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Unifying gene expression measures from multiple platforms using factor analysis.
PUBLISHED: 02-10-2011
In the Cancer Genome Atlas (TCGA) project, gene expression of the same set of samples is measured multiple times on different microarray platforms. There are two main advantages to combining these measurements. First, we have the opportunity to obtain a more precise and accurate estimate of expression levels than using the individual platforms alone. Second, the combined measure simplifies downstream analysis by eliminating the need to work with three sets of expression measures and to consolidate results from the three platforms.We propose to use factor analysis (FA) to obtain a unified gene expression measure (UE) from multiple platforms. The UE is a weighted average of the three platforms, and is shown to perform well in terms of accuracy and precision. In addition, the FA model produces parameter estimates that allow the assessment of the model fit.The R code is provided in File S2. Gene-level FA measurements for the TCGA data sets are available from
Hematopoietic stem cells (HSCs) are used clinically for transplantation treatment to rebuild a patient's hematopoietic system in many diseases such as leukemia and lymphoma. Elucidating the mechanisms controlling HSCs self-renewal and differentiation is important for application of HSCs for research and clinical uses. However, it is not possible to obtain large quantity of HSCs due to their inability to proliferate in vitro. To overcome this hurdle, we used a mouse bone marrow derived cell line, the EML (Erythroid, Myeloid, and Lymphocytic) cell line, as a model system for this study. RNA-sequencing (RNA-Seq) has been increasingly used to replace microarray for gene expression studies. We report here a detailed method of using RNA-Seq technology to investigate the potential key factors in regulation of EML cell self-renewal and differentiation. The protocol provided in this paper is divided into three parts. The first part explains how to culture EML cells and separate Lin-CD34+ and Lin-CD34- cells. The second part of the protocol offers detailed procedures for total RNA preparation and the subsequent library construction for high-throughput sequencing. The last part describes the method for RNA-Seq data analysis and explains how to use the data to identify differentially expressed transcription factors between Lin-CD34+ and Lin-CD34- cells. The most significantly differentially expressed transcription factors were identified to be the potential key regulators controlling EML cell self-renewal and differentiation. In the discussion section of this paper, we highlight the key steps for successful performance of this experiment. In summary, this paper offers a method of using RNA-Seq technology to identify potential regulators of self-renewal and differentiation in EML cells. The key factors identified are subjected to downstream functional analysis in vitro and in vivo.
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Recording and Analysis of Circadian Rhythms in Running-wheel Activity in Rodents
Authors: Michael Verwey, Barry Robinson, Shimon Amir.
Institutions: McGill University , Concordia University.
When rodents have free access to a running wheel in their home cage, voluntary use of this wheel will depend on the time of day1-5. Nocturnal rodents, including rats, hamsters, and mice, are active during the night and relatively inactive during the day. Many other behavioral and physiological measures also exhibit daily rhythms, but in rodents, running-wheel activity serves as a particularly reliable and convenient measure of the output of the master circadian clock, the suprachiasmatic nucleus (SCN) of the hypothalamus. In general, through a process called entrainment, the daily pattern of running-wheel activity will naturally align with the environmental light-dark cycle (LD cycle; e.g. 12 hr-light:12 hr-dark). However circadian rhythms are endogenously generated patterns in behavior that exhibit a ~24 hr period, and persist in constant darkness. Thus, in the absence of an LD cycle, the recording and analysis of running-wheel activity can be used to determine the subjective time-of-day. Because these rhythms are directed by the circadian clock the subjective time-of-day is referred to as the circadian time (CT). In contrast, when an LD cycle is present, the time-of-day that is determined by the environmental LD cycle is called the zeitgeber time (ZT). Although circadian rhythms in running-wheel activity are typically linked to the SCN clock6-8, circadian oscillators in many other regions of the brain and body9-14 could also be involved in the regulation of daily activity rhythms. For instance, daily rhythms in food-anticipatory activity do not require the SCN15,16 and instead, are correlated with changes in the activity of extra-SCN oscillators17-20. Thus, running-wheel activity recordings can provide important behavioral information not only about the output of the master SCN clock, but also on the activity of extra-SCN oscillators. Below we describe the equipment and methods used to record, analyze and display circadian locomotor activity rhythms in laboratory rodents.
Neuroscience, Issue 71, Medicine, Neurobiology, Physiology, Anatomy, Psychology, Psychiatry, Behavior, Suprachiasmatic nucleus, locomotor activity, mouse, rat, hamster, light-dark cycle, free-running activity, entrainment, circadian period, circadian rhythm, phase shift, animal model
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Measuring the Kinetics of mRNA Transcription in Single Living Cells
Authors: Yehuda Brody, Yaron Shav-Tal.
Institutions: Bar-Ilan University.
The transcriptional activity of RNA polymerase II (Pol II) is a dynamic process and therefore measuring the kinetics of the transcriptional process in vivo is of importance. Pol II kinetics have been measured using biochemical or molecular methods.1-3 In recent years, with the development of new visualization methods, it has become possible to follow transcription as it occurs in real time in single living cells.4 Herein we describe how to perform analysis of Pol II elongation kinetics on a specific gene in living cells.5, 6 Using a cell line in which a specific gene locus (DNA), its mRNA product, and the final protein product can be fluorescently labeled and visualized in vivo, it is possible to detect the actual transcription of mRNAs on the gene of interest.7, 8 The mRNA is fluorescently tagged using the MS2 system for tagging mRNAs in vivo, where the 3'UTR of the mRNA transcripts contain 24 MS2 stem-loop repeats, which provide highly specific binding sites for the YFP-MS2 coat protein that labels the mRNA as it is transcribed.9 To monitor the kinetics of transcription we use the Fluorescence Recovery After Photobleaching (FRAP) method. By photobleaching the YFP-MS2-tagged nascent transcripts at the site of transcription and then following the recovery of this signal over time, we obtain the synthesis rate of the newly made mRNAs.5 In other words, YFP-MS2 fluorescence recovery reflects the generation of new MS2 stem-loops in the nascent transcripts and their binding by fluorescent free YFP-MS2 molecules entering from the surrounding nucleoplasm. The FRAP recovery curves are then analyzed using mathematical mechanistic models formalized by a series of differential equations, in order to retrieve the kinetic time parameters of transcription.
Cell Biology, Issue 54, mRNA transcription, nucleus, live-cell imaging, cellular dynamics, FRAP
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A Practical Guide to Phylogenetics for Nonexperts
Authors: Damien O'Halloran.
Institutions: The George Washington University.
Many researchers, across incredibly diverse foci, are applying phylogenetics to their research question(s). However, many researchers are new to this topic and so it presents inherent problems. Here we compile a practical introduction to phylogenetics for nonexperts. We outline in a step-by-step manner, a pipeline for generating reliable phylogenies from gene sequence datasets. We begin with a user-guide for similarity search tools via online interfaces as well as local executables. Next, we explore programs for generating multiple sequence alignments followed by protocols for using software to determine best-fit models of evolution. We then outline protocols for reconstructing phylogenetic relationships via maximum likelihood and Bayesian criteria and finally describe tools for visualizing phylogenetic trees. While this is not by any means an exhaustive description of phylogenetic approaches, it does provide the reader with practical starting information on key software applications commonly utilized by phylogeneticists. The vision for this article would be that it could serve as a practical training tool for researchers embarking on phylogenetic studies and also serve as an educational resource that could be incorporated into a classroom or teaching-lab.
Basic Protocol, Issue 84, phylogenetics, multiple sequence alignments, phylogenetic tree, BLAST executables, basic local alignment search tool, Bayesian models
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Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale
Authors: Valentina Gandin, Kristina Sikström, Tommy Alain, Masahiro Morita, Shannon McLaughlan, Ola Larsson, Ivan Topisirovic.
Institutions: McGill University, Karolinska Institutet, McGill University.
mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. Accordingly, dysregulation of mRNA translation is considered to play a major role in a variety of pathological states including cancer. Ribosomes also host chaperones, which facilitate folding of nascent polypeptides, thereby modulating function and stability of newly synthesized polypeptides. In addition, emerging data indicate that ribosomes serve as a platform for a repertoire of signaling molecules, which are implicated in a variety of post-translational modifications of newly synthesized polypeptides as they emerge from the ribosome, and/or components of translational machinery. Herein, a well-established method of ribosome fractionation using sucrose density gradient centrifugation is described. In conjunction with the in-house developed “anota” algorithm this method allows direct determination of differential translation of individual mRNAs on a genome-wide scale. Moreover, this versatile protocol can be used for a variety of biochemical studies aiming to dissect the function of ribosome-associated protein complexes, including those that play a central role in folding and degradation of newly synthesized polypeptides.
Biochemistry, Issue 87, Cells, Eukaryota, Nutritional and Metabolic Diseases, Neoplasms, Metabolic Phenomena, Cell Physiological Phenomena, mRNA translation, ribosomes, protein synthesis, genome-wide analysis, translatome, mTOR, eIF4E, 4E-BP1
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Profiling of Estrogen-regulated MicroRNAs in Breast Cancer Cells
Authors: Anne Katchy, Cecilia Williams.
Institutions: University of Houston.
Estrogen plays vital roles in mammary gland development and breast cancer progression. It mediates its function by binding to and activating the estrogen receptors (ERs), ERα, and ERβ. ERα is frequently upregulated in breast cancer and drives the proliferation of breast cancer cells. The ERs function as transcription factors and regulate gene expression. Whereas ERα's regulation of protein-coding genes is well established, its regulation of noncoding microRNA (miRNA) is less explored. miRNAs play a major role in the post-transcriptional regulation of genes, inhibiting their translation or degrading their mRNA. miRNAs can function as oncogenes or tumor suppressors and are also promising biomarkers. Among the miRNA assays available, microarray and quantitative real-time polymerase chain reaction (qPCR) have been extensively used to detect and quantify miRNA levels. To identify miRNAs regulated by estrogen signaling in breast cancer, their expression in ERα-positive breast cancer cell lines were compared before and after estrogen-activation using both the µParaflo-microfluidic microarrays and Dual Labeled Probes-low density arrays. Results were validated using specific qPCR assays, applying both Cyanine dye-based and Dual Labeled Probes-based chemistry. Furthermore, a time-point assay was used to identify regulations over time. Advantages of the miRNA assay approach used in this study is that it enables a fast screening of mature miRNA regulations in numerous samples, even with limited sample amounts. The layout, including the specific conditions for cell culture and estrogen treatment, biological and technical replicates, and large-scale screening followed by in-depth confirmations using separate techniques, ensures a robust detection of miRNA regulations, and eliminates false positives and other artifacts. However, mutated or unknown miRNAs, or regulations at the primary and precursor transcript level, will not be detected. The method presented here represents a thorough investigation of estrogen-mediated miRNA regulation.
Medicine, Issue 84, breast cancer, microRNA, estrogen, estrogen receptor, microarray, qPCR
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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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Efficient Agroinfiltration of Plants for High-level Transient Expression of Recombinant Proteins
Authors: Kahlin Leuzinger, Matthew Dent, Jonathan Hurtado, Jake Stahnke, Huafang Lai, Xiaohong Zhou, Qiang Chen.
Institutions: Arizona State University .
Mammalian cell culture is the major platform for commercial production of human vaccines and therapeutic proteins. However, it cannot meet the increasing worldwide demand for pharmaceuticals due to its limited scalability and high cost. Plants have shown to be one of the most promising alternative pharmaceutical production platforms that are robust, scalable, low-cost and safe. The recent development of virus-based vectors has allowed rapid and high-level transient expression of recombinant proteins in plants. To further optimize the utility of the transient expression system, we demonstrate a simple, efficient and scalable methodology to introduce target-gene containing Agrobacterium into plant tissue in this study. Our results indicate that agroinfiltration with both syringe and vacuum methods have resulted in the efficient introduction of Agrobacterium into leaves and robust production of two fluorescent proteins; GFP and DsRed. Furthermore, we demonstrate the unique advantages offered by both methods. Syringe infiltration is simple and does not need expensive equipment. It also allows the flexibility to either infiltrate the entire leave with one target gene, or to introduce genes of multiple targets on one leaf. Thus, it can be used for laboratory scale expression of recombinant proteins as well as for comparing different proteins or vectors for yield or expression kinetics. The simplicity of syringe infiltration also suggests its utility in high school and college education for the subject of biotechnology. In contrast, vacuum infiltration is more robust and can be scaled-up for commercial manufacture of pharmaceutical proteins. It also offers the advantage of being able to agroinfiltrate plant species that are not amenable for syringe infiltration such as lettuce and Arabidopsis. Overall, the combination of syringe and vacuum agroinfiltration provides researchers and educators a simple, efficient, and robust methodology for transient protein expression. It will greatly facilitate the development of pharmaceutical proteins and promote science education.
Plant Biology, Issue 77, Genetics, Molecular Biology, Cellular Biology, Virology, Microbiology, Bioengineering, Plant Viruses, Antibodies, Monoclonal, Green Fluorescent Proteins, Plant Proteins, Recombinant Proteins, Vaccines, Synthetic, Virus-Like Particle, Gene Transfer Techniques, Gene Expression, Agroinfiltration, plant infiltration, plant-made pharmaceuticals, syringe agroinfiltration, vacuum agroinfiltration, monoclonal antibody, Agrobacterium tumefaciens, Nicotiana benthamiana, GFP, DsRed, geminiviral vectors, imaging, plant model
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Measuring Cation Transport by Na,K- and H,K-ATPase in Xenopus Oocytes by Atomic Absorption Spectrophotometry: An Alternative to Radioisotope Assays
Authors: Katharina L. Dürr, Neslihan N. Tavraz, Susan Spiller, Thomas Friedrich.
Institutions: Technical University of Berlin, Oregon Health & Science University.
Whereas cation transport by the electrogenic membrane transporter Na+,K+-ATPase can be measured by electrophysiology, the electroneutrally operating gastric H+,K+-ATPase is more difficult to investigate. Many transport assays utilize radioisotopes to achieve a sufficient signal-to-noise ratio, however, the necessary security measures impose severe restrictions regarding human exposure or assay design. Furthermore, ion transport across cell membranes is critically influenced by the membrane potential, which is not straightforwardly controlled in cell culture or in proteoliposome preparations. Here, we make use of the outstanding sensitivity of atomic absorption spectrophotometry (AAS) towards trace amounts of chemical elements to measure Rb+ or Li+ transport by Na+,K+- or gastric H+,K+-ATPase in single cells. Using Xenopus oocytes as expression system, we determine the amount of Rb+ (Li+) transported into the cells by measuring samples of single-oocyte homogenates in an AAS device equipped with a transversely heated graphite atomizer (THGA) furnace, which is loaded from an autosampler. Since the background of unspecific Rb+ uptake into control oocytes or during application of ATPase-specific inhibitors is very small, it is possible to implement complex kinetic assay schemes involving a large number of experimental conditions simultaneously, or to compare the transport capacity and kinetics of site-specifically mutated transporters with high precision. Furthermore, since cation uptake is determined on single cells, the flux experiments can be carried out in combination with two-electrode voltage-clamping (TEVC) to achieve accurate control of the membrane potential and current. This allowed e.g. to quantitatively determine the 3Na+/2K+ transport stoichiometry of the Na+,K+-ATPase and enabled for the first time to investigate the voltage dependence of cation transport by the electroneutrally operating gastric H+,K+-ATPase. In principle, the assay is not limited to K+-transporting membrane proteins, but it may work equally well to address the activity of heavy or transition metal transporters, or uptake of chemical elements by endocytotic processes.
Biochemistry, Issue 72, Chemistry, Biophysics, Bioengineering, Physiology, Molecular Biology, electrochemical processes, physical chemistry, spectrophotometry (application), spectroscopic chemical analysis (application), life sciences, temperature effects (biological, animal and plant), Life Sciences (General), Na+,K+-ATPase, H+,K+-ATPase, Cation Uptake, P-type ATPases, Atomic Absorption Spectrophotometry (AAS), Two-Electrode Voltage-Clamp, Xenopus Oocytes, Rb+ Flux, Transversely Heated Graphite Atomizer (THGA) Furnace, electrophysiology, animal model
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Comprehensive Analysis of Transcription Dynamics from Brain Samples Following Behavioral Experience
Authors: Hagit Turm, Diptendu Mukherjee, Doron Haritan, Maayan Tahor, Ami Citri.
Institutions: The Hebrew University of Jerusalem.
The encoding of experiences in the brain and the consolidation of long-term memories depend on gene transcription. Identifying the function of specific genes in encoding experience is one of the main objectives of molecular neuroscience. Furthermore, the functional association of defined genes with specific behaviors has implications for understanding the basis of neuropsychiatric disorders. Induction of robust transcription programs has been observed in the brains of mice following various behavioral manipulations. While some genetic elements are utilized recurrently following different behavioral manipulations and in different brain nuclei, transcriptional programs are overall unique to the inducing stimuli and the structure in which they are studied1,2. In this publication, a protocol is described for robust and comprehensive transcriptional profiling from brain nuclei of mice in response to behavioral manipulation. The protocol is demonstrated in the context of analysis of gene expression dynamics in the nucleus accumbens following acute cocaine experience. Subsequent to a defined in vivo experience, the target neural tissue is dissected; followed by RNA purification, reverse transcription and utilization of microfluidic arrays for comprehensive qPCR analysis of multiple target genes. This protocol is geared towards comprehensive analysis (addressing 50-500 genes) of limiting quantities of starting material, such as small brain samples or even single cells. The protocol is most advantageous for parallel analysis of multiple samples (e.g. single cells, dynamic analysis following pharmaceutical, viral or behavioral perturbations). However, the protocol could also serve for the characterization and quality assurance of samples prior to whole-genome studies by microarrays or RNAseq, as well as validation of data obtained from whole-genome studies.
Behavior, Issue 90, Brain, behavior, RNA, transcription, nucleus accumbens, cocaine, high-throughput qPCR, experience-dependent plasticity, gene regulatory networks, microdissection
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Global Gene Expression Analysis Using a Zebrafish Oligonucleotide Microarray Platform
Authors: Samuel M. Peterson, Jennifer L. Freeman.
Institutions: Purdue University.
Gene microarray technology permits quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. Gene microarray technology is used in numerous biological disciplines in a variety of applications including global gene expression analysis in relation to developmental stage, to a disease state, and in toxic responses. Herein, we include a demonstration of global gene expression analysis using a comprehensive zebrafish-specific oligonucleotide microarray platform. The zebrafish expression microarray platform contains 385,000 probes, 60 base pairs in length, interrogating 37,157 targets with up to 12 probes per target. For this platform, all cDNA and genomic information available for the zebrafish was collected from various genomic databases including Ensembl (, VEGA (, UCSC (, and ZFIN ( As a result this expression array provides complete coverage of the current zebrafish transcriptome. The zebrafish expression microarray was printed by Roche NimbleGen (Madison, WI). This technical demonstration includes the fluorescent labeling of a cDNA product, hybridization of the labeled cDNA product to the microarray platform, and array scanning for signal acquisition using the one color analysis strategy.
Developmental Biology, Issue 30, zebrafish, microarray, genomics, gene expression, RNA, oligonucleotide
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Strategies for Study of Neuroprotection from Cold-preconditioning
Authors: Heidi M. Mitchell, David M. White, Richard P. Kraig.
Institutions: The University of Chicago Medical Center.
Neurological injury is a frequent cause of morbidity and mortality from general anesthesia and related surgical procedures that could be alleviated by development of effective, easy to administer and safe preconditioning treatments. We seek to define the neural immune signaling responsible for cold-preconditioning as means to identify novel targets for therapeutics development to protect brain before injury onset. Low-level pro-inflammatory mediator signaling changes over time are essential for cold-preconditioning neuroprotection. This signaling is consistent with the basic tenets of physiological conditioning hormesis, which require that irritative stimuli reach a threshold magnitude with sufficient time for adaptation to the stimuli for protection to become evident. Accordingly, delineation of the immune signaling involved in cold-preconditioning neuroprotection requires that biological systems and experimental manipulations plus technical capacities are highly reproducible and sensitive. Our approach is to use hippocampal slice cultures as an in vitro model that closely reflects their in vivo counterparts with multi-synaptic neural networks influenced by mature and quiescent macroglia / microglia. This glial state is particularly important for microglia since they are the principal source of cytokines, which are operative in the femtomolar range. Also, slice cultures can be maintained in vitro for several weeks, which is sufficient time to evoke activating stimuli and assess adaptive responses. Finally, environmental conditions can be accurately controlled using slice cultures so that cytokine signaling of cold-preconditioning can be measured, mimicked, and modulated to dissect the critical node aspects. Cytokine signaling system analyses require the use of sensitive and reproducible multiplexed techniques. We use quantitative PCR for TNF-α to screen for microglial activation followed by quantitative real-time qPCR array screening to assess tissue-wide cytokine changes. The latter is a most sensitive and reproducible means to measure multiple cytokine system signaling changes simultaneously. Significant changes are confirmed with targeted qPCR and then protein detection. We probe for tissue-based cytokine protein changes using multiplexed microsphere flow cytometric assays using Luminex technology. Cell-specific cytokine production is determined with double-label immunohistochemistry. Taken together, this brain tissue preparation and style of use, coupled to the suggested investigative strategies, may be an optimal approach for identifying potential targets for the development of novel therapeutics that could mimic the advantages of cold-preconditioning.
Neuroscience, Issue 43, innate immunity, hormesis, microglia, hippocampus, slice culture, immunohistochemistry, neural-immune, gene expression, real-time PCR
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
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High Throughput Quantitative Expression Screening and Purification Applied to Recombinant Disulfide-rich Venom Proteins Produced in E. coli
Authors: Natalie J. Saez, Hervé Nozach, Marilyne Blemont, Renaud Vincentelli.
Institutions: Aix-Marseille Université, Commissariat à l'énergie atomique et aux énergies alternatives (CEA) Saclay, France.
Escherichia coli (E. coli) is the most widely used expression system for the production of recombinant proteins for structural and functional studies. However, purifying proteins is sometimes challenging since many proteins are expressed in an insoluble form. When working with difficult or multiple targets it is therefore recommended to use high throughput (HTP) protein expression screening on a small scale (1-4 ml cultures) to quickly identify conditions for soluble expression. To cope with the various structural genomics programs of the lab, a quantitative (within a range of 0.1-100 mg/L culture of recombinant protein) and HTP protein expression screening protocol was implemented and validated on thousands of proteins. The protocols were automated with the use of a liquid handling robot but can also be performed manually without specialized equipment. Disulfide-rich venom proteins are gaining increasing recognition for their potential as therapeutic drug leads. They can be highly potent and selective, but their complex disulfide bond networks make them challenging to produce. As a member of the FP7 European Venomics project (, our challenge is to develop successful production strategies with the aim of producing thousands of novel venom proteins for functional characterization. Aided by the redox properties of disulfide bond isomerase DsbC, we adapted our HTP production pipeline for the expression of oxidized, functional venom peptides in the E. coli cytoplasm. The protocols are also applicable to the production of diverse disulfide-rich proteins. Here we demonstrate our pipeline applied to the production of animal venom proteins. With the protocols described herein it is likely that soluble disulfide-rich proteins will be obtained in as little as a week. Even from a small scale, there is the potential to use the purified proteins for validating the oxidation state by mass spectrometry, for characterization in pilot studies, or for sensitive micro-assays.
Bioengineering, Issue 89, E. coli, expression, recombinant, high throughput (HTP), purification, auto-induction, immobilized metal affinity chromatography (IMAC), tobacco etch virus protease (TEV) cleavage, disulfide bond isomerase C (DsbC) fusion, disulfide bonds, animal venom proteins/peptides
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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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Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
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Test Samples for Optimizing STORM Super-Resolution Microscopy
Authors: Daniel J. Metcalf, Rebecca Edwards, Neelam Kumarswami, Alex E. Knight.
Institutions: National Physical Laboratory.
STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.
Molecular Biology, Issue 79, Genetics, Bioengineering, Biomedical Engineering, Biophysics, Basic Protocols, HeLa Cells, Actin Cytoskeleton, Coated Vesicles, Receptor, Epidermal Growth Factor, Actins, Fluorescence, Endocytosis, Microscopy, STORM, super-resolution microscopy, nanoscopy, cell biology, fluorescence microscopy, test samples, resolution, actin filaments, fiducial markers, epidermal growth factor, cell, imaging
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Authors: James Smadbeck, Meghan B. Peterson, George A. Khoury, Martin S. Taylor, Christodoulos A. Floudas.
Institutions: Princeton University.
The aim of de novo protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity. To disseminate these methods for broader use we present Protein WISDOM (, a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
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Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
Authors: Jeremy D. Smith, Abbie E. Ferris, Gary D. Heise, Richard N. Hinrichs, Philip E. Martin.
Institutions: University of Northern Colorado, Arizona State University, Iowa State University.
The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee prosthesis, and 2) contrast the effects of the proposed technique and that of using intact limb inertial properties on joint kinetic estimates during walking in unilateral, transtibial amputees. An oscillation and reaction board system was validated and shown to be reliable when measuring inertial properties of known geometrical solids. When direct measurements of inertial properties of the prosthesis were used in inverse dynamics modeling of the lower extremity compared with inertial estimates based on an intact shank and foot, joint kinetics at the hip and knee were significantly lower during the swing phase of walking. Differences in joint kinetics during stance, however, were smaller than those observed during swing. Therefore, researchers focusing on the swing phase of walking should consider the impact of prosthesis inertia property estimates on study outcomes. For stance, either one of the two inertial models investigated in our study would likely lead to similar outcomes with an inverse dynamics assessment.
Bioengineering, Issue 87, prosthesis inertia, amputee locomotion, below-knee prosthesis, transtibial amputee
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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
Authors: Viktor Martyanov, Robert H. Gross.
Institutions: Dartmouth College.
SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference1. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data1. In this article, we utilize a web version of SCOPE2 to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs3,4 and has been used in other studies5-8. The three algorithms that comprise SCOPE are BEAM9, which finds non-degenerate motifs (ACCGGT), PRISM10, which finds degenerate motifs (ASCGWT), and SPACER11, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from a file. The output from SCOPE contains a list of all identified motifs with their scores, number of occurrences, fraction of genes containing the motif, and the algorithm used to identify the motif. For each motif, result details include a consensus representation of the motif, a sequence logo, a position weight matrix, and a list of instances for every motif occurrence (with exact positions and "strand" indicated). Results are returned in a browser window and also optionally by email. Previous papers describe the SCOPE algorithms in detail1,2,9-11.
Genetics, Issue 51, gene regulation, computational biology, algorithm, promoter sequence motif
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Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
Authors: David C. Shih, Kevin C. Ho, Kyle M. Melnick, Ronald A. Rensink, Tobias R. Kollmann, Edgardo S. Fortuno III.
Institutions: University of British Columbia, University of British Columbia, University of British Columbia.
Visual analytics (VA) has emerged as a new way to analyze large dataset through interactive visual display. We demonstrated the utility and the flexibility of a VA approach in the analysis of biological datasets. Examples of these datasets in immunology include flow cytometry, Luminex data, and genotyping (e.g., single nucleotide polymorphism) data. Contrary to the traditional information visualization approach, VA restores the analysis power in the hands of analyst by allowing the analyst to engage in real-time data exploration process. We selected the VA software called Tableau after evaluating several VA tools. Two types of analysis tasks analysis within and between datasets were demonstrated in the video presentation using an approach called paired analysis. Paired analysis, as defined in VA, is an analysis approach in which a VA tool expert works side-by-side with a domain expert during the analysis. The domain expert is the one who understands the significance of the data, and asks the questions that the collected data might address. The tool expert then creates visualizations to help find patterns in the data that might answer these questions. The short lag-time between the hypothesis generation and the rapid visual display of the data is the main advantage of a VA approach.
Immunology, Issue 47, Visual analytics, flow cytometry, Luminex, Tableau, cytokine, innate immunity, single nucleotide polymorphism
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Quantifying Agonist Activity at G Protein-coupled Receptors
Authors: Frederick J. Ehlert, Hinako Suga, Michael T. Griffin.
Institutions: University of California, Irvine, University of California, Chapman University.
When an agonist activates a population of G protein-coupled receptors (GPCRs), it elicits a signaling pathway that culminates in the response of the cell or tissue. This process can be analyzed at the level of a single receptor, a population of receptors, or a downstream response. Here we describe how to analyze the downstream response to obtain an estimate of the agonist affinity constant for the active state of single receptors. Receptors behave as quantal switches that alternate between active and inactive states (Figure 1). The active state interacts with specific G proteins or other signaling partners. In the absence of ligands, the inactive state predominates. The binding of agonist increases the probability that the receptor will switch into the active state because its affinity constant for the active state (Kb) is much greater than that for the inactive state (Ka). The summation of the random outputs of all of the receptors in the population yields a constant level of receptor activation in time. The reciprocal of the concentration of agonist eliciting half-maximal receptor activation is equivalent to the observed affinity constant (Kobs), and the fraction of agonist-receptor complexes in the active state is defined as efficacy (ε) (Figure 2). Methods for analyzing the downstream responses of GPCRs have been developed that enable the estimation of the Kobs and relative efficacy of an agonist 1,2. In this report, we show how to modify this analysis to estimate the agonist Kb value relative to that of another agonist. For assays that exhibit constitutive activity, we show how to estimate Kb in absolute units of M-1. Our method of analyzing agonist concentration-response curves 3,4 consists of global nonlinear regression using the operational model 5. We describe a procedure using the software application, Prism (GraphPad Software, Inc., San Diego, CA). The analysis yields an estimate of the product of Kobs and a parameter proportional to efficacy (τ). The estimate of τKobs of one agonist, divided by that of another, is a relative measure of Kb (RAi) 6. For any receptor exhibiting constitutive activity, it is possible to estimate a parameter proportional to the efficacy of the free receptor complex (τsys). In this case, the Kb value of an agonist is equivalent to τKobssys 3. Our method is useful for determining the selectivity of an agonist for receptor subtypes and for quantifying agonist-receptor signaling through different G proteins.
Molecular Biology, Issue 58, agonist activity, active state, ligand bias, constitutive activity, G protein-coupled receptor
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Measuring Blood Pressure in Mice using Volume Pressure Recording, a Tail-cuff Method
Authors: Alan Daugherty, Debra Rateri, Lu Hong, Anju Balakrishnan.
Institutions: University of Kentucky.
The CODA 8-Channel High Throughput Non-Invasive Blood Pressure system measures the blood pressure in up to 8 mice or rats simultaneously. The CODA tail-cuff system uses Volume Pressure Recording (VPR) to measure the blood pressure by determining the tail blood volume. A specially designed differential pressure transducer and an occlusion tail-cuff measure the total blood volume in the tail without the need to obtain the individual pulse signal. Special attention is afforded to the length of the occlusion cuff in order to derive the most accurate blood pressure readings. VPR can easily obtain readings on dark-skinned rodents, such as C57BL6 mice and is MRI compatible. The CODA system provides you with measurements of six (6) different blood pressure parameters; systolic and diastolic blood pressure, heart rate, mean blood pressure, tail blood flow, and tail blood volume. Measurements can be made on either awake or anesthetized mice or rats. The CODA system includes a controller, laptop computer, software, cuffs, animal holders, infrared warming pads, and an infrared thermometer. There are seven different holder sizes for mice as small as 8 grams to rats as large as 900 grams.
Medicine, Issue 27, blood pressure, systolic, diastolic, tail-cuff, mouse, rat
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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