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Pubmed Article
Classification of lung cancer tumors based on structural and physicochemical properties of proteins by bioinformatics models.
PLoS ONE
Rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important in diagnosis of this disease. Furthermore sequence-derived structural and physicochemical descriptors are very useful for machine learning prediction of protein structural and functional classes, classifying proteins and the prediction performance. Herein, in this study is the classification of lung tumors based on 1497 attributes derived from structural and physicochemical properties of protein sequences (based on genes defined by microarray analysis) investigated through a combination of attribute weighting, supervised and unsupervised clustering algorithms. Eighty percent of the weighting methods selected features such as autocorrelation, dipeptide composition and distribution of hydrophobicity as the most important protein attributes in classification of SCLC, NSCLC and COMMON classes of lung tumors. The same results were observed by most tree induction algorithms while descriptors of hydrophobicity distribution were high in protein sequences COMMON in both groups and distribution of charge in these proteins was very low; showing COMMON proteins were very hydrophobic. Furthermore, compositions of polar dipeptide in SCLC proteins were higher than NSCLC proteins. Some clustering models (alone or in combination with attribute weighting algorithms) were able to nearly classify SCLC and NSCLC proteins. Random Forest tree induction algorithm, calculated on leaves one-out and 10-fold cross validation) shows more than 86% accuracy in clustering and predicting three different lung cancer tumors. Here for the first time the application of data mining tools to effectively classify three classes of lung cancer tumors regarding the importance of dipeptide composition, autocorrelation and distribution descriptor has been reported.
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.
22 Related JoVE Articles!
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Improved Visualization of Lung Metastases at Single Cell Resolution in Mice by Combined In-situ Perfusion of Lung Tissue and X-Gal Staining of lacZ-Tagged Tumor Cells
Authors: Matthias J.E. Arlt, Walter Born, Bruno Fuchs.
Institutions: Balgrist University Hospital, Zurich.
Metastasis is the main cause of death in the majority of cancer types and consequently a main focus in cancer research. However, the detection of micrometastases by radiologic imaging and the success in their therapeutic eradication remain limited. While animal models have proven to be invaluable tools for cancer research1, the monitoring/visualization of micrometastases remains a challenge and inaccurate evaluation of metastatic spread in preclinical studies potentially leads to disappointing results in clinical trials2. Consequently, there is great interest in refining the methods to finally allow reproducible and reliable detection of metastases down to the single cell level in normal tissue. The main focus therefore is on techniques, which allow the detection of tumor cells in vivo, like micro-computer tomography (micro-CT), positron emission tomography (PET), bioluminescence or fluorescence imaging3,4. We are currently optimizing these techniques for in vivo monitoring of primary tumor growth and metastasis in different osteosarcoma models. Some of these techniques can also be used for ex vivo analysis of metastasis beside classical methods like qPCR5, FACS6 or different types of histological staining. As a benchmark, we have established in the present study the stable transfection or transduction of tumor cells with the lacZ gene encoding the bacterial enzyme β-galactosidase that metabolizes the chromogenic substrate 5-bromo-4-chloro-3-indolyl-beta-D-galactopyranoside (X-Gal) to an insoluble indigo blue dye7 and allows highly sensitive and selective histochemical blue staining of tumor cells in mouse tissue ex vivo down to the single cell level as shown here. This is a low-cost and not equipment-intensive tool, which allows precise validation of metastasis8 in studies assessing new anticancer therapies9-11. A limiting factor of X-gal staining is the low contrast to e.g. blood-related red staining of well vascularized tissues. In lung tissue this problem can be solved by in-situ lung perfusion, a technique that was recently established by Borsig et al.12 who perfused the lungs of mice under anesthesia to clear them from blood and to fix and embed them in-situ under inflation through the trachea. This method prevents also the collapse of the lung and thereby maintains the morphology of functional lung alveoli, which improves the quality of the tissue for histological analysis. In the present study, we describe a new protocol, which takes advantage of a combination of X-gal staining of lacZ-expressing tumor cells and in-situ perfusion and fixation of lung tissue. This refined protocol allows high-sensitivity detection of single metastatic cells in the lung and enabled us in a recent study to detect "dormant" lung micrometastases in a mouse model13, which was originally described to be non-metastatic14.
Cancer Biology, Issue 66, Medicine, Molecular Biology, Cellular Biology, lung metastasis, lacZ-tagging, 5-Bromo-4-chloro-3-indolyl-beta-D-galactoside (X-Gal) staining, in-situ lung perfusion, metastases, imaging
4162
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Experimental Metastasis and CTL Adoptive Transfer Immunotherapy Mouse Model
Authors: Mary Zimmerman, Xiaolin Hu, Kebin Liu.
Institutions: Medical College of Georgia.
Experimental metastasis mouse model is a simple and yet physiologically relevant metastasis model. The tumor cells are injected intravenously (i.v) into mouse tail veins and colonize in the lungs, thereby, resembling the last steps of tumor cell spontaneous metastasis: survival in the circulation, extravasation and colonization in the distal organs. From a therapeutic point of view, the experimental metastasis model is the simplest and ideal model since the target of therapies is often the end point of metastasis: established metastatic tumor in the distal organ. In this model, tumor cells are injected i.v into mouse tail veins and allowed to colonize and grow in the lungs. Tumor-specific CTLs are then injected i.v into the metastases-bearing mouse. The number and size of the lung metastases can be controlled by the number of tumor cells to be injected and the time of tumor growth. Therefore, various stages of metastasis, from minimal metastasis to extensive metastasis, can be modeled. Lung metastases are analyzed by inflation with ink, thus allowing easier visual observation and quantification.
Immunology, Issue 45, Metastasis, CTL adoptive transfer, Lung, Tumor Immunology
2077
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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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Experimental Metastasis Assay
Authors: Sonali Mohanty, Lei Xu.
Institutions: University of Rochester Medical Center, University of Rochester Medical Center.
Metastasis is the leading cause of death in cancer patients. To understand the mechanism of metastasis, an experimental metastasis assay was established using immunodeficient mice. This article delineates the procedures involved in this assay, including sample preparation, intravenous injection, and culturing cells from lung metastases. Briefly, a pre-determined number of human cancer cells were prepared in vitro and directly injected into the circulation of immunodeficient mice through their tail veins. A small number of cells survive the turbulence in the circulation and grow as metastases in internal organs, such as lung. The injected mice are dissected after a certain period. The tissue distribution of metastases is determined under a dissecting microscope. The number of metastases in a specific tissue is counted and it directly correlates with the metastatic ability of the injected cancer cells. The arisen metastases are isolated and cultured in vitro as cell lines, which often show enhanced metastatic abilities than the parental line when injected again into immunodeficient mice. These highly metastatic derivatives become useful tools for identifying genes or molecular pathways that regulate metastatic progression.
medicine, Issue 42, cancer, metastasis, experimental, mouse, intravenous injection, lung
1942
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Low Molecular Weight Protein Enrichment on Mesoporous Silica Thin Films for Biomarker Discovery
Authors: Jia Fan, James W. Gallagher, Hung-Jen Wu, Matthew G. Landry, Jason Sakamoto, Mauro Ferrari, Ye Hu.
Institutions: The Methodist Hospital Research Institute, National Center for Nanoscience and Technology.
The identification of circulating biomarkers holds great potential for non invasive approaches in early diagnosis and prognosis, as well as for the monitoring of therapeutic efficiency.1-3 The circulating low molecular weight proteome (LMWP) composed of small proteins shed from tissues and cells or peptide fragments derived from the proteolytic degradation of larger proteins, has been associated with the pathological condition in patients and likely reflects the state of disease.4,5 Despite these potential clinical applications, the use of Mass Spectrometry (MS) to profile the LMWP from biological fluids has proven to be very challenging due to the large dynamic range of protein and peptide concentrations in serum.6 Without sample pre-treatment, some of the more highly abundant proteins obscure the detection of low-abundance species in serum/plasma. Current proteomic-based approaches, such as two-dimensional polyacrylamide gel-electrophoresis (2D-PAGE) and shotgun proteomics methods are labor-intensive, low throughput and offer limited suitability for clinical applications.7-9 Therefore, a more effective strategy is needed to isolate LMWP from blood and allow the high throughput screening of clinical samples. Here, we present a fast, efficient and reliable multi-fractionation system based on mesoporous silica chips to specifically target and enrich LMWP.10,11 Mesoporous silica (MPS) thin films with tunable features at the nanoscale were fabricated using the triblock copolymer template pathway. Using different polymer templates and polymer concentrations in the precursor solution, various pore size distributions, pore structures, connectivity and surface properties were determined and applied for selective recovery of low mass proteins. The selective parsing of the enriched peptides into different subclasses according to their physicochemical properties will enhance the efficiency of recovery and detection of low abundance species. In combination with mass spectrometry and statistic analysis, we demonstrated the correlation between the nanophase characteristics of the mesoporous silica thin films and the specificity and efficacy of low mass proteome harvesting. The results presented herein reveal the potential of the nanotechnology-based technology to provide a powerful alternative to conventional methods for LMWP harvesting from complex biological fluids. Because of the ability to tune the material properties, the capability for low-cost production, the simplicity and rapidity of sample collection, and the greatly reduced sample requirements for analysis, this novel nanotechnology will substantially impact the field of proteomic biomarker research and clinical proteomic assessment.
Bioengineering, Issue 62, Nanoporous silica chip, Low molecular weight proteomics, Peptidomics, MALDI-TOF mass spectrometry, early diagnostics, proteomics
3876
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Bioluminescent Bacterial Imaging In Vivo
Authors: Chwanrow K. Baban, Michelle Cronin, Ali R. Akin, Anne O'Brien, Xuefeng Gao, Sabin Tabirca, Kevin P. Francis, Mark Tangney.
Institutions: University College Cork.
This video describes the use of whole body bioluminesce imaging (BLI) for the study of bacterial trafficking in live mice, with an emphasis on the use of bacteria in gene and cell therapy for cancer. Bacteria present an attractive class of vector for cancer therapy, possessing a natural ability to grow preferentially within tumors following systemic administration. Bacteria engineered to express the lux gene cassette permit BLI detection of the bacteria and concurrently tumor sites. The location and levels of bacteria within tumors over time can be readily examined, visualized in two or three dimensions. The method is applicable to a wide range of bacterial species and tumor xenograft types. This article describes the protocol for analysis of bioluminescent bacteria within subcutaneous tumor bearing mice. Visualization of commensal bacteria in the Gastrointestinal tract (GIT) by BLI is also described. This powerful, and cheap, real-time imaging strategy represents an ideal method for the study of bacteria in vivo in the context of cancer research, in particular gene therapy, and infectious disease. This video outlines the procedure for studying lux-tagged E. coli in live mice, demonstrating the spatial and temporal readout achievable utilizing BLI with the IVIS system.
Immunology, Issue 69, Molecular Biology, Cancer Biology, Genetics, Gene Therapy, Cancer, Vector, Lux, Optical Imaging, Luciferase
4318
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An Orthotopic Murine Model of Human Prostate Cancer Metastasis
Authors: Janet Pavese, Irene M. Ogden, Raymond C. Bergan.
Institutions: Northwestern University, Northwestern University, Northwestern University.
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.
Medicine, Issue 79, Urogenital System, Male Urogenital Diseases, Surgical Procedures, Operative, Life Sciences (General), Prostate Cancer, Metastasis, Mouse Model, Drug Discovery, Molecular Biology
50873
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Polymalic Acid-based Nano Biopolymers for Targeting of Multiple Tumor Markers: An Opportunity for Personalized Medicine?
Authors: Julia Y. Ljubimova, Hui Ding, Jose Portilla-Arias, Rameshwar Patil, Pallavi R. Gangalum, Alexandra Chesnokova, Satoshi Inoue, Arthur Rekechenetskiy, Tala Nassoura, Keith L. Black, Eggehard Holler.
Institutions: Cedars-Sinai Medical Center.
Tumors with similar grade and morphology often respond differently to the same treatment because of variations in molecular profiling. To account for this diversity, personalized medicine is developed for silencing malignancy associated genes. Nano drugs fit these needs by targeting tumor and delivering antisense oligonucleotides for silencing of genes. As drugs for the treatment are often administered repeatedly, absence of toxicity and negligible immune response are desirable. In the example presented here, a nano medicine is synthesized from the biodegradable, non-toxic and non-immunogenic platform polymalic acid by controlled chemical ligation of antisense oligonucleotides and tumor targeting molecules. The synthesis and treatment is exemplified for human Her2-positive breast cancer using an experimental mouse model. The case can be translated towards synthesis and treatment of other tumors.
Chemistry, Issue 88, Cancer treatment, personalized medicine, polymalic acid, nanodrug, biopolymer, targeting, host compatibility, biodegradability
50668
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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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Induction of Invasive Transitional Cell Bladder Carcinoma in Immune Intact Human MUC1 Transgenic Mice: A Model for Immunotherapy Development
Authors: Daniel P. Vang, Gregory T. Wurz, Stephen M. Griffey, Chiao-Jung Kao, Audrey M. Gutierrez, Gregory K. Hanson, Michael Wolf, Michael W. DeGregorio.
Institutions: University of California, Davis, University of California, Davis, Merck KGaA, Darmstadt, Germany.
A preclinical model of invasive bladder cancer was developed in human mucin 1 (MUC1) transgenic (MUC1.Tg) mice for the purpose of evaluating immunotherapy and/or cytotoxic chemotherapy. To induce bladder cancer, C57BL/6 mice (MUC1.Tg and wild type) were treated orally with the carcinogen N-butyl-N-(4-hydroxybutyl)nitrosamine (OH-BBN) at 3.0 mg/day, 5 days/week for 12 weeks. To assess the effects of OH-BBN on serum cytokine profile during tumor development, whole blood was collected via submandibular bleeds prior to treatment and every four weeks. In addition, a MUC1-targeted peptide vaccine and placebo were administered to groups of mice weekly for eight weeks. Multiplex fluorometric microbead immunoanalyses of serum cytokines during tumor development and following vaccination were performed. At termination, interferon gamma (IFN-γ)/interleukin-4 (IL-4) ELISpot analysis for MUC1 specific T-cell immune response and histopathological evaluations of tumor type and grade were performed. The results showed that: (1) the incidence of bladder cancer in both MUC1.Tg and wild type mice was 67%; (2) transitional cell carcinomas (TCC) developed at a 2:1 ratio compared to squamous cell carcinomas (SCC); (3) inflammatory cytokines increased with time during tumor development; and (4) administration of the peptide vaccine induces a Th1-polarized serum cytokine profile and a MUC1 specific T-cell response. All tumors in MUC1.Tg mice were positive for MUC1 expression, and half of all tumors in MUC1.Tg and wild type mice were invasive. In conclusion, using a team approach through the coordination of the efforts of pharmacologists, immunologists, pathologists and molecular biologists, we have developed an immune intact transgenic mouse model of bladder cancer that expresses hMUC1.
Medicine, Issue 80, Urinary Bladder, Animals, Genetically Modified, Cancer Vaccines, Immunotherapy, Animal Experimentation, Models, Neoplasms Bladder Cancer, C57BL/6 Mouse, MUC1, Immunotherapy, Preclinical Model
50868
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High Resolution 3D Imaging of Ex-Vivo Biological Samples by Micro CT
Authors: Amnon Sharir, Gregory Ramniceanu, Vlad Brumfeld.
Institutions: Weizmann Institute of Science, Weizmann Institute of Science, Weizmann Institute of Science.
Non-destructive volume visualization can be achieved only by tomographic techniques, of which the most efficient is the x-ray micro computerized tomography (μCT). High resolution μCT is a very versatile yet accurate (1-2 microns of resolution) technique for 3D examination of ex-vivo biological samples1, 2. As opposed to electron tomography, the μCT allows the examination of up to 4 cm thick samples. This technique requires only few hours of measurement as compared to weeks in histology. In addition, μCT does not rely on 2D stereologic models, thus it may complement and in some cases can even replace histological methods3, 4, which are both time consuming and destructive. Sample conditioning and positioning in μCT is straightforward and does not require high vacuum or low temperatures, which may adversely affect the structure. The sample is positioned and rotated 180° or 360°between a microfocused x-ray source and a detector, which includes a scintillator and an accurate CCD camera, For each angle a 2D image is taken, and then the entire volume is reconstructed using one of the different available algorithms5-7. The 3D resolution increases with the decrease of the rotation step. The present video protocol shows the main steps in preparation, immobilization and positioning of the sample followed by imaging at high resolution.
Bioengineering, Issue 52, 3D imaging, tomography, x-ray, non invasive, ex-vivo
2688
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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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Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Authors: Helen H Won, Sasinya N Scott, A. Rose Brannon, Ronak H Shah, Michael F Berger.
Institutions: Memorial Sloan-Kettering Cancer Center, Memorial Sloan-Kettering Cancer Center.
Efforts to detect and investigate key oncogenic mutations have proven valuable to facilitate the appropriate treatment for cancer patients. The establishment of high-throughput, massively parallel "next-generation" sequencing has aided the discovery of many such mutations. To enhance the clinical and translational utility of this technology, platforms must be high-throughput, cost-effective, and compatible with formalin-fixed paraffin embedded (FFPE) tissue samples that may yield small amounts of degraded or damaged DNA. Here, we describe the preparation of barcoded and multiplexed DNA libraries followed by hybridization-based capture of targeted exons for the detection of cancer-associated mutations in fresh frozen and FFPE tumors by massively parallel sequencing. This method enables the identification of sequence mutations, copy number alterations, and select structural rearrangements involving all targeted genes. Targeted exon sequencing offers the benefits of high throughput, low cost, and deep sequence coverage, thus conferring high sensitivity for detecting low frequency mutations.
Molecular Biology, Issue 80, Molecular Diagnostic Techniques, High-Throughput Nucleotide Sequencing, Genetics, Neoplasms, Diagnosis, Massively parallel sequencing, targeted exon sequencing, hybridization capture, cancer, FFPE, DNA mutations
50710
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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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Live Imaging of Drug Responses in the Tumor Microenvironment in Mouse Models of Breast Cancer
Authors: Elizabeth S. Nakasone, Hanne A. Askautrud, Mikala Egeblad.
Institutions: Watson School of Biological Sciences, Cold Spring Harbor Laboratory, University of Oslo and Oslo University Hospital.
The tumor microenvironment plays a pivotal role in tumor initiation, progression, metastasis, and the response to anti-cancer therapies. Three-dimensional co-culture systems are frequently used to explicate tumor-stroma interactions, including their role in drug responses. However, many of the interactions that occur in vivo in the intact microenvironment cannot be completely replicated in these in vitro settings. Thus, direct visualization of these processes in real-time has become an important tool in understanding tumor responses to therapies and identifying the interactions between cancer cells and the stroma that can influence these responses. Here we provide a method for using spinning disk confocal microscopy of live, anesthetized mice to directly observe drug distribution, cancer cell responses and changes in tumor-stroma interactions following administration of systemic therapy in breast cancer models. We describe procedures for labeling different tumor components, treatment of animals for observing therapeutic responses, and the surgical procedure for exposing tumor tissues for imaging up to 40 hours. The results obtained from this protocol are time-lapse movies, in which such processes as drug infiltration, cancer cell death and stromal cell migration can be evaluated using image analysis software.
Cancer Biology, Issue 73, Medicine, Molecular Biology, Cellular Biology, Biomedical Engineering, Genetics, Oncology, Pharmacology, Surgery, Tumor Microenvironment, Intravital imaging, chemotherapy, Breast cancer, time-lapse, mouse models, cancer cell death, stromal cell migration, cancer, imaging, transgenic, animal model
50088
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
50341
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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Authors: Wen-Ting Tsai, Ahmed Hassan, Purbasha Sarkar, Joaquin Correa, Zoltan Metlagel, Danielle M. Jorgens, Manfred Auer.
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
51673
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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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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
50427
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Helical Organization of Blood Coagulation Factor VIII on Lipid Nanotubes
Authors: Jaimy Miller, Daniela Dalm, Alexey Y. Koyfman, Kirill Grushin, Svetla Stoilova-McPhie.
Institutions: University of Texas Medical Branch, University of Texas Medical Branch, University of Texas Medical Branch.
Cryo-electron microscopy (Cryo-EM)1 is a powerful approach to investigate the functional structure of proteins and complexes in a hydrated state and membrane environment2. Coagulation Factor VIII (FVIII)3 is a multi-domain blood plasma glycoprotein. Defect or deficiency of FVIII is the cause for Hemophilia type A - a severe bleeding disorder. Upon proteolytic activation, FVIII binds to the serine protease Factor IXa on the negatively charged platelet membrane, which is critical for normal blood clotting4. Despite the pivotal role FVIII plays in coagulation, structural information for its membrane-bound state is incomplete5. Recombinant FVIII concentrate is the most effective drug against Hemophilia type A and commercially available FVIII can be expressed as human or porcine, both forming functional complexes with human Factor IXa6,7. In this study we present a combination of Cryo-electron microscopy (Cryo-EM), lipid nanotechnology and structure analysis applied to resolve the membrane-bound structure of two highly homologous FVIII forms: human and porcine. The methodology developed in our laboratory to helically organize the two functional recombinant FVIII forms on negatively charged lipid nanotubes (LNT) is described. The representative results demonstrate that our approach is sufficiently sensitive to define the differences in the helical organization between the two highly homologous in sequence (86% sequence identity) proteins. Detailed protocols for the helical organization, Cryo-EM and electron tomography (ET) data acquisition are given. The two-dimensional (2D) and three-dimensional (3D) structure analysis applied to obtain the 3D reconstructions of human and porcine FVIII-LNT is discussed. The presented human and porcine FVIII-LNT structures show the potential of the proposed methodology to calculate the functional, membrane-bound organization of blood coagulation Factor VIII at high resolution.
Bioengineering, Issue 88, Cryo-electron microscopy, Lipid nanotubes, Helical assembly, Membrane-bound organization, Coagulation factor VIII
51254
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Electrophoretic Separation of Proteins
Authors: Bulbul Chakavarti, Deb Chakavarti.
Institutions: Keck Graduate Institute of Applied Life Sciences.
Electrophoresis is used to separate complex mixtures of proteins (e.g., from cells, subcellular fractions, column fractions, or immunoprecipitates), to investigate subunit compositions, and to verify homogeneity of protein samples. It can also serve to purify proteins for use in further applications. In polyacrylamide gel electrophoresis, proteins migrate in response to an electrical field through pores in a polyacrylamide gel matrix; pore size decreases with increasing acrylamide concentration. The combination of pore size and protein charge, size, and shape determines the migration rate of the protein. In this unit, the standard Laemmli method is described for discontinuous gel electrophoresis under denaturing conditions, i.e., in the presence of sodium dodecyl sulfate (SDS).
Basic Protocols, Issue 16, Current Protocols Wiley, Electrophoresis, Biochemistry, Protein Separage, Polyacrylamide Gel Electrophoresis, PAGE
758
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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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