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Pubmed Article
Regional scale high resolution ?18O prediction in precipitation using MODIS EVI.
The natural variation in stable water isotope ratio data, also known as water isoscape, is a spatiotemporal fingerprint and a powerful natural tracer that has been widely applied in disciplines as diverse as hydrology, paleoclimatology, ecology and forensic investigation. Although much effort has been devoted to developing a predictive water isoscape model, it remains a central challenge for scientists to generate high accuracy, fine scale spatiotemporal water isoscape prediction. Here we develop a novel approach of using the MODIS-EVI (the Moderate Resolution Imagining Spectroradiometer-Enhanced Vegetation Index), to predict ?(18)O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated ?(18)O are highly correlated and thus the EVI is a good predictor of precipitated ?(18)O. We then test the predictability of our EVI-?(18)O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale ?(18)O predictions (annual and monthly predictabilities [r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and ?(18)O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape.
Authors: Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang.
Published: 11-03-2011
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.
23 Related JoVE Articles!
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An Experimental Paradigm for the Prediction of Post-Operative Pain (PPOP)
Authors: Ruth Landau, John C. Kraft, Lisa Y. Flint, Brendan Carvalho, Philippe Richebé, Monica Cardoso, Patricia Lavand'homme, Michal Granot, David Yarnitsky, Alex Cahana.
Institutions: University of Washington School of Medicine.
Many women undergo cesarean delivery without problems, however some experience significant pain after cesarean section. Pain is associated with negative short-term and long-term effects on the mother. Prior to women undergoing surgery, can we predict who is at risk for developing significant postoperative pain and potentially prevent or minimize its negative consequences? These are the fundamental questions that a team from the University of Washington, Stanford University, the Catholic University in Brussels, Belgium, Santa Joana Women's Hospital in São Paulo, Brazil, and Rambam Medical Center in Israel is currently evaluating in an international research collaboration. The ultimate goal of this project is to provide optimal pain relief during and after cesarean section by offering individualized anesthetic care to women who appear to be more 'susceptible' to pain after surgery. A significant number of women experience moderate or severe acute post-partum pain after vaginal and cesarean deliveries. 1 Furthermore, 10-15% of women suffer chronic persistent pain after cesarean section. 2 With constant increase in cesarean rates in the US 3 and the already high rate in Brazil, this is bound to create a significant public health problem. When questioning women's fears and expectations from cesarean section, pain during and after it is their greatest concern. 4 Individual variability in severity of pain after vaginal or operative delivery is influenced by multiple factors including sensitivity to pain, psychological factors, age, and genetics. The unique birth experience leads to unpredictable requirements for analgesics, from 'none at all' to 'very high' doses of pain medication. Pain after cesarean section is an excellent model to study post-operative pain because it is performed on otherwise young and healthy women. Therefore, it is recommended to attenuate the pain during the acute phase because this may lead to chronic pain disorders. The impact of developing persistent pain is immense, since it may impair not only the ability of women to care for their child in the immediate postpartum period, but also their own well being for a long period of time. In a series of projects, an international research network is currently investigating the effect of pregnancy on pain modulation and ways to predict who will suffer acute severe pain and potentially chronic pain, by using simple pain tests and questionnaires in combination with genetic analysis. A relatively recent approach to investigate pain modulation is via the psychophysical measure of Diffuse Noxious Inhibitory Control (DNIC). This pain-modulating process is the neurophysiological basis for the well-known phenomenon of 'pain inhibits pain' from remote areas of the body. The DNIC paradigm has evolved recently into a clinical tool and simple test and has been shown to be a predictor of post-operative pain.5 Since pregnancy is associated with decreased pain sensitivity and/or enhanced processes of pain modulation, using tests that investigate pain modulation should provide a better understanding of the pathways involved with pregnancy-induced analgesia and may help predict pain outcomes during labor and delivery. For those women delivering by cesarean section, a DNIC test performed prior to surgery along with psychosocial questionnaires and genetic tests should enable one to identify women prone to suffer severe post-cesarean pain and persistent pain. These clinical tests should allow anesthesiologists to offer not only personalized medicine to women with the promise to improve well-being and satisfaction, but also a reduction in the overall cost of perioperative and long term care due to pain and suffering. On a larger scale, these tests that explore pain modulation may become bedside screening tests to predict the development of pain disorders following surgery.
JoVE Medicine, Issue 35, diffuse noxious inhibitory control, DNIC, temporal summation, TS, psychophysical testing, endogenous analgesia, pain modulation, pregnancy-induced analgesia, cesarean section, post-operative pain, prediction
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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
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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
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Authors: Johannes Felix Buyel, Rainer Fischer.
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
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Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism
Authors: Sina Mossahebi, Simeng Zhu, Howard Chen, Leonid Shmuylovich, Erina Ghosh, Sándor J. Kovács.
Institutions: Washington University in St. Louis, Washington University in St. Louis, Washington University in St. Louis, Washington University in St. Louis, Washington University in St. Louis.
Quantitative cardiac function assessment remains a challenge for physiologists and clinicians. Although historically invasive methods have comprised the only means available, the development of noninvasive imaging modalities (echocardiography, MRI, CT) having high temporal and spatial resolution provide a new window for quantitative diastolic function assessment. Echocardiography is the agreed upon standard for diastolic function assessment, but indexes in current clinical use merely utilize selected features of chamber dimension (M-mode) or blood/tissue motion (Doppler) waveforms without incorporating the physiologic causal determinants of the motion itself. The recognition that all left ventricles (LV) initiate filling by serving as mechanical suction pumps allows global diastolic function to be assessed based on laws of motion that apply to all chambers. What differentiates one heart from another are the parameters of the equation of motion that governs filling. Accordingly, development of the Parametrized Diastolic Filling (PDF) formalism has shown that the entire range of clinically observed early transmitral flow (Doppler E-wave) patterns are extremely well fit by the laws of damped oscillatory motion. This permits analysis of individual E-waves in accordance with a causal mechanism (recoil-initiated suction) that yields three (numerically) unique lumped parameters whose physiologic analogues are chamber stiffness (k), viscoelasticity/relaxation (c), and load (xo). The recording of transmitral flow (Doppler E-waves) is standard practice in clinical cardiology and, therefore, the echocardiographic recording method is only briefly reviewed. Our focus is on determination of the PDF parameters from routinely recorded E-wave data. As the highlighted results indicate, once the PDF parameters have been obtained from a suitable number of load varying E-waves, the investigator is free to use the parameters or construct indexes from the parameters (such as stored energy 1/2kxo2, maximum A-V pressure gradient kxo, load independent index of diastolic function, etc.) and select the aspect of physiology or pathophysiology to be quantified.
Bioengineering, Issue 91, cardiovascular physiology, ventricular mechanics, diastolic function, mathematical modeling, Doppler echocardiography, hemodynamics, biomechanics
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Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity
Authors: Angela J. Brandt, Gaston A. del Pino, Jean H. Burns.
Institutions: Case Western Reserve University.
Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.
Environmental Sciences, Issue 85, Coexistence, community assembly, environmental drivers, plant-soil feedback, soil heterogeneity, soil microbial communities, soil patch
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Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
Authors: Charmion Cruickshank-Quinn, Kevin D. Quinn, Roger Powell, Yanhui Yang, Michael Armstrong, Spencer Mahaffey, Richard Reisdorph, Nichole Reisdorph.
Institutions: National Jewish Health, University of Colorado Denver.
Metabolomics is an emerging field which enables profiling of samples from living organisms in order to obtain insight into biological processes. A vital aspect of metabolomics is sample preparation whereby inconsistent techniques generate unreliable results. This technique encompasses protein precipitation, liquid-liquid extraction, and solid-phase extraction as a means of fractionating metabolites into four distinct classes. Improved enrichment of low abundance molecules with a resulting increase in sensitivity is obtained, and ultimately results in more confident identification of molecules. This technique has been applied to plasma, bronchoalveolar lavage fluid, and cerebrospinal fluid samples with volumes as low as 50 µl.  Samples can be used for multiple downstream applications; for example, the pellet resulting from protein precipitation can be stored for later analysis. The supernatant from that step undergoes liquid-liquid extraction using water and strong organic solvent to separate the hydrophilic and hydrophobic compounds. Once fractionated, the hydrophilic layer can be processed for later analysis or discarded if not needed. The hydrophobic fraction is further treated with a series of solvents during three solid-phase extraction steps to separate it into fatty acids, neutral lipids, and phospholipids. This allows the technician the flexibility to choose which class of compounds is preferred for analysis. It also aids in more reliable metabolite identification since some knowledge of chemical class exists.
Bioengineering, Issue 89, plasma, chemistry techniques, analytical, solid phase extraction, mass spectrometry, metabolomics, fluids and secretions, profiling, small molecules, lipids, liquid chromatography, liquid-liquid extraction, cerebrospinal fluid, bronchoalveolar lavage fluid
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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 
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Integrated Field Lysimetry and Porewater Sampling for Evaluation of Chemical Mobility in Soils and Established Vegetation
Authors: Audrey R. Matteson, Denis J. Mahoney, Travis W. Gannon, Matthew L. Polizzotto.
Institutions: North Carolina State University, North Carolina State University.
Potentially toxic chemicals are routinely applied to land to meet growing demands on waste management and food production, but the fate of these chemicals is often not well understood. Here we demonstrate an integrated field lysimetry and porewater sampling method for evaluating the mobility of chemicals applied to soils and established vegetation. Lysimeters, open columns made of metal or plastic, are driven into bareground or vegetated soils. Porewater samplers, which are commercially available and use vacuum to collect percolating soil water, are installed at predetermined depths within the lysimeters. At prearranged times following chemical application to experimental plots, porewater is collected, and lysimeters, containing soil and vegetation, are exhumed. By analyzing chemical concentrations in the lysimeter soil, vegetation, and porewater, downward leaching rates, soil retention capacities, and plant uptake for the chemical of interest may be quantified. Because field lysimetry and porewater sampling are conducted under natural environmental conditions and with minimal soil disturbance, derived results project real-case scenarios and provide valuable information for chemical management. As chemicals are increasingly applied to land worldwide, the described techniques may be utilized to determine whether applied chemicals pose adverse effects to human health or the environment.
Environmental Sciences, Issue 89, Lysimetry, porewater, soil, chemical leaching, pesticides, turfgrass, waste
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Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
Authors: Julia F. Item-Glatthorn, Nicola A. Maffiuletti.
Institutions: Schulthess Clinic.
Spatial and temporal characteristics of human walking are frequently evaluated to identify possible gait impairments, mainly in orthopedic and neurological patients1-4, but also in healthy older adults5,6. The quantitative gait analysis described in this protocol is performed with a recently-introduced photoelectric system (see Materials table) which has the potential to be used in the clinic because it is portable, easy to set up (no subject preparation is required before a test), and does not require maintenance and sensor calibration. The photoelectric system consists of series of high-density floor-based photoelectric cells with light-emitting and light-receiving diodes that are placed parallel to each other to create a corridor, and are oriented perpendicular to the line of progression7. The system simply detects interruptions in light signal, for instance due to the presence of feet within the recording area. Temporal gait parameters and 1D spatial coordinates of consecutive steps are subsequently calculated to provide common gait parameters such as step length, single limb support and walking velocity8, whose validity against a criterion instrument has recently been demonstrated7,9. The measurement procedures are very straightforward; a single patient can be tested in less than 5 min and a comprehensive report can be generated in less than 1 min.
Medicine, Issue 93, gait analysis, walking, floor-based photocells, spatiotemporal, elderly, orthopedic patients, neurological patients
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
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 (, 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.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
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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
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Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking
Authors: Evan D. Morris, Su Jin Kim, Jenna M. Sullivan, Shuo Wang, Marc D. Normandin, Cristian C. Constantinescu, Kelly P. Cosgrove.
Institutions: Yale University, Yale University, Yale University, Yale University, Massachusetts General Hospital, University of California, Irvine.
We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized. We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters 1-7. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique 'HYPR' spatial filter 8 that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on 11C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model 7 to a conventional model 9. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.
Behavior, Issue 78, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Medicine, Anatomy, Physiology, Image Processing, Computer-Assisted, Receptors, Dopamine, Dopamine, Functional Neuroimaging, Binding, Competitive, mathematical modeling (systems analysis), Neurotransmission, transient, dopamine release, PET, modeling, linear, time-invariant, smoking, F-test, ventral-striatum, clinical techniques
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Toxin Induction and Protein Extraction from Fusarium spp. Cultures for Proteomic Studies
Authors: Matias Pasquali, Frédéric Giraud, Jean Paul Lasserre, Sebastien Planchon, Lucien Hoffmann, Torsten Bohn, Jenny Renaut.
Institutions: Centre de Recherche Public-Gabriel Lippmann.
Fusaria are filamentous fungi able to produce different toxins. Fusarium mycotoxins such as deoxynivalenol, nivalenol, T2, zearelenone, fusaric acid, moniliformin, etc... have adverse effects on both human and animal health and some are considered as pathogenicity factors. Proteomic studies showed to be effective for deciphering toxin production mechanisms (Taylor et al., 2008) as well as for identifying potential pathogenic factors (Paper et al., 2007, Houterman et al., 2007) in Fusaria. It becomes therefore fundamental to establish reliable methods for comparing between proteomic studies in order to rely on true differences found in protein expression among experiments, strains and laboratories. The procedure that will be described should contribute to an increased level of standardization of proteomic procedures by two ways. The filmed protocol is used to increase the level of details that can be described precisely. Moreover, the availability of standardized procedures to process biological replicates should guarantee a higher robustness of data, taking into account also the human factor within the technical reproducibility of the extraction procedure. The protocol described requires 16 days for its completion: fourteen days for cultures and two days for protein extraction (figure 1). Briefly, Fusarium strains are grown on solid media for 4 days; they are then manually fragmented and transferred into a modified toxin inducing media (Jiao et al., 2008) for 10 days. Mycelium is collected by filtration through a Miracloth layer. Grinding is performed in a cold chamber. Different operators performed extraction replicates (n=3) in order to take into account the bias due to technical variations (figure 2). Extraction was based on a SDS/DTT buffer as described in Taylor et al. (2008) with slight modifications. Total protein extraction required a precipitation process of the proteins using Aceton/TCA/DTT buffer overnight and Acetone /DTT washing (figure 3a,3b). Proteins were finally resolubilized in the protein-labelling buffer and quantified. Results of the extraction were visualized on a 1D gel (Figure 4, SDS-PAGE), before proceeding to 2D gels (IEF/SDS-PAGE). The same procedure can be applied for proteomic analyses on other growing media and other filamentous fungi (Miles et al., 2007).
Microbiology, Issue 36, MIAPE, Fusarium graminearum, toxin induction, fungal cultures, proteomics, sample processing, protein extraction
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Genome-wide Analysis of Aminoacylation (Charging) Levels of tRNA Using Microarrays
Authors: John Zaborske, Tao Pan.
Institutions: University of Chicago.
tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both prokaryotic and eukaryotic cells lead to translational regulation which is a major cellular mechanism of stress response. Familiar examples are the stringent response in E. coli and the Gcn2 stress response pathway in yeast ([2-6]). Recent work in E. coli and S. cerevisiae have shown that tRNA charging patterns are highly dynamic and depends on the type of stress experienced by cells [1, 6, 7]. The highly dynamic, variable nature of tRNA charging makes it essential to determine changes in tRNA charging levels at the genomic scale, in order to fully elucidate cellular response to environmental variations. In this review we present a method for simultaneously measuring the relative charging levels of all tRNAs in S. cerevisiae . While the protocol presented here is for yeast, this protocol has been successfully applied for determining relative charging levels in a wide variety of organisms including E. coli and human cell cultures[7, 8].
Cellular Biology, Issue 40, tRNA, aminoacylation, charging, microarray, S. cerevisiae
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DNA Stable-Isotope Probing (DNA-SIP)
Authors: Eric A. Dunford, Josh D. Neufeld.
Institutions: University of Waterloo.
DNA stable-isotope probing (DNA-SIP) is a powerful technique for identifying active microorganisms that assimilate particular carbon substrates and nutrients into cellular biomass. As such, this cultivation-independent technique has been an important methodology for assigning metabolic function to the diverse communities inhabiting a wide range of terrestrial and aquatic environments. Following the incubation of an environmental sample with stable-isotope labelled compounds, extracted nucleic acid is subjected to density gradient ultracentrifugation and subsequent gradient fractionation to separate nucleic acids of differing densities. Purification of DNA from cesium chloride retrieves labelled and unlabelled DNA for subsequent molecular characterization (e.g. fingerprinting, microarrays, clone libraries, metagenomics). This JoVE video protocol provides visual step-by-step explanations of the protocol for density gradient ultracentrifugation, gradient fractionation and recovery of labelled DNA. The protocol also includes sample SIP data and highlights important tips and cautions that must be considered to ensure a successful DNA-SIP analysis.
Microbiology, Issue 42, DNA stable-isotope probing, microbiology, microbial ecology, cultivation-independent, metagenomics, 16S rRNA gene community analysis, substrates, microbial ecology, enrichment
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Protein Crystallization for X-ray Crystallography
Authors: Moshe A. Dessau, Yorgo Modis.
Institutions: Yale University.
Using the three-dimensional structure of biological macromolecules to infer how they function is one of the most important fields of modern biology. The availability of atomic resolution structures provides a deep and unique understanding of protein function, and helps to unravel the inner workings of the living cell. To date, 86% of the Protein Data Bank (rcsb-PDB) entries are macromolecular structures that were determined using X-ray crystallography. To obtain crystals suitable for crystallographic studies, the macromolecule (e.g. protein, nucleic acid, protein-protein complex or protein-nucleic acid complex) must be purified to homogeneity, or as close as possible to homogeneity. The homogeneity of the preparation is a key factor in obtaining crystals that diffract to high resolution (Bergfors, 1999; McPherson, 1999). Crystallization requires bringing the macromolecule to supersaturation. The sample should therefore be concentrated to the highest possible concentration without causing aggregation or precipitation of the macromolecule (usually 2-50 mg/ mL). Introducing the sample to precipitating agent can promote the nucleation of protein crystals in the solution, which can result in large three-dimensional crystals growing from the solution. There are two main techniques to obtain crystals: vapor diffusion and batch crystallization. In vapor diffusion, a drop containing a mixture of precipitant and protein solutions is sealed in a chamber with pure precipitant. Water vapor then diffuses out of the drop until the osmolarity of the drop and the precipitant are equal (Figure 1A). The dehydration of the drop causes a slow concentration of both protein and precipitant until equilibrium is achieved, ideally in the crystal nucleation zone of the phase diagram. The batch method relies on bringing the protein directly into the nucleation zone by mixing protein with the appropriate amount of precipitant (Figure 1B). This method is usually performed under a paraffin/mineral oil mixture to prevent the diffusion of water out of the drop. Here we will demonstrate two kinds of experimental setup for vapor diffusion, hanging drop and sitting drop, in addition to batch crystallization under oil.
Molecular Biology, Issue 47, protein crystallization, nucleic acid crystallization, vapor diffusion, X-ray crystallography, precipitant
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Protease- and Acid-catalyzed Labeling Workflows Employing 18O-enriched Water
Authors: Diana Klingler, Markus Hardt.
Institutions: Boston Biomedical Research Institute.
Stable isotopes are essential tools in biological mass spectrometry. Historically, 18O-stable isotopes have been extensively used to study the catalytic mechanisms of proteolytic enzymes1-3. With the advent of mass spectrometry-based proteomics, the enzymatically-catalyzed incorporation of 18O-atoms from stable isotopically enriched water has become a popular method to quantitatively compare protein expression levels (reviewed by Fenselau and Yao4, Miyagi and Rao5 and Ye et al.6). 18O-labeling constitutes a simple and low-cost alternative to chemical (e.g. iTRAQ, ICAT) and metabolic (e.g. SILAC) labeling techniques7. Depending on the protease utilized, 18O-labeling can result in the incorporation of up to two 18O-atoms in the C-terminal carboxyl group of the cleavage product3. The labeling reaction can be subdivided into two independent processes, the peptide bond cleavage and the carboxyl oxygen exchange reaction8. In our PALeO (protease-assisted labeling employing 18O-enriched water) adaptation of enzymatic 18O-labeling, we utilized 50% 18O-enriched water to yield distinctive isotope signatures. In combination with high-resolution matrix-assisted laser desorption ionization time-of-flight tandem mass spectrometry (MALDI-TOF/TOF MS/MS), the characteristic isotope envelopes can be used to identify cleavage products with a high level of specificity. We previously have used the PALeO-methodology to detect and characterize endogenous proteases9 and monitor proteolytic reactions10-11. Since PALeO encodes the very essence of the proteolytic cleavage reaction, the experimental setup is simple and biochemical enrichment steps of cleavage products can be circumvented. The PALeO-method can easily be extended to (i) time course experiments that monitor the dynamics of proteolytic cleavage reactions and (ii) the analysis of proteolysis in complex biological samples that represent physiological conditions. PALeO-TimeCourse experiments help identifying rate-limiting processing steps and reaction intermediates in complex proteolytic pathway reactions. Furthermore, the PALeO-reaction allows us to identify proteolytic enzymes such as the serine protease trypsin that is capable to rebind its cleavage products and catalyze the incorporation of a second 18O-atom. Such "double-labeling" enzymes can be used for postdigestion 18O-labeling, in which peptides are exclusively labeled by the carboxyl oxygen exchange reaction. Our third strategy extends labeling employing 18O-enriched water beyond enzymes and uses acidic pH conditions to introduce 18O-stable isotope signatures into peptides.
Biochemistry, Issue 72, Molecular Biology, Proteins, Proteomics, Chemistry, Physics, MALDI-TOF mass spectrometry, proteomics, proteolysis, quantification, stable isotope labeling, labeling, catalyst, peptides, 18-O enriched water
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
Authors: Jennifer J. Heisz, Anthony R. McIntosh.
Institutions: Baycrest.
When considering human neuroimaging data, an appreciation of signal variability represents a fundamental innovation in the way we think about brain signal. Typically, researchers represent the brain's response as the mean across repeated experimental trials and disregard signal fluctuations over time as "noise". However, it is becoming clear that brain signal variability conveys meaningful functional information about neural network dynamics. This article describes the novel method of multiscale entropy (MSE) for quantifying brain signal variability. MSE may be particularly informative of neural network dynamics because it shows timescale dependence and sensitivity to linear and nonlinear dynamics in the data.
Neuroscience, Issue 76, Neurobiology, Anatomy, Physiology, Medicine, Biomedical Engineering, Electroencephalography, EEG, electroencephalogram, Multiscale entropy, sample entropy, MEG, neuroimaging, variability, noise, timescale, non-linear, brain signal, information theory, brain, imaging
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Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture
Authors: Bernd Rädle, Andrzej J. Rutkowski, Zsolt Ruzsics, Caroline C. Friedel, Ulrich H. Koszinowski, Lars Dölken.
Institutions: Max von Pettenkofer Institute, University of Cambridge, Ludwig-Maximilians-University Munich.
The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene expression. Along with a better understanding of the involved molecular mechanisms, precise measurements of the underlying kinetics have become increasingly important. Here, these powerful methodologies face major limitations due to intrinsic properties of the template samples they study, i.e. total cellular RNA. In many cases changes in total cellular RNA occur either too slowly or too quickly to represent the underlying molecular events and their kinetics with sufficient resolution. In addition, the contribution of alterations in RNA synthesis, processing, and decay are not readily differentiated. We recently developed high-resolution gene expression profiling to overcome these limitations. Our approach is based on metabolic labeling of newly transcribed RNA with 4-thiouridine (thus also referred to as 4sU-tagging) followed by rigorous purification of newly transcribed RNA using thiol-specific biotinylation and streptavidin-coated magnetic beads. It is applicable to a broad range of organisms including vertebrates, Drosophila, and yeast. We successfully applied 4sU-tagging to study real-time kinetics of transcription factor activities, provide precise measurements of RNA half-lives, and obtain novel insights into the kinetics of RNA processing. Finally, computational modeling can be employed to generate an integrated, comprehensive analysis of the underlying molecular mechanisms.
Genetics, Issue 78, Cellular Biology, Molecular Biology, Microbiology, Biochemistry, Eukaryota, Investigative Techniques, Biological Phenomena, Gene expression profiling, RNA synthesis, RNA processing, RNA decay, 4-thiouridine, 4sU-tagging, microarray analysis, RNA-seq, RNA, DNA, PCR, sequencing
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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
Authors: Corey D. Broeckling, Adam L. Heuberger, Jessica E. Prenni.
Institutions: Colorado State University.
Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. The approach offers an unbiased and in-depth analysis that can enable the development of diagnostic tests, novel therapies, and further our understanding of disease processes. The inherent chemical diversity of the metabolome creates significant analytical challenges and there is no single experimental approach that can detect all metabolites. Additionally, the biological variation in individual metabolism and the dependence of metabolism on environmental factors necessitates large sample numbers to achieve the appropriate statistical power required for meaningful biological interpretation. To address these challenges, this tutorial outlines an analytical workflow for large scale non-targeted metabolite profiling of serum by UPLC-MS. The procedure includes guidelines for sample organization and preparation, data acquisition, quality control, and metabolite identification and will enable reliable acquisition of data for large experiments and provide a starting point for laboratories new to non-targeted metabolite profiling by UPLC-MS.
Chemistry, Issue 73, Biochemistry, Genetics, Molecular Biology, Physiology, Genomics, Proteins, Proteomics, Metabolomics, Metabolite Profiling, Non-targeted metabolite profiling, mass spectrometry, Ultra Performance Liquid Chromatography, UPLC-MS, serum, spectrometry
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RNA Secondary Structure Prediction Using High-throughput SHAPE
Authors: Sabrina Lusvarghi, Joanna Sztuba-Solinska, Katarzyna J. Purzycka, Jason W. Rausch, Stuart F.J. Le Grice.
Institutions: Frederick National Laboratory for Cancer Research.
Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed "high-throughput selective 2' hydroxyl acylation analyzed by primer extension", or SHAPE, allows prediction of RNA secondary structure with single nucleotide resolution. This approach utilizes chemical probing agents that preferentially acylate single stranded or flexible regions of RNA in aqueous solution. Sites of chemical modification are detected by reverse transcription of the modified RNA, and the products of this reaction are fractionated by automated capillary electrophoresis (CE). Since reverse transcriptase pauses at those RNA nucleotides modified by the SHAPE reagents, the resulting cDNA library indirectly maps those ribonucleotides that are single stranded in the context of the folded RNA. Using ShapeFinder software, the electropherograms produced by automated CE are processed and converted into nucleotide reactivity tables that are themselves converted into pseudo-energy constraints used in the RNAStructure (v5.3) prediction algorithm. The two-dimensional RNA structures obtained by combining SHAPE probing with in silico RNA secondary structure prediction have been found to be far more accurate than structures obtained using either method alone.
Genetics, Issue 75, Molecular Biology, Biochemistry, Virology, Cancer Biology, Medicine, Genomics, Nucleic Acid Probes, RNA Probes, RNA, High-throughput SHAPE, Capillary electrophoresis, RNA structure, RNA probing, RNA folding, secondary structure, DNA, nucleic acids, electropherogram, synthesis, transcription, high throughput, sequencing
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From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
Authors: Carmine Di Rienzo, Enrico Gratton, Fabio Beltram, Francesco Cardarelli.
Institutions: Scuola Normale Superiore, Instituto Italiano di Tecnologia, University of California, Irvine.
It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn’t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.
Bioengineering, Issue 92, fluorescence, protein dynamics, lipid dynamics, membrane heterogeneity, transient confinement, single molecule, GFP
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