Computational methods for electron tomography

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.

Progressive alterations in polysomal architecture and activation of ribosome stalling relief factors in a mouse model of Huntington's disease

Given their highly polarized morphology and functional singularity, neurons require precise spatial and temporal control of protein synthesis. Alterations in protein translation have been implicated in the development and progression of a wide range of neurological and neurodegenerative disorders, including Huntington's disease (HD). In this study we examined the architecture of polysomes in their native brain context in striatal tissue from the zQ175 knock-in mouse model of HD. We performed 3D electron tomography of high-pressure frozen and freeze-substituted striatal tissue from HD models and corresponding controls at different ages. Electron tomography results revealed progressive remodelling towards a more compacted polysomal architecture in the mouse model, an effect that coincided with the emergence and progression of HD related symptoms. The aberrant polysomal architecture is compatible with ribosome stalling phenomena. In fact, we also detected in the zQ175 model an increase in the striatal expression of the stalling relief factor EIF5A2 and an increase in the accumulation of eIF5A1, eIF5A2 and hypusinated eIF5A1, the active form of eIF5A1. Polysomal sedimentation gradients showed differences in the relative accumulation of 40S ribosomal subunits and in polysomal distribution in striatal samples of the zQ175 model. These findings indicate that changes in the architecture of the protein synthesis machinery may underlie translational alterations associated with HD, opening new avenues for understanding the progression of the disease.

MarkerDetector: A method for robust fiducial marker detection in electron micrographs using wavelet-based template

Fiducial marker detection in electron micrographs becomes an important and challenging task with the development of large-field electron microscopy. The fiducial marker detection plays an important role in several steps during the process of electron micrographs, such as the alignment and parameter calibrations. However, limited by the conditions of low signal-to-noise ratio (SNR) in the electron micrographs, the performance of fiducial marker detection is severely affected. In this work, we propose the MarkerDetector, a novel algorithm for detecting fiducial markers in electron micrographs. The proposed MarkerDetector is built upon the following contributions: Firstly, a wavelet-based template generation algorithm is devised in MarkerDetector. By adopting a shape-based criterion, a high-quality template can be obtained. Secondly, a robust marker determination strategy is devised by utilizing statistic-based filtering, which can guarantee the correctness of the detected fiducial markers. The average running time of our algorithm is 1.67 seconds with promising accuracy, indicating its practical feasibility for applications in electron micrographs.

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.

A fast magnetic vector characterization method for quasi two-dimensional systems and heterostructures

The use of magnetic vector tomography/laminography has opened a 3D experimental window to access the magnetization at the nanoscale. These methods exploit the dependence of the magnetic contrast in transmission to recover its 3D configuration. However, hundreds of different angular projections are required leading to large measurement times. Here we present a fast method to dramatically reduce the experiment time specific for quasi two-dimensional magnetic systems. The algorithm uses the Beer-Lambert equation in the framework of X-ray transmission microscopy to obtain the 3D magnetic configuration of the sample. It has been demonstrated in permalloy microstructures, reconstructing the magnetization vector field with a reduced number of angular projections obtaining quantitative results. The throughput of the methodology is × 10-× 100 times faster than conventional magnetic vector tomography, making this characterization method of general interest for the community.

3D microscopy in industrial measurements

Quality control is essential to ensure the performance and yield of microdevices in industrial processing and manufacturing. In particular, 3D microscopy can be considered as a separate branch of microscopic instruments and plays a pivotal role in monitoring processing quality. For industrial measurements, 3D microscopy is mainly used for both the inspection of critical dimensions to ensure the design performance and detection of defects for improving the yield of microdevices. However, with the progress of advanced manufacturing technology and the increasing demand for high-performance microdevices, 3D microscopy has ushered in new challenges and development opportunities, such as breakthroughs in diffraction limit, 3D characterisation and calibrations of critical dimensions, high-precision detection and physical property determination of defects, and application of artificial intelligence. In this review, we provide a comprehensive survey about the state of the art and challenges in 3D microscopy for industrial measurements, and provide development ideas for future research. By describing techniques and methods with their advantages and limitations, we provide guidance to researchers and developers about the most suitable technique available for their intended industrial measurements.

Liver inter-organelle membrane contact sites revealed by serial section electron tomography

Inter-organelle membrane contact sites (MCSs) are defined as areas of close proximity between the membranes of two organelles (10-80nm). They have been implicated in many physiological processes such as Ca++, lipids or small molecules transfer, organelles biogenesis or dynamic and have an important role in many cellular processes such as apoptosis, autophagy, and signaling. Since the distance and the extent of these contacts are in the nanometer range, high resolution techniques are ideal for imaging these structures. It is for this reason that transmission electron microscopy (TEM) has been considered the gold standard for MCSs visualization and the first technique that described them. However, often TEM analysis is limited to 2D lacking information on the 3D association between the organelles involved in MCSs. To fully describe the complex architecture of MSCs and to unveil their role in cellular physiology a 3D analysis is required. This chapter provides a method for the analysis of MCSs using serial section electron tomography (ssET), a technique able to reconstruct in 3D at nanometer resolution cellular and subcellular structures. By applying this procedure, it was possible to elucidate the role of the contacts between Endoplasmic Reticulum (ER) and other organelles in liver lipid metabolism.

Efficient manual annotation of cryogenic electron tomograms using IMOD

Annotation highlights and segmentation isolates features in cryogenic electron tomograms to improve visualization and quantification of features (for example, their size and abundance, and spatial relationships with other features), facilitating phenotypic structural analyses of cellular tomograms. Here, we present a manual annotation protocol using the open-source software IMOD and describe segmentation of three types of common cellular features: membranes, large globules, and filaments. IMOD’s interpolation function can improve the speed of manual annotation up to an order of magnitude.

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Interpolation between sparsely annotated slices speeds up manual annotation

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Manual annotation differentiates between similar features in different contexts

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Turning annotations into segmentations shows actual data instead of representations of it

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

ScipionTomo: Towards cryo-electron tomography software integration, reproducibility, and validation

Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline.

The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project.

The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.

Statistical spatial analysis for cryo-electron tomography

Cryo-electron tomography (cryo-ET) is uniquely suited to precisely localize macromolecular complexes in situ, that is in a close-to-native state within their cellular compartments, in three-dimensions at high resolution. Point pattern analysis (PPA) allows quantitative characterization of the spatial organization of particles. However, current implementations of PPA functions are not suitable for applications to cryo-ET data because they do not consider the real, typically irregular 3D shape of cellular compartments and molecular complexes. Here, we designed and implemented first and the second-order, uni- and bivariate PPA functions in a Python package for statistical spatial analysis of particles located in three dimensional regions of arbitrary shape, such as those encountered in cellular cryo-ET imaging (PyOrg). To validate the implemented functions, we applied them to specially designed synthetic datasets. This allowed us to find the algorithmic solutions that provide the best accuracy and computational performance, and to evaluate the precision of the implemented functions. Applications to experimental data showed that despite the higher computational demand, the use of the second-order functions is advantageous to the first-order ones, because they allow characterization of the particle organization and statistical inference over a range of distance scales, as well as the comparative analysis between experimental groups comprising multiple tomograms. Altogether, PyOrg is a versatile, precise, and efficient open-source software for reliable quantitative characterization of macromolecular organization within cellular compartments imaged in situ by cryo-ET, as well as to other 3D imaging systems where real-size particles are located within regions possessing complex geometry.

TomoAlign: A novel approach to correcting sample motion and 3D CTF in CryoET

TomoAlign is a software package that integrates tools to mitigate two important resolution limiting factors in cryoET, namely the beam-induced sample motion and the contrast transfer function (CTF) of the microscope. The package is especially focused on cryoET of thick specimens where fiducial markers are required for accurate tilt-series alignment and sample motion estimation. TomoAlign models the beam-induced sample motion undergone during the tilt-series acquisition. The motion models are used to produce motion-corrected subtilt-series centered on the particles of interest. In addition, the defocus of each particle at each tilt image is determined and can be corrected, resulting in motion-corrected and CTF-corrected subtilt-series from which the subtomograms can be computed. Alternatively, the CTF information can be passed on so that CTF correction can be carried out entirely within external packages like Relion. TomoAlign serves as a versatile tool that can streamline the cryoET workflow from initial alignment of tilt-series to final subtomogram averaging during in situ structure determination.

Locating macromolecular assemblies in cells by 2D template matching with cisTEM

For a more complete understanding of molecular mechanisms, it is important to study macromolecules and their assemblies in the broader context of the cell. This context can be visualized at nanometer resolution in three dimensions (3D) using electron cryo-tomography, which requires tilt series to be recorded and computationally aligned, currently limiting throughput. Additionally, the high-resolution signal preserved in the raw tomograms is currently limited by a number of technical difficulties, leading to an increased false-positive detection rate when using 3D template matching to find molecular complexes in tomograms. We have recently described a 2D template matching approach that addresses these issues by including high-resolution signal preserved in single-tilt images. A current limitation of this approach is the high computational cost that limits throughput. We describe here a GPU-accelerated implementation of 2D template matching in the image processing software cisTEM that allows for easy scaling and improves the accessibility of this approach. We apply 2D template matching to identify ribosomes in images of frozen-hydrated Mycoplasma pneumoniae cells with high precision and sensitivity, demonstrating that this is a versatile tool for in situ visual proteomics and in situ structure determination. We benchmark the results with 3D template matching of tomograms acquired on identical sample locations and identify strengths and weaknesses of both techniques, which offer complementary information about target localization and identity.

Three-dimensional ultrastructure reconstruction of tendinous components at the bifurcation of the bovine superficial digital flexor tendon using array and STEM tomographies

Tendons transmit force from muscle to bone for joint movement. Tenocytes are a specialized type of fibroblast that produces collagen fibrils in tendons. Their cytoplasmic processes form a network surrounding collagen fibrils to define a collagen fibre. Glycosaminoglycan (GAG) chains link collagen fibrils and adhere at the D-band of the collagen fibril. In this study, we used array and scanning transmission electron microscope (STEM) tomographies to reconstruct the three-dimensional ultrastructure of tenocytes, collagen fibres, collagen fibrils and GAG chains at the bifurcation of the bovine hindlimb superficial digital flexor tendon (SDFT). Collagen fibrils comprising a collagen fibre were not aligned uniformly and had at least two running directions. Spindle-shaped tenocytes were arranged along the long axis of a plurality of collagen fibres, where two groups of collagen fibrils with oblique directions to each other exhibited an oblique overlap of the two collagen fibril layers. Collagen fibrils with different running directions were observed in separating layers of about 300 nm in thickness and had diameters of 0-200 nm. About 40% of all collagen fibrils had a peak in the range of 20-40 nm. STEM analysis of the same site where the crossing of collagen fibres was observed by transmission electron microscopy demonstrated the outline of collagen fibrils with a clear D-banding pattern at a regular interval. Collagen fibrils were reconstructed three-dimensionally using continuous images acquired by STEM tomography, which confirmed that the collagen fibrils at the crossing sites did not orientate in layers, but were woven one by one. Higher magnification observation of GAG chains attached between the crossing collagen fibrils revealed numerous GAG chains arranged either vertically or obliquely on collagen fibrils. Furthermore, GAG chains at the cross of collagen fibrils connected the closest D-bands. GAG chains are thought to be universally present between collagen fibrils of the tendon. These observations by array and STEM tomographies increase our knowledge of the anatomy in the bifurcation of the bovine hindlimb SDFT and demonstrate the utility of these new imaging technologies.

Template-free detection and classification of membrane-bound complexes in cryo-electron tomograms

With faithful sample preservation and direct imaging of fully hydrated biological material, cryo-electron tomography provides an accurate representation of molecular architecture of cells. However, detection and precise localization of macromolecular complexes within cellular environments is aggravated by the presence of many molecular species and molecular crowding. We developed a template-free image processing procedure for accurate tracing of complex networks of densities in cryo-electron tomograms, a comprehensive and automated detection of heterogeneous membrane-bound complexes and an unsupervised classification (PySeg). Applications to intact cells and isolated endoplasmic reticulum (ER) allowed us to detect and classify small protein complexes. This classification provided sufficiently homogeneous particle sets and initial references to allow subsequent de novo subtomogram averaging. Spatial distribution analysis showed that ER complexes have different localization patterns forming nanodomains. Therefore, this procedure allows a comprehensive detection and structural analysis of complexes in situ.

Segmentation by classification: A novel and reliable approach for semi-automatic selection of HIV/SIV envelope spikes

We describe a semiautomated approach to segment Env spikes from the membrane envelope of Simian Immunodeficiency Virus visualized by cryoelectron tomography of frozen-hydrated specimens. Multivariate data analysis is applied to a large set of overlapping subvolumes extracted semiautomatically from the viral envelope and does not utilize a template of the target structure. The major manual step used in the method involves determination of six points that define an ellipsoid approximating the virion shape. The approach is robust to departures of the actual virion from this starting ellipsoid. A point cage of sufficient density is generated to ensure that any spike-like protein is identified multiple times. Subsequently translational alignment of class averages to a cylindrical reference on a curved surface separates subvolumes with spikes from those without. Spike containing subvolumes identified multiple times are removed by proximity analysis. Slightly different procedures segment spikes in the equatorial and the polar regions. Once all spikes are segmented, further alignment of class averages using separately the polar and spin angles produces recognizable spike images. Our approach localized 96% of the equatorial spikes and 85% of all spikes identified manually; it identifies a significant number of additional spikes missed by manual selection. Two types of spike shapes were segmented, one with near 3-fold symmetry resembling the conventional spike, the other had a T-shape resembling the spike structure obtained when antibodies such as PG9 bind to HIV Env. The approach should be applicable to segmentation of any protein spikes extending from a cellular or virion envelope.

Measurement of local resolution in electron tomography

Resolution (global and local) is one of the most reported metrics of quality measurement in Single Particle Analysis (SPA). However, in electron tomography, the situation is different and its computation is not straightforward. Typically, resolution estimation is global and, therefore, reduces the assessment of a whole tomogram to a single number. However, it is known that tomogram quality is spatially variant. Still, up to our knowledge, a method to estimate local quality metrics in tomography is lacking. This work introduces MonoTomo, a method developed to estimate locally in a tomogram the highest reliable frequency component, expressed as a form of local resolution. The fundamentals lie in a local analysis of the density map via monogenic signals, which, in analogy to MonoRes, allows for local estimations. Results with experimental data show that the local resolution range that MonoTomo casts agrees with reported resolution values for experimental data sets, with the advantage of providing a local estimation. A range of applications of MonoTomo are suggested for further exploration.

AuTom-dualx: a toolkit for fully automatic fiducial marker-based alignment of dual-axis tilt series with simultaneous reconstruction

Motivation

Dual-axis electron tomography is an important 3 D macro-molecular structure reconstruction technology, which can reduce artifacts and suppress the effect of missing wedge. However, the fully automatic data process for dual-axis electron tomography still remains a challenge due to three difficulties: (i) how to track the mass of fiducial markers automatically; (ii) how to integrate the information from the two different tilt series; and (iii) how to cope with the inconsistency between the two different tilt series.

Results

Here we develop a toolkit for fully automatic alignment of dual-axis electron tomography, with a simultaneous reconstruction procedure. The proposed toolkit and its workflow carries out the following solutions: (i) fully automatic detection and tracking of fiducial markers under large-field datasets; (ii) automatic combination of two different tilt series and global calibration of projection parameters; and (iii) inconsistency correction based on distortion correction parameters and the consequently simultaneous reconstruction. With all of these features, the presented toolkit can achieve accurate alignment and reconstruction simultaneously and conveniently under a single global coordinate system.

Availability and implementation

The toolkit AuTom-dualx (alignment module dualxmauto and reconstruction module volrec_mltm) are accessible for general application at http://ear.ict.ac.cn, and the key source code is freely available under request.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

A joint method for marker-free alignment of tilt series in electron tomography

MOTIVATION

Electron tomography (ET) is a widely used technology for 3D macro-molecular structure reconstruction. To obtain a satisfiable tomogram reconstruction, several key processes are involved, one of which is the calibration of projection parameters of the tilt series. Although fiducial marker-based alignment for tilt series has been well studied, marker-free alignment remains a challenge, which requires identifying and tracking the identical objects (landmarks) through different projections. However, the tracking of these landmarks is usually affected by the pixel density (intensity) change caused by the geometry difference in different views. The tracked landmarks will be used to determine the projection parameters. Meanwhile, different projection parameters will also affect the localization of landmarks. Currently, there is no alignment method that takes interrelationship between the projection parameters and the landmarks.

RESULTS

Here, we propose a novel, joint method for marker-free alignment of tilt series in ET, by utilizing the information underlying the interrelationship between the projection model and the landmarks. The proposed method is the first joint solution that combines the extrinsic (track-based) alignment and the intrinsic (intensity-based) alignment, in which the localization of landmarks and projection parameters keep refining each other until convergence. This iterative approach makes our solution robust to different initial parameters and extreme geometric changes, which ensures a better reconstruction for marker-free ET. Comprehensive experimental results on three real datasets show that our new method achieved a significant improvement in alignment accuracy and reconstruction quality, compared to the state-of-the-art methods.

AVAILABILITY AND IMPLEMENTATION

The main program is available at https://github.com/icthrm/joint-marker-free-alignment.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Hybrid model for efficient prediction of poly(A) signals in human genomic DNA

Polyadenylation signals (PAS) are found in most protein-coding and some non-coding genes in eukaryotes. Their accurate recognition improves understanding gene regulation mechanisms and recognition of the 3'-end of transcribed gene regions where premature or alternate transcription ends may lead to various diseases. Although different methods and tools for in-silico prediction of genomic signals have been proposed, the correct identification of PAS in genomic DNA remains challenging due to a vast number of non-relevant hexamers identical to PAS hexamers. In this study, we developed a novel method for PAS recognition. The method is implemented in a hybrid PAS recognition model (HybPAS), which is based on deep neural networks (DNNs) and logistic regression models (LRMs). One of such models is developed for each of the 12 most frequent human PAS hexamers. DNN models appeared the best for eight PAS types (including the two most frequent PAS hexamers), while LRM appeared best for the remaining four PAS types. The new models use different combinations of signal processing-based, statistical, and sequence-based features as input. The results obtained on human genomic data show that HybPAS outperforms the well-tuned state-of-the-art Omni-PolyA models, reducing the classification error for different PAS hexamers by up to 57.35% for 10 out of 12 PAS types, with Omni-PolyA models being better for two PAS types. For the most frequent PAS types, 'AATAAA' and 'ATTAAA', HybPAS reduced the error rate by 35.14% and 34.48%, respectively. On average, HybPAS reduces the error by 30.29%. HybPAS is implemented partly in Python and in MATLAB available at https://github.com/EMANG-KAUST/PolyA_Prediction_LRM_DNN.

Electron Tomography Reveals the Droplet Covered Surface Structure of Nanowires Grown by Aerotaxy

For the purpose of functionalizing III-V semiconductor nanowires using n-doping, Sn-doped GaAs zincblende nanowires are produced, using the growth method of Aerotaxy. The growth conditions used are such that Ga droplets, formed on the nanowire surface, increase in number and concentrations when the Sn-precursor concentration is increased. Droplet-covered wires grown with varying Sn concentrations are analyzed by transmission electron microscopy and electron tomography, which together establish the positioning of the droplets to be preferentially on {-111}B facets. These facets have the same polarity as the main wire growth direction, [-1-1-1]B. This means that the generated Ga particles can form nucleation sites for possible nanowire branch growth. The concept of azimuthal mapping is introduced as a useful tool for nanowire surface visualization and evaluation. It is demonstrated here that electron tomography is useful in revealing both the surface and internal morphologies of the nanowires, opening up for applications in the analysis of more structurally complicated systems like radially asymmetrical nanowires. The analysis also gives a further understanding of the limits of the dopants which can be used for Aerotaxy nanowires.

Exemplar-based inpainting as a solution to the missing wedge problem in electron tomography

A new method for dealing with incomplete projection sets in electron tomography is proposed. The approach is inspired by exemplar-based inpainting techniques in image processing and heuristically generates data for missing projection directions. The method has been extended to work on three dimensional data. In general, electron tomography reconstructions suffer from elongation artifacts along the beam direction. These artifacts can be seen in the corresponding Fourier domain as a missing wedge. The new method synthetically generates projections for these missing directions with the help of a dictionary based approach that is able to convey both structure and texture at the same time. It constitutes a preprocessing step that can be combined with any tomographic reconstruction algorithm. The new algorithm was applied to phantom data, to a real electron tomography data set taken from a catalyst, as well as to a real dataset containing solely colloidal gold particles. Visually, the synthetic projections, reconstructions, and corresponding Fourier power spectra showed a decrease of the typical missing wedge artifacts. Quantitatively, the inpainting method is capable to reduce missing wedge artifacts and improves tomogram quality with respect to full width half maximum measurements.

Cryo-tomography tilt-series alignment with consideration of the beam-induced sample motion

Recent evidence suggests that the beam-induced motion of the sample during tilt-series acquisition is a major resolution-limiting factor in electron cryo-tomography (cryoET). It causes suboptimal tilt-series alignment and thus deterioration of the reconstruction quality. Here we present a novel approach to tilt-series alignment and tomographic reconstruction that considers the beam-induced sample motion through the tilt-series. It extends the standard fiducial-based alignment approach in cryoET by introducing quadratic polynomials to model the sample motion. The model can be used during reconstruction to yield a motion-compensated tomogram. We evaluated our method on various datasets with different sample sizes. The results demonstrate that our method could be a useful tool to improve the quality of tomograms and the resolution in cryoET.

Progress towards a methodology for high throughput 3D reconstruction of soot nanoparticles via electron tomography

The aim of this work is to make progress towards the development of 3D reconstruction as a legitimate alternative to traditional 2D characterization of soot. Time constraints are the greatest opposition to its implementation, as currently reconstruction of a single soot particle takes around 5-6 h to complete. As such, the accuracy and detail gains are currently insufficient to challenge 2D characterization of a representative sample (e.g. 200 particles). This work is a consideration of the optimization of the steps included within the computational reconstruction and manual segmentation of soot particles. Our optimal process reduced the time required by over 70% in comparison to a typical procedure, whilst producing models with no appreciable decrease in quality.

A parameter for the assessment of the segmentation of TEM tomography reconstructed volumes based on mutual information

A method is proposed and verified for selecting the optimum segmentation of a TEM reconstruction among the results of several segmentation algorithms. The selection criterion is the accuracy of the segmentation. To do this selection, a parameter for the comparison of the accuracies of the different segmentations has been defined. It consists of the mutual information value between the acquired TEM images of the sample and the Radon projections of the segmented volumes. In this work, it has been proved that this new mutual information parameter and the Jaccard coefficient between the segmented volume and the ideal one are correlated. In addition, the results of the new parameter are compared to the results obtained from another validated method to select the optimum segmentation.

AuTom: A novel automatic platform for electron tomography reconstruction

We have developed a software package towards automatic electron tomography (ET): Automatic Tomography (AuTom). The presented package has the following characteristics: accurate alignment modules for marker-free datasets containing substantial biological structures; fully automatic alignment modules for datasets with fiducial markers; wide coverage of reconstruction methods including a new iterative method based on the compressed-sensing theory that suppresses the "missing wedge" effect; and multi-platform acceleration solutions that support faster iterative algebraic reconstruction. AuTom aims to achieve fully automatic alignment and reconstruction for electron tomography and has already been successful for a variety of datasets. AuTom also offers user-friendly interface and auxiliary designs for file management and workflow management, in which fiducial marker-based datasets and marker-free datasets are addressed with totally different subprocesses. With all of these features, AuTom can serve as a convenient and effective tool for processing in electron tomography.

The advent of structural biology in situ by single particle cryo-electron tomography

Single particle tomography (SPT), also known as subtomogram averaging, is a powerful technique uniquely poised to address questions in structural biology that are not amenable to more traditional approaches like X-ray crystallography, nuclear magnetic resonance, and conventional cryoEM single particle analysis. Owing to its potential for in situ structural biology at subnanometer resolution, SPT has been gaining enormous momentum in the last five years and is becoming a prominent, widely used technique. This method can be applied to unambiguously determine the structures of macromolecular complexes that exhibit compositional and conformational heterogeneity, both in vitro and in situ. Here we review the development of SPT, highlighting its applications and identifying areas of ongoing development.

Graph-based sinogram denoising for tomographic reconstructions

Limited data and low-dose constraints are common problems in a variety of tomographic reconstruction paradigms, leading to noisy and incomplete data. Over the past few years, sinogram denoising has become an essential preprocessing step for low-dose Computed Tomographic (CT) reconstructions. We propose a novel sinogram denoising algorithm inspired by signal processing on graphs. Graph-based methods often perform better than standard filtering operations since they can exploit the signal structure. This makes the sinogram an ideal candidate for graph based denoising since it generally has a piecewise smooth structure. We test our method with a variety of phantoms using different reconstruction methods. Our numerical study shows that the proposed algorithm improves the performance of analytical filtered back-projection (FBP) and iterative methods such as ART (Kaczmarz), and SIRT (Cimmino). We observed that graph denoised sinograms always minimize the error measure and improve the accuracy of the solution, compared to regular reconstructions.

FIJI Macro 3D ART VeSElecT: 3D Automated Reconstruction Tool for Vesicle Structures of Electron Tomograms

Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation. Both automatic and semi-automatic modes are explained including a tutorial.

A methodology for finding the optimal iteration number of the SIRT algorithm for quantitative Electron Tomography

The SIRT (Simultaneous Iterative Reconstruction Technique) algorithm is commonly used in Electron Tomography to calculate the original volume of the sample from noisy images, but the results provided by this iterative procedure are strongly dependent on the specific implementation of the algorithm, as well as on the number of iterations employed for the reconstruction. In this work, a methodology for selecting the iteration number of the SIRT reconstruction that provides the most accurate segmentation is proposed. The methodology is based on the statistical analysis of the intensity profiles at the edge of the objects in the reconstructed volume. A phantom which resembles a a carbon black aggregate has been created to validate the methodology and the SIRT implementations of two free software packages (TOMOJ and TOMO3D) have been used.

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.

Cryo-Electron Tomography: Can it Reveal the Molecular Sociology of Cells in Atomic Detail?

Traditionally, macromolecular structure determination is performed ex situ, that is, with purified materials. But, there are strong incentives to develop approaches to study them in situ in their native functional context. In recent years, cryo-electron tomography (cryo-ET) has emerged as a powerful method for visualizing the molecular organization of unperturbed cellular landscapes with the potential to attain near-atomic resolution. Here, we review recent work on several macromolecular assemblies, demonstrating the power of in situ studies. We also highlight technical challenges and discuss ways to meet them.

3D electron tomography of brain tissue unveils distinct Golgi structures that sequester cytoplasmic contents in neurons

Macroautophagy is morphologically characterized by autophagosome formation. Autophagosomes are double-membraned vesicles that sequester cytoplasmic components for further degradation in the lysosome. Basal autophagy is paramount for intracellular quality control in post-mitotic cells but, surprisingly, the number of autophagosomes in post-mitotic neurons is very low, suggesting that alternative degradative structures could exist in neurons. To explore this possibility, we have examined neuronal subcellular architecture by performing three-dimensional (3D) electron tomography analysis of mouse brain tissue that had been preserved through high-pressure freezing. Here, we report that sequestration of neuronal cytoplasmic contents occurs at the Golgi complex in distinct and dynamic structures that coexist with autophagosomes in the brain. These structures are composed of several concentric double-membraned layers that appear to be formed simultaneously by the direct bending and sealing of discrete Golgi stacks. These structures are labelled for proteolytic enzymes, and lysosomes and late endosomes are found in contact with them, leading to the possibility that the sequestered material could be degraded inside them. Our findings highlight the key role that 3D electron tomography, together with tissue rapid-freezing techniques, will have in gaining new knowledge about subcellular architecture.

Electron tomography of rabbit cardiomyocyte three-dimensional ultrastructure

The field of cardiovascular research has benefitted from rapid developments in imaging technology over the last few decades. Accordingly, an ever growing number of large, multidimensional data sets have begun to appear, often challenging existing pre-conceptions about structure and function of biological systems. For tissue and cell structure imaging, the move from 2D section-based microscopy to true 3D data collection has been a major driver of new insight. In the sub-cellular domain, electron tomography is a powerful technique for exploration of cellular structures in 3D with unparalleled fidelity at nanometer resolution.

Electron tomography is particularly advantageous for studying highly compartmentalised cells such as cardiomyocytes, where elaborate sub-cellular structures play crucial roles in electrophysiology and mechanics. Although the anatomy of specific ultra-structures, such as dyadic couplons, has been extensively explored using 2D electron microscopy of thin sections, we still lack accurate, quantitative knowledge of true individual shape, volume and surface area of sub-cellular domains, as well as their 3D spatial interrelations; let alone of how these are reshaped during the cycle of contraction and relaxation. Here we discuss and illustrate the utility of ET for identification, visualisation, and analysis of 3D cardiomyocyte ultrastructures such as the T-tubular system, sarcoplasmic reticulum, mitochondria and microtubules.

Alignment algorithms and per-particle CTF correction for single particle cryo-electron tomography

Single particle cryo-electron tomography (cryoSPT) extracts features from cryo-electron tomograms, followed by 3D classification, alignment and averaging to generate improved 3D density maps of such features. Robust methods to correct for the contrast transfer function (CTF) of the electron microscope are necessary for cryoSPT to reach its resolution potential. Many factors can make CTF correction for cryoSPT challenging, such as lack of eucentricity of the specimen stage, inherent low dose per image, specimen charging, beam-induced specimen motions, and defocus gradients resulting both from specimen tilting and from unpredictable ice thickness variations. Current CTF correction methods for cryoET make at least one of the following assumptions: that the defocus at the center of the image is the same across the images of a tiltseries, that the particles all lie at the same Z-height in the embedding ice, and/or that the specimen, the cryo-electron microscopy (cryoEM) grid and/or the carbon support are flat. These experimental conditions are not always met. We have developed a CTF correction algorithm for cryoSPT without making any of the aforementioned assumptions. We also introduce speed and accuracy improvements and a higher degree of automation to the subtomogram averaging algorithms available in EMAN2. Using motion-corrected images of isolated virus particles as a benchmark specimen, recorded with a DE20 direct detection camera, we show that our CTF correction and subtomogram alignment routines can yield subtomogram averages close to 4/5 Nyquist frequency of the detector under our experimental conditions.

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.

Automated batch fiducial-less tilt-series alignment in Appion using Protomo

The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliable correlation-based tilt-series alignment. Here we present a set of automated, correlation-based tilt-series alignment, contrast transfer function (CTF) correction, and reconstruction workflows for use in conjunction with the Appion/Leginon package that are primarily targeted at automating structure determination with cryogenic electron microscopy.

Matched Backprojection Operator for Combined Scanning Transmission Electron Microscopy Tilt- and Focal Series

Combined tilt- and focal series scanning transmission electron microscopy is a recently developed method to obtain nanoscale three-dimensional (3D) information of thin specimens. In this study, we formulate the forward projection in this acquisition scheme as a linear operator and prove that it is a generalization of the Ray transform for parallel illumination. We analytically derive the corresponding backprojection operator as the adjoint of the forward projection. We further demonstrate that the matched backprojection operator drastically improves the convergence rate of iterative 3D reconstruction compared to the case where a backprojection based on heuristic weighting is used. In addition, we show that the 3D reconstruction is of better quality.

Progressive Stochastic Reconstruction Technique (PSRT) for cryo electron tomography

Cryo Electron Tomography (cryoET) plays an essential role in Structural Biology, as it is the only technique that allows to study the structure of large macromolecular complexes in their close to native environment in situ. The reconstruction methods currently in use, such as Weighted Back Projection (WBP) or Simultaneous Iterative Reconstruction Technique (SIRT), deliver noisy and low-contrast reconstructions, which complicates the application of high-resolution protocols, such as Subtomogram Averaging (SA). We propose a Progressive Stochastic Reconstruction Technique (PSRT) - a novel iterative approach to tomographic reconstruction in cryoET based on Monte Carlo random walks guided by Metropolis-Hastings sampling strategy. We design a progressive reconstruction scheme to suit the conditions present in cryoET and apply it successfully to reconstructions of macromolecular complexes from both synthetic and experimental datasets. We show how to integrate PSRT into SA, where it provides an elegant solution to the region-of-interest problem and delivers high-contrast reconstructions that significantly improve template-based localization without any loss of high-resolution structural information. Furthermore, the locality of SA is exploited to design an importance sampling scheme which significantly speeds up the otherwise slow Monte Carlo approach. Finally, we design a new memory efficient solution for the specimen-level interior problem of cryoET, removing all associated artifacts.

Tomo3D 2.0--exploitation of advanced vector extensions (AVX) for 3D reconstruction

Tomo3D is a program for fast tomographic reconstruction on multicore computers. Its high speed stems from code optimization, vectorization with Streaming SIMD Extensions (SSE), multithreading and optimization of disk access. Recently, Advanced Vector eXtensions (AVX) have been introduced in the x86 processor architecture. Compared to SSE, AVX double the number of simultaneous operations, thus pointing to a potential twofold gain in speed. However, in practice, achieving this potential is extremely difficult. Here, we provide a technical description and an assessment of the optimizations included in Tomo3D to take advantage of AVX instructions. Tomo3D 2.0 allows huge reconstructions to be calculated in standard computers in a matter of minutes. Thus, it will be a valuable tool for electron tomography studies with increasing resolution needs.

Averaging of viral envelope glycoprotein spikes from electron cryotomography reconstructions using Jsubtomo

Enveloped viruses utilize membrane glycoproteins on their surface to mediate entry into host cells. Three-dimensional structural analysis of these glycoprotein ‘spikes’ is often technically challenging but important for understanding viral pathogenesis and in drug design. Here, a protocol is presented for viral spike structure determination through computational averaging of electron cryo-tomography data. Electron cryo-tomography is a technique in electron microscopy used to derive three-dimensional tomographic volume reconstructions, or tomograms, of pleomorphic biological specimens such as membrane viruses in a near-native, frozen-hydrated state. These tomograms reveal structures of interest in three dimensions, albeit at low resolution. Computational averaging of sub-volumes, or sub-tomograms, is necessary to obtain higher resolution detail of repeating structural motifs, such as viral glycoprotein spikes. A detailed computational approach for aligning and averaging sub-tomograms using the Jsubtomo software package is outlined. This approach enables visualization of the structure of viral glycoprotein spikes to a resolution in the range of 20-40 Å and study of the study of higher order spike-to-spike interactions on the virion membrane. Typical results are presented for Bunyamwera virus, an enveloped virus from the family Bunyaviridae. This family is a structurally diverse group of pathogens posing a threat to human and animal health.

Three-Dimensional Imaging of Viral Infections

Three-dimensional (3D) imaging technologies are beginning to have significant impact in the field of virology, as they are helping us understand how viruses take control of cells. In this article we review several methodologies for 3D imaging of cells and show how these technologies are contributing to the study of viral infections and the characterization of specialized structures formed in virus-infected cells. We include 3D reconstruction by transmission electron microscopy (TEM) using serial sections, electron tomography, and focused ion beam scanning electron microscopy (FIB-SEM). We summarize from these methods selected contributions to our understanding of viral entry, replication, morphogenesis, egress and propagation, and changes in the spatial architecture of virus-infected cells. In combination with live-cell imaging, correlative microscopy, and new techniques for molecular mapping in situ, the availability of these methods for 3D imaging is expected to provide deeper insights into understanding the structural and dynamic aspects of viral infection.

Molecular architecture of the bacterial flagellar motor in cells

The flagellum is one of the most sophisticated self-assembling molecular machines in bacteria. Powered by the proton-motive force, the flagellum rapidly rotates in either a clockwise or counterclockwise direction, which ultimately controls bacterial motility and behavior. Escherichia coli and Salmonella enterica have served as important model systems for extensive genetic, biochemical, and structural analysis of the flagellum, providing unparalleled insights into its structure, function, and gene regulation. Despite these advances, our understanding of flagellar assembly and rotational mechanisms remains incomplete, in part because of the limited structural information available regarding the intact rotor–stator complex and secretion apparatus. Cryo-electron tomography (cryo-ET) has become a valuable imaging technique capable of visualizing the intact flagellar motor in cells at molecular resolution. Because the resolution that can be achieved by cryo-ET with large bacteria (such as E. coli and S. enterica) is limited, analysis of small-diameter bacteria (including Borrelia burgdorferi and Campylobacter jejuni) can provide additional insights into the in situ structure of the flagellar motor and other cellular components. This review is focused on the application of cryo-ET, in combination with genetic and biophysical approaches, to the study of flagellar structures and its potential for improving the understanding of rotor–stator interactions, the rotational switching mechanism, and the secretion and assembly of flagellar components.