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Pubmed Article
Bagging statistical network inference from large-scale gene expression data.
PLoS ONE
Modern biology and medicine aim at hunting molecular and cellular causes of biological functions and diseases. Gene regulatory networks (GRN) inferred from gene expression data are considered an important aid for this research by providing a map of molecular interactions. Hence, GRNs have the potential enabling and enhancing basic as well as applied research in the life sciences. In this paper, we introduce a new method called BC3NET for inferring causal gene regulatory networks from large-scale gene expression data. BC3NET is an ensemble method that is based on bagging the C3NET algorithm, which means it corresponds to a Bayesian approach with noninformative priors. In this study we demonstrate for a variety of simulated and biological gene expression data from S. cerevisiae that BC3NET is an important enhancement over other inference methods that is capable of capturing biochemical interactions from transcription regulation and protein-protein interaction sensibly. An implementation of BC3NET is freely available as an R package from the CRAN repository.
Authors: Alla Gagarinova, Mohan Babu, Jack Greenblatt, Andrew Emili.
Published: 11-12-2012
ABSTRACT
Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10. Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.
28 Related JoVE Articles!
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Detection of Protein Interactions in Plant using a Gateway Compatible Bimolecular Fluorescence Complementation (BiFC) System
Authors: Gang Tian, Qing Lu, Li Zhang, Susanne E. Kohalmi, Yuhai Cui.
Institutions: University of Western Ontario, Agriculture and Agri-Food Canada.
We have developed a BiFC technique to test the interaction between two proteins in vivo. This is accomplished by splitting a yellow fluorescent protein (YFP) into two non-overlapping fragments. Each fragment is cloned in-frame to a gene of interest. These constructs can then be co-transformed into Nicotiana benthamiana via Agrobacterium mediated transformation, allowing the transit expression of fusion proteins. The reconstitution of YFP signal only occurs when the inquest proteins interact 1-7. To test and validate the protein-protein interactions, BiFC can be used together with yeast two hybrid (Y2H) assay. This may detect indirect interactions which can be overlooked in the Y2H. Gateway technology is a universal platform that enables researchers to shuttle the gene of interest (GOI) into as many expression and functional analysis systems as possible8,9. Both the orientation and reading frame can be maintained without using restriction enzymes or ligation to make expression-ready clones. As a result, one can eliminate all the re-sequencing steps to ensure consistent results throughout the experiments. We have created a series of Gateway compatible BiFC and Y2H vectors which provide researchers with easy-to-use tools to perform both BiFC and Y2H assays10. Here, we demonstrate the ease of using our BiFC system to test protein-protein interactions in N. benthamiana plants.
Plant Biology, Issue 55, protein interaction, Gateway, Bimolecular fluorescence complementation, Confocal microscope, Agrobacterium, Nicotiana benthamiana, Arabidopsis
3473
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
4273
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Cryosectioning Yeast Communities for Examining Fluorescence Patterns
Authors: Babak Momeni, Wenying Shou.
Institutions: Fred Hutchinson Cancer Research Center.
Microbes typically live in communities. The spatial organization of cells within a community is believed to impact the survival and function of the community1. Optical sectioning techniques, including confocal and two-photon microscopy, have proven useful for observing spatial organization of bacterial and archaeal communities2,3. A combination of confocal imaging and physical sectioning of yeast colonies has revealed internal organization of cells4. However, direct optical sectioning using confocal or two-photon microscopy has been only able to reach a few cell layers deep into yeast colonies. This limitation is likely because of strong scattering of light from yeast cells4. Here, we present a method based on fixing and cryosectioning to obtain spatial distribution of fluorescent cells within Saccharomyces cerevisiae communities. We use methanol as the fixative agent to preserve the spatial distribution of cells. Fixed communities are infiltrated with OCT compound, frozen, and cryosectioned in a cryostat. Fluorescence imaging of the sections reveals the internal organization of fluorescent cells within the community. Examples of yeast communities consisting of strains expressing red and green fluorescent proteins demonstrate the potentials of the cryosectioning method to reveal the spatial distribution of fluorescent cells as well as that of gene expression within yeast colonies2,3. Even though our focus has been on Saccharomyces cerevisiae communities, the same method can potentially be applied to examine other microbial communities.
Microbiology, Issue 70, Molecular Biology, Cellular Biology, Basic Protocols, Yeasts, Saccharomyces cerevisiae, Clinical Laboratory Techniques, Cytological Techniques, Environmental Microbiology, Investigative Techniques, Life Sciences, cryosectioning, sectioning, cryotome, fixing, microbial community, yeast colonies, Saccharomyces cerevisiae, community interactions
50101
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A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions
Authors: Mandy Muller, Patricia Cassonnet, Michel Favre, Yves Jacob, Caroline Demeret.
Institutions: Institut Pasteur , Université Sorbonne Paris Cité, Dana Farber Cancer Institute.
Significant efforts were gathered to generate large-scale comprehensive protein-protein interaction network maps. This is instrumental to understand the pathogen-host relationships and was essentially performed by genetic screenings in yeast two-hybrid systems. The recent improvement of protein-protein interaction detection by a Gaussia luciferase-based fragment complementation assay now offers the opportunity to develop integrative comparative interactomic approaches necessary to rigorously compare interaction profiles of proteins from different pathogen strain variants against a common set of cellular factors. This paper specifically focuses on the utility of combining two orthogonal methods to generate protein-protein interaction datasets: yeast two-hybrid (Y2H) and a new assay, high-throughput Gaussia princeps protein complementation assay (HT-GPCA) performed in mammalian cells. A large-scale identification of cellular partners of a pathogen protein is performed by mating-based yeast two-hybrid screenings of cDNA libraries using multiple pathogen strain variants. A subset of interacting partners selected on a high-confidence statistical scoring is further validated in mammalian cells for pair-wise interactions with the whole set of pathogen variants proteins using HT-GPCA. This combination of two complementary methods improves the robustness of the interaction dataset, and allows the performance of a stringent comparative interaction analysis. Such comparative interactomics constitute a reliable and powerful strategy to decipher any pathogen-host interplays.
Immunology, Issue 77, Genetics, Microbiology, Biochemistry, Molecular Biology, Cellular Biology, Biomedical Engineering, Infection, Cancer Biology, Virology, Medicine, Host-Pathogen Interactions, Host-Pathogen Interactions, Protein-protein interaction, High-throughput screening, Luminescence, Yeast two-hybrid, HT-GPCA, Network, protein, yeast, cell, culture
50404
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Manufacturing Of Robust Natural Fiber Preforms Utilizing Bacterial Cellulose as Binder
Authors: Koon-Yang Lee, Siti Rosminah Shamsuddin, Marta Fortea-Verdejo, Alexander Bismarck.
Institutions: University of Vienna, University College London, Imperial College London.
A novel method of manufacturing rigid and robust natural fiber preforms is presented here. This method is based on a papermaking process, whereby loose and short sisal fibers are dispersed into a water suspension containing bacterial cellulose. The fiber and nanocellulose suspension is then filtered (using vacuum or gravity) and the wet filter cake pressed to squeeze out any excess water, followed by a drying step. This will result in the hornification of the bacterial cellulose network, holding the loose natural fibers together. Our method is specially suited for the manufacturing of rigid and robust preforms of hydrophilic fibers. The porous and hydrophilic nature of such fibers results in significant water uptake, drawing in the bacterial cellulose dispersed in the suspension. The bacterial cellulose will then be filtered against the surface of these fibers, forming a bacterial cellulose coating. When the loose fiber-bacterial cellulose suspension is filtered and dried, the adjacent bacterial cellulose forms a network and hornified to hold the otherwise loose fibers together. The introduction of bacterial cellulose into the preform resulted in a significant increase of the mechanical properties of the fiber preforms. This can be attributed to the high stiffness and strength of the bacterial cellulose network. With this preform, renewable high performance hierarchical composites can also be manufactured by using conventional composite production methods, such as resin film infusion (RFI) or resin transfer molding (RTM). Here, we also describe the manufacturing of renewable hierarchical composites using double bag vacuum assisted resin infusion.
Bioengineering, Issue 87, bacterial cellulose, natural fibers, preform, vacuum assisted resin infusion, hierarchical composites, binder
51432
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A Practical Guide to Phylogenetics for Nonexperts
Authors: Damien O'Halloran.
Institutions: The George Washington University.
Many researchers, across incredibly diverse foci, are applying phylogenetics to their research question(s). However, many researchers are new to this topic and so it presents inherent problems. Here we compile a practical introduction to phylogenetics for nonexperts. We outline in a step-by-step manner, a pipeline for generating reliable phylogenies from gene sequence datasets. We begin with a user-guide for similarity search tools via online interfaces as well as local executables. Next, we explore programs for generating multiple sequence alignments followed by protocols for using software to determine best-fit models of evolution. We then outline protocols for reconstructing phylogenetic relationships via maximum likelihood and Bayesian criteria and finally describe tools for visualizing phylogenetic trees. While this is not by any means an exhaustive description of phylogenetic approaches, it does provide the reader with practical starting information on key software applications commonly utilized by phylogeneticists. The vision for this article would be that it could serve as a practical training tool for researchers embarking on phylogenetic studies and also serve as an educational resource that could be incorporated into a classroom or teaching-lab.
Basic Protocol, Issue 84, phylogenetics, multiple sequence alignments, phylogenetic tree, BLAST executables, basic local alignment search tool, Bayesian models
50975
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Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Authors: Adrian K.C. Lee, Eric Larson, Ross K. Maddox.
Institutions: University of Washington.
Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources. Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising the sensor data from environmental and physiological contaminants. We will then outline the procedure for combining and mapping MEG/EEG sensor data onto the cortical space, thereby producing a family of time-series of cortical dipole activation on the brain surface (or "brain movies") related to each experimental condition. Finally, we will highlight a few statistical techniques that enable us to make scientific inference across a subject population (i.e., perform group-level analysis) based on a common cortical coordinate space.
Neuroscience, Issue 68, Magnetoencephalography, MEG, Electroencephalography, EEG, audition, attention, inverse imaging
4262
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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
3358
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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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A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Authors: Bianca DeBenedictis, J. Bruce Morton.
Institutions: University of Western Ontario.
The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional Change Card Sort task, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color. Adjusting behavior in this way exacts a small performance cost, or switch cost, such that responses are typically slower and more error-prone on switch trials in which the sorting rule changes as compared to repeat trials in which the sorting rule remains the same. The ability to flexibly adjust behavior is often said to develop gradually, in part because behavioral costs such as switch costs typically decrease with increasing age. Why aspects of higher-order cognition, such as behavioral flexibility, develop so gradually remains an open question. One hypothesis is that these changes occur in association with functional changes in broad-scale cognitive control networks. On this view, complex mental operations, such as switching, involve rapid interactions between several distributed brain regions, including those that update and maintain task rules, re-orient attention, and select behaviors. With development, functional connections between these regions strengthen, leading to faster and more efficient switching operations. The current video describes a method of testing this hypothesis through the collection and multivariate analysis of fMRI data from participants of different ages.
Behavior, Issue 87, Neurosciences, fMRI, Cognitive Control, Development, Functional Connectivity
51003
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Measurement of Lifespan in Drosophila melanogaster
Authors: Nancy J. Linford, Ceyda Bilgir, Jennifer Ro, Scott D. Pletcher.
Institutions: University of Michigan , University of Michigan .
Aging is a phenomenon that results in steady physiological deterioration in nearly all organisms in which it has been examined, leading to reduced physical performance and increased risk of disease. Individual aging is manifest at the population level as an increase in age-dependent mortality, which is often measured in the laboratory by observing lifespan in large cohorts of age-matched individuals. Experiments that seek to quantify the extent to which genetic or environmental manipulations impact lifespan in simple model organisms have been remarkably successful for understanding the aspects of aging that are conserved across taxa and for inspiring new strategies for extending lifespan and preventing age-associated disease in mammals. The vinegar fly, Drosophila melanogaster, is an attractive model organism for studying the mechanisms of aging due to its relatively short lifespan, convenient husbandry, and facile genetics. However, demographic measures of aging, including age-specific survival and mortality, are extraordinarily susceptible to even minor variations in experimental design and environment, and the maintenance of strict laboratory practices for the duration of aging experiments is required. These considerations, together with the need to practice careful control of genetic background, are essential for generating robust measurements. Indeed, there are many notable controversies surrounding inference from longevity experiments in yeast, worms, flies and mice that have been traced to environmental or genetic artifacts1-4. In this protocol, we describe a set of procedures that have been optimized over many years of measuring longevity in Drosophila using laboratory vials. We also describe the use of the dLife software, which was developed by our laboratory and is available for download (http://sitemaker.umich.edu/pletcherlab/software). dLife accelerates throughput and promotes good practices by incorporating optimal experimental design, simplifying fly handling and data collection, and standardizing data analysis. We will also discuss the many potential pitfalls in the design, collection, and interpretation of lifespan data, and we provide steps to avoid these dangers.
Developmental Biology, Issue 71, Cellular Biology, Molecular Biology, Anatomy, Physiology, Entomology, longevity, lifespan, aging, Drosophila melanogaster, fruit fly, Drosophila, mortality, animal model
50068
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
50319
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Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking
Authors: Evan D. Morris, Su Jin Kim, Jenna M. Sullivan, Shuo Wang, Marc D. Normandin, Cristian C. Constantinescu, Kelly P. Cosgrove.
Institutions: Yale University, Yale University, Yale University, Yale University, Massachusetts General Hospital, University of California, Irvine.
We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized. We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters 1-7. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique 'HYPR' spatial filter 8 that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on 11C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model 7 to a conventional model 9. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.
Behavior, Issue 78, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Medicine, Anatomy, Physiology, Image Processing, Computer-Assisted, Receptors, Dopamine, Dopamine, Functional Neuroimaging, Binding, Competitive, mathematical modeling (systems analysis), Neurotransmission, transient, dopamine release, PET, modeling, linear, time-invariant, smoking, F-test, ventral-striatum, clinical techniques
50358
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High Efficiency Differentiation of Human Pluripotent Stem Cells to Cardiomyocytes and Characterization by Flow Cytometry
Authors: Subarna Bhattacharya, Paul W. Burridge, Erin M. Kropp, Sandra L. Chuppa, Wai-Meng Kwok, Joseph C. Wu, Kenneth R. Boheler, Rebekah L. Gundry.
Institutions: Medical College of Wisconsin, Stanford University School of Medicine, Medical College of Wisconsin, Hong Kong University, Johns Hopkins University School of Medicine, Medical College of Wisconsin.
There is an urgent need to develop approaches for repairing the damaged heart, discovering new therapeutic drugs that do not have toxic effects on the heart, and improving strategies to accurately model heart disease. The potential of exploiting human induced pluripotent stem cell (hiPSC) technology to generate cardiac muscle “in a dish” for these applications continues to generate high enthusiasm. In recent years, the ability to efficiently generate cardiomyogenic cells from human pluripotent stem cells (hPSCs) has greatly improved, offering us new opportunities to model very early stages of human cardiac development not otherwise accessible. In contrast to many previous methods, the cardiomyocyte differentiation protocol described here does not require cell aggregation or the addition of Activin A or BMP4 and robustly generates cultures of cells that are highly positive for cardiac troponin I and T (TNNI3, TNNT2), iroquois-class homeodomain protein IRX-4 (IRX4), myosin regulatory light chain 2, ventricular/cardiac muscle isoform (MLC2v) and myosin regulatory light chain 2, atrial isoform (MLC2a) by day 10 across all human embryonic stem cell (hESC) and hiPSC lines tested to date. Cells can be passaged and maintained for more than 90 days in culture. The strategy is technically simple to implement and cost-effective. Characterization of cardiomyocytes derived from pluripotent cells often includes the analysis of reference markers, both at the mRNA and protein level. For protein analysis, flow cytometry is a powerful analytical tool for assessing quality of cells in culture and determining subpopulation homogeneity. However, technical variation in sample preparation can significantly affect quality of flow cytometry data. Thus, standardization of staining protocols should facilitate comparisons among various differentiation strategies. Accordingly, optimized staining protocols for the analysis of IRX4, MLC2v, MLC2a, TNNI3, and TNNT2 by flow cytometry are described.
Cellular Biology, Issue 91, human induced pluripotent stem cell, flow cytometry, directed differentiation, cardiomyocyte, IRX4, TNNI3, TNNT2, MCL2v, MLC2a
52010
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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
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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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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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Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale
Authors: Valentina Gandin, Kristina Sikström, Tommy Alain, Masahiro Morita, Shannon McLaughlan, Ola Larsson, Ivan Topisirovic.
Institutions: McGill University, Karolinska Institutet, McGill University.
mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. Accordingly, dysregulation of mRNA translation is considered to play a major role in a variety of pathological states including cancer. Ribosomes also host chaperones, which facilitate folding of nascent polypeptides, thereby modulating function and stability of newly synthesized polypeptides. In addition, emerging data indicate that ribosomes serve as a platform for a repertoire of signaling molecules, which are implicated in a variety of post-translational modifications of newly synthesized polypeptides as they emerge from the ribosome, and/or components of translational machinery. Herein, a well-established method of ribosome fractionation using sucrose density gradient centrifugation is described. In conjunction with the in-house developed “anota” algorithm this method allows direct determination of differential translation of individual mRNAs on a genome-wide scale. Moreover, this versatile protocol can be used for a variety of biochemical studies aiming to dissect the function of ribosome-associated protein complexes, including those that play a central role in folding and degradation of newly synthesized polypeptides.
Biochemistry, Issue 87, Cells, Eukaryota, Nutritional and Metabolic Diseases, Neoplasms, Metabolic Phenomena, Cell Physiological Phenomena, mRNA translation, ribosomes, protein synthesis, genome-wide analysis, translatome, mTOR, eIF4E, 4E-BP1
51455
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DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems
Authors: Lara Rajeev, Eric G. Luning, Aindrila Mukhopadhyay.
Institutions: Lawrence Berkeley National Laboratory.
In vivo methods such as ChIP-chip are well-established techniques used to determine global gene targets for transcription factors. However, they are of limited use in exploring bacterial two component regulatory systems with uncharacterized activation conditions. Such systems regulate transcription only when activated in the presence of unique signals. Since these signals are often unknown, the in vitro microarray based method described in this video article can be used to determine gene targets and binding sites for response regulators. This DNA-affinity-purified-chip method may be used for any purified regulator in any organism with a sequenced genome. The protocol involves allowing the purified tagged protein to bind to sheared genomic DNA and then affinity purifying the protein-bound DNA, followed by fluorescent labeling of the DNA and hybridization to a custom tiling array. Preceding steps that may be used to optimize the assay for specific regulators are also described. The peaks generated by the array data analysis are used to predict binding site motifs, which are then experimentally validated. The motif predictions can be further used to determine gene targets of orthologous response regulators in closely related species. We demonstrate the applicability of this method by determining the gene targets and binding site motifs and thus predicting the function for a sigma54-dependent response regulator DVU3023 in the environmental bacterium Desulfovibrio vulgaris Hildenborough.
Genetics, Issue 89, DNA-Affinity-Purified-chip, response regulator, transcription factor binding site, two component system, signal transduction, Desulfovibrio, lactate utilization regulator, ChIP-chip
51715
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Monitoring Cell-autonomous Circadian Clock Rhythms of Gene Expression Using Luciferase Bioluminescence Reporters
Authors: Chidambaram Ramanathan, Sanjoy K. Khan, Nimish D. Kathale, Haiyan Xu, Andrew C. Liu.
Institutions: The University of Memphis.
In mammals, many aspects of behavior and physiology such as sleep-wake cycles and liver metabolism are regulated by endogenous circadian clocks (reviewed1,2). The circadian time-keeping system is a hierarchical multi-oscillator network, with the central clock located in the suprachiasmatic nucleus (SCN) synchronizing and coordinating extra-SCN and peripheral clocks elsewhere1,2. Individual cells are the functional units for generation and maintenance of circadian rhythms3,4, and these oscillators of different tissue types in the organism share a remarkably similar biochemical negative feedback mechanism. However, due to interactions at the neuronal network level in the SCN and through rhythmic, systemic cues at the organismal level, circadian rhythms at the organismal level are not necessarily cell-autonomous5-7. Compared to traditional studies of locomotor activity in vivo and SCN explants ex vivo, cell-based in vitro assays allow for discovery of cell-autonomous circadian defects5,8. Strategically, cell-based models are more experimentally tractable for phenotypic characterization and rapid discovery of basic clock mechanisms5,8-13. Because circadian rhythms are dynamic, longitudinal measurements with high temporal resolution are needed to assess clock function. In recent years, real-time bioluminescence recording using firefly luciferase as a reporter has become a common technique for studying circadian rhythms in mammals14,15, as it allows for examination of the persistence and dynamics of molecular rhythms. To monitor cell-autonomous circadian rhythms of gene expression, luciferase reporters can be introduced into cells via transient transfection13,16,17 or stable transduction5,10,18,19. Here we describe a stable transduction protocol using lentivirus-mediated gene delivery. The lentiviral vector system is superior to traditional methods such as transient transfection and germline transmission because of its efficiency and versatility: it permits efficient delivery and stable integration into the host genome of both dividing and non-dividing cells20. Once a reporter cell line is established, the dynamics of clock function can be examined through bioluminescence recording. We first describe the generation of P(Per2)-dLuc reporter lines, and then present data from this and other circadian reporters. In these assays, 3T3 mouse fibroblasts and U2OS human osteosarcoma cells are used as cellular models. We also discuss various ways of using these clock models in circadian studies. Methods described here can be applied to a great variety of cell types to study the cellular and molecular basis of circadian clocks, and may prove useful in tackling problems in other biological systems.
Genetics, Issue 67, Molecular Biology, Cellular Biology, Chemical Biology, Circadian clock, firefly luciferase, real-time bioluminescence technology, cell-autonomous model, lentiviral vector, RNA interference (RNAi), high-throughput screening (HTS)
4234
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Acquiring Fluorescence Time-lapse Movies of Budding Yeast and Analyzing Single-cell Dynamics using GRAFTS
Authors: Christopher J. Zopf, Narendra Maheshri.
Institutions: Massachusetts Institute of Technology.
Fluorescence time-lapse microscopy has become a powerful tool in the study of many biological processes at the single-cell level. In particular, movies depicting the temporal dependence of gene expression provide insight into the dynamics of its regulation; however, there are many technical challenges to obtaining and analyzing fluorescence movies of single cells. We describe here a simple protocol using a commercially available microfluidic culture device to generate such data, and a MATLAB-based, graphical user interface (GUI) -based software package to quantify the fluorescence images. The software segments and tracks cells, enables the user to visually curate errors in the data, and automatically assigns lineage and division times. The GUI further analyzes the time series to produce whole cell traces as well as their first and second time derivatives. While the software was designed for S. cerevisiae, its modularity and versatility should allow it to serve as a platform for studying other cell types with few modifications.
Microbiology, Issue 77, Cellular Biology, Molecular Biology, Genetics, Biophysics, Saccharomyces cerevisiae, Microscopy, Fluorescence, Cell Biology, microscopy/fluorescence and time-lapse, budding yeast, gene expression dynamics, segmentation, lineage tracking, image tracking, software, yeast, cells, imaging
50456
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Analysis of Nephron Composition and Function in the Adult Zebrafish Kidney
Authors: Kristen K. McCampbell, Kristin N. Springer, Rebecca A. Wingert.
Institutions: University of Notre Dame.
The zebrafish model has emerged as a relevant system to study kidney development, regeneration and disease. Both the embryonic and adult zebrafish kidneys are composed of functional units known as nephrons, which are highly conserved with other vertebrates, including mammals. Research in zebrafish has recently demonstrated that two distinctive phenomena transpire after adult nephrons incur damage: first, there is robust regeneration within existing nephrons that replaces the destroyed tubule epithelial cells; second, entirely new nephrons are produced from renal progenitors in a process known as neonephrogenesis. In contrast, humans and other mammals seem to have only a limited ability for nephron epithelial regeneration. To date, the mechanisms responsible for these kidney regeneration phenomena remain poorly understood. Since adult zebrafish kidneys undergo both nephron epithelial regeneration and neonephrogenesis, they provide an outstanding experimental paradigm to study these events. Further, there is a wide range of genetic and pharmacological tools available in the zebrafish model that can be used to delineate the cellular and molecular mechanisms that regulate renal regeneration. One essential aspect of such research is the evaluation of nephron structure and function. This protocol describes a set of labeling techniques that can be used to gauge renal composition and test nephron functionality in the adult zebrafish kidney. Thus, these methods are widely applicable to the future phenotypic characterization of adult zebrafish kidney injury paradigms, which include but are not limited to, nephrotoxicant exposure regimes or genetic methods of targeted cell death such as the nitroreductase mediated cell ablation technique. Further, these methods could be used to study genetic perturbations in adult kidney formation and could also be applied to assess renal status during chronic disease modeling.
Cellular Biology, Issue 90, zebrafish; kidney; nephron; nephrology; renal; regeneration; proximal tubule; distal tubule; segment; mesonephros; physiology; acute kidney injury (AKI)
51644
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Targeted Expression of GFP in the Hair Follicle Using Ex Vivo Viral Transduction
Authors: Robert M. Hoffman, Lingna Li.
Institutions: AntiCancer, Inc..
There are many cell types in the hair follicle, including hair matrix cells which form the hair shaft and stem cells which can initiate the hair shaft during early anagen, the growth phase of the hair cycle, as well as pluripotent stem cells that play a role in hair follicle growth but have the potential to differentiate to non-follicle cells such as neurons. These properties of the hair follicle are discussed. The various cell types of the hair follicle are potential targets for gene therapy. Gene delivery system for the hair follicle using viral vectors or liposomes for gene targeting to the various cell types in the hair follicle and the results obtained are also discussed.
Cellular Biology, Issue 13, Springer Protocols, hair follicles, liposomes, adenovirus, genes, stem cells
708
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Interview: Protein Folding and Studies of Neurodegenerative Diseases
Authors: Susan Lindquist.
Institutions: MIT - Massachusetts Institute of Technology.
In this interview, Dr. Lindquist describes relationships between protein folding, prion diseases and neurodegenerative disorders. The problem of the protein folding is at the core of the modern biology. In addition to their traditional biochemical functions, proteins can mediate transfer of biological information and therefore can be considered a genetic material. This recently discovered function of proteins has important implications for studies of human disorders. Dr. Lindquist also describes current experimental approaches to investigate the mechanism of neurodegenerative diseases based on genetic studies in model organisms.
Neuroscience, issue 17, protein folding, brain, neuron, prion, neurodegenerative disease, yeast, screen, Translational Research
786
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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
Authors: Viktor Martyanov, Robert H. Gross.
Institutions: Dartmouth College.
SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference1. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data1. In this article, we utilize a web version of SCOPE2 to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs3,4 and has been used in other studies5-8. The three algorithms that comprise SCOPE are BEAM9, which finds non-degenerate motifs (ACCGGT), PRISM10, which finds degenerate motifs (ASCGWT), and SPACER11, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from a file. The output from SCOPE contains a list of all identified motifs with their scores, number of occurrences, fraction of genes containing the motif, and the algorithm used to identify the motif. For each motif, result details include a consensus representation of the motif, a sequence logo, a position weight matrix, and a list of instances for every motif occurrence (with exact positions and "strand" indicated). Results are returned in a browser window and also optionally by email. Previous papers describe the SCOPE algorithms in detail1,2,9-11.
Genetics, Issue 51, gene regulation, computational biology, algorithm, promoter sequence motif
2703
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Laser Microdissection Applied to Gene Expression Profiling of Subset of Cells from the Drosophila Wing Disc
Authors: Rosario Vicidomini, Giuseppe Tortoriello, Maria Furia, Gianluca Polese.
Institutions: University of Naples.
Heterogeneous nature of tissues has proven to be a limiting factor in the amount of information that can be generated from biological samples, compromising downstream analyses. Considering the complex and dynamic cellular associations existing within many tissues, in order to recapitulate the in vivo interactions thorough molecular analysis one must be able to analyze specific cell populations within their native context. Laser-mediated microdissection can achieve this goal, allowing unambiguous identification and successful harvest of cells of interest under direct microscopic visualization while maintaining molecular integrity. We have applied this technology to analyse gene expression within defined areas of the developing Drosophila wing disc, which represents an advantageous model system to study growth control, cell differentiation and organogenesis. Larval imaginal discs are precociously subdivided into anterior and posterior, dorsal and ventral compartments by lineage restriction boundaries. Making use of the inducible GAL4-UAS binary expression system, each of these compartments can be specifically labelled in transgenic flies expressing an UAS-GFP transgene under the control of the appropriate GAL4-driver construct. In the transgenic discs, gene expression profiling of discrete subsets of cells can precisely be determined after laser-mediated microdissection, using the fluorescent GFP signal to guide laser cut. Among the variety of downstream applications, we focused on RNA transcript profiling after localised RNA interference (RNAi). With the advent of RNAi technology, GFP labelling can be coupled with localised knockdown of a given gene, allowing to determinate the transcriptional response of a discrete cell population to the specific gene silencing. To validate this approach, we dissected equivalent areas of the disc from the posterior (labelled by GFP expression), and the anterior (unlabelled) compartment upon regional silencing in the P compartment of an otherwise ubiquitously expressed gene. RNA was extracted from microdissected silenced and unsilenced areas and comparative gene expression profiling determined by quantitative real-time RT-PCR. We show that this method can effectively be applied for accurate transcriptomics of subsets of cells within the Drosophila imaginal discs. Indeed, while massive disc preparation as source of RNA generally assumes cell homogeneity, it is well known that transcriptional expression can vary greatly within these structures in consequence of positional information. Using localized fluorescent GFP signal to guide laser cut, more accurate transcriptional analyses can be performed and profitably applied to disparate applications, including transcript profiling of distinct cell lineages within their native context.
Developmental Biology, Issue 38, Drosophila, Imaginal discs, Laser microdissection, Gene expression, Transcription profiling, Regulatory pathways , in vivo RNAi, GAL4-UAS, GFP labelling, Positional information
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Principles of Site-Specific Recombinase (SSR) Technology
Authors: Frank Bucholtz.
Institutions: Max Plank Institute for Molecular Cell Biology and Genetics, Dresden.
Site-specific recombinase (SSR) technology allows the manipulation of gene structure to explore gene function and has become an integral tool of molecular biology. Site-specific recombinases are proteins that bind to distinct DNA target sequences. The Cre/lox system was first described in bacteriophages during the 1980's. Cre recombinase is a Type I topoisomerase that catalyzes site-specific recombination of DNA between two loxP (locus of X-over P1) sites. The Cre/lox system does not require any cofactors. LoxP sequences contain distinct binding sites for Cre recombinases that surround a directional core sequence where recombination and rearrangement takes place. When cells contain loxP sites and express the Cre recombinase, a recombination event occurs. Double-stranded DNA is cut at both loxP sites by the Cre recombinase, rearranged, and ligated ("scissors and glue"). Products of the recombination event depend on the relative orientation of the asymmetric sequences. SSR technology is frequently used as a tool to explore gene function. Here the gene of interest is flanked with Cre target sites loxP ("floxed"). Animals are then crossed with animals expressing the Cre recombinase under the control of a tissue-specific promoter. In tissues that express the Cre recombinase it binds to target sequences and excises the floxed gene. Controlled gene deletion allows the investigation of gene function in specific tissues and at distinct time points. Analysis of gene function employing SSR technology --- conditional mutagenesis -- has significant advantages over traditional knock-outs where gene deletion is frequently lethal.
Cellular Biology, Issue 15, Molecular Biology, Site-Specific Recombinase, Cre recombinase, Cre/lox system, transgenic animals, transgenic technology
718
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Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells
Authors: Adam M. McCoy, Claudia Litterst, Michelle L. Collins, Luis A. Ugozzoli.
Institutions: Bio-Rad Laboratories.
The use of siRNA mediated gene knockdown is continuing to be an important tool in studies of gene expression. siRNA studies are being conducted not only to study the effects of downregulating single genes, but also to interrogate signaling pathways and other complex interaction networks. These pathway analyses require both the use of relevant cellular models and methods that cause less perturbation to the cellular physiology. Electroporation is increasingly being used as an effective way to introduce siRNA and other nucleic acids into difficult to transfect cell lines and primary cells without altering the signaling pathway under investigation. There are multiple critical steps to a successful siRNA experiment, and there are ways to simplify the work while improving the data quality at several experimental stages. To help you get started with your siRNA mediated gene knockdown project, we will demonstrate how to perform a pathway study complete from collecting and counting the cells prior to electroporation through post transfection real-time PCR gene expression analysis. The following study investigates the role of the transcriptional activator STAT6 in IL-4 dependent gene expression of CCL17 in a Burkitt lymphoma cell line (Namalwa). The techniques demonstrated are useful for a wide range of siRNA-based experiments on both adherent and suspension cells. We will also show how to streamline cell counting with the TC10 automated cell counter, how to electroporate multiple samples simultaneously using the MXcell electroporation system, and how to simultaneously assess RNA quality and quantity with the Experion automated electrophoresis system.
Cellular Biology, Issue 38, Cell Counting, Gene Silencing, siRNA, Namalwa Cells, IL4, Gene Expression, Electroporation, Real Time PCR
1904
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