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A note on exact differences between beta distributions in genomic (Methylation) studies.
PUBLISHED: 01-01-2014
We apply a known algorithm for computing exactly inequalities between Beta distributions to assess whether a given position in a genome is differentially methylated across samples. We discuss the advantages brought by the adoption of this solution with respect to two approximations (Fisher's test and Z score). The same formalism presented here can be applied in a similar way to variant calling.
Authors: Srikanth Kudithipudi, Denis Kusevic, Sara Weirich, Albert Jeltsch.
Published: 11-29-2014
Lysine methylation is an emerging post-translation modification and it has been identified on several histone and non-histone proteins, where it plays crucial roles in cell development and many diseases. Approximately 5,000 lysine methylation sites were identified on different proteins, which are set by few dozens of protein lysine methyltransferases. This suggests that each PKMT methylates multiple proteins, however till now only one or two substrates have been identified for several of these enzymes. To approach this problem, we have introduced peptide array based substrate specificity analyses of PKMTs. Peptide arrays are powerful tools to characterize the specificity of PKMTs because methylation of several substrates with different sequences can be tested on one array. We synthesized peptide arrays on cellulose membrane using an Intavis SPOT synthesizer and analyzed the specificity of various PKMTs. Based on the results, for several of these enzymes, novel substrates could be identified. For example, for NSD1 by employing peptide arrays, we showed that it methylates K44 of H4 instead of the reported H4K20 and in addition H1.5K168 is the highly preferred substrate over the previously known H3K36. Hence, peptide arrays are powerful tools to biochemically characterize the PKMTs.
23 Related JoVE Articles!
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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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Ultrasonic Assessment of Myocardial Microstructure
Authors: Pranoti Hiremath, Michael Bauer, Hui-Wen Cheng, Kazumasa Unno, Ronglih Liao, Susan Cheng.
Institutions: Harvard Medical School, Brigham and Women's Hospital, Harvard Medical School.
Echocardiography is a widely accessible imaging modality that is commonly used to noninvasively characterize and quantify changes in cardiac structure and function. Ultrasonic assessments of cardiac tissue can include analyses of backscatter signal intensity within a given region of interest. Previously established techniques have relied predominantly on the integrated or mean value of backscatter signal intensities, which may be susceptible to variability from aliased data from low frame rates and time delays for algorithms based on cyclic variation. Herein, we describe an ultrasound-based imaging algorithm that extends from previous methods, can be applied to a single image frame and accounts for the full distribution of signal intensity values derived from a given myocardial sample. When applied to representative mouse and human imaging data, the algorithm distinguishes between subjects with and without exposure to chronic afterload resistance. The algorithm offers an enhanced surrogate measure of myocardial microstructure and can be performed using open-access image analysis software.
Medicine, Issue 83, echocardiography, image analysis, myocardial fibrosis, hypertension, cardiac cycle, open-access image analysis software
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Methods to Identify the NMR Resonances of the 13C-Dimethyl N-terminal Amine on Reductively Methylated Proteins
Authors: Kevin J. Roberson, Pamlea N. Brady, Michelle M. Sweeney, Megan A. Macnaughtan.
Institutions: Louisiana State University.
Nuclear magnetic resonance (NMR) spectroscopy is a proven technique for protein structure and dynamic studies. To study proteins with NMR, stable magnetic isotopes are typically incorporated metabolically to improve the sensitivity and allow for sequential resonance assignment. Reductive 13C-methylation is an alternative labeling method for proteins that are not amenable to bacterial host over-expression, the most common method of isotope incorporation. Reductive 13C-methylation is a chemical reaction performed under mild conditions that modifies a protein's primary amino groups (lysine ε-amino groups and the N-terminal α-amino group) to 13C-dimethylamino groups. The structure and function of most proteins are not altered by the modification, making it a viable alternative to metabolic labeling. Because reductive 13C-methylation adds sparse, isotopic labels, traditional methods of assigning the NMR signals are not applicable. An alternative assignment method using mass spectrometry (MS) to aid in the assignment of protein 13C-dimethylamine NMR signals has been developed. The method relies on partial and different amounts of 13C-labeling at each primary amino group. One limitation of the method arises when the protein's N-terminal residue is a lysine because the α- and ε-dimethylamino groups of Lys1 cannot be individually measured with MS. To circumvent this limitation, two methods are described to identify the NMR resonance of the 13C-dimethylamines associated with both the N-terminal α-amine and the side chain ε-amine. The NMR signals of the N-terminal α-dimethylamine and the side chain ε-dimethylamine of hen egg white lysozyme, Lys1, are identified in 1H-13C heteronuclear single-quantum coherence spectra.
Chemistry, Issue 82, Boranes, Formaldehyde, Dimethylamines, Tandem Mass Spectrometry, nuclear magnetic resonance, MALDI-TOF, Reductive methylation, lysozyme, dimethyllysine, mass spectrometry, NMR
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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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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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The ChroP Approach Combines ChIP and Mass Spectrometry to Dissect Locus-specific Proteomic Landscapes of Chromatin
Authors: Monica Soldi, Tiziana Bonaldi.
Institutions: European Institute of Oncology.
Chromatin is a highly dynamic nucleoprotein complex made of DNA and proteins that controls various DNA-dependent processes. Chromatin structure and function at specific regions is regulated by the local enrichment of histone post-translational modifications (hPTMs) and variants, chromatin-binding proteins, including transcription factors, and DNA methylation. The proteomic characterization of chromatin composition at distinct functional regions has been so far hampered by the lack of efficient protocols to enrich such domains at the appropriate purity and amount for the subsequent in-depth analysis by Mass Spectrometry (MS). We describe here a newly designed chromatin proteomics strategy, named ChroP (Chromatin Proteomics), whereby a preparative chromatin immunoprecipitation is used to isolate distinct chromatin regions whose features, in terms of hPTMs, variants and co-associated non-histonic proteins, are analyzed by MS. We illustrate here the setting up of ChroP for the enrichment and analysis of transcriptionally silent heterochromatic regions, marked by the presence of tri-methylation of lysine 9 on histone H3. The results achieved demonstrate the potential of ChroP in thoroughly characterizing the heterochromatin proteome and prove it as a powerful analytical strategy for understanding how the distinct protein determinants of chromatin interact and synergize to establish locus-specific structural and functional configurations.
Biochemistry, Issue 86, chromatin, histone post-translational modifications (hPTMs), epigenetics, mass spectrometry, proteomics, SILAC, chromatin immunoprecipitation , histone variants, chromatome, hPTMs cross-talks
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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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Quantification of Global Diastolic Function by Kinematic Modeling-based Analysis of Transmitral Flow via the Parametrized Diastolic Filling Formalism
Authors: Sina Mossahebi, Simeng Zhu, Howard Chen, Leonid Shmuylovich, Erina Ghosh, Sándor J. Kovács.
Institutions: Washington University in St. Louis, Washington University in St. Louis, Washington University in St. Louis, Washington University in St. Louis, Washington University in St. Louis.
Quantitative cardiac function assessment remains a challenge for physiologists and clinicians. Although historically invasive methods have comprised the only means available, the development of noninvasive imaging modalities (echocardiography, MRI, CT) having high temporal and spatial resolution provide a new window for quantitative diastolic function assessment. Echocardiography is the agreed upon standard for diastolic function assessment, but indexes in current clinical use merely utilize selected features of chamber dimension (M-mode) or blood/tissue motion (Doppler) waveforms without incorporating the physiologic causal determinants of the motion itself. The recognition that all left ventricles (LV) initiate filling by serving as mechanical suction pumps allows global diastolic function to be assessed based on laws of motion that apply to all chambers. What differentiates one heart from another are the parameters of the equation of motion that governs filling. Accordingly, development of the Parametrized Diastolic Filling (PDF) formalism has shown that the entire range of clinically observed early transmitral flow (Doppler E-wave) patterns are extremely well fit by the laws of damped oscillatory motion. This permits analysis of individual E-waves in accordance with a causal mechanism (recoil-initiated suction) that yields three (numerically) unique lumped parameters whose physiologic analogues are chamber stiffness (k), viscoelasticity/relaxation (c), and load (xo). The recording of transmitral flow (Doppler E-waves) is standard practice in clinical cardiology and, therefore, the echocardiographic recording method is only briefly reviewed. Our focus is on determination of the PDF parameters from routinely recorded E-wave data. As the highlighted results indicate, once the PDF parameters have been obtained from a suitable number of load varying E-waves, the investigator is free to use the parameters or construct indexes from the parameters (such as stored energy 1/2kxo2, maximum A-V pressure gradient kxo, load independent index of diastolic function, etc.) and select the aspect of physiology or pathophysiology to be quantified.
Bioengineering, Issue 91, cardiovascular physiology, ventricular mechanics, diastolic function, mathematical modeling, Doppler echocardiography, hemodynamics, biomechanics
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In vitro Methylation Assay to Study Protein Arginine Methylation
Authors: Rama Kamesh Bikkavilli, Sreedevi Avasarala, Michelle Van Scoyk, Manoj Kumar Karuppusamy Rathinam, Jordi Tauler, Stanley Borowicz, Robert A. Winn.
Institutions: University of Illinois at Chicago, University of Illinois at Chicago, Jesse Brown Veterans Affairs Medical Center.
Protein arginine methylation is one of the most abundant post-translational modifications in the nucleus. Protein arginine methylation can be identified and/or determined via proteomic approaches, and/or immunoblotting with methyl-arginine specific antibodies. However, these techniques sometimes can be misleading and often provide false positive results. Most importantly, these techniques cannot provide direct evidence in support of the PRMT substrate specificity. In vitro methylation assays, on the other hand, are useful biochemical assays, which are sensitive, and consistently reveal if the identified proteins are indeed PRMT substrates. A typical in vitro methylation assay includes purified, active PRMTs, purified substrate and a radioisotope labeled methyl donor (S-adenosyl-L-[methyl-3H] methionine). Here we describe a step-by-step protocol to isolate catalytically active PRMT1, a ubiquitously expressed PRMT family member. The methyl transferase activities of the purified PRMT1 were later tested on Ras-GTPase activating protein binding protein 1 (G3BP1), a known PRMT substrate, in the presence of S-adenosyl-L-[methyl-3H] methionine as the methyl donor. This protocol can be employed not only for establishing the methylation status of novel physiological PRMT1 substrates, but also for understanding the basic mechanism of protein arginine methylation.
Genetics, Issue 92, PRMT, protein methylation, SAMe, arginine, methylated proteins, methylation assay
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Sequence-specific Labeling of Nucleic Acids and Proteins with Methyltransferases and Cofactor Analogues
Authors: Gisela Maria Hanz, Britta Jung, Anna Giesbertz, Matyas Juhasz, Elmar Weinhold.
Institutions: RWTH Aachen University.
S-Adenosyl-l-methionine (AdoMet or SAM)-dependent methyltransferases (MTase) catalyze the transfer of the activated methyl group from AdoMet to specific positions in DNA, RNA, proteins and small biomolecules. This natural methylation reaction can be expanded to a wide variety of alkylation reactions using synthetic cofactor analogues. Replacement of the reactive sulfonium center of AdoMet with an aziridine ring leads to cofactors which can be coupled with DNA by various DNA MTases. These aziridine cofactors can be equipped with reporter groups at different positions of the adenine moiety and used for Sequence-specific Methyltransferase-Induced Labeling of DNA (SMILing DNA). As a typical example we give a protocol for biotinylation of pBR322 plasmid DNA at the 5’-ATCGAT-3’ sequence with the DNA MTase M.BseCI and the aziridine cofactor 6BAz in one step. Extension of the activated methyl group with unsaturated alkyl groups results in another class of AdoMet analogues which are used for methyltransferase-directed Transfer of Activated Groups (mTAG). Since the extended side chains are activated by the sulfonium center and the unsaturated bond, these cofactors are called double-activated AdoMet analogues. These analogues not only function as cofactors for DNA MTases, like the aziridine cofactors, but also for RNA, protein and small molecule MTases. They are typically used for enzymatic modification of MTase substrates with unique functional groups which are labeled with reporter groups in a second chemical step. This is exemplified in a protocol for fluorescence labeling of histone H3 protein. A small propargyl group is transferred from the cofactor analogue SeAdoYn to the protein by the histone H3 lysine 4 (H3K4) MTase Set7/9 followed by click labeling of the alkynylated histone H3 with TAMRA azide. MTase-mediated labeling with cofactor analogues is an enabling technology for many exciting applications including identification and functional study of MTase substrates as well as DNA genotyping and methylation detection.
Biochemistry, Issue 93, S-adenosyl-l-methionine, AdoMet, SAM, aziridine cofactor, double activated cofactor, methyltransferase, DNA methylation, protein methylation, biotin labeling, fluorescence labeling, SMILing, mTAG
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Setting Limits on Supersymmetry Using Simplified Models
Authors: Christian Gütschow, Zachary Marshall.
Institutions: University College London, CERN, Lawrence Berkeley National Laboratories.
Experimental limits on supersymmetry and similar theories are difficult to set because of the enormous available parameter space and difficult to generalize because of the complexity of single points. Therefore, more phenomenological, simplified models are becoming popular for setting experimental limits, as they have clearer physical interpretations. The use of these simplified model limits to set a real limit on a concrete theory has not, however, been demonstrated. This paper recasts simplified model limits into limits on a specific and complete supersymmetry model, minimal supergravity. Limits obtained under various physical assumptions are comparable to those produced by directed searches. A prescription is provided for calculating conservative and aggressive limits on additional theories. Using acceptance and efficiency tables along with the expected and observed numbers of events in various signal regions, LHC experimental results can be recast in this manner into almost any theoretical framework, including nonsupersymmetric theories with supersymmetry-like signatures.
Physics, Issue 81, high energy physics, particle physics, Supersymmetry, LHC, ATLAS, CMS, New Physics Limits, Simplified Models
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
Authors: Stéphanie Beaucourt, Antonio V. Bordería, Lark L. Coffey, Nina F. Gnädig, Marta Sanz-Ramos, Yasnee Beeharry, Marco Vignuzzi.
Institutions: Institut Pasteur .
RNA viruses use RNA dependent RNA polymerases to replicate their genomes. The intrinsically high error rate of these enzymes is a large contributor to the generation of extreme population diversity that facilitates virus adaptation and evolution. Increasing evidence shows that the intrinsic error rates, and the resulting mutation frequencies, of RNA viruses can be modulated by subtle amino acid changes to the viral polymerase. Although biochemical assays exist for some viral RNA polymerases that permit quantitative measure of incorporation fidelity, here we describe a simple method of measuring mutation frequencies of RNA viruses that has proven to be as accurate as biochemical approaches in identifying fidelity altering mutations. The approach uses conventional virological and sequencing techniques that can be performed in most biology laboratories. Based on our experience with a number of different viruses, we have identified the key steps that must be optimized to increase the likelihood of isolating fidelity variants and generating data of statistical significance. The isolation and characterization of fidelity altering mutations can provide new insights into polymerase structure and function1-3. Furthermore, these fidelity variants can be useful tools in characterizing mechanisms of virus adaptation and evolution4-7.
Immunology, Issue 52, Polymerase fidelity, RNA virus, mutation frequency, mutagen, RNA polymerase, viral evolution
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DNA Methylation: Bisulphite Modification and Analysis
Authors: Kate Patterson, Laura Molloy, Wenjia Qu, Susan Clark.
Institutions: Garvan Institute of Medical Research, University of NSW.
Epigenetics describes the heritable changes in gene function that occur independently to the DNA sequence. The molecular basis of epigenetic gene regulation is complex, but essentially involves modifications to the DNA itself or the proteins with which DNA associates. The predominant epigenetic modification of DNA in mammalian genomes is methylation of cytosine nucleotides (5-MeC). DNA methylation provides instruction to gene expression machinery as to where and when the gene should be expressed. The primary target sequence for DNA methylation in mammals is 5'-CpG-3' dinucleotides (Figure 1). CpG dinucleotides are not uniformly distributed throughout the genome, but are concentrated in regions of repetitive genomic sequences and CpG "islands" commonly associated with gene promoters (Figure 1). DNA methylation patterns are established early in development, modulated during tissue specific differentiation and disrupted in many disease states including cancer. To understand the biological role of DNA methylation and its role in human disease, precise, efficient and reproducible methods are required to detect and quantify individual 5-MeCs. This protocol for bisulphite conversion is the "gold standard" for DNA methylation analysis and facilitates identification and quantification of DNA methylation at single nucleotide resolution. The chemistry of cytosine deamination by sodium bisulphite involves three steps (Figure 2). (1) Sulphonation: The addition of bisulphite to the 5-6 double bond of cytosine (2) Hydrolic Deamination: hydrolytic deamination of the resulting cytosine-bisulphite derivative to give a uracil-bisulphite derivative (3) Alkali Desulphonation: Removal of the sulphonate group by an alkali treatment, to give uracil. Bisulphite preferentially deaminates cytosine to uracil in single stranded DNA, whereas 5-MeC, is refractory to bisulphite-mediated deamination. Upon PCR amplification, uracil is amplified as thymine while 5-MeC residues remain as cytosines, allowing methylated CpGs to be distinguished from unmethylated CpGs by presence of a cytosine "C" versus thymine "T" residue during sequencing. DNA modification by bisulphite conversion is a well-established protocol that can be exploited for many methods of DNA methylation analysis. Since the detection of 5-MeC by bisulphite conversion was first demonstrated by Frommer et al.1 and Clark et al.2, methods based around bisulphite conversion of genomic DNA account for the majority of new data on DNA methylation. Different methods of post PCR analysis may be utilized, depending on the degree of specificity and resolution of methylation required. Cloning and sequencing is still the most readily available method that can give single nucleotide resolution for methylation across the DNA molecule.
Genetics, Issue 56, epigenetics, DNA methylation, Bisulphite, 5-methylcytosine (5-MeC), PCR
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Application of MassSQUIRM for Quantitative Measurements of Lysine Demethylase Activity
Authors: Lauren P. Blair, Nathan L. Avaritt, Alan J. Tackett.
Institutions: University of Arkansas for Medical Sciences .
Recently, epigenetic regulators have been discovered as key players in many different diseases 1-3. As a result, these enzymes are prime targets for small molecule studies and drug development 4. Many epigenetic regulators have only recently been discovered and are still in the process of being classified. Among these enzymes are lysine demethylases which remove methyl groups from lysines on histones and other proteins. Due to the novel nature of this class of enzymes, few assays have been developed to study their activity. This has been a road block to both the classification and high throughput study of histone demethylases. Currently, very few demethylase assays exist. Those that do exist tend to be qualitative in nature and cannot simultaneously discern between the different lysine methylation states (un-, mono-, di- and tri-). Mass spectrometry is commonly used to determine demethylase activity but current mass spectrometric assays do not address whether differentially methylated peptides ionize differently. Differential ionization of methylated peptides makes comparing methylation states difficult and certainly not quantitative (Figure 1A). Thus available assays are not optimized for the comprehensive analysis of demethylase activity. Here we describe a method called MassSQUIRM (mass spectrometric quantitation using isotopic reductive methylation) that is based on reductive methylation of amine groups with deuterated formaldehyde to force all lysines to be di-methylated, thus making them essentially the same chemical species and therefore ionize the same (Figure 1B). The only chemical difference following the reductive methylation is hydrogen and deuterium, which does not affect MALDI ionization efficiencies. The MassSQUIRM assay is specific for demethylase reaction products with un-, mono- or di-methylated lysines. The assay is also applicable to lysine methyltransferases giving the same reaction products. Here, we use a combination of reductive methylation chemistry and MALDI mass spectrometry to measure the activity of LSD1, a lysine demethylase capable of removing di- and mono-methyl groups, on a synthetic peptide substrate 5. This assay is simple and easily amenable to any lab with access to a MALDI mass spectrometer in lab or through a proteomics facility. The assay has ~8-fold dynamic range and is readily scalable to plate format 5.
Molecular Biology, Issue 61, LSD1, lysine demethylase, mass spectrometry, reductive methylation, demethylase quantification
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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Authors: Francesco Vallania, Enrique Ramos, Sharon Cresci, Robi D. Mitra, Todd E. Druley.
Institutions: Washington University School of Medicine, Washington University School of Medicine, Washington University School of Medicine.
As DNA sequencing technology has markedly advanced in recent years2, it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought3. In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease4,5. Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual's personal profile of rare or private DNA variants6-8. However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today's platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators. To address this need, we have developed a pooled sequencing approach1,9 and a novel software package1 for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis ( We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.
Genetics, Issue 64, Genomics, Cancer Biology, Bioinformatics, Pooled DNA sequencing, SPLINTER, rare genetic variants, genetic screening, phenotype, high throughput, computational analysis, DNA, PCR, primers
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Single Oocyte Bisulfite Mutagenesis
Authors: Michelle M. Denomme, Liyue Zhang, Mellissa R.W. Mann.
Institutions: Schulich School of Medicine and Dentistry, University of Western Ontario, Schulich School of Medicine and Dentistry, University of Western Ontario, Children's Health Research Institute.
Epigenetics encompasses all heritable and reversible modifications to chromatin that alter gene accessibility, and thus are the primary mechanisms for regulating gene transcription1. DNA methylation is an epigenetic modification that acts predominantly as a repressive mark. Through the covalent addition of a methyl group onto cytosines in CpG dinucleotides, it can recruit additional repressive proteins and histone modifications to initiate processes involved in condensing chromatin and silencing genes2. DNA methylation is essential for normal development as it plays a critical role in developmental programming, cell differentiation, repression of retroviral elements, X-chromosome inactivation and genomic imprinting. One of the most powerful methods for DNA methylation analysis is bisulfite mutagenesis. Sodium bisulfite is a DNA mutagen that deaminates cytosines into uracils. Following PCR amplification and sequencing, these conversion events are detected as thymines. Methylated cytosines are protected from deamination and thus remain as cytosines, enabling identification of DNA methylation at the individual nucleotide level3. Development of the bisulfite mutagenesis assay has advanced from those originally reported4-6 towards ones that are more sensitive and reproducible7. One key advancement was embedding smaller amounts of DNA in an agarose bead, thereby protecting DNA from the harsh bisulfite treatment8. This enabled methylation analysis to be performed on pools of oocytes and blastocyst-stage embryos9. The most sophisticated bisulfite mutagenesis protocol to date is for individual blastocyst-stage embryos10. However, since blastocysts have on average 64 cells (containing 120-720 pg of genomic DNA), this method is not efficacious for methylation studies on individual oocytes or cleavage-stage embryos. Taking clues from agarose embedding of minute DNA amounts including oocytes11, here we present a method whereby oocytes are directly embedded in an agarose and lysis solution bead immediately following retrieval and removal of the zona pellucida from the oocyte. This enables us to bypass the two main challenges of single oocyte bisulfite mutagenesis: protecting a minute amount of DNA from degradation, and subsequent loss during the numerous protocol steps. Importantly, as data are obtained from single oocytes, the issue of PCR bias within pools is eliminated. Furthermore, inadvertent cumulus cell contamination is detectable by this method since any sample with more than one methylation pattern may be excluded from analysis12. This protocol provides an improved method for successful and reproducible analyses of DNA methylation at the single-cell level and is ideally suited for individual oocytes as well as cleavage-stage embryos.
Genetics, Issue 64, Developmental Biology, Biochemistry, Bisulfite mutagenesis, DNA methylation, individual oocyte, individual embryo, mouse model, PCR, epigenetics
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
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RNA-seq Analysis of Transcriptomes in Thrombin-treated and Control Human Pulmonary Microvascular Endothelial Cells
Authors: Dilyara Cheranova, Margaret Gibson, Suman Chaudhary, Li Qin Zhang, Daniel P. Heruth, Dmitry N. Grigoryev, Shui Qing Ye.
Institutions: Children's Mercy Hospital and Clinics, School of Medicine, University of Missouri-Kansas City.
The characterization of gene expression in cells via measurement of mRNA levels is a useful tool in determining how the transcriptional machinery of the cell is affected by external signals (e.g. drug treatment), or how cells differ between a healthy state and a diseased state. With the advent and continuous refinement of next-generation DNA sequencing technology, RNA-sequencing (RNA-seq) has become an increasingly popular method of transcriptome analysis to catalog all species of transcripts, to determine the transcriptional structure of all expressed genes and to quantify the changing expression levels of the total set of transcripts in a given cell, tissue or organism1,2 . RNA-seq is gradually replacing DNA microarrays as a preferred method for transcriptome analysis because it has the advantages of profiling a complete transcriptome, providing a digital type datum (copy number of any transcript) and not relying on any known genomic sequence3. Here, we present a complete and detailed protocol to apply RNA-seq to profile transcriptomes in human pulmonary microvascular endothelial cells with or without thrombin treatment. This protocol is based on our recent published study entitled "RNA-seq Reveals Novel Transcriptome of Genes and Their Isoforms in Human Pulmonary Microvascular Endothelial Cells Treated with Thrombin,"4 in which we successfully performed the first complete transcriptome analysis of human pulmonary microvascular endothelial cells treated with thrombin using RNA-seq. It yielded unprecedented resources for further experimentation to gain insights into molecular mechanisms underlying thrombin-mediated endothelial dysfunction in the pathogenesis of inflammatory conditions, cancer, diabetes, and coronary heart disease, and provides potential new leads for therapeutic targets to those diseases. The descriptive text of this protocol is divided into four parts. The first part describes the treatment of human pulmonary microvascular endothelial cells with thrombin and RNA isolation, quality analysis and quantification. The second part describes library construction and sequencing. The third part describes the data analysis. The fourth part describes an RT-PCR validation assay. Representative results of several key steps are displayed. Useful tips or precautions to boost success in key steps are provided in the Discussion section. Although this protocol uses human pulmonary microvascular endothelial cells treated with thrombin, it can be generalized to profile transcriptomes in both mammalian and non-mammalian cells and in tissues treated with different stimuli or inhibitors, or to compare transcriptomes in cells or tissues between a healthy state and a disease state.
Genetics, Issue 72, Molecular Biology, Immunology, Medicine, Genomics, Proteins, RNA-seq, Next Generation DNA Sequencing, Transcriptome, Transcription, Thrombin, Endothelial cells, high-throughput, DNA, genomic DNA, RT-PCR, PCR
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Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
Authors: Julie Chaumeil, Mariann Micsinai, Jane A. Skok.
Institutions: New York University School of Medicine, New York University Center for Health Informatics and Bioinformatics, NYU Cancer Institute, Yale University School of Medicine .
Fluorescent in situ hybridization using DNA probes on 3-dimensionally preserved nuclei followed by 3D confocal microscopy (3D DNA FISH) represents the most direct way to visualize the location of gene loci, chromosomal sub-regions or entire territories in individual cells. This type of analysis provides insight into the global architecture of the nucleus as well as the behavior of specific genomic loci and regions within the nuclear space. Immunofluorescence, on the other hand, permits the detection of nuclear proteins (modified histones, histone variants and modifiers, transcription machinery and factors, nuclear sub-compartments, etc). The major challenge in combining immunofluorescence and 3D DNA FISH is, on the one hand to preserve the epitope detected by the antibody as well as the 3D architecture of the nucleus, and on the other hand, to allow the penetration of the DNA probe to detect gene loci or chromosome territories 1-5. Here we provide a protocol that combines visualization of chromatin modifications with genomic loci in 3D preserved nuclei.
Genetics, Issue 72, Molecular Biology, Bioinformatics, Cancer Biology, Pathology, Biomedical Engineering, Immunology, Intranuclear Space, Nuclear Matrix, Fluorescence in situ Hybridization, FISH, 3D DNA FISH, DNA, immunofluorescence, immuno-FISH, 3D microscopy, Nuclear organization, interphase nuclei, chromatin modifications
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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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A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Authors: Gauthier Julie, Fadi F. Hamdan, Guy A. Rouleau.
Institutions: Universite de Montreal, Universite de Montreal, Universite de Montreal.
There are several lines of evidence supporting the role of de novo mutations as a mechanism for common disorders, such as autism and schizophrenia. First, the de novo mutation rate in humans is relatively high, so new mutations are generated at a high frequency in the population. However, de novo mutations have not been reported in most common diseases. Mutations in genes leading to severe diseases where there is a strong negative selection against the phenotype, such as lethality in embryonic stages or reduced reproductive fitness, will not be transmitted to multiple family members, and therefore will not be detected by linkage gene mapping or association studies. The observation of very high concordance in monozygotic twins and very low concordance in dizygotic twins also strongly supports the hypothesis that a significant fraction of cases may result from new mutations. Such is the case for diseases such as autism and schizophrenia. Second, despite reduced reproductive fitness1 and extremely variable environmental factors, the incidence of some diseases is maintained worldwide at a relatively high and constant rate. This is the case for autism and schizophrenia, with an incidence of approximately 1% worldwide. Mutational load can be thought of as a balance between selection for or against a deleterious mutation and its production by de novo mutation. Lower rates of reproduction constitute a negative selection factor that should reduce the number of mutant alleles in the population, ultimately leading to decreased disease prevalence. These selective pressures tend to be of different intensity in different environments. Nonetheless, these severe mental disorders have been maintained at a constant relatively high prevalence in the worldwide population across a wide range of cultures and countries despite a strong negative selection against them2. This is not what one would predict in diseases with reduced reproductive fitness, unless there was a high new mutation rate. Finally, the effects of paternal age: there is a significantly increased risk of the disease with increasing paternal age, which could result from the age related increase in paternal de novo mutations. This is the case for autism and schizophrenia3. The male-to-female ratio of mutation rate is estimated at about 4–6:1, presumably due to a higher number of germ-cell divisions with age in males. Therefore, one would predict that de novo mutations would more frequently come from males, particularly older males4. A high rate of new mutations may in part explain why genetic studies have so far failed to identify many genes predisposing to complexes diseases genes, such as autism and schizophrenia, and why diseases have been identified for a mere 3% of genes in the human genome. Identification for de novo mutations as a cause of a disease requires a targeted molecular approach, which includes studying parents and affected subjects. The process for determining if the genetic basis of a disease may result in part from de novo mutations and the molecular approach to establish this link will be illustrated, using autism and schizophrenia as examples.
Medicine, Issue 52, de novo mutation, complex diseases, schizophrenia, autism, rare variations, DNA sequencing
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A Simple Composite Phenotype Scoring System for Evaluating Mouse Models of Cerebellar Ataxia
Authors: Stephan J. Guyenet, Stephanie A. Furrer, Vincent M. Damian, Travis D. Baughan, Albert R. La Spada, Gwenn A. Garden.
Institutions: University of Washington, University of Washington, University of California, San Diego - Rady Children’s Hospital.
We describe a protocol for the rapid and sensitive quantification of disease severity in mouse models of cerebella ataxia. It is derived from previously published phenotype assessments in several disease models, including spinocerebellar ataxias, Huntington s disease and spinobulbar muscular atrophy. Measures include hind limb clasping, ledge test, gait and kyphosis. Each measure is recorded on a scale of 0-3, with a combined total of 0-12 for all four measures. The results effectively discriminate between affected and non-affected individuals, while also quantifying the temporal progression of neurodegenerative disease phenotypes. Measures may be analyzed individually or combined into a composite phenotype score for greater statistical power. The ideal combination of the four described measures will depend upon the disorder in question. We present an example of the protocol used to assess disease severity in a transgenic mouse model of spinocerebellar ataxia type 7 (SCA7). Albert R. La Spada and Gwenn A. Garden contributed to this manuscript equally.
JoVE Neuroscience, Issue 39, Neurodegeneration, Mouse behavior assay, cerebellar ataxia, polyglutamine disease
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