Computational exploration of structural information from cryo-electron tomograms

Computational Methods Toward Unbiased Pattern Mining and Structure Determination in Cryo-Electron Tomography Data

Cryo-electron tomography can uniquely probe the native cellular environment for macromolecular structures. Tomograms feature complex data with densities of diverse, densely crowded macromolecular complexes, low signal-to-noise, and artifacts such as the missing wedge effect. Post-processing of this data generally involves isolating regions or particles of interest from tomograms, organizing them into related groups, and rendering final structures through subtomogram averaging. Template-matching and reference-based structure determination are popular analysis methods but are vulnerable to biases and can often require significant user input. Most importantly, these approaches cannot identify novel complexes that reside within the imaged cellular environment. To reliably extract and resolve structures of interest, efficient and unbiased approaches are therefore of great value. This review highlights notable computational software and discusses how they contribute to making automated structural pattern discovery a possibility. Perspectives emphasizing the importance of features for user-friendliness and accessibility are also presented.

ArtiaX: An electron tomography toolbox for the interactive handling of sub-tomograms in UCSF ChimeraX

Cryo-electron tomography analysis involves the selection of macromolecular complexes to be used for subsequent sub-tomogram averaging and structure determination. Here, we describe a plugin developed for UCSF ChimeraX that allows for the display, selection, and editing of particles within tomograms. Positions and orientations of selected particles can be manually set, modified and inspected in real time, both on screen and in virtual reality, and exported to various file formats. The plugin allows for the parallel visualization of particles stored in several meta data lists, in the context of any three-dimensional image that can be opened with UCSF ChimeraX. The particles are rendered in user-defined colors or using colormaps, such that individual classes or groups of particles, cross-correlation coefficients, or other types of information can be highlighted to the user. The implemented functions are fast, reliable, and intuitive, exploring the broad range of features in UCSF ChimeraX. They allow for a fluent human-machine interaction, which enables an effective understanding of the sub-tomogram processing pipeline, even for non-specialist users.

Neuronal SNARE complex assembly guided by Munc18-1 and Munc13-1

Neurotransmitter release by Ca²⁺ -triggered synaptic vesicle exocytosis is essential for information transmission in the nervous system. The soluble N-ethylmaleimide sensitive factor attachment protein receptors (SNAREs) syntaxin-1, SNAP-25, and synaptobrevin-2 form the SNARE complex to bring synaptic vesicles and the plasma membranes together and to catalyze membrane fusion. Munc18-1 and Munc13-1 regulate synaptic vesicle priming via orchestrating neuronal SNARE complex assembly. In this review, we summarize recent advances toward the functions and molecular mechanisms of Munc18-1 and Munc13-1 in guiding neuronal SNARE complex assembly, and discuss the functional similarities and differences between Munc18-1 and Munc13-1 in neurons and their homologs in other intracellular membrane trafficking systems.

Functional genomics, genetic risk profiling and cell phenotypes in neurodegenerative disease

Human genetics provides unbiased insights into the causes of human disease, which can be used to create a foundation for effective ways to more accurately diagnose patients, stratify patients for more successful clinical trials, discover and develop new therapies, and ultimately help patients choose the safest and most promising therapeutic option based on their risk profile. But the process for translating basic observations from human genetics studies into pathogenic disease mechanisms and treatments is laborious and complex, and this challenge has particularly slowed the development of interventions for neurodegenerative disease. In this review, we discuss the many steps in the process, the important considerations at each stage, and some of the latest tools and technologies that are available to help investigators translate insights from human genetics into diagnostic and therapeutic strategies that will lead to the sort of advances in clinical care that make a difference for patients.

Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench

Segmentation is the process of isolating specific regions or objects within an imaged volume, so that further study can be undertaken on these areas of interest. When considering the analysis of complex biological systems, the segmentation of three-dimensional image data is a time consuming and labor intensive step. With the increased availability of many imaging modalities and with automated data collection schemes, this poses an increased challenge for the modern experimental biologist to move from data to knowledge. This publication describes the use of SuRVoS Workbench, a program designed to address these issues by providing methods to semi-automatically segment complex biological volumetric data. Three datasets of differing magnification and imaging modalities are presented here, each highlighting different strategies of segmenting with SuRVoS. Phase contrast X-ray tomography (microCT) of the fruiting body of a plant is used to demonstrate segmentation using model training, cryo electron tomography (cryoET) of human platelets is used to demonstrate segmentation using super- and megavoxels, and cryo soft X-ray tomography (cryoSXT) of a mammalian cell line is used to demonstrate the label splitting tools. Strategies and parameters for each datatype are also presented. By blending a selection of semi-automatic processes into a single interactive tool, SuRVoS provides several benefits. Overall time to segment volumetric data is reduced by a factor of five when compared to manual segmentation, a mainstay in many image processing fields. This is a significant savings when full manual segmentation can take weeks of effort. Additionally, subjectivity is addressed through the use of computationally identified boundaries, and splitting complex collections of objects by their calculated properties rather than on a case-by-case basis.

SuRVoS: Super-Region Volume Segmentation workbench

Segmentation of biological volumes is a crucial step needed to fully analyse their scientific content. Not having access to convenient tools with which to segment or annotate the data means many biological volumes remain under-utilised. Automatic segmentation of biological volumes is still a very challenging research field, and current methods usually require a large amount of manually-produced training data to deliver a high-quality segmentation. However, the complex appearance of cellular features and the high variance from one sample to another, along with the time-consuming work of manually labelling complete volumes, makes the required training data very scarce or non-existent. Thus, fully automatic approaches are often infeasible for many practical applications. With the aim of unifying the segmentation power of automatic approaches with the user expertise and ability to manually annotate biological samples, we present a new workbench named SuRVoS (Super-Region Volume Segmentation). Within this software, a volume to be segmented is first partitioned into hierarchical segmentation layers (named Super-Regions) and is then interactively segmented with the user's knowledge input in the form of training annotations. SuRVoS first learns from and then extends user inputs to the rest of the volume, while using Super-Regions for quicker and easier segmentation than when using a voxel grid. These benefits are especially noticeable on noisy, low-dose, biological datasets.

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.

Quantifying Variability of Manual Annotation in Cryo-Electron Tomograms

Although acknowledged to be variable and subjective, manual annotation of cryo-electron tomography data is commonly used to answer structural questions and to create a "ground truth" for evaluation of automated segmentation algorithms. Validation of such annotation is lacking, but is critical for understanding the reproducibility of manual annotations. Here, we used voxel-based similarity scores for a variety of specimens, ranging in complexity and segmented by several annotators, to quantify the variation among their annotations. In addition, we have identified procedures for merging annotations to reduce variability, thereby increasing the reliability of manual annotation. Based on our analyses, we find that it is necessary to combine multiple manual annotations to increase the confidence level for answering structural questions. We also make recommendations to guide algorithm development for automated annotation of features of interest.

Efficient Extraction of Macromolecular Complexes from Electron Tomograms Based on Reduced Representation Templates

Electron tomography is the most widely applicable method for obtaining 3D information by electron microscopy. In the field of biology it has been realized that electron tomography is capable of providing a complete, molecular resolution three-dimensional mapping of entire proteoms. However, to realize this goal, information needs to be extracted efficiently from these tomograms. Owing to extremely low signal-to-noise ratios, this task is mostly carried out manually. Standard template matching approaches tend to generate large amounts of false positives. We developed an alternative method for feature extraction in biological electron tomography based on reduced representation templates, approximating the search model by a small number of anchor points used to calculate the scoring function. Using this approach we see a reduction of about 50% false positives with matched-filter approaches to below 5%. At the same time, false negatives stay below 5%, thus essentially matching the performance one would expect from human operators.

Conformational States of macromolecular assemblies explored by integrative structure calculation

A detailed description of macromolecular assemblies in multiple conformational states can be very valuable for understanding cellular processes. At present, structural determination of most assemblies in different biologically relevant conformations cannot be achieved by a single technique and thus requires an integrative approach that combines information from multiple sources. Different techniques require different computational methods to allow efficient and accurate data processing and analysis. Here, we summarize the latest advances and future challenges in computational methods that help the interpretation of data from two techniques—mass spectrometry and three-dimensional cryo-electron microscopy (with focus on alignment and classification of heterogeneous subtomograms from cryo-electron tomography). We evaluate how new developments in these two broad fields will lead to further integration with atomic structures to broaden our picture of the dynamic behavior of assemblies in their native environment.

Structural analysis of supramolecular assemblies by cryo-electron tomography

Structural analysis of macromolecular assemblies in their physiological environment is a challenging task that is instrumental in answering fundamental questions in cellular and molecular structural biology. The continuous development of computational and analytical tools for cryo-electron tomography (cryo-ET) enables the study of these assemblies at a resolution of a few nanometers. Through the implementation of thinning procedures, cryo-ET can now be applied to the reconstruction of macromolecular structures located inside thick regions of vitrified cells and tissues, thus becoming a central tool for structural determinations in various biological disciplines. Here, we focus on the successful in situ applications of cryo-ET to reveal structures of macromolecular complexes within eukaryotic cells.

Visualizing the bacterial cell surface: an overview

The ultrastructure of bacteria is only accessible by electron microscopy. Our insights into the architecture of cells and cellular compartments such as the envelope and appendages is thus dependent on the progress of preparative and imaging techniques in electron microscopy. Here, I give a short overview of the development and characteristics of methods applied for imaging (components of) the bacterial surface and refer to key investigations and exemplary results. In the beginning of electron microscopy, fixation of biological material and staining for contrast enhancement were the standard techniques. The results from freeze-etching, metal shadowing and from ultrathin-sections of plastic-embedded material shaped our view of the cellular organization of bacteria. The introduction of cryo-preparations, keeping samples in their natural environment, and three-dimensional (3D) electron microscopy of isolated protein complexes and intact cells opened the door to a new dimension and has provided insight into the native structure of macromolecules and the in situ organization of cells at molecular resolution. Cryo-electron microscopy of single particles, together with other methods of structure determination, and cellular cryo-electron tomography will provide us with a quasi-atomic model of the bacterial cell surface in the years to come.

Developing a denoising filter for electron microscopy and tomography data in the cloud

The low radiation conditions and the predominantly phase-object image formation of cryo-electron microscopy (cryo-EM) result in extremely high noise levels and low contrast in the recorded micrographs. The process of single particle or tomographic 3D reconstruction does not completely eliminate this noise and is even capable of introducing new sources of noise during alignment or when correcting for instrument parameters. The recently developed Digital Paths Supervised Variance (DPSV) denoising filter uses local variance information to control regional noise in a robust and adaptive manner. The performance of the DPSV filter was evaluated in this review qualitatively and quantitatively using simulated and experimental data from cryo-EM and tomography in two and three dimensions. We also assessed the benefit of filtering experimental reconstructions for visualization purposes and for enhancing the accuracy of feature detection. The DPSV filter eliminates high-frequency noise artifacts (density gaps), which would normally preclude the accurate segmentation of tomography reconstructions or the detection of alpha-helices in single-particle reconstructions. This collaborative software development project was carried out entirely by virtual interactions among the authors using publicly available development and file sharing tools.

Automated tracing of filaments in 3D electron tomography reconstructions using Sculptor and Situs

The molecular graphics program Sculptor and the command-line suite Situs are software packages for the integration of biophysical data across spatial resolution scales. Herein, we provide an overview of recently developed tools relevant to cryo-electron tomography (cryo-ET), with an emphasis on functionality supported by Situs 2.7.1 and Sculptor 2.1.1. We describe a work flow for automatically segmenting filaments in cryo-ET maps including denoising, local normalization, feature detection, and tracing. Tomograms of cellular actin networks exhibit both cross-linked and bundled filament densities. Such filamentous regions in cryo-ET data sets can then be segmented using a stochastic template-based search, VolTrac. The approach combines a genetic algorithm and a bidirectional expansion with a tabu search strategy to localize and characterize filamentous regions. The automated filament segmentation by VolTrac compares well to a manual one performed by expert users, and it allows an efficient and reproducible analysis of large data sets. The software is free, open source, and can be used on Linux, Macintosh or Windows computers.

High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching

Cryo-electron tomography allows the visualization of macromolecular complexes in their cellular environments in close-to-live conditions. The nominal resolution of subtomograms can be significantly increased when individual subtomograms of the same kind are aligned and averaged. A vital step for such a procedure are algorithms that speedup subtomogram alignment and improve its accuracy to allow reference-free subtomogram classifications. Such methods will facilitate automation of tomography analysis and overall high throughput in the data processing. Building on previous work, here we propose a fast rotational alignment method that uses the Fourier equivalent form of a popular constrained correlation measure that considers missing wedge corrections and density variances in the subtomograms. The fast rotational search is based on 3D volumetric matching, which improves the rotational alignment accuracy in particular for highly distorted subtomograms with low SNR and tilt angle ranges in comparison to fast rotational matching of projected 2D spherical images. We further integrate our fast rotational alignment method in a reference-free iterative subtomogram classification scheme, and propose a local feature enhancement strategy in the classification process. As a proof of principle, we can demonstrate that the automatic method can successfully classify a large number of experimental subtomograms without the need of a reference structure.

PyTom: a python-based toolbox for localization of macromolecules in cryo-electron tomograms and subtomogram analysis

Cryo-electron tomography (CET) is a three-dimensional imaging technique for structural studies of macromolecules under close-to-native conditions. In-depth analysis of macromolecule populations depicted in tomograms requires identification of subtomograms corresponding to putative particles, averaging of subtomograms to enhance their signal, and classification to capture the structural variations among them. Here, we introduce the open-source platform PyTom that unifies standard tomogram processing steps in a python toolbox. For subtomogram averaging, we implemented an adaptive adjustment of scoring and sampling that clearly improves the resolution of averages compared to static strategies. Furthermore, we present a novel stochastic classification method that yields significantly more accurate classification results than two deterministic approaches in simulations. We demonstrate that the PyTom workflow yields faithful results for alignment and classification of simulated and experimental subtomograms of ribosomes and GroEL(14)/GroEL(14)GroES(7), respectively, as well as for the analysis of ribosomal 60S subunits in yeast cell lysate. PyTom enables parallelized processing of large numbers of tomograms, but also provides a convenient, sustainable environment for algorithmic development.

Bacterial protein interaction networks: puzzle stones from solved complex structures add to a clearer picture

Global scale studies of protein-protein interaction (PPI) networks have considerably expanded our view of how proteins act in the cell. In particular, bacterial "interactome" surveys have revealed that proteins can sometimes interact with a large number of protein partners and connect different cellular processes. More targeted, pathway-orientated PPI studies have also helped to propose functions for unknown proteins based on the "guilty by association" principle. However, given the immense repertoire of PPIs generated and the variability of PPI networks, more studies are required to understand the role(s) of these interactions in the cell. With the availability of bioinformatic analysis tools, transcriptomics and co-expression experiments for a given interaction, interactomes are being deciphered. More recently, functional and structural studies have been derived from these PPI networks. In this review, we will give a number of examples of how combining functional and structural studies into PPI networks has contributed to understanding the functions of some of these interactions. We discuss how interactomes now represent a unique opportunity to determine the structures of bacterial protein complexes on a large scale by the integration of multiple technologies.

Methods for segmentation and interpretation of electron tomographic reconstructions

Electron tomography has become a powerful tool for revealing the molecular architecture of biological cells and tissues. In principle, electron tomography can provide high-resolution mapping of entire proteomes. The achievable resolution (3-8 nm) is capable of bridging the gap between live-cell imaging and atomic resolution structures. However, the relevant information is not readily accessible from the data and needs to be identified, extracted, and processed before it can be used. Because electron tomography imaging and image acquisition technologies have enjoyed major advances in the last few years and continue to increase data throughput, the need for approaches that allow automatic and objective interpretation of electron tomograms becomes more and more urgent. This chapter provides an overview of the state of the art in this field and attempts to identify the major bottlenecks that prevent approaches for interpreting electron tomography data to develop their full potential.

The actin cytoskeleton in whole mount preparations and sections

In non-muscle cells, the actin cytoskeleton plays a key role by providing a scaffold contributing to the definition of cell shape, force for driving cell motility, cytokinesis, endocytosis, and propulsion of pathogens, as well as tracks for intracellular transport. A thorough understanding of these processes requires insight into the spatial and temporal organisation of actin filaments into diverse higher-order structures, such as networks, parallel bundles, and contractile arrays. Transmission and scanning electron microscopy can be used to visualise the actin cytoskeleton, but due to the delicate nature of actin filaments, they are easily affected by standard preparation protocols, yielding variable degrees of ultrastructural preservation. In this chapter, we describe different conventional and cryo-approaches to visualise the actin cytoskeleton using transmission electron microscopy and discuss their specific advantages and drawbacks. In the first part, we present three different whole mount techniques, which allow visualisation of actin in the peripheral, thinly spread parts of cells grown in monolayers. In the second part, we describe specific issues concerning the visualisation of actin in thin sections. Techniques for three-dimensional visualisation of actin, protein localisation, and correlative light and electron microscopy are also included.

Electron tomography in life science

Electron tomography (ET) is a three-dimensional technique suitable to study pleomorphic biological structures with nanometer resolution. This makes the methodology remarkably versatile, allowing the exploration of a large range of biological specimens, both in an isolated state and in their cellular context. The application of ET has undergone an exponential growth over the last decade, enabled by seminal technological advances in methods and instrumentation, and is starting to make a significant impact on our understanding of the cellular world. While the attained results are already remarkable, ET remains a young technique with ample potential to be exploited. Current developments towards large-scale automation, higher resolution, macromolecular labeling and integration with other imaging techniques hold promise for a near future in which ET will extend its role as a pivotal tool in structural and cell biology.

Electron cryotomography: a new view into microbial ultrastructure

Electron cryotomography (ECT) is an emerging technology that allows thin samples such as small bacterial cells to be imaged in 3D in a nearly native state to 'molecular' (approximately 4nm) resolution. As such, ECT is beginning to deliver long-awaited insight into the positions and structures of cytoskeletal filaments, cell wall elements, motility machines, chemoreceptor arrays, internal compartments, and other ultrastructures. Here we briefly explain ECT, review its recent contributions to microbiology, and conclude with a discussion of future prospects.

Evaluation of denoising algorithms for biological electron tomography

Tomograms of biological specimens derived using transmission electron microscopy can be intrinsically noisy due to the use of low electron doses, the presence of a "missing wedge" in most data collection schemes, and inaccuracies arising during 3D volume reconstruction. Before tomograms can be interpreted reliably, for example, by 3D segmentation, it is essential that the data be suitably denoised using procedures that can be individually optimized for specific data sets. Here, we implement a systematic procedure to compare various nonlinear denoising techniques on tomograms recorded at room temperature and at cryogenic temperatures, and establish quantitative criteria to select a denoising approach that is most relevant for a given tomogram. We demonstrate that using an appropriate denoising algorithm facilitates robust segmentation of tomograms of HIV-infected macrophages and Bdellovibrio bacteria obtained from specimens at room and cryogenic temperatures, respectively. We validate this strategy of automated segmentation of optimally denoised tomograms by comparing its performance with manual extraction of key features from the same tomograms.

Segmentation of electron tomographic data sets using fuzzy set theory principles

In electron tomography the reconstructed density function is typically corrupted by noise and artifacts. Under those conditions, separating the meaningful regions of the reconstructed density function is not trivial. Despite development efforts that specifically target electron tomography manual segmentation continues to be the preferred method. Based on previous good experiences using a segmentation based on fuzzy logic principles (fuzzy segmentation) where the reconstructed density functions also have low signal-to-noise ratio, we applied it to electron tomographic reconstructions. We demonstrate the usefulness of the fuzzy segmentation algorithm evaluating it within the limits of segmenting electron tomograms of selectively stained, plastic embedded spiny dendrites. The results produced by the fuzzy segmentation algorithm within the framework presented are encouraging.

Chapter 5: Imaging in depth: controversies and opportunities

One enduring challenge of biological imaging is achieving depth of penetration-into cells, tissues, and animals. How deeply can we probe and with what resolution and efficacy? These are critical issues as microscopists seek to push ever deeper, while resolving structural details and observing specific molecular events. In this guide to depth-appropriate modalities, standard optical platforms such as confocal and two-photon microscopes are considered along with complementary imaging modalities that range in depth of penetration. After an introduction to basic techniques, the trade-offs and limitations that distinguish competing technologies are considered, with emphasis on the visualization of subcellular structures and dynamic events. Not surprisingly, there are differences of opinion regarding imaging technologies, as highlighted in a section on point-scanning and Nipkow-disk style confocal microscopes. Confocal microscopy is then contrasted with deconvolution and multi-photon imaging modalities. It is also important to consider the detectors used by current instruments (such as PMTs and CCD cameras). Ultimately specimen properties, in conjunction with instrumentation, determine the depth at which subcellular operations and larger-scale biological processes can be visualized. Relative advantages are mentioned in the context of experiment planning and instrument-purchase decisions. Given the rate at which new optical techniques are being invented, this report should be viewed as a snapshot of current capabilities, with the goal of providing a framework for thinking about new developments.

Integrating diverse data for structure determination of macromolecular assemblies

To understand the cell, we need to determine the macromolecular assembly structures, which may consist of tens to hundreds of components. First, we review the varied experimental data that characterize the assemblies at several levels of resolution. We then describe computational methods for generating the structures using these data. To maximize completeness, resolution, accuracy, precision, and efficiency of the structure determination, a computational approach is required that uses spatial information from a variety of experimental methods. We propose such an approach, defined by its three main components: a hierarchical representation of the assembly, a scoring function consisting of spatial restraints derived from experimental data, and an optimization method that generates structures consistent with the data. This approach is illustrated by determining the configuration of the 456 proteins in the nuclear pore complex (NPC) from baker's yeast. With these tools, we are poised to integrate structural information gathered at multiple levels of the biological hierarchy--from atoms to cells--into a common framework.

The hard cell: From proteomics to a whole cell model

Proteomics has provided a wealth of data related to the nature of the proteome, including subcellular location, copy number, interaction partners and protein complexes. This raises the question of whether it is feasible to combine these data, together with other data related to overall cellular structure, to construct a static picture of the cell. In this minireview, we discuss these data, and the issues of turning them into whole cell models.

Three-dimensional cryotransmission electron microscopy of cells and organelles

Cryoelectron microscopy of frozen-hydrated specimens is currently the only available technique for determining the "native" three-dimensional ultrastructure of individual examples of organelles and cells. Two techniques are available, stereo pair imaging and electron tomography, the latter providing full three-dimensional information about the specimen. A resolution of 4 to 10 nm can currently be obtained with cryotomography. We describe specimen preparation by means of plunge-freezing, which is straightforward and rapid compared with conventional EM techniques. We detail the considerations and preparation needed for successful cryotomography. Frozen-hydrated specimens are very radiation-sensitive and have low contrast because they lack heavy metal stains. The total electron dose that can be applied without damage to the specimen at a given resolution must be estimated, and this dose is fractionated among the images in the tilt series. The desired resolution determines the number and magnification of the images in the tilt series, as well as the objective lens defocus used for phase contrast imaging. The combination of the desired resolution and the maximum number of images into which a given dose can be fractionated sets an upper limit on specimen thickness. Because of these constraints, careful choice of imaging conditions, use of a sensitive CCD camera system, and microscope automation, are important requirements for conducting cryoelectron tomography.

Current and future issues in the manufacturing and development of monoclonal antibodies

Despite a slow beginning, monoclonal antibodies have had many successes over the past decade. It is important that these successes continue, bringing more products for more indications to market. Although manufacturing is not the most common cause of product failure, product quality issues can delay antibody development. Manufacturing has depended on the triad of process validation, process control and product testing. Applying product knowledge proactively to manufacturing (quality by design) may allow greater flexibility and maintain or improve product quality. An integrated approach to biological characterization is an important aspect of product knowledge. Greater product knowledge also facilitates development in other disciplines. Independent of manufacturing strategy, there are a number of regulatory hurdles in initial and ongoing antibody development. These are described to help prevent unnecessary delays.

Electron tomography of membrane-bound cellular organelles

Electron microscope tomography produces three-dimensional reconstructions and has been used to image organelles both isolated and in situ, providing new insight into their structure and function. It is analogous to the various tomographies used in medical imaging. Compared with light microscopy, electron tomography offers an improvement in resolution of 30- to 80-fold and currently ranges from 3 to 8 nm, thus filling the gap between high-resolution structure determinations of isolated macromolecules and larger-scale studies on cells and tissues by light microscopy. Here, we provide an introduction to electron tomography and applications of the method in characterizing organelle architecture that also show its power for suggesting functional significance. Further improvements in labeling modalities, imaging tools, specimen preparation, and reconstruction algorithms promise to increase the quality and breadth of reconstructions by electron tomography and eventually to allow the mapping of the cellular proteomes onto detailed three-dimensional models of cellular structure.

Structure of complex viruses and virus-infected cells by electron cryo tomography

In microbiology, and in particular in virus research, electron microscopy (EM) is an important tool, offering a broad approach for investigating viral structure throughout their intracellular and extracellular life cycles. Currently, molecular tools and rapid developments in advanced light microscopy dominate the field and supply an enormous amount of information concerning virus biology. In recent years, numerous fascinating high-resolution EM structures obtained by single-particle electron cryo microscopy (cryo-EM) were revealed for viral particles that possess icosahedral symmetry. However, no comprehensive three-dimensional analysis of complex viruses or viruses within cells has yet been achieved using EM. Recent developments in electron cryo-tomography render this a proficient tool for the analysis of complex viruses and viruses within cells in greater detail.

Automated segmentation of molecular subunits in electron cryomicroscopy density maps

Electron cryomicroscopy (cryoEM) is capable of imaging large macromolecular machines composed of multiple components. However, it is currently only possible to achieve moderate resolution at which it may be possible to computationally extract the individual components in the machine. In this work, we present application details of an automated method for detecting and segmenting the components of a large machine in an experimentally determined density map. This method is applicable to object with and without symmetry and takes advantage of global and local symmetry axes if present. We have applied this segmentation algorithm to several cryoEM data sets already deposited in EMDB with various complexities, symmetries and resolutions and validated the results using manually segmented density and available structures of the components in the PDB. As such, automated segmentation could become a useful tool for the analysis of the ever-increasing number of structures of macromolecular machines derived from cryoEM.

A visual approach to proteomics

Cryo-electron tomography is an emerging imaging technique that has unique potential for molecular cell biology. At the present resolution of 4-5 nm, large supramolecular structures can be studied in unperturbed cellular environments and, in the future, it will become possible to map molecular landscapes inside cells in a more comprehensive manner. 'Visual proteomics' aims to complement and extend mass-spectrometry-based inventories, and to provide a quantitative description of the macromolecular interactions that underlie cellular functions.

CTF determination and correction in electron cryotomography

Electron cryotomography (cryoET) has the potential to elucidate the structure of complex biological specimens at molecular resolution but technical and computational improvements are still needed. This work addresses the determination and correction of the contrast transfer function (CTF) of the electron microscope in cryoET. Our approach to CTF detection and defocus determination depends on strip-based periodogram averaging, extended throughout the tilt series to overcome the low contrast conditions found in cryoET. A method for CTF correction that deals with the defocus gradient in images of tilted specimens is also proposed. These approaches to CTF determination and correction have been applied here to several examples of cryoET of pleomorphic specimens and of single particles. CTF correction is essential for improving the resolution, particularly in those studies that combine cryoET with single particle averaging techniques.

Towards high-resolution three-dimensional imaging of native mammalian tissue: Electron tomography of frozen-hydrated rat liver sections

Cryo-electron tomography of frozen-hydrated specimens holds considerable promise for high-resolution three-dimensional imaging of organelles and macromolecular complexes in their native cellular environment. While the technique has been successfully used with small, plunge-frozen cells and organelles, application to bulk mammalian tissue has proven to be difficult. We report progress with cryo-electron tomography of frozen-hydrated sections of rat liver prepared by high-pressure freezing and cryo-ultramicrotomy. Improvements include identification of suitable grids for mounting sections for tomography, reduction of surface artifacts on the sections, improved image quality by the use of energy filtering, and more rapid tissue excision using a biopsy needle. Tomographic reconstructions of frozen-hydrated liver sections reveal the native structure of such cellular components as mitochondria, endoplasmic reticulum, and ribosomes, without the selective attenuation or enhancement of ultrastructural details associated with the osmication and post-staining used with freeze-substitution.

Structural studies by electron tomography: from cells to molecules

Electron tomography (ET) is uniquely suited to obtain three-dimensional reconstructions of pleomorphic structures, such as cells, organelles or supramolecular assemblies. Although the principles of ET have been known for decades, its use has gathered momentum only in recent years, thanks to technological advances and its combination with improved specimen preparation techniques. The rapid freezing/freeze-substitution preparation is applicable to whole cells and tissues, and it is the method of choice for ET investigations of cellular ultrastructure. The frozen-hydrated preparation provides the best possible structural preservation and allows the imaging of molecules, complexes, and supramolecular assemblies in their native state and their natural environment. Devoid of staining and chemical fixation artifacts, cryo-ET provides a faithful representation of both the surface and internal structure of molecules. In combination with advanced computational methods, such as molecular identification based on pattern recognition techniques, cryo-ET is currently the most promising approach to comprehensively map macromolecular architecture inside cellular tomograms.

Automatic ultrastructure segmentation of reconstructed cryoEM maps of icosahedral viruses

We present an automatic algorithm to segment all the local and global asymmetric units of a three-dimensional density map of icosahedral viruses. This approach is readily applicable to the structural analysis of a broad range of virus structures that are reconstructed using cryo-electron microscopy (cryo-EM) technique. Our algorithm includes three major steps operating on the three dimensional density map: the detection of critical points of the volumetric density function, the detection of global and local symmetry axes, and, finally, the boundary segmentation of all the asymmetric units. We demonstrate the efficacy of our algorithm and report our results on several experimental volumetric datasets, consisting of both reconstructed cryo-EM molecular density maps taken from the European Bioinformatics Institute archive, as well our own synthetically generated (blurred) maps calculated from X-ray resolution molecular structural data taken from the Protein Data Bank.

Bridging the imaging gap: visualizing subcellular architecture with electron tomography

Transmission electron microscopy is a powerful tool that is used to explore the internal structure of tissues, cells, organelles and macromolecular complexes. By integrating data from a series of images in which the orientation of the specimen is progressively varied relative to the incident electron beam it is also possible to extend electron microscopic imaging into the third dimension. This approach, commonly referred to as electron tomography, has been greatly aided in recent years by advances in technology for imaging specimens at cryogenic temperatures, as well as by substantial progress in procedures for automated data collection and image processing. The intense pace of developments in this field is inspired, in a large part, by the hope that the quality of the data will ultimately be good enough to allow interpretation of tomograms of cells, organelles, bacteria and viruses in terms of the three-dimensional spatial arrangements of the constituent molecules.

New views of cells in 3D: an introduction to electron tomography

The most important goal of structural cell biology is to elucidate the mechanisms of the processes of life. The structure of a membrane system or fibrous array, the changes in such structures over time or the localizations of enzymes relative to organelle boundaries can often illuminate associated cellular functions. To be of maximal value, structural studies should provide isotropic, 3D information about well-preserved samples at the highest possible resolution. Electron tomography can provide such information about many kinds of cells and organelles.

Lessons from tomographic studies of the mammalian Golgi

Basic structure studies of the biosynthetic machinery of the cell by electron microscopy (EM) have underpinned much of our fundamental knowledge in the areas of molecular cell biology and membrane traffic. Driven by our collective desire to understand how changes in the complex and dynamic structure of this enigmatic organelle relate to its pivotal roles in the cell, the comparatively high-resolution glimpses of the Golgi and other compartments of the secretory pathway offered to us through EM have helped to inspire the development and application of some of our most informative, complimentary (molecular, biochemical and genetic) approaches. Even so, no one has yet even come close to relating the basic molecular mechanisms of transport, through and from the Golgi, to its ultrastructure, to everybody's satisfaction. Over the past decade, EM tomography has afforded new insights into structure-function relationships of the Golgi and provoked a re-evaluation of older paradigms. By providing a set of tools for structurally dissecting cells at high-resolution in three-dimensions (3D), EM tomography has emerged as a method for studying molecular cell biology in situ. As we move rapidly toward the establishment of molecular atlases of organelles through advances in proteomics and genomics, tomographic studies of the Golgi offer the tantalizing possibility that one day, we will be able to map the spatio-temporal coordinates of Golgi-related proteins and lipids accurately in the context of 4D cellular space.

Peach: A Simple Perl-Based System for Distributed Computation and Its Application to Cryo-EM Data Processing

A simple distributed processing system named "Peach" was developed to meet the rising computational demands of modern structural biology (and other) laboratories without additional expense by using existing hardware resources more efficiently. A central server distributes jobs to idle workstations in such a way that each computer is used maximally, but without disturbing intermittent interactive users. As compared to other distributed systems, Peach is simple, easy to install, easy to administer, easy to use, scalable, and robust. While it was designed to queue and distribute large numbers of small tasks to participating computers, it can also be used to send single jobs automatically to the fastest currently available computer and/or survey the activity of an entire laboratory's computers. Tests of robustness and scalability are reported, as are three specific electron cryomicroscopy applications where Peach enabled projects that would not otherwise have been feasible without an expensive, dedicated cluster.

Electron tomography of biological samples

Electron tomography allows computing three-dimensional (3D) reconstructions of objects from their projections recorded at several angles. Combined with transmission electron microscopy, electron tomography has contributed greatly to the understanding of subcellular structures and organelles. Performed on frozen-hydrated samples, electron tomography has yielded useful information about complex biological structures. Combined with energy filtered transmission electron microscopy (EFTEM) it can be used to analyze the spatial distribution of chemical elements in biological or material sciences samples. In the present review, we present an overview of the requirements, applications, and perspectives of electron tomography in structural biology.