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Pubmed Article
Systematic construction of kinetic models from genome-scale metabolic networks.
PLoS ONE
PUBLISHED: 01-01-2013
The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.
Authors: Maggie Roy, Scott Nugent, Sébastien Tremblay, Maxime Descoteaux, Jean-François Beaudoin, Luc Tremblay, Roger Lecomte, Stephen C Cunnane.
Published: 12-28-2013
ABSTRACT
We present a method for comparing the uptake of the brain's two key energy substrates: glucose and ketones (acetoacetate [AcAc] in this case) in the rat. The developed method is a small-animal positron emission tomography (PET) protocol, in which 11C-AcAc and 18F-fluorodeoxyglucose (18F-FDG) are injected sequentially in each animal. This dual tracer PET acquisition is possible because of the short half-life of 11C (20.4 min). The rats also undergo a magnetic resonance imaging (MRI) acquisition seven days before the PET protocol. Prior to image analysis, PET and MRI images are coregistered to allow the measurement of regional cerebral uptake (cortex, hippocampus, striatum, and cerebellum). A quantitative measure of 11C-AcAc and 18F-FDG brain uptake (cerebral metabolic rate; μmol/100 g/min) is determined by kinetic modeling using the image-derived input function (IDIF) method. Our new dual tracer PET protocol is robust and flexible; the two tracers used can be replaced by different radiotracers to evaluate other processes in the brain. Moreover, our protocol is applicable to the study of brain fuel supply in multiple conditions such as normal aging and neurodegenerative pathologies such as Alzheimer's and Parkinson's diseases.
28 Related JoVE Articles!
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Hot Biological Catalysis: Isothermal Titration Calorimetry to Characterize Enzymatic Reactions
Authors: Luca Mazzei, Stefano Ciurli, Barbara Zambelli.
Institutions: University of Bologna.
Isothermal titration calorimetry (ITC) is a well-described technique that measures the heat released or absorbed during a chemical reaction, using it as an intrinsic probe to characterize virtually every chemical process. Nowadays, this technique is extensively applied to determine thermodynamic parameters of biomolecular binding equilibria. In addition, ITC has been demonstrated to be able of directly measuring kinetics and thermodynamic parameters (kcat, KM, ΔH) of enzymatic reactions, even though this application is still underexploited. As heat changes spontaneously occur during enzymatic catalysis, ITC does not require any modification or labeling of the system under analysis and can be performed in solution. Moreover, the method needs little amount of material. These properties make ITC an invaluable, powerful and unique tool to study enzyme kinetics in several applications, such as, for example, drug discovery. In this work an experimental ITC-based method to quantify kinetics and thermodynamics of enzymatic reactions is thoroughly described. This method is applied to determine kcat and KM of the enzymatic hydrolysis of urea by Canavalia ensiformis (jack bean) urease. Calculation of intrinsic molar enthalpy (ΔHint) of the reaction is performed. The values thus obtained are consistent with previous data reported in literature, demonstrating the reliability of the methodology.
Chemistry, Issue 86, Isothermal titration calorimetry, enzymatic catalysis, kinetics, thermodynamics, enthalpy, Michaelis constant, catalytic rate constant, urease
51487
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Recapitulation of an Ion Channel IV Curve Using Frequency Components
Authors: John R. Rigby, Steven Poelzing.
Institutions: University of Utah.
INTRODUCTION: Presently, there are no established methods to measure multiple ion channel types simultaneously and decompose the measured current into portions attributable to each channel type. This study demonstrates how impedance spectroscopy may be used to identify specific frequencies that highly correlate with the steady state current amplitude measured during voltage clamp experiments. The method involves inserting a noise function containing specific frequencies into the voltage step protocol. In the work presented, a model cell is used to demonstrate that no high correlations are introduced by the voltage clamp circuitry, and also that the noise function itself does not introduce any high correlations when no ion channels are present. This validation is necessary before the technique can be applied to preparations containing ion channels. The purpose of the protocol presented is to demonstrate how to characterize the frequency response of a single ion channel type to a noise function. Once specific frequencies have been identified in an individual channel type, they can be used to reproduce the steady state current voltage (IV) curve. Frequencies that highly correlate with one channel type and minimally correlate with other channel types may then be used to estimate the current contribution of multiple channel types measured simultaneously. METHODS: Voltage clamp measurements were performed on a model cell using a standard voltage step protocol (-150 to +50 mV, 5mV steps). Noise functions containing equal magnitudes of 1-15 kHz frequencies (zero to peak amplitudes: 50 or 100mV) were inserted into each voltage step. The real component of the Fast Fourier transform (FFT) of the output signal was calculated with and without noise for each step potential. The magnitude of each frequency as a function of voltage step was correlated with the current amplitude at the corresponding voltages. RESULTS AND CONCLUSIONS: In the absence of noise (control), magnitudes of all frequencies except the DC component correlated poorly (|R|<0.5) with the IV curve, whereas the DC component had a correlation coefficient greater than 0.999 in all measurements. The quality of correlation between individual frequencies and the IV curve did not change when a noise function was added to the voltage step protocol. Likewise, increasing the amplitude of the noise function also did not increase the correlation. Control measurements demonstrate that the voltage clamp circuitry by itself does not cause any frequencies above 0 Hz to highly correlate with the steady-state IV curve. Likewise, measurements in the presence of the noise function demonstrate that the noise function does not cause any frequencies above 0 Hz to correlate with the steady-state IV curve when no ion channels are present. Based on this verification, the method can now be applied to preparations containing a single ion channel type with the intent of identifying frequencies whose amplitudes correlate specifically with that channel type.
Biophysics, Issue 48, Ion channel, Kir2.1, impedance spectroscopy, frequency response, voltage clamp, electrophysiology
2361
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Measurement of Vacuolar and Cytosolic pH In Vivo in Yeast Cell Suspensions
Authors: Theodore T. Diakov, Maureen Tarsio, Patricia M. Kane.
Institutions: SUNY Upstate Medical University.
Vacuolar and cytosolic pH are highly regulated in yeast cells and occupy a central role in overall pH homeostasis. We describe protocols for ratiometric measurement of pH in vivo using pH-sensitive fluorophores localized to the vacuole or cytosol. Vacuolar pH is measured using BCECF, which localizes to the vacuole in yeast when introduced into cells in its acetoxymethyl ester form. Cytosolic pH is measured with a pH-sensitive GFP expressed under control of a yeast promoter, yeast pHluorin. Methods for measurement of fluorescence ratios in yeast cell suspensions in a fluorimeter are described. Through these protocols, single time point measurements of pH under different conditions or in different yeast mutants have been compared and changes in pH over time have been monitored. These methods have also been adapted to a fluorescence plate reader format for high-throughput experiments. Advantages of ratiometric pH measurements over other approaches currently in use, potential experimental problems and solutions, and prospects for future use of these techniques are also described.
Molecular Biology, Issue 74, Biochemistry, Microbiology, Cellular Biology, Biophysics, Physiology, Proteins, Vacuoles, Cytosol, Yeasts, Membrane Transport Proteins, Ion Pumps, Fluorometry, yeast, intracellular pH, vacuole, fluorescence, ratiometric, cells
50261
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Monitoring the Reductive and Oxidative Half-Reactions of a Flavin-Dependent Monooxygenase using Stopped-Flow Spectrophotometry
Authors: Elvira Romero, Reeder Robinson, Pablo Sobrado.
Institutions: Virginia Polytechnic Institute and State University.
Aspergillus fumigatus siderophore A (SidA) is an FAD-containing monooxygenase that catalyzes the hydroxylation of ornithine in the biosynthesis of hydroxamate siderophores that are essential for virulence (e.g. ferricrocin or N',N",N'''-triacetylfusarinine C)1. The reaction catalyzed by SidA can be divided into reductive and oxidative half-reactions (Scheme 1). In the reductive half-reaction, the oxidized FAD bound to Af SidA, is reduced by NADPH2,3. In the oxidative half-reaction, the reduced cofactor reacts with molecular oxygen to form a C4a-hydroperoxyflavin intermediate, which transfers an oxygen atom to ornithine. Here, we describe a procedure to measure the rates and detect the different spectral forms of SidA using a stopped-flow instrument installed in an anaerobic glove box. In the stopped-flow instrument, small volumes of reactants are rapidly mixed, and after the flow is stopped by the stop syringe (Figure 1), the spectral changes of the solution placed in the observation cell are recorded over time. In the first part of the experiment, we show how we can use the stopped-flow instrument in single mode, where the anaerobic reduction of the flavin in Af SidA by NADPH is directly measured. We then use double mixing settings where Af SidA is first anaerobically reduced by NADPH for a designated period of time in an aging loop, and then reacted with molecular oxygen in the observation cell (Figure 1). In order to perform this experiment, anaerobic buffers are necessary because when only the reductive half-reaction is monitored, any oxygen in the solutions will react with the reduced flavin cofactor and form a C4a-hydroperoxyflavin intermediate that will ultimately decay back into the oxidized flavin. This would not allow the user to accurately measure rates of reduction since there would be complete turnover of the enzyme. When the oxidative half-reaction is being studied the enzyme must be reduced in the absence of oxygen so that just the steps between reduction and oxidation are observed. One of the buffers used in this experiment is oxygen saturated so that we can study the oxidative half-reaction at higher concentrations of oxygen. These are often the procedures carried out when studying either the reductive or oxidative half-reactions with flavin-containing monooxygenases. The time scale of the pre-steady-state experiments performed with the stopped-flow is milliseconds to seconds, which allow the determination of intrinsic rate constants and the detection and identification of intermediates in the reaction4. The procedures described here can be applied to other flavin-dependent monooxygenases.5,6
Bioengineering, Issue 61, Stopped-flow, kinetic mechanism, SidA, C4a-hydroperoxyflavin, monooxygenase, Aspergillus fumigatus
3803
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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Authors: Alla Gagarinova, Mohan Babu, Jack Greenblatt, Andrew Emili.
Institutions: University of Toronto, University of Toronto, University of Regina.
Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10. Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.
Genetics, Issue 69, Molecular Biology, Medicine, Biochemistry, Microbiology, Aggravating, alleviating, conjugation, double mutant, Escherichia coli, genetic interaction, Gram-negative bacteria, homologous recombination, network, synthetic lethality or sickness, suppression
4056
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Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
Authors: Jeremy D. Smith, Abbie E. Ferris, Gary D. Heise, Richard N. Hinrichs, Philip E. Martin.
Institutions: University of Northern Colorado, Arizona State University, Iowa State University.
The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee prosthesis, and 2) contrast the effects of the proposed technique and that of using intact limb inertial properties on joint kinetic estimates during walking in unilateral, transtibial amputees. An oscillation and reaction board system was validated and shown to be reliable when measuring inertial properties of known geometrical solids. When direct measurements of inertial properties of the prosthesis were used in inverse dynamics modeling of the lower extremity compared with inertial estimates based on an intact shank and foot, joint kinetics at the hip and knee were significantly lower during the swing phase of walking. Differences in joint kinetics during stance, however, were smaller than those observed during swing. Therefore, researchers focusing on the swing phase of walking should consider the impact of prosthesis inertia property estimates on study outcomes. For stance, either one of the two inertial models investigated in our study would likely lead to similar outcomes with an inverse dynamics assessment.
Bioengineering, Issue 87, prosthesis inertia, amputee locomotion, below-knee prosthesis, transtibial amputee
50977
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
50319
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The Use of Chemostats in Microbial Systems Biology
Authors: Naomi Ziv, Nathan J. Brandt, David Gresham.
Institutions: New York University .
Cells regulate their rate of growth in response to signals from the external world. As the cell grows, diverse cellular processes must be coordinated including macromolecular synthesis, metabolism and ultimately, commitment to the cell division cycle. The chemostat, a method of experimentally controlling cell growth rate, provides a powerful means of systematically studying how growth rate impacts cellular processes - including gene expression and metabolism - and the regulatory networks that control the rate of cell growth. When maintained for hundreds of generations chemostats can be used to study adaptive evolution of microbes in environmental conditions that limit cell growth. We describe the principle of chemostat cultures, demonstrate their operation and provide examples of their various applications. Following a period of disuse after their introduction in the middle of the twentieth century, the convergence of genome-scale methodologies with a renewed interest in the regulation of cell growth and the molecular basis of adaptive evolution is stimulating a renaissance in the use of chemostats in biological research.
Environmental Sciences, Issue 80, Saccharomyces cerevisiae, Molecular Biology, Computational Biology, Systems Biology, Cell Biology, Genetics, Environmental Microbiology, Biochemistry, Chemostat, growth-rate, steady state, nutrient limitation, adaptive evolution
50168
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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
50195
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A Chemical Screening Procedure for Glucocorticoid Signaling with a Zebrafish Larva Luciferase Reporter System
Authors: Benjamin D. Weger, Meltem Weger, Nicole Jung, Christin Lederer, Stefan Bräse, Thomas Dickmeis.
Institutions: Karlsruhe Institute of Technology - Campus North, Karlsruhe Institute of Technology - Campus North, Karlsruhe Institute of Technology - Campus South.
Glucocorticoid stress hormones and their artificial derivatives are widely used drugs to treat inflammation, but long-term treatment with glucocorticoids can lead to severe side effects. Test systems are needed to search for novel compounds influencing glucocorticoid signaling in vivo or to determine unwanted effects of compounds on the glucocorticoid signaling pathway. We have established a transgenic zebrafish assay which allows the measurement of glucocorticoid signaling activity in vivo and in real-time, the GRIZLY assay (Glucocorticoid Responsive In vivo Zebrafish Luciferase activitY). The luciferase-based assay detects effects on glucocorticoid signaling with high sensitivity and specificity, including effects by compounds that require metabolization or affect endogenous glucocorticoid production. We present here a detailed protocol for conducting chemical screens with this assay. We describe data acquisition, normalization, and analysis, placing a focus on quality control and data visualization. The assay provides a simple, time-resolved, and quantitative readout. It can be operated as a stand-alone platform, but is also easily integrated into high-throughput screening workflows. It furthermore allows for many applications beyond chemical screening, such as environmental monitoring of endocrine disruptors or stress research.
Developmental Biology, Issue 79, Biochemistry, Vertebrates, Zebrafish, environmental effects (biological and animal), genetics (animal), life sciences, animal biology, animal models, biochemistry, bioengineering (general), Hormones, Hormone Substitutes, and Hormone Antagonists, zebrafish, Danio rerio, chemical screening, luciferase, glucocorticoid, stress, high-throughput screening, receiver operating characteristic curve, in vivo, animal model
50439
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Monitoring Cell-autonomous Circadian Clock Rhythms of Gene Expression Using Luciferase Bioluminescence Reporters
Authors: Chidambaram Ramanathan, Sanjoy K. Khan, Nimish D. Kathale, Haiyan Xu, Andrew C. Liu.
Institutions: The University of Memphis.
In mammals, many aspects of behavior and physiology such as sleep-wake cycles and liver metabolism are regulated by endogenous circadian clocks (reviewed1,2). The circadian time-keeping system is a hierarchical multi-oscillator network, with the central clock located in the suprachiasmatic nucleus (SCN) synchronizing and coordinating extra-SCN and peripheral clocks elsewhere1,2. Individual cells are the functional units for generation and maintenance of circadian rhythms3,4, and these oscillators of different tissue types in the organism share a remarkably similar biochemical negative feedback mechanism. However, due to interactions at the neuronal network level in the SCN and through rhythmic, systemic cues at the organismal level, circadian rhythms at the organismal level are not necessarily cell-autonomous5-7. Compared to traditional studies of locomotor activity in vivo and SCN explants ex vivo, cell-based in vitro assays allow for discovery of cell-autonomous circadian defects5,8. Strategically, cell-based models are more experimentally tractable for phenotypic characterization and rapid discovery of basic clock mechanisms5,8-13. Because circadian rhythms are dynamic, longitudinal measurements with high temporal resolution are needed to assess clock function. In recent years, real-time bioluminescence recording using firefly luciferase as a reporter has become a common technique for studying circadian rhythms in mammals14,15, as it allows for examination of the persistence and dynamics of molecular rhythms. To monitor cell-autonomous circadian rhythms of gene expression, luciferase reporters can be introduced into cells via transient transfection13,16,17 or stable transduction5,10,18,19. Here we describe a stable transduction protocol using lentivirus-mediated gene delivery. The lentiviral vector system is superior to traditional methods such as transient transfection and germline transmission because of its efficiency and versatility: it permits efficient delivery and stable integration into the host genome of both dividing and non-dividing cells20. Once a reporter cell line is established, the dynamics of clock function can be examined through bioluminescence recording. We first describe the generation of P(Per2)-dLuc reporter lines, and then present data from this and other circadian reporters. In these assays, 3T3 mouse fibroblasts and U2OS human osteosarcoma cells are used as cellular models. We also discuss various ways of using these clock models in circadian studies. Methods described here can be applied to a great variety of cell types to study the cellular and molecular basis of circadian clocks, and may prove useful in tackling problems in other biological systems.
Genetics, Issue 67, Molecular Biology, Cellular Biology, Chemical Biology, Circadian clock, firefly luciferase, real-time bioluminescence technology, cell-autonomous model, lentiviral vector, RNA interference (RNAi), high-throughput screening (HTS)
4234
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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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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
3891
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Application of Stopped-flow Kinetics Methods to Investigate the Mechanism of Action of a DNA Repair Protein
Authors: F. Noah Biro, Jie Zhai, Christopher W. Doucette, Manju M. Hingorani.
Institutions: Wesleyan University.
Transient kinetic analysis is indispensable for understanding the workings of biological macromolecules, since this approach yields mechanistic information including active site concentrations and intrinsic rate constants that govern macromolecular function. In case of enzymes, for example, transient or pre-steady state measurements identify and characterize individual events in the reaction pathway, whereas steady state measurements only yield overall catalytic efficiency and specificity. Individual events such as protein-protein or protein-ligand interactions and rate-limiting conformational changes often occur in the millisecond timescale, and can be measured directly by stopped-flow and chemical-quench flow methods. Given an optical signal such as fluorescence, stopped-flow serves as a powerful and accessible tool for monitoring reaction progress from substrate binding to product release and catalytic turnover1,2. Here, we report application of stopped-flow kinetics to probe the mechanism of action of Msh2-Msh6, a eukaryotic DNA repair protein that recognizes base-pair mismatches and insertion/deletion loops in DNA and signals mismatch repair (MMR)3-5. In doing so, Msh2-Msh6 increases the accuracy of DNA replication by three orders of magnitude (error frequency decreases from ~10-6 to10-9 bases), and thus helps preserve genomic integrity. Not surprisingly, defective human Msh2-Msh6 function is associated with hereditary non-polyposis colon cancer and other sporadic cancers6-8. In order to understand the mechanism of action of this critical DNA metabolic protein, we are probing the dynamics of Msh2-Msh6 interaction with mismatched DNA as well as the ATPase activity that fuels its actions in MMR. DNA binding is measured by rapidly mixing Msh2-Msh6 with DNA containing a 2-aminopurine (2-Ap) fluorophore adjacent to a G:T mismatch and monitoring the resulting increase in 2-aminopurine fluorescence in real time. DNA dissociation is measured by mixing pre-formed Msh2-Msh6 G:T(2-Ap) mismatch complex with unlabeled trap DNA and monitoring decrease in fluorescence over time9. Pre-steady state ATPase kinetics are measured by the change in fluorescence of 7-diethylamino-3-((((2-maleimidyl)ethyl)amino)carbonyl) coumarin)-labeled Phosphate Binding Protein (MDCC-PBP) on binding phosphate (Pi) released by Msh2-Msh6 following ATP hydrolysis9,10. The data reveal rapid binding of Msh2-Msh6 to a G:T mismatch and formation of a long-lived Msh2-Msh6 G:T complex, which in turn results in suppression of ATP hydrolysis and stabilization of the protein in an ATP-bound form. The reaction kinetics provide clear support for the hypothesis that ATP-bound Msh2-Msh6 signals DNA repair on binding a mismatched base pair in the double helix. F. Noah Biro and Jie Zhai contributed to this paper equally.
Cellular Biology, Issue 37, DNA mismatch repair, Stopped-flow kinetics, Msh2-Msh6, ATPase rate, DNA binding
1874
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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
50242
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Determination of Protein-ligand Interactions Using Differential Scanning Fluorimetry
Authors: Mirella Vivoli, Halina R. Novak, Jennifer A. Littlechild, Nicholas J. Harmer.
Institutions: University of Exeter.
A wide range of methods are currently available for determining the dissociation constant between a protein and interacting small molecules. However, most of these require access to specialist equipment, and often require a degree of expertise to effectively establish reliable experiments and analyze data. Differential scanning fluorimetry (DSF) is being increasingly used as a robust method for initial screening of proteins for interacting small molecules, either for identifying physiological partners or for hit discovery. This technique has the advantage that it requires only a PCR machine suitable for quantitative PCR, and so suitable instrumentation is available in most institutions; an excellent range of protocols are already available; and there are strong precedents in the literature for multiple uses of the method. Past work has proposed several means of calculating dissociation constants from DSF data, but these are mathematically demanding. Here, we demonstrate a method for estimating dissociation constants from a moderate amount of DSF experimental data. These data can typically be collected and analyzed within a single day. We demonstrate how different models can be used to fit data collected from simple binding events, and where cooperative binding or independent binding sites are present. Finally, we present an example of data analysis in a case where standard models do not apply. These methods are illustrated with data collected on commercially available control proteins, and two proteins from our research program. Overall, our method provides a straightforward way for researchers to rapidly gain further insight into protein-ligand interactions using DSF.
Biophysics, Issue 91, differential scanning fluorimetry, dissociation constant, protein-ligand interactions, StepOne, cooperativity, WcbI.
51809
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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
51216
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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
50358
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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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In Situ SIMS and IR Spectroscopy of Well-defined Surfaces Prepared by Soft Landing of Mass-selected Ions
Authors: Grant E. Johnson, K. Don Dasitha Gunaratne, Julia Laskin.
Institutions: Pacific Northwest National Laboratory.
Soft landing of mass-selected ions onto surfaces is a powerful approach for the highly-controlled preparation of materials that are inaccessible using conventional synthesis techniques. Coupling soft landing with in situ characterization using secondary ion mass spectrometry (SIMS) and infrared reflection absorption spectroscopy (IRRAS) enables analysis of well-defined surfaces under clean vacuum conditions. The capabilities of three soft-landing instruments constructed in our laboratory are illustrated for the representative system of surface-bound organometallics prepared by soft landing of mass-selected ruthenium tris(bipyridine) dications, [Ru(bpy)3]2+ (bpy = bipyridine), onto carboxylic acid terminated self-assembled monolayer surfaces on gold (COOH-SAMs). In situ time-of-flight (TOF)-SIMS provides insight into the reactivity of the soft-landed ions. In addition, the kinetics of charge reduction, neutralization and desorption occurring on the COOH-SAM both during and after ion soft landing are studied using in situ Fourier transform ion cyclotron resonance (FT-ICR)-SIMS measurements. In situ IRRAS experiments provide insight into how the structure of organic ligands surrounding metal centers is perturbed through immobilization of organometallic ions on COOH-SAM surfaces by soft landing. Collectively, the three instruments provide complementary information about the chemical composition, reactivity and structure of well-defined species supported on surfaces.
Chemistry, Issue 88, soft landing, mass selected ions, electrospray, secondary ion mass spectrometry, infrared spectroscopy, organometallic, catalysis
51344
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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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Measuring Cation Transport by Na,K- and H,K-ATPase in Xenopus Oocytes by Atomic Absorption Spectrophotometry: An Alternative to Radioisotope Assays
Authors: Katharina L. Dürr, Neslihan N. Tavraz, Susan Spiller, Thomas Friedrich.
Institutions: Technical University of Berlin, Oregon Health & Science University.
Whereas cation transport by the electrogenic membrane transporter Na+,K+-ATPase can be measured by electrophysiology, the electroneutrally operating gastric H+,K+-ATPase is more difficult to investigate. Many transport assays utilize radioisotopes to achieve a sufficient signal-to-noise ratio, however, the necessary security measures impose severe restrictions regarding human exposure or assay design. Furthermore, ion transport across cell membranes is critically influenced by the membrane potential, which is not straightforwardly controlled in cell culture or in proteoliposome preparations. Here, we make use of the outstanding sensitivity of atomic absorption spectrophotometry (AAS) towards trace amounts of chemical elements to measure Rb+ or Li+ transport by Na+,K+- or gastric H+,K+-ATPase in single cells. Using Xenopus oocytes as expression system, we determine the amount of Rb+ (Li+) transported into the cells by measuring samples of single-oocyte homogenates in an AAS device equipped with a transversely heated graphite atomizer (THGA) furnace, which is loaded from an autosampler. Since the background of unspecific Rb+ uptake into control oocytes or during application of ATPase-specific inhibitors is very small, it is possible to implement complex kinetic assay schemes involving a large number of experimental conditions simultaneously, or to compare the transport capacity and kinetics of site-specifically mutated transporters with high precision. Furthermore, since cation uptake is determined on single cells, the flux experiments can be carried out in combination with two-electrode voltage-clamping (TEVC) to achieve accurate control of the membrane potential and current. This allowed e.g. to quantitatively determine the 3Na+/2K+ transport stoichiometry of the Na+,K+-ATPase and enabled for the first time to investigate the voltage dependence of cation transport by the electroneutrally operating gastric H+,K+-ATPase. In principle, the assay is not limited to K+-transporting membrane proteins, but it may work equally well to address the activity of heavy or transition metal transporters, or uptake of chemical elements by endocytotic processes.
Biochemistry, Issue 72, Chemistry, Biophysics, Bioengineering, Physiology, Molecular Biology, electrochemical processes, physical chemistry, spectrophotometry (application), spectroscopic chemical analysis (application), life sciences, temperature effects (biological, animal and plant), Life Sciences (General), Na+,K+-ATPase, H+,K+-ATPase, Cation Uptake, P-type ATPases, Atomic Absorption Spectrophotometry (AAS), Two-Electrode Voltage-Clamp, Xenopus Oocytes, Rb+ Flux, Transversely Heated Graphite Atomizer (THGA) Furnace, electrophysiology, animal model
50201
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A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Authors: Xiaojing Liu, Zheng Ser, Ahmad A. Cluntun, Samantha J. Mentch, Jason W. Locasale.
Institutions: Cornell University, Cornell University.
Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.
Chemistry, Issue 87, high-resolution mass spectrometry, metabolomics, positive/negative switching, low mass calibration, Orbitrap
51358
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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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The Importance of Correct Protein Concentration for Kinetics and Affinity Determination in Structure-function Analysis
Authors: Ewa Pol.
Institutions: GE Healthcare Bio-Sciences AB.
In this study, we explore the interaction between the bovine cysteine protease inhibitor cystatin B and a catalytically inactive form of papain (Fig. 1), a plant cysteine protease, by real-time label-free analysis using Biacore X100. Several cystatin B variants with point mutations in areas of interaction with papain, are produced. For each cystatin B variant we determine its specific binding concentration using calibration-free concentration analysis (CFCA) and compare the values obtained with total protein concentration as determined by A280. After that, the kinetics of each cystatin B variant binding to papain is measured using single-cycle kinetics (SCK). We show that one of the four cystatin B variants we examine is only partially active for binding. This partial activity, revealed by CFCA, translates to a significant difference in the association rate constant (ka) and affinity (KD), compared to the values calculated using total protein concentration. Using CFCA in combination with kinetic analysis in a structure-function study contributes to obtaining reliable results, and helps to make the right interpretation of the interaction mechanism.
Cellular Biology, Issue 37, Protein interaction, Surface Plasmon Resonance, Biacore X100, CFCA, Cystatin B, Papain
1746
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Metabolic Pathway Confirmation and Discovery Through 13C-labeling of Proteinogenic Amino Acids
Authors: Le You, Lawrence Page, Xueyang Feng, Bert Berla, Himadri B. Pakrasi, Yinjie J. Tang.
Institutions: Washington University, Washington University, Washington University.
Microbes have complex metabolic pathways that can be investigated using biochemistry and functional genomics methods. One important technique to examine cell central metabolism and discover new enzymes is 13C-assisted metabolism analysis 1. This technique is based on isotopic labeling, whereby microbes are fed with a 13C labeled substrates. By tracing the atom transition paths between metabolites in the biochemical network, we can determine functional pathways and discover new enzymes. As a complementary method to transcriptomics and proteomics, approaches for isotopomer-assisted analysis of metabolic pathways contain three major steps 2. First, we grow cells with 13C labeled substrates. In this step, the composition of the medium and the selection of labeled substrates are two key factors. To avoid measurement noises from non-labeled carbon in nutrient supplements, a minimal medium with a sole carbon source is required. Further, the choice of a labeled substrate is based on how effectively it will elucidate the pathway being analyzed. Because novel enzymes often involve different reaction stereochemistry or intermediate products, in general, singly labeled carbon substrates are more informative for detection of novel pathways than uniformly labeled ones for detection of novel pathways3, 4. Second, we analyze amino acid labeling patterns using GC-MS. Amino acids are abundant in protein and thus can be obtained from biomass hydrolysis. Amino acids can be derivatized by N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide (TBDMS) before GC separation. TBDMS derivatized amino acids can be fragmented by MS and result in different arrays of fragments. Based on the mass to charge (m/z) ratio of fragmented and unfragmented amino acids, we can deduce the possible labeled patterns of the central metabolites that are precursors of the amino acids. Third, we trace 13C carbon transitions in the proposed pathways and, based on the isotopomer data, confirm whether these pathways are active 2. Measurement of amino acids provides isotopic labeling information about eight crucial precursor metabolites in the central metabolism. These metabolic key nodes can reflect the functions of associated central pathways. 13C-assisted metabolism analysis via proteinogenic amino acids can be widely used for functional characterization of poorly-characterized microbial metabolism1. In this protocol, we will use Cyanothece 51142 as the model strain to demonstrate the use of labeled carbon substrates for discovering new enzymatic functions.
Molecular Biology, Issue 59, GC-MS, novel pathway, metabolism, labeling, phototrophic microorganism
3583
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Generation of Shear Adhesion Map Using SynVivo Synthetic Microvascular Networks
Authors: Ashley M. Smith, Balabhaskar Prabhakarpandian, Kapil Pant.
Institutions: CFD Research Corporation.
Cell/particle adhesion assays are critical to understanding the biochemical interactions involved in disease pathophysiology and have important applications in the quest for the development of novel therapeutics. Assays using static conditions fail to capture the dependence of adhesion on shear, limiting their correlation with in vivo environment. Parallel plate flow chambers that quantify adhesion under physiological fluid flow need multiple experiments for the generation of a shear adhesion map. In addition, they do not represent the in vivo scale and morphology and require large volumes (~ml) of reagents for experiments. In this study, we demonstrate the generation of shear adhesion map from a single experiment using a microvascular network based microfluidic device, SynVivo-SMN. This device recreates the complex in vivo vasculature including geometric scale, morphological elements, flow features and cellular interactions in an in vitro format, thereby providing a biologically realistic environment for basic and applied research in cellular behavior, drug delivery, and drug discovery. The assay was demonstrated by studying the interaction of the 2 µm biotin-coated particles with avidin-coated surfaces of the microchip. The entire range of shear observed in the microvasculature is obtained in a single assay enabling adhesion vs. shear map for the particles under physiological conditions.
Bioengineering, Issue 87, particle, adhesion, shear, microfluidics, vasculature, networks
51025
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Identification of Key Factors Regulating Self-renewal and Differentiation in EML Hematopoietic Precursor Cells by RNA-sequencing Analysis
Authors: Shan Zong, Shuyun Deng, Kenian Chen, Jia Qian Wu.
Institutions: The University of Texas Graduate School of Biomedical Sciences at Houston.
Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient's hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study. RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment. In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro and in vivo.
Genetics, Issue 93, EML Cells, Self-renewal, Differentiation, Hematopoietic precursor cell, RNA-Sequencing, Data analysis
52104
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