Journal of Structural Biology: X

Affinity chromatography is a powerful and therefore popular method for the purification of proteins for structural studies. The success of the technique relies on the specificity of the interaction between the target protein and the affinity resin. Here, we present the identification of two protein contaminants isolated from HEK293 cell lysate following affinity purification of twin Strep-tagged or FLAG-tagged proteins. The contaminants were identified as human propionyl-coenzyme A carboxylase (hPCC) and protein arginine methyltransferase 5 in complex with methylosome protein 50 (PRMT5:MEP50) via a combination of cryo-EM data processing and proteomic analyses. This report serves to illustrate how these contaminants may appear in cryo-EM datasets and to highlight the paramount importance of affinity chromatography resin specificity for efficient protein purification.

Standardized biological specimens are essential for optimizing cryoEM workflows and benchmarking instrument performance. While apoferritin fulfills this role for single-particle analysis, no equivalent exists for cryo-electron tomography. Ribosomes are frequently used but require large datasets due to C1 symmetry and structural heterogeneity, limiting rapid optimization and standardized comparison of workflows. Here, we present PP7 virus-like particles (VLPs) overexpressed in E. coli as a scalable in situ benchmark. VLPs have high orders of symmetry enabling rapid, high-resolution validation of tomographic pipelines from minimal datasets, while their distinct structural features across low to high resolutions provide a practical resolution metric.

Structure elucidation of biological macromolecules by single particle cryogenic electron microscopy (SPA cryo-EM) or cryogenic electron tomography (cryo-ET) relies on low-dose imaging on cryogenic transmission electron microscopes (cryo-TEMs). Routine microscope setup remains technically demanding and can be time-consuming, particularly for inexperienced or infrequent users. We present LowDoseWizard, a guided workflow implemented in SerialEM that enables rapid and standardised setup of cryo-TEM imaging conditions. From minimal user input, the workflow configures microscope optics, camera parameters and image shift settings for all low-dose imaging states, and guides the user through key daily alignment procedures including beam shift offset calibration, objective lens astigmatism correction and coma-free alignment. The workflow is organised into modular routines that can be executed sequentially or independently, while microscope-specific acquisition parameters are defined in editable configuration files, allowing flexible adaptation to different instruments without modification of the core scripts. Across user sessions on three microscopes at EMBL Heidelberg, the complete setup required on average less than 15 minutes. To assess whether predefined imaging conditions generated by the workflow are compatible with high-resolution data collection, we acquired apoferritin data on a 200 kV Glacios and a 300 kV Titan Krios. These datasets yielded reconstructions at 1.62 [A] and 1.09 [A] resolution, respectively, demonstrating that rapid, guided setup can support near-atomic and atomic-resolution single particle cryo-EM. LowDoseWizard lowers the barrier to robust cryo-TEM setup, reduces the time spent on routine parameter selection and alignment, and helps users focus on sample-specific aspects of data acquisition such as target selection. The workflow should be particularly valuable in shared instrumentation environments, where accessibility, reproducibility and efficient microscope use are critical.

Cryo-electron tomography (cryo-ET) is fast developing from a tool primarily used to investigate structures of individual macromolecular complexes in situ into a high-resolution probe for molecular processes within diverse functional contexts in intact cells. It is thus increasingly necessary that the data are analyzed and quantified as completely as possible. But annotating and structurally characterizing macromolecular complexes with a high degree of completeness is a significant challenge, especially for smaller molecular targets. In particular, it is difficult to avoid incomplete localizations of complexes, false identifications, or losses during computational classification. To address these issues, we assessed parameters in data processing, including the role of voxel size in template matching, the effects of Volta phase plate imaging on localization, classification, and map refinement, and the extent to which multi-particle-based refinement of tiltseries improves these data processing steps. Our analyses provide practical guidelines that help maximize completeness in cellular cryo-ET data; accurate description of the sample is crucial for visual proteomics experiments, and these optimizations help ensure that data annotation and analysis are comprehensive.

Ligand binding has been shown to induce significant alterations in the conformational landscape of proteins. Traditional crystallography approaches have provided valuable input about the end states in ligand-binding reactions. However, dynamical relationships between ligand binding and backbone rearrangement often remain obscured by crystallographic structures. In the present study, we use time-resolved serial synchrotron crystallography (TR-SSX) to directly visualize indole binding in the cavity of T4 lysozyme L99A in microcrystals under controlled environmental conditions. By integrating fixed target crystallography with LAMA-based ligand delivery, we have been able to track the progression of ligand binding and backbone rearrangement. By utilizing an occupancy refinement protocol, we have been able to quantify structural populations. Our studies reveal that ligand binding for this protein cavity follows a diffusion-limited process that progressively rearranges the F -helix of the protein towards a dominant conformational state. These findings establish an observable link between ligand diffusion, occupancy evolution and conformational adaptation within a crystalline environment. More broadly, our work shows how TR-SSX can quantify ligand and conformational populations during binding, providing a framework to interpret structural adaptation in real time.

Mitochondria are dynamic signaling organelles that transduce metabolic and biochemical cues to facilitate cellular adaptation. Their complex structure and dynamics are essential for integrating metabolic pathways, responding to stressors, and communicating inter- and intra-cellular signals. While optimal mitochondrial activity is frequently linked to cellular and organismal health--influencing processes ranging from metabolism and regulated cell death to differentiation and growth--the mechanistic links between mitochondrial dysfunction and cellular defects leading to human disease remain incompletely understood. Understanding how mitochondrial shape and function are linked is crucial for deciphering the regulatory mechanisms of cell survival and fate. Here, we present a molecular resolution cryo-electron tomography (cryo-ET) imaging and image analysis platform to investigate the structure of isolated human mitochondria under different conditions. We describe optimized protocols for isolating mitochondria from human cells, vitrifying these samples with high-pressure freezing (HPF) using the waffle method, cryo-focused ion beam (cryo-FIB) milling to generate thin sections (lamellae), and imaging with cryo-transmission electron microscopy (cryo-TEM). This is complemented by a robust downstream processing pipeline for tilt-series alignment, tomogram reconstruction, and three-dimensional (3D) segmentation of tomograms using the latest state-of-the-art algorithms. With some variations, this versatile workflow is adaptable to other subcellular compartments for structural studies in isolation or within intact cells. Furthermore, our protocols provide a critical foundation for investigating the in-situ structure of protein machineries that govern key cellular processes.

The emergence of single-particle cryoEM as a powerful method for structure determination has in large part been fueled by its ability to resolve both single static structures and complex conformational landscapes. Indeed, modern approaches to the heterogeneous reconstruction task can resolve 100s-1,000s of different maps from a single cryoEM dataset. How accurate these algorithms are, however, has proven difficult to rigorously assess, due to a lack of suitable benchmark datasets containing both realistic noise features and ground-truth labels. To address this obstacle, we recently developed a series of benchmark datasets that leverage the targeting power of Cas9 and the programmable heterogeneity of DNA to newly offer access to ground-truth per-particle structural labels in real data. Here, we challenged two popular heterogeneous reconstruction algorithms with mixed particle stacks resampled in silico from these datasets, finding that existing approaches resolve the encoded heterogeneity with limited accuracy. In particular, in realistic particle stacks with complex, multi-scale, and multi-axis heterogeneity, we observed that reconstruction of encoded heterogeneity depended strongly on the application of prior information about where heterogeneity was expected, and that individual particle assignments were made with significant error even when the correct structural states were reconstructed. Both molecular breathing motions and data collection features, such as defocus and projection angle, contributed to the observed particle assignment error. These results highlight important shortcomings of existing heterogeneous reconstruction methods and suggest new avenues for method development in both data collection strategies and in heterogeneous classification and reconstruction algorithms.

Bacteria microcompartments (BMCs) are pseudo-organelles comprised of a self-assembling, semi-permeable protein shell, most commonly enclosing components of enzymatic pathways. -Carboxysomes (-CBs) are anabolic BMCs known for their role in sequestering Rubisco, the enzyme responsible for carbon fixation in plants, algae and bacteria, along with an upstream enzyme and an assembly protein. Rubisco has low selectivity for its substrate, CO2, and has a slow enzymatic turnover rate, resulting in an inefficient metabolic pathway. Within the -CB, Rubisco has been observed at a range of concentrations and with either a liquid-like assembly or a pseudo-lattice of polymerized fibrils. The biophysical origins of the fibril ultrastructure organization are unclear; however, it is only observed inside -CBs. Quantitative knowledge of the binding constants and energies for assembly and maintenance of these fibrils is critical for understanding this organization and Rubisco regulation, but quantitative methods for in situ analysis of Rubisco polymerization have been lacking. Here, we present an approach to convert tomography-derived -CB volumes and Rubisco particle positions into polymerization binding curves. We used this procedure to determine the Rubisco polymerization constants, including the nucleus size (n) and equilibrium polymerization constant (Kpol). The adopted modeling approach is consistent with in situ constraints, such as concentration-dependent binding interactions and confinement. This approach offers a powerful tool to evaluate both in vitro and potentially in vivo biomolecular interactions, both of Rubisco and of other proteins and polymers suitable for analysis by cryo-electron tomography. Significance StatementCryogenic electron tomography (cryoET) is a powerful method to resolve structures of proteins in their native environment at subnanometer-level resolution. Because tomography data retains spatial relationships of all particles, it intrinsically contains information about component (e.g., protein) binding interactions. Here, we use Rubisco polymerization in -carboxysomes as a model system to demonstrate that quantitative, biochemical binding analysis is possible with cryoET.

Correlative Light and Electron Microscopy (CLEM) integrates the molecular specificity of light microscopy (LM) with the ultrastructural detail of electron microscopy (EM), enabling comprehensive spatial analysis of biological samples. Despite growing demand, processing 3D CLEM datasets remains challenging, specifically for service provision in facilities, due to their multimodal nature and the lack of unified approaches. Typical steps include EM slice alignment, LM-EM registration, segmentation, and 3D visualization. We present a modular, end-to-end pipeline that consolidates existing and newly developed tools into a coherent workflow for 3D CLEM analysis and allows railroading the approach. Designed as interoperable modules accessible through a user-friendly interface, the pipeline is fully open-source and scales from standard workstations to high-performance computing environments to address the need for analysis of growing datasets. While some steps still require manual input, individual components can be automated to increase throughput and reproducibility. Together, this integrated solution lowers technical barriers and supports broader adoption of 3D CLEM methodologies.

Single-particle cryogenic electron microscopy (cryoEM) is a widely used technique for structure determination of biomacromolecules to near-atomic resolution. Random distributions of these molecules in vitrified ice are necessary to accumulate enough two-dimensional views to generate a complete three-dimensional (3-D) reconstruction. However, interactions between the sample and the air-water interface (AWI) that occur during vitrification often bias the views of the sample, a phenomenon termed preferred orientation, limiting our ability to obtain 3-D reconstructions. Surfactants are often used as sample additives to prevent AWI-induced deterioration, but no general strategy exists for surfactant choice, requiring laborious screening for each sample. To circumvent these issues, we developed SurfACT, a cocktail of diverse surfactants with distinct physicochemical properties that limits AWI-dependent sample denaturation and orientation bias, while mitigating individual surfactant-specific drawbacks. Here we demonstrate SurfACTs effectiveness with four proteins plagued by AWI-induced issues, including two species of hemagglutinin (HA), molybdenum-iron protein (MoFeP) from the nitrogenase enzyme, and aldolase. All four samples show drastically improved viewing distribution and map completeness when SurfACT is applied. Cryogenic electron tomography demonstrates that SurfACT redistributes particles from the AWI into the bulk ice, driving signal recovery and inhibiting denaturation. This versatile sample additive minimizes sample-specific screening and expands the capabilities and range of suitable samples for cryoEM.

Surface ice contamination is a persistent challenge in cryo-electron tomography (cryo-ET) workflows, where it can obscure regions of interest and contribute to curtaining artefacts during focused ion beam (FIB) milling. We demonstrate using high-pressure frozen yeast cells that a sublimation step within the scanning electron microscope (SEM) chamber before lamella milling visually removes surface ice and reduces sample roughness without detectable devitrification. While sublimation has been widely applied in cryo-SEM and volume imaging, it is not common on cryo-ET samples due to concerns about devitrification. Using tomographic reconstructions, we show that controlled sublimation improves lamella quality by reducing surface roughness and minimizing curtaining without compromising sample vitrification. Furthermore, subtomogram averaging of the 80S ribosome confirmed lamellae quality are preserved after sublimation. This approach offers a practical refinement to existing cryo-ET preparation protocols, requiring no additional instrumentation or workflow modifications.

Cryo-electron tomography (cryo-ET) enables in situ three-dimensional visualization of many protein complexes and other macromolecular assemblies such as ribosomes in cells, yet automated macromolecule particle identification in 3D cryo-ET tomograms remains a major bottleneck due to dose-limited low signal-to-noise ratios, missing-wedge artifacts, and densely crowded cellular backgrounds. We present TomoSwin3D, an end-to-end three-dimensional (3D) macromolecule particle identification and classification pipeline centered on a Swin Transformer-based U-Net that performs particle identification and classification and outputs particle centroid coordinates. TomoSwin3D leverages a multi-channel input representation that augments raw tomogram densities with complementary 3D feature maps capturing edge strength (Sobel gradients), local contrast enhancement (morphological top-hat), and multiscale blob responses (Difference-of-Gaussians), improving detectability of small and low-contrast targets. To better preserve particle geometry and avoid hand-crafted shape assumptions, it adopts occupancy-preserving supervision that directly uses available 3D instance masks rather than heuristic Gaussian/spherical labels and applies scalable patch-wise inference followed by lightweight post-processing (connected-component analysis, size filtering, centroid extraction) for robust centroid coordinate extraction. Across diverse simulated and experimental cryo-ET tomogram benchmarks including SHREC 2021 and 2020 test datasets, EMPIAR dataset, and Cryo-ET data portal dataset, TomoSwin3D achieves strong and consistent performance in detecting proteins and other particles, outperforming existing methods, with a pronounced advantage in picking hard, small protein particles. These results establish TomoSwin3D as a scalable and accurate solution for high-throughput cryo-ET macromolecule particle picking and downstream subtomogram averaging.

The liver has a complex architecture composed of millions of lobules. Within these lobules, hepatocytes, the main hepatic cells, are organized in rows separated by blood capillaries known as sinusoids. These capillaries are lined by liver sinusoidal endothelial cells (LSEC) that form a very specific fenestrated endothelium essential for the exchange of metabolites and proteins between the blood and hepatocytes. Alterations in the size and number of LSEC fenestrations are associated with the onset and the progression of various liver diseases. The analysis of liver architecture is thus of utmost importance for advancing our knowledge of liver ultrastructure and its alterations. Liver architecture has been studied since decades, mainly using 2D electron microscopy, and more recently using advanced super-resolution fluorescence microscopy. In recent years, volume electron microscopy techniques, including focused ion beam-scanning electron microscopy (FIB-SEM) progressed and nowadays enable the 3D reconstruction of biological ultrastructures down to nanometer resolution. However, the analysis of large volumes (e.g., several tens of {micro}m3) remains challenging due to various constraints in the segmentation of large datasets. In the current study, we developed a workflow to semi-automatically segment hepatic sinusoids from FIB-SEM mice liver datasets using the CNN-based (convolutional neural network) tool known as "nnU-Net", after fine-tuning a ground truth model. We also implemented tools for semi-automatic quantification of LSEC fenestrae diameters and sinusoid porosity from segmented datasets. This workflow enabled us to compare the distribution of LSEC fenestrae diameters in wild-type versus Bmp9-deleted mice, a hepatic factor known to be involved in fenestration maintenance. Our results confirm the importance of BMP9 for LSEC differentiation. Therefore, the developed methodology represents a valuable tool for characterizing the fenestrated endothelium under various physiological and pathological conditions.

Capturing meta-stable conformations of enzymes and ligand complexes demands structural snapshots beyond static crystal structures. While time-resolved serial crystallography at room temperature, offers a time-resolution down to the femto-second domain it requires large amounts of micro crystals, specialized beamlines and considerable experience. Moreover, as the majority of enzymes displays turnover-times in the millisecond domain or slower, simpler methods can provide meaningful structural insight into enzyme catalysis. Vitrification of protein crystals can trap reaction intermediates by rapid cooling to {inverted exclamation} 100 K, and has traditionally been used to gain insight into long lived reaction intermediates such as product complexes. However, manual vitrification procedures are limited to long delay times of at least several seconds and heavily suffer from operator variability. A solution to this problem is provided by automatic crystal plunging devices, such as the Spitrobot, that plunge loop-mounted protein crystals into liquid nitrogen within millisecond time-scales. Versatile means of reaction initiation can be achieved either by micro dispensing a ligand droplet, or via optical excitation of light-sensitive proteins, or via the photoactivation of caged compounds. In addition to the conceptual simplicity, another benefit of cryo-trapping is that data can be collected at conventional synchrotron beamlines, exploiting their robust high-throughput capabilities. Thus, compared to room-temperature time-resolved crystallography, users not only benefit from uncoupling sample-preparation and data-collection, but also from a reduction in the required technical expertise and ready access to radiation sources. However, as cryo-trapping crystallography explores dynamic structural changes that become only visible by the comparison of several samples, experiments have to be carefully planned to carry out the necessary controls and to avoid mis- or over-interpretation of the results. Here we describe a detailed protocol for cryo-trapping time-resolved crystallography using automated crystal-plungers that enables researchers to map enzymatic reaction coordinate pathways within the millisecond domain.

We introduce a workflow to identify oligomeric structures that are recorded with single-molecule localization microscopy (SMLM) under cryogenic conditions. Typically, these oligomers are assumed to consist of protomers arranged as equilateral two-dimensional polygons and every protomer is labeled with a dye molecule for visualization. Unlike previous work, we consider scenarios in which the sample plane has an unknown orientation relative to the focal plane. Our contribution is a high-precision plane-fitting algorithm to determine the sample plane, combined with geometrical transformations and two circle-fitting algorithms to identify the oligomeric structures. Our simulations on synthetic data demonstrate that the proposed workflow achieves high accuracy in estimating both the unknown tilted plane and the oligomer size.

Cryo-electron tomography (cryo-ET) enables in situ structural analysis of macromolecular complexes within native cellular environments. However, the limited field of view required for high-resolution structure determination necessarily restricts a wider assessment of the broader cellular context. We present a multi-magnification cryo-ET acquisition strategy that integrates low- and high-magnification information from coincident sample regions during the same tilt-series. By interleaving acquisition of the magnifications at each tilt angle, this strategy enables simultaneous collection of large field-of-view, low-resolution tomograms and high-resolution, small field-of-view tomograms while minimising the impact of the increased electron dose. We demonstrate that we can capture cellular organisation across tens of microns, while still enabling subtomogram averaging to resolutions below 4 [A]. This integrated acquisition framework establishes a practical route to multi-scale cryo-ET, bridging molecular and cellular scales for more comprehensive biological insight.

The NMR Exchange Format (NEF) is a community-driven standard for representing NMR experimental data in a consistent, interoperable, and machine-readable form. Built on the STAR syntax, NEF provides a structured framework for storing and exchanging chemical shifts, peak lists, various types of structural restraints, and related metadata, thus allowing for data exchange across software platforms. By enabling direct, lossless transfer of information, NEF simplifies multi-software workflows, improves reproducibility, and supports FAIR (Findable, Accessible, Interoperable, Reusable) data principles. We describe the NEF specification, its current implementation across commonly used NMR software packages, and its application in areas including biomolecular structure determination, metabolomics, and ligand screening. Testing demonstrates that NEF can be used to exchange complete datasets between programs without loss of information or functionality. We also outline recent developments and future directions, such as inclusion of NMR relaxation data and support for non-standard residue topologies. NEFs growing adoption highlights its potential as a unifying standard for NMR data, enabling more efficient, transparent and collaborative research.

Cryo-electron tomography (cryo-ET) is a powerful method for studying biological structures in near-native states, yet vitrification of thick and complex specimens remains a major limitation. High-pressure freezing (HPF) allows vitrification of up to [~]200 {micro}m thick samples, but its seamless integration into cryo-electron microscopy (cryo-EM) workflows is hindered by planchettes that are not optimized for EM grids, resulting in extensive handling, reliance on user experience, and frequent grid damage. Here, we present a streamlined HPF workflow based on newly designed planchettes that directly accommodate clipped EM Autogrids. Combined with interchangeable lids for controlling sample thickness, this system enables robust vitrification of diverse specimens, including single-celled eukaryotes and tissue biopsies, while minimizing post-freezing handling. Integration with plasma-focused ion beam milling supports both on-grid lamella preparation and lift-out approaches. We demonstrate reliable preservation of cellular ultrastructure and macromolecular integrity by cryo-ET and subtomogram averaging. This resource provides a practical and scalable solution for integrating HPF into modern cryo-ET pipelines, expanding access to structurally complex biological systems and supporting future clinical applications.

The structural and functional characteristics of membrane proteins can be influenced by the composition of the membrane. Consequently, native membranes are most relevant for the study of receptors and other membrane proteins. In this study, we investigated two types of cell-derived vesicles: natively shed extracellular vesicles (EVs) and mechanically derived vesicles (MVs). To this end, we utilized the human breast cancer cell line SKBR3, which strongly overexpresses the receptor HER2. We designed a protocol based on designed ankyrin repeat proteins (DARPins) to purify EVs and MVs enriched in HER2, and to ensure the native orientation of the HER2 receptors within the vesicle. The isolated HER2-containing EVs and MVs were characterized by cryo-EM, cryo-electron tomography (cryo-ET) and mass spectrometry (MS), which revealed fundamental differences between the different vesicle types. Our study highlights the greater structural diversity of EVs over MVs. A single particle cryo-EM analysis and classification of all visible receptors on the vesicle surface yielded electron density consistent with HER2 at modest resolution. Taken together, our results suggest that MVs can serve better than EVs as a suitable platform for the structure determination of membrane proteins within their native membrane environments.

Due to recent technological advances, in situ structural cell biology is becoming a high throughput microscopy technique as all the steps of the workflow, from sample preparation to data analysis, are executed faster, more reliable and more reproducible. Sample thinning by cryoFIB-SEM is an essential tool in preparing electron transparent lamellae of biological specimens suitable for further characterization by cryoET. Modern cryoFIB-SEM instruments can be operated remotely and are capable of automated and unsupervised lamellae preparation. To take full advantage of these developments they need a constant supply of LN2 to maintain cryogenic conditions inside the microscope chamber. Here, we introduce a custom automated LN2 refill system that is compatible with gas cooled cryostages, supports long-term cryoFIB-SEM operations and liberates the user from highly repetitive and manual work. We believe this solution can be utilized with other cryoSEM or cryoFIB-SEM devices requiring N2 gas-flow cooling.