Volumetric feature extraction and visualization of tomographic molecular imaging

Electron tomography and immunogold labeling of plant cells

Electron microscopy enables the imaging of organelles and macromolecular complexes within cells at nanometer scale resolution. Electron tomography of biological samples, either in vitrified ice or fixed and embedded in resin, provides three-dimensional structural information of relatively small volumes (a few cubic microns) of cells at axial resolutions of 1-7nm. This chapter discusses approaches for plant sample preparation by high-pressure freezing/freeze-substitution and resin-embedding for electron tomography and immunogold labeling using transmission electron microscopy.

RAZA: A Rapid 3D z-crossings algorithm to segment electron tomograms and extract organelles and macromolecules

Resolving the 3D architecture of cells to atomic resolution is one of the most ambitious challenges of cellular and structural biology. Central to this process is the ability to automate tomogram segmentation to identify sub-cellular components, facilitate molecular docking and annotate detected objects with associated metadata. Here we demonstrate that RAZA (Rapid 3D z-crossings algorithm) provides a robust, accurate, intuitive, fast, and generally applicable segmentation algorithm capable of detecting organelles, membranes, macromolecular assemblies and extrinsic membrane protein domains. RAZA defines each continuous contour within a tomogram as a discrete object and extracts a set of 3D structural fingerprints (major, middle and minor axes, surface area and volume), enabling selective, semi-automated segmentation and object extraction. RAZA takes advantage of the fact that the underlying algorithm is a true 3D edge detector, allowing the axes of a detected object to be defined, independent of its random orientation within a cellular tomogram. The selectivity of object segmentation and extraction can be controlled by specifying a user-defined detection tolerance threshold for each fingerprint parameter, within which segmented objects must fall and/or by altering the number of search parameters, to define morphologically similar structures. We demonstrate the capability of RAZA to selectively extract subgroups of organelles (mitochondria) and macromolecular assemblies (ribosomes) from cellular tomograms. Furthermore, the ability of RAZA to define objects and their contours, provides a basis for molecular docking and rapid tomogram annotation.

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data

Managing, processing and understanding big healthcare data is challenging, costly and demanding. Without a robust fundamental theory for representation, analysis and inference, a roadmap for uniform handling and analyzing of such complex data remains elusive. In this article, we outline various big data challenges, opportunities, modeling methods and software techniques for blending complex healthcare data, advanced analytic tools, and distributed scientific computing. Using imaging, genetic and healthcare data we provide examples of processing heterogeneous datasets using distributed cloud services, automated and semi-automated classification techniques, and open-science protocols. Despite substantial advances, new innovative technologies need to be developed that enhance, scale and optimize the management and processing of large, complex and heterogeneous data. Stakeholder investments in data acquisition, research and development, computational infrastructure and education will be critical to realize the huge potential of big data, to reap the expected information benefits and to build lasting knowledge assets. Multi-faceted proprietary, open-source, and community developments will be essential to enable broad, reliable, sustainable and efficient data-driven discovery and analytics. Big data will affect every sector of the economy and their hallmark will be 'team science'.

Accurate membrane tracing in three-dimensional reconstructions from electron cryotomography data

The connection between the extracellular matrix and the cell is of major importance for mechanotransduction and mechanobiology. Electron cryo-tomography, in principle, enables better than nanometer-resolution analysis of these connections, but restrictions of data collection geometry hamper the accurate extraction of the ventral membrane location from these tomograms, an essential prerequisite for the analysis. Here, we introduce a novel membrane tracing strategy that enables ventral membrane extraction at high fidelity and extraordinary accuracy. The approach is based on detecting the boundary between the inside and the outside of the cell rather than trying to explicitly trace the membrane. Simulation studies show that over 99% of the membrane can be correctly modeled using this principle and the excellent match of visually identifiable membrane stretches with the extracted boundary of experimental data indicates that the accuracy is comparable for actual data.

From voxels to knowledge: a practical guide to the segmentation of complex electron microscopy 3D-data

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation.

The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.

Combined approaches to flexible fitting and assessment in virus capsids undergoing conformational change

Fitting of atomic components into electron cryo-microscopy (cryoEM) density maps is routinely used to understand the structure and function of macromolecular machines. Many fitting methods have been developed, but a standard protocol for successful fitting and assessment of fitted models has yet to be agreed upon among the experts in the field. Here, we created and tested a protocol that highlights important issues related to homology modelling, density map segmentation, rigid and flexible fitting, as well as the assessment of fits. As part of it, we use two different flexible fitting methods (Flex-EM and iMODfit) and demonstrate how combining the analysis of multiple fits and model assessment could result in an improved model. The protocol is applied to the case of the mature and empty capsids of Coxsackievirus A7 (CAV7) by flexibly fitting homology models into the corresponding cryoEM density maps at 8.2 and 6.1 Å resolution. As a result, and due to the improved homology models (derived from recently solved crystal structures of a close homolog – EV71 capsid – in mature and empty forms), the final models present an improvement over previously published models. In close agreement with the capsid expansion observed in the EV71 structures, the new CAV7 models reveal that the expansion is accompanied by ∼5° counterclockwise rotation of the asymmetric unit, predominantly contributed by the capsid protein VP1. The protocol could be applied not only to viral capsids but also to many other complexes characterised by a combination of atomic structure modelling and cryoEM density fitting.

Bacterial social networks: structure and composition of Myxococcus xanthus outer membrane vesicle chains

The social soil bacterium, Myxococcus xanthus, displays a variety of complex and highly coordinated behaviours, including social motility, predatory rippling and fruiting body formation. Here we show that M. xanthus cells produce a network of outer membrane extensions in the form of outer membrane vesicle chains and membrane tubes that interconnect cells. We observed peritrichous display of vesicles and vesicle chains, and increased abundance in biofilms compared with planktonic cultures. By applying a range of imaging techniques, including three-dimensional (3D) focused ion beam scanning electron microscopy, we determined these structures to range between 30 and 60 nm in width and up to 5 μm in length. Purified vesicle chains consist of typical M. xanthus lipids, fucose, mannose, N-acetylglucosamine and N-acetylgalactoseamine carbohydrates and a small set of cargo protein. The protein content includes CglB and Tgl outer membrane proteins known to be transferable between cells in a contact-dependent manner. Most significantly, the 3D organization of cells within biofilms indicates that cells are connected via an extensive network of membrane extensions that may connect cells at the level of the periplasmic space. Such a network would allow the transfer of membrane proteins and other molecules between cells, and therefore could provide a mechanism for the coordination of social activities.

Shape-based regularization of electron tomographic reconstruction

We introduce a tomographic reconstruction method implemented using a shape-based regularization technique. Spatial models of known features in the structure being reconstructed are integrated into the reconstruction process as regularizers. Our regularization scheme is driven locally through shape information obtained from segmentation and compared with a known spatial model. We demonstrated our method on tomography data from digital phantoms, simulated data, and experimental electron tomography (ET) data of virus complexes. Our reconstruction showed reduced blurring and an improvement in the resolution of the reconstructed volume was also measured. This method also produced improved demarcation of spike boundaries in viral membranes when compared with popular techniques like weighted back projection and the algebraic reconstruction technique. Improved ET reconstructions will provide better structure elucidation and improved feature visualization, which can aid in solving key biological issues. Our method can also be generalized to other tomographic modalities.

Putative binding sites, and pathways to them, for amidine and guanidine current inhibitors on acid-sensing ion channels (ASIC). A theoretical approach with hASIC1a homology model

Central inhibition of the acid-sensing hASIC1a channel, acting upstream of the opiate system, might serve to treat any type of pain, avoiding the unwanted addiction problems of the opioid drugs. To this end, inhibition of hASIC1a channel by PcTx1, a peptide from the Trinidad chevron tarantula, is under development. New inhibitors of the hASIC1a channel are also being sought, in the hope of further modulating the activity, from which antiplasmodial amidine and guanidine phenyl drugs have emerged as promising candidates. However, how such current inhibition takes place remains obscure from the molecular point of view, hindering any further progress in developing drugs. Therefore, the nature of the binding sites, and how they are reached by the amidine-guanidine drugs, was investigated here via automated docking and molecular dynamics with hASIC1a homology models. This study has revealed that this ion channel is rich in binding sites, and that flexible drugs, such as nafamostat, may penetrate it in a snake-like elongated conformation. Then, crawling like a snake through temporary holes in the protein, nafamostat either simply flips, or changes to a high-energy folded conformation to become adapted to the shape of the binding site.

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.

Three-dimensional macromolecular organization of cryofixed Myxococcus xanthus biofilms as revealed by electron microscopic tomography

Despite the fact that most bacteria grow in biofilms in natural and pathogenic ecosystems, very little is known about the ultrastructure of their component cells or about the details of their community architecture. We used high-pressure freezing and freeze-substitution to minimize the artifacts of chemical fixation, sample aggregation, and sample extraction. As a further innovation we have, for the first time in biofilm research, used electron tomography and three-dimensional (3D) visualization to better resolve the macromolecular 3D ultrastructure of a biofilm. This combination of superb specimen preparation and greatly improved resolution in the z axis has opened a window in studies of Myxococcus xanthus cell ultrastructure and biofilm community architecture. New structural information on the chromatin body, cytoplasmic organization, membrane apposition between adjacent cells, and structure and distribution of pili and vesicles in the biofilm matrix is presented.

Three-dimensional geometric modeling of membrane-bound organelles in ventricular myocytes: bridging the gap between microscopic imaging and mathematical simulation

A general framework of image-based geometric processing is presented to bridge the gap between three-dimensional (3D) imaging that provides structural details of a biological system and mathematical simulation where high-quality surface or volumetric meshes are required. A 3D density map is processed in the order of image pre-processing (contrast enhancement and anisotropic filtering), feature extraction (boundary segmentation and skeletonization), and high-quality and realistic surface (triangular) and volumetric (tetrahedral) mesh generation. While the tool-chain described is applicable to general types of 3D imaging data, the performance is demonstrated specifically on membrane-bound organelles in ventricular myocytes that are imaged and reconstructed with electron microscopic (EM) tomography and two-photon microscopy (T-PM). Of particular interest in this study are two types of membrane-bound Ca(2+)-handling organelles, namely, transverse tubules (T-tubules) and junctional sarcoplasmic reticulum (jSR), both of which play an important role in regulating the excitation-contraction (E-C) coupling through dynamic Ca(2+) mobilization in cardiomyocytes.

PROTO-PLASM: parallel language for adaptive and scalable modelling of biosystems

This paper discusses the design goals and the first developments of PROTO-PLASM, a novel computational environment to produce libraries of executable, combinable and customizable computer models of natural and synthetic biosystems, aiming to provide a supporting framework for predictive understanding of structure and behaviour through multiscale geometric modelling and multiphysics simulations. Admittedly, the PROTO-PLASM platform is still in its infancy. Its computational framework--language, model library, integrated development environment and parallel engine--intends to provide patient-specific computational modelling and simulation of organs and biosystem, exploiting novel functionalities resulting from the symbolic combination of parametrized models of parts at various scales. PROTO-PLASM may define the model equations, but it is currently focused on the symbolic description of model geometry and on the parallel support of simulations. Conversely, CellML and SBML could be viewed as defining the behavioural functions (the model equations) to be used within a PROTO-PLASM program. Here we exemplify the basic functionalities of PROTO-PLASM, by constructing a schematic heart model. We also discuss multiscale issues with reference to the geometric and physical modelling of neuromuscular junctions.

Shape-driven three-dimensional watersnake segmentation of biological membranes in electron tomography

Due to the significant complexity of membrane morphology and the generally poor image quality in electron tomographic volumes, current automatic methods for segmentation of membranes perform poorly. Users must resort to manual tracing of recognized patterns on 2-D slices of the volume, a method that suffers from subjectivity and is very labor intensive, preventing quantitative analyses of tomographic data that require comparative analyses of many volumes. To overcome these limitations, we develop an automatic 3-D segmentation method that fully exploits the prior knowledge about the shape of the membranes as well as the 3-D information provided by the tomograms, and systematically combines this knowledge with the image data to improve segmentation results. The method is based on the watersnake framework. By mathematically reformulating the traditional watershed segmentation as an energy minimization problem, the watersnake inherits the many strengths of the watershed method while overcoming the limitations of the traditional energy-based segmentation methods. In our previous work (H. Nguyen et al., 2003), the original watersnake model was successfully modified by incorporating smoothness into watershed segmentation. In this work, we further extend that model to incorporate into the energy function various constraints representing our prior knowledge about the global shape of the cellular features to be segmented. Segmentation can, therefore, be accomplished via minimization of the energy function subject to the shape prior constraints. Finally, the mathematical framework is further extended from 2-D to 3-D so that segmentation can be carried out in 3-D to take advantage of the additional information provided by the tomograms. We apply this method for the automatic extraction of biological membranes of varying complexities including those of bacterial walls and mitochondrial boundaries.

Three-dimensional architecture of hair-bundle linkages revealed by electron-microscopic tomography

The senses of hearing and balance rest upon mechanoelectrical transduction by the hair bundles of hair cells in the inner ear. Located at the apical cellular surface, each hair bundle comprises several tens of stereocilia and a single kinocilium that are interconnected by extracellular proteinaceous links. Using electron-microscopic tomography of bullfrog saccular sensory epithelia, we examined the three-dimensional structures of basal links, kinociliary links, and tip links. We observed significant differences in the appearances and dimensions of these three structures and found two distinct populations of tip links suggestive of the involvement of different proteins, splice variants, or protein-protein interactions. We noted auxiliary links connecting the upper portions of tip links to the taller stereocilia. Tip links and auxiliary links show a tendency to adopt a globular conformation when disconnected from the membrane surface.

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.

JUST (Java User Segmentation Tool) for semi-automatic segmentation of tomographic maps

We are presenting a program for interactive segmentation of tomographic maps, based on objective criteria so as to yield reproducible results. The strategy starts with the automatic segmentation of the entire volume with the watershed algorithm in 3D. The watershed regions are clustered successively by supervised classification, allowing the segmentation of known organelles, such as membranes, vesicles and microtubules. These organelles are processed with topological models and input parameters manually derived from the tomograms. After known organelles are extracted from the volume, all other watershed regions can be organized into homogeneous assemblies on the basis of their densities. To complete the process, all voxels in the volume are assigned either to the background or individual structures, which can then be extracted for visualization with any rendering technique. The user interface of the program is written in Java, and computational routines are written in C. For some operations, involving the visualization of the tomogram, we refer to existing software, either open or commercial. While the program runs, a history file is created, that allows all parameters and other data to be saved for the purposes of comparison or exchange. Initially, the program was developed for the segmentation of synapses, and organelles belonging to these structures have thus far been the principal targets modeled with JUST. Since each organelle is clustered independently from the rest of the volume, however, the program can accommodate new models of different organelles as well as tomograms of other types of preparations of tissue, such as cytoskeletal components in vitreous ice.

Local or global minima: flexible dual-front active contours

Most variational active contour models are designed to find local minima of data-dependent energy functionals with the hope that reasonable initial placement of the active contour will drive it toward a "desirable" local minimum as opposed to an undesirable configuration due to noise or complex image structure. As such, there has been much research into the design of complex region-based energy functionals that are less likely to yield undesirable local minima when compared to simpler edge-based energy functionals whose sensitivity to noise and texture is significantly worse. Unfortunately, most of these more "robust" region-based energy functionals are applicable to a much narrower class of imagery compared to typical edge-based energies due to stronger global assumptions about the underlying image data. Devising new implementation algorithms for active contours that attempt to capture more global minimizers of already proposed image-based energies would allow us to choose an energy that makes sense for a particular class of energy without concern over its sensitivity to local minima. Such implementations have been proposed for capturing global minima. However, sometimes the completely-global minimum is just as undesirable as a minimum that is too local. In this paper, we propose a novel, fast, and flexible dual front implementation of active contours, motivated by minimal path techniques and utilizing fast sweeping algorithms, which is easily manipulated to yield minima with variable "degrees" of localness and globalness. By simply adjusting the size of active regions, the ability to gracefully move from capturing minima that are more local (according to the initial placement of the active contour/surface) to minima that are more global allows this model to more easily obtain "desirable" minimizers (which often are neither the most local nor the most global). Experiments on various 2D and 3D images and comparisons with some active contour models and region-growing methods are also given to illustrate the properties of this model and its performance in a variety of segmentation applications.

[3D modeling in the field of morphology: methods, interest and results]

The aim of this paper is to show the major role played by the new computerized imaging tools available today in the fields of morphology and anatomy. For anatomical studies or educational purpose, they enhance the classical techniques. The 3D reconstruction, already used in daily clinical practice, will be the basis for computation of validated volumetric protocols enhancing our diagnosis and prognosis means. It is also a fantastic educational tool: the interactivity makes it simple, efficient, attractive and easily accessible and diffusable. For the research, mathematical modeling of embryogenesis and morphogenesis using finite elements method will open new ways for biomecanics and a dynamic quantification approach.

Model-based automated extraction of microtubules from electron tomography volume

We propose a model-based automated approach to extracting microtubules from noisy electron tomography volume. Our approach consists of volume enhancement, microtubule localization, and boundary segmentation to exploit the unique geometric and photometric properties of microtubules. The enhancement starts with an anisotropic invariant wavelet transform to enhance the microtubules globally, followed by a three-dimensional (3-D) tube-enhancing filter based on Weingarten matrix to further accentuate the tubular structures locally. The enhancement ends with a modified coherence-enhancing diffusion to complete the interruptions along the microtubules. The microtubules are then localized with a centerline extraction algorithm adapted for tubular objects. To perform segmentation, we novelly modify and extend active shape model method. We first use 3-D local surface enhancement to characterize the microtubule boundary and improve shape searching by relating the boundary strength with the weight matrix of the searching error. We then integrate the active shape model with Kalman filtering to utilize the longitudinal smoothness along the microtubules. The segmentation improved in this way is robust against missing boundaries and outliers that are often present in the tomography volume. Experimental results demonstrate that our automated method produces results close to those by manual process and uses only a fraction of the time of the latter.

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.

Automated extraction of fine features of kinetochore microtubules and plus-ends from electron tomography volume

Kinetochore microtubules (KMTs) and the associated plus-ends have been areas of intense investigation in both cell biology and molecular medicine. Though electron tomography opens up new possibilities in understanding their function by imaging their high-resolution structures, the interpretation of the acquired data remains an obstacle because of the complex and cluttered cellular environment. As a result, practical segmentation of the electron tomography data has been dominated by manual operation, which is time consuming and subjective. In this paper, we propose a model-based automated approach to extracting KMTs and the associated plus-ends with a coarse-to-fine scale scheme consisting of volume preprocessing, microtubule segmentation and plus-end tracing. In volume preprocessing, we first apply an anisotropic invariant wavelet transform and a tube-enhancing filter to enhance the microtubules at coarse level for localization. This is followed with a surface-enhancing filter to accentuate the fine microtubule boundary features. The microtubule body is then segmented using a modified active shape model method. Starting from the segmented microtubule body, the plus-ends are extracted with a probabilistic tracing method improved with rectangular window based feature detection and the integration of multiple cues. Experimental results demonstrate that our automated method produces results comparable to manual segmentation but using only a fraction of the manual segmentation time.

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.

Application of electron tomography to fungal ultrastructure studies

Access to structural information at the nanoscale enables fundamental insights into many complex biological systems. The development of the transmission electron microscope (TEM) has vastly increased our understanding of multiple biological systems. However, when attempting to visualize and understand the organizational and functional complexities that are typical of cells and tissues, the standard 2-D analyses that TEM affords often fall short. In recent years, high-resolution electron tomography methods, coupled with advances in specimen preparation and instrumentation and computational speed, have resulted in a revolution in the biological sciences. Electron tomography is analogous to medical computerized axial tomography (CAT-scan imaging) except at a far finer scale. It utilizes the TEM to assemble multiple projections of an object which are then combined for 3-D analyses. For biological specimens, tomography enables the highest 3-D resolution (5 nm spatial resolution) of internal structures in relatively thick slices of material (0.2-0.4 microm) without requiring the collection and alignment of large numbers of thin serial sections. Thus accurate and revealing 3-D reconstructions of complex cytoplasmic entities and architecture can be obtained. Electron tomography is now being applied to a variety of biological questions with great success. This review gives a brief introduction into cryopreservation and electron tomography relative to aspects of cytoplasmic organization in the hyphal tip of Aspergillus nidulans.

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.

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.

Methods for generating high-resolution structural models from electron microscope tomography data

Reconstructed volumes generated by tilt-image electron-microscope tomography offer the best spatial resolution currently available for studying cell structures in situ. Analysis is often accomplished by creating surface models that delineate grayscale contrast boundaries. Here, we introduce a specialized and convenient sequence of segmentation operations for making such models that greatly improves their reliability and spatial resolution as compared to current approaches, providing a basis for making accurate measurements. To assess the reliability of the surface models, we introduce a spatial uncertainty measurement based on grayscale gradient scale length. The model generation and measurement methods are validated by applying them to synthetic data, and their utility is demonstrated by using them to characterize macromolecular architecture of active zone material at the frog's neuromuscular junction.

Computational exploration of structural information from cryo-electron tomograms

Cryo-electron tomography aims to act as an interface between in vivo cell imaging and techniques achieving atomic resolution. This attempt to bridge the resolution gap is facilitated by recent software and hardware advances. Information provided by atomically resolved macromolecules and molecular interaction data need to be put into a common framework in order to create a hybrid multidimensional cellular image. A major partner in this enterprise is the development of regularization and pattern recognition techniques, which try to identify macromolecular complexes as a function of their structural signature in cryo-electron tomograms of living cells.