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Pubmed Article
Analysis and prediction of the critical regions of antimicrobial peptides based on conditional random fields.
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PLoS ONE
PUBLISHED: 03-25-2015
Antimicrobial peptides (AMPs) are potent drug candidates against microbes such as bacteria, fungi, parasites, and viruses. The size of AMPs ranges from less than ten to hundreds of amino acids. Often only a few amino acids or the critical regions of antimicrobial proteins matter the functionality. Accurately predicting the AMP critical regions could benefit the experimental designs. However, no extensive analyses have been done specifically on the AMP critical regions and computational modeling on them is either non-existent or settled to other problems. With a focus on the AMP critical regions, we thus develop a computational model AMPcore by introducing a state-of-the-art machine learning method, conditional random fields. We generate a comprehensive dataset of 798 AMPs cores and a low similarity dataset of 510 representative AMP cores. AMPcore could reach a maximal accuracy of 90% and 0.79 Matthew's correlation coefficient on the comprehensive dataset and a maximal accuracy of 83% and 0.66 MCC on the low similarity dataset. Our analyses of AMP cores follow what we know about AMPs: High in glycine and lysine, but low in aspartic acid, glutamic acid, and methionine; the abundance of ?-helical structures; the dominance of positive net charges; the peculiarity of amphipathicity. Two amphipathic sequence motifs within the AMP cores, an amphipathic ?-helix and an amphipathic ?-helix, are revealed. In addition, a short sequence motif at the N-terminal boundary of AMP cores is reported for the first time: arginine at the P(-1) coupling with glycine at the P1 of AMP cores occurs the most, which might link to microbial cell adhesion.
Authors: Ambrish Roy, Dong Xu, Jonathan Poisson, Yang Zhang.
Published: 11-03-2011
ABSTRACT
Genome sequencing projects have ciphered millions of protein sequence, which require knowledge of their structure and function to improve the understanding of their biological role. Although experimental methods can provide detailed information for a small fraction of these proteins, computational modeling is needed for the majority of protein molecules which are experimentally uncharacterized. The I-TASSER server is an on-line workbench for high-resolution modeling of protein structure and function. Given a protein sequence, a typical output from the I-TASSER server includes secondary structure prediction, predicted solvent accessibility of each residue, homologous template proteins detected by threading and structure alignments, up to five full-length tertiary structural models, and structure-based functional annotations for enzyme classification, Gene Ontology terms and protein-ligand binding sites. All the predictions are tagged with a confidence score which tells how accurate the predictions are without knowing the experimental data. To facilitate the special requests of end users, the server provides channels to accept user-specified inter-residue distance and contact maps to interactively change the I-TASSER modeling; it also allows users to specify any proteins as template, or to exclude any template proteins during the structure assembly simulations. The structural information could be collected by the users based on experimental evidences or biological insights with the purpose of improving the quality of I-TASSER predictions. The server was evaluated as the best programs for protein structure and function predictions in the recent community-wide CASP experiments. There are currently >20,000 registered scientists from over 100 countries who are using the on-line I-TASSER server.
24 Related JoVE Articles!
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Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA
Authors: Ashwin Prakash, Jason Bechtel, Alexei Fedorov.
Institutions: University of Toledo Health Science Campus.
Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in their nucleotide composition and consist of a complex mosaic of sequence patterns. These patterns include so-called Mid-Range Inhomogeneity (MRI) regions -- sequences 30-10000 nucleotides in length that are enriched by a particular base or combination of bases (e.g. (G+T)-rich, purine-rich, etc.). MRI regions are associated with unusual (non-B-form) DNA structures that are often involved in regulation of gene expression, recombination, and other genetic processes (Fedorova & Fedorov 2010). The existence of a strong fixation bias within MRI regions against mutations that tend to reduce their sequence inhomogeneity additionally supports the functionality and importance of these genomic sequences (Prakash et al. 2009). Here we demonstrate a freely available Internet resource -- the Genomic MRI program package -- designed for computational analysis of genomic sequences in order to find and characterize various MRI patterns within them (Bechtel et al. 2008). This package also allows generation of randomized sequences with various properties and level of correspondence to the natural input DNA sequences. The main goal of this resource is to facilitate examination of vast regions of non-coding DNA that are still scarcely investigated and await thorough exploration and recognition.
Genetics, Issue 51, bioinformatics, computational biology, genomics, non-randomness, signals, gene regulation, DNA conformation
2663
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A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
Authors: Regina Salvat, Leonard Moise, Chris Bailey-Kellogg, Karl E. Griswold.
Institutions: Dartmouth College, University of Rhode Island, Dartmouth College.
Biochemical assays with recombinant human MHC II molecules can provide rapid, quantitative insights into immunogenic epitope identification, deletion, or design1,2. Here, a peptide-MHC II binding assay is scaled to 384-well format. The scaled down protocol reduces reagent costs by 75% and is higher throughput than previously described 96-well protocols1,3-5. Specifically, the experimental design permits robust and reproducible analysis of up to 15 peptides against one MHC II allele per 384-well ELISA plate. Using a single liquid handling robot, this method allows one researcher to analyze approximately ninety test peptides in triplicate over a range of eight concentrations and four MHC II allele types in less than 48 hr. Others working in the fields of protein deimmunization or vaccine design and development may find the protocol to be useful in facilitating their own work. In particular, the step-by-step instructions and the visual format of JoVE should allow other users to quickly and easily establish this methodology in their own labs.
Biochemistry, Issue 85, Immunoassay, Protein Immunogenicity, MHC II, T cell epitope, High Throughput Screen, Deimmunization, Vaccine Design
51308
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Laboratory-determined Phosphorus Flux from Lake Sediments as a Measure of Internal Phosphorus Loading
Authors: Mary E. Ogdahl, Alan D. Steinman, Maggie E. Weinert.
Institutions: Grand Valley State University.
Eutrophication is a water quality issue in lakes worldwide, and there is a critical need to identify and control nutrient sources. Internal phosphorus (P) loading from lake sediments can account for a substantial portion of the total P load in eutrophic, and some mesotrophic, lakes. Laboratory determination of P release rates from sediment cores is one approach for determining the role of internal P loading and guiding management decisions. Two principal alternatives to experimental determination of sediment P release exist for estimating internal load: in situ measurements of changes in hypolimnetic P over time and P mass balance. The experimental approach using laboratory-based sediment incubations to quantify internal P load is a direct method, making it a valuable tool for lake management and restoration. Laboratory incubations of sediment cores can help determine the relative importance of internal vs. external P loads, as well as be used to answer a variety of lake management and research questions. We illustrate the use of sediment core incubations to assess the effectiveness of an aluminum sulfate (alum) treatment for reducing sediment P release. Other research questions that can be investigated using this approach include the effects of sediment resuspension and bioturbation on P release. The approach also has limitations. Assumptions must be made with respect to: extrapolating results from sediment cores to the entire lake; deciding over what time periods to measure nutrient release; and addressing possible core tube artifacts. A comprehensive dissolved oxygen monitoring strategy to assess temporal and spatial redox status in the lake provides greater confidence in annual P loads estimated from sediment core incubations.
Environmental Sciences, Issue 85, Limnology, internal loading, eutrophication, nutrient flux, sediment coring, phosphorus, lakes
51617
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Modeling Astrocytoma Pathogenesis In Vitro and In Vivo Using Cortical Astrocytes or Neural Stem Cells from Conditional, Genetically Engineered Mice
Authors: Robert S. McNeill, Ralf S. Schmid, Ryan E. Bash, Mark Vitucci, Kristen K. White, Andrea M. Werneke, Brian H. Constance, Byron Huff, C. Ryan Miller.
Institutions: University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, University of North Carolina School of Medicine, Emory University School of Medicine, University of North Carolina School of Medicine.
Current astrocytoma models are limited in their ability to define the roles of oncogenic mutations in specific brain cell types during disease pathogenesis and their utility for preclinical drug development. In order to design a better model system for these applications, phenotypically wild-type cortical astrocytes and neural stem cells (NSC) from conditional, genetically engineered mice (GEM) that harbor various combinations of floxed oncogenic alleles were harvested and grown in culture. Genetic recombination was induced in vitro using adenoviral Cre-mediated recombination, resulting in expression of mutated oncogenes and deletion of tumor suppressor genes. The phenotypic consequences of these mutations were defined by measuring proliferation, transformation, and drug response in vitro. Orthotopic allograft models, whereby transformed cells are stereotactically injected into the brains of immune-competent, syngeneic littermates, were developed to define the role of oncogenic mutations and cell type on tumorigenesis in vivo. Unlike most established human glioblastoma cell line xenografts, injection of transformed GEM-derived cortical astrocytes into the brains of immune-competent littermates produced astrocytomas, including the most aggressive subtype, glioblastoma, that recapitulated the histopathological hallmarks of human astrocytomas, including diffuse invasion of normal brain parenchyma. Bioluminescence imaging of orthotopic allografts from transformed astrocytes engineered to express luciferase was utilized to monitor in vivo tumor growth over time. Thus, astrocytoma models using astrocytes and NSC harvested from GEM with conditional oncogenic alleles provide an integrated system to study the genetics and cell biology of astrocytoma pathogenesis in vitro and in vivo and may be useful in preclinical drug development for these devastating diseases.
Neuroscience, Issue 90, astrocytoma, cortical astrocytes, genetically engineered mice, glioblastoma, neural stem cells, orthotopic allograft
51763
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Ischemic Tissue Injury in the Dorsal Skinfold Chamber of the Mouse: A Skin Flap Model to Investigate Acute Persistent Ischemia
Authors: Yves Harder, Daniel Schmauss, Reto Wettstein, José T. Egaña, Fabian Weiss, Andrea Weinzierl, Anna Schuldt, Hans-Günther Machens, Michael D. Menger, Farid Rezaeian.
Institutions: Technische Universität München, University Hospital of Basel, University of Saarland, University Hospital Zurich.
Despite profound expertise and advanced surgical techniques, ischemia-induced complications ranging from wound breakdown to extensive tissue necrosis are still occurring, particularly in reconstructive flap surgery. Multiple experimental flap models have been developed to analyze underlying causes and mechanisms and to investigate treatment strategies to prevent ischemic complications. The limiting factor of most models is the lacking possibility to directly and repetitively visualize microvascular architecture and hemodynamics. The goal of the protocol was to present a well-established mouse model affiliating these before mentioned lacking elements. Harder et al. have developed a model of a musculocutaneous flap with a random perfusion pattern that undergoes acute persistent ischemia and results in ~50% necrosis after 10 days if kept untreated. With the aid of intravital epi-fluorescence microscopy, this chamber model allows repetitive visualization of morphology and hemodynamics in different regions of interest over time. Associated processes such as apoptosis, inflammation, microvascular leakage and angiogenesis can be investigated and correlated to immunohistochemical and molecular protein assays. To date, the model has proven feasibility and reproducibility in several published experimental studies investigating the effect of pre-, peri- and postconditioning of ischemically challenged tissue.
Medicine, Issue 93, flap, ischemia, microcirculation, angiogenesis, skin, necrosis, inflammation, apoptosis, preconditioning, persistent ischemia, in vivo model, muscle.
51900
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Purifying the Impure: Sequencing Metagenomes and Metatranscriptomes from Complex Animal-associated Samples
Authors: Yan Wei Lim, Matthew Haynes, Mike Furlan, Charles E. Robertson, J. Kirk Harris, Forest Rohwer.
Institutions: San Diego State University, DOE Joint Genome Institute, University of Colorado, University of Colorado.
The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and microbial communities, a comprehensive workflow for DNA and RNA extraction was developed. The workflow concurrently generates viral and microbial metagenomes, as well as metatranscriptomes, from a single sample for next-generation sequencing. The coupling of these approaches provides an overview of both the taxonomical characteristics and the community encoded functions. The presented methods use Cystic Fibrosis (CF) sputum, a problematic sample type, because it is exceptionally viscous and contains high amount of mucins, free neutrophil DNA, and other unknown contaminants. The protocols described here target these problems and successfully recover viral and microbial DNA with minimal human DNA contamination. To complement the metagenomics studies, a metatranscriptomics protocol was optimized to recover both microbial and host mRNA that contains relatively few ribosomal RNA (rRNA) sequences. An overview of the data characteristics is presented to serve as a reference for assessing the success of the methods. Additional CF sputum samples were also collected to (i) evaluate the consistency of the microbiome profiles across seven consecutive days within a single patient, and (ii) compare the consistency of metagenomic approach to a 16S ribosomal RNA gene-based sequencing. The results showed that daily fluctuation of microbial profiles without antibiotic perturbation was minimal and the taxonomy profiles of the common CF-associated bacteria were highly similar between the 16S rDNA libraries and metagenomes generated from the hypotonic lysis (HL)-derived DNA. However, the differences between 16S rDNA taxonomical profiles generated from total DNA and HL-derived DNA suggest that hypotonic lysis and the washing steps benefit in not only removing the human-derived DNA, but also microbial-derived extracellular DNA that may misrepresent the actual microbial profiles.
Molecular Biology, Issue 94, virome, microbiome, metagenomics, metatranscriptomics, cystic fibrosis, mucosal-surface
52117
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Unraveling the Unseen Players in the Ocean - A Field Guide to Water Chemistry and Marine Microbiology
Authors: Andreas Florian Haas, Ben Knowles, Yan Wei Lim, Tracey McDole Somera, Linda Wegley Kelly, Mark Hatay, Forest Rohwer.
Institutions: San Diego State University, University of California San Diego.
Here we introduce a series of thoroughly tested and well standardized research protocols adapted for use in remote marine environments. The sampling protocols include the assessment of resources available to the microbial community (dissolved organic carbon, particulate organic matter, inorganic nutrients), and a comprehensive description of the viral and bacterial communities (via direct viral and microbial counts, enumeration of autofluorescent microbes, and construction of viral and microbial metagenomes). We use a combination of methods, which represent a dispersed field of scientific disciplines comprising already established protocols and some of the most recent techniques developed. Especially metagenomic sequencing techniques used for viral and bacterial community characterization, have been established only in recent years, and are thus still subjected to constant improvement. This has led to a variety of sampling and sample processing procedures currently in use. The set of methods presented here provides an up to date approach to collect and process environmental samples. Parameters addressed with these protocols yield the minimum on information essential to characterize and understand the underlying mechanisms of viral and microbial community dynamics. It gives easy to follow guidelines to conduct comprehensive surveys and discusses critical steps and potential caveats pertinent to each technique.
Environmental Sciences, Issue 93, dissolved organic carbon, particulate organic matter, nutrients, DAPI, SYBR, microbial metagenomics, viral metagenomics, marine environment
52131
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Subcloning Plus Insertion (SPI) - A Novel Recombineering Method for the Rapid Construction of Gene Targeting Vectors
Authors: Thimma R. Reddy, Emma J. Kelsall, Léna M.S. Fevat, Sarah E. Munson, Shaun M. Cowley.
Institutions: University of Leicester, Center for Fisheries, Environment and Aquaculture Sciences, University of Leicester.
Gene targeting refers to the precise modification of a genetic locus using homologous recombination. The generation of novel cell lines and transgenic mouse models using this method necessitates the construction of a ‘targeting’ vector, which contains homologous DNA sequences to the target gene, and has for many years been a limiting step in the process. Vector construction can be performed in vivo in Escherichia coli cells using homologous recombination mediated by phage recombinases using a technique termed recombineering. Recombineering is the preferred technique to subclone the long homology sequences (>4kb) and various targeting elements including selection markers that are required to mediate efficient allelic exchange between a targeting vector and its cognate genomic locus. Typical recombineering protocols follow an iterative scheme of step-wise integration of the targeting elements and require intermediate purification and transformation steps. Here, we present a novel recombineering methodology of vector assembly using a multiplex approach. Plasmid gap repair is performed by the simultaneous capture of genomic sequence from mouse Bacterial Artificial Chromosome libraries and the insertion of dual bacterial and mammalian selection markers. This subcloning plus insertion method is highly efficient and yields a majority of correct recombinants. We present data for the construction of different types of conditional gene knockout, or knock-in, vectors and BAC reporter vectors that have been constructed using this method. SPI vector construction greatly extends the repertoire of the recombineering toolbox and provides a simple, rapid and cost-effective method of constructing these highly complex vectors.
Molecular Biology, Issue 95, recombineering, gap-repair, subcloning plus insertion, transgene, knockout, mouse
52155
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A Technical Perspective in Modern Tree-ring Research - How to Overcome Dendroecological and Wood Anatomical Challenges
Authors: Holger Gärtner, Paolo Cherubini, Patrick Fonti, Georg von Arx, Loïc Schneider, Daniel Nievergelt, Anne Verstege, Alexander Bast, Fritz H. Schweingruber, Ulf Büntgen.
Institutions: Swiss Federal Research Institute WSL.
Dendroecological research uses information stored in tree rings to understand how single trees and even entire forest ecosystems responded to environmental changes and to finally reconstruct such changes. This is done by analyzing growth variations back in time and correlating various plant-specific parameters to (for example) temperature records. Integrating wood anatomical parameters in these analyses would strengthen reconstructions, even down to intra-annual resolution. We therefore present a protocol on how to sample, prepare, and analyze wooden specimen for common macroscopic analyses, but also for subsequent microscopic analyses. Furthermore we introduce a potential solution for analyzing digital images generated from common small and large specimens to support time-series analyses. The protocol presents the basic steps as they currently can be used. Beyond this, there is an ongoing need for the improvement of existing techniques, and development of new techniques, to record and quantify past and ongoing environmental processes. Traditional wood anatomical research needs to be expanded to include ecological information to this field of research. This would support dendro-scientists who intend to analyze new parameters and develop new methodologies to understand the short and long term effects of specific environmental factors on the anatomy of woody plants.
Environmental Sciences, Issue 97, Cell parameters, dendroecology, image analysis, micro sectioning, microtomes, sample preparation, wood anatomy
52337
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Forward Genetics Screens Using Macrophages to Identify Toxoplasma gondii Genes Important for Resistance to IFN-γ-Dependent Cell Autonomous Immunity
Authors: Odaelys Walwyn, Sini Skariah, Brian Lynch, Nathaniel Kim, Yukari Ueda, Neal Vohora, Josh Choe, Dana G. Mordue.
Institutions: New York Medical College.
Toxoplasma gondii, the causative agent of toxoplasmosis, is an obligate intracellular protozoan pathogen. The parasite invades and replicates within virtually any warm blooded vertebrate cell type. During parasite invasion of a host cell, the parasite creates a parasitophorous vacuole (PV) that originates from the host cell membrane independent of phagocytosis within which the parasite replicates. While IFN-dependent-innate and cell mediated immunity is important for eventual control of infection, innate immune cells, including neutrophils, monocytes and dendritic cells, can also serve as vehicles for systemic dissemination of the parasite early in infection. An approach is described that utilizes the host innate immune response, in this case macrophages, in a forward genetic screen to identify parasite mutants with a fitness defect in infected macrophages following activation but normal invasion and replication in naïve macrophages. Thus, the screen isolates parasite mutants that have a specific defect in their ability to resist the effects of macrophage activation. The paper describes two broad phenotypes of mutant parasites following activation of infected macrophages: parasite stasis versus parasite degradation, often in amorphous vacuoles. The parasite mutants are then analyzed to identify the responsible parasite genes specifically important for resistance to induced mediators of cell autonomous immunity. The paper presents a general approach for the forward genetics screen that, in theory, can be modified to target parasite genes important for resistance to specific antimicrobial mediators. It also describes an approach to evaluate the specific macrophage antimicrobial mediators to which the parasite mutant is susceptible. Activation of infected macrophages can also promote parasite differentiation from the tachyzoite to bradyzoite stage that maintains chronic infection. Therefore, methodology is presented to evaluate the importance of the identified parasite gene to establishment of chronic infection.
Immunology, Issue 97, Toxoplasma, macrophages, innate immunity, intracellular pathogen, immune evasion, infectious disease, forward genetics, parasite
52556
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Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Authors: Savannah E. Sanchez, Daniel A. Cuevas, Jason E. Rostron, Tiffany Y. Liang, Cullen G. Pivaroff, Matthew R. Haynes, Jim Nulton, Ben Felts, Barbara A. Bailey, Peter Salamon, Robert A. Edwards, Alex B. Burgin, Anca M. Segall, Forest Rohwer.
Institutions: San Diego State University, San Diego State University, San Diego State University, San Diego State University, San Diego State University, Argonne National Laboratory, Broad Institute.
Current investigations into phage-host interactions are dependent on extrapolating knowledge from (meta)genomes. Interestingly, 60 - 95% of all phage sequences share no homology to current annotated proteins. As a result, a large proportion of phage genes are annotated as hypothetical. This reality heavily affects the annotation of both structural and auxiliary metabolic genes. Here we present phenomic methods designed to capture the physiological response(s) of a selected host during expression of one of these unknown phage genes. Multi-phenotype Assay Plates (MAPs) are used to monitor the diversity of host substrate utilization and subsequent biomass formation, while metabolomics provides bi-product analysis by monitoring metabolite abundance and diversity. Both tools are used simultaneously to provide a phenotypic profile associated with expression of a single putative phage open reading frame (ORF). Representative results for both methods are compared, highlighting the phenotypic profile differences of a host carrying either putative structural or metabolic phage genes. In addition, the visualization techniques and high throughput computational pipelines that facilitated experimental analysis are presented.
Immunology, Issue 100, phenomics, phage, viral metagenome, Multi-phenotype Assay Plates (MAPs), continuous culture, metabolomics
52854
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Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
Authors: Johannes Felix Buyel, Rainer Fischer.
Institutions: RWTH Aachen University, Fraunhofer Gesellschaft.
Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.
Bioengineering, Issue 83, design of experiments (DoE), transient protein expression, plant-derived biopharmaceuticals, promoter, 5'UTR, fluorescent reporter protein, model building, incubation conditions, monoclonal antibody
51216
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Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Authors: Philippe Pérot, Valérie Cheynet, Myriam Decaussin-Petrucci, Guy Oriol, Nathalie Mugnier, Claire Rodriguez-Lafrasse, Alain Ruffion, François Mallet.
Institutions: Joint Unit Hospices de Lyon-bioMérieux, BioMérieux, Hospices Civils de Lyon, Lyon 1 University, BioMérieux, Hospices Civils de Lyon, Hospices Civils de Lyon.
The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values1​​. ‘How to use PSA' remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer2 or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application3,4. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g. PCA3 in prostate cancer5,6 and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer7-10. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1).
Medicine, Issue 81, Cancer Biology, Genetics, Molecular Biology, Prostate, Retroviridae, Biomarkers, Pharmacological, Tumor Markers, Biological, Prostatectomy, Microarray Analysis, Gene Expression, Diagnosis, Human Endogenous Retroviruses, HERV, microarray, Transcriptome, prostate cancer, Affymetrix
50713
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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
2703
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Ex Vivo Infection of Live Tissue with Oncolytic Viruses
Authors: Jean-Simon Diallo, Dominic Roy, Hesham Abdelbary, Naomi De Silva, John C. Bell.
Institutions: Ottawa Hospital Research Institute (OHRI).
Oncolytic Viruses (OVs) are novel therapeutics that selectively replicate in and kill tumor cells1. Several clinical trials evaluating the effectiveness of a variety of oncolytic platforms including HSV, Reovirus, and Vaccinia OVs as treatment for cancer are currently underway2-5. One key characteristic of oncolytic viruses is that they can be genetically modified to express reporter transgenes which makes it possible to visualize the infection of tissues by microscopy or bio-luminescence imaging6,7. This offers a unique advantage since it is possible to infect tissues from patients ex vivo prior to therapy in order to ascertain the likelihood of successful oncolytic virotherapy8. To this end, it is critical to appropriately sample tissue to compensate for tissue heterogeneity and assess tissue viability, particularly prior to infection9. It is also important to follow viral replication using reporter transgenes if expressed by the oncolytic platform as well as by direct titration of tissues following homogenization in order to discriminate between abortive and productive infection. The object of this protocol is to address these issues and herein describes 1. The sampling and preparation of tumor tissue for cell culture 2. The assessment of tissue viability using the metabolic dye alamar blue 3. Ex vivo infection of cultured tissues with vaccinia virus expressing either GFP or firefly luciferase 4. Detection of transgene expression by fluorescence microscopy or using an In Vivo Imaging System (IVIS) 5. Quantification of virus by plaque assay. This comprehensive method presents several advantages including ease of tissue processing, compensation for tissue heterogeneity, control of tissue viability, and discrimination between abortive infection and bone fide viral replication.
Medicine, Issue 52, Cancer, Oncolytic Virus, Tissue culture, Tissue processing, Virus quantification
2854
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In vitro Uncoating of HIV-1 Cores
Authors: Vaibhav B. Shah, Christopher Aiken.
Institutions: Vanderbilt University School of Medicine.
The genome of the retroviruses is encased in a capsid surrounded by a lipid envelope. For lentiviruses, such as HIV-1, the conical capsid shell is composed of CA protein arranged as a lattice of hexagon. The capsid is closed by 7 pentamers at the broad end and 5 at the narrow end of the cone1, 2. Encased in this capsid shell is the viral ribonucleoprotein complex, and together they comprise the core. Following fusion of the viral membrane with the target cell membrane, the HIV-1 is released into the cytoplasm. The capsid then disassembles releasing free CA in the soluble form3 in a process referred to as uncoating. The intracellular location and timing of HIV-1 uncoating are poorly understood. Single amino-acid substitutions in CA that alter the stability of the capsid also impair the ability of HIV-1 to infect cells4. This indicates that the stability of the capsid is critical for HIV-1 infection. HIV-1 uncoating has been difficult to study due to lack of availability of sensitive and reliable assays for this process. Here we describe a quantitative method for studying uncoating in vitro using cores isolated from infectious HIV-1 particles. The approach involves isolation of cores by sedimentation of concentrated virions through a layer of detergent and into a linear sucrose gradient, in the cold. To quantify uncoating, the isolated cores are incubated at 37°C for various timed intervals and subsequently pelleted by ultracentrifugation. The extent of uncoating is analyzed by quantifying the fraction of CA in the supernatant. This approach has been employed to analyze effects of viral mutations on HIV-1 capsid stability4, 5, 6. It should also be useful for studying the role of cellular factors in HIV-1 uncoating.
Immunology, Issue 57, Lentivirus, HIV, virus, infection, capsid, virons, 293T Cells, T Cells
3384
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Measuring Peptide Translocation into Large Unilamellar Vesicles
Authors: Sara A. Spinella, Rachel B. Nelson, Donald E. Elmore.
Institutions: Wellesley College, .
There is an active interest in peptides that readily cross cell membranes without the assistance of cell membrane receptors1. Many of these are referred to as cell-penetrating peptides, which are frequently noted for their potential as drug delivery vectors1-3. Moreover, there is increasing interest in antimicrobial peptides that operate via non-membrane lytic mechanisms4,5, particularly those that cross bacterial membranes without causing cell lysis and kill cells by interfering with intracellular processes6,7. In fact, authors have increasingly pointed out the relationship between cell-penetrating and antimicrobial peptides1,8. A firm understanding of the process of membrane translocation and the relationship between peptide structure and its ability to translocate requires effective, reproducible assays for translocation. Several groups have proposed methods to measure translocation into large unilamellar lipid vesicles (LUVs)9-13. LUVs serve as useful models for bacterial and eukaryotic cell membranes and are frequently used in peptide fluorescent studies14,15. Here, we describe our application of the method first developed by Matsuzaki and co-workers to consider antimicrobial peptides, such as magainin and buforin II16,17. In addition to providing our protocol for this method, we also present a straightforward approach to data analysis that quantifies translocation ability using this assay. The advantages of this translocation assay compared to others are that it has the potential to provide information about the rate of membrane translocation and does not require the addition of a fluorescent label, which can alter peptide properties18, to tryptophan-containing peptides. Briefly, translocation ability into lipid vesicles is measured as a function of the Foster Resonance Energy Transfer (FRET) between native tryptophan residues and dansyl phosphatidylethanolamine when proteins are associated with the external LUV membrane (Figure 1). Cell-penetrating peptides are cleaved as they encounter uninhibited trypsin encapsulated with the LUVs, leading to disassociation from the LUV membrane and a drop in FRET signal. The drop in FRET signal observed for a translocating peptide is significantly greater than that observed for the same peptide when the LUVs contain both trypsin and trypsin inhibitor, or when a peptide that does not spontaneously cross lipid membranes is exposed to trypsin-containing LUVs. This change in fluorescence provides a direct quantification of peptide translocation over time.
Molecular Biology, Issue 59, membrane translocation, vesicle, FRET, peptide, tryptophan
3571
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The ITS2 Database
Authors: Benjamin Merget, Christian Koetschan, Thomas Hackl, Frank Förster, Thomas Dandekar, Tobias Müller, Jörg Schultz, Matthias Wolf.
Institutions: University of Würzburg, University of Würzburg.
The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation2-8. The ITS2 Database9 presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank11 accurately reannotated10. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold12 (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling13. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold. The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST14 search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE15,16 and ProfDistS17 for multiple sequence-structure alignment calculation and Neighbor Joining18 tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure. In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
Genetics, Issue 61, alignment, internal transcribed spacer 2, molecular systematics, secondary structure, ribosomal RNA, phylogenetic tree, homology modeling, phylogeny
3806
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Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
Authors: Wenan Chen, Ashwin Belle, Charles Cockrell, Kevin R. Ward, Kayvan Najarian.
Institutions: Virginia Commonwealth University, Virginia Commonwealth University Reanimation Engineering Science (VCURES) Center, Virginia Commonwealth University, Virginia Commonwealth University, Virginia Commonwealth University.
In this paper we present an automated system based mainly on the computed tomography (CT) images consisting of two main components: the midline shift estimation and intracranial pressure (ICP) pre-screening system. To estimate the midline shift, first an estimation of the ideal midline is performed based on the symmetry of the skull and anatomical features in the brain CT scan. Then, segmentation of the ventricles from the CT scan is performed and used as a guide for the identification of the actual midline through shape matching. These processes mimic the measuring process by physicians and have shown promising results in the evaluation. In the second component, more features are extracted related to ICP, such as the texture information, blood amount from CT scans and other recorded features, such as age, injury severity score to estimate the ICP are also incorporated. Machine learning techniques including feature selection and classification, such as Support Vector Machines (SVMs), are employed to build the prediction model using RapidMiner. The evaluation of the prediction shows potential usefulness of the model. The estimated ideal midline shift and predicted ICP levels may be used as a fast pre-screening step for physicians to make decisions, so as to recommend for or against invasive ICP monitoring.
Medicine, Issue 74, Biomedical Engineering, Molecular Biology, Neurobiology, Biophysics, Physiology, Anatomy, Brain CT Image Processing, CT, Midline Shift, Intracranial Pressure Pre-screening, Gaussian Mixture Model, Shape Matching, Machine Learning, traumatic brain injury, TBI, imaging, clinical techniques
3871
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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
4273
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Determination of the Gas-phase Acidities of Oligopeptides
Authors: Jianhua Ren, Ashish Sawhney, Yuan Tian, Bhupinder Padda, Patrick Batoon.
Institutions: University of the Pacific.
Amino acid residues located at different positions in folded proteins often exhibit different degrees of acidities. For example, a cysteine residue located at or near the N-terminus of a helix is often more acidic than that at or near the C-terminus 1-6. Although extensive experimental studies on the acid-base properties of peptides have been carried out in the condensed phase, in particular in aqueous solutions 6-8, the results are often complicated by solvent effects 7. In fact, most of the active sites in proteins are located near the interior region where solvent effects have been minimized 9,10. In order to understand intrinsic acid-base properties of peptides and proteins, it is important to perform the studies in a solvent-free environment. We present a method to measure the acidities of oligopeptides in the gas-phase. We use a cysteine-containing oligopeptide, Ala3CysNH2 (A3CH), as the model compound. The measurements are based on the well-established extended Cooks kinetic method (Figure 1) 11-16. The experiments are carried out using a triple-quadrupole mass spectrometer interfaced with an electrospray ionization (ESI) ion source (Figure 2). For each peptide sample, several reference acids are selected. The reference acids are structurally similar organic compounds with known gas-phase acidities. A solution of the mixture of the peptide and a reference acid is introduced into the mass spectrometer, and a gas-phase proton-bound anionic cluster of peptide-reference acid is formed. The proton-bound cluster is mass isolated and subsequently fragmented via collision-induced dissociation (CID) experiments. The resulting fragment ion abundances are analyzed using a relationship between the acidities and the cluster ion dissociation kinetics. The gas-phase acidity of the peptide is then obtained by linear regression of the thermo-kinetic plots 17,18. The method can be applied to a variety of molecular systems, including organic compounds, amino acids and their derivatives, oligonucleotides, and oligopeptides. By comparing the gas-phase acidities measured experimentally with those values calculated for different conformers, conformational effects on the acidities can be evaluated.
Chemistry, Issue 76, Biochemistry, Molecular Biology, Oligopeptide, gas-phase acidity, kinetic method, collision-induced dissociation, triple-quadrupole mass spectrometry, oligopeptides, peptides, mass spectrometry, MS
4348
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
4375
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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 (http://www.proteinwisdom.org), 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
50476
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Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues
Authors: R. Wolfgang Rumpf, William C. Ray.
Institutions: The Research Institute at Nationwide Children's Hospital.
Protein alignments are commonly used to evaluate the similarity of protein residues, and the derived consensus sequence used for identifying functional units (e.g., domains). Traditional consensus-building models fail to account for interpositional dependencies – functionally required covariation of residues that tend to appear simultaneously throughout evolution and across the phylogentic tree. These relationships can reveal important clues about the processes of protein folding, thermostability, and the formation of functional sites, which in turn can be used to inform the engineering of synthetic proteins. Unfortunately, these relationships essentially form sub-motifs which cannot be predicted by simple “majority rule” or even HMM-based consensus models, and the result can be a biologically invalid “consensus” which is not only never seen in nature but is less viable than any extant protein. We have developed a visual analytics tool, StickWRLD, which creates an interactive 3D representation of a protein alignment and clearly displays covarying residues. The user has the ability to pan and zoom, as well as dynamically change the statistical threshold underlying the identification of covariants. StickWRLD has previously been successfully used to identify functionally-required covarying residues in proteins such as Adenylate Kinase and in DNA sequences such as endonuclease target sites.
Chemistry, Issue 101, protein engineering, covariation, codependent residues, visualization
52878
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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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