Journal of Structural Biology

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.

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.

Cryo-electron ptychography is an emerging technique for studying radiation-sensitive biological specimens, developed from four-dimensional transmission electron microscopy (4D-STEM). Although ptychography has achieved ultrahigh resolution beyond conventional transmission electron microscopy limits for radiation-resistant samples, its application to frozen hydrated biological specimens currently remains at sub-nanometer resolution. Here we overcome this limitation by implementing electron counting with a hybrid-pixel detector, establishing key technical foundations for near-atomic-resolution cryo-ptychography. This counting approach significantly improves weak signal detection in convergent-beam electron diffraction, enabling ptychographic reconstruction at doses below 1 e-/[A]{superscript 2}. Additionally, we found beam-induced motion is effectively eliminated within single scans, suggesting conventional cryoEMs dose-fractionation approach may need reevaluation. Demonstrating high contrast under both low-dose and tilted conditions, along with achieving 3.59 [A] resolution for the [~]700 kDa T20S proteasome, we validate cryo-electron ptychography as a viable general imaging modality that could complement or surpass conventional phase-contrast cryoEM methods.

Otolith organs are specialized structures of the vertebrate inner ear that provide the inertial mass required for maintaining equilibrium. Mammals possess two otolithic organs, the utricle and the saccule, whereas birds and other non-mammalian vertebrates also retain a third one, the lagena, whose development remains poorly understood and whose function is still debated. In birds, the lagena contains thousands of calcium carbonate biomineral particles, termed otoconia. Here, we reconstruct the developmental crystallization of lagena otoconia in the Japanese quail (Coturnix japonica) throughout embryogenesis. We combine multiscale imaging with structural, compositional, and crystallographic analyses across length scales. We show that lagena mineralization precedes cranial bone formation and proceeds predominantly through the growth of existing otoconia rather than continued nucleation. Otoconia develop through progressive particle growth, alignment, and fusion within a pre-existing organic compartment while maintaining a persistent central core, ultimately forming magnesium calcite biominerals. This maturation is accompanied by progressive nanoscale densification, transforming early mineral deposits into mature hierarchical crystals. This work establishes a developmental model of avian otoconia formation and provides new insights into how hierarchical calcium carbonate crystals are assembled during vertebrate development. Statement of significanceOtoliths are the only calcite based biomineral in our body that has a physiological function, yet their developmental assembly remain incompletely understood. While the utricle and saccule have been extensively investigated across vertebrates, the lagena, a third otolithic organ lost during mammalian evolution, has received comparatively little attention. Here, we combine multiscale imaging and materials characterization to reconstruct the developmental crystallization of lagena otoconia in the Japanese quail. We establish how hierarchical magnesium calcite biominerals emerge through coordinated mineral growth, structural maturation, and crystallization, providing a developmental framework for avian otoconia formation and new insights into the assembly of vertebrate calcium carbonate crystals.

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

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.

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.

Cryo-electron tomography is an expanding technology for the study of macromolecules, viruses, and cells. It is often applied to specimens that are too large or heterogeneous for methods based on 2D image averaging such as single particle analysis, e.g., intracellular membranes or organelles. Current practice records a tilt series of projection images in rotation. Reconstruction is normally an ill-posed mathematical problem. Particularly for the under-determined case of sparse data, discrete tilt angles, and a limited tilt range, characteristic artifacts appear in the reconstructed slices. Much of what appears as noise is in fact structural: the projection of contrast from different planes. Various schemes are employed to regularize the reconstruction, including machine-learning frameworks built on neural networks. To the extent that the noise is structural, it might be suppressed by deconvolution with a suitable kernel. This was demonstrated and has been used regularly in cryo-STEM tomography of thick specimens where the under-sampling problem is particularly acute. Here we present 3dcon as an open-source extension of the entropy-regularized deconvolution algorithm that had been adopted from fluorescence microscopy. It takes advantage of modern computing hardware for convenient and fast processing. Deconvolution is entirely algorithmic, meaning that successful processing of the data does not depend on the data itself. As such it should be robust in a wide variety of applications.

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.

Microtubules are cytoskeletal filaments that are involved in intracellular transport, cell division, and motility. Despite their biological importance, determining their high-resolution structures via cryo-electron microscopy remains a significant technical challenge due to their polymorphisms and pseudo-helical assembly. Current processing workflows are complex, often requiring the integration of multiple software packages and custom scripts, which creates a steep learning curve for many research groups. To address these limitations, we introduce CsMT, a streamlined workflow implemented entirely within the CryoSPARC environment and using synthetic references. CsMT simplifies microtubule reconstruction by utilizing a novel protofilament-pair classification approach, which effectively handles the inherent pseudo-symmetry and structural heterogeneity of microtubules with minimal manual intervention. Our workflow is versatile, capable of processing both undecorated and decorated microtubules while accurately determining seams and performing high-resolution refinement. We demonstrate the efficacy of this workflow by achieving a 2.3 and 2.7 [A] resolution reconstruction of homotypic and heterotypic maps of undecorated microtubules, matching the best-resolved microtubule structures in the field. By unifying the pipeline into a single and portable workflow, CsMT enhances reproducibility and accessibility, empowering more laboratories to explore the structural biology of microtubules and associated proteins, yielding new insights into their function.

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.

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.

Most atomic model refinement methods in cryo-EM fit models to the reconstructed density map and effectively treat Fourier voxels as equally reliable. However, the uncertainty in the estimation of Fourier coefficients is highly anisotropic, primarily due to the common variability in SNR in different frequency shells and the distribution of particle images across viewing directions. First-principles arguments suggest that atomic models should be fitted to particle images rather than volumes; this strategy may be computationally demanding. We show that under certain modeling choices, fitting atomic models to weighted volumes is equivalent to fitting directly to particle images. Furthermore, we argue that various proxies can be used to capture this and other sources of uncertainty and distortions. We propose that the principle can be implemented in most atomic model-fitting software with relative ease, using information readily available in existing pipelines. As a proof of concept, we extracted the necessary information from standard RELION runs and fed it into a modified version of Servalcat in which we implemented a reinterpreted version of the idea.

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 (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.

Current segmentation models are capable of routine identification of biological features in noisy cryogenic electron microscopy (cryoEM) images. However, there are still challenges with complete segmentation of high boundary, thin objects such as bacterial cell envelopes and flagella. Moreover, ultralow-dose cryoEM images pose as an additional challenge to boundary distinctions between the object and background. Here, we present TileBac, a benchmark dataset of ultralow-dose montage tiles of Pantoea sp. YR343 to segment bacterial inner and outer membranes for evaluation of model effectiveness. We show that foundation models outperform convolutional neural networks at continuous bacterial cell envelope segmentation despite having lower performance metrics. We release the TileBac benchmark dataset on Hugging Face for further insights into model architecture development.

Accurate estimation of the contrast transfer function (CTF) of tilt images is a critical first step in cryo electron tomography (cryoET), enabling reliable recovery of high-resolution structural information from thick, heterogeneous specimens. This challenge is especially acute in in situ cryoET, where macromolecules are imaged in their native cellular environment, often at high tilt and through substantial specimen thickness, with correspondingly low signal-to-noise ratios. Although CTF parameters can be later refined using reference-based approaches, accurate initial estimates are critical for downstream processing and the interpretability of tomographic reconstructions, yet they remain difficult to automate. Here, we present Quinoa, a software package designed to address these challenges. Quinoa first validates the tilt geometry and assesses data quality to generate robust initial estimates of defocus and phase shift. These estimates are then refined through optimization of a single global model, enabling precise fitting of the per-image defoci, tilt-dependent astigmatisms, time-dependent phase shifts, the specimen orientation (rotation, tilt and pitch) and the specimen thickness. Notably, and as a key distinguishing feature of this approach is that Quinoa fits equiphase-binned polar power spectra. This substantially reduces the computational cost of optimization without sacrificing accuracy, enabling more progressive and exhaustive refinement passes that further improve robustness. We validated Quinoa using both simulated and experimental data and benchmarked its performance against Warp, Ctfplotter, CTFMeasure, and AreTomo. Our results show that Quinoa is the most robust approach across all simulated cases, maintaining high accuracy even in the simultaneous presence of severe astigmatism, high specimen inclination and variable phase shift. Integrated recovery mechanisms further allow Quinoa to adapt automatically to a wide range of pixel sizes, defoci, astigmatisms and specimen thicknesses. Despite fitting a more complex and dynamic model, Quinoa remains extremely efficient due to extensive GPU acceleration, making it well suited for real-time monitoring during data collection as well as high-throughput offline batch processing. By improving automated CTF estimation in challenging tomographic data, Quinoa supports more accurate structural analysis of cells and tissues in situ.

Although an increasing number of protein structures are determined by cryogenic electron microscopy (cryo-EM), protein structure modeling frequently suffers from residue misassignments and sequence register shifts, particularly in regions with ambiguous density. Here, we present DAQplugin, a ChimeraX plugin that performs real-time evaluation of protein models against cryo-EM density maps using the deep-learning-based residue-wise model quality (DAQ) score. Unlike existing validation tools that are typically applied after model construction, DAQplugin enables real-time deep-learning-based validation during model building and refinement. To our knowledge, DAQplugin is the first tool that provides real-time deep-learning based validation of protein models for cryo-EM map within an interactive modeling environment. In addition to identifying potential modeling errors, DAQplugin also provides guidance for correcting sequence register shifts by suggesting alternative residue placements along the backbone. The computation in this plugin is designed to run efficiently on general CPUs without requiring GPU hardware. Using DAQplugin, users can perform deep-learning-based validation on standard laptops during interactive model building, model-map fitting, and refinement. DAQplugin is able to facilitate more accurate interpretation of cryo-EM density maps and improve the reliability assessment of protein structure models. SynopsisDAQplugin provides real-time residue-wise validation of protein models with cryo-EM maps in ChimeraX.

Plant Light Harvesting Complex II (LHCII) is found in the thylakoid membranes of chloroplasts and balances two roles: energy collection for photosynthesis and energy dissipation to prevent photo-damage when there is excessive sunlight. The mechanism for LHCII to switch between two energetic states has been debated but may involve a pH-triggered conformational change. Here we present single-particle cryo-electron microscopy (EM) structures of "light-harvesting" LHCII in detergent at pH 7.5 and pH 4.5. The high resolution (2.48 [A]) maps provide clear placements for all bound pigments, giving high confidence in the models. Surprisingly, we find that there is little conformational change to the polypeptide between these new light harvesting structures and previously published crystals structures, thought to be energy dissipating. The crossing angles of helix A/B and the Lutein 1-Chlorophyll 612 separation distances are similar. This contrasts with other recent analyses of LHCII by single-particle EM that suggested a change to the helix A/B angle and a reduction in Lutein 1-Chlorophyll 612 separation may trigger quenching and a photoprotective state. The high resolution of our structures also allowed us to investigate small conformational changes of the lutein within L1/L2 binding sites of LHCII, revealing rotations and distortions in the pigment that could lead to changes in energy transfer. In addition, we find that low pH causes LHCII to form a destabilised structure where pigment loss from the V1 binding site (usually violaxanthin or zeaxanthin) correlated with a disordered C-terminus, often for just one LHCII monomer with an LHCII trimer. Overall, our findings have important implications for the molecular mechanism of photoprotection.

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.