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Pubmed Article
RTK/ERK Pathway under Natural Selection Associated with Prostate Cancer.
PLoS ONE
PUBLISHED: 01-01-2013
Prostate cancer (PCa) is a global disease causing large numbers of deaths every year. Recent studies have indicated the RTK/ERK pathway might be a key pathway in the development of PCa. However, the exact association and evolution-based mechanism remain unclear. This study was conducted by combining genotypic and phenotypic data from the Chinese Consortium for Prostate Cancer Genetics (ChinaPCa) with related databases such as the HapMap Project and Genevar. In this analysis, expression of quantitative trait loci (eQTLs) analysis, natural selection and gene-based pathway analysis were involved. The pathway analysis confirmed the positive relationship between PCa risk and several key genes. In addition, combined with the natural selection, it seems that 4 genes (EGFR, ERBB2, PTK2, and RAF1) with five SNPs (rs11238349, rs17172438, rs984654, rs11773818, and rs17172432) especially rs17172432, might be pivotal factors in the development of PCa. The results indicate that the RTK/ERK pathway under natural selection is a key link in PCa risk. The joint effect of the genes and loci with positive selection might be one reason for the development of PCa. Dealing with all the factors simultaneously might give insight into prevention and aid in predicting the success of potential therapies for PCa.
Authors: Janet Pavese, Irene M. Ogden, Raymond C. Bergan.
Published: 09-18-2013
ABSTRACT
Our laboratory has developed a novel orthotopic implantation model of human prostate cancer (PCa). As PCa death is not due to the primary tumor, but rather the formation of distinct metastasis, the ability to effectively model this progression pre-clinically is of high value. In this model, cells are directly implanted into the ventral lobe of the prostate in Balb/c athymic mice, and allowed to progress for 4-6 weeks. At experiment termination, several distinct endpoints can be measured, such as size and molecular characterization of the primary tumor, the presence and quantification of circulating tumor cells in the blood and bone marrow, and formation of metastasis to the lung. In addition to a variety of endpoints, this model provides a picture of a cells ability to invade and escape the primary organ, enter and survive in the circulatory system, and implant and grow in a secondary site. This model has been used effectively to measure metastatic response to both changes in protein expression as well as to response to small molecule therapeutics, in a short turnaround time.
23 Related JoVE Articles!
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In vitro Method to Observe E-selectin-mediated Interactions Between Prostate Circulating Tumor Cells Derived From Patients and Human Endothelial Cells
Authors: Gunjan Gakhar, Neil H. Bander, David M. Nanus.
Institutions: Weill Cornell Medical College, Weill Cornell Medical College.
Metastasis is a process in which tumor cells shed from the primary tumor intravasate blood vascular and lymphatic system, thereby, gaining access to extravasate and form a secondary niche. The extravasation of tumor cells from the blood vascular system can be studied using endothelial cells (ECs) and tumor cells obtained from different cell lines. Initial studies were conducted using static conditions but it has been well documented that ECs behave differently under physiological flow conditions. Therefore, different flow chamber assemblies are currently being used to studying cancer cell interactions with ECs. Current flow chamber assemblies offer reproducible results using either different cell lines or fluid at different shear stress conditions. However, to observe and study interactions with rare cells such as circulating tumor cells (CTCs), certain changes are required to be made to the conventional flow chamber assembly. CTCs are a rare cell population among millions of blood cells. Consequently, it is difficult to obtain a pure population of CTCs. Contamination of CTCs with different types of cells normally found in the circulation is inevitable using present enrichment or depletion techniques. In the present report, we describe a unique method to fluorescently label circulating prostate cancer cells and study their interactions with ECs in a self-assembled flow chamber system. This technique can be further applied to observe interactions between prostate CTCs and any protein of interest.
Medicine, Issue 87, E-selectin, Metastasis, Microslides, Circulating tumor cells, PSMA, Prostate cancer, rolling velocity, immunostaining, HUVECs, flow chambers
51468
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A Functional Assay for Gap Junctional Examination; Electroporation of Adherent Cells on Indium-Tin Oxide
Authors: Mulu Geletu, Stephanie Guy, Kevin Firth, Leda Raptis.
Institutions: Queen's University, Ask Science Products Inc..
In this technique, cells are cultured on a glass slide that is partly coated with indium-tin oxide (ITO), a transparent, electrically conductive material. A variety of molecules, such as peptides or oligonucleotides can be introduced into essentially 100% of the cells in a non-traumatic manner.  Here, we describe how it can be used to study intercellular, gap junctional communication. Lucifer yellow penetrates into the cells when an electric pulse, applied to the conductive surface on which they are growing, causes pores to form through the cell membrane. This is electroporation. Cells growing on the nonconductive glass surface immediately adjacent to the electroporated region do not take up Lucifer yellow by electroporation but do acquire the fluorescent dye as it is passed to them via gap junctions that link them to the electroporated cells. The results of the transfer of dye from cell to cell can be observed microscopically under fluorescence illumination. This technique allows for precise quantitation of gap junctional communication. In addition, it can be used for the introduction of peptides or other non-permeant molecules, and the transfer of small electroporated peptides via gap junctions to inhibit the signal in the adjacent, non-electroporated cells is a powerful demonstration of signal inhibition.
Molecular Biology, Issue 92, Electroporation, Indium-Tin oxide, signal transduction, gap junctional communication, peptides, Stat3
51710
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Isolation of Cancer Stem Cells From Human Prostate Cancer Samples
Authors: Samuel J. Vidal, S. Aidan Quinn, Janis de la Iglesia-Vicente, Dennis M. Bonal, Veronica Rodriguez-Bravo, Adolfo Firpo-Betancourt, Carlos Cordon-Cardo, Josep Domingo-Domenech.
Institutions: Icahn School of Medicine at Mount Sinai, Memorial Sloan-Kettering Cancer Center.
The cancer stem cell (CSC) model has been considerably revisited over the last two decades. During this time CSCs have been identified and directly isolated from human tissues and serially propagated in immunodeficient mice, typically through antibody labeling of subpopulations of cells and fractionation by flow cytometry. However, the unique clinical features of prostate cancer have considerably limited the study of prostate CSCs from fresh human tumor samples. We recently reported the isolation of prostate CSCs directly from human tissues by virtue of their HLA class I (HLAI)-negative phenotype. Prostate cancer cells are harvested from surgical specimens and mechanically dissociated. A cell suspension is generated and labeled with fluorescently conjugated HLAI and stromal antibodies. Subpopulations of HLAI-negative cells are finally isolated using a flow cytometer. The principal limitation of this protocol is the frequently microscopic and multifocal nature of primary cancer in prostatectomy specimens. Nonetheless, isolated live prostate CSCs are suitable for molecular characterization and functional validation by transplantation in immunodeficient mice.
Medicine, Issue 85, Cancer Stem Cells, Tumor Initiating Cells, Prostate Cancer, HLA class I, Primary Prostate Cancer, Castration Resistant Prostate Cancer, Metastatic Prostate Cancer, Human Tissue Samples, Intratumoral heterogeneity
51332
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Enhancement of Apoptotic and Autophagic Induction by a Novel Synthetic C-1 Analogue of 7-deoxypancratistatin in Human Breast Adenocarcinoma and Neuroblastoma Cells with Tamoxifen
Authors: Dennis Ma, Jonathan Collins, Tomas Hudlicky, Siyaram Pandey.
Institutions: University of Windsor, Brock University.
Breast cancer is one of the most common cancers amongst women in North America. Many current anti-cancer treatments, including ionizing radiation, induce apoptosis via DNA damage. Unfortunately, such treatments are non-selective to cancer cells and produce similar toxicity in normal cells. We have reported selective induction of apoptosis in cancer cells by the natural compound pancratistatin (PST). Recently, a novel PST analogue, a C-1 acetoxymethyl derivative of 7-deoxypancratistatin (JCTH-4), was produced by de novo synthesis and it exhibits comparable selective apoptosis inducing activity in several cancer cell lines. Recently, autophagy has been implicated in malignancies as both pro-survival and pro-death mechanisms in response to chemotherapy. Tamoxifen (TAM) has invariably demonstrated induction of pro-survival autophagy in numerous cancers. In this study, the efficacy of JCTH-4 alone and in combination with TAM to induce cell death in human breast cancer (MCF7) and neuroblastoma (SH-SY5Y) cells was evaluated. TAM alone induced autophagy, but insignificant cell death whereas JCTH-4 alone caused significant induction of apoptosis with some induction of autophagy. Interestingly, the combinatory treatment yielded a drastic increase in apoptotic and autophagic induction. We monitored time-dependent morphological changes in MCF7 cells undergoing TAM-induced autophagy, JCTH-4-induced apoptosis and autophagy, and accelerated cell death with combinatorial treatment using time-lapse microscopy. We have demonstrated these compounds to induce apoptosis/autophagy by mitochondrial targeting in these cancer cells. Importantly, these treatments did not affect the survival of noncancerous human fibroblasts. Thus, these results indicate that JCTH-4 in combination with TAM could be used as a safe and very potent anti-cancer therapy against breast cancer and neuroblastoma cells.
Cancer Biology, Issue 63, Medicine, Biochemistry, Breast adenocarcinoma, neuroblastoma, tamoxifen, combination therapy, apoptosis, autophagy
3586
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Adaptation of Semiautomated Circulating Tumor Cell (CTC) Assays for Clinical and Preclinical Research Applications
Authors: Lori E. Lowes, Benjamin D. Hedley, Michael Keeney, Alison L. Allan.
Institutions: London Health Sciences Centre, Western University, London Health Sciences Centre, Lawson Health Research Institute, Western University.
The majority of cancer-related deaths occur subsequent to the development of metastatic disease. This highly lethal disease stage is associated with the presence of circulating tumor cells (CTCs). These rare cells have been demonstrated to be of clinical significance in metastatic breast, prostate, and colorectal cancers. The current gold standard in clinical CTC detection and enumeration is the FDA-cleared CellSearch system (CSS). This manuscript outlines the standard protocol utilized by this platform as well as two additional adapted protocols that describe the detailed process of user-defined marker optimization for protein characterization of patient CTCs and a comparable protocol for CTC capture in very low volumes of blood, using standard CSS reagents, for studying in vivo preclinical mouse models of metastasis. In addition, differences in CTC quality between healthy donor blood spiked with cells from tissue culture versus patient blood samples are highlighted. Finally, several commonly discrepant items that can lead to CTC misclassification errors are outlined. Taken together, these protocols will provide a useful resource for users of this platform interested in preclinical and clinical research pertaining to metastasis and CTCs.
Medicine, Issue 84, Metastasis, circulating tumor cells (CTCs), CellSearch system, user defined marker characterization, in vivo, preclinical mouse model, clinical research
51248
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Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing (ChIP-seq)
Authors: Sandra Deliard, Jianhua Zhao, Qianghua Xia, Struan F.A. Grant.
Institutions: Children's Hospital of Philadelphia Research Institute, University of Pennsylvania .
ChIP-sequencing (ChIP-seq) methods directly offer whole-genome coverage, where combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing can be utilized to identify the repertoire of mammalian DNA sequences bound by transcription factors in vivo. "Next-generation" genome sequencing technologies provide 1-2 orders of magnitude increase in the amount of sequence that can be cost-effectively generated over older technologies thus allowing for ChIP-seq methods to directly provide whole-genome coverage for effective profiling of mammalian protein-DNA interactions. For successful ChIP-seq approaches, one must generate high quality ChIP DNA template to obtain the best sequencing outcomes. The description is based around experience with the protein product of the gene most strongly implicated in the pathogenesis of type 2 diabetes, namely the transcription factor transcription factor 7-like 2 (TCF7L2). This factor has also been implicated in various cancers. Outlined is how to generate high quality ChIP DNA template derived from the colorectal carcinoma cell line, HCT116, in order to build a high-resolution map through sequencing to determine the genes bound by TCF7L2, giving further insight in to its key role in the pathogenesis of complex traits.
Molecular Biology, Issue 74, Genetics, Biochemistry, Microbiology, Medicine, Proteins, DNA-Binding Proteins, Transcription Factors, Chromatin Immunoprecipitation, Genes, chromatin, immunoprecipitation, ChIP, DNA, PCR, sequencing, antibody, cross-link, cell culture, assay
50286
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Bimolecular Fluorescence Complementation
Authors: Katy A. Wong, John P. O'Bryan.
Institutions: University of Illinois at Chicago.
Defining the subcellular distribution of signaling complexes is imperative to understanding the output from that complex. Conventional methods such as immunoprecipitation do not provide information on the spatial localization of complexes. In contrast, BiFC monitors the interaction and subcellular compartmentalization of protein complexes. In this method, a fluororescent protein is split into amino- and carboxy-terminal non-fluorescent fragments which are then fused to two proteins of interest. Interaction of the proteins results in reconstitution of the fluorophore (Figure 1)1,2. A limitation of BiFC is that once the fragmented fluorophore is reconstituted the complex is irreversible3. This limitation is advantageous in detecting transient or weak interactions, but precludes a kinetic analysis of complex dynamics. An additional caveat is that the reconstituted flourophore requires 30min to mature and fluoresce, again precluding the observation of real time interactions4. BiFC is a specific example of the protein fragment complementation assay (PCA) which employs reporter proteins such as green fluorescent protein variants (BiFC), dihydrofolate reductase, b-lactamase, and luciferase to measure protein:protein interactions5,6. Alternative methods to study protein:protein interactions in cells include fluorescence co-localization and Förster resonance energy transfer (FRET)7. For co-localization, two proteins are individually tagged either directly with a fluorophore or by indirect immunofluorescence. However, this approach leads to high background of non-interacting proteins making it difficult to interpret co-localization data. In addition, due to the limits of resolution of confocal microscopy, two proteins may appear co-localized without necessarily interacting. With BiFC, fluorescence is only observed when the two proteins of interest interact. FRET is another excellent method for studying protein:protein interactions, but can be technically challenging. FRET experiments require the donor and acceptor to be of similar brightness and stoichiometry in the cell. In addition, one must account for bleed through of the donor into the acceptor channel and vice versa. Unlike FRET, BiFC has little background fluorescence, little post processing of image data, does not require high overexpression, and can detect weak or transient interactions. Bioluminescence resonance energy transfer (BRET) is a method similar to FRET except the donor is an enzyme (e.g. luciferase) that catalyzes a substrate to become bioluminescent thereby exciting an acceptor. BRET lacks the technical problems of bleed through and high background fluorescence but lacks the ability to provide spatial information due to the lack of substrate localization to specific compartments8. Overall, BiFC is an excellent method for visualizing subcellular localization of protein complexes to gain insight into compartmentalized signaling.
Cellular Biology, Issue 50, Fluorescence, imaging, compartmentalized signaling, subcellular localization, signal transduction
2643
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Renal Capsule Xenografting and Subcutaneous Pellet Implantation for the Evaluation of Prostate Carcinogenesis and Benign Prostatic Hyperplasia
Authors: Tristan M. Nicholson, Kristen S. Uchtmann, Conrad D. Valdez, Ashleigh B. Theberge, Tihomir Miralem, William A. Ricke.
Institutions: University of Wisconsin-Madison, University of Rochester School of Medicine & Dentistry, University of Wisconsin-Madison.
New therapies for two common prostate diseases, prostate cancer (PrCa) and benign prostatic hyperplasia (BPH), depend critically on experiments evaluating their hormonal regulation. Sex steroid hormones (notably androgens and estrogens) are important in PrCa and BPH; we probe their respective roles in inducing prostate growth and carcinogenesis in mice with experiments using compressed hormone pellets. Hormone and/or drug pellets are easily manufactured with a pellet press, and surgically implanted into the subcutaneous tissue of the male mouse host. We also describe a protocol for the evaluation of hormonal carcinogenesis by combining subcutaneous hormone pellet implantation with xenografting of prostate cell recombinants under the renal capsule of immunocompromised mice. Moreover, subcutaneous hormone pellet implantation, in combination with renal capsule xenografting of BPH tissue, is useful to better understand hormonal regulation of benign prostate growth, and to test new therapies targeting sex steroid hormone pathways.
Medicine, Issue 78, Cancer Biology, Prostatic Hyperplasia, Prostatic Neoplasms, Neoplastic Processes, Estradiol, Testosterone, Transplantation, Heterologous, Growth, Xenotransplantation, Heterologous Transplantation, Hormones, Prostate, Testosterone, 17beta-Estradiol, Benign prostatic hyperplasia, Prostate Cancer, animal model
50574
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Quantification of Orofacial Phenotypes in Xenopus
Authors: Allyson E. Kennedy, Amanda J. Dickinson.
Institutions: Virginia Commonwealth University.
Xenopus has become an important tool for dissecting the mechanisms governing craniofacial development and defects. A method to quantify orofacial development will allow for more rigorous analysis of orofacial phenotypes upon abrogation with substances that can genetically or molecularly manipulate gene expression or protein function. Using two dimensional images of the embryonic heads, traditional size dimensions-such as orofacial width, height and area- are measured. In addition, a roundness measure of the embryonic mouth opening is used to describe the shape of the mouth. Geometric morphometrics of these two dimensional images is also performed to provide a more sophisticated view of changes in the shape of the orofacial region. Landmarks are assigned to specific points in the orofacial region and coordinates are created. A principle component analysis is used to reduce landmark coordinates to principle components that then discriminate the treatment groups. These results are displayed as a scatter plot in which individuals with similar orofacial shapes cluster together. It is also useful to perform a discriminant function analysis, which statistically compares the positions of the landmarks between two treatment groups. This analysis is displayed on a transformation grid where changes in landmark position are viewed as vectors. A grid is superimposed on these vectors so that a warping pattern is displayed to show where significant landmark positions have changed. Shape changes in the discriminant function analysis are based on a statistical measure, and therefore can be evaluated by a p-value. This analysis is simple and accessible, requiring only a stereoscope and freeware software, and thus will be a valuable research and teaching resource.
Developmental Biology, Issue 93, Orofacial quantification, geometric morphometrics, Xenopus, orofacial development, orofacial defects, shape changes, facial dimensions
52062
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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Authors: Alla Gagarinova, Mohan Babu, Jack Greenblatt, Andrew Emili.
Institutions: University of Toronto, University of Toronto, University of Regina.
Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10. Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.
Genetics, Issue 69, Molecular Biology, Medicine, Biochemistry, Microbiology, Aggravating, alleviating, conjugation, double mutant, Escherichia coli, genetic interaction, Gram-negative bacteria, homologous recombination, network, synthetic lethality or sickness, suppression
4056
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Simulating Pancreatic Neuroplasticity: In Vitro Dual-neuron Plasticity Assay
Authors: Ihsan Ekin Demir, Elke Tieftrunk, Karl-Herbert Schäfer, Helmut Friess, Güralp O. Ceyhan.
Institutions: Technische Universität München, University of Applied Sciences Kaiserslautern/Zweibrücken.
Neuroplasticity is an inherent feature of the enteric nervous system and gastrointestinal (GI) innervation under pathological conditions. However, the pathophysiological role of neuroplasticity in GI disorders remains unknown. Novel experimental models which allow simulation and modulation of GI neuroplasticity may enable enhanced appreciation of the contribution of neuroplasticity in particular GI diseases such as pancreatic cancer (PCa) and chronic pancreatitis (CP). Here, we present a protocol for simulation of pancreatic neuroplasticity under in vitro conditions using newborn rat dorsal root ganglia (DRG) and myenteric plexus (MP) neurons. This dual-neuron approach not only permits monitoring of both organ-intrinsic and -extrinsic neuroplasticity, but also represents a valuable tool to assess neuronal and glial morphology and electrophysiology. Moreover, it allows functional modulation of supplied microenvironmental contents for studying their impact on neuroplasticity. Once established, the present neuroplasticity assay bears the potential of being applicable to the study of neuroplasticity in any GI organ.
Medicine, Issue 86, Autonomic Nervous System Diseases, Digestive System Neoplasms, Gastrointestinal Diseases, Pancreatic Diseases, Pancreatic Neoplasms, Pancreatitis, Pancreatic neuroplasticity, dorsal root ganglia, myenteric plexus, Morphometry, neurite density, neurite branching, perikaryonal hypertrophy, neuronal plasticity
51049
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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
51455
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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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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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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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Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
Authors: Vivian P. Chou, Novie Ko, Theodore R. Holman, Amy B. Manning-Boğ.
Institutions: SRI International, University of California-Santa Cruz.
Lipoxygenase (LOX) activity has been implicated in neurodegenerative disorders such as Alzheimer's disease, but its effects in Parkinson's disease (PD) pathogenesis are less understood. Gene-environment interaction models have utility in unmasking the impact of specific cellular pathways in toxicity that may not be observed using a solely genetic or toxicant disease model alone. To evaluate if distinct LOX isozymes selectively contribute to PD-related neurodegeneration, transgenic (i.e. 5-LOX and 12/15-LOX deficient) mice can be challenged with a toxin that mimics cell injury and death in the disorder. Here we describe the use of a neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which produces a nigrostriatal lesion to elucidate the distinct contributions of LOX isozymes to neurodegeneration related to PD. The use of MPTP in mouse, and nonhuman primate, is well-established to recapitulate the nigrostriatal damage in PD. The extent of MPTP-induced lesioning is measured by HPLC analysis of dopamine and its metabolites and semi-quantitative Western blot analysis of striatum for tyrosine hydroxylase (TH), the rate-limiting enzyme for the synthesis of dopamine. To assess inflammatory markers, which may demonstrate LOX isozyme-selective sensitivity, glial fibrillary acidic protein (GFAP) and Iba-1 immunohistochemistry are performed on brain sections containing substantia nigra, and GFAP Western blot analysis is performed on striatal homogenates. This experimental approach can provide novel insights into gene-environment interactions underlying nigrostriatal degeneration and PD.
Medicine, Issue 83, MPTP, dopamine, Iba1, TH, GFAP, lipoxygenase, transgenic, gene-environment interactions, mouse, Parkinson's disease, neurodegeneration, neuroinflammation
50960
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
50319
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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
2534
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Electrophysiological Measurements and Analysis of Nociception in Human Infants
Authors: L. Fabrizi, A. Worley, D. Patten, S. Holdridge, L. Cornelissen, J. Meek, S. Boyd, R. Slater.
Institutions: University College London, Great Ormond Street Hospital, University College Hospital, University of Oxford.
Pain is an unpleasant sensory and emotional experience. Since infants cannot verbally report their experiences, current methods of pain assessment are based on behavioural and physiological body reactions, such as crying, body movements or changes in facial expression. While these measures demonstrate that infants mount a response following noxious stimulation, they are limited: they are based on activation of subcortical somatic and autonomic motor pathways that may not be reliably linked to central sensory processing in the brain. Knowledge of how the central nervous system responds to noxious events could provide an insight to how nociceptive information and pain is processed in newborns. The heel lancing procedure used to extract blood from hospitalised infants offers a unique opportunity to study pain in infancy. In this video we describe how electroencephalography (EEG) and electromyography (EMG) time-locked to this procedure can be used to investigate nociceptive activity in the brain and spinal cord. This integrative approach to the measurement of infant pain has the potential to pave the way for an effective and sensitive clinical measurement tool.
Neuroscience, Issue 58, pain, infant, electrophysiology, human development
3118
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Interview: Glycolipid Antigen Presentation by CD1d and the Therapeutic Potential of NKT cell Activation
Authors: Mitchell Kronenberg.
Institutions: La Jolla Institute for Allergy and Immunology.
Natural Killer T cells (NKT) are critical determinants of the immune response to cancer, regulation of autioimmune disease, clearance of infectious agents, and the development of artheriosclerotic plaques. In this interview, Mitch Kronenberg discusses his laboratory's efforts to understand the mechanism through which NKT cells are activated by glycolipid antigens. Central to these studies is CD1d - the antigen presenting molecule that presents glycolipids to NKT cells. The advent of CD1d tetramer technology, a technique developed by the Kronenberg lab, is critical for the sorting and identification of subsets of specific glycolipid-reactive T cells. Mitch explains how glycolipid agonists are being used as therapeutic agents to activate NKT cells in cancer patients and how CD1d tetramers can be used to assess the state of the NKT cell population in vivo following glycolipid agonist therapy. Current status of ongoing clinical trials using these agonists are discussed as well as Mitch's prediction for areas in the field of immunology that will have emerging importance in the near future.
Immunology, Issue 10, Natural Killer T cells, NKT cells, CD1 Tetramers, antigen presentation, glycolipid antigens, CD1d, Mucosal Immunity, Translational Research
635
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Tomato Analyzer: A Useful Software Application to Collect Accurate and Detailed Morphological and Colorimetric Data from Two-dimensional Objects
Authors: Gustavo R. Rodríguez, Jennifer B. Moyseenko, Matthew D. Robbins, Nancy Huarachi Morejón, David M. Francis, Esther van der Knaap.
Institutions: The Ohio State University.
Measuring fruit morphology and color traits of vegetable and fruit crops in an objective and reproducible way is important for detailed phenotypic analyses of these traits. Tomato Analyzer (TA) is a software program that measures 37 attributes related to two-dimensional shape in a semi-automatic and reproducible manner1,2. Many of these attributes, such as angles at the distal and proximal ends of the fruit and areas of indentation, are difficult to quantify manually. The attributes are organized in ten categories within the software: Basic Measurement, Fruit Shape Index, Blockiness, Homogeneity, Proximal Fruit End Shape, Distal Fruit End Shape, Asymmetry, Internal Eccentricity, Latitudinal Section and Morphometrics. The last category requires neither prior knowledge nor predetermined notions of the shape attributes, so morphometric analysis offers an unbiased option that may be better adapted to high-throughput analyses than attribute analysis. TA also offers the Color Test application that was designed to collect color measurements from scanned images and allow scanning devices to be calibrated using color standards3. TA provides several options to export and analyze shape attribute, morphometric, and color data. The data may be exported to an excel file in batch mode (more than 100 images at one time) or exported as individual images. The user can choose between output that displays the average for each attribute for the objects in each image (including standard deviation), or an output that displays the attribute values for each object on the image. TA has been a valuable and effective tool for indentifying and confirming tomato fruit shape Quantitative Trait Loci (QTL), as well as performing in-depth analyses of the effect of key fruit shape genes on plant morphology. Also, TA can be used to objectively classify fruit into various shape categories. Lastly, fruit shape and color traits in other plant species as well as other plant organs such as leaves and seeds can be evaluated with TA.
Plant Biology, Issue 37, morphology, color, image processing, quantitative trait loci, software
1856
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Enrichment of NK Cells from Human Blood with the RosetteSep Kit from StemCell Technologies
Authors: Christine Beeton, K. George Chandy.
Institutions: University of California, Irvine (UCI).
Natural killer (NK) cells are large granular cytotoxic lymphocytes that belong to the innate immune system and play major roles in fighting against cancer and infections, but are also implicated in the early stages of pregnancy and transplant rejection. These cells are present in peripheral blood, from which they can be isolated. Cells can be isolated using either positive or negative selection. For positive selection we use antibodies directed to a surface marker present only on the cells of interest whereas for negative selection we use cocktails of antibodies targeted to surface markers present on all cells but the cells of interest. This latter technique presents the advantage of leaving the cells of interest free of antibodies, thereby reducing the risk of unwanted cell activation or differenciation. In this video-protocol we demonstrate how to separate NK cells from human blood by negative selection, using the RosetteSep kit from StemCell technologies. The procedure involves obtaining human peripheral blood (under an institutional review board-approved protocol to protect the human subjects) and mixing it with a cocktail of antibodies that will bind to markers absent on NK cells, but present on all other mononuclear cells present in peripheral blood (e.g., T lymphocytes, monocytes...). The antibodies present in the cocktail are conjugated to antibodies directed to glycophorin A on erythrocytes. All unwanted cells and red blood cells will therefore be trapped in complexes. The mix of blood and antibody cocktail is then diluted, overlayed on a Histopaque gradient, and centrifuged. NK cells (>80% pure) can be collected at the interface between the Histopaque and the diluted plasma. Similar cocktails are available for enrichment of other cell populations, such as human T lymphocytes.
Immunology, issue 8, blood, cell isolation, natural killer, lymphocyte, primary cells, negative selection, PBMC, Ficoll gradient, cell separation
326
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
1988
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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