Thicker Ice Improves the Integrity and Angular Distribution of CDC48A Hexamers on Cryo-EM Grids.

Particles are a key component of aquatic light climate due to their attenuation of light. Near the water surface, waves and sheared currents can induce a preferential orientation of nonspherical particles that alters their inherent optical properties and the associated light attenuation. This modeling study focuses on how particle shape, and the corresponding preferential orientation, impacts the light climate in an aquatic environment. We assume aquatic particles, such as bacteria, algae, and microplastic pollutants, are optically homogeneous spheroids that move with the flow. The model computes their preferential orientations within the upper water column in flow driven by linear water waves and sheared currents. This is combined with the anomalous diffraction optical approximation to examine the effect of particle orientation on the beam attenuation coefficient. We find that the preferential orientation by waves and shear tends to increase the projected area of the spheroid compared to random (isotropic) orientation. This has particle size‐dependent effects on light attenuation: for particles comparable in size and shape to algae or microplastics, the preferential orientation corresponds to an increase of 10–25% in the beam attenuation coefficient, whereas there is a decrease of 10–20% in the beam attenuation coefficient for smaller particles comparable in size to bacteria. Overall, our results reveal how preferential orientation of nonspherical particles by waves and currents can impact light climate in the upper water column.

X-ray crystallography and single-particle analysis cryogenic electron microscopy are essential techniques for uncovering the three-dimensional structures of biological macromolecules. Both techniques rely on the Fourier transform to calculate experimental maps. However, one of the crucial parameters, resolution, is rather broadly defined. Here, the methods to determine the resolution in X-ray crystallography and single-particle analysis are summarized. In X-ray crystallography, it is becoming increasingly more common to include reflections discarded previously by traditionally used standards, allowing for the inclusion of incomplete and anisotropic reflections into the refinement process. In general, the resolution is the smallest lattice spacing given by Bragg’s law for a particular set of X-ray diffraction intensities; however, typically the resolution is truncated by the user during the data processing based on certain parameters and later it is used during refinement. However, at which resolution to perform such a truncation is not always clear and this makes it very confusing for the novices entering the structural biology field. Furthermore, it is argued that the effective resolution should be also reported as it is a more descriptive measure accounting for anisotropy and incompleteness of the data. In single particle cryo-EM, the situation is not much better, as multiple ways exist to determine the resolution, such as Fourier shell correlation, spectral signal-to-noise ratio and the Fourier neighbor correlation. The most widely accepted is the Fourier shell correlation using a threshold of 0.143 to define the resolution (so-called “gold-standard”), although it is still debated whether this is the correct threshold. Besides, the resolution obtained from the Fourier shell correlation is an estimate of varying resolution across the density map. In reality, the interpretability of the map is more important than the numerical value of the resolution.

Electron microscopy has been an important method for visualising biological structures and processes since the 1940s. The discovery of a practical vitreous-ice specimen-preparation technique in the mid-1980s [Adrian 1984] led to modern-day Cryogenic Electron Microscopy (Cryo-EM) which in recent years has become a major technique for studying the architecture of biological macromolecules. Many further instrumental and data-analysis improvements were established in the decades after the introduction of the “vitreous-ice” state of water. Especially the advent of direct electron detectors boosted the quality of the recorded data, allowing atomic-resolution information of biological complexes to be harvested in the early 2010s, developments that truly revolutionized the use of Cryo-EM in structural biology. Single-Particle Analysis (SPA) of isolated molecules, prepared in a thin layer of vitreous water, has proven a most successful approach in structural biology and now often supplants the use of classical techniques like X-ray crystallography, especially for large biological complexes. The ever-increasing number of researchers using Cryo-EM is reflected by the growing number of depositions in the Electron Microscopy Data Bank (EMDB). Explaining this methodology to a new generation of researchers has now become a priority. In writing this review we were reminded of some persistent confusions that emerged in the early days of Cryo-EM but that continue to muddle the field. A new problem with the prolific use of Graphic User Interfaces (GUIs), is that the underlying methodology is often no longer transparent to the users of these “black boxes”. Complicated procedures, well hidden behind a GUI window, may contain methodological flaws that the user must be aware of. The conquering of markets in this booming Cryo-EM field – crucial for developing new pharmaceuticals – must not prevail over scientific integrity. We here describe and critically review the principles of single-particle Cryo-EM. We warn for procedures that have gone astray and could generate serious problems especially in the quality-control of Single-Particle Cryogenic Electron Microscopy.

Advances in cryogenic electron microscopy (cryoEM) single particle analysis have revolutionized structural biology by facilitating the in vitro determination of atomic- and near-atomic-resolution structures for fully hydrated macromolecular complexes exhibiting compositional and conformational heterogeneity across a wide range of sizes. Cryogenic electron tomography (cryoET) and subtomogram averaging are rapidly progressing toward delivering similar insights for macromolecular complexes in situ, without requiring tags or harsh biochemical purification. Furthermore, cryoET enables the visualization of cellular and tissue phenotypes directly at molecular, nanometric resolution without chemical fixation or staining artifacts. This forward-looking review covers recent developments in cryoEM/ET and related technologies such as cryogenic focused ion beam milling scanning electron microscopy and correlative light microscopy, increasingly enhanced and supported by artificial intelligence algorithms. Their potential application to emerging concepts is discussed, primarily the prospect of complementing medical histopathology analysis. Machine learning solutions are poised to address current challenges posed by "big data" in cryoET of tissues, cells, and macromolecules, offering the promise of enabling novel, quantitative insights into disease processes, which may translate into the clinic and lead to improved diagnostics and targeted therapeutics.

For many years, the Cryo-EM community is expecting that software automation will achieve the ultimate goal of providing a Single Particle Analysis (SPA) data acquisition workflow that requires no setup from the user's side [1,2]. Achieving that will allow many more researchers, who are not necessarily application or microscope experts an optimal use of time in high throughput cryo-electron microscopes. This is particularly important in industrial set-ups or entry-level labs where efficiency and ease of use are key adoption barriers. Moreover, it has been identified that one of the main bottlenecks in Single Particle Acquisition (SPA) is screening automation [2]. Thermo Scientific Smart EPU with EPU Multigrid already provides a workflow that enables screening of multiple samples in highly automated way [3]. We are now expanding on that with the goal to make SPA screening fully unattended. With the use of EPU Multigrid, EPU Quality Monitor (EQM) and Embedded CryoSPARC Live, and a novel set of AI/DL algorithms, we can now demonstrate a workflow that allows users to screen a full cassette of samples on an autoloader system without the need to pass through any manual setup tasks.To achieve that level of automation, many parts of the workflow need to be optimized. User workflows for screening often include the acquisition and subsequent analysis of small datasets from numerous grids in different conditions to find optimal ice thickness and particle behavior [2]. This task is quite tedious: Users need to load each grid, select grid squares with a variation in ice thickness, identify foil holes, select foil holes with a variation in ice thickness, curate initial selections and afterwards perform data analysis to find favorable conditions for data acquisition. Smart EPU introduces a set of innovative AI/DL plugins that automate all the above steps. Experimental results show that the algorithms perform to a comparable level to an experienced user. We also combine these innovations with a redesigned UI to invoke the setup with just one click. This screening solution will be connected to EQM and Embedded CryoSPARC Live, so data analysis also happens in real time.With these developments in place, users will be able to load the samples, immediately start the screening process, and after a few hours get the results visualized in our data integration platform on their laptop.

Cryo-electron microscopy (cryoEM) is a powerful technique for structure determination of macromolecular complexes, via single particle analysis (SPA). The overall process involves i) vitrifying the specimen in a thin film supported on a cryoEM grid; ii) screening the specimen to assess particle distribution and ice quality; iii) if the grid is suitable, collecting a single particle dataset for analysis; and iv) image processing to yield an EM density map. In this protocol, an overview for each of these steps is provided, with a focus on the variables which a user can modify during the workflow and the troubleshooting of common issues. With remote microscope operation becoming standard in many facilities, variations on imaging protocols to assist users in efficient operation and imaging when physical access to the microscope is limited will be described.

Electron cryomicroscopy (cryo-EM) has revolutionised structural biology, enhancing applicability, size limits and speed. Despite these successes, cryo-EM sample preparation remains a major bottleneck for routinely achieving high-resolution structures through single particle analysis. Challenges such as inconsistent ice thicknesses, air-water interface interactions and preferred particle orientation persist. Here, we introduce a blot-free vitrification method that uses free-standing surfactant-stabilised foam films to address some of these issues. The method achieves uniform ice thicknesses, enables thickness control of the foam film prior to vitrification, and for some specimens enhances orientation distribution efficiency. Furthermore, it reduces particle adsorption to carbon foil on the specimen support. The method simplifies cryo-EM specimen preparation, offering improved control over ice thickness and particle orientation, to help streamline and accelerate structure determination.

Single-particle reconstruction (SPR) in cryogenic electron microscopy (cryo-EM) aims at aligning and averaging two-dimensional micrographs to reconstruct a three-dimensional particle.How to reconstruct micrographs from heavy noise is a crucial point for achieving better micrograph quality, and thus many methods focus on noise removal. However, new problems such as over-smoothing often occur in their results due to failure in handling heavy noise well. This paper proposes a three-dimensional weighted nuclear norm minimization (3DWNNM) model for SPR in the cryo-EM task to address these issues. Specifically, we design a minimization solver based on the forward-backward splitting algorithm to tackle our model efficiently. Under certain conditions, this solution has an energy-decaying feature and performs exceptionally well in reconstruction. Numerical experiments fully demonstrate the effectiveness and the robustness of the proposed method.

Integrating Molecular Models Into CryoEM Heterogeneity Analysis Using Scalable High-resolution Deep Gaussian Mixture Models

Cryogenic electron microscopy has become an essential tool for structure determination of biological macromolecules. In practice, the difficulty to reliably prepare samples with uniform ice thickness still represents a barrier for routine high-resolution imaging and limits the current throughput of the technique. We show that a nanofluidic sample support with well-defined geometry can be used to prepare cryo-EM specimens with reproducible ice thickness from picoliter sample volumes. The sample solution is contained in electron-transparent nanochannels that provide uniform thickness gradients without further optimisation and eliminate the potentially destructive air-water interface. We demonstrate the possibility to perform high-resolution structure determination with three standard protein specimens. Nanofabricated sample supports bear potential to automate the cryo-EM workflow, and to explore new frontiers for cryo-EM applications such as time-resolved imaging and high-throughput screening.

Single-particle cryogenic electron microscopy (cryo-EM) enables reconstruction of atomic-resolution 3D maps of proteins by visualizing thousands to millions of purified protein particles embedded in vitreous ice. This corresponds to picograms of purified protein, which can potentially be isolated from a few thousand cells. Hence, cryo-EM holds the potential of a very sensitive analytical method for delivering high-resolution protein structure as a readout. In practice, millions of times more starting biological material is required to prepare cryo-EM grids. Here we show that using a micro isolation (MISO) method, which combines microfluidics-based protein purification with cryo-EM grid preparation, cryo-EM structures of soluble bacterial and eukaryotic membrane proteins can be solved starting from less than 1 µg of a target protein and progressing from cells to cryo-EM grids within a few hours. This scales down the amount of starting biological material hundreds to thousands of times, opening possibilities for the structural characterization of hitherto inaccessible proteins.

A critical step in cryogenic electron microscopy (cryo-EM) image analysis is to calculate the average of all images aligned to a projection direction. This average, called the class mean, improves the signal-to-noise ratio in single-particle reconstruction. The averaging step is often compromised because of the outlier images of ice, contaminants, and particle fragments. Outlier detection and rejection in the majority of current cryo-EM methods are done using cross-correlation with a manually determined threshold. Empirical assessment shows that the performance of these methods is very sensitive to the threshold. This paper proposes an alternative: a w-estimator of the average image, which is robust to outliers and which does not use a threshold. Various properties of the estimator, such as consistency and influence function are investigated. An extension of the estimator to images with different contrast transfer functions is also provided. Experiments with simulated and real cryo-EM images show that the proposed estimator performs quite well in the presence of outliers.

For macromolecular structures determined by cryogenic electron microscopy, no technique currently exists for mapping elements to defined locations, leading to errors in the assignment of metals and other ions, cofactors, substrates, inhibitors and lipids that play essential roles in activity and regulation. Elemental mapping in the electron microscope is well established for dose-tolerant samples but is challenging for biological samples, especially in a cryo-preserved state. Here we combine electron energy-loss spectroscopy with single-particle image processing to allow elemental mapping in cryo-preserved macromolecular complexes. Proof-of-principle data show that our method, reconstructed electron energy-loss (REEL) analysis, allows a three-dimensional reconstruction of electron energy-loss spectroscopy data, such that a high total electron dose is accumulated across many copies of a complex. Working with two test samples, we demonstrate that we can reliably localize abundant elements. We discuss the current limitations of the method and potential future developments.

The lack of detailed insight into the structure of aggregates formed by the huntingtin protein (HTT) has hampered the efforts to develop therapeutics and diagnostics targeting pathology formation in the brain of patients with Huntington's disease. To address this knowledge gap, we investigated the structural properties of in vitro-generated fibrils from exon1 of the huntingtin protein by cryogenic electron microscopy and single-particle analyses. We show that wildtype and mutant exon1 of the huntingtin protein form nonhelical fibrils with a polyglutamine amyloid core composed of β-hairpins with unique characteristics that have not been previously observed with other amyloid filaments. The stacks of β-hairpins form long planar β-sheets (protofilaments) which combine inter- and intra-molecular interactions, with variable stacking angles and occasional out-of-register states of individual β-hairpins. These features and the propensity of protofilaments to undergo lateral association result in a high degree of fibril polymorphisms, including fibrils composed of varying numbers of protofilaments. Our results allow us to speculate on how the flanking domains are organized around the polyglutamine core of the fibril and provide insight into how they might affect the huntingtin fibril structure and polymorphism. The removal of the first 17 amino acids at the N-terminus resulted in surprising intra-fibril structural heterogeneity and reduced fibril's propensity to lateral associations. Overall, this work provides valuable insights that could help guide future mechanistic studies to elucidate the sequence and structural determinants of huntingtin aggregation, as well as for cryo-EM and structural studies of fibrils derived from huntingtin protein and other disease-associated polyglutamine-containing proteins.

Mass spectrometers as cryoEM grid preparation instruments