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Pubmed Article
Bayesian weighting of statistical potentials in NMR structure calculation.
PLoS ONE
PUBLISHED: 01-01-2014
The use of statistical potentials in NMR structure calculation improves the accuracy of the final structure but also raises issues of double counting and possible bias. Because statistical potentials are averaged over a large set of structures, they may not reflect the preferences of a particular structure or data set. We propose a Bayesian method to incorporate a knowledge-based backbone dihedral angle potential into an NMR structure calculation. To avoid bias exerted through the backbone potential, we adjust its weight by inferring it from the experimental data. We demonstrate that an optimally weighted potential leads to an improvement in the accuracy and quality of the final structure, especially with sparse and noisy data. Our findings suggest that no universally optimal weight exists, and that the weight should be determined based on the experimental data. Other knowledge-based potentials can be incorporated using the same approach.
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.
20 Related JoVE Articles!
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Structure and Coordination Determination of Peptide-metal Complexes Using 1D and 2D 1H NMR
Authors: Michal S. Shoshan, Edit Y. Tshuva, Deborah E. Shalev.
Institutions: The Hebrew University of Jerusalem, The Hebrew University of Jerusalem.
Copper (I) binding by metallochaperone transport proteins prevents copper oxidation and release of the toxic ions that may participate in harmful redox reactions. The Cu (I) complex of the peptide model of a Cu (I) binding metallochaperone protein, which includes the sequence MTCSGCSRPG (underlined is conserved), was determined in solution under inert conditions by NMR spectroscopy. NMR is a widely accepted technique for the determination of solution structures of proteins and peptides. Due to difficulty in crystallization to provide single crystals suitable for X-ray crystallography, the NMR technique is extremely valuable, especially as it provides information on the solution state rather than the solid state. Herein we describe all steps that are required for full three-dimensional structure determinations by NMR. The protocol includes sample preparation in an NMR tube, 1D and 2D data collection and processing, peak assignment and integration, molecular mechanics calculations, and structure analysis. Importantly, the analysis was first conducted without any preset metal-ligand bonds, to assure a reliable structure determination in an unbiased manner.
Chemistry, Issue 82, solution structure determination, NMR, peptide models, copper-binding proteins, copper complexes
50747
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Microwave-assisted Functionalization of Poly(ethylene glycol) and On-resin Peptides for Use in Chain Polymerizations and Hydrogel Formation
Authors: Amy H. Van Hove, Brandon D. Wilson, Danielle S. W. Benoit.
Institutions: University of Rochester, University of Rochester, University of Rochester Medical Center.
One of the main benefits to using poly(ethylene glycol) (PEG) macromers in hydrogel formation is synthetic versatility. The ability to draw from a large variety of PEG molecular weights and configurations (arm number, arm length, and branching pattern) affords researchers tight control over resulting hydrogel structures and properties, including Young’s modulus and mesh size. This video will illustrate a rapid, efficient, solvent-free, microwave-assisted method to methacrylate PEG precursors into poly(ethylene glycol) dimethacrylate (PEGDM). This synthetic method provides much-needed starting materials for applications in drug delivery and regenerative medicine. The demonstrated method is superior to traditional methacrylation methods as it is significantly faster and simpler, as well as more economical and environmentally friendly, using smaller amounts of reagents and solvents. We will also demonstrate an adaptation of this technique for on-resin methacrylamide functionalization of peptides. This on-resin method allows the N-terminus of peptides to be functionalized with methacrylamide groups prior to deprotection and cleavage from resin. This allows for selective addition of methacrylamide groups to the N-termini of the peptides while amino acids with reactive side groups (e.g. primary amine of lysine, primary alcohol of serine, secondary alcohols of threonine, and phenol of tyrosine) remain protected, preventing functionalization at multiple sites. This article will detail common analytical methods (proton Nuclear Magnetic Resonance spectroscopy (;H-NMR) and Matrix Assisted Laser Desorption Ionization Time of Flight mass spectrometry (MALDI-ToF)) to assess the efficiency of the functionalizations. Common pitfalls and suggested troubleshooting methods will be addressed, as will modifications of the technique which can be used to further tune macromer functionality and resulting hydrogel physical and chemical properties. Use of synthesized products for the formation of hydrogels for drug delivery and cell-material interaction studies will be demonstrated, with particular attention paid to modifying hydrogel composition to affect mesh size, controlling hydrogel stiffness and drug release.
Chemistry, Issue 80, Poly(ethylene glycol), peptides, polymerization, polymers, methacrylation, peptide functionalization, 1H-NMR, MALDI-ToF, hydrogels, macromer synthesis
50890
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A Practical Guide to Phylogenetics for Nonexperts
Authors: Damien O'Halloran.
Institutions: The George Washington University.
Many researchers, across incredibly diverse foci, are applying phylogenetics to their research question(s). However, many researchers are new to this topic and so it presents inherent problems. Here we compile a practical introduction to phylogenetics for nonexperts. We outline in a step-by-step manner, a pipeline for generating reliable phylogenies from gene sequence datasets. We begin with a user-guide for similarity search tools via online interfaces as well as local executables. Next, we explore programs for generating multiple sequence alignments followed by protocols for using software to determine best-fit models of evolution. We then outline protocols for reconstructing phylogenetic relationships via maximum likelihood and Bayesian criteria and finally describe tools for visualizing phylogenetic trees. While this is not by any means an exhaustive description of phylogenetic approaches, it does provide the reader with practical starting information on key software applications commonly utilized by phylogeneticists. The vision for this article would be that it could serve as a practical training tool for researchers embarking on phylogenetic studies and also serve as an educational resource that could be incorporated into a classroom or teaching-lab.
Basic Protocol, Issue 84, phylogenetics, multiple sequence alignments, phylogenetic tree, BLAST executables, basic local alignment search tool, Bayesian models
50975
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The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
Authors: Sara Tremblay, Vincent Beaulé, Sébastien Proulx, Louis-Philippe Lafleur, Julien Doyon, Małgorzata Marjańska, Hugo Théoret.
Institutions: University of Montréal, McGill University, University of Minnesota.
Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of neurological and psychiatric disorders such as stroke and depression. Yet, the mechanisms underlying its ability to modulate brain excitability to improve clinical symptoms remains poorly understood 33. To help improve this understanding, proton magnetic resonance spectroscopy (1H-MRS) can be used as it allows the in vivo quantification of brain metabolites such as γ-aminobutyric acid (GABA) and glutamate in a region-specific manner 41. In fact, a recent study demonstrated that 1H-MRS is indeed a powerful means to better understand the effects of tDCS on neurotransmitter concentration 34. This article aims to describe the complete protocol for combining tDCS (NeuroConn MR compatible stimulator) with 1H-MRS at 3 T using a MEGA-PRESS sequence. We will describe the impact of a protocol that has shown great promise for the treatment of motor dysfunctions after stroke, which consists of bilateral stimulation of primary motor cortices 27,30,31. Methodological factors to consider and possible modifications to the protocol are also discussed.
Neuroscience, Issue 93, proton magnetic resonance spectroscopy, transcranial direct current stimulation, primary motor cortex, GABA, glutamate, stroke
51631
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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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Cortical Source Analysis of High-Density EEG Recordings in Children
Authors: Joe Bathelt, Helen O'Reilly, Michelle de Haan.
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2, because the composition and spatial configuration of head tissues changes dramatically over development3.  In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis. 
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials 
51705
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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
51823
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Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts
Authors: Norbert W. Lutz, Evelyne Béraud, Patrick J. Cozzone.
Institutions: Aix-Marseille Université, Aix-Marseille Université.
Studies of gene expression on the RNA and protein levels have long been used to explore biological processes underlying disease. More recently, genomics and proteomics have been complemented by comprehensive quantitative analysis of the metabolite pool present in biological systems. This strategy, termed metabolomics, strives to provide a global characterization of the small-molecule complement involved in metabolism. While the genome and the proteome define the tasks cells can perform, the metabolome is part of the actual phenotype. Among the methods currently used in metabolomics, spectroscopic techniques are of special interest because they allow one to simultaneously analyze a large number of metabolites without prior selection for specific biochemical pathways, thus enabling a broad unbiased approach. Here, an optimized experimental protocol for metabolomic analysis by high-resolution NMR spectroscopy is presented, which is the method of choice for efficient quantification of tissue metabolites. Important strengths of this method are (i) the use of crude extracts, without the need to purify the sample and/or separate metabolites; (ii) the intrinsically quantitative nature of NMR, permitting quantitation of all metabolites represented by an NMR spectrum with one reference compound only; and (iii) the nondestructive nature of NMR enabling repeated use of the same sample for multiple measurements. The dynamic range of metabolite concentrations that can be covered is considerable due to the linear response of NMR signals, although metabolites occurring at extremely low concentrations may be difficult to detect. For the least abundant compounds, the highly sensitive mass spectrometry method may be advantageous although this technique requires more intricate sample preparation and quantification procedures than NMR spectroscopy. We present here an NMR protocol adjusted to rat brain analysis; however, the same protocol can be applied to other tissues with minor modifications.
Neuroscience, Issue 91, metabolomics, brain tissue, rodents, neurochemistry, tissue extracts, NMR spectroscopy, quantitative metabolite analysis, cerebral metabolism, metabolic profile
51829
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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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High-Sensitivity Nuclear Magnetic Resonance at Giga-Pascal Pressures: A New Tool for Probing Electronic and Chemical Properties of Condensed Matter under Extreme Conditions
Authors: Thomas Meier, Jürgen Haase.
Institutions: University of Leipzig.
Nuclear Magnetic Resonance (NMR) is one of the most important techniques for the study of condensed matter systems, their chemical structure, and their electronic properties. The application of high pressure enables one to synthesize new materials, but the response of known materials to high pressure is a very useful tool for studying their electronic structure and developing theories. For example, high-pressure synthesis might be at the origin of life; and understanding the behavior of small molecules under extreme pressure will tell us more about fundamental processes in our universe. It is no wonder that there has always been great interest in having NMR available at high pressures. Unfortunately, the desired pressures are often well into the Giga-Pascal (GPa) range and require special anvil cell devices where only very small, secluded volumes are available. This has restricted the use of NMR almost entirely in the past, and only recently, a new approach to high-sensitivity GPa NMR, which has a resonating micro-coil inside the sample chamber, was put forward. This approach enables us to achieve high sensitivity with experiments that bring the power of NMR to Giga-Pascal pressure condensed matter research. First applications, the detection of a topological electronic transition in ordinary aluminum metal and the closing of the pseudo-gap in high-temperature superconductivity, show the power of such an approach. Meanwhile, the range of achievable pressures was increased tremendously with a new generation of anvil cells (up to 10.1 GPa), that fit standard-bore NMR magnets. This approach might become a new, important tool for the investigation of many condensed matter systems, in chemistry, geochemistry, and in physics, since we can now watch structural changes with the eyes of a very versatile probe.
Physics, Issue 92, NMR, micro-coil, anvil cell, high pressures, condensed matter, radio-frequency
52243
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
50427
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Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding
Authors: David Almond, Timothy Cardozo.
Institutions: School of Medicine, New York University.
The antigenic diversity of HIV-1 has long been an obstacle to vaccine design, and this variability is especially pronounced in the V3 loop of the virus' surface envelope glycoprotein. We previously proposed that the crown of the V3 loop, although dynamic and sequence variable, is constrained throughout the population of HIV-1 viruses to an immunologically relevant β-hairpin tertiary structure. Importantly, there are thousands of different V3 loop crown sequences in circulating HIV-1 viruses, making 3D structural characterization of trends across the diversity of viruses difficult or impossible by crystallography or NMR. Our previous successful studies with folding of the V3 crown1, 2 used the ab initio algorithm 3 accessible in the ICM-Pro molecular modeling software package (Molsoft LLC, La Jolla, CA) and suggested that the crown of the V3 loop, specifically from positions 10 to 22, benefits sufficiently from the flexibility and length of its flanking stems to behave to a large degree as if it were an unconstrained peptide freely folding in solution. As such, rapid ab initio folding of just this portion of the V3 loop of any individual strain of the 60,000+ circulating HIV-1 strains can be informative. Here, we folded the V3 loop of the R2 strain to gain insight into the structural basis of its unique properties. R2 bears a rare V3 loop sequence thought to be responsible for the exquisite sensitivity of this strain to neutralization by patient sera and monoclonal antibodies4, 5. The strain mediates CD4-independent infection and appears to elicit broadly neutralizing antibodies. We demonstrate how evaluation of the results of the folding can be informative for associating observed structures in the folding with the immunological activities observed for R2.
Infection, Issue 43, HIV-1, structure-activity relationships, ab initio simulations, antibody-mediated neutralization, vaccine design
2118
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Automated Sholl Analysis of Digitized Neuronal Morphology at Multiple Scales
Authors: Melinda K. Kutzing, Christopher G. Langhammer, Vincent Luo, Hersh Lakdawala, Bonnie L. Firestein.
Institutions: Rutgers University, Rutgers University.
Neuronal morphology plays a significant role in determining how neurons function and communicate1-3. Specifically, it affects the ability of neurons to receive inputs from other cells2 and contributes to the propagation of action potentials4,5. The morphology of the neurites also affects how information is processed. The diversity of dendrite morphologies facilitate local and long range signaling and allow individual neurons or groups of neurons to carry out specialized functions within the neuronal network6,7. Alterations in dendrite morphology, including fragmentation of dendrites and changes in branching patterns, have been observed in a number of disease states, including Alzheimer's disease8, schizophrenia9,10, and mental retardation11. The ability to both understand the factors that shape dendrite morphologies and to identify changes in dendrite morphologies is essential in the understanding of nervous system function and dysfunction. Neurite morphology is often analyzed by Sholl analysis and by counting the number of neurites and the number of branch tips. This analysis is generally applied to dendrites, but it can also be applied to axons. Performing this analysis by hand is both time consuming and inevitably introduces variability due to experimenter bias and inconsistency. The Bonfire program is a semi-automated approach to the analysis of dendrite and axon morphology that builds upon available open-source morphological analysis tools. Our program enables the detection of local changes in dendrite and axon branching behaviors by performing Sholl analysis on subregions of the neuritic arbor. For example, Sholl analysis is performed on both the neuron as a whole as well as on each subset of processes (primary, secondary, terminal, root, etc.) Dendrite and axon patterning is influenced by a number of intracellular and extracellular factors, many acting locally. Thus, the resulting arbor morphology is a result of specific processes acting on specific neurites, making it necessary to perform morphological analysis on a smaller scale in order to observe these local variations12. The Bonfire program requires the use of two open-source analysis tools, the NeuronJ plugin to ImageJ and NeuronStudio. Neurons are traced in ImageJ, and NeuronStudio is used to define the connectivity between neurites. Bonfire contains a number of custom scripts written in MATLAB (MathWorks) that are used to convert the data into the appropriate format for further analysis, check for user errors, and ultimately perform Sholl analysis. Finally, data are exported into Excel for statistical analysis. A flow chart of the Bonfire program is shown in Figure 1.
Neuroscience, Issue 45, Sholl Analysis, Neurite, Morphology, Computer-assisted, Tracing
2354
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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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How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
Authors: Marie Schaer, Meritxell Bach Cuadra, Nick Schmansky, Bruce Fischl, Jean-Philippe Thiran, Stephan Eliez.
Institutions: University of Geneva School of Medicine, École Polytechnique Fédérale de Lausanne, University Hospital Center and University of Lausanne, Massachusetts General Hospital.
Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues2, several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry3. These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface4. The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index5, a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name local Gyrification Index (lGI1), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion6, our method was specifically designed to identify early defects of cortical development. In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer Software (http://surfer.nmr.mgh.harvard.edu/, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the lGI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study1. This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues7, where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.
Medicine, Issue 59, neuroimaging, brain, cortical complexity, cortical development
3417
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The ITS2 Database
Authors: Benjamin Merget, Christian Koetschan, Thomas Hackl, Frank Förster, Thomas Dandekar, Tobias Müller, Jörg Schultz, Matthias Wolf.
Institutions: University of Würzburg, University of Würzburg.
The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation2-8. The ITS2 Database9 presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank11 accurately reannotated10. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold12 (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling13. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold. The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST14 search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE15,16 and ProfDistS17 for multiple sequence-structure alignment calculation and Neighbor Joining18 tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure. In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
Genetics, Issue 61, alignment, internal transcribed spacer 2, molecular systematics, secondary structure, ribosomal RNA, phylogenetic tree, homology modeling, phylogeny
3806
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
4375
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Using Learning Outcome Measures to assess Doctoral Nursing Education
Authors: Glenn H. Raup, Jeff King, Romana J. Hughes, Natasha Faidley.
Institutions: Harris College of Nursing and Health Sciences, Texas Christian University.
Education programs at all levels must be able to demonstrate successful program outcomes. Grades alone do not represent a comprehensive measurement methodology for assessing student learning outcomes at either the course or program level. The development and application of assessment rubrics provides an unequivocal measurement methodology to ensure a quality learning experience by providing a foundation for improvement based on qualitative and quantitatively measurable, aggregate course and program outcomes. Learning outcomes are the embodiment of the total learning experience and should incorporate assessment of both qualitative and quantitative program outcomes. The assessment of qualitative measures represents a challenge for educators in any level of a learning program. Nursing provides a unique challenge and opportunity as it is the application of science through the art of caring. Quantification of desired student learning outcomes may be enhanced through the development of assessment rubrics designed to measure quantitative and qualitative aspects of the nursing education and learning process. They provide a mechanism for uniform assessment by nursing faculty of concepts and constructs that are otherwise difficult to describe and measure. A protocol is presented and applied to a doctoral nursing education program with recommendations for application and transformation of the assessment rubric to other education programs. Through application of these specially designed rubrics, all aspects of an education program can be adequately assessed to provide information for program assessment that facilitates the closure of the gap between desired and actual student learning outcomes for any desired educational competency.
Medicine, Issue 40, learning, outcomes, measurement, program, assessment, rubric
2048
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T-wave Ion Mobility-mass Spectrometry: Basic Experimental Procedures for Protein Complex Analysis
Authors: Izhak Michaelevski, Noam Kirshenbaum, Michal Sharon.
Institutions: Weizmann Institute of Science.
Ion mobility (IM) is a method that measures the time taken for an ion to travel through a pressurized cell under the influence of a weak electric field. The speed by which the ions traverse the drift region depends on their size: large ions will experience a greater number of collisions with the background inert gas (usually N2) and thus travel more slowly through the IM device than those ions that comprise a smaller cross-section. In general, the time it takes for the ions to migrate though the dense gas phase separates them, according to their collision cross-section (Ω). Recently, IM spectrometry was coupled with mass spectrometry and a traveling-wave (T-wave) Synapt ion mobility mass spectrometer (IM-MS) was released. Integrating mass spectrometry with ion mobility enables an extra dimension of sample separation and definition, yielding a three-dimensional spectrum (mass to charge, intensity, and drift time). This separation technique allows the spectral overlap to decrease, and enables resolution of heterogeneous complexes with very similar mass, or mass-to-charge ratios, but different drift times. Moreover, the drift time measurements provide an important layer of structural information, as Ω is related to the overall shape and topology of the ion. The correlation between the measured drift time values and Ω is calculated using a calibration curve generated from calibrant proteins with defined cross-sections1. The power of the IM-MS approach lies in its ability to define the subunit packing and overall shape of protein assemblies at micromolar concentrations, and near-physiological conditions1. Several recent IM studies of both individual proteins2,3 and non-covalent protein complexes4-9, successfully demonstrated that protein quaternary structure is maintained in the gas phase, and highlighted the potential of this approach in the study of protein assemblies of unknown geometry. Here, we provide a detailed description of IMS-MS analysis of protein complexes using the Synapt (Quadrupole-Ion Mobility-Time-of-Flight) HDMS instrument (Waters Ltd; the only commercial IM-MS instrument currently available)10. We describe the basic optimization steps, the calibration of collision cross-sections, and methods for data processing and interpretation. The final step of the protocol discusses methods for calculating theoretical Ω values. Overall, the protocol does not attempt to cover every aspect of IM-MS characterization of protein assemblies; rather, its goal is to introduce the practical aspects of the method to new researchers in the field.
cellular biology, Issue 41, mass spectrometry, ion-mobility, protein complexes, non-covalent interactions, structural biology
1985
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Functional Mapping with Simultaneous MEG and EEG
Authors: Hesheng Liu, Naoaki Tanaka, Steven Stufflebeam, Seppo Ahlfors, Matti Hämäläinen.
Institutions: MGH - Massachusetts General Hospital.
We use magnetoencephalography (MEG) and electroencephalography (EEG) to locate and determine the temporal evolution in brain areas involved in the processing of simple sensory stimuli. We will use somatosensory stimuli to locate the hand somatosensory areas, auditory stimuli to locate the auditory cortices, visual stimuli in four quadrants of the visual field to locate the early visual areas. These type of experiments are used for functional mapping in epileptic and brain tumor patients to locate eloquent cortices. In basic neuroscience similar experimental protocols are used to study the orchestration of cortical activity. The acquisition protocol includes quality assurance procedures, subject preparation for the combined MEG/EEG study, and acquisition of evoked-response data with somatosensory, auditory, and visual stimuli. We also demonstrate analysis of the data using the equivalent current dipole model and cortically-constrained minimum-norm estimates. Anatomical MRI data are employed in the analysis for visualization and for deriving boundaries of tissue boundaries for forward modeling and cortical location and orientation constraints for the minimum-norm estimates.
JoVE neuroscience, Issue 40, neuroscience, brain, MEG, EEG, functional imaging
1668
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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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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.