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Pubmed Article
UFSRAT: Ultra-fast Shape Recognition with Atom Types--the discovery of novel bioactive small molecular scaffolds for FKBP12 and 11?HSD1.
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PLoS ONE
PUBLISHED: 02-09-2015
Using molecular similarity to discover bioactive small molecules with novel chemical scaffolds can be computationally demanding. We describe Ultra-fast Shape Recognition with Atom Types (UFSRAT), an efficient algorithm that considers both the 3D distribution (shape) and electrostatics of atoms to score and retrieve molecules capable of making similar interactions to those of the supplied query.
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Published: 07-25-2013
ABSTRACT
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
21 Related JoVE Articles!
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Interview: Bioreactors and Surfaced-Modified 3D-Scaffolds for Stem Cell Research
Authors: Karl-Friedrich Weibezahn.
Institutions: Karlsruhe Institute of Technology.
A Nature Editorial in 2003 asked the question "Good-bye, flat biology?" What does this question imply? In the past, many in vitro culture systems, mainly monolayer cultures, often suffered from the disadvantage that differentiated primary cells had a relatively short life-span and de-differentiated during culture. As a consequence, most of their organ-specific functions were lost rapidly. Thus, in order to reproduce better conditions for these cells in vitro, modifications and adaptations have been made to conventional monolayer cultures. The last generation of CellChips -- micro-thermoformed containers -- a specific technology was developed, which offers the additional possibility to modify the whole surface of the 3D formed containers. This allows a surface-patterning on a submicron scale with distinct signalling molecules. Sensors and signal electrodes may be incorporated. Applications range from basic research in cell biology to toxicology and pharmacology. Using biodegradable polymers, clinical applications become a possibility. Furthermore, the last generation of micro-thermoformed chips has been optimized to allow for cheap mass production.
Cellular Biology, Issue 15, Interview, bioreactors, cell culture systems, 3D cell culture, stem cells
792
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Optimized Negative Staining: a High-throughput Protocol for Examining Small and Asymmetric Protein Structure by Electron Microscopy
Authors: Matthew Rames, Yadong Yu, Gang Ren.
Institutions: The Molecular Foundry.
Structural determination of proteins is rather challenging for proteins with molecular masses between 40 - 200 kDa. Considering that more than half of natural proteins have a molecular mass between 40 - 200 kDa1,2, a robust and high-throughput method with a nanometer resolution capability is needed. Negative staining (NS) electron microscopy (EM) is an easy, rapid, and qualitative approach which has frequently been used in research laboratories to examine protein structure and protein-protein interactions. Unfortunately, conventional NS protocols often generate structural artifacts on proteins, especially with lipoproteins that usually form presenting rouleaux artifacts. By using images of lipoproteins from cryo-electron microscopy (cryo-EM) as a standard, the key parameters in NS specimen preparation conditions were recently screened and reported as the optimized NS protocol (OpNS), a modified conventional NS protocol 3 . Artifacts like rouleaux can be greatly limited by OpNS, additionally providing high contrast along with reasonably high‐resolution (near 1 nm) images of small and asymmetric proteins. These high-resolution and high contrast images are even favorable for an individual protein (a single object, no average) 3D reconstruction, such as a 160 kDa antibody, through the method of electron tomography4,5. Moreover, OpNS can be a high‐throughput tool to examine hundreds of samples of small proteins. For example, the previously published mechanism of 53 kDa cholesteryl ester transfer protein (CETP) involved the screening and imaging of hundreds of samples 6. Considering cryo-EM rarely successfully images proteins less than 200 kDa has yet to publish any study involving screening over one hundred sample conditions, it is fair to call OpNS a high-throughput method for studying small proteins. Hopefully the OpNS protocol presented here can be a useful tool to push the boundaries of EM and accelerate EM studies into small protein structure, dynamics and mechanisms.
Environmental Sciences, Issue 90, small and asymmetric protein structure, electron microscopy, optimized negative staining
51087
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Synthesis of an Intein-mediated Artificial Protein Hydrogel
Authors: Miguel A. Ramirez, Zhilei Chen.
Institutions: Texas A&M University, College Station, Texas A&M University, College Station.
We present the synthesis of a highly stable protein hydrogel mediated by a split-intein-catalyzed protein trans-splicing reaction. The building blocks of this hydrogel are two protein block-copolymers each containing a subunit of a trimeric protein that serves as a crosslinker and one half of a split intein. A highly hydrophilic random coil is inserted into one of the block-copolymers for water retention. Mixing of the two protein block copolymers triggers an intein trans-splicing reaction, yielding a polypeptide unit with crosslinkers at either end that rapidly self-assembles into a hydrogel. This hydrogel is very stable under both acidic and basic conditions, at temperatures up to 50 °C, and in organic solvents. The hydrogel rapidly reforms after shear-induced rupture. Incorporation of a "docking station peptide" into the hydrogel building block enables convenient incorporation of "docking protein"-tagged target proteins. The hydrogel is compatible with tissue culture growth media, supports the diffusion of 20 kDa molecules, and enables the immobilization of bioactive globular proteins. The application of the intein-mediated protein hydrogel as an organic-solvent-compatible biocatalyst was demonstrated by encapsulating the horseradish peroxidase enzyme and corroborating its activity.
Bioengineering, Issue 83, split-intein, self-assembly, shear-thinning, enzyme, immobilization, organic synthesis
51202
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Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis
Authors: Benjamin N. Doblack, Tim Allis, Lilian P. Dávila.
Institutions: University of California Merced.
The increasing development of computing (hardware and software) in the last decades has impacted scientific research in many fields including materials science, biology, chemistry and physics among many others. A new computational system for the accurate and fast simulation and 3D/VR visualization of nanostructures is presented here, using the open-source molecular dynamics (MD) computer program LAMMPS. This alternative computational method uses modern graphics processors, NVIDIA CUDA technology and specialized scientific codes to overcome processing speed barriers common to traditional computing methods. In conjunction with a virtual reality system used to model materials, this enhancement allows the addition of accelerated MD simulation capability. The motivation is to provide a novel research environment which simultaneously allows visualization, simulation, modeling and analysis. The research goal is to investigate the structure and properties of inorganic nanostructures (e.g., silica glass nanosprings) under different conditions using this innovative computational system. The work presented outlines a description of the 3D/VR Visualization System and basic components, an overview of important considerations such as the physical environment, details on the setup and use of the novel system, a general procedure for the accelerated MD enhancement, technical information, and relevant remarks. The impact of this work is the creation of a unique computational system combining nanoscale materials simulation, visualization and interactivity in a virtual environment, which is both a research and teaching instrument at UC Merced.
Physics, Issue 94, Computational systems, visualization and immersive environments, interactive learning, graphical processing unit accelerated simulations, molecular dynamics simulations, nanostructures.
51384
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
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.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
51673
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A Manual Small Molecule Screen Approaching High-throughput Using Zebrafish Embryos
Authors: Shahram Jevin Poureetezadi, Eric K. Donahue, Rebecca A. Wingert.
Institutions: University of Notre Dame.
Zebrafish have become a widely used model organism to investigate the mechanisms that underlie developmental biology and to study human disease pathology due to their considerable degree of genetic conservation with humans. Chemical genetics entails testing the effect that small molecules have on a biological process and is becoming a popular translational research method to identify therapeutic compounds. Zebrafish are specifically appealing to use for chemical genetics because of their ability to produce large clutches of transparent embryos, which are externally fertilized. Furthermore, zebrafish embryos can be easily drug treated by the simple addition of a compound to the embryo media. Using whole-mount in situ hybridization (WISH), mRNA expression can be clearly visualized within zebrafish embryos. Together, using chemical genetics and WISH, the zebrafish becomes a potent whole organism context in which to determine the cellular and physiological effects of small molecules. Innovative advances have been made in technologies that utilize machine-based screening procedures, however for many labs such options are not accessible or remain cost-prohibitive. The protocol described here explains how to execute a manual high-throughput chemical genetic screen that requires basic resources and can be accomplished by a single individual or small team in an efficient period of time. Thus, this protocol provides a feasible strategy that can be implemented by research groups to perform chemical genetics in zebrafish, which can be useful for gaining fundamental insights into developmental processes, disease mechanisms, and to identify novel compounds and signaling pathways that have medically relevant applications.
Developmental Biology, Issue 93, zebrafish, chemical genetics, chemical screen, in vivo small molecule screen, drug discovery, whole mount in situ hybridization (WISH), high-throughput screening (HTS), high-content screening (HCS)
52063
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Fabricating Complex Culture Substrates Using Robotic Microcontact Printing (R-µCP) and Sequential Nucleophilic Substitution
Authors: Gavin T. Knight, Tyler Klann, Jason D. McNulty, Randolph S. Ashton.
Institutions: University of Wisconsin, Madison, University of Wisconsin, Madison.
In tissue engineering, it is desirable to exhibit spatial control of tissue morphology and cell fate in culture on the micron scale. Culture substrates presenting grafted poly(ethylene glycol) (PEG) brushes can be used to achieve this task by creating microscale, non-fouling and cell adhesion resistant regions as well as regions where cells participate in biospecific interactions with covalently tethered ligands. To engineer complex tissues using such substrates, it will be necessary to sequentially pattern multiple PEG brushes functionalized to confer differential bioactivities and aligned in microscale orientations that mimic in vivo niches. Microcontact printing (μCP) is a versatile technique to pattern such grafted PEG brushes, but manual μCP cannot be performed with microscale precision. Thus, we combined advanced robotics with soft-lithography techniques and emerging surface chemistry reactions to develop a robotic microcontact printing (R-μCP)-assisted method for fabricating culture substrates with complex, microscale, and highly ordered patterns of PEG brushes presenting orthogonal ‘click’ chemistries. Here, we describe in detail the workflow to manufacture such substrates.
Bioengineering, Issue 92, Robotic microcontact printing, R-μCP, click chemistry, surface chemistry, tissue engineering, micropattern, advanced manufacturing
52186
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Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
Authors: Sandra Zehentmeier, Zoltan Cseresnyes, Juan Escribano Navarro, Raluca A. Niesner, Anja E. Hauser.
Institutions: German Rheumatism Research Center, a Leibniz Institute, German Rheumatism Research Center, a Leibniz Institute, Max-Delbrück Center for Molecular Medicine, Wimasis GmbH, Charité - University of Medicine.
Confocal microscopy is the method of choice for the analysis of localization of multiple cell types within complex tissues such as the bone marrow. However, the analysis and quantification of cellular localization is difficult, as in many cases it relies on manual counting, thus bearing the risk of introducing a rater-dependent bias and reducing interrater reliability. Moreover, it is often difficult to judge whether the co-localization between two cells results from random positioning, especially when cell types differ strongly in the frequency of their occurrence. Here, a method for unbiased quantification of cellular co-localization in the bone marrow is introduced. The protocol describes the sample preparation used to obtain histological sections of whole murine long bones including the bone marrow, as well as the staining protocol and the acquisition of high-resolution images. An analysis workflow spanning from the recognition of hematopoietic and non-hematopoietic cell types in 2-dimensional (2D) bone marrow images to the quantification of the direct contacts between those cells is presented. This also includes a neighborhood analysis, to obtain information about the cellular microenvironment surrounding a certain cell type. In order to evaluate whether co-localization of two cell types is the mere result of random cell positioning or reflects preferential associations between the cells, a simulation tool which is suitable for testing this hypothesis in the case of hematopoietic as well as stromal cells, is used. This approach is not limited to the bone marrow, and can be extended to other tissues to permit reproducible, quantitative analysis of histological data.
Developmental Biology, Issue 98, Image analysis, neighborhood analysis, bone marrow, stromal cells, bone marrow niches, simulation, bone cryosectioning, bone histology
52544
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Atomically Traceable Nanostructure Fabrication
Authors: Josh B. Ballard, Don D. Dick, Stephen J. McDonnell, Maia Bischof, Joseph Fu, James H. G. Owen, William R. Owen, Justin D. Alexander, David L. Jaeger, Pradeep Namboodiri, Ehud Fuchs, Yves J. Chabal, Robert M. Wallace, Richard Reidy, Richard M. Silver, John N. Randall, James Von Ehr.
Institutions: Zyvex Labs, University of Texas at Dallas, University of Texas at Dallas, University of North Texas, National Institute of Standards and Technology.
Reducing the scale of etched nanostructures below the 10 nm range eventually will require an atomic scale understanding of the entire fabrication process being used in order to maintain exquisite control over both feature size and feature density. Here, we demonstrate a method for tracking atomically resolved and controlled structures from initial template definition through final nanostructure metrology, opening up a pathway for top-down atomic control over nanofabrication. Hydrogen depassivation lithography is the first step of the nanoscale fabrication process followed by selective atomic layer deposition of up to 2.8 nm of titania to make a nanoscale etch mask. Contrast with the background is shown, indicating different mechanisms for growth on the desired patterns and on the H passivated background. The patterns are then transferred into the bulk using reactive ion etching to form 20 nm tall nanostructures with linewidths down to ~6 nm. To illustrate the limitations of this process, arrays of holes and lines are fabricated. The various nanofabrication process steps are performed at disparate locations, so process integration is discussed. Related issues are discussed including using fiducial marks for finding nanostructures on a macroscopic sample and protecting the chemically reactive patterned Si(100)-H surface against degradation due to atmospheric exposure.
Engineering, Issue 101, Nanolithography, Scanning Tunneling Microscopy, Atomic Layer Deposition, Reactive Ion Etching
52900
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Methods for Studying the Mechanisms of Action of Antipsychotic Drugs in Caenorhabditis elegans
Authors: Limin Hao, Edgar A. Buttner.
Institutions: Harvard Medical School, McLean Hospital.
Caenorhabditis elegans is a simple genetic organism amenable to large-scale forward and reverse genetic screens and chemical genetic screens. The C. elegans genome includes potential antipsychotic drug (APD) targets conserved in humans, including genes encoding proteins required for neurotransmitter synthesis and for synaptic structure and function. APD exposure produces developmental delay and/or lethality in nematodes in a concentration-dependent manner. These phenotypes are caused, in part, by APD-induced inhibition of pharyngeal pumping1,2. Thus, the developmental phenotype has a neuromuscular basis, making it useful for pharmacogenetic studies of neuroleptics. Here we demonstrate detailed procedures for testing APD effects on nematode development and pharyngeal pumping. For the developmental assay, synchronized embryos are placed on nematode growth medium (NGM) plates containing APDs, and the stages of developing animals are then scored daily. For the pharyngeal pumping rate assay, staged young adult animals are tested on NGM plates containing APDs. The number of pharyngeal pumps per unit time is recorded, and the pumping rate is calculated. These assays can be used for studying many other types of small molecules or even large molecules.
Neuroscience, Issue 84, antipsychotic drug, Caenorhabditis elegans, clozapine, developmental delay, lethality, nematode, pharmacogenetics, pharyngeal pumping, schizophrenia
50864
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Microfluidic On-chip Capture-cycloaddition Reaction to Reversibly Immobilize Small Molecules or Multi-component Structures for Biosensor Applications
Authors: Carlos Tassa, Monty Liong, Scott Hilderbrand, Jason E. Sandler, Thomas Reiner, Edmund J. Keliher, Ralph Weissleder, Stanley Y. Shaw.
Institutions: Massachusetts General Hospital.
Methods for rapid surface immobilization of bioactive small molecules with control over orientation and immobilization density are highly desirable for biosensor and microarray applications. In this Study, we use a highly efficient covalent bioorthogonal [4+2] cycloaddition reaction between trans-cyclooctene (TCO) and 1,2,4,5-tetrazine (Tz) to enable the microfluidic immobilization of TCO/Tz-derivatized molecules. We monitor the process in real-time under continuous flow conditions using surface plasmon resonance (SPR). To enable reversible immobilization and extend the experimental range of the sensor surface, we combine a non-covalent antigen-antibody capture component with the cycloaddition reaction. By alternately presenting TCO or Tz moieties to the sensor surface, multiple capture-cycloaddition processes are now possible on one sensor surface for on-chip assembly and interaction studies of a variety of multi-component structures. We illustrate this method with two different immobilization experiments on a biosensor chip; a small molecule, AP1497 that binds FK506-binding protein 12 (FKBP12); and the same small molecule as part of an immobilized and in situ-functionalized nanoparticle.
Chemistry, Issue 79, Organic Chemicals, Macromolecular Substances, Chemistry and Materials (General), Surface Plasmon Resonance, Bioorthogonal Chemistry, Diels-Alder Cycloaddition Reaction, Small Molecule Immobilization, Binding Kinetics, Immobilized Nanoparticles
50772
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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
50680
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A Protocol for Computer-Based Protein Structure and Function Prediction
Authors: Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang.
Institutions: University of Michigan , University of Kansas.
Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.
Biochemistry, Issue 57, On-line server, I-TASSER, protein structure prediction, function prediction
3259
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
3358
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Cellular Lipid Extraction for Targeted Stable Isotope Dilution Liquid Chromatography-Mass Spectrometry Analysis
Authors: Stacy L. Gelhaus, A. Clementina Mesaros, Ian A. Blair.
Institutions: University of Pennsylvania , University of Pennsylvania .
The metabolism of fatty acids, such as arachidonic acid (AA) and linoleic acid (LA), results in the formation of oxidized bioactive lipids, including numerous stereoisomers1,2. These metabolites can be formed from free or esterified fatty acids. Many of these oxidized metabolites have biological activity and have been implicated in various diseases including cardiovascular and neurodegenerative diseases, asthma, and cancer3-7. Oxidized bioactive lipids can be formed enzymatically or by reactive oxygen species (ROS). Enzymes that metabolize fatty acids include cyclooxygenase (COX), lipoxygenase (LO), and cytochromes P450 (CYPs)1,8. Enzymatic metabolism results in enantioselective formation whereas ROS oxidation results in the racemic formation of products. While this protocol focuses primarily on the analysis of AA- and some LA-derived bioactive metabolites; it could be easily applied to metabolites of other fatty acids. Bioactive lipids are extracted from cell lysate or media using liquid-liquid (l-l) extraction. At the beginning of the l-l extraction process, stable isotope internal standards are added to account for errors during sample preparation. Stable isotope dilution (SID) also accounts for any differences, such as ion suppression, that metabolites may experience during the mass spectrometry (MS) analysis9. After the extraction, derivatization with an electron capture (EC) reagent, pentafluorylbenzyl bromide (PFB) is employed to increase detection sensitivity10,11. Multiple reaction monitoring (MRM) is used to increase the selectivity of the MS analysis. Before MS analysis, lipids are separated using chiral normal phase high performance liquid chromatography (HPLC). The HPLC conditions are optimized to separate the enantiomers and various stereoisomers of the monitored lipids12. This specific LC-MS method monitors prostaglandins (PGs), isoprostanes (isoPs), hydroxyeicosatetraenoic acids (HETEs), hydroxyoctadecadienoic acids (HODEs), oxoeicosatetraenoic acids (oxoETEs) and oxooctadecadienoic acids (oxoODEs); however, the HPLC and MS parameters can be optimized to include any fatty acid metabolites13. Most of the currently available bioanalytical methods do not take into account the separate quantification of enantiomers. This is extremely important when trying to deduce whether or not the metabolites were formed enzymatically or by ROS. Additionally, the ratios of the enantiomers may provide evidence for a specific enzymatic pathway of formation. The use of SID allows for accurate quantification of metabolites and accounts for any sample loss during preparation as well as the differences experienced during ionization. Using the PFB electron capture reagent increases the sensitivity of detection by two orders of magnitude over conventional APCI methods. Overall, this method, SID-LC-EC-atmospheric pressure chemical ionization APCI-MRM/MS, is one of the most sensitive, selective, and accurate methods of quantification for bioactive lipids.
Bioengineering, Issue 57, lipids, extraction, stable isotope dilution, chiral chromatography, electron capture, mass spectrometry
3399
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
3871
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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Authors: Alla Gagarinova, Mohan Babu, Jack Greenblatt, Andrew Emili.
Institutions: University of Toronto, University of Toronto, University of Regina.
Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10. Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.
Genetics, Issue 69, Molecular Biology, Medicine, Biochemistry, Microbiology, Aggravating, alleviating, conjugation, double mutant, Escherichia coli, genetic interaction, Gram-negative bacteria, homologous recombination, network, synthetic lethality or sickness, suppression
4056
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An Analytical Tool that Quantifies Cellular Morphology Changes from Three-dimensional Fluorescence Images
Authors: Carolina L. Haass-Koffler, Mohammad Naeemuddin, Selena E. Bartlett.
Institutions: University of California, San Francisco , University of California, San Francisco , Queensland University of Technology, Brisbane, Australia.
The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology1 even in complex tissue sections2. Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells3, however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.
Cellular Biology, Issue 66, 3-dimensional, microscopy, quantification, morphometric, single-cell, cell dynamics
4233
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
4273
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Self-reporting Scaffolds for 3-Dimensional Cell Culture
Authors: Helen Harrington, Felicity R.A.J. Rose, Jonathan W. Aylott, Amir M. Ghaemmaghami.
Institutions: University of Nottingham, University of Nottingham, University of Nottingham.
Culturing cells in 3D on appropriate scaffolds is thought to better mimic the in vivo microenvironment and increase cell-cell interactions. The resulting 3D cellular construct can often be more relevant to studying the molecular events and cell-cell interactions than similar experiments studied in 2D. To create effective 3D cultures with high cell viability throughout the scaffold the culture conditions such as oxygen and pH need to be carefully controlled as gradients in analyte concentration can exist throughout the 3D construct. Here we describe the methods of preparing biocompatible pH responsive sol-gel nanosensors and their incorporation into poly(lactic-co-glycolic acid) (PLGA) electrospun scaffolds along with their subsequent preparation for the culture of mammalian cells. The pH responsive scaffolds can be used as tools to determine microenvironmental pH within a 3D cellular construct. Furthermore, we detail the delivery of pH responsive nanosensors to the intracellular environment of mammalian cells whose growth was supported by electrospun PLGA scaffolds. The cytoplasmic location of the pH responsive nanosensors can be utilized to monitor intracellular pH (pHi) during ongoing experimentation.
Bioengineering, Issue 81, Biocompatible Materials, Nanosensors, scaffold, electrospinning, 3D cell culture, PLGA
50608
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Adapting the Electrospinning Process to Provide Three Unique Environments for a Tri-layered In Vitro Model of the Airway Wall
Authors: Jack C. Bridge, Jonathan W. Aylott, Christopher E. Brightling, Amir M. Ghaemmaghami, Alan J. Knox, Mark P. Lewis, Felicity R.A.J. Rose, Gavin E. Morris.
Institutions: University of Nottingham, University of Nottingham, University of Nottingham, University of Nottingham, University of Leicester, Loughborough University.
Electrospinning is a highly adaptable method producing porous 3D fibrous scaffolds that can be exploited in in vitro cell culture. Alterations to intrinsic parameters within the process allow a high degree of control over scaffold characteristics including fiber diameter, alignment and porosity. By developing scaffolds with similar dimensions and topographies to organ- or tissue-specific extracellular matrices (ECM), micro-environments representative to those that cells are exposed to in situ can be created. The airway bronchiole wall, comprised of three main micro-environments, was selected as a model tissue. Using decellularized airway ECM as a guide, we electrospun the non-degradable polymer, polyethylene terephthalate (PET), by three different protocols to produce three individual electrospun scaffolds optimized for epithelial, fibroblast or smooth muscle cell-culture. Using a commercially available bioreactor system, we stably co-cultured the three cell-types to provide an in vitro model of the airway wall over an extended time period. This model highlights the potential for such methods being employed in in vitro diagnostic studies investigating important inter-cellular cross-talk mechanisms or assessing novel pharmaceutical targets, by providing a relevant platform to allow the culture of fully differentiated adult cells within 3D, tissue-specific environments.
Bioengineering, Issue 101, Electrospinning, 3D Cell Culture, Bioreactor, Airway, Tissue Engineering, In Vitro Model
52986
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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