Towards high-throughput in situ structural biology using electron cryotomography

The advent of preventive high-resolution structural histopathology by artificial-intelligence-powered cryogenic electron tomography

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.

Optimize Electron Beam Energy toward In Situ Imaging of Thick Frozen Bio-Samples with Nanometer Resolution Using MeV-STEM

To optimize electron energy for in situ imaging of large biological samples up to 10 μm in thickness with nanoscale resolutions, we implemented an analytical model based on elastic and inelastic characteristic angles. This model has been benchmarked by Monte Carlo simulations and can be used to predict the transverse beam size broadening as a function of electron energy while the probe beam traverses through the sample. As a result, the optimal choice of the electron beam energy can be realized. In addition, the impact of the dose-limited resolution was analysed. While the sample thickness is less than 10 μm, there exists an optimal electron beam energy below 10 MeV regarding a specific sample thickness. However, for samples thicker than 10 μm, the optimal beam energy is 10 MeV or higher depending on the sample thickness, and the ultimate resolution could become worse with the increase in the sample thickness. Moreover, a MeV-STEM column based on a two-stage lens system can be applied to reduce the beam size from one micron at aperture to one nanometre at the sample with the energy tuning range from 3 to 10 MeV. In conjunction with the state-of-the-art ultralow emittance electron source that we recently implemented, the maximum size of an electron beam when it traverses through an up to 10 μm thick bio-sample can be kept less than 10 nm. This is a critical step toward the in situ imaging of large, thick biological samples with nanometer resolution.

The application and development of electron microscopy for three-dimensional reconstruction in life science: a review

Imaging technologies have played a pivotal role in advancing biological research by enabling visualization of biological structures and processes. While traditional electron microscopy (EM) produces two-dimensional images, emerging techniques now allow high-resolution three-dimensional (3D) characterization of specimens in situ, meeting growing needs in molecular and cellular biology. Combining transmission electron microscopy (TEM) with serial sectioning inaugurated 3D imaging, attracting biologists seeking to explore cell ultrastructure and driving advancement of 3D EM reconstruction. By comprehensively and precisely rendering internal structure and distribution, 3D TEM reconstruction provides unparalleled ultrastructural insights into cells and molecules, holding tremendous value for elucidating structure-function relationships and broadly propelling structural biology. Here, we first introduce the principle of 3D reconstruction of cells and tissues by classical approaches in TEM and then discuss modern technologies utilizing TEM and on new SEM-based as well as cryo-electron microscope (cryo-EM) techniques. 3D reconstruction techniques from serial sections, electron tomography (ET), and the recent single-particle analysis (SPA) are examined; the focused ion beam scanning electron microscopy (FIB-SEM), the serial block-face scanning electron microscopy (SBF-SEM), and automatic tape-collecting lathe ultramicrotome (ATUM-SEM) for 3D reconstruction of large volumes are discussed. Finally, we review the challenges and development prospects of these technologies in life science. It aims to provide an informative reference for biological researchers.

High-Throughput Identification of Crystalline Natural Products from Crude Extracts Enabled by Microarray Technology and microED

The structural determination of natural products (NPs) can be arduous because of sample heterogeneity. This often demands iterative purification processes and characterization of complex molecules that may be available only in miniscule quantities. Microcrystal electron diffraction (microED) has recently shown promise as a method to solve crystal structures of NPs from nanogram quantities of analyte. However, its implementation in NP discovery remains hampered by sample throughput and purity requirements, akin to traditional NP-discovery workflows. In the methods described herein, we leverage the resolving power of transmission electron microscopy (TEM) and the miniaturization capabilities of deoxyribonucleic acid (DNA) microarray technology to address these challenges through the establishment of an NP screening platform, array electron diffraction (ArrayED). In this workflow, an array of high-performance liquid chromatography (HPLC) fractions taken from crude extracts was deposited onto TEM grids in picoliter-sized droplets. This multiplexing of analytes on TEM grids enables 1200 or more unique samples to be simultaneously inserted into a TEM instrument equipped with an autoloader. Selected area electron diffraction analysis of these microarrayed grids allows for the rapid identification of crystalline metabolites. In this study, ArrayED enabled structural characterization of 14 natural products, including four novel crystal structures and two novel polymorphs, from 20 crude extracts. Moreover, we identify several chemical species that would not be detected by standard mass spectrometry (MS) or ultraviolet-visible (UV/vis) spectroscopy and crystal forms that would not be characterized using traditional methods.

Charting the molecular landscape of the cell

Biological function of macromolecules is closely tied to their cellular location, as well as to interactions with other molecules within the native environment of the cell. Therefore, to obtain detailed mechanistic insights into macromolecular functionality, one of the outstanding targets for structural biology is to produce an atomic-level understanding of the cell. One structural biology technique that has already been used to directly derive atomic models of macromolecules from cells, without any additional external information, is electron cryotomography (cryoET). In this perspective article, we discuss possible routes to chart the molecular landscape of the cell by advancing cryoET imaging as well as by embedding cryoET into correlative imaging workflows.

Volume EM: a quiet revolution takes shape

Volume Electron Microscopy is a group of techniques that reveal the 3D ultrastructure of cells and tissues through volumes greater than 1 cubic micron. A burgeoning grass roots community effort is fast building the profile, and revealing the impact, of vEM technology in the life sciences and clinical research.

Are extraordinary nucleosome structures more ordinary than we thought?

The nucleosome is a DNA-protein assembly that is the basic unit of chromatin. A nucleosome can adopt various structures. In the canonical nucleosome structure, 145-147 bp of DNA is wrapped around a histone heterooctamer. The strong histone-DNA interactions cause the DNA to be inaccessible for nuclear processes such as transcription. Therefore, the canonical nucleosome structure has to be altered into different, non-canonical structures to increase DNA accessibility. While it is recognised that non-canonical structures do exist, these structures are not well understood. In this review, we discuss both the evidence for various non-canonical nucleosome structures in the nucleus and the factors that are believed to induce these structures. The wide range of non-canonical structures is likely to regulate the amount of accessible DNA, and thus have important nuclear functions.

Graph identification of proteins in tomograms (GRIP-Tomo)

In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases for refinement. We hypothesized that the topological connectivity of protein structures is invariant, and they are distinctive for the purpose of protein identification from distorted data presented in volume densities. Three-dimensional densities of a protein or a complex from simulated tomographic volumes were transformed into mathematical graphs as observables. We systematically introduced data distortion or defects such as missing fullness of data, the tumbling effect, and the missing wedge effect into the simulated volumes, and varied the distance cutoffs in pixels to capture the varying connectivity between the density cluster centroids in the presence of defects. A similarity score between the graphs from the simulated volumes and the graphs transformed from the physical protein structures in point data was calculated by comparing their network theory order parameters including node degrees, betweenness centrality, and graph densities. By capturing the essential topological features defining the heterogeneous morphologies of a network, we were able to accurately identify proteins and homo-multimeric complexes from 10 topologically distinctive samples without realistic noise added. Our approach empowers future developments of tomogram processing by providing pattern mining with interpretability, to enable the classification of single-domain protein native topologies as well as distinct single-domain proteins from multimeric complexes within noisy volumes.

Recent advances and current trends in cryo-electron microscopy

All steps of cryogenic electron-microscopy (cryo-EM) workflows have rapidly evolved over the last decade. Advances in both single-particle analysis (SPA) cryo-EM and cryo-electron tomography (cryo-ET) have facilitated the determination of high-resolution biomolecular structures that are not tractable with other methods. However, challenges remain. For SPA, these include improved resolution in an additional dimension: time. For cryo-ET, these include accessing difficult-to-image areas of a cell and finding rare molecules. Finally, there is a need for automated and faster workflows, as many projects are limited by throughput. Here, we review current developments in SPA cryo-EM and cryo-ET that push these boundaries. Collectively, these advances are poised to propel our spatial and temporal understanding of macromolecular processes.

Multi-curve fitting and tubulin-lattice signal removal for structure determination of large microtubule-based motors

Revealing high-resolution structures of microtubule-associated proteins (MAPs) is critical for understanding their fundamental roles in various cellular activities, such as cell motility and intracellular cargo transport. Nevertheless, large flexible molecular motors that dynamically bind and release microtubule networks are challenging for cryo-electron microscopy (cryo-EM). Traditional structure determination of MAPs bound to microtubules needs alignment information from the reconstruction of microtubules, which cannot be readily applied to large MAPs without a fixed binding pattern. Here, we developed a comprehensive approach to estimate the microtubule networks (multi-curve fitting), model the tubulin-lattice signals, and remove them (tubulin-lattice subtraction) from the raw cryo-EM micrographs. The approach does not require an ordered binding pattern of MAPs on microtubules, nor does it need a reconstruction of the microtubules. We demonstrated the capability of our approach using the reconstituted outer-arm dynein (OAD) bound to microtubule doublets. The tubulin-lattice subtraction improves the OAD alignment, thus leading to high-resolution reconstructions. In addition, the multi-curve fitting approach provides an accurate automatic alternative method to pick or segment filaments in 2D images and potentially in 3D tomograms. The accuracy of our approach has been demonstrated by using several other biological filaments. Our work provides a new tool to determine high-resolution structures of large MAPs bound to curved microtubule networks.

Cryomicroscopy in situ: what is the smallest molecule that can be directly identified without labels in a cell?

Electron cryomicroscopy (cryoEM) has made great strides in the last decade, such that the atomic structure of most biological macromolecules can, at least in principle, be determined. Major technological advances - in electron imaging hardware, data analysis software, and cryogenic specimen preparation technology - continue at pace and contribute to the exponential growth in the number of atomic structures determined by cryoEM. It is now conceivable that within the next decade we will have structures for hundreds of thousands of unique protein and nucleic acid molecular complexes. But the answers to many important questions in biology would become obvious if we could identify these structures precisely inside cells with quantifiable error. In the context of an abundance of known structures, it is appropriate to consider the current state of electron cryomicroscopy for frozen specimens prepared directly from cells, and try to answer to the question of the title, both now and in the foreseeable future.

Gold nanomaterials and their potential use as cryo-electron tomography labels

Rapid advances in cryo-electron tomography (cryo-ET) are driving a revolution in cellular structural biology. However, unambiguous identification of specific biomolecules within cellular tomograms remains challenging. Overcoming this obstacle and reliably identifying targets in the crowded cellular environment is of major importance for the understanding of cellular function and is a pre-requisite for high-resolution structural analysis. The use of highly-specific, readily visualised and adjustable labels would help mitigate this issue, improving both data quality and sample throughput. While progress has been made in cryo-CLEM and in the development of cloneable high-density tags, technical issues persist and a robust 'cryo-GFP' remains elusive. Readily-synthesized gold nanomaterials conjugated to small 'affinity modules' may represent a solution. The synthesis of materials including gold nanoclusters (AuNCs) and gold nanoparticles (AuNPs) is increasingly well understood and is now within the capabilities of non-specialist laboratories. The remarkable chemical and photophysical properties of <3nm diameter nanomaterials and their emergence as tools with widespread biomedical application presents significant opportunities to the cryo-microscopy community. In this review, we will outline developments in the synthesis, functionalisation and labelling uses of both AuNPs and AuNCs in cryo-ET, while discussing their potential as multi-modal probes for cryo-CLEM.

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.

Capturing actin assemblies in cells using in situ cryo-electron tomography

Actin contributes to an exceptionally wide range of cellular processes through the assembly and disassembly of highly dynamic and ordered structures. Visualizing these structures in cells can help us understand how the molecular players of the actin machinery work together to produce force-generating systems. In recent years, cryo-electron tomography (cryo-ET) has become the method of choice for structural analysis of the cell interior at the molecular scale. Here we review advances in cryo-ET workflows that have enabled this transformation, especially the automation of sample preparation procedures, data collection, and processing. We discuss new structural analyses of dynamic actin assemblies in cryo-preserved cells, which have provided mechanistic insights into actin assembly and function at the nanoscale. Finally, we highlight the latest visual proteomics studies of actin filaments and their interactors reaching sub-nanometer resolutions in cells.

Compressed sensing for electron cryotomography and high-resolution subtomogram averaging of biological specimens

Cryoelectron tomography (cryo-ET) and subtomogram averaging (STA) allow direct visualization and structural studies of biological macromolecules in their native cellular environment, in situ. Often, low signal-to-noise ratios in tomograms, low particle abundance within the cell, and low throughput in typical cryo-ET workflows severely limit the obtainable structural information. To help mitigate these limitations, here we apply a compressed sensing approach using 3D second-order total variation (CS-TV²) to tomographic reconstruction. We show that CS-TV² increases the signal-to-noise ratio in tomograms, enhancing direct visualization of macromolecules, while preserving high-resolution information up to the secondary structure level. We show that, particularly with small datasets, CS-TV² allows improvement of the resolution of STA maps. We further demonstrate that the CS-TV² algorithm is applicable to cellular specimens, leading to increased visibility of molecular detail within tomograms. This work highlights the potential of compressed sensing-based reconstruction algorithms for cryo-ET and in situ structural biology.

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Compressed sensing (CS-TV²) for cryo-ET using 3D second-order total variation

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CS-TV² increases signal contrast while retaining high-resolution information

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Improved subtomogram averaging from CS-TV² reconstructions of small datasets

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Increased contrast and detail in CS-TV² reconstructions of cellular specimens

Entropy-regularized deconvolution of cellular cryotransmission electron tomograms

Cellular cryo-electron tomography suffers from severely compromised Z resolution due to the missing wedges of information not collected during the acquisition of tilt series. This paper shows that application of entropy-regularized deconvolution to transmission electron tomography substantially fills in this missing information, allowing for improved Z resolution and better interpretation of cellular structures.

Cryo-electron tomography (cryo-ET) allows for the high-resolution visualization of biological macromolecules. However, the technique is limited by a low signal-to-noise ratio (SNR) and variance in contrast at different frequencies, as well as reduced Z resolution. Here, we applied entropy-regularized deconvolution (ER-DC) to cryo-ET data generated from transmission electron microscopy (TEM) and reconstructed using weighted back projection (WBP). We applied deconvolution to several in situ cryo-ET datasets and assessed the results by Fourier analysis and subtomogram analysis (STA).

The high-throughput production of membrane proteins

Membrane proteins, found at the junctions between the outside world and the inner workings of the cell, play important roles in human disease and are used as biosensors. More than half of all therapeutics directly affect membrane protein function while nanopores enable DNA sequencing. The structural and functional characterisation of membrane proteins is therefore crucial. However, low levels of naturally abundant protein and the hydrophobic nature of membrane proteins makes production difficult. To maximise success, high-throughput strategies were developed that rely upon simple screens to identify successful constructs and rapidly exclude those unlikely to work. Parameters that affect production such as expression host, membrane protein origin, expression vector, fusion-tags, encapsulation reagent and solvent composition are screened in parallel. In this way, constructs with divergent requirements can be produced for a variety of structural applications. As structural techniques advance, sample requirements will change. Single-particle cryo-electron microscopy requires less protein than crystallography and as cryo-electron tomography and time-resolved serial crystallography are developed new sample production requirements will evolve. Here we discuss different methods used for the high-throughput production of membrane proteins for structural biology.

Architecture of cell-cell junctions in situ reveals a mechanism for bacterial biofilm inhibition

Many bacteria, including the major human pathogen Pseudomonas aeruginosa, are naturally found in multicellular, antibiotic-tolerant biofilm communities, in which cells are embedded in an extracellular matrix of polymeric molecules. Cell-cell interactions within P. aeruginosa biofilms are mediated by CdrA, a large, membrane-associated adhesin present in the extracellular matrix of biofilms, regulated by the cytoplasmic concentration of cyclic diguanylate. Here, using electron cryotomography of focused ion beam-milled specimens, we report the architecture of CdrA molecules in the extracellular matrix of P. aeruginosa biofilms at intact cell-cell junctions. Combining our in situ observations at cell-cell junctions with biochemistry, native mass spectrometry, and cellular imaging, we demonstrate that CdrA forms an extended structure that projects from the outer membrane to tether cells together via polysaccharide binding partners. We go on to show the functional importance of CdrA using custom single-domain antibody (nanobody) binders. Nanobodies targeting the tip of functional cell-surface CdrA molecules could be used to inhibit bacterial biofilm formation or disrupt preexisting biofilms in conjunction with bactericidal antibiotics. These results reveal a functional mechanism for cell-cell interactions within bacterial biofilms and highlight the promise of using inhibitors targeting biofilm cell-cell junctions to prevent or treat problematic, chronic bacterial infections.

Integrative Structural Biology in the Era of Accurate Structure Prediction

Characterizing the three-dimensional structure of macromolecules is central to understanding their function. Traditionally, structures of proteins and their complexes have been determined using experimental techniques such as X-ray crystallography, NMR, or cryo-electron microscopy-applied individually or in an integrative manner. Meanwhile, however, computational methods for protein structure prediction have been improving their accuracy, gradually, then suddenly, with the breakthrough advance by AlphaFold2, whose models of monomeric proteins are often as accurate as experimental structures. This breakthrough foreshadows a new era of computational methods that can build accurate models for most monomeric proteins. Here, we envision how such accurate modeling methods can combine with experimental structural biology techniques, enhancing integrative structural biology. We highlight the challenges that arise when considering multiple structural conformations, protein complexes, and polymorphic assemblies. These challenges will motivate further developments, both in modeling programs and in methods to solve experimental structures, towards better and quicker investigation of structure-function relationships.

Current data processing strategies for cryo-electron tomography and subtomogram averaging

Cryo-electron tomography (cryo-ET) can be used to reconstruct three-dimensional (3D) volumes, or tomograms, from a series of tilted two-dimensional images of biological objects in their near-native states in situ or in vitro. 3D subvolumes, or subtomograms, containing particles of interest can be extracted from tomograms, aligned, and averaged in a process called subtomogram averaging (STA). STA overcomes the low signal to noise ratio within the individual subtomograms to generate structures of the particle(s) of interest. In recent years, cryo-ET with STA has increasingly been capable of reaching subnanometer resolution due to improvements in microscope hardware and data processing strategies. There has also been an increase in the number and quality of software packages available to process cryo-ET data with STA. In this review, we describe and assess the data processing strategies available for cryo-ET data and highlight the recent software developments which have enabled the extraction of high-resolution information from cryo-ET datasets.

The In Situ Structure of Parkinson's Disease-Linked LRRK2

Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most frequent cause of familial Parkinson's disease. LRRK2 is a multi-domain protein containing a kinase and GTPase. Using correlative light and electron microscopy, in situ cryo-electron tomography, and subtomogram analysis, we reveal a 14-Å structure of LRRK2 bearing a pathogenic mutation that oligomerizes as a right-handed double helix around microtubules, which are left-handed. Using integrative modeling, we determine the architecture of LRRK2, showing that the GTPase and kinase are in close proximity, with the GTPase closer to the microtubule surface, whereas the kinase is exposed to the cytoplasm. We identify two oligomerization interfaces mediated by non-catalytic domains. Mutation of one of these abolishes LRRK2 microtubule-association. Our work demonstrates the power of cryo-electron tomography to generate models of previously unsolved structures in their cellular environment.