Automatic ultrastructure segmentation of reconstructed cryoEM maps of icosahedral viruses

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.

3D membrane segmentation and quantification of intact thick cells using cryo soft X-ray transmission microscopy: A pilot study

Structural analysis of biological membranes is important for understanding cell and sub-cellular organelle function as well as their interaction with the surrounding environment. Imaging of whole cells in three dimension at high spatial resolution remains a significant challenge, particularly for thick cells. Cryo-transmission soft X-ray microscopy (cryo-TXM) has recently gained popularity to image, in 3D, intact thick cells (∼10μm) with details of sub-cellular architecture and organization in near-native state. This paper reports a new tool to segment and quantify structural changes of biological membranes in 3D from cryo-TXM images by tracking an initial 2D contour along the third axis of the microscope, through a multi-scale ridge detection followed by an active contours-based model, with a subsequent refinement along the other two axes. A quantitative metric that assesses the grayscale profiles perpendicular to the membrane surfaces is introduced and shown to be linearly related to the membrane thickness. Our methodology has been validated on synthetic phantoms using realistic microscope properties and structure dimensions, as well as on real cryo-TXM data. Results demonstrate the validity of our algorithms for cryo-TXM data analysis.

High-resolution cryo-electron microscopy structure of the Trypanosoma brucei ribosome

Ribosomes, the protein factories of living cells, translate genetic information carried by messenger RNAs into proteins, and are thus involved in virtually all aspects of cellular development and maintenance. The few available structures of the eukaryotic ribosome reveal that it is more complex than its prokaryotic counterpart, owing mainly to the presence of eukaryote-specific ribosomal proteins and additional ribosomal RNA insertions, called expansion segments. The structures also differ among species, partly in the size and arrangement of these expansion segments. Such differences are extreme in kinetoplastids, unicellular eukaryotic parasites often infectious to humans. Here we present a high-resolution cryo-electron microscopy structure of the ribosome of Trypanosoma brucei, the parasite that is transmitted by the tsetse fly and that causes African sleeping sickness. The atomic model reveals the unique features of this ribosome, characterized mainly by the presence of unusually large expansion segments and ribosomal-protein extensions leading to the formation of four additional inter-subunit bridges. We also find additional rRNA insertions, including one large rRNA domain that is not found in other eukaryotes. Furthermore, the structure reveals the five cleavage sites of the kinetoplastid large ribosomal subunit (LSU) rRNA chain, which is known to be cleaved uniquely into six pieces, and suggests that the cleavage is important for the maintenance of the T. brucei ribosome in the observed structure. We discuss several possible implications of the large rRNA expansion segments for the translation-regulation process. The structure could serve as a basis for future experiments aimed at understanding the functional importance of these kinetoplastid-specific ribosomal features in protein-translation regulation, an essential step towards finding effective and safe kinetoplastid-specific drugs.

Nhs: network-based hierarchical segmentation for cryo-electron microscopy density maps

Cryo-electron microscopy (cryo-EM) experiments yield low-resolution (3-30 Å) 3D-density maps of macromolecules. These density maps are segmented to identify structurally distinct proteins, protein domains, and subunits. Such partitioning aids the inference of protein motions and guides fitting of high-resolution atomistic structures. Cryo-EM density map segmentation has traditionally required tedious and subjective manual partitioning or semisupervised computational methods, whereas validation of resulting segmentations has remained an open problem in this field. We introduce a network-based hierarchical segmentation (Nhs) method, that provides a multi-scale partitioning, reflecting local and global clustering, while requiring no user input. This approach models each map as a graph, where map voxels constitute nodes and weighted edges connect neighboring voxels. Nhs initiates Markov diffusion (or random walk) on the weighted graph. As Markov probabilities homogenize through diffusion, an intrinsic segmentation emerges. We validate the segmentations with ground-truth maps based on atomistic models. When implemented on density maps in the 2010 Cryo-EM Modeling Challenge, Nhs efficiently and objectively partitions macromolecules into structurally and functionally relevant subregions at multiple scales.

Macromolecular structure modeling from 3D EM using VolRover 2.0

We review tools for structure identification and model-based refinement from three-dimensional electron microscopy implemented in our in-house software package, VOLROVER 2.0. For viral density maps with icosahedral symmetry, we segment the capsid, polymeric, and monomeric subunits using techniques based on automatic symmetry detection and multidomain fast marching. For large biomolecules without symmetry information, we again use our multidomain fast-marching method with manual or fit-based multiseeding to segment meaningful substructures. In either case, we subject the resulting segmented subunit to secondary structure detection when the EM resolution is sufficiently high, and rigid-body structure fitting when the corresponding X-ray structure is available. Secondary structure elements are identified by three techniques: our earlier volume-based and boundary-based skeletonization methods as well as a new method, currently in development, based on solving the grassfire flow equation. For rigid-body fitting, we adapt our earlier fast Fourier-based correlation scheme F2Dock. Our reported segmentation, secondary structure elements identification, and rigid-body fitting techniques, implemented in VOLROVER 2.0 are applied to the PSB 2011 cryo-EM modeling challenge data, and our results are briefly compared to similar results submitted from other research groups. The comparisons show that our techniques are equally capable of segmenting relatively accurate subunits from a viral or protein assembly, and that high segmentation quality leads in turn to higher-quality results of secondary structure elements identification and correlation-based rigid-body fitting. © 2012 Wiley Periodicals, Inc. Biopolymers 97: 709-731, 2012.

RENNSH: a novel α-helix identification approach for intermediate resolution electron density maps

Accurate identification of protein secondary structures is beneficial to understand three-dimensional structures of biological macromolecules. In this paper, a novel refined classification framework is proposed, which treats alpha-helix identification as a machine learning problem by representing each voxel in the density map with its Spherical Harmonic Descriptors (SHD). An energy function is defined to provide statistical analysis of its identification performance, which can be applied to all the α-helix identification approaches. Comparing with other existing α-helix identification methods for intermediate resolution electron density maps, the experimental results demonstrate that our approach gives the best identification accuracy and is more robust to the noise.

Detection of secondary and supersecondary structures of proteins from cryo-electron microscopy

Recent advances in three-dimensional electron microscopy (3D EM) have enabled the quantitative visualization of the structural building blocks of proteins at improved resolutions. We provide algorithms to detect the secondary structures (α-helices and β-sheets) from proteins for which the volumetric maps are reconstructed at 6-10Å resolution. Additionally, we show that when the resolution is coarser than 10Å, some of the supersecondary structures can be detected from 3D EM maps. For both these algorithms, we employ tools from computational geometry and differential topology, specifically the computation of stable/unstable manifolds of certain critical points of the distance function induced by the molecular surface. Our results connect mathematically well-defined constructions with bio-chemically induced structures observed in proteins.

Edged watershed segmentation: a semi-interactive algorithm for segmentation of low-resolution maps from electron cryomicroscopy

Electron cryomicroscopy (cryo-EM) allows for the structural analysis of large protein complexes that may be difficult to study by other means. Frequently, maps of complexes from cryo-EM are obtained at resolutions between 10 and 25Å. To aid in the interpretation of these medium- to low-resolution maps, they may be subdivided into three-dimensional segments representing subunits or subcomplexes. This division is often accomplished using a manual segmentation approach. While extremely useful, manual segmentation is subjective. We have developed a novel semi-interactive segmentation algorithm that can incorporate prior knowledge of subunit composition or structure without biasing the boundaries between subunits or subcomplexes. This algorithm has been characterized with experimental and simulated cryo-EM density maps at resolutions between 10 and 25Å.

Multiclass maximum-likelihood symmetry determination and motif reconstruction of 3-D helical objects from projection images for electron microscopy

Many micro- to nano-scale 3-D biological objects have a helical symmetry. Cryo electron microscopy provides 2-D projection images where, however, the images have low SNR and unknown projection directions. The object is described as a helical array of identical motifs, where both the parameters of the helical symmetry and the motif are unknown. Using a detailed image formation model, a maximum-likelihood estimator for the parameters of the symmetry and the 3-D motif based on images of many objects and algorithms for computing the estimate are described. The possibility that the objects are not identical but rather come from a small set of homogeneous classes is included. The first example is based on 316 128 × 100 pixel experimental images of Tobacco Mosaic Virus, has one class, and achieves 12.40-Å spatial resolution in the reconstruction. The second example is based on 400 128 × 128 pixel synthetic images of helical objects constructed from NaK ion channel pore macromolecular complexes, has two classes differing in helical symmetry, and achieves 7.84- and 7.90-Å spatial resolution in the reconstructions for the two classes.

Biomedical image segmentation via constrained graph cuts and pre-segmentation

In this paper we present a high-fidelity method for 2D and 3D image boundary segmentation. The algorithm is a novel combination of graph-cuts and initial image segmentation. The pre-segmentation using anisotropic vector diffusion and the fast marching method is employed so that the size of the graph being considered is significantly reduced. To further improve the segmentation accuracy, some user guidance is taken into account in finding the minimal graph cut. To this end, a user-friendly graphical user interface (GUI) is developed not only for visualization purposes but for user input and editing as well. The approaches and tools developed are validated on a number of 2D/3D biomedical imaging data, showing the high efficiency and effectiveness of our method.

Quality Multi-domain Meshing for Volumetric Data

Multi-domain meshing from volumetric data is of great importance in many fields like medicine, biology and geology. This paper proposes a new approach to produce a high quality mesh with separated multiple domains. A point cloud is generated from a preliminary mesh representing the boundary between different domains from the discrete volumetric representation used as input. A higher-order level-set method is employed to produce a quality sub-mesh from this point cloud and geometric flow is used as smoothing mechanism. A new approach to detect and curate intersections within an assembly of these 2-manifold sub-meshes by utilizing the intermediate volumetric representation is developed. The separation between sub-meshes can be controlled by the user using a gap threshold parameter. The resulting high quality multi-domain mesh is free from self- and inter-domain intersections and can be further utilized in finite element and boundary element computations. The proposed pipeline has been efficiently implemented and sample meshes have been provided for visualization.

Variational image segmentation for endoscopic human colonic aberrant crypt foci

The aim of this paper is to introduce a variational image segmentation method for assessing the aberrant crypt foci (ACF) in the human colon captured in vivo by endoscopy. ACF are thought to be precursors for colorectal cancer, and therefore their early detection may play an important clinical role. We enhance the active contours without edges model of Chan and Vese to account for the ACF's particular structure. We employ level sets to represent the segmentation boundaries and discretize in space by finite elements and in (artificial) time by finite differences. The approach is able to identify the ACF, their boundaries, and some of the internal crypts' orifices.

A multiscale model for virus capsid dynamics

Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows.

An Automatic 3D Mesh Generation Method for Domains with Multiple Materials

This paper describes an automatic and efficient approach to construct unstructured tetrahedral and hexahedral meshes for a composite domain made up of heterogeneous materials. The boundaries of these material regions form non-manifold surfaces. In earlier papers, we developed an octree-based isocontouring method to construct unstructured 3D meshes for a single-material (homogeneous) domain with manifold boundary. In this paper, we introduce the notion of a material change edge and use it to identify the interface between two or several different materials. A novel method to calculate the minimizer point for a cell shared by more than two materials is provided, which forms a non-manifold node on the boundary. We then mesh all the material regions simultaneously and automatically while conforming to their boundaries directly from volumetric data. Both material change edges and interior edges are analyzed to construct tetrahedral meshes, and interior grid points are analyzed for proper hexahedral mesh construction. Finally, edge-contraction and smoothing methods are used to improve the quality of tetrahedral meshes, and a combination of pillowing, geometric flow and optimization techniques is used for hexahedral mesh quality improvement. The shrink set of pillowing schemes is defined automatically as the boundary of each material region. Several application results of our multi-material mesh generation method are also provided.

Interpretation of very low resolution X-ray electron-density maps using core objects

A novel approach to obtaining structural information from macromolecular X-ray data extending to resolutions as low as 20 A is presented. Following a simple map-segmentation procedure, the approximate shapes of the domains forming the structure are identified. A pattern-recognition comparative analysis of these shapes and those derived from the structures of domains from the PDB results in candidate structural models that can be used for a fit into the density map. It is shown that the placed candidate models can be employed for subsequent phase extension to higher resolution.

Topology Based Selection and Curation of Level Sets

The selection of appropriate level sets for the quantitative visualization of three dimensional imaging or simulation data is a problem that is both fundamental and essential. The selected level set needs to satisfy several topological and geometric constraints to be useful for subsequent quantitative processing and visualization. For an initial selection of an isosurface, guided by contour tree data structures, we detect the topological features by computing stable and unstable manifolds of the critical points of the distance function induced by the isosurface. We further enhance the description of these features by associating geometric attributes with them. We then rank the attributed features and provide a handle to them for curation of the topological anomalies.

The capsid proteins of a large, icosahedral dsDNA virus

Chilo iridescent virus (CIV) is a large (approximately 1850 A diameter) insect virus with an icosahedral, T=147 capsid, a double-stranded DNA (dsDNA) genome, and an internal lipid membrane. The structure of CIV was determined to 13 A resolution by means of cryoelectron microscopy (cryoEM) and three-dimensional image reconstruction. A homology model of P50, the CIV major capsid protein (MCP), was built based on its amino acid sequence and the structure of the homologous Paramecium bursaria chlorella virus 1 Vp54 MCP. This model was fitted into the cryoEM density for each of the 25 trimeric CIV capsomers per icosahedral asymmetric unit. A difference map, in which the fitted CIV MCP capsomers were subtracted from the CIV cryoEM reconstruction, showed that there are at least three different types of minor capsid proteins associated with the capsomers outside the lipid membrane. "Finger" proteins are situated at many, but not all, of the spaces between three adjacent capsomers within each trisymmetron, and "zip" proteins are situated between sets of three adjacent capsomers at the boundary between neighboring trisymmetrons and pentasymmetrons. Based on the results of segmentation and density correlations, there are at least eight finger proteins and three dimeric and two monomeric zip proteins in one asymmetric unit of the CIV capsid. These minor proteins appear to stabilize the virus by acting as intercapsomer cross-links. One transmembrane "anchor" protein per icosahedral asymmetric unit, which extends from beneath one of the capsomers in the pentasymmetron to the internal leaflet of the lipid membrane, may provide additional stabilization for the capsid. These results are consistent with the observations for other large, icosahedral dsDNA viruses that also utilize minor capsid proteins for stabilization and for determining their assembly.

Computational approaches for automatic structural analysis of large biomolecular complexes

We present computational solutions to two problems of macromolecular structure interpretation from reconstructed three-dimensional electron microscopy (3D-EM) maps of large bio-molecular complexes at intermediate resolution (5A-15 A). The two problems addressed are: 1) 3D structural alignment (matching) between identified and segmented 3D maps of structure units (e.g. trimeric configuration of proteins), and 2) the secondary structure identification of a segmented protein 3D map (i.e.locations of alpha-helices, beta-sheets). For problem 1, we present an efficient algorithm to correlate spatially (and structurally) two 3D maps of structure units. Besides providing a similarity score between structure units, the algorithm yields an effective technique for resolution refinement of repeated structure units, by 3D alignment and averaging. For problem 2, we present an efficient algorithm to compute eigenvalues and link eigenvectors of a Gaussian convoluted structure tensor derived from the protein 3D Map, thereby identifying and locating secondary structural motifs of proteins. The efficiency and performance of our approach is demonstrated on several experimentally reconstructed 3D maps of virus capsid shells from single-particle cryo-electron microscopy (cryo-EM), as well as computationally simulated protein structure density 3D maps generated from protein model entries in the Protein Data Bank.

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.

DNA poised for release in bacteriophage phi29

We present here the first asymmetric, three-dimensional reconstruction of a tailed dsDNA virus, the mature bacteriophage phi29, at subnanometer resolution. This structure reveals the rich detail of the asymmetric interactions and conformational dynamics of the phi29 protein and DNA components, and provides novel insight into the mechanics of virus assembly. For example, the dodecameric head-tail connector protein undergoes significant rearrangement upon assembly into the virion. Specific interactions occur between the tightly packed dsDNA and the proteins of the head and tail. Of particular interest and novelty, an approximately 60A diameter toroid of dsDNA was observed in the connector-lower collar cavity. The extreme deformation that occurs over a small stretch of DNA is likely a consequence of the high pressure of the packaged genome. This toroid structure may help retain the DNA inside the capsid prior to its injection into the bacterial host.

Visualization software for molecular assemblies

Software for viewing three-dimensional models and maps of viruses, ribosomes, filaments, and other molecular assemblies is advancing on many fronts. New developments include molecular representations that offer better control over level of detail, lighting that improves the perception of depth, and two-dimensional projections that simplify data interpretation. Programmable graphics processors offer quality, speed, and visual effects not previously possible, while 3D printers, haptic interaction devices, and auto-stereo displays show promise in more naturally engaging our senses. Visualization methods are developed by diverse groups of researchers with differing goals: experimental biologists, database developers, computer scientists, and package developers. We survey recent developments and problems faced by the developer community in bringing innovative visualization methods into widespread use.

AUTOMATIC STRUCTURE INTERPRETATION OF SINGLE PARTICLE CRYO-ELECTRON MICROSCOPY: FROM IMAGES TO PSUEDO-ATOMIC MODELS

Three dimensional Electron Microscopy (EM) and in particular single particle reconstruction using cryo-EM, has rapidly advanced over recent years, such that increasingly several macromolecular complexes can be resolved at subnanometer resolution (6-10 Å). This paper reviews some of the main volumetric image and geometric post-processing steps once a three dimensional EM map (henceforth a 3D map) has been reconstructed from single particle Cryo-EM, as essential steps in an enhanced and automated computational structure interpretation pipeline. In particular the paper addresses automated filtering, critical point calculations, symmetric and non-symmetric molecular domain segmentation, molecular surface selection, curation, and protein secondary structure (α- helices and β-sheets) elucidation from 3D maps.

Multi-resolution anchor-point registration of biomolecular assemblies and their components

An atomic scale interpretation facilitates the assignment of functional properties to 3D reconstructions of macromolecular assemblies in electron microscopy (EM). Such a high-resolution interpretation is typically achieved by docking the known atomic structures of components into the volumetric EM maps. Docking locations are often determined by maximizing the cross-correlation coefficient of the two objects in a slow, exhaustive search. If time is of essence, such as in related visualization and image processing fields, the matching of data is accelerated by incorporating feature points that form a compact description of 3D objects. The complexity reduction afforded by the feature point representation enables a near-instantaneous matching. We show that such reduced matching can also deliver robust and accurate results in the presence of noise or artifacts. We therefore propose a novel multi-resolution registration technique employing feature-based shape descriptions of the volumetric and structural data. The pattern-matching algorithm carries out a hierarchical alignment of the point sets generated by vector quantization. The search-space complexity is reduced by an integrated tree-pruning technique, which permits the detection of subunits in large macromolecular assemblies in real-time. The efficiency and accuracy of the novel algorithm are validated on a standard test system of homo-oligomeric assemblies.

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.