Journal of Structural Biology

Serial-sectioning electron microscopy allows the exploration of the 3D ultrastructure of cells, tissues or whole organisms. Sample preparation is a critical step for this technique, which determines the quality of downstream imaging and analysis. Here we optimize a high-pressure freezing sample-preparation workflow for larvae of the marine annelid Platynereis dumerilii. We tested several fixation and staining methods and screened a large number of specimens by synchrotron X-ray imaging to evaluate specimen integrity and contrast. We further evaluated selected blocks by array tomography SEM to select the best performing protocols. Our protocols and robust workflow could be adapted to similar marine planktonic organisms including ciliated invertebrate larvae.

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.

Cryogenic focused ion beam (cryo-FIB) milling enables cellular cryo-electron tomography but can compromise high-resolution structural information near milled surfaces. Here we establish recombinant human apoferritin (apoF) as a reporter of depth-dependent structural preservation in cellular lamellae. ApoF yielded a 2.05 [A] in situ reconstruction. Apparent FIB damage was most pronounced within the first 15 nm for xenon, 30 nm for gallium, 45 nm for argon and remained detectable at least 75 nm from oxygen-milled surfaces under the workflows tested. Endogenous 70S ribosomes in the same xenon-milled tomograms showed a broader 30-45 nm profile, whereas {beta}-galactosidase showed a similar narrow xenon-associated profile in a different specimen. Xenon-milled lamellae 125-150 nm thick yielded the highest resolution among the thickness groups examined, with lower resolution in the thinner and thickest groups. These findings show structural preservation is constrained by both surface-associated damage and lamella thickness, with the apparent extent of damage varying by molecular reporter. Previous ribosome-based surface-exclusion estimates may therefore be overly conservative for some molecular targets.

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 tomography of 100-200 nm lamellae prepared by focused ion beam milling enables structural analysis of macromolecules within cells, tissues, and small organisms, but lamella preparation remains time-consuming and limits throughput. Although automated workflows enable unsupervised fabrication, they commonly produce variable results because fixed, pre-calibrated parameters are applied without accounting for lamella-to-lamella variability. To overcome these limitations, we developed an Adaptive Milling approach that adapts milling parameters based on imaging feedback. We implemented this approach for the critical polishing stage as Adaptive Polishing, which uses machine-learning-based segmentation of scanning electron microscopy images to identify lamella features predictive of imminent collapse. These are used to periodically assess whether to continue or stop thinning during polishing. We performed a systematic comparison of the quality of lamellae prepared with Adaptive Polishing and conventional automation, and demonstrate that Adaptive Polishing produces thinner lamellae with greater consistency in thickness, and performs well for in situ cryo-electron tomography. Adaptive Polishing was tested on three different microscopes with minimal model retraining required, demonstrating transferability of the approach. We implemented Adaptive Polishing as an open-source plugin for fibsemOS together with machine-learning model training software and pre-trained models.

Cryogenic electron microscopy (cryo-EM) has enabled rapid progress in structural biology throughout the last decade. However, cryo-EM sample preparation still represents a major bottleneck in high-resolution structure determination. Many proteins and macromolecular complexes interact with the air-water interface during sample preparation, which can cause protein denaturation, complex disassembly, and preferred particle orientation. Development of methods to alleviate these issues is an active field of investigation. However, a universally applicable solution to this problem has not been found so far. Here, we describe the simple and cost-effective usage of synthetic peptides with defined amino acid sequence to protect cryo-EM samples from complex disassembly and reduce preferred orientation. We show benefits during cryo-EM grid preparation of a large E3 ubiquitin ligase termed the anaphase-promoting complex (APC/C), and the small CDK11:cyclin L:SAP30BP complex.

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.

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.

Cryogenic plasma focused ion beam-scanning electron microscopy (cryo-pFIB-SEM) enables nanoscale volume imaging of vitrified cells and tissues, but the fidelity of each newly exposed block-face depends on how ions interact with compositionally heterogeneous biological material. Using xenon, argon, oxygen, and nitrogen plasma beams across a 30-2 kV voltage range, we examined how ion species and accelerating voltage influence block-face quality and ultrastructural fidelity. Curtaining imposed a species-dependent lower limit on accelerating voltage, with xenon and argon supporting uniform milling to 10 kV and oxygen and nitrogen to 15 kV. Monte Carlo simulations predicted substantially reduced ion penetration and atomic displacement under these species-specific low-kV conditions. Experimentally, lowering milling voltage suppressed charging and topographic artifacts, with the largest effects observed at heterogeneous interfaces. Oxygen and nitrogen produced greater membrane sharpness and organelle contrast than the noble gases, and these differences influenced machine-learning-based recognition of fine organelle features in 3D datasets. Together, these findings show that cryo-pFIB-SEM image quality cannot be optimized by accelerating voltage or ion species independently. Instead, milling performance reflects a tradeoff among surface fidelity, charging, contrast, and curtaining that depends on local specimen composition. Species-specific low-kV milling therefore provides a practical framework for matching cryo-pFIB-SEM acquisition conditions to the structural and biophysical properties of the biological target.

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.

Single-particle cryo-EM routinely delivers near-atomic structures; however, optimizing data collection requires a delicate balance among magnification, sampling bandwidth, and particle throughput. Although low-magnification super-resolution imaging can recover information beyond the physical Nyquist limit, its benefit varies substantially among specimens. This variability suggests that the effectiveness of super-resolution may depend on whether reconstruction is limited by detector sampling bandwidth or by the recoverable particle signal. However, the conditions that distinguish these two regimes remain poorly defined. Here, we systematically compared super-resolution and physical-pixel workflows at two magnifications using apoferritin (APO) and malate synthase G (MSG) as representative specimens with contrasting molecular size, symmetry, and image contrast. At low magnification, APO exhibited sampling-limited behavior, with super-resolution processing achieving 1.72 Angstrom compared with 2.74 Angstrom for physical-pixel processing. In contrast, MSG exhibited predominantly signal-limited behavior under the same conditions, yielding comparable resolutions of 3.05 Angstrom and 2.98 Angstrom for super-resolution and physical-pixel processing, respectively, despite the increased sampling bandwidth. These contrasting responses were further supported by particle-number saturation, per-particle motion correction, and Q-score analyses, which provided complementary evidence for the underlying sampling-limited and signal-limited regimes. Together, these results provide a practical framework for assessing whether reconstruction quality is predominantly constrained by sampling bandwidth or recoverable particle signal and offer a rational basis for balancing achievable resolution and particle throughput when selecting acquisition strategies.

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.

Preferred particle orientation, which results from the adsorption of proteins to the air-water interface, is a frequently encountered issue in single-particle cryo-electron microscopy (cryo-EM). Particles then present only a limited number of views, which are oversampled during data acquisition at the expense of throughput, while other views may be missing altogether. In severe cases, a high-resolution reconstruction becomes unattainable. We have recently established that ultrasonic excitation of the sample during vitrification improves the angular distribution by detaching particles from the air-water interface and reshuffling their orientations. Here, we describe an implementation of this principle for a plunge freezing apparatus, in which the ultrasonic transducer is integrated into the head of the pair of tweezers holding the sample, and show that this design is able to reduce preferred orientation. We demonstrate this for hemagglutinin, the canonical example of preferred orientation, and show that the fraction of side and tilted views increases with the excitation amplitude. This allows us to obtain a complete reconstruction of the trimer at 2.5 [A].

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 visualisation of large biological samples in cryo-electron tomography requires both few-nanometre resolution and a wide, ideally >10 micrometrre, field of view. For a single image, increasing magnification trades increased resolution for a smaller field of view. Montaging, where high-magnification images are stitched together to increase field of view, addresses the trade-off but is dose-inefficient with round beams that are standard in transmission electron microscopy (TEM), since this illumination shape does not tessellate. Our workflow greatly simplifies montaging schemes for dose-sensitive specimens, allowing large montages of any shape - from individual cells or other features of interest up to whole lamellae - to be collected at high resolution without compromising electron dose efficiency. We demonstrate the workflow by acquiring montage tomograms of whole yeast (Saccharomyces cerevisiae) cells in cryo-FIB lamellae and of human neurons.

The ability of cryo-electron microscopy (cryo-EM) to interrogate the atomic structure and motion of biomolecules has motivated the development of a wide range of algorithms for heterogeneity analysis. However, evaluating and comparing these methods remains challenging because ground-truth structures are generally unknown for experimental samples. Here, we introduce the 2026 Community-Wide Assessment of Heterogeneous Reconstruction Algorithms (CAHRA), a community-wide challenge centered on three benchmark datasets that probe distinct tasks in heterogeneity analysis. These include (1) compositional heterogeneity arising from mixtures of distinct protein complexes, (2) continuous conformational variability and atomic modeling, and (3) entanglement between molecular conformation and particle pose. We describe the design, construction, and validation of these datasets, as well as their use in the recently completed CAHRA Challenge.

Cryo-Electron Microscopy (CryoEM) Single Particle Analysis (SPA) is pivotal for elucidating protein structures and their conformational dynamics. Several critical steps are required to obtain accurate maps. First, the \textit{ab initio} relative orientations and shifts between images must be determined. Second, the common issue of specimens presenting a preferred orientation should be adequately addressed. Third, all of the above must account for particle flexibility and sample heterogeneity. Additionally, these steps are interrelated, making the search for all these parameters a real challenge when considering convergence robustness. In this context, we present ReconSIREN, a novel deep learning framework that addresses the key steps outlined before in an \textit{ab initio} manner while greatly minimizing one of the most important practical burdens in SPA, namely the errors introduced in the CryoEM maps by the existence of preferred orientations; the latter is achieved by a change of the optimization approach that avoids the so-called ``attraction problem'', and by the introduction of a new type of geometrical priors. It does so fully \textit{ab initio}, using deep learning training/inference steps without resorting to more traditional optimization approaches, and generating highly accurate initial reconstructions. We present maps as both homogeneous (consensus) maps and a full conformational landscape for analyzing flexibility and heterogeneity. Thanks to its Mixture-of-Experts (MoE) architecture, ReconSIREN distributes the estimation workload across independent experts, improving optimization efficiency and simplifying the process.

Heterogeneous cryo-EM reconstruction methods can resolve multiple conformational states, but understanding their functional implications often requires determining which regions move between states and quantifying their displacement magnitudes. Comparing atomic models can quantify motion, but flexible regions are often incompletely modeled. Direct map comparison is limited by variable map quality and ambiguous correspondence between displaced density features. Here, we present CryoFlex, a method that estimates the direction and magnitude of structural motion directly from reconstructed density maps of selected states. The resulting motion analysis supports functional interpretation and guides downstream structure processing. CryoFlex localized and quantified structural motion across diverse map pairs, including those with incomplete atomic-model coverage or weak local density. Against C; displacements, CryoFlex achieved an endpoint error of about 1 angstrom. In separate benchmarks, it outperformed registration baselines on clean and noisy inputs. Thus, CryoFlex complements heterogeneous reconstruction workflows with direct quantification of structural motion between reconstructed states.