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Processing technology investigation of loquat (Eriobotrya japonica) leaf by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry combined with chemometrics.
PUBLISHED: 01-01-2013
Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) and multivariate statistical analysis were used to investigate the processing technology of Loquat (Eriobotrya japonica) leaf (pipaye, PPY). The differences in samples processed using different methods were revealed by unsupervised principal component analysis (PCA). In the scores plot of PCA, honey-processed PPY (PPPY), crude PPY (CPPY), and heated PPY (HPPY) were clearly discriminated. Furthermore, samples processed at different temperatures could also be distinguished; indeed, our PCA results demonstrated the importance of temperature during processing. Two unique marker ions were found to discriminate between PPPY and CPPY by orthogonal partial least squares discriminant analysis (OPLS-DA), which could be used as potential chemical markers. The method was further confirmed by a verification test with commercial PPY. The orthogonal array experiment revealed an optimized processing condition with 50% honey at 140°C for 20 min after 4 h of moistening time, a process that provides significant information for standardized production.
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.
22 Related JoVE Articles!
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Quantification of Orofacial Phenotypes in Xenopus
Authors: Allyson E. Kennedy, Amanda J. Dickinson.
Institutions: Virginia Commonwealth University.
Xenopus has become an important tool for dissecting the mechanisms governing craniofacial development and defects. A method to quantify orofacial development will allow for more rigorous analysis of orofacial phenotypes upon abrogation with substances that can genetically or molecularly manipulate gene expression or protein function. Using two dimensional images of the embryonic heads, traditional size dimensions-such as orofacial width, height and area- are measured. In addition, a roundness measure of the embryonic mouth opening is used to describe the shape of the mouth. Geometric morphometrics of these two dimensional images is also performed to provide a more sophisticated view of changes in the shape of the orofacial region. Landmarks are assigned to specific points in the orofacial region and coordinates are created. A principle component analysis is used to reduce landmark coordinates to principle components that then discriminate the treatment groups. These results are displayed as a scatter plot in which individuals with similar orofacial shapes cluster together. It is also useful to perform a discriminant function analysis, which statistically compares the positions of the landmarks between two treatment groups. This analysis is displayed on a transformation grid where changes in landmark position are viewed as vectors. A grid is superimposed on these vectors so that a warping pattern is displayed to show where significant landmark positions have changed. Shape changes in the discriminant function analysis are based on a statistical measure, and therefore can be evaluated by a p-value. This analysis is simple and accessible, requiring only a stereoscope and freeware software, and thus will be a valuable research and teaching resource.
Developmental Biology, Issue 93, Orofacial quantification, geometric morphometrics, Xenopus, orofacial development, orofacial defects, shape changes, facial dimensions
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Analyzing Protein Dynamics Using Hydrogen Exchange Mass Spectrometry
Authors: Nikolai Hentze, Matthias P. Mayer.
Institutions: University of Heidelberg.
All cellular processes depend on the functionality of proteins. Although the functionality of a given protein is the direct consequence of its unique amino acid sequence, it is only realized by the folding of the polypeptide chain into a single defined three-dimensional arrangement or more commonly into an ensemble of interconverting conformations. Investigating the connection between protein conformation and its function is therefore essential for a complete understanding of how proteins are able to fulfill their great variety of tasks. One possibility to study conformational changes a protein undergoes while progressing through its functional cycle is hydrogen-1H/2H-exchange in combination with high-resolution mass spectrometry (HX-MS). HX-MS is a versatile and robust method that adds a new dimension to structural information obtained by e.g. crystallography. It is used to study protein folding and unfolding, binding of small molecule ligands, protein-protein interactions, conformational changes linked to enzyme catalysis, and allostery. In addition, HX-MS is often used when the amount of protein is very limited or crystallization of the protein is not feasible. Here we provide a general protocol for studying protein dynamics with HX-MS and describe as an example how to reveal the interaction interface of two proteins in a complex.   
Chemistry, Issue 81, Molecular Chaperones, mass spectrometers, Amino Acids, Peptides, Proteins, Enzymes, Coenzymes, Protein dynamics, conformational changes, allostery, protein folding, secondary structure, mass spectrometry
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Conducting Miller-Urey Experiments
Authors: Eric T. Parker, James H. Cleaves, Aaron S. Burton, Daniel P. Glavin, Jason P. Dworkin, Manshui Zhou, Jeffrey L. Bada, Facundo M. Fernández.
Institutions: Georgia Institute of Technology, Tokyo Institute of Technology, Institute for Advanced Study, NASA Johnson Space Center, NASA Goddard Space Flight Center, University of California at San Diego.
In 1953, Stanley Miller reported the production of biomolecules from simple gaseous starting materials, using an apparatus constructed to simulate the primordial Earth's atmosphere-ocean system. Miller introduced 200 ml of water, 100 mmHg of H2, 200 mmHg of CH4, and 200 mmHg of NH3 into the apparatus, then subjected this mixture, under reflux, to an electric discharge for a week, while the water was simultaneously heated. The purpose of this manuscript is to provide the reader with a general experimental protocol that can be used to conduct a Miller-Urey type spark discharge experiment, using a simplified 3 L reaction flask. Since the experiment involves exposing inflammable gases to a high voltage electric discharge, it is worth highlighting important steps that reduce the risk of explosion. The general procedures described in this work can be extrapolated to design and conduct a wide variety of electric discharge experiments simulating primitive planetary environments.
Chemistry, Issue 83, Geosciences (General), Exobiology, Miller-Urey, Prebiotic chemistry, amino acids, spark discharge
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A Proboscis Extension Response Protocol for Investigating Behavioral Plasticity in Insects: Application to Basic, Biomedical, and Agricultural Research
Authors: Brian H. Smith, Christina M. Burden.
Institutions: Arizona State University.
Insects modify their responses to stimuli through experience of associating those stimuli with events important for survival (e.g., food, mates, threats). There are several behavioral mechanisms through which an insect learns salient associations and relates them to these events. It is important to understand this behavioral plasticity for programs aimed toward assisting insects that are beneficial for agriculture. This understanding can also be used for discovering solutions to biomedical and agricultural problems created by insects that act as disease vectors and pests. The Proboscis Extension Response (PER) conditioning protocol was developed for honey bees (Apis mellifera) over 50 years ago to study how they perceive and learn about floral odors, which signal the nectar and pollen resources a colony needs for survival. The PER procedure provides a robust and easy-to-employ framework for studying several different ecologically relevant mechanisms of behavioral plasticity. It is easily adaptable for use with several other insect species and other behavioral reflexes. These protocols can be readily employed in conjunction with various means for monitoring neural activity in the CNS via electrophysiology or bioimaging, or for manipulating targeted neuromodulatory pathways. It is a robust assay for rapidly detecting sub-lethal effects on behavior caused by environmental stressors, toxins or pesticides. We show how the PER protocol is straightforward to implement using two procedures. One is suitable as a laboratory exercise for students or for quick assays of the effect of an experimental treatment. The other provides more thorough control of variables, which is important for studies of behavioral conditioning. We show how several measures for the behavioral response ranging from binary yes/no to more continuous variable like latency and duration of proboscis extension can be used to test hypotheses. And, we discuss some pitfalls that researchers commonly encounter when they use the procedure for the first time.
Neuroscience, Issue 91, PER, conditioning, honey bee, olfaction, olfactory processing, learning, memory, toxin assay
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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 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
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Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
Authors: Charmion Cruickshank-Quinn, Kevin D. Quinn, Roger Powell, Yanhui Yang, Michael Armstrong, Spencer Mahaffey, Richard Reisdorph, Nichole Reisdorph.
Institutions: National Jewish Health, University of Colorado Denver.
Metabolomics is an emerging field which enables profiling of samples from living organisms in order to obtain insight into biological processes. A vital aspect of metabolomics is sample preparation whereby inconsistent techniques generate unreliable results. This technique encompasses protein precipitation, liquid-liquid extraction, and solid-phase extraction as a means of fractionating metabolites into four distinct classes. Improved enrichment of low abundance molecules with a resulting increase in sensitivity is obtained, and ultimately results in more confident identification of molecules. This technique has been applied to plasma, bronchoalveolar lavage fluid, and cerebrospinal fluid samples with volumes as low as 50 µl.  Samples can be used for multiple downstream applications; for example, the pellet resulting from protein precipitation can be stored for later analysis. The supernatant from that step undergoes liquid-liquid extraction using water and strong organic solvent to separate the hydrophilic and hydrophobic compounds. Once fractionated, the hydrophilic layer can be processed for later analysis or discarded if not needed. The hydrophobic fraction is further treated with a series of solvents during three solid-phase extraction steps to separate it into fatty acids, neutral lipids, and phospholipids. This allows the technician the flexibility to choose which class of compounds is preferred for analysis. It also aids in more reliable metabolite identification since some knowledge of chemical class exists.
Bioengineering, Issue 89, plasma, chemistry techniques, analytical, solid phase extraction, mass spectrometry, metabolomics, fluids and secretions, profiling, small molecules, lipids, liquid chromatography, liquid-liquid extraction, cerebrospinal fluid, bronchoalveolar lavage fluid
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Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees
Authors: Martin Fritz Brill, Maren Reuter, Wolfgang Rössler, Martin Fritz Strube-Bloss.
Institutions: University of Würzburg.
In both mammals and insects neuronal information is processed in different higher and lower order brain centers. These centers are coupled via convergent and divergent anatomical connections including feed forward and feedback wiring. Furthermore, information of the same origin is partially sent via parallel pathways to different and sometimes into the same brain areas. To understand the evolutionary benefits as well as the computational advantages of these wiring strategies and especially their temporal dependencies on each other, it is necessary to have simultaneous access to single neurons of different tracts or neuropiles in the same preparation at high temporal resolution. Here we concentrate on honeybees by demonstrating a unique extracellular long term access to record multi unit activity at two subsequent neuropiles1, the antennal lobe (AL), the first olfactory processing stage and the mushroom body (MB), a higher order integration center involved in learning and memory formation, or two parallel neuronal tracts2 connecting the AL with the MB. The latter was chosen as an example and will be described in full. In the supporting video the construction and permanent insertion of flexible multi channel wire electrodes is demonstrated. Pairwise differential amplification of the micro wire electrode channels drastically reduces the noise and verifies that the source of the signal is closely related to the position of the electrode tip. The mechanical flexibility of the used wire electrodes allows stable invasive long term recordings over many hours up to days, which is a clear advantage compared to conventional extra and intracellular in vivo recording techniques.
Neuroscience, Issue 89, honeybee brain, olfaction, extracellular long term recordings, double recordings, differential wire electrodes, single unit, multi-unit recordings
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Quantitative Detection of Trace Explosive Vapors by Programmed Temperature Desorption Gas Chromatography-Electron Capture Detector
Authors: Christopher R. Field, Adam Lubrano, Morgan Woytowitz, Braden C. Giordano, Susan L. Rose-Pehrsson.
Institutions: U.S. Naval Research Laboratory, NOVA Research, Inc., U.S. Naval Research Laboratory, U.S. Naval Research Laboratory.
The direct liquid deposition of solution standards onto sorbent-filled thermal desorption tubes is used for the quantitative analysis of trace explosive vapor samples. The direct liquid deposition method yields a higher fidelity between the analysis of vapor samples and the analysis of solution standards than using separate injection methods for vapors and solutions, i.e., samples collected on vapor collection tubes and standards prepared in solution vials. Additionally, the method can account for instrumentation losses, which makes it ideal for minimizing variability and quantitative trace chemical detection. Gas chromatography with an electron capture detector is an instrumentation configuration sensitive to nitro-energetics, such as TNT and RDX, due to their relatively high electron affinity. However, vapor quantitation of these compounds is difficult without viable vapor standards. Thus, we eliminate the requirement for vapor standards by combining the sensitivity of the instrumentation with a direct liquid deposition protocol to analyze trace explosive vapor samples.
Chemistry, Issue 89, Gas Chromatography (GC), Electron Capture Detector, Explosives, Quantitation, Thermal Desorption, TNT, RDX
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Dithranol as a Matrix for Matrix Assisted Laser Desorption/Ionization Imaging on a Fourier Transform Ion Cyclotron Resonance Mass Spectrometer
Authors: Cuong H. Le, Jun Han, Christoph H. Borchers.
Institutions: University of Victoria, University of Victoria.
Mass spectrometry imaging (MSI) determines the spatial localization and distribution patterns of compounds on the surface of a tissue section, mainly using MALDI (matrix assisted laser desorption/ionization)-based analytical techniques. New matrices for small-molecule MSI, which can improve the analysis of low-molecular weight (MW) compounds, are needed. These matrices should provide increased analyte signals while decreasing MALDI background signals. In addition, the use of ultrahigh-resolution instruments, such as Fourier transform ion cyclotron resonance (FTICR) mass spectrometers, has the ability to resolve analyte signals from matrix signals, and this can partially overcome many problems associated with the background originating from the MALDI matrix. The reduction in the intensities of the metastable matrix clusters by FTICR MS can also help to overcome some of the interferences associated with matrix peaks on other instruments. High-resolution instruments such as the FTICR mass spectrometers are advantageous as they can produce distribution patterns of many compounds simultaneously while still providing confidence in chemical identifications. Dithranol (DT; 1,8-dihydroxy-9,10-dihydroanthracen-9-one) has previously been reported as a MALDI matrix for tissue imaging. In this work, a protocol for the use of DT for MALDI imaging of endogenous lipids from the surfaces of mammalian tissue sections, by positive-ion MALDI-MS, on an ultrahigh-resolution hybrid quadrupole FTICR instrument has been provided.
Basic Protocol, Issue 81, eye, molecular imaging, chemistry technique, analytical, mass spectrometry, matrix assisted laser desorption/ionization (MALDI), tandem mass spectrometry, lipid, tissue imaging, bovine lens, dithranol, matrix, FTICR (Fourier Transform Ion Cyclotron Resonance)
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Matrix-assisted Laser Desorption/Ionization Time of Flight (MALDI-TOF) Mass Spectrometric Analysis of Intact Proteins Larger than 100 kDa
Authors: Luca Signor, Elisabetta Boeri Erba.
Institutions: Université J. Fourier.
Effectively determining masses of proteins is critical to many biological studies (e.g. for structural biology investigations). Accurate mass determination allows one to evaluate the correctness of protein primary sequences, the presence of mutations and/or post-translational modifications, the possible protein degradation, the sample homogeneity, and the degree of isotope incorporation in case of labelling (e.g. 13C labelling). Electrospray ionization (ESI) mass spectrometry (MS) is widely used for mass determination of denatured proteins, but its efficiency is affected by the composition of the sample buffer. In particular, the presence of salts, detergents, and contaminants severely undermines the effectiveness of protein analysis by ESI-MS. Matrix-assisted laser desorption/ionization (MALDI) MS is an attractive alternative, due to its salt tolerance and the simplicity of data acquisition and interpretation. Moreover, the mass determination of large heterogeneous proteins (bigger than 100 kDa) is easier by MALDI-MS due to the absence of overlapping high charge state distributions which are present in ESI spectra. Here we present an accessible approach for analyzing proteins larger than 100 kDa by MALDI-time of flight (TOF). We illustrate the advantages of using a mixture of two matrices (i.e. 2,5-dihydroxybenzoic acid and α-cyano-4-hydroxycinnamic acid) and the utility of the thin layer method as approach for sample deposition. We also discuss the critical role of the matrix and solvent purity, of the standards used for calibration, of the laser energy, and of the acquisition time. Overall, we provide information necessary to a novice for analyzing intact proteins larger than 100 kDa by MALDI-MS.
Chemistry, Issue 79, Chemistry Techniques, Analytical, Mass Spectrometry, Analytic Sample Preparation Methods, biochemistry, Analysis of intact proteins, mass spectrometry, matrix-assisted laser desorption ionization, time of flight, sample preparation
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Stable Isotopic Profiling of Intermediary Metabolic Flux in Developing and Adult Stage Caenorhabditis elegans
Authors: Marni J. Falk, Meera Rao, Julian Ostrovsky, Evgueni Daikhin, Ilana Nissim, Marc Yudkoff.
Institutions: The Children's Hospital of Philadelphia, University of Pennsylvania.
Stable isotopic profiling has long permitted sensitive investigations of the metabolic consequences of genetic mutations and/or pharmacologic therapies in cellular and mammalian models. Here, we describe detailed methods to perform stable isotopic profiling of intermediary metabolism and metabolic flux in the nematode, Caenorhabditis elegans. Methods are described for profiling whole worm free amino acids, labeled carbon dioxide, labeled organic acids, and labeled amino acids in animals exposed to stable isotopes either from early development on nematode growth media agar plates or beginning as young adults while exposed to various pharmacologic treatments in liquid culture. Free amino acids are quantified by high performance liquid chromatography (HPLC) in whole worm aliquots extracted in 4% perchloric acid. Universally labeled 13C-glucose or 1,6-13C2-glucose is utilized as the stable isotopic precursor whose labeled carbon is traced by mass spectrometry in carbon dioxide (both atmospheric and dissolved) as well as in metabolites indicative of flux through glycolysis, pyruvate metabolism, and the tricarboxylic acid cycle. Representative results are included to demonstrate effects of isotope exposure time, various bacterial clearing protocols, and alternative worm disruption methods in wild-type nematodes, as well as the relative extent of isotopic incorporation in mitochondrial complex III mutant worms (isp-1(qm150)) relative to wild-type worms. Application of stable isotopic profiling in living nematodes provides a novel capacity to investigate at the whole animal level real-time metabolic alterations that are caused by individual genetic disorders and/or pharmacologic therapies.
Developmental Biology, Issue 48, Stable isotope, amino acid quantitation, organic acid quantitation, nematodes, metabolism
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Concentration of Metabolites from Low-density Planktonic Communities for Environmental Metabolomics using Nuclear Magnetic Resonance Spectroscopy
Authors: R. Craig Everroad, Seiji Yoshida, Yuuri Tsuboi, Yasuhiro Date, Jun Kikuchi, Shigeharu Moriya.
Institutions: RIKEN Advanced Science Institute, Yokohama City University, RIKEN Plant Science Center, Nagoya University.
Environmental metabolomics is an emerging field that is promoting new understanding in how organisms respond to and interact with the environment and each other at the biochemical level1. Nuclear magnetic resonance (NMR) spectroscopy is one of several technologies, including gas chromatography–mass spectrometry (GC-MS), with considerable promise for such studies. Advantages of NMR are that it is suitable for untargeted analyses, provides structural information and spectra can be queried in quantitative and statistical manners against recently available databases of individual metabolite spectra2,3. In addition, NMR spectral data can be combined with data from other omics levels (e.g. transcriptomics, genomics) to provide a more comprehensive understanding of the physiological responses of taxa to each other and the environment4,5,6. However, NMR is less sensitive than other metabolomic techniques, making it difficult to apply to natural microbial systems where sample populations can be low-density and metabolite concentrations low compared to metabolites from well-defined and readily extractable sources such as whole tissues, biofluids or cell-cultures. Consequently, the few direct environmental metabolomic studies of microbes performed to date have been limited to culture-based or easily defined high-density ecosystems such as host-symbiont systems, constructed co-cultures or manipulations of the gut environment where stable isotope labeling can be additionally used to enhance NMR signals7,8,9,10,11,12. Methods that facilitate the concentration and collection of environmental metabolites at concentrations suitable for NMR are lacking. Since recent attention has been given to the environmental metabolomics of organisms within the aquatic environment, where much of the energy and material flow is mediated by the planktonic community13,14, we have developed a method for the concentration and extraction of whole-community metabolites from planktonic microbial systems by filtration. Commercially available hydrophilic poly-1,1-difluoroethene (PVDF) filters are specially treated to completely remove extractables, which can otherwise appear as contaminants in subsequent analyses. These treated filters are then used to filter environmental or experimental samples of interest. Filters containing the wet sample material are lyophilized and aqueous-soluble metabolites are extracted directly for conventional NMR spectroscopy using a standardized potassium phosphate extraction buffer2. Data derived from these methods can be analyzed statistically to identify meaningful patterns, or integrated with other omics levels for comprehensive understanding of community and ecosystem function.
Molecular Biology, Issue 62, environmental metabolomics, metabolic profiling, microbial ecology, plankton, NMR spectroscopy, PCA
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Micropunching Lithography for Generating Micro- and Submicron-patterns on Polymer Substrates
Authors: Anirban Chakraborty, Xinchuan Liu, Cheng Luo.
Institutions: University of Texas at Arlington .
Conducting polymers have attracted great attention since the discovery of high conductivity in doped polyacetylene in 19771. They offer the advantages of low weight, easy tailoring of properties and a wide spectrum of applications2,3. Due to sensitivity of conducting polymers to environmental conditions (e.g., air, oxygen, moisture, high temperature and chemical solutions), lithographic techniques present significant technical challenges when working with these materials4. For example, current photolithographic methods, such as ultra-violet (UV), are unsuitable for patterning the conducting polymers due to the involvement of wet and/or dry etching processes in these methods. In addition, current micro/nanosystems mainly have a planar form5,6. One layer of structures is built on the top surfaces of another layer of fabricated features. Multiple layers of these structures are stacked together to form numerous devices on a common substrate. The sidewall surfaces of the microstructures have not been used in constructing devices. On the other hand, sidewall patterns could be used, for example, to build 3-D circuits, modify fluidic channels and direct horizontal growth of nanowires and nanotubes. A macropunching method has been applied in the manufacturing industry to create macropatterns in a sheet metal for over a hundred years. Motivated by this approach, we have developed a micropunching lithography method (MPL) to overcome the obstacles of patterning conducting polymers and generating sidewall patterns. Like the macropunching method, the MPL also includes two operations (Fig. 1): (i) cutting; and (ii) drawing. The "cutting" operation was applied to pattern three conducting polymers4, polypyrrole (PPy), Poly(3,4-ethylenedioxythiophen)-poly(4-styrenesulphonate) (PEDOT) and polyaniline (PANI). It was also employed to create Al microstructures7. The fabricated microstructures of conducting polymers have been used as humidity8, chemical8, and glucose sensors9. Combined microstructures of Al and conducting polymers have been employed to fabricate capacitors and various heterojunctions9,10,11. The "cutting" operation was also applied to generate submicron-patterns, such as 100- and 500-nm-wide PPy lines as well as 100-nm-wide Au wires. The "drawing" operation was employed for two applications: (i) produce Au sidewall patterns on high density polyethylene (HDPE) channels which could be used for building 3D microsystems12,13,14, and (ii) fabricate polydimethylsiloxane (PDMS) micropillars on HDPE substrates to increase the contact angle of the channel15.
Mechanical Engineering, Issue 65, Physics, micropunching lithography, conducting polymers, nanowires, sidewall patterns, microlines
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Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy
Authors: Miriam Votteler, Daniel A. Carvajal Berrio, Marieke Pudlas, Heike Walles, Katja Schenke-Layland.
Institutions: Eberhard Karls University, Tübingen, Fraunhofer Institute of Interfacial Engineering and Biotechnology (IGB) Stuttgart, Germany, University of Stuttgart, Germany, Julius-Maximillians University, Würzburg, Germany.
Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, currently available routine methods require processing steps and alter sample integrity. Raman spectroscopy is a fast method that enables the measurement of biological samples without the need for further processing steps. This laser-based technology detects the inelastic scattering of monochromatic light.6 As every chemical vibration is assigned to a specific Raman band (wavenumber in cm-1), each biological sample features a typical spectral pattern due to their inherent biochemical composition.7-9 Within Raman spectra, the peak intensities correlate with the amount of the present molecular bonds.1 Similarities and differences of the spectral data sets can be detected by employing a multivariate analysis (e.g. principal component analysis (PCA)).10 Here, we perform Raman spectroscopy of living cells and native tissues. Cells are either seeded on glass bottom dishes or kept in suspension under normal cell culture conditions (37 °C, 5% CO2) before measurement. Native tissues are dissected and stored in phosphate buffered saline (PBS) at 4 °C prior measurements. Depending on our experimental set up, we then either focused on the cell nucleus or extracellular matrix (ECM) proteins such as elastin and collagen. For all studies, a minimum of 30 cells or 30 random points of interest within the ECM are measured. Data processing steps included background subtraction and normalization.
Bioengineering, Issue 63, Raman spectroscopy, label-free analysis, living cells, extracellular matrix, tissue engineering
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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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Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)
Authors: Nathaniel W. Snyder, Maya Khezam, Clementina A. Mesaros, Andrew Worth, Ian A. Blair.
Institutions: University of Pennsylvania .
Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.
Biochemistry, Issue 75, Chemistry, Molecular Biology, Cellular Biology, Physiology, Medicine, Pharmacology, Genetics, Genomics, Mass Spectrometry, MS, Metabolism, Metabolomics, untargeted, extraction, lipids, accurate mass, liquid chromatography, ultraperformance liquid chromatography, UPLC, high resolution mass spectrometry, HRMS, spectrometry
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Isolation and Chemical Characterization of Lipid A from Gram-negative Bacteria
Authors: Jeremy C. Henderson, John P. O'Brien, Jennifer S. Brodbelt, M. Stephen Trent.
Institutions: The University of Texas at Austin, The University of Texas at Austin, The University of Texas at Austin.
Lipopolysaccharide (LPS) is the major cell surface molecule of gram-negative bacteria, deposited on the outer leaflet of the outer membrane bilayer. LPS can be subdivided into three domains: the distal O-polysaccharide, a core oligosaccharide, and the lipid A domain consisting of a lipid A molecular species and 3-deoxy-D-manno-oct-2-ulosonic acid residues (Kdo). The lipid A domain is the only component essential for bacterial cell survival. Following its synthesis, lipid A is chemically modified in response to environmental stresses such as pH or temperature, to promote resistance to antibiotic compounds, and to evade recognition by mediators of the host innate immune response. The following protocol details the small- and large-scale isolation of lipid A from gram-negative bacteria. Isolated material is then chemically characterized by thin layer chromatography (TLC) or mass-spectrometry (MS). In addition to matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) MS, we also describe tandem MS protocols for analyzing lipid A molecular species using electrospray ionization (ESI) coupled to collision induced dissociation (CID) and newly employed ultraviolet photodissociation (UVPD) methods. Our MS protocols allow for unequivocal determination of chemical structure, paramount to characterization of lipid A molecules that contain unique or novel chemical modifications. We also describe the radioisotopic labeling, and subsequent isolation, of lipid A from bacterial cells for analysis by TLC. Relative to MS-based protocols, TLC provides a more economical and rapid characterization method, but cannot be used to unambiguously assign lipid A chemical structures without the use of standards of known chemical structure. Over the last two decades isolation and characterization of lipid A has led to numerous exciting discoveries that have improved our understanding of the physiology of gram-negative bacteria, mechanisms of antibiotic resistance, the human innate immune response, and have provided many new targets in the development of antibacterial compounds.
Chemistry, Issue 79, Membrane Lipids, Toll-Like Receptors, Endotoxins, Glycolipids, Lipopolysaccharides, Lipid A, Microbiology, Lipids, lipid A, Bligh-Dyer, thin layer chromatography (TLC), lipopolysaccharide, mass spectrometry, Collision Induced Dissociation (CID), Photodissociation (PD)
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Electrophysiological Measurements and Analysis of Nociception in Human Infants
Authors: L. Fabrizi, A. Worley, D. Patten, S. Holdridge, L. Cornelissen, J. Meek, S. Boyd, R. Slater.
Institutions: University College London, Great Ormond Street Hospital, University College Hospital, University of Oxford.
Pain is an unpleasant sensory and emotional experience. Since infants cannot verbally report their experiences, current methods of pain assessment are based on behavioural and physiological body reactions, such as crying, body movements or changes in facial expression. While these measures demonstrate that infants mount a response following noxious stimulation, they are limited: they are based on activation of subcortical somatic and autonomic motor pathways that may not be reliably linked to central sensory processing in the brain. Knowledge of how the central nervous system responds to noxious events could provide an insight to how nociceptive information and pain is processed in newborns. The heel lancing procedure used to extract blood from hospitalised infants offers a unique opportunity to study pain in infancy. In this video we describe how electroencephalography (EEG) and electromyography (EMG) time-locked to this procedure can be used to investigate nociceptive activity in the brain and spinal cord. This integrative approach to the measurement of infant pain has the potential to pave the way for an effective and sensitive clinical measurement tool.
Neuroscience, Issue 58, pain, infant, electrophysiology, human development
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
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Monitoring Plant Hormones During Stress Responses
Authors: Marie J. Engelberth, Jurgen Engelberth.
Institutions: University of Texas.
Plant hormones and related signaling compounds play an important role in the regulation of plant responses to various environmental stimuli and stresses. Among the most severe stresses are insect herbivory, pathogen infection, and drought stress. For each of these stresses a specific set of hormones and/or combinations thereof are known to fine-tune the responses, thereby ensuring the plant's survival. The major hormones involved in the regulation of these responses are jasmonic acid (JA), salicylic acid (SA), and abscisic acid (ABA). To better understand the role of individual hormones as well as their potential interaction during these responses it is necessary to monitor changes in their abundance in a temporal as well as in a spatial fashion. For the easy, sensitive, and reproducible quantification of these and other signaling compounds we developed a method based on vapor phase extraction and gas chromatography/mass spectrometry (GC/MS) analysis (1, 2, 3, 4). After extracting these compounds from the plant tissue by acidic aqueous 1-propanol mixed with dichloromethane the carboxylic acid-containing compounds are methylated, volatilized under heat, and collected on a polymeric absorbent. After elution into a sample vial the analytes are separated by gas chromatography and detected by chemical ionization mass spectrometry. The use of appropriate internal standards then allows for the simple quantification by relating the peak areas of analyte and internal standard.
Plant Biology, Issue 28, Jasmonic acid, salicylic acid, abscisic acid, plant hormones, GC/MS, vapor phase extraction
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.