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Genome-wide pathway association studies of multiple correlated quantitative phenotypes using principle component analyses.
Genome-wide pathway association studies provide novel insight into the biological mechanism underlying complex diseases. Current pathway association studies primarily focus on single important disease phenotype, which is sometimes insufficient to characterize the clinical manifestations of complex diseases. We present a multi-phenotypes pathway association study(MPPAS) approach using principle component analysis(PCA). In our approach, PCA is first applied to multiple correlated quantitative phenotypes for extracting a set of orthogonal phenotypic components. The extracted phenotypic components are then used for pathway association analysis instead of original quantitative phenotypes. Four statistics were proposed for PCA-based MPPAS in this study. Simulations using the real data from the HapMap project were conducted to evaluate the power and type I error rates of PCA-based MPPAS under various scenarios considering sample sizes, additive and interactive genetic effects. A real genome-wide association study data set of bone mineral density (BMD) at hip and spine were also analyzed by PCA-based MPPAS. Simulation studies illustrated the performance of PCA-based MPPAS for identifying the causal pathways underlying complex diseases. Genome-wide MPPAS of BMD detected associations between BMD and KENNY_CTNNB1_TARGETS_UP as well as LONGEVITYPATHWAY pathways in this study. We aim to provide a applicable MPPAS approach, which may help to gain deep understanding the potential biological mechanism of association results for complex diseases.
Authors: Allyson E. Kennedy, Amanda J. Dickinson.
Published: 11-06-2014
Xenopus has become an important tool for dissecting the mechanisms governing craniofacial development and defects. A method to quantify orofacial development will allow for more rigorous analysis of orofacial phenotypes upon abrogation with substances that can genetically or molecularly manipulate gene expression or protein function. Using two dimensional images of the embryonic heads, traditional size dimensions-such as orofacial width, height and area- are measured. In addition, a roundness measure of the embryonic mouth opening is used to describe the shape of the mouth. Geometric morphometrics of these two dimensional images is also performed to provide a more sophisticated view of changes in the shape of the orofacial region. Landmarks are assigned to specific points in the orofacial region and coordinates are created. A principle component analysis is used to reduce landmark coordinates to principle components that then discriminate the treatment groups. These results are displayed as a scatter plot in which individuals with similar orofacial shapes cluster together. It is also useful to perform a discriminant function analysis, which statistically compares the positions of the landmarks between two treatment groups. This analysis is displayed on a transformation grid where changes in landmark position are viewed as vectors. A grid is superimposed on these vectors so that a warping pattern is displayed to show where significant landmark positions have changed. Shape changes in the discriminant function analysis are based on a statistical measure, and therefore can be evaluated by a p-value. This analysis is simple and accessible, requiring only a stereoscope and freeware software, and thus will be a valuable research and teaching resource.
21 Related JoVE Articles!
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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Authors: Hans-Peter Müller, Jan Kassubek.
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
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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 (, 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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Infinium Assay for Large-scale SNP Genotyping Applications
Authors: Adam J. Adler, Graham B. Wiley, Patrick M. Gaffney.
Institutions: Oklahoma Medical Research Foundation.
Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of variants within families or populations can facilitate identification of the genetic factors of disease. Illumina's panel of genotyping BeadChips allows investigators to genotype thousands or millions of single nucleotide polymorphisms (SNPs) or to analyze other genomic variants, such as copy number, across a large number of DNA samples. These SNPs can be spread throughout the genome or targeted in specific regions in order to maximize potential discovery. The Infinium assay has been optimized to yield high-quality, accurate results quickly. With proper setup, a single technician can process from a few hundred to over a thousand DNA samples per week, depending on the type of array. This assay guides users through every step, starting with genomic DNA and ending with the scanning of the array. Using propriety reagents, samples are amplified, fragmented, precipitated, resuspended, hybridized to the chip, extended by a single base, stained, and scanned on either an iScan or Hi Scan high-resolution optical imaging system. One overnight step is required to amplify the DNA. The DNA is denatured and isothermally amplified by whole-genome amplification; therefore, no PCR is required. Samples are hybridized to the arrays during a second overnight step. By the third day, the samples are ready to be scanned and analyzed. Amplified DNA may be stockpiled in large quantities, allowing bead arrays to be processed every day of the week, thereby maximizing throughput.
Basic Protocol, Issue 81, genomics, SNP, Genotyping, Infinium, iScan, HiScan, Illumina
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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
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Simulating Pancreatic Neuroplasticity: In Vitro Dual-neuron Plasticity Assay
Authors: Ihsan Ekin Demir, Elke Tieftrunk, Karl-Herbert Schäfer, Helmut Friess, Güralp O. Ceyhan.
Institutions: Technische Universität München, University of Applied Sciences Kaiserslautern/Zweibrücken.
Neuroplasticity is an inherent feature of the enteric nervous system and gastrointestinal (GI) innervation under pathological conditions. However, the pathophysiological role of neuroplasticity in GI disorders remains unknown. Novel experimental models which allow simulation and modulation of GI neuroplasticity may enable enhanced appreciation of the contribution of neuroplasticity in particular GI diseases such as pancreatic cancer (PCa) and chronic pancreatitis (CP). Here, we present a protocol for simulation of pancreatic neuroplasticity under in vitro conditions using newborn rat dorsal root ganglia (DRG) and myenteric plexus (MP) neurons. This dual-neuron approach not only permits monitoring of both organ-intrinsic and -extrinsic neuroplasticity, but also represents a valuable tool to assess neuronal and glial morphology and electrophysiology. Moreover, it allows functional modulation of supplied microenvironmental contents for studying their impact on neuroplasticity. Once established, the present neuroplasticity assay bears the potential of being applicable to the study of neuroplasticity in any GI organ.
Medicine, Issue 86, Autonomic Nervous System Diseases, Digestive System Neoplasms, Gastrointestinal Diseases, Pancreatic Diseases, Pancreatic Neoplasms, Pancreatitis, Pancreatic neuroplasticity, dorsal root ganglia, myenteric plexus, Morphometry, neurite density, neurite branching, perikaryonal hypertrophy, neuronal plasticity
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A Proboscis Extension Response Protocol for Investigating Behavioral Plasticity in Insects: Application to Basic, Biomedical, and Agricultural Research
Authors: Brian H. Smith, Christina M. Burden.
Institutions: Arizona State University.
Insects modify their responses to stimuli through experience of associating those stimuli with events important for survival (e.g., food, mates, threats). There are several behavioral mechanisms through which an insect learns salient associations and relates them to these events. It is important to understand this behavioral plasticity for programs aimed toward assisting insects that are beneficial for agriculture. This understanding can also be used for discovering solutions to biomedical and agricultural problems created by insects that act as disease vectors and pests. The Proboscis Extension Response (PER) conditioning protocol was developed for honey bees (Apis mellifera) over 50 years ago to study how they perceive and learn about floral odors, which signal the nectar and pollen resources a colony needs for survival. The PER procedure provides a robust and easy-to-employ framework for studying several different ecologically relevant mechanisms of behavioral plasticity. It is easily adaptable for use with several other insect species and other behavioral reflexes. These protocols can be readily employed in conjunction with various means for monitoring neural activity in the CNS via electrophysiology or bioimaging, or for manipulating targeted neuromodulatory pathways. It is a robust assay for rapidly detecting sub-lethal effects on behavior caused by environmental stressors, toxins or pesticides. We show how the PER protocol is straightforward to implement using two procedures. One is suitable as a laboratory exercise for students or for quick assays of the effect of an experimental treatment. The other provides more thorough control of variables, which is important for studies of behavioral conditioning. We show how several measures for the behavioral response ranging from binary yes/no to more continuous variable like latency and duration of proboscis extension can be used to test hypotheses. And, we discuss some pitfalls that researchers commonly encounter when they use the procedure for the first time.
Neuroscience, Issue 91, PER, conditioning, honey bee, olfaction, olfactory processing, learning, memory, toxin assay
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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
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A Restriction Enzyme Based Cloning Method to Assess the In vitro Replication Capacity of HIV-1 Subtype C Gag-MJ4 Chimeric Viruses
Authors: Daniel T. Claiborne, Jessica L. Prince, Eric Hunter.
Institutions: Emory University, Emory University.
The protective effect of many HLA class I alleles on HIV-1 pathogenesis and disease progression is, in part, attributed to their ability to target conserved portions of the HIV-1 genome that escape with difficulty. Sequence changes attributed to cellular immune pressure arise across the genome during infection, and if found within conserved regions of the genome such as Gag, can affect the ability of the virus to replicate in vitro. Transmission of HLA-linked polymorphisms in Gag to HLA-mismatched recipients has been associated with reduced set point viral loads. We hypothesized this may be due to a reduced replication capacity of the virus. Here we present a novel method for assessing the in vitro replication of HIV-1 as influenced by the gag gene isolated from acute time points from subtype C infected Zambians. This method uses restriction enzyme based cloning to insert the gag gene into a common subtype C HIV-1 proviral backbone, MJ4. This makes it more appropriate to the study of subtype C sequences than previous recombination based methods that have assessed the in vitro replication of chronically derived gag-pro sequences. Nevertheless, the protocol could be readily modified for studies of viruses from other subtypes. Moreover, this protocol details a robust and reproducible method for assessing the replication capacity of the Gag-MJ4 chimeric viruses on a CEM-based T cell line. This method was utilized for the study of Gag-MJ4 chimeric viruses derived from 149 subtype C acutely infected Zambians, and has allowed for the identification of residues in Gag that affect replication. More importantly, the implementation of this technique has facilitated a deeper understanding of how viral replication defines parameters of early HIV-1 pathogenesis such as set point viral load and longitudinal CD4+ T cell decline.
Infectious Diseases, Issue 90, HIV-1, Gag, viral replication, replication capacity, viral fitness, MJ4, CEM, GXR25
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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
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In Vivo Modeling of the Morbid Human Genome using Danio rerio
Authors: Adrienne R. Niederriter, Erica E. Davis, Christelle Golzio, Edwin C. Oh, I-Chun Tsai, Nicholas Katsanis.
Institutions: Duke University Medical Center, Duke University, Duke University Medical Center.
Here, we present methods for the development of assays to query potentially clinically significant nonsynonymous changes using in vivo complementation in zebrafish. Zebrafish (Danio rerio) are a useful animal system due to their experimental tractability; embryos are transparent to enable facile viewing, undergo rapid development ex vivo, and can be genetically manipulated.1 These aspects have allowed for significant advances in the analysis of embryogenesis, molecular processes, and morphogenetic signaling. Taken together, the advantages of this vertebrate model make zebrafish highly amenable to modeling the developmental defects in pediatric disease, and in some cases, adult-onset disorders. Because the zebrafish genome is highly conserved with that of humans (~70% orthologous), it is possible to recapitulate human disease states in zebrafish. This is accomplished either through the injection of mutant human mRNA to induce dominant negative or gain of function alleles, or utilization of morpholino (MO) antisense oligonucleotides to suppress genes to mimic loss of function variants. Through complementation of MO-induced phenotypes with capped human mRNA, our approach enables the interpretation of the deleterious effect of mutations on human protein sequence based on the ability of mutant mRNA to rescue a measurable, physiologically relevant phenotype. Modeling of the human disease alleles occurs through microinjection of zebrafish embryos with MO and/or human mRNA at the 1-4 cell stage, and phenotyping up to seven days post fertilization (dpf). This general strategy can be extended to a wide range of disease phenotypes, as demonstrated in the following protocol. We present our established models for morphogenetic signaling, craniofacial, cardiac, vascular integrity, renal function, and skeletal muscle disorder phenotypes, as well as others.
Molecular Biology, Issue 78, Genetics, Biomedical Engineering, Medicine, Developmental Biology, Biochemistry, Anatomy, Physiology, Bioengineering, Genomics, Medical, zebrafish, in vivo, morpholino, human disease modeling, transcription, PCR, mRNA, DNA, Danio rerio, animal model
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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
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Driving Simulation in the Clinic: Testing Visual Exploratory Behavior in Daily Life Activities in Patients with Visual Field Defects
Authors: Johanna Hamel, Antje Kraft, Sven Ohl, Sophie De Beukelaer, Heinrich J. Audebert, Stephan A. Brandt.
Institutions: Universitätsmedizin Charité, Universitätsmedizin Charité, Humboldt Universität zu Berlin.
Patients suffering from homonymous hemianopia after infarction of the posterior cerebral artery (PCA) report different degrees of constraint in daily life, despite similar visual deficits. We assume this could be due to variable development of compensatory strategies such as altered visual scanning behavior. Scanning compensatory therapy (SCT) is studied as part of the visual training after infarction next to vision restoration therapy. SCT consists of learning to make larger eye movements into the blind field enlarging the visual field of search, which has been proven to be the most useful strategy1, not only in natural search tasks but also in mastering daily life activities2. Nevertheless, in clinical routine it is difficult to identify individual levels and training effects of compensatory behavior, since it requires measurement of eye movements in a head unrestrained condition. Studies demonstrated that unrestrained head movements alter the visual exploratory behavior compared to a head-restrained laboratory condition3. Martin et al.4 and Hayhoe et al.5 showed that behavior demonstrated in a laboratory setting cannot be assigned easily to a natural condition. Hence, our goal was to develop a study set-up which uncovers different compensatory oculomotor strategies quickly in a realistic testing situation: Patients are tested in the clinical environment in a driving simulator. SILAB software (Wuerzburg Institute for Traffic Sciences GmbH (WIVW)) was used to program driving scenarios of varying complexity and recording the driver's performance. The software was combined with a head mounted infrared video pupil tracker, recording head- and eye-movements (EyeSeeCam, University of Munich Hospital, Clinical Neurosciences). The positioning of the patient in the driving simulator and the positioning, adjustment and calibration of the camera is demonstrated. Typical performances of a patient with and without compensatory strategy and a healthy control are illustrated in this pilot study. Different oculomotor behaviors (frequency and amplitude of eye- and head-movements) are evaluated very quickly during the drive itself by dynamic overlay pictures indicating where the subjects gaze is located on the screen, and by analyzing the data. Compensatory gaze behavior in a patient leads to a driving performance comparable to a healthy control, while the performance of a patient without compensatory behavior is significantly worse. The data of eye- and head-movement-behavior as well as driving performance are discussed with respect to different oculomotor strategies and in a broader context with respect to possible training effects throughout the testing session and implications on rehabilitation potential.
Medicine, Issue 67, Neuroscience, Physiology, Anatomy, Ophthalmology, compensatory oculomotor behavior, driving simulation, eye movements, homonymous hemianopia, stroke, visual field defects, visual field enlargement
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Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays
Authors: Alla Gagarinova, Mohan Babu, Jack Greenblatt, Andrew Emili.
Institutions: University of Toronto, University of Toronto, University of Regina.
Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10. Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.
Genetics, Issue 69, Molecular Biology, Medicine, Biochemistry, Microbiology, Aggravating, alleviating, conjugation, double mutant, Escherichia coli, genetic interaction, Gram-negative bacteria, homologous recombination, network, synthetic lethality or sickness, suppression
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High Content Screening in Neurodegenerative Diseases
Authors: Shushant Jain, Ronald E. van Kesteren, Peter Heutink.
Institutions: VU University Medical Center, Neuroscience Campus Amsterdam.
The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency1-4. Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation5. For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known6, 7. As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long. There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity8. This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention. High-throughput screening (HTS) is an ideal methodology to address these issues9-12. but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties13, 14. This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS)4, 15-17. HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS. HCS has many advantages over HTS18, 19, but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility. Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing20 and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism21. Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets.
Medicine, Issue 59, High-throughput screening, high-content screening, neurodegeneration, automated cell culturing, Parkinson’s disease
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Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans
Authors: Barbara Squiban, Jérôme Belougne, Jonathan Ewbank, Olivier Zugasti.
Institutions: Université de la Méditerranée.
RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. elegans, gene function can be knocked down simply and efficiently by feeding worms with bacteria expressing a dsRNA corresponding to a specific gene 1. While the creation of libraries of RNAi clones covering most of the C. elegans genome 2,3 opened the way for true functional genomic studies (see for example 4-7), most established methods are laborious. Moy and colleagues have developed semi-automated protocols that facilitate genome-wide screens 8. The approach relies on microscopic imaging and image analysis. Here we describe an alternative protocol for a high-throughput genome-wide screen, based on robotic handling of bacterial RNAi clones, quantitative analysis using the COPAS Biosort (Union Biometrica (UBI)), and an integrated software: the MBioLIMS (Laboratory Information Management System from Modul-Bio) a technology that provides increased throughput for data management and sample tracking. The method allows screens to be conducted on solid medium plates. This is particularly important for some studies, such as those addressing host-pathogen interactions in C. elegans, since certain microbes do not efficiently infect worms in liquid culture. We show how the method can be used to quantify the importance of genes in anti-fungal innate immunity in C. elegans. In this case, the approach relies on the use of a transgenic strain carrying an epidermal infection-inducible fluorescent reporter gene, with GFP under the control of the promoter of the antimicrobial peptide gene nlp 29 and a red fluorescent reporter that is expressed constitutively in the epidermis. The latter provides an internal control for the functional integrity of the epidermis and nonspecific transgene silencing9. When control worms are infected by the fungus they fluoresce green. Knocking down by RNAi a gene required for nlp 29 expression results in diminished fluorescence after infection. Currently, this protocol allows more than 3,000 RNAi clones to be tested and analyzed per week, opening the possibility of screening the entire genome in less than 2 months.
Molecular Biology, Issue 60, C. elegans, fluorescent reporter, Biosort, LIMS, innate immunity, Drechmeria coniospora
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Aseptic Laboratory Techniques: Plating Methods
Authors: Erin R. Sanders.
Institutions: University of California, Los Angeles .
Microorganisms are present on all inanimate surfaces creating ubiquitous sources of possible contamination in the laboratory. Experimental success relies on the ability of a scientist to sterilize work surfaces and equipment as well as prevent contact of sterile instruments and solutions with non-sterile surfaces. Here we present the steps for several plating methods routinely used in the laboratory to isolate, propagate, or enumerate microorganisms such as bacteria and phage. All five methods incorporate aseptic technique, or procedures that maintain the sterility of experimental materials. Procedures described include (1) streak-plating bacterial cultures to isolate single colonies, (2) pour-plating and (3) spread-plating to enumerate viable bacterial colonies, (4) soft agar overlays to isolate phage and enumerate plaques, and (5) replica-plating to transfer cells from one plate to another in an identical spatial pattern. These procedures can be performed at the laboratory bench, provided they involve non-pathogenic strains of microorganisms (Biosafety Level 1, BSL-1). If working with BSL-2 organisms, then these manipulations must take place in a biosafety cabinet. Consult the most current edition of the Biosafety in Microbiological and Biomedical Laboratories (BMBL) as well as Material Safety Data Sheets (MSDS) for Infectious Substances to determine the biohazard classification as well as the safety precautions and containment facilities required for the microorganism in question. Bacterial strains and phage stocks can be obtained from research investigators, companies, and collections maintained by particular organizations such as the American Type Culture Collection (ATCC). It is recommended that non-pathogenic strains be used when learning the various plating methods. By following the procedures described in this protocol, students should be able to: ● Perform plating procedures without contaminating media. ● Isolate single bacterial colonies by the streak-plating method. ● Use pour-plating and spread-plating methods to determine the concentration of bacteria. ● Perform soft agar overlays when working with phage. ● Transfer bacterial cells from one plate to another using the replica-plating procedure. ● Given an experimental task, select the appropriate plating method.
Basic Protocols, Issue 63, Streak plates, pour plates, soft agar overlays, spread plates, replica plates, bacteria, colonies, phage, plaques, dilutions
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Bimolecular Fluorescence Complementation
Authors: Katy A. Wong, John P. O'Bryan.
Institutions: University of Illinois at Chicago.
Defining the subcellular distribution of signaling complexes is imperative to understanding the output from that complex. Conventional methods such as immunoprecipitation do not provide information on the spatial localization of complexes. In contrast, BiFC monitors the interaction and subcellular compartmentalization of protein complexes. In this method, a fluororescent protein is split into amino- and carboxy-terminal non-fluorescent fragments which are then fused to two proteins of interest. Interaction of the proteins results in reconstitution of the fluorophore (Figure 1)1,2. A limitation of BiFC is that once the fragmented fluorophore is reconstituted the complex is irreversible3. This limitation is advantageous in detecting transient or weak interactions, but precludes a kinetic analysis of complex dynamics. An additional caveat is that the reconstituted flourophore requires 30min to mature and fluoresce, again precluding the observation of real time interactions4. BiFC is a specific example of the protein fragment complementation assay (PCA) which employs reporter proteins such as green fluorescent protein variants (BiFC), dihydrofolate reductase, b-lactamase, and luciferase to measure protein:protein interactions5,6. Alternative methods to study protein:protein interactions in cells include fluorescence co-localization and Förster resonance energy transfer (FRET)7. For co-localization, two proteins are individually tagged either directly with a fluorophore or by indirect immunofluorescence. However, this approach leads to high background of non-interacting proteins making it difficult to interpret co-localization data. In addition, due to the limits of resolution of confocal microscopy, two proteins may appear co-localized without necessarily interacting. With BiFC, fluorescence is only observed when the two proteins of interest interact. FRET is another excellent method for studying protein:protein interactions, but can be technically challenging. FRET experiments require the donor and acceptor to be of similar brightness and stoichiometry in the cell. In addition, one must account for bleed through of the donor into the acceptor channel and vice versa. Unlike FRET, BiFC has little background fluorescence, little post processing of image data, does not require high overexpression, and can detect weak or transient interactions. Bioluminescence resonance energy transfer (BRET) is a method similar to FRET except the donor is an enzyme (e.g. luciferase) that catalyzes a substrate to become bioluminescent thereby exciting an acceptor. BRET lacks the technical problems of bleed through and high background fluorescence but lacks the ability to provide spatial information due to the lack of substrate localization to specific compartments8. Overall, BiFC is an excellent method for visualizing subcellular localization of protein complexes to gain insight into compartmentalized signaling.
Cellular Biology, Issue 50, Fluorescence, imaging, compartmentalized signaling, subcellular localization, signal transduction
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
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A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Authors: Gauthier Julie, Fadi F. Hamdan, Guy A. Rouleau.
Institutions: Universite de Montreal, Universite de Montreal, Universite de Montreal.
There are several lines of evidence supporting the role of de novo mutations as a mechanism for common disorders, such as autism and schizophrenia. First, the de novo mutation rate in humans is relatively high, so new mutations are generated at a high frequency in the population. However, de novo mutations have not been reported in most common diseases. Mutations in genes leading to severe diseases where there is a strong negative selection against the phenotype, such as lethality in embryonic stages or reduced reproductive fitness, will not be transmitted to multiple family members, and therefore will not be detected by linkage gene mapping or association studies. The observation of very high concordance in monozygotic twins and very low concordance in dizygotic twins also strongly supports the hypothesis that a significant fraction of cases may result from new mutations. Such is the case for diseases such as autism and schizophrenia. Second, despite reduced reproductive fitness1 and extremely variable environmental factors, the incidence of some diseases is maintained worldwide at a relatively high and constant rate. This is the case for autism and schizophrenia, with an incidence of approximately 1% worldwide. Mutational load can be thought of as a balance between selection for or against a deleterious mutation and its production by de novo mutation. Lower rates of reproduction constitute a negative selection factor that should reduce the number of mutant alleles in the population, ultimately leading to decreased disease prevalence. These selective pressures tend to be of different intensity in different environments. Nonetheless, these severe mental disorders have been maintained at a constant relatively high prevalence in the worldwide population across a wide range of cultures and countries despite a strong negative selection against them2. This is not what one would predict in diseases with reduced reproductive fitness, unless there was a high new mutation rate. Finally, the effects of paternal age: there is a significantly increased risk of the disease with increasing paternal age, which could result from the age related increase in paternal de novo mutations. This is the case for autism and schizophrenia3. The male-to-female ratio of mutation rate is estimated at about 4–6:1, presumably due to a higher number of germ-cell divisions with age in males. Therefore, one would predict that de novo mutations would more frequently come from males, particularly older males4. A high rate of new mutations may in part explain why genetic studies have so far failed to identify many genes predisposing to complexes diseases genes, such as autism and schizophrenia, and why diseases have been identified for a mere 3% of genes in the human genome. Identification for de novo mutations as a cause of a disease requires a targeted molecular approach, which includes studying parents and affected subjects. The process for determining if the genetic basis of a disease may result in part from de novo mutations and the molecular approach to establish this link will be illustrated, using autism and schizophrenia as examples.
Medicine, Issue 52, de novo mutation, complex diseases, schizophrenia, autism, rare variations, DNA sequencing
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Electrophysiological Measurements and Analysis of Nociception in Human Infants
Authors: L. Fabrizi, A. Worley, D. Patten, S. Holdridge, L. Cornelissen, J. Meek, S. Boyd, R. Slater.
Institutions: University College London, Great Ormond Street Hospital, University College Hospital, University of Oxford.
Pain is an unpleasant sensory and emotional experience. Since infants cannot verbally report their experiences, current methods of pain assessment are based on behavioural and physiological body reactions, such as crying, body movements or changes in facial expression. While these measures demonstrate that infants mount a response following noxious stimulation, they are limited: they are based on activation of subcortical somatic and autonomic motor pathways that may not be reliably linked to central sensory processing in the brain. Knowledge of how the central nervous system responds to noxious events could provide an insight to how nociceptive information and pain is processed in newborns. The heel lancing procedure used to extract blood from hospitalised infants offers a unique opportunity to study pain in infancy. In this video we describe how electroencephalography (EEG) and electromyography (EMG) time-locked to this procedure can be used to investigate nociceptive activity in the brain and spinal cord. This integrative approach to the measurement of infant pain has the potential to pave the way for an effective and sensitive clinical measurement tool.
Neuroscience, Issue 58, pain, infant, electrophysiology, human development
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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
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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

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