Electron Tomograms Research Articles

Control of Shape and Material Composition of Solid-State Nanopores

Solid-state nanopores fabricated by a high-intensity electron beam in ceramic membranes can be fine-tuned on three-dimensional geometry and composition by choice of materials and beam sculpting conditions. For similar beam conditions, 8 nm diameter nanopores fabricated in membranes containing SiO(2) show large depletion areas (70 nm in radius) with small sidewall angles (55 degrees ), whereas those made in SiN membranes show small depletion areas (40 nm) with larger sidewall angles (75 degrees ). Three-dimensional electron tomograms of nanopores fabricated in a SiO(2)/SiN/SiO(2) membrane show a biconical shape with symmetric top and bottom and indicate a mixing of SiN and SiO(2) layers up to 30 nm from the edge of nanopore, with Si-rich particles throughout the membrane. Electron-energy-loss spectroscopy (EELS) reveals that the oxygen/nitrogen ratio near the pore depends on the beam sculpting conditions.

Visualization of the three-dimensional microstructure of TiO 2 nanotubes by electron tomography

The internal microstructure of pure rutile nanotubes has been elucidated by means of high angle annular dark field scanning transmission electron tomography. The formation and stability of pure rutile fully hollow nanotubes, after removal of carbon nanotubes used as templates is confirmed by 3D electron tomogram analysis. The size, shape and distribution of the nanocrystals which constitute the nanotube, are also characterized by tomography.

Structure and Biochemical Properties of Fission Yeast Arp2/3 Complex Lacking the Arp2 Subunit

Arp2/3 (actin-related protein 2/3) complex is a seven-subunit complex that nucleates branched actin filaments in response to cellular signals. Nucleation-promoting factors such as WASp/Scar family proteins activate the complex by facilitating the activating conformational change and recruiting the first actin monomer for the daughter branch. Here we address the role of the Arp2 subunit in the function of Arp2/3 complex by isolating a version of the complex lacking Arp2 (Arp2Delta Arp2/3 complex) from fission yeast. An x-ray crystal structure of the DeltaArp2 Arp2/3 complex showed that the rest of the complex is unperturbed by the loss of Arp2. However, the Arp2Delta Arp2/3 complex was inactive in actin nucleation assays, indicating that Arp2 is essential to form a branch. A fluorescence anisotropy assay showed that Arp2 does not contribute to the affinity of the complex for Wsp1-VCA, a Schizosaccharomyces pombe nucleation-promoting factor protein. Fluorescence resonance energy transfer experiments showed that the loss of Arp2 does not prevent VCA from recruiting an actin monomer to the complex. Truncation of the N terminus of ARPC5, the smallest subunit in the complex, increased the yield of Arp2Delta Arp2/3 complex during purification but did not compromise nucleation activity of the full Arp2/3 complex.

Improved specimen reconstruction by Hilbert phase contrast tomography

The low signal-to-noise ratio (SNR) in images of unstained specimens recorded with conventional defocus phase contrast makes it difficult to interpret 3D volumes obtained by electron tomography (ET). The high defocus applied for conventional tilt series generates some phase contrast but leads to an incomplete transfer of object information. For tomography of biological weak-phase objects, optimal image contrast and subsequently an optimized SNR are essential for the reconstruction of details such as macromolecular assemblies at molecular resolution. The problem of low contrast can be partially solved by applying a Hilbert phase plate positioned in the back focal plane (BFP) of the objective lens while recording images in Gaussian focus. Images recorded with the Hilbert phase plate provide optimized positive phase contrast at low spatial frequencies, and the contrast transfer in principle extends to the information limit of the microscope. The antisymmetric Hilbert phase contrast (HPC) can be numerically converted into isotropic contrast, which is equivalent to the contrast obtained by a Zernike phase plate. Thus, in-focus HPC provides optimal structure factor information without limiting effects of the transfer function. In this article, we present the first electron tomograms of biological specimens reconstructed from Hilbert phase plate image series. We outline the technical implementation of the phase plate and demonstrate that the technique is routinely applicable for tomography. A comparison between conventional defocus tomograms and in-focus HPC volumes shows an enhanced SNR and an improved specimen visibility for in-focus Hilbert tomography.

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.

Electron Tomography of Nascent Herpes Simplex Virus Virions

Cells infected with herpes simplex virus type 1 (HSV-1) were conventionally embedded or freeze substituted after high-pressure freezing and stained with uranyl acetate. Electron tomograms of capsids attached to or undergoing envelopment at the inner nuclear membrane (INM), capsids within cytoplasmic vesicles near the nuclear membrane, and extracellular virions revealed the following phenomena. (i) Nucleocapsids undergoing envelopment at the INM, or B capsids abutting the INM, were connected to thickened patches of the INM by fibers 8 to 19 nm in length and < or =5 nm in width. The fibers contacted both fivefold symmetrical vertices (pentons) and sixfold symmetrical faces (hexons) of the nucleocapsid, although relative to the respective frequencies of these subunits in the capsid, fibers engaged pentons more frequently than hexons. (ii) Fibers of similar dimensions bridged the virion envelope and surface of the nucleocapsid in perinuclear virions. (iii) The tegument of perinuclear virions was considerably less dense than that of extracellular virions; connecting fibers were observed in the former case but not in the latter. (iv) The prominent external spikes emanating from the envelope of extracellular virions were absent from perinuclear virions. (v) The virion envelope of perinuclear virions appeared denser and thicker than that of extracellular virions. (vi) Vesicles near, but apparently distinct from, the nuclear membrane in single sections were derived from extensions of the perinuclear space as seen in the electron tomograms. These observations suggest very different mechanisms of tegumentation and envelopment in extracellular compared with perinuclear virions and are consistent with application of the final tegument to unenveloped nucleocapsids in a compartment(s) distinct from the perinuclear space.

Segmentation of thin structures in electron micrographs using orientation fields

In this paper, we introduce a new approach for segmenting thin structures in electron micrographs. We introduce two new transforms, the Line Filter Transform (LFT) and the Orientation Filter Transform (OFT). The LFT can be viewed as an alternative to anisotropic diffusion algorithms that is particularly useful for thin structures. The OFT utilizes geometrical information about the structure by measuring correlations of local orientations in the image. By combining these methods with a contour extraction and labeling method we construct a segmentation method for thin structures in 2D images. We discuss how the method can be applied slice-by-slice to electron tomograms and illustrate the process by constructing two models of membrane structures from cellular tomograms. The suggested method has the advantage of being relatively insensitive to non-uniform contrast and high-contrast features such as ribosomes.

Electron tomography of nanoparticle clusters: Implications for atmospheric lifetimes and radiative forcing of soot

Nanoparticles are ubiquitous in nature. Their large surface areas and consequent chemical reactivity typically result in their aggregation into clusters. Their chemical and physical properties depend on cluster shapes, which are commonly complex and unknown. This is the first application of electron tomography with a transmission electron microscope to quantitatively determine the three‐dimensional (3D) shapes, volumes, and surface areas of nanoparticle clusters. We use soot (black carbon, BC) nanoparticles as an example because it is a major contributor to environmental degradation and global climate change. To the extent that our samples are representative, we find that quantitative measurements of soot surface areas and volumes derived from electron tomograms differ from geometrically derived values by, respectively, almost one and two orders of magnitude. Global sensitivity studies suggest that the global burden and direct radiative forcing of fractal BC are only about 60% of the value if it is assumed that BC has a spherical shape.

An energy-based three-dimensional segmentation approach for the quantitative interpretation of electron tomograms

Electron tomography allows for the determination of the three-dimensional structures of cells and tissues at resolutions significantly higher than that which is possible with optical microscopy. Electron tomograms contain, in principle, vast amounts of information on the locations and architectures of large numbers of subcellular assemblies and organelles. The development of reliable quantitative approaches for the analysis of features in tomograms is an important problem, and a challenging prospect due to the low signal-to-noise ratios that are inherent to biological electron microscopic images. This is, in part, a consequence of the tremendous complexity of biological specimens. We report on a new method for the automated segmentation of HIV particles and selected cellular compartments in electron tomograms recorded from fixed, plastic-embedded sections derived from HIV-infected human macrophages. Individual features in the tomogram are segmented using a novel robust algorithm that finds their boundaries as global minimal surfaces in a metric space defined by image features. The optimization is carried out in a transformed spherical domain with the center an interior point of the particle of interest, providing a proper setting for the fast and accurate minimization of the segmentation energy. This method provides tools for the semi-automated detection and statistical evaluation of HIV particles at different stages of assembly in the cells and presents opportunities for correlation with biochemical markers of HIV infection. The segmentation algorithm developed here forms the basis of the automated analysis of electron tomograms and will be especially useful given the rapid increases in the rate of data acquisition. It could also enable studies of much larger data sets, such as those which might be obtained from the tomographic analysis of HIV-infected cells from studies of large populations.

Retrovirus envelope protein complex structure in situ studied by cryo-electron tomography

We used cryo-electron tomography in conjunction with single-particle averaging techniques to study the structures of frozen-hydrated envelope glycoprotein (Env) complexes on intact Moloney murine leukemia retrovirus particles. Cryo-electron tomography allows 3D imaging of viruses in toto at a resolution sufficient to locate individual macromolecules, and local averaging of abundant complexes substantially improves the resolution. The averaging of repetitive features in electron tomograms is hampered by a low signal-to-noise ratio and anisotropic resolution, which results from the "missing-wedge" effect. We developed an iterative 3D averaging algorithm that compensates for this effect and used it to determine the trimeric structure of Env to a resolution of 2.7 nm, at which individual domains can be resolved. Strikingly, the 3D reconstruction is shaped like a tripod in which the trimer penetrates the membrane at three distinct locations approximately 4.5 nm apart from one another. The Env reconstruction allows tentative docking of the x-ray crystal structure of the receptor-binding domain. This study thus provides 3D structural information regarding the prefusion conformation of an intact unstained retrovirus surface protein.

Three-dimensional structure of herpes simplex virus from cryo-electron tomography.

Herpes simplex virus, a DNA virus of high complexity, consists of a nucleocapsid surrounded by the tegument-a protein compartment-and the envelope. The latter components, essential for infectivity, are pleiomorphic. Visualized in cryo-electron tomograms of isolated virions, the tegument was seen to form an asymmetric cap: On one side, the capsid closely approached the envelope; on the other side, they were separated by approximately 35 nanometers of tegument. The tegument substructure was particulate, with some short actin-like filaments. The envelope contained 600 to 750 glycoprotein spikes that varied in length, spacing, and in the angles at which they emerge from the membrane. Their distribution was nonrandom, suggesting functional clustering.

Signal Extraction and Visualization of Biological Structures from Electron Tomograms

Signal Extraction and Visualization of Biological Structures from Electron Tomograms

Identification of macromolecular complexes in cryoelectron tomograms of phantom cells.

Electron tomograms of intact frozen-hydrated cells are essentially three-dimensional images of the entire proteome of the cell, and they depict the whole network of macromolecular interactions. However, this information is not easily accessible because of the poor signal-to-noise ratio of the tomograms and the crowded nature of the cytoplasm. Here, we describe a template matching algorithm that is capable of detecting and identifying macromolecules in tomographic volumes in a fully automated manner. The algorithm is based on nonlinear cross correlation and incorporates elements of multivariate statistical analysis. Phantom cells, i.e., lipid vesicles filled with macromolecules, provide a realistic experimental scenario for an assessment of the fidelity of this approach. At the current resolution of approximately 4 nm, macromolecules in the size range of 0.5-1 MDa can be identified with good fidelity.

Quantitative self-organizing maps for clustering electron tomograms

Tomography emerges as a powerful methodology for determining the complex architectures of biological specimens that are better regarded from the structural point of view as singular entities. However, once the structure of a sufficiently large number of singular specimens is solved, quite possibly structural patterns start to emerge. This latter situation is addressed here, where the clustering of a set of 3D reconstructions using a novel quantitative approach is presented. In general terms, we propose a new variant of a self-organizing neural network for the unsupervised classification of 3D reconstructions. The novelty of the algorithm lies in its rigorous mathematical formulation that, starting from a large set of noisy input data, finds a set of “representative” items, organized onto an ordered output map, such that the probability density of this set of representative items resembles at its possible best the probability density of the input data. In this study, we evaluate the feasibility of application of the proposed neural approach to the problem of identifying similar 3D motifs within tomograms of insect flight muscle. Our experimental results prove that this technique is suitable for this type of problem, providing the electron microscopy community with a new tool for exploring large sets of tomogram data to find complex patterns.

A novel three-dimensional variant of the watershed transform for segmentation of electron density maps

Electron density maps at moderate resolution are often difficult to interpret due to the lack of recognizable features. This is especially true for electron tomograms that suffer in addition to the resolution limitation from low signal-to-noise ratios. Reliable segmentation of such maps into smaller, manageable units can greatly facilitate interpretation. Here, we present a segmentation approach targeting three-dimensional electron density maps derived by electron microscopy. The approach consists of a novel three-dimensional variant of the immersion-based watershed algorithm. We tested the algorithm on calculated data and applied it to a wide variety of electron density maps ranging from reconstructions of single macromolecules to tomograms of subcellular structures. The results indicate that the algorithm is reliable, efficient, accurate, and applicable to a wide variety of biological problems.

CTF Correction in Electron Tomography of Insect Flight Muscle

In order to extend the resolution available in electron tomograms, we have been experimenting with various deconvolution procedures that will ultimately enable correction of the focus gradient thereby allowing the resolution to be extended to beyond the first zero in the contrast transfer function (CTF). This effort requires first a determination of the amount of amplitude and phase contrast in the typical specimen used by us.For the determination of the percentage of amplitude contrast a focus series of 19 images was taken at a magnification of 13500 on a CM300. The micrographs were digitized on a PDS scanner, the pixel size was 0.888 nm. After correction of translational shifts, rotations, and defocus dependent magnification differences the image restoration was carried out according to [1,2]. From the resulting complex wave function an averaged amplitude contrast amount of 18% was obtained for the stained specimen. The phase contrast part and amplitude contrast part are shown in Figs, 1b, and 1c, respectively, and can be compared with the micrograph taken at 960 nm underfocus (Fig. 1a).

Detection and Identification of Macromolecular Complexes in Electron Tomograms of ‘Phantom Cells’

One of the most promising and exciting developments in electron tomography is its application to ice-embedded cells and cellular organelles. The primary goal of cellular electron tomography is not to obtain a high-resolution structure of a particular protein complex, but to identify a macromolecule by virtue of its structural signature and to locate it in the context of the native cellular environment . We present a computationally feasible approach, which demonstrates that an objective identification of large macromolecular complexes in cells is possible, given that a highresolution reconstruction and the structure of the molecular assembly under scrutiny are available. Our aim is to quantify the identification results using a realistic test specimen, open for the modification of experimental parameters like thickness, protein density or protein composition. in this study, the reliability of the algorithm applied to electron tomograms of ‘phantom cells’ - mimicking a real cell - is shown.We prepared phospholipid vesicles that were filled with different macromolecular complexes. First, a phospholipid solution (SOPC) was sonicated and mixed with His-tagged macromolecular complexes, such as thermosomes, 20S proteasomes or a mixture of both. The lipid-protein mixture was subjected to several freeze-thaw cycles and extruded to produce uni-laminar ‘phantom cells’ of various sizes.

Toward detecting and identifying macromolecules in a cellular context: template matching applied to electron tomograms.

Electron tomography is the only technique available that allows us to visualize the three-dimensional structure of unfixed and unstained cells currently with a resolution of 6-8 nm, but with the prospect to reach 2-4 nm. This raises the possibility of detecting and identifying specific macromolecular complexes within their cellular context by virtue of their structural signature. Templates derived from the high-resolution structure of the molecule under scrutiny are used to search the reconstructed volume. Here we outline and test a computationally feasible two-step procedure: In a first step, mean-curvature motion is used for segmentation, yielding subvolumes that contain with a high probability macromolecules in the expected size range. Subsequently, the particles contained in the subvolumes are identified by cross-correlation, using a set of three-dimensional templates. With simulated and real tomographic data we demonstrate that such an approach is feasible and we explore the detection limits. Even structurally similar particles, such as the thermosome, GroEL, and the 20S proteasome can be identified with high fidelity. This opens up exciting prospects for mapping the territorial distribution of macromolecules and for analyzing molecular interactions in situ.

The theoretical basis of electron emission holography and tomography

We investigate the theoretical foundation of electron emission holography for surface structure analysis by using the Lippmann-Schwinger integral equation to examine the reconstruction integral for electron holography. We elucidate the physical content of single-energy electron emission holograms and demonstrate the non-uniqueness of the holographic image. We examine the physical meaning of images obtained by the coherent superposition of multi-energy holograms in the weak scattering limit. We show that the coherent superposition of holographic image fields is an electron tomogram of the scattering potential. This establishes close connection between recently proposed methods for image improvement in electron holography and conventional image reconstruction schemes by computerized tomography. An optimal reconstruction algorithm, which retrieves a 3D image of the scattering potential in the weak scattering limit, is proposed.