An improved algorithm for anisotropic nonlinear diffusion for denoising cryo-tomograms

Disruption of the mitochondrial network in a mouse model of Huntington's disease visualized by in-tissue multiscale 3D electron microscopy

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the coding sequence of huntingtin protein. Initially, it predominantly affects medium-sized spiny neurons (MSSNs) of the corpus striatum. No effective treatment is still available, thus urging the identification of potential therapeutic targets. While evidence of mitochondrial structural alterations in HD exists, previous studies mainly employed 2D approaches and were performed outside the strictly native brain context. In this study, we adopted a novel multiscale approach to conduct a comprehensive 3D in situ structural analysis of mitochondrial disturbances in a mouse model of HD. We investigated MSSNs within brain tissue under optimal structural conditions utilizing state-of-the-art 3D imaging technologies, specifically FIB/SEM for the complete imaging of neuronal somas and Electron Tomography for detailed morphological examination, and image processing-based quantitative analysis. Our findings suggest a disruption of the mitochondrial network towards fragmentation in HD. The network of interlaced, slim and long mitochondria observed in healthy conditions transforms into isolated, swollen and short entities, with internal cristae disorganization, cavities and abnormally large matrix granules.

Self-supervised noise modeling and sparsity guided electron tomography volumetric image denoising

Cryo-Electron Tomography (cryo-ET) is a revolutionary technique for visualizing macromolecular structures in near-native states. However, the physical limitations of imaging instruments lead to cryo-ET volumetric images with very low Signal-to-Noise Ratio (SNR) with complex noise, which has a side effect on the downstream analysis of the characteristics of observed macromolecules. Additionally, existing methods for image denoising are difficult to be well generalized to the complex noise in cryo-ET volumes. In this work, we propose a self-supervised deep learning model for cryo-ET volumetric image denoising based on noise modeling and sparsity guidance (NMSG), achieved by learning the noise distribution in noisy cryo-ET volumes and introducing sparsity guidance to ensure smoothness. Firstly, a Generative Adversarial Network (GAN) is utilized to learn noise distribution in cryo-ET volumes and generate noisy volumes pair from single volume. Then, a new loss function is devised to both ensure the recovery of ultrastructure and local smoothness. Experiments are done on five real cryo-ET datasets and three simulated cryo-ET datasets. The comprehensive experimental results demonstrate that our method can perform reliable denoising by training on single noisy volume, achieving better results than state-of-the-art single volume-based methods and competitive with methods trained on large-scale datasets.

Structure-preserving Gaussian denoising of FIB-SEM volumes

FIB-SEM (Focused Ion Beam-Scanning Electron Microscopy) is an imaging technique that allows 3D ultrastructural analysis of cells and tissues at the nanoscale. The acquired FIB-SEM data are highly noisy, which makes denoising an essential step prior to volume interpretation. Gaussian filtering is a standard method in the field because it is fast and straightforward. However, it tends to blur the biological features due to its linear nature that ignores the rapid changes of the structures throughout the volume. To address this issue, we have developed a new approach to structure-preserving noise reduction for FIB-SEM. It has abilities to locally adapt the filtering to the biological structures while taking advantage of the simplicity of Gaussian filtering. It uses the Optical Flow (OF) to estimate the variations of the structural features across the volume, so that they are compensated before the subsequent filtering with a Gaussian function. As demonstrated qualitatively and objectively with datasets from different samples and acquired under different conditions, our denoising approach outperforms the standard Gaussian filtering and is competitive with state-of-the-art methods in terms of noise reduction and preservation of the sharpness of the structures.

Quantitative Cryo-Electron Tomography

The three-dimensional organization of biomolecules important for the functioning of all living systems can be determined by cryo-electron tomography imaging under native biological contexts. Cryo-electron tomography is continually expanding and evolving, and the development of new methods that use the latest technology for sample thinning is enabling the visualization of ever larger and more complex biological systems, allowing imaging across scales. Quantitative cryo-electron tomography possesses the capability of visualizing the impact of molecular and environmental perturbations in subcellular structure and function to understand fundamental biological processes. This review provides an overview of current hardware and software developments that allow quantitative cryo-electron tomography studies and their limitations and how overcoming them may allow us to unleash the full power of cryo-electron tomography.

Quantitative Evaluation of Supported Catalysts Key Properties from Electron Tomography Studies: Assessing Accuracy Using Material-Realistic 3D-Models

Electron Tomography (ET) reconstructions can be analysed, via segmentation techniques, to obtain quantitative, 3D-information about individual nanoparticles in supported catalysts. This includes values of parameters out of reach for any other technique, like their volume and surface, which are required to determine the dispersion of the supported particle system or the specific surface area of the support; two figures that play a major role in the performance of this type of catalysts.

However, both the experimental conditions during the acquisition of the tilt series and the limited fidelity of the reconstruction and segmentation algorithms, restrict the quality of the ET results and introduce an undefined amount of error both in the qualitative features of the reconstructions and in all the quantitative parameters measured from them.

Here, a method based on the use of well-defined 3D geometrical models (phantoms), with morphological features closely resembling those observed in experimental images of an Au/CeO2 catalyst, has been devised to provide a precise estimation of the accuracy of the reconstructions. Using this approach, the influence of noise and the number of projections on the errors of reconstructions obtained using a Total Variation Minimization in 3D (TVM-3D) algorithm have been determined. Likewise, the benefits of using smart denoising techniques based on Undecimated Wavelet Transforms (UWT) have been also evaluated.

The results clearly reveal a large impact of usual noise levels on both the quality of the reconstructions and nanometrological measurement errors. Quantitative clues about the key role of UWT to largely compensate them are also provided.

Enhancement of Cryo-EM maps by a multiscale tubular filter

We present an approach to enhance cryo-electron microscopy (cryo-EM) postprocessed maps based on a multiscale tubular filter. The method determines a tubularness measure locally by the analysis of the eigenvalues of the Hessian matrix. This information is used to enhance elongated local structures and to attenuate blob-like and plate-like structures. The approach, thus, introduces a priori information in the reconstructions to improve their interpretability and analysis at high-resolution. The proposed method has been tested with simulated and real cryo-EM maps including recent reconstructions of the SARS-CoV-2. Our results show that our methods can improve obtained reconstructions.

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).

Monitoring reversion of hepatitis C virus-induced cellular alterations by direct-acting antivirals using cryo soft X-ray tomography and infrared microscopy

Hepatitis C virus (HCV) is an enveloped RNA virus. One of the hallmarks of HCV infection is a rearrangement of the host cell membranes, known as the `membranous web'. Full-field cryo soft X-ray tomography (cryo-SXT) in the water-window energy range (284-543 eV) was performed on the MISTRAL beamline to investigate, in whole unstained cells, the morphology of the membranous rearrangements induced in HCV replicon-harbouring cells in conditions close to the living physiological state. All morphological alterations could be reverted by a combination of sofosbuvir/daclatasvir, which are clinically approved antivirals (direct-acting antivirals; DAAs) for HCV infection. Correlatively combining cryo-SXT and 2D synchrotron-based infrared microscopy provides critical information on the chemical nature of specific infection-related structures, which allows specific patterns of the infection process or the DAA-mediated healing process to be distinguished.

High resolution electron tomography and segmentation-by-modeling interpretation in Bsoft

Bsoft offers many tools for the processing of tomographic tilt series and the interpretation of tomograms. Since I introduced tomography into Bsoft almost two decades ago, the field has advanced significantly, requiring refinement of old algorithms and development of new ones. The current direct detectors allow us to collect data more efficiently and with better quality, progressing towards automation. The goal is then to also automate alignment of tilt series and reconstruction. I added an estimation of the specimen thickness as well as fiducialless alignment, to augment the existing fiducial-based alignment. High-resolution work requires correction for the contrast transfer function, in tomography complicated by the tilted specimen. For this, I developed a method to generate a power spectrum using the whole micrograph, compensating for tilting. This is followed by routine determination of the contrast transfer function, and correction for it during reconstruction. The next steps involve interpretation of the tomogram, either by subtomogram averaging where possible, or by segmentation and modeling otherwise. Such interpretation actually constitutes the main time-consuming part of tomography and is less amenable to automation compared to the initial reconstruction.

The promise and the challenges of cryo-electron tomography

Structural biologists have traditionally approached cellular complexity in a reductionist manner in which the cellular molecular components are fractionated and purified before being studied individually. This 'divide and conquer' approach has been highly successful. However, awareness has grown in recent years that biological functions can rarely be attributed to individual macromolecules. Most cellular functions arise from their concerted action, and there is thus a need for methods enabling structural studies performed in situ, ideally in unperturbed cellular environments. Cryo-electron tomography (Cryo-ET) combines the power of 3D molecular-level imaging with the best structural preservation that is physically possible to achieve. Thus, it has a unique potential to reveal the supramolecular architecture or 'molecular sociology' of cells and to discover the unexpected. Here, we review state-of-the-art Cryo-ET workflows, provide examples of biological applications, and discuss what is needed to realize the full potential of Cryo-ET.

3D mesh processing using GAMer 2 to enable reaction-diffusion simulations in realistic cellular geometries

Recent advances in electron microscopy have enabled the imaging of single cells in 3D at nanometer length scale resolutions. An uncharted frontier for in silico biology is the ability to simulate cellular processes using these observed geometries. Enabling such simulations requires watertight meshing of electron micrograph images into 3D volume meshes, which can then form the basis of computer simulations of such processes using numerical techniques such as the finite element method. In this paper, we describe the use of our recently rewritten mesh processing software, GAMer 2, to bridge the gap between poorly conditioned meshes generated from segmented micrographs and boundary marked tetrahedral meshes which are compatible with simulation. We demonstrate the application of a workflow using GAMer 2 to a series of electron micrographs of neuronal dendrite morphology explored at three different length scales and show that the resulting meshes are suitable for finite element simulations. This work is an important step towards making physical simulations of biological processes in realistic geometries routine. Innovations in algorithms to reconstruct and simulate cellular length scale phenomena based on emerging structural data will enable realistic physical models and advance discovery at the interface of geometry and cellular processes. We posit that a new frontier at the intersection of computational technologies and single cell biology is now open.

Multiparametric analysis of the effectiveness of cisplatin on cutaneous squamous carcinoma cells using two different types of adjuvants

The objective of this study was to regulate the cytotoxicity of cisplatin (cisPt) minimizing its adverse effects. For this purpose, the lowest cisPt concentration needed to obtain a significant positive response in cutaneous squamous cell carcinoma (cSCC) was explored. Two adjuvant agents as gold nanoparticles (AuNP) and chelating tricine were tested as enhancers in cisPt treatment. Effectiveness of all treatments was assessed by means of biochemical techniques, which offer quantitative data, as well as two microscopy–based techniques that provided qualitative cell imaging. The present work confirms the effectiveness of free cisplatin at very low concentrations. In order to enhance its effectiveness while the side effects were probably diminished, cisPt 3.5 μM was administered with AuNP 2.5 mM, showing an effectiveness practically equal to that observed with free cisPt. However, the second treatment investigated, based on cisPt 3.5 μM combined with tricine 50 mM, enhanced drug effectiveness, increasing the percentage of cells dying by apoptosis. This treatment was even better in terms of cell damage than free cisPt at 15 μM. Images obtained by TEM and cryo-SXT confirmed these results, since a notable number of apoptotic bodies were detected when cisPt was combined with tricine. Thus, tricine was clearly a better adjuvant for cisPt treatments.

Tricalbin-Mediated Contact Sites Control ER Curvature to Maintain Plasma Membrane Integrity

Membrane contact sites (MCS) between the endoplasmic reticulum (ER) and the plasma membrane (PM) play fundamental roles in all eukaryotic cells. ER-PM MCS are particularly abundant in Saccharomyces cerevisiae, where approximately half of the PM surface is covered by cortical ER (cER). Several proteins, including Ist2, Scs2/22, and Tcb1/2/3 are implicated in cER formation, but the specific roles of these molecules are poorly understood. Here, we use cryo-electron tomography to show that ER-PM tethers are key determinants of cER morphology. Notably, Tcb proteins (tricalbins) form peaks of extreme curvature on the cER membrane facing the PM. Combined modeling and functional assays suggest that Tcb-mediated cER peaks facilitate the transport of lipids between the cER and the PM, which is necessary to maintain PM integrity under heat stress. ER peaks were also present at other MCS, implying that membrane curvature enforcement may be a widespread mechanism to regulate MCS function.

A Monte Carlo framework for missing wedge restoration and noise removal in cryo-electron tomography

We propose a statistical method to address an important issue in cryo-electron tomography image analysis: reduction of a high amount of noise and artifacts due to the presence of a missing wedge (MW) in the spectral domain. The method takes as an input a 3D tomogram derived from limited-angle tomography, and gives as an output a 3D denoised and artifact compensated volume. The artifact compensation is achieved by filling up the MW with meaningful information. To address this inverse problem, we compute a Minimum Mean Square Error (MMSE) estimator of the uncorrupted image. The underlying high-dimensional integral is computed by applying a dedicated Markov Chain Monte-Carlo (MCMC) sampling procedure based on the Metropolis-Hasting (MH) algorithm. The proposed MWR (Missing Wedge Restoration) algorithm can be used to enhance visualization or as a pre-processing step for image analysis, including segmentation and classification of macromolecules. Results are presented for both synthetic data and real 3D cryo-electron images.

TomoEED: fast edge-enhancing denoising of tomographic volumes

Summary

TomoEED is an optimized software tool for fast feature-preserving noise filtering of large 3D tomographic volumes on CPUs and GPUs. The tool is based on the anisotropic nonlinear diffusion method. It has been developed with special emphasis in the reduction of the computational demands by using different strategies, from the algorithmic to the high performance computing perspectives. TomoEED manages to filter large volumes in a matter of minutes in standard computers.

Availability and implementation

TomoEED has been developed in C. It is available for Linux platforms at http://www.cnb.csic.es/%7ejjfernandez/tomoeed.

Supplementary information

Supplementary data are available at Bioinformatics online.

Towards a mechanistic understanding of cellular processes by cryoEM

A series of recent hardware and software developments have transformed cryo-electron microscopy (cryoEM) from a niche tool into a method that has become indispensable in structural and functional biology. Samples that are rapidly frozen are encased in a near-native state inside a layer of amorphous ice, and then imaged in an electron microscope cooled to cryogenic temperatures. Despite being conceptually simple, cryoEM owns its success to a plethora of technological developments from numerous research groups. Here, we review the key technologies that have made this astonishing transformation possible and highlight recent trends with a focus on cryo-electron tomography. Additionally, we discuss how correlated microscopy is an exciting and perpendicular development route forward in this already rapidly growing field. We specifically discuss microscopy techniques that allow to complement time-dependent information of dynamic processes to the unique high resolution obtained in cryoEM.

Membrane reshaping by micrometric curvature sensitive septin filaments

Septins are cytoskeletal filaments that assemble at the inner face of the plasma membrane. They are localized at constriction sites and impact membrane remodeling. We report in vitro tools to examine how yeast septins behave on curved and deformable membranes. Septins reshape the membranes of Giant Unilamellar Vesicles with the formation of periodic spikes, while flattening smaller vesicles. We show that membrane deformations are associated to preferential arrangement of septin filaments on specific curvatures. When binding to bilayers supported on custom-designed periodic wavy patterns displaying positive and negative micrometric radii of curvatures, septin filaments remain straight and perpendicular to the curvature of the convex parts, while bending negatively to follow concave geometries. Based on these results, we propose a theoretical model that describes the deformations and micrometric curvature sensitivity observed in vitro. The model captures the reorganizations of septin filaments throughout cytokinesis in vivo, providing mechanistic insights into cell division.

Septins are cytoskeletal filaments that localize at constriction sites and impact membrane remodeling. Here authors examine the curvature sensitivity of septins using bilayers on wavy patterns and derive a theoretical model that quantitatively describe the results.

Pleomorphic linkers as ubiquitous structural organizers of vesicles in axons

Many cellular processes depend on a precise structural organization of molecular components. Here, we established that neurons grown in culture provide a suitable system for in situ structural investigations of cellular structures by cryo-electron tomography, a method that allows high resolution, three-dimensional imaging of fully hydrated, vitrified cellular samples. A higher level of detail of cellular components present in our images allowed us to quantitatively characterize presynaptic and cytoskeletal organization, as well as structures involved in axonal transport and endocytosis. In this way we provide a structural framework into which information from other methods need to fit. Importantly, we show that short pleomorphic linkers (tethers and connectors) extensively interconnect different types of spherical vesicles and other lipid membranes in neurons imaged in a close-to-native state. These linkers likely serve to organize and precisely position vesicles involved in endocytosis, axonal transport and synaptic release. Hence, structural interactions via short linkers may serve as ubiquitous vesicle organizers in neuronal cells.

Marker-free method for accurate alignment between correlated light, cryo-light, and electron cryo-microscopy data using sample support features

Combining fluorescence microscopy with electron cryo-tomography allows, in principle, spatial localization of tagged macromolecular assemblies and structural features within the cellular environment. To allow precise localization and scale integration between the two disparate imaging modalities, accurate alignment procedures are needed. Here, we describe a marker-free method for aligning images from light or cryo-light fluorescence microscopy and from electron cryo-microscopy that takes advantage of sample support features, namely the holes in the carbon film. We find that the accuracy of this method, as judged by prediction errors of the hole center coordinates, is better than 100 nm.

Synucleins Have Multiple Effects on Presynaptic Architecture

Synucleins (α, β, γ-synuclein) are a family of abundant presynaptic proteins. α-Synuclein is causally linked to the pathogenesis of Parkinson's disease (PD). In an effort to define their physiological and pathological function or functions, we investigated the effects of deleting synucleins and overexpressing α-synuclein PD mutations, in mice, on synapse architecture using electron microscopy (EM) and cryoelectron tomography (cryo-ET). We show that synucleins are regulators of presynapse size and synaptic vesicle (SV) pool organization. Using cryo-ET, we observed that deletion of synucleins increases SV tethering to the active zone but decreases the inter-linking of SVs by short connectors. These ultrastructural changes were correlated with discrete protein phosphorylation changes in αβγ-synuclein-/- neurons. We also determined that α-synuclein PD mutants (PARK1/hA30P and PARK4/hα-syn) primarily affected presynaptic cytomatrix proximal to the active zone, congruent with previous findings that these PD mutations decrease neurotransmission. Collectively, our results suggest that synucleins are important orchestrators of presynaptic terminal topography.

Membrane-assisted viral DNA ejection

Genome packaging and delivery are fundamental steps in the replication cycle of all viruses. Icosahedral viruses with linear double-stranded DNA (dsDNA) usually package their genome into a preformed, rigid procapsid using the power generated by a virus-encoded packaging ATPase. The pressure and stored energy due to this confinement of DNA at a high density is assumed to drive the initial stages of genome ejection. Membrane-containing icosahedral viruses, such as bacteriophage PRD1, present an additional architectural complexity by enclosing their genome within an internal membrane vesicle. Upon adsorption to a host cell, the PRD1 membrane remodels into a proteo-lipidic tube that provides a conduit for passage of the ejected linear dsDNA through the cell envelope. Based on volume analyses of PRD1 membrane vesicles captured by cryo-electron tomography and modeling of the elastic properties of the vesicle, we propose that the internal membrane makes a crucial and active contribution during infection by maintaining the driving force for DNA ejection and countering the internal turgor pressure of the host. These novel functions extend the role of the PRD1 viral membrane beyond tube formation or the mere physical confinement of the genome. The presence and assistance of an internal membrane might constitute a biological advantage that extends also to other viruses that package their linear dsDNA to high density within an internal vesicle.

The benefit of thresholding carbon layers in electron tomographic tilt series by intensity downshifting

When performing electron tomography, tilt series of images are often acquired from samples that contain unwanted carbonaceous material, such as an embedding resin, a thin carbon support film or hydrocarbon contamination. The presence of such layers can introduce artefacts in reconstructions, obscuring features of interest. Here, we illustrate the benefit of preprocessing a high-angle annular dark-field tomographic tilt series by thresholding unwanted low-density materials using a simple intensity downshifting procedure. The resulting tomograms have fewer artefacts and segmentation can be performed more accurately. We present two representative examples taken from studies of catalyst nanoparticles and amyloid plaque core material from the human brain.

Hierarchical detection and analysis of macromolecular complexes in cryo-electron tomograms using Pyto software

Molecular complexes, arguably the basic units carrying cellular function, can be visualized directly in their native environment by cryo-electron tomography. Here we describe a procedure for the detection of small, pleomorphic membrane-bound molecular complexes in cryo-tomograms by a hierarchical connectivity segmentation. Validation on phantom and real data showed above 90% true positive rates. This segmentation procedure is implemented in the Pyto software package, together with methods for quantitative characterization and classification of complexes detected by our segmentation procedure and for statistical analysis between experimental conditions. Therefore, the methods presented provide a means for the detection and quantitative interpretation of structures captured in cryo-electron tomograms, as well as for the elucidation of their cellular function.

Structural Changes In Cells Imaged by Soft X-ray Cryo-Tomography During Hepatitis C Virus Infection

Chronic hepatitis C virus (HCV) infection causes severe liver disease in millions of humans worldwide. Pathogenesis of HCV infection is strongly driven by a deficient immune response of the host, although intersection of different aspects of the virus life cycle with cellular homeostasis is emerging as an important player in the pathogenesis and progression of the disease. Cryo soft X-ray tomography (cryo-SXT) was performed to investigate the ultrastructural alterations induced by the interference of HCV replication with cellular homeostasis. Native, whole cell, three-dimensional (3D) maps were obtained in HCV replicon-harboring cells and in a surrogate model of HCV infection. Tomograms from HCV-replicating cells show blind-ended endoplasmic reticulum tubules with pseudospherical extrusions and marked alterations of mitochondrial morphology that correlated spatially with the presence of endoplasmic reticulum alterations, suggesting a short-range influence of the viral machinery on mitochondrial homeostasis. Both mitochondrial and endoplasmic reticulum alterations could be reverted by a combination of sofosbuvir/daclatasvir, which are clinically approved direct-acting antivirals for the treatment of chronic HCV infection. In addition to providing structural insight into cellular aspects of HCV pathogenesis, our study illustrates how cryo-SXT is a powerful 3D wide-field imaging tool for the assessment and understanding of complex cellular processes in a setting of near-native whole hydrated cells. Our results also constitute a proof of concept for the use of cryo-SXT as a platform that enables determining the potential impact of candidate compounds on the ultrastructure of the cell that may assist drug development at a preclinical level.

Denoising of high-resolution single-particle electron-microscopy density maps by their approximation using three-dimensional Gaussian functions

Cryo-electron microscopy (cryo-EM) of frozen-hydrated preparations of isolated macromolecular complexes is the method of choice to obtain the structure of complexes that cannot be easily studied by other experimental methods due to their flexibility or large size. An increasing number of macromolecular structures are currently being obtained at subnanometer resolution but the interpretation of structural details in such EM-derived maps is often difficult because of noise at these high-frequency signal components that reduces their contrast. In this paper, we show that the method for EM density-map approximation using Gaussian functions can be used for denoising of single-particle EM maps of high (typically subnanometer) resolution. We show its denoising performance using simulated and experimental EM density maps of several complexes.

Characterization of Septin Ultrastructure in Budding Yeast Using Electron Tomography

Septins are essential for the completion of cytokinesis. In budding yeast, Saccharomyces cerevisiae, septins are located at the bud neck during mitosis and are closely connected to the inner plasma membrane. In vitro, yeast septins have been shown to self-assemble into a variety of filamentous structures, including rods, paired filaments, bundles, and rings (Bertin et al. Proc Natl Acad Sci U S A, 105(24):8274-8279, 2008; Garcia et al. J Cell Biol, 195(6):993-1004, 2011; Bertin et al. J Mol Biol, 404(4):711-731, 2010). Using electron tomography of freeze-substituted sections and cryo-electron tomography of frozen sections, we determined the three-dimensional organization of the septin cytoskeleton in dividing budding yeast with molecular resolution (Bertin et al. Mol Biol Cell, 23(3):423-432, 2012; Bertin and Nogales. Commun Integr Biol 5(5):503-505, 2012). Here, we describe the detailed procedures used for our characterization of the septin cellular ultrastructure.

Removing Contamination-Induced Reconstruction Artifacts from Cryo-electron Tomograms

Imaging of fully hydrated, vitrified biological samples by electron tomography yields structural information about cellular protein complexes in situ. Here we present a computational procedure that removes artifacts of three-dimensional reconstruction caused by contamination present in samples during imaging by electron microscopy. Applying the procedure to phantom data and electron tomograms of cellular samples significantly improved the resolution and the interpretability of tomograms. Artifacts caused by surface contamination associated with thinning by focused ion beam, as well as those arising from gold fiducial markers and from common, lower contrast contamination, could be removed. Our procedure is widely applicable and is especially suited for applications that strive to reach a higher resolution and involve the use of recently developed, state-of-the-art instrumentation.

Machine learning as a tool for classifying electron tomographic reconstructions

Electron tomographic reconstructions often contain artefacts from sources such as noise in the projections and a “missing wedge” of projection angles which can hamper quantitative analysis. We present a machine-learning approach using freely available software for analysing imperfect reconstructions to be used in place of the more traditional thresholding based on grey-level technique and show that a properly trained image classifier can achieve manual levels of accuracy even on heavily artefacted data, though if multiple reconstructions are being processed, a separate classifier will need to be trained on each reconstruction for maximum accuracy.

Persistent topology for cryo-EM data analysis

In this work, we introduce persistent homology for the analysis of cryo-electron microscopy (cryo-EM) density maps. We identify the topological fingerprint or topological signature of noise, which is widespread in cryo-EM data. For low signal-to-noise ratio (SNR) volumetric data, intrinsic topological features of biomolecular structures are indistinguishable from noise. To remove noise, we employ geometric flows that are found to preserve the intrinsic topological fingerprints of cryo-EM structures and diminish the topological signature of noise. In particular, persistent homology enables us to visualize the gradual separation of the topological fingerprints of cryo-EM structures from those of noise during the denoising process, which gives rise to a practical procedure for prescribing a noise threshold to extract cryo-EM structure information from noise contaminated data after certain iterations of the geometric flow equation. To further demonstrate the utility of persistent homology for cryo-EM data analysis, we consider a microtubule intermediate structure Electron Microscopy Data (EMD 1129). Three helix models, an alpha-tubulin monomer model, an alpha-tubulin and beta-tubulin model, and an alpha-tubulin and beta-tubulin dimer model, are constructed to fit the cryo-EM data. The least square fitting leads to similarly high correlation coefficients, which indicates that structure determination via optimization is an ill-posed inverse problem. However, these models have dramatically different topological fingerprints. Especially, linkages or connectivities that discriminate one model from another, play little role in the traditional density fitting or optimization but are very sensitive and crucial to topological fingerprints. The intrinsic topological features of the microtubule data are identified after topological denoising. By a comparison of the topological fingerprints of the original data and those of three models, we found that the third model is topologically favored. The present work offers persistent homology based new strategies for topological denoising and for resolving ill-posed inverse problems.

Removing the effects of the "dark matter" in tomography

Electron tomography (ET) using different imaging modes has been progressively consolidating its position as a key tool in materials science. The fidelity of a tomographic reconstruction, or tomogram, is affected by several experimental factors. Most often, an unrealistic cloud of intensity that does not correspond to a real material phase of the specimen ("dark matter") blurs the tomograms and enhances artefacts arising from the missing wedge (MW). Here we show that by simple preprocessing of the background level of any tomographic tilt series, it is possible to minimise the negative effects of that "dark matter". Iterative reconstruction algorithms converge better, leading to tomograms with fewer streaking artefacts from the MW, more contrast, and increased accuracy. The conclusions are valid irrespective of the imaging mode used, and the methodology improves the segmentation and visualisation of tomograms of both crystalline and amorphous materials. We show examples of HAADF STEM and BF TEM tomography.

Cryo-electron tomography of plunge-frozen whole bacteria and vitreous sections to analyze the recently described bacterial cytoplasmic structure, the Stack

Cryo-electron tomography (CET) of plunge-frozen whole bacteria and vitreous sections (CETOVIS) were used to revise and expand the structural knowledge of the "Stack", a recently described cytoplasmic structure in the Antarctic bacterium Pseudomonas deceptionensis M1(T). The advantages of both techniques can be complementarily combined to obtain more reliable insights into cells and their components with three-dimensional imaging at different resolutions. Cryo-electron microscopy (Cryo-EM) and CET of frozen-hydrated P. deceptionensis M1(T) cells confirmed that Stacks are found at different locations within the cell cytoplasm, in variable number, separately or grouped together, very close to the plasma membrane (PM) and oriented at different angles (from 35° to 90°) to the PM, thus establishing that they were not artifacts of the previous sample preparation methods. CET of plunge-frozen whole bacteria and vitreous sections verified that each Stack consisted of a pile of oval disc-like subunits, each disc being surrounded by a lipid bilayer membrane and separated from each other by a constant distance with a mean value of 5.2±1.3nm. FM4-64 staining and confocal microscopy corroborated the lipid nature of the membrane of the Stacked discs. Stacks did not appear to be invaginations of the PM because no continuity between both membranes was visible when whole bacteria were analyzed. We are still far from deciphering the function of these new structures, but a first experimental attempt links the Stacks with a given phase of the cell replication process.

Electron Tomography Methods for C. elegans

Methods for electron tomography of the nematode C. elegans are explained in detail, including a brief introduction to specimen preparation, methods for image collection, and a comparison of several general methods for producing dual-axis tomograms, with or without external fiducial reference objects. New electron tomograms highlight features in software for data display, annotation, and analysis. This chapter discusses the ultrastructural analysis of cells and tissues, rather than molecular studies.

Electron tomography of cryo-immobilized plant tissue: a novel approach to studying 3D macromolecular architecture of mature plant cell walls in situ

Cost-effective production of lignocellulosic biofuel requires efficient breakdown of cell walls present in plant biomass to retrieve the wall polysaccharides for fermentation. In-depth knowledge of plant cell wall composition is therefore essential for improving the fuel production process. The precise spatial three-dimensional (3D) organization of cellulose, hemicellulose, pectin and lignin within plant cell walls remains unclear to date since the microscopy techniques used so far have been limited to two-dimensional, topographic or low-resolution imaging, or required isolation or chemical extraction of the cell walls. In this paper we demonstrate that by cryo-immobilizing fresh tissue, then either cryo-sectioning or freeze-substituting and resin embedding, followed by cryo- or room temperature (RT) electron tomography, respectively, we can visualize previously unseen details of plant cell wall architecture in 3D, at macromolecular resolution (∼2 nm), and in near-native state. Qualitative and quantitative analyses showed that wall organization of cryo-immobilized samples were preserved remarkably better than conventionally prepared samples that suffer substantial extraction. Lignin-less primary cell walls were well preserved in both self-pressurized rapidly frozen (SPRF), cryo-sectioned samples as well as high-pressure frozen, freeze-substituted and resin embedded (HPF-FS-resin) samples. Lignin-rich secondary cell walls appeared featureless in HPF-FS-resin sections presumably due to poor stain penetration, but their macromolecular features could be visualized in unprecedented details in our cryo-sections. While cryo-tomography of vitreous tissue sections is currently proving to be instrumental in developing 3D models of lignin-rich secondary cell walls, here we confirm that the technically easier method of RT-tomography of HPF-FS-resin sections could be used immediately for routine study of low-lignin cell walls. As a proof of principle, we characterized the primary cell walls of a mutant (cob-6) and wild type Arabidopsis hypocotyl parenchyma cells by RT-tomography of HPF-FS-resin sections, and detected a small but significant difference in spatial organization of cellulose microfibrils in the mutant walls.

Robust membrane detection based on tensor voting for electron tomography

Electron tomography enables three-dimensional (3D) visualization and analysis of the subcellular architecture at a resolution of a few nanometers. Segmentation of structural components present in 3D images (tomograms) is often necessary for their interpretation. However, it is severely hampered by a number of factors that are inherent to electron tomography (e.g. noise, low contrast, distortion). Thus, there is a need for new and improved computational methods to facilitate this challenging task. In this work, we present a new method for membrane segmentation that is based on anisotropic propagation of the local structural information using the tensor voting algorithm. The local structure at each voxel is then refined according to the information received from other voxels. Because voxels belonging to the same membrane have coherent structural information, the underlying global structure is strengthened. In this way, local information is easily integrated at a global scale to yield segmented structures. This method performs well under low signal-to-noise ratio typically found in tomograms of vitrified samples under cryo-tomography conditions and can bridge gaps present on membranes. The performance of the method is demonstrated by applications to tomograms of different biological samples and by quantitative comparison with standard template matching procedure.

A cylindrical specimen holder for electron cryo-tomography

The use of slab-like flat specimens for electron cryo-tomography restricts the range of viewing angles that can be used. This leads to the "missing wedge" problem, which causes artefacts and anisotropic resolution in reconstructed tomograms. Cylindrical specimens provide a way to eliminate the problem, since they allow imaging from a full range of viewing angles around the tilt axis. Such specimens have been used before for tomography of radiation-insensitive samples at room temperature, but never for frozen-hydrated specimens. Here, we demonstrate the use of thin-walled carbon tubes as specimen holders, allowing the preparation of cylindrical frozen-hydrated samples of ribosomes, liposomes and whole bacterial cells. Images acquired from these cylinders have equal quality at all viewing angles, and the accessible tilt range is restricted only by the physical limits of the microscope. Tomographic reconstructions of these specimens demonstrate that the effects of the missing wedge are substantially reduced, and could be completely eliminated if a full tilt range was used. The overall quality of these tomograms is still lower than that obtained by existing methods, but improvements are likely in future.

Electron tomography for organelles, cells, and tissues

Electron tomography (ET) is an emerging electron microscopy (EM) technique for three-dimensional (3D) visualization of molecular arrangements and ultrastructural architectures in organelles, cells, and tissues at 2-10 nm resolution. The 3D tomogram is reconstructed from a series of 2D EM images taken from a single specimen at different projecting orientations. The specimen for ET must be specially prepared to meet the ET imaging requirements, i.e., ultrastructural preservation, specimen thickness, tolerance of electron dose and vacuum, and image contrast. In this chapter, the strategies of specimen preparation of organelles, cells, and tissues and the corresponding EM imaging requirements for ET will be described in detail. In addition, the general procedures tomographic reconstruction and tomogram interpretation will be described.

Multiscale geometric modeling of macromolecules I: Cartesian representation

This paper focuses on the geometric modeling and computational algorithm development of biomolecular structures from two data sources: Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB) in the Eulerian (or Cartesian) representation. Molecular surface (MS) contains non-smooth geometric singularities, such as cusps, tips and self-intersecting facets, which often lead to computational instabilities in molecular simulations, and violate the physical principle of surface free energy minimization. Variational multiscale surface definitions are proposed based on geometric flows and solvation analysis of biomolecular systems. Our approach leads to geometric and potential driven Laplace-Beltrami flows for biomolecular surface evolution and formation. The resulting surfaces are free of geometric singularities and minimize the total free energy of the biomolecular system. High order partial differential equation (PDE)-based nonlinear filters are employed for EMDB data processing. We show the efficacy of this approach in feature-preserving noise reduction. After the construction of protein multiresolution surfaces, we explore the analysis and characterization of surface morphology by using a variety of curvature definitions. Apart from the classical Gaussian curvature and mean curvature, maximum curvature, minimum curvature, shape index, and curvedness are also applied to macromolecular surface analysis for the first time. Our curvature analysis is uniquely coupled to the analysis of electrostatic surface potential, which is a by-product of our variational multiscale solvation models. As an expository investigation, we particularly emphasize the numerical algorithms and computational protocols for practical applications of the above multiscale geometric models. Such information may otherwise be scattered over the vast literature on this topic. Based on the curvature and electrostatic analysis from our multiresolution surfaces, we introduce a new concept, the polarized curvature, for the prediction of protein binding sites.

Cryo-electron tomography: the challenge of doing structural biology in situ

Electron microscopy played a key role in establishing cell biology as a discipline, by producing fundamental insights into cellular organization and ultrastructure. Many seminal discoveries were made possible by the development of new sample preparation methods and imaging modalities. Recent technical advances include sample vitrification that faithfully preserves molecular structures, three-dimensional imaging by electron tomography, and improved image-processing methods. These new techniques have enabled the extraction of high fidelity structural information and are beginning to reveal the macromolecular organization of unperturbed cellular environments.

Mechanism of membranous tunnelling nanotube formation in viral genome delivery

In internal membrane-containing viruses, a lipid vesicle enclosed by the icosahedral capsid protects the genome. It has been postulated that this internal membrane is the genome delivery device of the virus. Viruses built with this architectural principle infect hosts in all three domains of cellular life. Here, using a combination of electron microscopy techniques, we investigate bacteriophage PRD1, the best understood model for such viruses, to unveil the mechanism behind the genome translocation across the cell envelope. To deliver its double-stranded DNA, the icosahedral protein-rich virus membrane transforms into a tubular structure protruding from one of the 12 vertices of the capsid. We suggest that this viral nanotube exits from the same vertex used for DNA packaging, which is biochemically distinct from the other 11. The tube crosses the capsid through an aperture corresponding to the loss of the peripentonal P3 major capsid protein trimers, penton protein P31 and membrane protein P16. The remodeling of the internal viral membrane is nucleated by changes in osmolarity and loss of capsid-membrane interactions as consequence of the de-capping of the vertices. This engages the polymerization of the tail tube, which is structured by membrane-associated proteins. We have observed that the proteo-lipidic tube in vivo can pierce the gram-negative bacterial cell envelope allowing the viral genome to be shuttled to the host cell. The internal diameter of the tube allows one double-stranded DNA chain to be translocated. We conclude that the assembly principles of the viral tunneling nanotube take advantage of proteo-lipid interactions that confer to the tail tube elastic, mechanical and functional properties employed also in other protein-membrane systems.

Cryo-electron tomography reveals a critical role of RIM1α in synaptic vesicle tethering

Synaptic vesicles are embedded in a complex filamentous network at the presynaptic terminal. Before fusion, vesicles are linked to the active zone (AZ) by short filaments (tethers). The identity of the molecules that form and regulate tethers remains unknown, but Rab3-interacting molecule (RIM) is a prominent candidate, given its central role in AZ organization. In this paper, we analyzed presynaptic architecture of RIM1α knockout (KO) mice by cryo-electron tomography. In stark contrast to previous work on dehydrated, chemically fixed samples, our data show significant alterations in vesicle distribution and AZ tethering that could provide a structural basis for the functional deficits of RIM1α KO synapses. Proteasome inhibition reversed these structural defects, suggesting a functional recovery confirmed by electrophysiological recordings. Altogether, our results not only point to the ubiquitin-proteasome system as an important regulator of presynaptic architecture and function but also show that the tethering machinery plays a critical role in exocytosis, converging into a structural model of synaptic vesicle priming by RIM1α.

A Zernike-moment-based non-local denoising filter for cryo-EM images

Cryo-electron microscopy (cryo-EM) plays an important role in determining the structure of proteins, viruses, and even the whole cell. It can capture dynamic structural changes of large protein complexes, which other methods such as X-ray crystallography and nuclear magnetic resonance analysis find difficult. The signal-to-noise ratio of cryo-EM images is low and the contrast is very weak, and therefore, the images are very noisy and require filtering. In this paper, a filtering method based on non-local means and Zernike moments is proposed. The method takes into account the rotational symmetry of some biological molecules to enhance the signal-to-noise ratio of cryo-EM images. The method may be useful in cryo-EM image processing such as the automatic selection of particles, orientation determination, and the building of initial models.

Geometric modeling of subcellular structures, organelles, and multiprotein complexes

Recently, the structure, function, stability, and dynamics of subcellular structures, organelles, and multiprotein complexes have emerged as a leading interest in structural biology. Geometric modeling not only provides visualizations of shapes for large biomolecular complexes but also fills the gap between structural information and theoretical modeling, and enables the understanding of function, stability, and dynamics. This paper introduces a suite of computational tools for volumetric data processing, information extraction, surface mesh rendering, geometric measurement, and curvature estimation of biomolecular complexes. Particular emphasis is given to the modeling of cryo-electron microscopy data. Lagrangian-triangle meshes are employed for the surface presentation. On the basis of this representation, algorithms are developed for surface area and surface-enclosed volume calculation, and curvature estimation. Methods for volumetric meshing have also been presented. Because the technological development in computer science and mathematics has led to multiple choices at each stage of the geometric modeling, we discuss the rationales in the design and selection of various algorithms. Analytical models are designed to test the computational accuracy and convergence of proposed algorithms. Finally, we select a set of six cryo-electron microscopy data representing typical subcellular complexes to demonstrate the efficacy of the proposed algorithms in handling biomolecular surfaces and explore their capability of geometric characterization of binding targets. This paper offers a comprehensive protocol for the geometric modeling of subcellular structures, organelles, and multiprotein complexes.