminal loops. These interfaces generate a structurally plastic oligomeric lattice in which neighbouring N subunits can undergo substantial rigid-body rotations and positional rearrangements while preserving conserved local contacts and continuous RNA encapsidation. Such quasi-equivalent interactions provide a plausible mechanism for accommodating the progressive changes in helical diameter required for the transition from the highly curved bullet tip to the wider cylindrical trunk of rhabdovirus nucleocapsids. The assembly is stabilised by the bound RNA molecule, where nine RNA bases are accommodated by each N subunit. The RNA-binding mechanism is consistent with that of VSV, the closest BEFV homologue characterised structurally, but differs at about half of the RNA-binding residues, demonstrating the versatility of the nucleoprotein scaffold in interacting with ssRNA. Comparative analysis with other rhabdoviruses, as well as negative-sense RNA viruses with constant-diameter nucleocapsids, such as Ebola, further confirms the structural features that enable bullet-shaped versus cylindrical nucleocapsid assembly.

Human LonP1 is an ATP-dependent mitochondrial protease that degrades damaged or redundant proteins. Indiscriminate proteolysis by LonP1 is limited through tight coordination of substrate recognition, unfolding, translocation and catalytic cleavage, yet the role of ATP hydrolysis in these individual steps remains unclear. Here, we show that LonP1 binds substrates and cleaves peptide bonds without ATP hydrolysis, whereas degradation of folded proteins strictly depends on ATP-driven unfolding and translocation. Initial substrate binding opens a closed ADP-bound resting state, enabling nucleotide exchange and stimulating ATPase activity. The opening also increases accessibility of the proteolytic chamber, modestly enhancing peptidase activity. Maximal peptidase activity is observed in a transition-state mimic stabilised by ADP{middle dot}AlF, in which substrate is engaged within the translocation channel. Cryo-EM analysis reveals that in this state the proteolytic active sites are no longer occluded, linking ATP-driven substrate translocation to full proteolytic activation. Together, these findings reveal how LonP1 prevents indiscriminate proteolysis during substrate selection by ensuring that efficient proteolysis occurs only in substrate-translocating states. Model of the conformational landscape and functional cycle of LonP1Schematic overview of LonP1 states and their inter-conversion. State transitions are modulated by substrate, nucleotide occupancy, temperature, and inhibitors. Key distinguishing features include the presence or absence of the lateral gap, nucleotide state, substrate engagement within the A-tunnel, and the handedness of the ATPase (A) domains. Additional indicators include the compactness of the proteolytic (P) domain and the presence of substrate density within the N-terminal (N) domain or at the coiled-coil domain (CCD) as well as the position of a loop within the catalytic centre. The depicted cryo-EM structures represent a model of a continuous conformational landscape and correspond to the closest matching biological states and positions within the reaction cycle, but may also capture transient intermediates or conformations stabilised by experimental conditions. The shown atomic models correspond to the states highlighted in larger font (R-state: PDB 7NGL; P1-state: PDB 7NFY; P2-state: PDB 7NGC; closed LonP1-ADP-substrate: PDB 9CC1). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/733973v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@16e0491org.highwire.dtl.DTLVardef@1ee02b1org.highwire.dtl.DTLVardef@f2b47aorg.highwire.dtl.DTLVardef@26f6b2_HPS_FORMAT_FIGEXP M_FIG C_FIG

Biomolecular structure prediction tools such as AlphaFold have achieved remarkable success in predicting structures of single proteins and multiprotein complexes. AlphaFold3 now incorporates the capability to model complexes containing nucleic acids and chemically modified side chains. Investigators can now predict structures of proteins bound to chromatin, where interactions with nucleosomal DNA and histone post-translational modifications converge to control genome function. To evaluate its robustness in modeling chromatin complexes, we benchmarked AlphaFold3 on 115 structures containing nucleosomes whose coordinates were released by the Protein Data Bank after the training set cutoff date. We find that AlphaFold3 excels at predicting histone-driven interactions and accurately models complexes that deposit and recognize post-translational modifications. By contrast, AlphaFold3 struggles to predict structures of chromatin factors that primarily engage nucleosomal DNA, notably transcription factors and chromatin remodelers. Finally, we show that AlphaFold3 can faithfully recapitulate known post-translational modification recognition patterns, matching experimentally determined specificity profiles. This assessment of the capabilities and limitations of AF3 in chromatin structural biology provides a roadmap for its effective application to studies of chromatin regulation and PTM readout, while identifying key areas for future algorithmic refinement. SignificanceStructure prediction with AlphaFold has become an invaluable tool in experimental biology, and the accuracy of many of its predictions has been verified in structural and biochemical studies. With the recent incorporation into AlphaFold3 of nucleic acids and post-translational modifications, this prediction tool can now be applied to chromatin structural biology. Our benchmarking of AlphaFold3 reveals its strengths and weaknesses in predicting structures of proteins bound to nucleosomes, thereby providing a framework for using these models in mechanistic studies of chromatin regulation. We introduce metrics for evaluating structures of nucleosome complexes that highlight AlphaFold3s strengths in predicting protein-nucleosome interactions and post-translational modification specificity.

Structure prediction methods are now highly successful at predicting three-dimensional structures from sequence. However, it is still often desirable to supplement these methods with additional external priors on pairwise distances in the structures. We present a general method for injecting prior information into AlphaFold-like structure predictors by biasing the pair representation to produce desirable features in the distogram, which are then reflected in the structures. We demonstrate this approach to: sample alternate states by selectively pushing or pulling mobile amino acid pairs; integrate NMR NOESY data with structure pre-diction; and improve the success of protein-protein and protein-ligand complex prediction. We demonstrate that this approach is applicable both to AlphaFold2 and a reproduction of AlphaFold 3 (OpenFold3). resTrain is open source, available to all users on GitHub and as a Colab notebook: https://github.com/clami66/resTrain

Methanogenic archaea conserve energy by coupling methyl-group transfer to the generation of a chemiosmotic sodium-ion (Na+) gradient. This central energy-conserving step is catalyzed by the membrane-bound N5-methyl-H4MPT:coenzyme M methyltransferase (Mtr). Here, we present high-resolution cryo-electron microscopy structures of the Mtr complex from Methanosarcina mazei determined under strictly anaerobic conditions. The structures reveal an unexpected, electron-dense metallocluster embedded within the central cavity of the MtrCDE trimer in the membrane plane. Based on the unique topology and density we modeled it as an [FeSC] L-type cluster. It is positioned adjacent to both the coenzyme M substrate and the corrinoid cofactor of MtrA in the MtrA-MtrCDE engaged state, thereby being located right at the catalytic core of the enzyme. We could further show that binding of MtrA to MtrCDE triggers rearrangements within the interface of MtrDE that widen a putative ion-conduction pathway. The proximity of the conserved sodium-binding site to the catalytic center suggests a putative link between methyl-transfer chemistry and Na+ translocation. In a broader context, these findings improve our understanding of how methyl transfer, analogous to redox chemistry, can drive chemiosmotic energy conversion.

Accurate evaluation of extracellular matrix (ECM) mineralization at the nano-scale is essential for establishing relevant in vitro bone models. This is particularly important with the development and increased application of three-dimensional (3D) cell models for biological research. Transmission electron microscopy (TEM) allows to perform ultra-structural analysis of cells and ECM organization, but its application in in vitro bone models remains limited, due to the potential alteration or loss of the mineral phase during sample preparation. In this study, we compared two TEM sample preparation methods - the conventional chemical fixation and the anhydrous methods - to evaluate their ability to preserve the mineralized ECM in MC3T3-E1 cells cultured as monolayers and as alginate-encapsulated bone spheroids. Chemical fixation preserved cellular ultra-structure and collagen organization, allowing for detailed assessment of cells and ECM organization. Although mineral deposits were detected and their needle-like morphology assessed, characterization of more immature deposits was partially limited by the effects of uranyl acetate and the overall sample preparation process, which could lead to alteration or loss of less stable mineral phases. The anhydrous preparation method resulted in limited preservation of cellular and ECM morphology and did not allow reliable identification of mineral deposits. When applied to spheroids, the chemical fixation method preserved the 3D architecture, collagen-rich ECM and inner mineral deposits, confirming spheroids as a relevant model for bone studies. Overall, these results highlight the need for optimized sample preparation strategies that preserve both ultra-structure and mineral components for accurate nano-scale characterization of bone mineralization.