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Pubmed Article
A semi-automated image analysis procedure for in situ plankton imaging systems.
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PLoS ONE
PUBLISHED: 05-27-2015
Plankton imaging systems are capable of providing fine-scale observations that enhance our understanding of key physical and biological processes. However, processing the large volumes of data collected by imaging systems remains a major obstacle for their employment, and existing approaches are designed either for images acquired under laboratory controlled conditions or within clear waters. In the present study, we developed a semi-automated approach to analyze plankton taxa from images acquired by the ZOOplankton VISualization (ZOOVIS) system within turbid estuarine waters, in Chesapeake Bay. When compared to images under laboratory controlled conditions or clear waters, images from highly turbid waters are often of relatively low quality and more variable, due to the large amount of objects and nonlinear illumination within each image. We first customized a segmentation procedure to locate objects within each image and extracted them for classification. A maximally stable extremal regions algorithm was applied to segment large gelatinous zooplankton and an adaptive threshold approach was developed to segment small organisms, such as copepods. Unlike the existing approaches for images acquired from laboratory, controlled conditions or clear waters, the target objects are often the majority class, and the classification can be treated as a multi-class classification problem. We customized a two-level hierarchical classification procedure using support vector machines to classify the target objects (< 5%), and remove the non-target objects (> 95%). First, histograms of oriented gradients feature descriptors were constructed for the segmented objects. In the first step all non-target and target objects were classified into different groups: arrow-like, copepod-like, and gelatinous zooplankton. Each object was passed to a group-specific classifier to remove most non-target objects. After the object was classified, an expert or non-expert then manually removed the non-target objects that could not be removed by the procedure. The procedure was tested on 89,419 images collected in Chesapeake Bay, and results were consistent with visual counts with >80% accuracy for all three groups.
Authors: Gustavo R. Rodríguez, Jennifer B. Moyseenko, Matthew D. Robbins, Nancy Huarachi Morejón, David M. Francis, Esther van der Knaap.
Published: 03-16-2010
ABSTRACT
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.
26 Related JoVE Articles!
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High-throughput Image Analysis of Tumor Spheroids: A User-friendly Software Application to Measure the Size of Spheroids Automatically and Accurately
Authors: Wenjin Chen, Chung Wong, Evan Vosburgh, Arnold J. Levine, David J. Foran, Eugenia Y. Xu.
Institutions: Raymond and Beverly Sackler Foundation, New Jersey, Rutgers University, Rutgers University, Institute for Advanced Study, New Jersey.
The increasing number of applications of three-dimensional (3D) tumor spheroids as an in vitro model for drug discovery requires their adaptation to large-scale screening formats in every step of a drug screen, including large-scale image analysis. Currently there is no ready-to-use and free image analysis software to meet this large-scale format. Most existing methods involve manually drawing the length and width of the imaged 3D spheroids, which is a tedious and time-consuming process. This study presents a high-throughput image analysis software application – SpheroidSizer, which measures the major and minor axial length of the imaged 3D tumor spheroids automatically and accurately; calculates the volume of each individual 3D tumor spheroid; then outputs the results in two different forms in spreadsheets for easy manipulations in the subsequent data analysis. The main advantage of this software is its powerful image analysis application that is adapted for large numbers of images. It provides high-throughput computation and quality-control workflow. The estimated time to process 1,000 images is about 15 min on a minimally configured laptop, or around 1 min on a multi-core performance workstation. The graphical user interface (GUI) is also designed for easy quality control, and users can manually override the computer results. The key method used in this software is adapted from the active contour algorithm, also known as Snakes, which is especially suitable for images with uneven illumination and noisy background that often plagues automated imaging processing in high-throughput screens. The complimentary “Manual Initialize” and “Hand Draw” tools provide the flexibility to SpheroidSizer in dealing with various types of spheroids and diverse quality images. This high-throughput image analysis software remarkably reduces labor and speeds up the analysis process. Implementing this software is beneficial for 3D tumor spheroids to become a routine in vitro model for drug screens in industry and academia.
Cancer Biology, Issue 89, computer programming, high-throughput, image analysis, tumor spheroids, 3D, software application, cancer therapy, drug screen, neuroendocrine tumor cell line, BON-1, cancer research
51639
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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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Analysis of Tubular Membrane Networks in Cardiac Myocytes from Atria and Ventricles
Authors: Eva Wagner, Sören Brandenburg, Tobias Kohl, Stephan E. Lehnart.
Institutions: Heart Research Center Goettingen, University Medical Center Goettingen, German Center for Cardiovascular Research (DZHK) partner site Goettingen, University of Maryland School of Medicine.
In cardiac myocytes a complex network of membrane tubules - the transverse-axial tubule system (TATS) - controls deep intracellular signaling functions. While the outer surface membrane and associated TATS membrane components appear to be continuous, there are substantial differences in lipid and protein content. In ventricular myocytes (VMs), certain TATS components are highly abundant contributing to rectilinear tubule networks and regular branching 3D architectures. It is thought that peripheral TATS components propagate action potentials from the cell surface to thousands of remote intracellular sarcoendoplasmic reticulum (SER) membrane contact domains, thereby activating intracellular Ca2+ release units (CRUs). In contrast to VMs, the organization and functional role of TATS membranes in atrial myocytes (AMs) is significantly different and much less understood. Taken together, quantitative structural characterization of TATS membrane networks in healthy and diseased myocytes is an essential prerequisite towards better understanding of functional plasticity and pathophysiological reorganization. Here, we present a strategic combination of protocols for direct quantitative analysis of TATS membrane networks in living VMs and AMs. For this, we accompany primary cell isolations of mouse VMs and/or AMs with critical quality control steps and direct membrane staining protocols for fluorescence imaging of TATS membranes. Using an optimized workflow for confocal or superresolution TATS image processing, binarized and skeletonized data are generated for quantitative analysis of the TATS network and its components. Unlike previously published indirect regional aggregate image analysis strategies, our protocols enable direct characterization of specific components and derive complex physiological properties of TATS membrane networks in living myocytes with high throughput and open access software tools. In summary, the combined protocol strategy can be readily applied for quantitative TATS network studies during physiological myocyte adaptation or disease changes, comparison of different cardiac or skeletal muscle cell types, phenotyping of transgenic models, and pharmacological or therapeutic interventions.
Bioengineering, Issue 92, cardiac myocyte, atria, ventricle, heart, primary cell isolation, fluorescence microscopy, membrane tubule, transverse-axial tubule system, image analysis, image processing, T-tubule, collagenase
51823
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Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
Authors: Simon R. Stockwell, Sibylle Mittnacht.
Institutions: UCL Cancer Institute.
Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators. Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software1 to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.
Cellular Biology, Issue 94, Image analysis, High-content analysis, Screening, Microscopy, Individual cell analysis, Multiplexed assays
51882
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Isolation and Quantitative Immunocytochemical Characterization of Primary Myogenic Cells and Fibroblasts from Human Skeletal Muscle
Authors: Chibeza C. Agley, Anthea M. Rowlerson, Cristiana P. Velloso, Norman L. Lazarus, Stephen D. R. Harridge.
Institutions: King's College London, Cambridge Stem Cell Institute.
The repair and regeneration of skeletal muscle requires the action of satellite cells, which are the resident muscle stem cells. These can be isolated from human muscle biopsy samples using enzymatic digestion and their myogenic properties studied in culture. Quantitatively, the two main adherent cell types obtained from enzymatic digestion are: (i) the satellite cells (termed myogenic cells or muscle precursor cells), identified initially as CD56+ and later as CD56+/desmin+ cells and (ii) muscle-derived fibroblasts, identified as CD56 and TE-7+. Fibroblasts proliferate very efficiently in culture and in mixed cell populations these cells may overrun myogenic cells to dominate the culture. The isolation and purification of different cell types from human muscle is thus an important methodological consideration when trying to investigate the innate behavior of either cell type in culture. Here we describe a system of sorting based on the gentle enzymatic digestion of cells using collagenase and dispase followed by magnetic activated cell sorting (MACS) which gives both a high purity (>95% myogenic cells) and good yield (~2.8 x 106 ± 8.87 x 105 cells/g tissue after 7 days in vitro) for experiments in culture. This approach is based on incubating the mixed muscle-derived cell population with magnetic microbeads beads conjugated to an antibody against CD56 and then passing cells though a magnetic field. CD56+ cells bound to microbeads are retained by the field whereas CD56cells pass unimpeded through the column. Cell suspensions from any stage of the sorting process can be plated and cultured. Following a given intervention, cell morphology, and the expression and localization of proteins including nuclear transcription factors can be quantified using immunofluorescent labeling with specific antibodies and an image processing and analysis package.
Developmental Biology, Issue 95, Stem cell Biology, Tissue Engineering, Stem Cells, Satellite Cells, Skeletal Muscle, Adipocytes, Myogenic Cells, Myoblasts, Fibroblasts, Magnetic Activated Cell Sorting, Image Analysis
52049
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A Manual Small Molecule Screen Approaching High-throughput Using Zebrafish Embryos
Authors: Shahram Jevin Poureetezadi, Eric K. Donahue, Rebecca A. Wingert.
Institutions: University of Notre Dame.
Zebrafish have become a widely used model organism to investigate the mechanisms that underlie developmental biology and to study human disease pathology due to their considerable degree of genetic conservation with humans. Chemical genetics entails testing the effect that small molecules have on a biological process and is becoming a popular translational research method to identify therapeutic compounds. Zebrafish are specifically appealing to use for chemical genetics because of their ability to produce large clutches of transparent embryos, which are externally fertilized. Furthermore, zebrafish embryos can be easily drug treated by the simple addition of a compound to the embryo media. Using whole-mount in situ hybridization (WISH), mRNA expression can be clearly visualized within zebrafish embryos. Together, using chemical genetics and WISH, the zebrafish becomes a potent whole organism context in which to determine the cellular and physiological effects of small molecules. Innovative advances have been made in technologies that utilize machine-based screening procedures, however for many labs such options are not accessible or remain cost-prohibitive. The protocol described here explains how to execute a manual high-throughput chemical genetic screen that requires basic resources and can be accomplished by a single individual or small team in an efficient period of time. Thus, this protocol provides a feasible strategy that can be implemented by research groups to perform chemical genetics in zebrafish, which can be useful for gaining fundamental insights into developmental processes, disease mechanisms, and to identify novel compounds and signaling pathways that have medically relevant applications.
Developmental Biology, Issue 93, zebrafish, chemical genetics, chemical screen, in vivo small molecule screen, drug discovery, whole mount in situ hybridization (WISH), high-throughput screening (HTS), high-content screening (HCS)
52063
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Flying Insect Detection and Classification with Inexpensive Sensors
Authors: Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, Eamonn Keogh.
Institutions: University of California, Riverside, University of California, Riverside, University of São Paulo - USP, ISCA Technologies.
An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.
Bioengineering, Issue 92, flying insect detection, automatic insect classification, pseudo-acoustic optical sensors, Bayesian classification framework, flight sound, circadian rhythm
52111
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Detection and Analysis of DNA Damage in Mouse Skeletal Muscle In Situ Using the TUNEL Method
Authors: Saniya Fayzullina, Lee J. Martin.
Institutions: Johns Hopkins School of Medicine.
Terminal deoxynucleotidyl transferase (TdT) deoxyuridine triphosphate (dUTP) nick end labeling (TUNEL) is the method of using the TdT enzyme to covalently attach a tagged form of dUTP to 3’ ends of double- and single-stranded DNA breaks in cells. It is a reliable and useful method to detect DNA damage and cell death in situ. This video describes dissection, tissue processing, sectioning, and fluorescence-based TUNEL labeling of mouse skeletal muscle. It also describes a method of semi-automated TUNEL signal quantitation. Inherent normal tissue features and tissue processing conditions affect the ability of the TdT enzyme to efficiently label DNA. Tissue processing may also add undesirable autofluorescence that will interfere with TUNEL signal detection. Therefore, it is important to empirically determine tissue processing and TUNEL labeling methods that will yield the optimal signal-to-noise ratio for subsequent quantitation. The fluorescence-based assay described here provides a way to exclude autofluorescent signal by digital channel subtraction. The TUNEL assay, used with appropriate tissue processing techniques and controls, is a relatively fast, reproducible, quantitative method for detecting apoptosis in tissue. It can be used to confirm DNA damage and apoptosis as pathological mechanisms, to identify affected cell types, and to assess the efficacy of therapeutic treatments in vivo.
Physiology, Issue 94, TUNEL, fluorescence, skeletal muscle, DNA damage, image analysis, histology, SMA, motor neuron disease
52211
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Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images
Authors: Aliya Gifford, Theodore F. Towse, Ronald C. Walker, Malcolm J. Avison, E. Brian Welch.
Institutions: Vanderbilt University, Vanderbilt University School of Medicine, Vanderbilt University Medical Center, Vanderbilt University.
Reliably differentiating brown adipose tissue (BAT) from other tissues using a non-invasive imaging method is an important step toward studying BAT in humans. Detecting BAT is typically confirmed by the uptake of the injected radioactive tracer 18F-Fluorodeoxyglucose (18F-FDG) into adipose tissue depots, as measured by positron emission tomography/computed tomography (PET-CT) scans after exposing the subject to cold stimulus. Fat-water separated magnetic resonance imaging (MRI) has the ability to distinguish BAT without the use of a radioactive tracer. To date, MRI of BAT in adult humans has not been co-registered with cold-activated PET-CT. Therefore, this protocol uses 18F-FDG PET-CT scans to automatically generate a BAT mask, which is then applied to co-registered MRI scans of the same subject. This approach enables measurement of quantitative MRI properties of BAT without manual segmentation. BAT masks are created from two PET-CT scans: after exposure for 2 hr to either thermoneutral (TN) (24 °C) or cold-activated (CA) (17 °C) conditions. The TN and CA PET-CT scans are registered, and the PET standardized uptake and CT Hounsfield values are used to create a mask containing only BAT. CA and TN MRI scans are also acquired on the same subject and registered to the PET-CT scans in order to establish quantitative MRI properties within the automatically defined BAT mask. An advantage of this approach is that the segmentation is completely automated and is based on widely accepted methods for identification of activated BAT (PET-CT). The quantitative MRI properties of BAT established using this protocol can serve as the basis for an MRI-only BAT examination that avoids the radiation associated with PET-CT.
Medicine, Issue 96, magnetic resonance imaging, brown adipose tissue, cold-activation, adult human, fat water imaging, fluorodeoxyglucose, positron emission tomography, computed tomography
52415
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Automated Quantification of Hematopoietic Cell – Stromal Cell Interactions in Histological Images of Undecalcified Bone
Authors: Sandra Zehentmeier, Zoltan Cseresnyes, Juan Escribano Navarro, Raluca A. Niesner, Anja E. Hauser.
Institutions: German Rheumatism Research Center, a Leibniz Institute, German Rheumatism Research Center, a Leibniz Institute, Max-Delbrück Center for Molecular Medicine, Wimasis GmbH, Charité - University of Medicine.
Confocal microscopy is the method of choice for the analysis of localization of multiple cell types within complex tissues such as the bone marrow. However, the analysis and quantification of cellular localization is difficult, as in many cases it relies on manual counting, thus bearing the risk of introducing a rater-dependent bias and reducing interrater reliability. Moreover, it is often difficult to judge whether the co-localization between two cells results from random positioning, especially when cell types differ strongly in the frequency of their occurrence. Here, a method for unbiased quantification of cellular co-localization in the bone marrow is introduced. The protocol describes the sample preparation used to obtain histological sections of whole murine long bones including the bone marrow, as well as the staining protocol and the acquisition of high-resolution images. An analysis workflow spanning from the recognition of hematopoietic and non-hematopoietic cell types in 2-dimensional (2D) bone marrow images to the quantification of the direct contacts between those cells is presented. This also includes a neighborhood analysis, to obtain information about the cellular microenvironment surrounding a certain cell type. In order to evaluate whether co-localization of two cell types is the mere result of random cell positioning or reflects preferential associations between the cells, a simulation tool which is suitable for testing this hypothesis in the case of hematopoietic as well as stromal cells, is used. This approach is not limited to the bone marrow, and can be extended to other tissues to permit reproducible, quantitative analysis of histological data.
Developmental Biology, Issue 98, Image analysis, neighborhood analysis, bone marrow, stromal cells, bone marrow niches, simulation, bone cryosectioning, bone histology
52544
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Three-Dimensional (3D) Tumor Spheroid Invasion Assay
Authors: Maria Vinci, Carol Box, Suzanne A. Eccles.
Institutions: The Institute of Cancer Research, The Institute of Cancer Research.
Invasion of surrounding normal tissues is generally considered to be a key hallmark of malignant (as opposed to benign) tumors. For some cancers in particular (e.g., brain tumors such as glioblastoma multiforme and squamous cell carcinoma of the head and neck – SCCHN) it is a cause of severe morbidity and can be life-threatening even in the absence of distant metastases. In addition, cancers which have relapsed following treatment unfortunately often present with a more aggressive phenotype. Therefore, there is an opportunity to target the process of invasion to provide novel therapies that could be complementary to standard anti-proliferative agents. Until now, this strategy has been hampered by the lack of robust, reproducible assays suitable for a detailed analysis of invasion and for drug screening. Here we provide a simple micro-plate method (based on uniform, self-assembling 3D tumor spheroids) which has great potential for such studies. We exemplify the assay platform using a human glioblastoma cell line and also an SCCHN model where the development of resistance against targeted epidermal growth factor receptor (EGFR) inhibitors is associated with enhanced matrix-invasive potential. We also provide two alternative methods of semi-automated quantification: one using an imaging cytometer and a second which simply requires standard microscopy and image capture with digital image analysis.
Medicine, Issue 99, invasion, metastasis, 3D, tumor spheroids, extracellular matrix, imaging, high-throughput, drug development.
52686
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Understanding Early Organogenesis Using a Simplified In Situ Hybridization Protocol in Xenopus
Authors: Steven J. Deimling, Rami R. Halabi, Stephanie A. Grover, Jean H. Wang, Thomas A. Drysdale.
Institutions: Hospital for Sick Children, University of Western Ontario, University of Western Ontario, Hospital for Sick Children, University of Western Ontario.
Organogenesis is the study of how organs are specified and then acquire their specific shape and functions during development. The Xenopuslaevis embryo is very useful for studying organogenesis because their large size makes them very suitable for identifying organs at the earliest steps in organogenesis. At this time, the primary method used for identifying a specific organ or primordium is whole mount in situ hybridization with labeled antisense RNA probes specific to a gene that is expressed in the organ of interest. In addition, it is relatively easy to manipulate genes or signaling pathways in Xenopus and in situ hybridization allows one to then assay for changes in the presence or morphology of a target organ. Whole mount in situ hybridization is a multi-day protocol with many steps involved. Here we provide a simplified protocol with reduced numbers of steps and reagents used that works well for routine assays. In situ hybridization robots have greatly facilitated the process and we detail how and when we utilize that technology in the process. Once an in situ hybridization is complete, capturing the best image of the result can be frustrating. We provide advice on how to optimize imaging of in situ hybridization results. Although the protocol describes assessing organogenesis in Xenopus laevis, the same basic protocol can almost certainly be adapted to Xenopus tropicalis and other model systems.
Developmental Biology, Issue 95, Xenopus, organogenesis, in situ hybridization, RNA methods, embryology, imaging, whole mount
51526
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Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
Authors: Rushin Shojaii, Stephanie Bacopulos, Wenyi Yang, Tigran Karavardanyan, Demetri Spyropoulos, Afshin Raouf, Anne Martel, Arun Seth.
Institutions: University of Toronto, Sunnybrook Research Institute, University of Toronto, Sunnybrook Research Institute, Medical University of South Carolina, University of Manitoba.
Histology volume reconstruction facilitates the study of 3D shape and volume change of an organ at the level of macrostructures made up of cells. It can also be used to investigate and validate novel techniques and algorithms in volumetric medical imaging and therapies. Creating 3D high-resolution atlases of different organs1,2,3 is another application of histology volume reconstruction. This provides a resource for investigating tissue structures and the spatial relationship between various cellular features. We present an image registration approach for histology volume reconstruction, which uses a set of optical blockface images. The reconstructed histology volume represents a reliable shape of the processed specimen with no propagated post-processing registration error. The Hematoxylin and Eosin (H&E) stained sections of two mouse mammary glands were registered to their corresponding blockface images using boundary points extracted from the edges of the specimen in histology and blockface images. The accuracy of the registration was visually evaluated. The alignment of the macrostructures of the mammary glands was also visually assessed at high resolution. This study delineates the different steps of this image registration pipeline, ranging from excision of the mammary gland through to 3D histology volume reconstruction. While 2D histology images reveal the structural differences between pairs of sections, 3D histology volume provides the ability to visualize the differences in shape and volume of the mammary glands.
Bioengineering, Issue 89, Histology Volume Reconstruction, Transgenic Mouse Model, Image Registration, Digital Histology, Image Processing, Mouse Mammary Gland
51325
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Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Authors: Marc N. Coutanche, Sharon L. Thompson-Schill.
Institutions: University of Pennsylvania.
It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain activity, even for conditions with similar levels of univariate activation. Multi-voxel pattern (MVP) analysis has been used to decode this information with great success. FMRI investigators also often seek to understand how brain regions interact in interconnected networks, and use functional connectivity (FC) to identify regions that have correlated responses over time. Just as univariate analyses can be insensitive to information in MVPs, FC may not fully characterize the brain networks that process conditions with characteristic MVP signatures. The method described here, informational connectivity (IC), can identify regions with correlated changes in MVP-discriminability across time, revealing connectivity that is not accessible to FC. The method can be exploratory, using searchlights to identify seed-connected areas, or planned, between pre-selected regions-of-interest. The results can elucidate networks of regions that process MVP-related conditions, can breakdown MVPA searchlight maps into separate networks, or can be compared across tasks and patient groups.
Neuroscience, Issue 89, fMRI, MVPA, connectivity, informational connectivity, functional connectivity, networks, multi-voxel pattern analysis, decoding, classification, method, multivariate
51226
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Quantitatively Measuring In situ Flows using a Self-Contained Underwater Velocimetry Apparatus (SCUVA)
Authors: Kakani Katija, Sean P. Colin, John H. Costello, John O. Dabiri.
Institutions: Woods Hole Oceanographic Institution, Roger Williams University, Whitman Center, Providence College, California Institute of Technology.
The ability to directly measure velocity fields in a fluid environment is necessary to provide empirical data for studies in fields as diverse as oceanography, ecology, biology, and fluid mechanics. Field measurements introduce practical challenges such as environmental conditions, animal availability, and the need for field-compatible measurement techniques. To avoid these challenges, scientists typically use controlled laboratory environments to study animal-fluid interactions. However, it is reasonable to question whether one can extrapolate natural behavior (i.e., that which occurs in the field) from laboratory measurements. Therefore, in situ quantitative flow measurements are needed to accurately describe animal swimming in their natural environment. We designed a self-contained, portable device that operates independent of any connection to the surface, and can provide quantitative measurements of the flow field surrounding an animal. This apparatus, a self-contained underwater velocimetry apparatus (SCUVA), can be operated by a single scuba diver in depths up to 40 m. Due to the added complexity inherent of field conditions, additional considerations and preparation are required when compared to laboratory measurements. These considerations include, but are not limited to, operator motion, predicting position of swimming targets, available natural suspended particulate, and orientation of SCUVA relative to the flow of interest. The following protocol is intended to address these common field challenges and to maximize measurement success.
Bioengineering, Issue 56, In situ DPIV, SCUVA, animal flow measurements, zooplankton, propulsion
2615
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Lensless Fluorescent Microscopy on a Chip
Authors: Ahmet F. Coskun, Ting-Wei Su, Ikbal Sencan, Aydogan Ozcan.
Institutions: University of California, Los Angeles .
On-chip lensless imaging in general aims to replace bulky lens-based optical microscopes with simpler and more compact designs, especially for high-throughput screening applications. This emerging technology platform has the potential to eliminate the need for bulky and/or costly optical components through the help of novel theories and digital reconstruction algorithms. Along the same lines, here we demonstrate an on-chip fluorescent microscopy modality that can achieve e.g., <4μm spatial resolution over an ultra-wide field-of-view (FOV) of >0.6-8 cm2 without the use of any lenses, mechanical-scanning or thin-film based interference filters. In this technique, fluorescent excitation is achieved through a prism or hemispherical-glass interface illuminated by an incoherent source. After interacting with the entire object volume, this excitation light is rejected by total-internal-reflection (TIR) process that is occurring at the bottom of the sample micro-fluidic chip. The fluorescent emission from the excited objects is then collected by a fiber-optic faceplate or a taper and is delivered to an optoelectronic sensor array such as a charge-coupled-device (CCD). By using a compressive-sampling based decoding algorithm, the acquired lensfree raw fluorescent images of the sample can be rapidly processed to yield e.g., <4μm resolution over an FOV of >0.6-8 cm2. Moreover, vertically stacked micro-channels that are separated by e.g., 50-100 μm can also be successfully imaged using the same lensfree on-chip microscopy platform, which further increases the overall throughput of this modality. This compact on-chip fluorescent imaging platform, with a rapid compressive decoder behind it, could be rather valuable for high-throughput cytometry, rare-cell research and microarray-analysis.
Bioengineering, Issue 54, Lensless Microscopy, Fluorescent On-chip Imaging, Wide-field Microscopy, On-Chip Cytometry, Compressive Sampling/Sensing
3181
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Cross-Modal Multivariate Pattern Analysis
Authors: Kaspar Meyer, Jonas T. Kaplan.
Institutions: University of Southern California.
Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5 or, analogously, the content of speech from activity in early auditory cortices6. Here, we present an extension of the classical MVPA paradigm, according to which perceptual stimuli are not predicted within, but across sensory systems. Specifically, the method we describe addresses the question of whether stimuli that evoke memory associations in modalities other than the one through which they are presented induce content-specific activity patterns in the sensory cortices of those other modalities. For instance, seeing a muted video clip of a glass vase shattering on the ground automatically triggers in most observers an auditory image of the associated sound; is the experience of this image in the "mind's ear" correlated with a specific neural activity pattern in early auditory cortices? Furthermore, is this activity pattern distinct from the pattern that could be observed if the subject were, instead, watching a video clip of a howling dog? In two previous studies7,8, we were able to predict sound- and touch-implying video clips based on neural activity in early auditory and somatosensory cortices, respectively. Our results are in line with a neuroarchitectural framework proposed by Damasio9,10, according to which the experience of mental images that are based on memories - such as hearing the shattering sound of a vase in the "mind's ear" upon seeing the corresponding video clip - is supported by the re-construction of content-specific neural activity patterns in early sensory cortices.
Neuroscience, Issue 57, perception, sensory, cross-modal, top-down, mental imagery, fMRI, MRI, neuroimaging, multivariate pattern analysis, MVPA
3307
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Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2. Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings. First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints. Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases. Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms. Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper. We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have. Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
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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
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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Authors: Marcus Cheetham, Lutz Jancke.
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2 proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness (DHL) (Figure 1). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
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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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Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
Authors: Yongsook C. Lee, Gary D. Fullerton, Beth A. Goins.
Institutions: University of Kansas School of Medicine, University of Texas Health Science Center at San Antonio.
World Health Organization (WHO) and the Response Evaluation Criteria in Solid Tumors (RECIST) working groups advocated standardized criteria for radiologic assessment of solid tumors in response to anti-tumor drug therapy in the 1980s and 1990s, respectively. WHO criteria measure solid tumors in two-dimensions, whereas RECIST measurements use only one-dimension which is considered to be more reproducible 1, 2, 3,4,5. These criteria have been widely used as the only imaging biomarker approved by the United States Food and Drug Administration (FDA) 6. In order to measure tumor response to anti-tumor drugs on images with accuracy, therefore, a robust quality assurance (QA) procedures and corresponding QA phantom are needed. To address this need, the authors constructed a preclinical multimodality (for ultrasound (US), computed tomography (CT) and magnetic resonance imaging (MRI)) phantom using tissue-mimicking (TM) materials based on the limited number of target lesions required by RECIST by revising a Gammex US commercial phantom 7. The Appendix in Lee et al. demonstrates the procedures of phantom fabrication 7. In this article, all protocols are introduced in a step-by-step fashion beginning with procedures for preparing the silicone molds for casting tumor-simulating test objects in the phantom, followed by preparation of TM materials for multimodality imaging, and finally construction of the preclinical multimodality QA phantom. The primary purpose of this paper is to provide the protocols to allow anyone interested in independently constructing a phantom for their own projects. QA procedures for tumor size measurement, and RECIST, WHO and volume measurement results of test objects made at multiple institutions using this QA phantom are shown in detail in Lee et al. 8.
Biomedical Engineering, Issue 77, Bioengineering, Medicine, Anatomy, Physiology, Cancer Biology, Molecular Biology, Genetics, Therapeutics, Chemistry and Materials (General), Composite Materials, Quality Assurance and Reliability, Physics (General), Tissue-mimicking materials, Preclinical, Multimodality, Quality assurance, Phantom, Tumor size measurement, Cancer, Imaging
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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
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Preparation of Primary Neurons for Visualizing Neurites in a Frozen-hydrated State Using Cryo-Electron Tomography
Authors: Sarah H. Shahmoradian, Mauricio R. Galiano, Chengbiao Wu, Shurui Chen, Matthew N. Rasband, William C. Mobley, Wah Chiu.
Institutions: Baylor College of Medicine, Baylor College of Medicine, University of California at San Diego, Baylor College of Medicine.
Neurites, both dendrites and axons, are neuronal cellular processes that enable the conduction of electrical impulses between neurons. Defining the structure of neurites is critical to understanding how these processes move materials and signals that support synaptic communication. Electron microscopy (EM) has been traditionally used to assess the ultrastructural features within neurites; however, the exposure to organic solvent during dehydration and resin embedding can distort structures. An important unmet goal is the formulation of procedures that allow for structural evaluations not impacted by such artifacts. Here, we have established a detailed and reproducible protocol for growing and flash-freezing whole neurites of different primary neurons on electron microscopy grids followed by their examination with cryo-electron tomography (cryo-ET). This technique allows for 3-D visualization of frozen, hydrated neurites at nanometer resolution, facilitating assessment of their morphological differences. Our protocol yields an unprecedented view of dorsal root ganglion (DRG) neurites, and a visualization of hippocampal neurites in their near-native state. As such, these methods create a foundation for future studies on neurites of both normal neurons and those impacted by neurological disorders.
Neuroscience, Issue 84, Neurons, Cryo-electron Microscopy, Electron Microscope Tomography, Brain, rat, primary neuron culture, morphological assay
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Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly
Authors: Joel Ramirez, Christopher J.M. Scott, Alicia A. McNeely, Courtney Berezuk, Fuqiang Gao, Gregory M. Szilagyi, Sandra E. Black.
Institutions: Sunnybrook Health Sciences Centre, University of Toronto.
Obtaining in vivo human brain tissue volumetrics from MRI is often complicated by various technical and biological issues. These challenges are exacerbated when significant brain atrophy and age-related white matter changes (e.g. Leukoaraiosis) are present. Lesion Explorer (LE) is an accurate and reliable neuroimaging pipeline specifically developed to address such issues commonly observed on MRI of Alzheimer's disease and normal elderly. The pipeline is a complex set of semi-automatic procedures which has been previously validated in a series of internal and external reliability tests1,2. However, LE's accuracy and reliability is highly dependent on properly trained manual operators to execute commands, identify distinct anatomical landmarks, and manually edit/verify various computer-generated segmentation outputs. LE can be divided into 3 main components, each requiring a set of commands and manual operations: 1) Brain-Sizer, 2) SABRE, and 3) Lesion-Seg. Brain-Sizer's manual operations involve editing of the automatic skull-stripped total intracranial vault (TIV) extraction mask, designation of ventricular cerebrospinal fluid (vCSF), and removal of subtentorial structures. The SABRE component requires checking of image alignment along the anterior and posterior commissure (ACPC) plane, and identification of several anatomical landmarks required for regional parcellation. Finally, the Lesion-Seg component involves manual checking of the automatic lesion segmentation of subcortical hyperintensities (SH) for false positive errors. While on-site training of the LE pipeline is preferable, readily available visual teaching tools with interactive training images are a viable alternative. Developed to ensure a high degree of accuracy and reliability, the following is a step-by-step, video-guided, standardized protocol for LE's manual procedures.
Medicine, Issue 86, Brain, Vascular Diseases, Magnetic Resonance Imaging (MRI), Neuroimaging, Alzheimer Disease, Aging, Neuroanatomy, brain extraction, ventricles, white matter hyperintensities, cerebrovascular disease, Alzheimer disease
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Generation and Multi-phenotypic High-content Screening of Coxiella burnetii Transposon Mutants
Authors: Eric Martinez, Franck Cantet, Matteo Bonazzi.
Institutions: Université Montpellier.
Invasion and colonization of host cells by bacterial pathogens depend on the activity of a large number of prokaryotic proteins, defined as virulence factors, which can subvert and manipulate key host functions. The study of host/pathogen interactions is therefore extremely important to understand bacterial infections and develop alternative strategies to counter infectious diseases. This approach however, requires the development of new high-throughput assays for the unbiased, automated identification and characterization of bacterial virulence determinants. Here, we describe a method for the generation of a GFP-tagged mutant library by transposon mutagenesis and the development of high-content screening approaches for the simultaneous identification of multiple transposon-associated phenotypes. Our working model is the intracellular bacterial pathogen Coxiellaburnetii, the etiological agent of the zoonosis Q fever, which is associated with severe outbreaks with a consequent health and economic burden. The obligate intracellular nature of this pathogen has, until recently, severely hampered the identification of bacterial factors involved in host pathogen interactions, making of Coxiella the ideal model for the implementation of high-throughput/high-content approaches.
Infection, Issue 99, Infection biology, Coxiella burnetii, Vero cells, high-content/high-throughput screening assays, morphological analysis.
52851
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

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.