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Pubmed Article
Simulating metabolism with statistical thermodynamics.
PUBLISHED: 01-01-2014
New methods are needed for large scale modeling of metabolism that predict metabolite levels and characterize the thermodynamics of individual reactions and pathways. Current approaches use either kinetic simulations, which are difficult to extend to large networks of reactions because of the need for rate constants, or flux-based methods, which have a large number of feasible solutions because they are unconstrained by the law of mass action. This report presents an alternative modeling approach based on statistical thermodynamics. The principles of this approach are demonstrated using a simple set of coupled reactions, and then the system is characterized with respect to the changes in energy, entropy, free energy, and entropy production. Finally, the physical and biochemical insights that this approach can provide for metabolism are demonstrated by application to the tricarboxylic acid (TCA) cycle of Escherichia coli. The reaction and pathway thermodynamics are evaluated and predictions are made regarding changes in concentration of TCA cycle intermediates due to 10- and 100-fold changes in the ratio of NAD+:NADH concentrations. Finally, the assumptions and caveats regarding the use of statistical thermodynamics to model non-equilibrium reactions are discussed.
Authors: Luca Mazzei, Stefano Ciurli, Barbara Zambelli.
Published: 04-04-2014
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.
24 Related JoVE Articles!
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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
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Waste Water Derived Electroactive Microbial Biofilms: Growth, Maintenance, and Basic Characterization
Authors: Carla Gimkiewicz, Falk Harnisch.
Institutions: UFZ - Helmholtz-Centre for Environmental Research.
The growth of anodic electroactive microbial biofilms from waste water inocula in a fed-batch reactor is demonstrated using a three-electrode setup controlled by a potentiostat. Thereby the use of potentiostats allows an exact adjustment of the electrode potential and ensures reproducible microbial culturing conditions. During growth the current production is monitored using chronoamperometry (CA). Based on these data the maximum current density (jmax) and the coulombic efficiency (CE) are discussed as measures for characterization of the bioelectrocatalytic performance. Cyclic voltammetry (CV), a nondestructive, i.e. noninvasive, method, is used to study the extracellular electron transfer (EET) of electroactive bacteria. CV measurements are performed on anodic biofilm electrodes in the presence of the microbial substrate, i.e. turnover conditions, and in the absence of the substrate, i.e. nonturnover conditions, using different scan rates. Subsequently, data analysis is exemplified and fundamental thermodynamic parameters of the microbial EET are derived and explained: peak potential (Ep), peak current density (jp), formal potential (Ef) and peak separation (ΔEp). Additionally the limits of the method and the state-of the art data analysis are addressed. Thereby this video-article shall provide a guide for the basic experimental steps and the fundamental data analysis.
Environmental Sciences, Issue 82, Electrochemistry, Microbial fuel cell, microbial bioelectrochemical system, cyclic voltammetry, electroactive bacteria, microbial bioelectrochemistry, bioelectrocatalysis
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Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues
Authors: Jason Bell, Edwin Dickinson, David R. Badcock, Frederick A. A. Kingdom.
Institutions: Australian National University, University of Western Australia, McGill University.
The speed and accuracy of object recognition is compromised by a change in viewpoint; demonstrating that human observers are sensitive to this transformation. Here we discuss a novel method for simulating the appearance of an object that has undergone a rotation-in-depth, and include an exposition of the differences between perspective and orthographic projections. Next we describe a method by which human sensitivity to rotation-in-depth can be measured. Finally we discuss an apparatus for creating a vivid percept of a 3-dimensional rotation-in-depth; the Wheatstone Eight Mirror Stereoscope. By doing so, we reveal a means by which to evaluate the role of stereoscopic cues in the discrimination of viewpoint rotated shapes and objects.
Behavior, Issue 82, stereo, curvature, shape, viewpoint, 3D, object recognition, rotation-in-depth (RID)
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Submillisecond Conformational Changes in Proteins Resolved by Photothermal Beam Deflection
Authors: Walter G. Gonzalez, Jaroslava Miksovska.
Institutions: Florida International University.
Photothermal beam deflection together with photo-acoustic calorimetry and thermal grating belongs to the family of photothermal methods that monitor the time-profile volume and enthalpy changes of light induced conformational changes in proteins on microsecond to millisecond time-scales that are not accessible using traditional stop-flow instruments. In addition, since overall changes in volume and/or enthalpy are probed, these techniques can be applied to proteins and other biomacromolecules that lack a fluorophore and or a chromophore label. To monitor dynamics and energetics of structural changes associated with Ca2+ binding to calcium transducers, such neuronal calcium sensors, a caged calcium compound, DM-nitrophen, is employed to photo-trigger a fast (τ < 20 μsec) increase in free calcium concentration and the associated volume and enthalpy changes are probed using photothermal beam deflection technique.
Chemistry, Issue 84, photothermal techniques, photothermal beam deflection, volume change, enthalpy change, calcium sensors, potassium channel interaction protein, DM-nitrophen
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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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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
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A Restriction Enzyme Based Cloning Method to Assess the In vitro Replication Capacity of HIV-1 Subtype C Gag-MJ4 Chimeric Viruses
Authors: Daniel T. Claiborne, Jessica L. Prince, Eric Hunter.
Institutions: Emory University, Emory University.
The protective effect of many HLA class I alleles on HIV-1 pathogenesis and disease progression is, in part, attributed to their ability to target conserved portions of the HIV-1 genome that escape with difficulty. Sequence changes attributed to cellular immune pressure arise across the genome during infection, and if found within conserved regions of the genome such as Gag, can affect the ability of the virus to replicate in vitro. Transmission of HLA-linked polymorphisms in Gag to HLA-mismatched recipients has been associated with reduced set point viral loads. We hypothesized this may be due to a reduced replication capacity of the virus. Here we present a novel method for assessing the in vitro replication of HIV-1 as influenced by the gag gene isolated from acute time points from subtype C infected Zambians. This method uses restriction enzyme based cloning to insert the gag gene into a common subtype C HIV-1 proviral backbone, MJ4. This makes it more appropriate to the study of subtype C sequences than previous recombination based methods that have assessed the in vitro replication of chronically derived gag-pro sequences. Nevertheless, the protocol could be readily modified for studies of viruses from other subtypes. Moreover, this protocol details a robust and reproducible method for assessing the replication capacity of the Gag-MJ4 chimeric viruses on a CEM-based T cell line. This method was utilized for the study of Gag-MJ4 chimeric viruses derived from 149 subtype C acutely infected Zambians, and has allowed for the identification of residues in Gag that affect replication. More importantly, the implementation of this technique has facilitated a deeper understanding of how viral replication defines parameters of early HIV-1 pathogenesis such as set point viral load and longitudinal CD4+ T cell decline.
Infectious Diseases, Issue 90, HIV-1, Gag, viral replication, replication capacity, viral fitness, MJ4, CEM, GXR25
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Nanomanipulation of Single RNA Molecules by Optical Tweezers
Authors: William Stephenson, Gorby Wan, Scott A. Tenenbaum, Pan T. X. Li.
Institutions: University at Albany, State University of New York, University at Albany, State University of New York, University at Albany, State University of New York, University at Albany, State University of New York, University at Albany, State University of New York.
A large portion of the human genome is transcribed but not translated. In this post genomic era, regulatory functions of RNA have been shown to be increasingly important. As RNA function often depends on its ability to adopt alternative structures, it is difficult to predict RNA three-dimensional structures directly from sequence. Single-molecule approaches show potentials to solve the problem of RNA structural polymorphism by monitoring molecular structures one molecule at a time. This work presents a method to precisely manipulate the folding and structure of single RNA molecules using optical tweezers. First, methods to synthesize molecules suitable for single-molecule mechanical work are described. Next, various calibration procedures to ensure the proper operations of the optical tweezers are discussed. Next, various experiments are explained. To demonstrate the utility of the technique, results of mechanically unfolding RNA hairpins and a single RNA kissing complex are used as evidence. In these examples, the nanomanipulation technique was used to study folding of each structural domain, including secondary and tertiary, independently. Lastly, the limitations and future applications of the method are discussed.
Bioengineering, Issue 90, RNA folding, single-molecule, optical tweezers, nanomanipulation, RNA secondary structure, RNA tertiary structure
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Tissue-simulating Phantoms for Assessing Potential Near-infrared Fluorescence Imaging Applications in Breast Cancer Surgery
Authors: Rick Pleijhuis, Arwin Timmermans, Johannes De Jong, Esther De Boer, Vasilis Ntziachristos, Gooitzen Van Dam.
Institutions: University Medical Center Groningen, Technical University of Munich.
Inaccuracies in intraoperative tumor localization and evaluation of surgical margin status result in suboptimal outcome of breast-conserving surgery (BCS). Optical imaging, in particular near-infrared fluorescence (NIRF) imaging, might reduce the frequency of positive surgical margins following BCS by providing the surgeon with a tool for pre- and intraoperative tumor localization in real-time. In the current study, the potential of NIRF-guided BCS is evaluated using tissue-simulating breast phantoms for reasons of standardization and training purposes. Breast phantoms with optical characteristics comparable to those of normal breast tissue were used to simulate breast conserving surgery. Tumor-simulating inclusions containing the fluorescent dye indocyanine green (ICG) were incorporated in the phantoms at predefined locations and imaged for pre- and intraoperative tumor localization, real-time NIRF-guided tumor resection, NIRF-guided evaluation on the extent of surgery, and postoperative assessment of surgical margins. A customized NIRF camera was used as a clinical prototype for imaging purposes. Breast phantoms containing tumor-simulating inclusions offer a simple, inexpensive, and versatile tool to simulate and evaluate intraoperative tumor imaging. The gelatinous phantoms have elastic properties similar to human tissue and can be cut using conventional surgical instruments. Moreover, the phantoms contain hemoglobin and intralipid for mimicking absorption and scattering of photons, respectively, creating uniform optical properties similar to human breast tissue. The main drawback of NIRF imaging is the limited penetration depth of photons when propagating through tissue, which hinders (noninvasive) imaging of deep-seated tumors with epi-illumination strategies.
Medicine, Issue 91, Breast cancer, tissue-simulating phantoms, NIRF imaging, tumor-simulating inclusions, fluorescence, intraoperative imaging
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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.
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Protocols for Implementing an Escherichia coli Based TX-TL Cell-Free Expression System for Synthetic Biology
Authors: Zachary Z. Sun, Clarmyra A. Hayes, Jonghyeon Shin, Filippo Caschera, Richard M. Murray, Vincent Noireaux.
Institutions: California Institute of Technology, California Institute of Technology, Massachusetts Institute of Technology, University of Minnesota.
Ideal cell-free expression systems can theoretically emulate an in vivo cellular environment in a controlled in vitro platform.1 This is useful for expressing proteins and genetic circuits in a controlled manner as well as for providing a prototyping environment for synthetic biology.2,3 To achieve the latter goal, cell-free expression systems that preserve endogenous Escherichia coli transcription-translation mechanisms are able to more accurately reflect in vivo cellular dynamics than those based on T7 RNA polymerase transcription. We describe the preparation and execution of an efficient endogenous E. coli based transcription-translation (TX-TL) cell-free expression system that can produce equivalent amounts of protein as T7-based systems at a 98% cost reduction to similar commercial systems.4,5 The preparation of buffers and crude cell extract are described, as well as the execution of a three tube TX-TL reaction. The entire protocol takes five days to prepare and yields enough material for up to 3000 single reactions in one preparation. Once prepared, each reaction takes under 8 hr from setup to data collection and analysis. Mechanisms of regulation and transcription exogenous to E. coli, such as lac/tet repressors and T7 RNA polymerase, can be supplemented.6 Endogenous properties, such as mRNA and DNA degradation rates, can also be adjusted.7 The TX-TL cell-free expression system has been demonstrated for large-scale circuit assembly, exploring biological phenomena, and expression of proteins under both T7- and endogenous promoters.6,8 Accompanying mathematical models are available.9,10 The resulting system has unique applications in synthetic biology as a prototyping environment, or "TX-TL biomolecular breadboard."
Cellular Biology, Issue 79, Bioengineering, Synthetic Biology, Chemistry Techniques, Synthetic, Molecular Biology, control theory, TX-TL, cell-free expression, in vitro, transcription-translation, cell-free protein synthesis, synthetic biology, systems biology, Escherichia coli cell extract, biological circuits, biomolecular breadboard
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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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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
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Thermodynamics of Membrane Protein Folding Measured by Fluorescence Spectroscopy
Authors: Diana E. Schlamadinger, Judy E. Kim.
Institutions: University of California San Diego - UCSD.
Membrane protein folding is an emerging topic with both fundamental and health-related significance. The abundance of membrane proteins in cells underlies the need for comprehensive study of the folding of this ubiquitous family of proteins. Additionally, advances in our ability to characterize diseases associated with misfolded proteins have motivated significant experimental and theoretical efforts in the field of protein folding. Rapid progress in this important field is unfortunately hindered by the inherent challenges associated with membrane proteins and the complexity of the folding mechanism. Here, we outline an experimental procedure for measuring the thermodynamic property of the Gibbs free energy of unfolding in the absence of denaturant, ΔH2O, for a representative integral membrane protein from E. coli. This protocol focuses on the application of fluorescence spectroscopy to determine equilibrium populations of folded and unfolded states as a function of denaturant concentration. Experimental considerations for the preparation of synthetic lipid vesicles as well as key steps in the data analysis procedure are highlighted. This technique is versatile and may be pursued with different types of denaturant, including temperature and pH, as well as in various folding environments of lipids and micelles. The current protocol is one that can be generalized to any membrane or soluble protein that meets the set of criteria discussed below.
Bioengineering, Issue 50, tryptophan, peptides, Gibbs free energy, protein stability, vesicles
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Isothermal Titration Calorimetry for Measuring Macromolecule-Ligand Affinity
Authors: Michael R. Duff, Jr., Jordan Grubbs, Elizabeth E. Howell.
Institutions: University of Tennessee .
Isothermal titration calorimetry (ITC) is a useful tool for understanding the complete thermodynamic picture of a binding reaction. In biological sciences, macromolecular interactions are essential in understanding the machinery of the cell. Experimental conditions, such as buffer and temperature, can be tailored to the particular binding system being studied. However, careful planning is needed since certain ligand and macromolecule concentration ranges are necessary to obtain useful data. Concentrations of the macromolecule and ligand need to be accurately determined for reliable results. Care also needs to be taken when preparing the samples as impurities can significantly affect the experiment. When ITC experiments, along with controls, are performed properly, useful binding information, such as the stoichiometry, affinity and enthalpy, are obtained. By running additional experiments under different buffer or temperature conditions, more detailed information can be obtained about the system. A protocol for the basic setup of an ITC experiment is given.
Molecular Biology, Issue 55, Isothermal titration calorimetry, thermodynamics, binding affinity, enthalpy, entropy, free energy
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
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Determining the Contribution of the Energy Systems During Exercise
Authors: Guilherme G. Artioli, Rômulo C. Bertuzzi, Hamilton Roschel, Sandro H. Mendes, Antonio H. Lancha Jr., Emerson Franchini.
Institutions: University of Sao Paulo, University of Sao Paulo, University of Sao Paulo, University of Sao Paulo.
One of the most important aspects of the metabolic demand is the relative contribution of the energy systems to the total energy required for a given physical activity. Although some sports are relatively easy to be reproduced in a laboratory (e.g., running and cycling), a number of sports are much more difficult to be reproduced and studied in controlled situations. This method presents how to assess the differential contribution of the energy systems in sports that are difficult to mimic in controlled laboratory conditions. The concepts shown here can be adapted to virtually any sport. The following physiologic variables will be needed: rest oxygen consumption, exercise oxygen consumption, post-exercise oxygen consumption, rest plasma lactate concentration and post-exercise plasma peak lactate. To calculate the contribution of the aerobic metabolism, you will need the oxygen consumption at rest and during the exercise. By using the trapezoidal method, calculate the area under the curve of oxygen consumption during exercise, subtracting the area corresponding to the rest oxygen consumption. To calculate the contribution of the alactic anaerobic metabolism, the post-exercise oxygen consumption curve has to be adjusted to a mono or a bi-exponential model (chosen by the one that best fits). Then, use the terms of the fitted equation to calculate anaerobic alactic metabolism, as follows: ATP-CP metabolism = A1 (mL . s-1) x t1 (s). Finally, to calculate the contribution of the lactic anaerobic system, multiply peak plasma lactate by 3 and by the athlete’s body mass (the result in mL is then converted to L and into kJ). The method can be used for both continuous and intermittent exercise. This is a very interesting approach as it can be adapted to exercises and sports that are difficult to be mimicked in controlled environments. Also, this is the only available method capable of distinguishing the contribution of three different energy systems. Thus, the method allows the study of sports with great similarity to real situations, providing desirable ecological validity to the study.
Physiology, Issue 61, aerobic metabolism, anaerobic alactic metabolism, anaerobic lactic metabolism, exercise, athletes, mathematical model
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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
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Polymerase Chain Reaction: Basic Protocol Plus Troubleshooting and Optimization Strategies
Authors: Todd C. Lorenz.
Institutions: University of California, Los Angeles .
In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of microbiology was transformed with the advent of Anton van Leeuwenhoek's microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR) is one of those innovations that changed the course of molecular science with its impact spanning countless subdisciplines in biology. The theoretical process was outlined by Keppe and coworkers in 1971; however, it was another 14 years until the complete PCR procedure was described and experimentally applied by Kary Mullis while at Cetus Corporation in 1985. Automation and refinement of this technique progressed with the introduction of a thermal stable DNA polymerase from the bacterium Thermus aquaticus, consequently the name Taq DNA polymerase. PCR is a powerful amplification technique that can generate an ample supply of a specific segment of DNA (i.e., an amplicon) from only a small amount of starting material (i.e., DNA template or target sequence). While straightforward and generally trouble-free, there are pitfalls that complicate the reaction producing spurious results. When PCR fails it can lead to many non-specific DNA products of varying sizes that appear as a ladder or smear of bands on agarose gels. Sometimes no products form at all. Another potential problem occurs when mutations are unintentionally introduced in the amplicons, resulting in a heterogeneous population of PCR products. PCR failures can become frustrating unless patience and careful troubleshooting are employed to sort out and solve the problem(s). This protocol outlines the basic principles of PCR, provides a methodology that will result in amplification of most target sequences, and presents strategies for optimizing a reaction. By following this PCR guide, students should be able to: ● Set up reactions and thermal cycling conditions for a conventional PCR experiment ● Understand the function of various reaction components and their overall effect on a PCR experiment ● Design and optimize a PCR experiment for any DNA template ● Troubleshoot failed PCR experiments
Basic Protocols, Issue 63, PCR, optimization, primer design, melting temperature, Tm, troubleshooting, additives, enhancers, template DNA quantification, thermal cycler, molecular biology, genetics
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A Toolkit to Enable Hydrocarbon Conversion in Aqueous Environments
Authors: Eva K. Brinkman, Kira Schipper, Nadine Bongaerts, Mathias J. Voges, Alessandro Abate, S. Aljoscha Wahl.
Institutions: Delft University of Technology, Delft University of Technology.
This work puts forward a toolkit that enables the conversion of alkanes by Escherichia coli and presents a proof of principle of its applicability. The toolkit consists of multiple standard interchangeable parts (BioBricks)9 addressing the conversion of alkanes, regulation of gene expression and survival in toxic hydrocarbon-rich environments. A three-step pathway for alkane degradation was implemented in E. coli to enable the conversion of medium- and long-chain alkanes to their respective alkanols, alkanals and ultimately alkanoic-acids. The latter were metabolized via the native β-oxidation pathway. To facilitate the oxidation of medium-chain alkanes (C5-C13) and cycloalkanes (C5-C8), four genes (alkB2, rubA3, rubA4and rubB) of the alkane hydroxylase system from Gordonia sp. TF68,21 were transformed into E. coli. For the conversion of long-chain alkanes (C15-C36), theladA gene from Geobacillus thermodenitrificans was implemented. For the required further steps of the degradation process, ADH and ALDH (originating from G. thermodenitrificans) were introduced10,11. The activity was measured by resting cell assays. For each oxidative step, enzyme activity was observed. To optimize the process efficiency, the expression was only induced under low glucose conditions: a substrate-regulated promoter, pCaiF, was used. pCaiF is present in E. coli K12 and regulates the expression of the genes involved in the degradation of non-glucose carbon sources. The last part of the toolkit - targeting survival - was implemented using solvent tolerance genes, PhPFDα and β, both from Pyrococcus horikoshii OT3. Organic solvents can induce cell stress and decreased survivability by negatively affecting protein folding. As chaperones, PhPFDα and β improve the protein folding process e.g. under the presence of alkanes. The expression of these genes led to an improved hydrocarbon tolerance shown by an increased growth rate (up to 50%) in the presences of 10% n-hexane in the culture medium were observed. Summarizing, the results indicate that the toolkit enables E. coli to convert and tolerate hydrocarbons in aqueous environments. As such, it represents an initial step towards a sustainable solution for oil-remediation using a synthetic biology approach.
Bioengineering, Issue 68, Microbiology, Biochemistry, Chemistry, Chemical Engineering, Oil remediation, alkane metabolism, alkane hydroxylase system, resting cell assay, prefoldin, Escherichia coli, synthetic biology, homologous interaction mapping, mathematical model, BioBrick, iGEM
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Determination of the Gas-phase Acidities of Oligopeptides
Authors: Jianhua Ren, Ashish Sawhney, Yuan Tian, Bhupinder Padda, Patrick Batoon.
Institutions: University of the Pacific.
Amino acid residues located at different positions in folded proteins often exhibit different degrees of acidities. For example, a cysteine residue located at or near the N-terminus of a helix is often more acidic than that at or near the C-terminus 1-6. Although extensive experimental studies on the acid-base properties of peptides have been carried out in the condensed phase, in particular in aqueous solutions 6-8, the results are often complicated by solvent effects 7. In fact, most of the active sites in proteins are located near the interior region where solvent effects have been minimized 9,10. In order to understand intrinsic acid-base properties of peptides and proteins, it is important to perform the studies in a solvent-free environment. We present a method to measure the acidities of oligopeptides in the gas-phase. We use a cysteine-containing oligopeptide, Ala3CysNH2 (A3CH), as the model compound. The measurements are based on the well-established extended Cooks kinetic method (Figure 1) 11-16. The experiments are carried out using a triple-quadrupole mass spectrometer interfaced with an electrospray ionization (ESI) ion source (Figure 2). For each peptide sample, several reference acids are selected. The reference acids are structurally similar organic compounds with known gas-phase acidities. A solution of the mixture of the peptide and a reference acid is introduced into the mass spectrometer, and a gas-phase proton-bound anionic cluster of peptide-reference acid is formed. The proton-bound cluster is mass isolated and subsequently fragmented via collision-induced dissociation (CID) experiments. The resulting fragment ion abundances are analyzed using a relationship between the acidities and the cluster ion dissociation kinetics. The gas-phase acidity of the peptide is then obtained by linear regression of the thermo-kinetic plots 17,18. The method can be applied to a variety of molecular systems, including organic compounds, amino acids and their derivatives, oligonucleotides, and oligopeptides. By comparing the gas-phase acidities measured experimentally with those values calculated for different conformers, conformational effects on the acidities can be evaluated.
Chemistry, Issue 76, Biochemistry, Molecular Biology, Oligopeptide, gas-phase acidity, kinetic method, collision-induced dissociation, triple-quadrupole mass spectrometry, oligopeptides, peptides, mass spectrometry, MS
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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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Purification of Transcripts and Metabolites from Drosophila Heads
Authors: Kurt Jensen, Jonatan Sanchez-Garcia, Caroline Williams, Swati Khare, Krishanu Mathur, Rita M. Graze, Daniel A. Hahn, Lauren M. McIntyre, Diego E. Rincon-Limas, Pedro Fernandez-Funez.
Institutions: University of Florida , University of Florida , University of Florida , University of Florida .
For the last decade, we have tried to understand the molecular and cellular mechanisms of neuronal degeneration using Drosophila as a model organism. Although fruit flies provide obvious experimental advantages, research on neurodegenerative diseases has mostly relied on traditional techniques, including genetic interaction, histology, immunofluorescence, and protein biochemistry. These techniques are effective for mechanistic, hypothesis-driven studies, which lead to a detailed understanding of the role of single genes in well-defined biological problems. However, neurodegenerative diseases are highly complex and affect multiple cellular organelles and processes over time. The advent of new technologies and the omics age provides a unique opportunity to understand the global cellular perturbations underlying complex diseases. Flexible model organisms such as Drosophila are ideal for adapting these new technologies because of their strong annotation and high tractability. One challenge with these small animals, though, is the purification of enough informational molecules (DNA, mRNA, protein, metabolites) from highly relevant tissues such as fly brains. Other challenges consist of collecting large numbers of flies for experimental replicates (critical for statistical robustness) and developing consistent procedures for the purification of high-quality biological material. Here, we describe the procedures for collecting thousands of fly heads and the extraction of transcripts and metabolites to understand how global changes in gene expression and metabolism contribute to neurodegenerative diseases. These procedures are easily scalable and can be applied to the study of proteomic and epigenomic contributions to disease.
Genetics, Issue 73, Biochemistry, Molecular Biology, Neurobiology, Neuroscience, Bioengineering, Cellular Biology, Anatomy, Neurodegenerative Diseases, Biological Assay, Drosophila, fruit fly, head separation, purification, mRNA, RNA, cDNA, DNA, transcripts, metabolites, replicates, SCA3, neurodegeneration, NMR, gene expression, animal model
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In Situ Neutron Powder Diffraction Using Custom-made Lithium-ion Batteries
Authors: William R. Brant, Siegbert Schmid, Guodong Du, Helen E. A. Brand, Wei Kong Pang, Vanessa K. Peterson, Zaiping Guo, Neeraj Sharma.
Institutions: University of Sydney, University of Wollongong, Australian Synchrotron, Australian Nuclear Science and Technology Organisation, University of Wollongong, University of New South Wales.
Li-ion batteries are widely used in portable electronic devices and are considered as promising candidates for higher-energy applications such as electric vehicles.1,2 However, many challenges, such as energy density and battery lifetimes, need to be overcome before this particular battery technology can be widely implemented in such applications.3 This research is challenging, and we outline a method to address these challenges using in situ NPD to probe the crystal structure of electrodes undergoing electrochemical cycling (charge/discharge) in a battery. NPD data help determine the underlying structural mechanism responsible for a range of electrode properties, and this information can direct the development of better electrodes and batteries. We briefly review six types of battery designs custom-made for NPD experiments and detail the method to construct the ‘roll-over’ cell that we have successfully used on the high-intensity NPD instrument, WOMBAT, at the Australian Nuclear Science and Technology Organisation (ANSTO). The design considerations and materials used for cell construction are discussed in conjunction with aspects of the actual in situ NPD experiment and initial directions are presented on how to analyze such complex in situ data.
Physics, Issue 93, In operando, structure-property relationships, electrochemical cycling, electrochemical cells, crystallography, battery performance
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