Daniel Baum

Automated Segmentation of Electron Tomograms for a Quantitative Description of Actin Filament Networks

Cryo-electron tomography allows to visualize individual actin filaments and to describe the three-dimensional organization of actin networks in the context of unperturbed cellular environments. For a quantitative characterization of actin filament networks, the tomograms must be segmented in a reproducible manner. Here, we describe an automated procedure for the segmentation of actin filaments, which combines template matching with a new tracing algorithm. The result is a set of lines, each one representing the central line of a filament. As demonstrated with cryo-tomograms of cellular actin networks, these line sets can be used to characterize filament networks in terms of filament length, orientation, density, stiffness (persistence length), or the occurrence of branching points.

Voronoi-Based Extraction and Visualization of Molecular Paths

Visual analysis is widely used to study the behavior of molecules. Of particular interest are the analysis of molecular interactions and the investigation of binding sites. For large molecules, however, it is difficult to detect possible binding sites and paths leading to these sites by pure visual inspection. In this paper, we present new methods for the computation and visualization of potential molecular paths. Using a novel filtering method, we extract the significant paths from the Voronoi diagram of spheres. For the interactive visualization of molecules and their paths, we present several methods using deferred shading and other state-of-theart techniques. To allow for a fast overview of reachable regions of the molecule, we illuminate the molecular surface using a large number of light sources placed on the extracted paths. We also provide a method to compute the extension surface of selected paths and visualize it using the skin surface. Furthermore, we use the extension surface to clip the molecule to allow easy visual tracking of even deeply buried paths. The methods are applied to several proteins to demonstrate their usefulness.

Accelerated visualization of dynamic molecular surfaces

Molecular surfaces play an important role in studying the interactions between molecules. Visualizing the dynamic behavior of molecules is particularly interesting to gain insights into a molecular system. Only recently it has become possible to interactively visualize dynamic molecular surfaces using ray casting techniques.

Automated tracing of microtubules in electron tomograms of plastic embedded samples of Caenorhabditis elegans embryos.

The ability to rapidly assess microtubule number in 3D image stacks from electron tomograms is essential for collecting statistically meaningful data sets. Here we implement microtubule tracing using 3D template matching. We evaluate our results by comparing the automatically traced centerlines to manual tracings in a large number of electron tomograms of the centrosome of the early Caenorhabditis elegans embryo. Furthermore, we give a qualitative description of the tracing results for three other types of samples. For dual-axis tomograms, the automatic tracing yields 4% false negatives and 8% false positives on average. For single-axis tomograms, the accuracy of tracing is lower (16% false negatives and 14% false positives) due to the missing wedge in electron tomography. We also implemented an editor specifically designed for correcting the automatic tracing. Besides, this editor can be used for annotating microtubules. The automatic tracing together with a manual correction significantly reduces the amount of manual labor for tracing microtubule centerlines so that large-scale analysis of microtubule network properties becomes feasible.

Interactive Rendering of Materials and Biological Structures on Atomic and Nanoscopic Scale

The properties of both inorganic and organic materials and the function of biological structures can often only be understood by analyzing them simultaneously on atomic and nanoscopic, if not mesoscopic, scale. Here, the problem arises to render millions to billions of atoms. We propose a method by which it is possible to interactively visualize atomic data, bridging five orders of magnitude in length scale. For this, we propose a simple yet efficient GPU rendering method that enables interactive visualization of biological structures consisting of up to several billions of atoms. To be able to load all atomic data onto the GPU, we exploit the fact that biological structures often consist of recurring molecular substructures. We also exploit that these objects typically are rendered opaquely, so that only a fraction of the atoms is visible. The method is demonstrated on both biological structures as well as atom probe tomography data of an inorganic specimen. We conclude with a discussion about when ‐during ascension from atomic to mesoscopic scale – level‐of‐detail representations become necessary.

Membrane Protein Structure, Function and Dynamics: A Perspective from Experiments and Theory

Membrane proteins mediate processes that are fundamental for the flourishing of biological cells. Membrane-embedded transporters move ions and larger solutes across membranes; receptors mediate communication between the cell and its environment and membrane-embedded enzymes catalyze chemical reactions. Understanding these mechanisms of action requires knowledge of how the proteins couple to their fluid, hydrated lipid membrane environment. We present here current studies in computational and experimental membrane protein biophysics, and show how they address outstanding challenges in understanding the complex environmental effects on the structure, function, and dynamics of membrane proteins.

Exploring cavity dynamics in biomolecular systems

BackgroundThe internal cavities of proteins are dynamic structures and their dynamics may be associated with conformational changes which are required for the functioning of the protein. In order to study the dynamics of these internal protein cavities, appropriate tools are required that allow rapid identification of the cavities as well as assessment of their time-dependent structures.ResultsIn this paper, we present such a tool and give results that illustrate the applicability for the analysis of molecular dynamics trajectories. Our algorithm consists of a pre-processing step where the structure of the cavity is computed from the Voronoi diagram of the van der Waals spheres based on coordinate sets from the molecular dynamics trajectory. The pre-processing step is followed by an interactive stage, where the user can compute, select and visualize the dynamic cavities. Importantly, the tool we discuss here allows the user to analyze the time-dependent changes of the components of the cavity structure. An overview of the cavity dynamics is derived by rendering the dynamic cavities in a single image that gives the cavity surface colored according to its time-dependent dynamics.ConclusionThe Voronoi-based approach used here enables the user to perform accurate computations of the geometry of the internal cavities in biomolecules. For the first time, it is possible to compute dynamic molecular paths that have a user-defined minimum constriction size. To illustrate the usefulness of the tool for understanding protein dynamics, we probe the dynamic structure of internal cavities in the bacteriorhodopsin proton pump.

Dynamic channels in biomolecular systems: Path analysis and visualization

Analysis of protein dynamics suggests that internal cavities and channels can be rather dynamic structures. Here, we present a Voronoi-based algorithm to extract the geometry and the dynamics of cavities and channels from a molecular dynamics trajectory. The algorithm requires a pre-processing step in which the Voronoi diagram of the van der Waals spheres is used to calculate the cavity structure for each coordinate set of the trajectory. In the next step, we interactively compute dynamic channels by analyzing the time evolution of components of the cavity structure. Tracing of the cavity dynamics is supported by timeline visualization tools that allow the user to select specific components of the cavity structures for detailed exploration. All visualization methods are interactive and enable the user to animate the time-dependent molecular structure together with its cavity structure. To facilitate a comprehensive overview of the dynamics of a channel, we have also developed a visualization technique that renders a dynamic channel in a single image and color-codes time on its extension surface. We illustrate the usefullness of our tools by inspecting the structure and dynamics of internal cavities in the bacteriorhodopsin proton pump.

Visualization of Biomolecular Structures: State of the Art

Structural properties of molecules are of primary concern in many fields. This report provides a comprehensive overview on techniques that have been developed in the fields of molecular graphics and visualization with a focus on applications in structural biology. The field heavily relies on computerized geometric and visual representations of three-dimensional, complex, large, and time-varying molecular structures. The report presents a taxonomy that demonstrates which areas of molecular visualization have already been extensively investigated and where the field is currently heading. It discusses visualizations for molecular structures, strategies for efficient display regarding image quality and frame rate, covers different aspects of level of detail, and reviews visualizations illustrating the dynamic aspects of molecular simulation data. The report concludes with an outlook on promising and important research topics to enable further success in advancing the knowledge about interaction of molecular structures.

Visual analysis of biomolecular cavities: state of the art

In this report we review and structure the branch of molecular visualization that is concerned with the visual analysis of cavities in macromolecular protein structures. First the necessary background, the domain terminology, and the goals of analytical reasoning are introduced. Based on a comprehensive collection of relevant research works, we present a novel classification for cavity detection approaches and structure them into four distinct classes: grid‐based, Voronoi‐based, surface‐based, and probe‐based methods. The subclasses are then formed by their combinations. We match these approaches with corresponding visualization technologies starting with direct 3D visualization, followed with non‐spatial visualization techniques that for example abstract the interactions between structures into a relational graph, straighten the cavity of interest to see its profile in one view, or aggregate the time sequence into a single contour plot. We also discuss the current state of methods for the visual analysis of cavities in dynamic data such as molecular dynamics simulations. Finally, we give an overview of the most common tools that are actively developed and used in the structural biology and biochemistry research. Our report is concluded by an outlook on future challenges in the field.