Rapid tilt-series method for cryo-electron tomography: Characterizing stage behavior during FISE acquisition

Combining per-particle cryo-ET and cryo-EM single particle analysis to elucidate heterogeneous DNA-protein organization

Cryo-electron microscopy single particle analysis (cryo-EM SPA) and cryo-electron tomography (cryo-ET) have historically been employed as distinct approaches for investigating molecular structures of disparate sample types, focusing on highly purified biological macromolecules and in situ cellular contexts, respectively. However, these techniques offer inherently complementary structural insights that, when combined, provide a more comprehensive understanding of complex biological systems. For example, if both techniques are applied to the same purified biological macromolecules, cryo-ET has the ability to resolve highly flexible yet strong signal features on an individual target molecule which will not be preserved in the high-resolution cryo-EM SPA results. In this review, we highlight recent achievements utilizing such applications to unveil new insights into the chromatin assembly and activities of DNA-protein assemblies. This convergence of cryo-EM SPA and cryo-ET holds great promise for elucidating new structural aspects of these essential molecular processes.

Rapid Synthesis of Cryo-ET Data for Training Deep Learning Models

Deep learning excels at cryo-tomographic image restoration and segmentation tasks but is hindered by a lack of training data. Here we introduce cryo-TomoSim (CTS), a MATLAB-based software package that builds coarse-grained models of macromolecular complexes embedded in vitreous ice and then simulates transmitted electron tilt series for tomographic reconstruction. We then demonstrate the effectiveness of these simulated datasets in training different deep learning models for use on real cryotomographic reconstructions. Computer-generated ground truth datasets provide the means for training models with voxel-level precision, allowing for unprecedented denoising and precise molecular segmentation of datasets. By modeling phenomena such as a three-dimensional contrast transfer function, probabilistic detection events, and radiation-induced damage, the simulated cryo-electron tomograms can cover a large range of imaging content and conditions to optimize training sets. When paired with small amounts of training data from real tomograms, networks become incredibly accurate at segmenting in situ macromolecular assemblies across a wide range of biological contexts.

Structure and Function of the Dot/Icm T4SS

The Legionella pneumophila Dot/Icm type IV secretion system (T4SS) delivers effector proteins into host cells during infection. Despite its significance as a potential drug target, our current understanding of its atomic structure is limited to isolated subcomplexes. In this study, we used subtomogram averaging and integrative modeling to construct a nearly-complete model of the Dot/Icm T4SS accounting for seventeen protein components. We locate and provide insights into the structure and function of six new components including DotI, DotJ, DotU, IcmF, IcmT, and IcmX. We find that the cytosolic N-terminal domain of IcmF, a key protein forming a central hollow cylinder, interacts with DotU, providing insight into previously uncharacterized density. Furthermore, our model, in combination with analyses of compositional heterogeneity, explains how the cytoplasmic ATPase DotO is connected to the periplasmic complex via interactions with membrane-bound DotI/DotJ proteins. Coupled with in situ infection data, our model offers new insights into the T4SS-mediated secretion mechanism.

Structural basis of a transcription pre-initiation complex on a divergent promoter

Most eukaryotic promoter regions are divergently transcribed. As the RNA polymerase II pre-initiation complex (PIC) is intrinsically asymmetric and responsible for transcription in a single direction, it is unknown how divergent transcription arises. Here, the Saccharomyces cerevisiae Mediator complexed with a PIC (Med-PIC) was assembled on a divergent promoter and analyzed by cryoelectron microscopy. The structure reveals two distinct Med-PICs forming a dimer through the Mediator tail module, induced by a homodimeric activator protein localized near the dimerization interface. The tail dimer is associated with ∼80-bp upstream DNA, such that two flanking core promoter regions are positioned and oriented in a suitable form for PIC assembly in opposite directions. Also, cryoelectron tomography visualized the progress of the PIC assembly on the two core promoter regions, providing direct evidence for the role of the Med-PIC dimer in divergent transcription.

Electron microscopy of cellular ultrastructure in three dimensions

Electron microscopy in three dimensions (3D) of cells and tissues can be essential for understanding the ultrastructural aspects of biological processes. The quest for 3D information reveals challenges at many stages of the workflow, from sample preparation, to imaging, data analysis and segmentation. Here, we outline several available methods, including volume SEM imaging, cryo-TEM and cryo-STEM tomography, each one occupying a different domain in the basic tradeoff between field-of-view and resolution. We discuss the considerations for choosing a suitable method depending on research needs and highlight recent developments that are essential for making 3D volume imaging of cells and tissues a standard tool for cellular and structural biologists.

Montage electron tomography of vitrified specimens

Cryo-electron tomography provides detailed views of macromolecules in situ. However, imaging a large field of view to provide more cellular context requires reducing magnification during data collection, which in turn restricts the resolution. To circumvent this trade-off between field of view and resolution, we have developed a montage data collection scheme that uniformly distributes the dose throughout the specimen. In this approach, sets of slightly overlapping circular tiles are collected at high magnification and stitched to form a composite projection image at each tilt angle. These montage tilt-series are then reconstructed into massive tomograms with a small pixel size but a large field of view. For proof-of-principle, we applied this method to the thin edge of HeLa cells. Thon rings to better than 10 Å were detected in the montaged tilt-series, and diverse cellular features were observed in the resulting tomograms. These results indicate that the additional dose required by this technique is not prohibitive to performing structural analysis to intermediate resolution across a large field of view. We anticipate that montage tomography will prove particularly useful for lamellae, increase the likelihood of imaging rare cellular events, and facilitate visual proteomics.

A feature-guided, focused 3D signal permutation method for subtomogram averaging

Advances in electron microscope instrumentation, cryo-electron tomography data collection, and subtomogram averaging have allowed for the in-situ visualization of molecules and their complexes in their native environment. Current data processing pipelines commonly extract subtomograms as a cubic subvolume with the key assumption that the selected object of interest is discrete from its surroundings. However, in instances when the object is in its native environment, surrounding densities may negatively affect the subsequent alignment and refinement processes, leading to loss of information due to misalignment. For example, the strong densities from surrounding membranes may dominate the alignment process for membrane proteins. Here, we developed methods for feature-guided subtomogram alignment and 3D signal permutation for subtomogram averaging. Our 3D signal permutation method randomizes and filters voxels outside a mask of any shape and blurs the boundary of the mask that encapsulates the object of interest. The randomization preserves global statistical properties such as mean density and standard deviation of voxel density values, effectively producing a featureless background surrounding the object of interest. This signal permutation process can be repeatedly applied with intervening alignments of the 3D signal-permuted subvolumes, recentering of the mask, and optional adjustments of the shape of the mask. We have implemented these methods in a new processing pipeline which starts from tomograms, contains feature-guided subtomogram extraction and alignment, 3D signal-permutation, and subtomogram visualization tools. As an example, feature-guided alignment and 3D signal permutation leads to improved subtomogram average maps for a dataset of synaptic protein complexes in their native environment.

How advances in cryo-electron tomography have contributed to our current view of bacterial cell biology

Advancements in the field of cryo-electron tomography have greatly contributed to our current understanding of prokaryotic cell organization and revealed intracellular structures with remarkable architecture. In this review, we present some of the prominent advancements in cryo-electron tomography, illustrated by a subset of structural examples to demonstrate the power of the technique. More specifically, we focus on technical advances in automation of data collection and processing, sample thinning approaches, correlative cryo-light and electron microscopy, and sub-tomogram averaging methods. In turn, each of these advances enabled new insights into bacterial cell architecture, cell cycle progression, and the structure and function of molecular machines. Taken together, these significant advances within the cryo-electron tomography workflow have led to a greater understanding of prokaryotic biology. The advances made the technique available to a wider audience and more biological questions and provide the basis for continued advances in the near future.

Micropatterning Transmission Electron Microscopy Grids to Direct Cell Positioning within Whole-Cell Cryo-Electron Tomography Workflows

Whole-cell cryo-electron tomography (cryo-ET) is a powerful technology that is used to produce nanometer-level resolution structures of macromolecules present in the cellular context and preserved in a near-native frozen-hydrated state. However, there are challenges associated with culturing and/or adhering cells onto TEM grids in a manner that is suitable for tomography while retaining the cells in their physiological state. Here, a detailed step-by-step protocol is presented on the use of micropatterning to direct and promote eukaryotic cell growth on TEM grids. During micropatterning, cell growth is directed by depositing extra-cellular matrix (ECM) proteins within specified patterns and positions on the foil of the TEM grid while the other areas remain coated with an anti-fouling layer. Flexibility in the choice of surface coating and pattern design makes micropatterning broadly applicable for a wide range of cell types. Micropatterning is useful for studies of structures within individual cells as well as more complex experimental systems such as host-pathogen interactions or differentiated multi-cellular communities. Micropatterning may also be integrated into many downstream whole-cell cryo-ET workflows, including correlative light and electron microscopy (cryo-CLEM) and focused-ion beam milling (cryo-FIB).

Programmed Flagellar Ejection in Caulobacter crescentus Leaves PL-subcomplexes

The bacterial flagellum consists of a long extracellular filament that is rotated by a motor embedded in the cell envelope. While flagellar assembly has been extensively studied,¹ the disassembly process remains less well understood. In addition to the programmed flagellar ejection that occurs during the life cycle of Caulobacter crescentus, we and others have recently shown that many bacterial species lose their flagella under starvation conditions, leaving relic structures in the outer membrane.^2-7 However, it remains unknown whether the programmed flagellar ejection of C. crescentus leaves similar relics or not. Here, we imaged the various stages of the C. crescentus life cycle using electron cryo-tomography (cryo-ET) and found that flagellar relic subcomplexes, akin to those produced in the starvation-induced process, remain as a result of flagellar ejection during cell development. This similarity suggests that the programmed flagellar ejection of C. crescentus might share a common evolutionary path with the more general, and likely more ancient,³ starvation-related flagellar loss.

Challenges in solving structures from radiation-damaged tomograms of protein nanocrystals assessed by simulation

Structure-determination methods are needed to resolve the atomic details that underlie protein function. X-ray crystallography has provided most of our knowledge of protein structure, but is constrained by the need for large, well ordered crystals and the loss of phase information. The rapidly developing methods of serial femtosecond crystallography, micro-electron diffraction and single-particle reconstruction circumvent the first of these limitations by enabling data collection from nanocrystals or purified proteins. However, the first two methods also suffer from the phase problem, while many proteins fall below the molecular-weight threshold required for single-particle reconstruction. Cryo-electron tomography of protein nanocrystals has the potential to overcome these obstacles of mainstream structure-determination methods. Here, a data-processing scheme is presented that combines routines from X-ray crystallography and new algorithms that have been developed to solve structures from tomograms of nanocrystals. This pipeline handles image-processing challenges specific to tomographic sampling of periodic specimens and is validated using simulated crystals. The tolerance of this workflow to the effects of radiation damage is also assessed. The simulations indicate a trade-off between a wider tilt range to facilitate merging data from multiple tomograms and a smaller tilt increment to improve phase accuracy. Since phase errors, but not merging errors, can be overcome with additional data sets, these results recommend distributing the dose over a wide angular range rather than using a finer sampling interval to solve the protein structure.