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Edge principal components and squash clustering: using the special structure of phylogenetic placement data for sample comparison.
PUBLISHED: 01-16-2013
Principal components analysis (PCA) and hierarchical clustering are two of the most heavily used techniques for analyzing the differences between nucleic acid sequence samples taken from a given environment. They have led to many insights regarding the structure of microbial communities. We have developed two new complementary methods that leverage how this microbial community data sits on a phylogenetic tree. Edge principal components analysis enables the detection of important differences between samples that contain closely related taxa. Each principal component axis is a collection of signed weights on the edges of the phylogenetic tree, and these weights are easily visualized by a suitable thickening and coloring of the edges. Squash clustering outputs a (rooted) clustering tree in which each internal node corresponds to an appropriate "average" of the original samples at the leaves below the node. Moreover, the length of an edge is a suitably defined distance between the averaged samples associated with the two incident nodes, rather than the less interpretable average of distances produced by UPGMA, the most widely used hierarchical clustering method in this context. We present these methods and illustrate their use with data from the human microbiome.
Authors: Karin Hauffen, Eugene Bart, Mark Brady, Daniel Kersten, Jay Hegdé.
Published: 11-02-2012
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.
24 Related JoVE Articles!
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Unraveling the Unseen Players in the Ocean - A Field Guide to Water Chemistry and Marine Microbiology
Authors: Andreas Florian Haas, Ben Knowles, Yan Wei Lim, Tracey McDole Somera, Linda Wegley Kelly, Mark Hatay, Forest Rohwer.
Institutions: San Diego State University, University of California San Diego.
Here we introduce a series of thoroughly tested and well standardized research protocols adapted for use in remote marine environments. The sampling protocols include the assessment of resources available to the microbial community (dissolved organic carbon, particulate organic matter, inorganic nutrients), and a comprehensive description of the viral and bacterial communities (via direct viral and microbial counts, enumeration of autofluorescent microbes, and construction of viral and microbial metagenomes). We use a combination of methods, which represent a dispersed field of scientific disciplines comprising already established protocols and some of the most recent techniques developed. Especially metagenomic sequencing techniques used for viral and bacterial community characterization, have been established only in recent years, and are thus still subjected to constant improvement. This has led to a variety of sampling and sample processing procedures currently in use. The set of methods presented here provides an up to date approach to collect and process environmental samples. Parameters addressed with these protocols yield the minimum on information essential to characterize and understand the underlying mechanisms of viral and microbial community dynamics. It gives easy to follow guidelines to conduct comprehensive surveys and discusses critical steps and potential caveats pertinent to each technique.
Environmental Sciences, Issue 93, dissolved organic carbon, particulate organic matter, nutrients, DAPI, SYBR, microbial metagenomics, viral metagenomics, marine environment
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Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Authors: Nikki M. Curthoys, Michael J. Mlodzianoski, Dahan Kim, Samuel T. Hess.
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
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Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System
Authors: Tomohiro Kodani, Alex Rodriguez-Palacios, Daniele Corridoni, Loris Lopetuso, Luca Di Martino, Brian Marks, James Pizarro, Theresa Pizarro, Amitabh Chak, Fabio Cominelli.
Institutions: Case Western Reserve University School of Medicine, Cleveland, Case Western Reserve University School of Medicine, Cleveland, Case Western Reserve University School of Medicine, Cleveland.
The use of modern endoscopy for research purposes has greatly facilitated our understanding of gastrointestinal pathologies. In particular, experimental endoscopy has been highly useful for studies that require repeated assessments in a single laboratory animal, such as those evaluating mechanisms of chronic inflammatory bowel disease and the progression of colorectal cancer. However, the methods used across studies are highly variable. At least three endoscopic scoring systems have been published for murine colitis and published protocols for the assessment of colorectal tumors fail to address the presence of concomitant colonic inflammation. This study develops and validates a reproducible endoscopic scoring system that integrates evaluation of both inflammation and tumors simultaneously. This novel scoring system has three major components: 1) assessment of the extent and severity of colorectal inflammation (based on perianal findings, transparency of the wall, mucosal bleeding, and focal lesions), 2) quantitative recording of tumor lesions (grid map and bar graph), and 3) numerical sorting of clinical cases by their pathological and research relevance based on decimal units with assigned categories of observed lesions and endoscopic complications (decimal identifiers). The video and manuscript presented herein were prepared, following IACUC-approved protocols, to allow investigators to score their own experimental mice using a well-validated and highly reproducible endoscopic methodology, with the system option to differentiate distal from proximal endoscopic colitis (D-PECS).
Medicine, Issue 80, Crohn's disease, ulcerative colitis, colon cancer, Clostridium difficile, SAMP mice, DSS/AOM-colitis, decimal scoring identifier
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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
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Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Authors: C. R. Gallistel, Fuat Balci, David Freestone, Aaron Kheifets, Adam King.
Institutions: Rutgers University, Koç University, New York University, Fairfield University.
We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.
Behavior, Issue 84, genetics, cognitive mechanisms, behavioral screening, learning, memory, timing
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2D and 3D Chromosome Painting in Malaria Mosquitoes
Authors: Phillip George, Atashi Sharma, Igor V Sharakhov.
Institutions: Virginia Tech.
Fluorescent in situ hybridization (FISH) of whole arm chromosome probes is a robust technique for mapping genomic regions of interest, detecting chromosomal rearrangements, and studying three-dimensional (3D) organization of chromosomes in the cell nucleus. The advent of laser capture microdissection (LCM) and whole genome amplification (WGA) allows obtaining large quantities of DNA from single cells. The increased sensitivity of WGA kits prompted us to develop chromosome paints and to use them for exploring chromosome organization and evolution in non-model organisms. Here, we present a simple method for isolating and amplifying the euchromatic segments of single polytene chromosome arms from ovarian nurse cells of the African malaria mosquito Anopheles gambiae. This procedure provides an efficient platform for obtaining chromosome paints, while reducing the overall risk of introducing foreign DNA to the sample. The use of WGA allows for several rounds of re-amplification, resulting in high quantities of DNA that can be utilized for multiple experiments, including 2D and 3D FISH. We demonstrated that the developed chromosome paints can be successfully used to establish the correspondence between euchromatic portions of polytene and mitotic chromosome arms in An. gambiae. Overall, the union of LCM and single-chromosome WGA provides an efficient tool for creating significant amounts of target DNA for future cytogenetic and genomic studies.
Immunology, Issue 83, Microdissection, whole genome amplification, malaria mosquito, polytene chromosome, mitotic chromosomes, fluorescence in situ hybridization, chromosome painting
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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
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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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Reduced-gravity Environment Hardware Demonstrations of a Prototype Miniaturized Flow Cytometer and Companion Microfluidic Mixing Technology
Authors: William S. Phipps, Zhizhong Yin, Candice Bae, Julia Z. Sharpe, Andrew M. Bishara, Emily S. Nelson, Aaron S. Weaver, Daniel Brown, Terri L. McKay, DeVon Griffin, Eugene Y. Chan.
Institutions: DNA Medicine Institute, Harvard Medical School, NASA Glenn Research Center, ZIN Technologies.
Until recently, astronaut blood samples were collected in-flight, transported to earth on the Space Shuttle, and analyzed in terrestrial laboratories. If humans are to travel beyond low Earth orbit, a transition towards space-ready, point-of-care (POC) testing is required. Such testing needs to be comprehensive, easy to perform in a reduced-gravity environment, and unaffected by the stresses of launch and spaceflight. Countless POC devices have been developed to mimic laboratory scale counterparts, but most have narrow applications and few have demonstrable use in an in-flight, reduced-gravity environment. In fact, demonstrations of biomedical diagnostics in reduced gravity are limited altogether, making component choice and certain logistical challenges difficult to approach when seeking to test new technology. To help fill the void, we are presenting a modular method for the construction and operation of a prototype blood diagnostic device and its associated parabolic flight test rig that meet the standards for flight-testing onboard a parabolic flight, reduced-gravity aircraft. The method first focuses on rig assembly for in-flight, reduced-gravity testing of a flow cytometer and a companion microfluidic mixing chip. Components are adaptable to other designs and some custom components, such as a microvolume sample loader and the micromixer may be of particular interest. The method then shifts focus to flight preparation, by offering guidelines and suggestions to prepare for a successful flight test with regard to user training, development of a standard operating procedure (SOP), and other issues. Finally, in-flight experimental procedures specific to our demonstrations are described.
Cellular Biology, Issue 93, Point-of-care, prototype, diagnostics, spaceflight, reduced gravity, parabolic flight, flow cytometry, fluorescence, cell counting, micromixing, spiral-vortex, blood mixing
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Simultaneous Long-term Recordings at Two Neuronal Processing Stages in Behaving Honeybees
Authors: Martin Fritz Brill, Maren Reuter, Wolfgang Rössler, Martin Fritz Strube-Bloss.
Institutions: University of Würzburg.
In both mammals and insects neuronal information is processed in different higher and lower order brain centers. These centers are coupled via convergent and divergent anatomical connections including feed forward and feedback wiring. Furthermore, information of the same origin is partially sent via parallel pathways to different and sometimes into the same brain areas. To understand the evolutionary benefits as well as the computational advantages of these wiring strategies and especially their temporal dependencies on each other, it is necessary to have simultaneous access to single neurons of different tracts or neuropiles in the same preparation at high temporal resolution. Here we concentrate on honeybees by demonstrating a unique extracellular long term access to record multi unit activity at two subsequent neuropiles1, the antennal lobe (AL), the first olfactory processing stage and the mushroom body (MB), a higher order integration center involved in learning and memory formation, or two parallel neuronal tracts2 connecting the AL with the MB. The latter was chosen as an example and will be described in full. In the supporting video the construction and permanent insertion of flexible multi channel wire electrodes is demonstrated. Pairwise differential amplification of the micro wire electrode channels drastically reduces the noise and verifies that the source of the signal is closely related to the position of the electrode tip. The mechanical flexibility of the used wire electrodes allows stable invasive long term recordings over many hours up to days, which is a clear advantage compared to conventional extra and intracellular in vivo recording techniques.
Neuroscience, Issue 89, honeybee brain, olfaction, extracellular long term recordings, double recordings, differential wire electrodes, single unit, multi-unit recordings
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Quantification of Orofacial Phenotypes in Xenopus
Authors: Allyson E. Kennedy, Amanda J. Dickinson.
Institutions: Virginia Commonwealth University.
Xenopus has become an important tool for dissecting the mechanisms governing craniofacial development and defects. A method to quantify orofacial development will allow for more rigorous analysis of orofacial phenotypes upon abrogation with substances that can genetically or molecularly manipulate gene expression or protein function. Using two dimensional images of the embryonic heads, traditional size dimensions-such as orofacial width, height and area- are measured. In addition, a roundness measure of the embryonic mouth opening is used to describe the shape of the mouth. Geometric morphometrics of these two dimensional images is also performed to provide a more sophisticated view of changes in the shape of the orofacial region. Landmarks are assigned to specific points in the orofacial region and coordinates are created. A principle component analysis is used to reduce landmark coordinates to principle components that then discriminate the treatment groups. These results are displayed as a scatter plot in which individuals with similar orofacial shapes cluster together. It is also useful to perform a discriminant function analysis, which statistically compares the positions of the landmarks between two treatment groups. This analysis is displayed on a transformation grid where changes in landmark position are viewed as vectors. A grid is superimposed on these vectors so that a warping pattern is displayed to show where significant landmark positions have changed. Shape changes in the discriminant function analysis are based on a statistical measure, and therefore can be evaluated by a p-value. This analysis is simple and accessible, requiring only a stereoscope and freeware software, and thus will be a valuable research and teaching resource.
Developmental Biology, Issue 93, Orofacial quantification, geometric morphometrics, Xenopus, orofacial development, orofacial defects, shape changes, facial dimensions
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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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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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Concentration of Metabolites from Low-density Planktonic Communities for Environmental Metabolomics using Nuclear Magnetic Resonance Spectroscopy
Authors: R. Craig Everroad, Seiji Yoshida, Yuuri Tsuboi, Yasuhiro Date, Jun Kikuchi, Shigeharu Moriya.
Institutions: RIKEN Advanced Science Institute, Yokohama City University, RIKEN Plant Science Center, Nagoya University.
Environmental metabolomics is an emerging field that is promoting new understanding in how organisms respond to and interact with the environment and each other at the biochemical level1. Nuclear magnetic resonance (NMR) spectroscopy is one of several technologies, including gas chromatography–mass spectrometry (GC-MS), with considerable promise for such studies. Advantages of NMR are that it is suitable for untargeted analyses, provides structural information and spectra can be queried in quantitative and statistical manners against recently available databases of individual metabolite spectra2,3. In addition, NMR spectral data can be combined with data from other omics levels (e.g. transcriptomics, genomics) to provide a more comprehensive understanding of the physiological responses of taxa to each other and the environment4,5,6. However, NMR is less sensitive than other metabolomic techniques, making it difficult to apply to natural microbial systems where sample populations can be low-density and metabolite concentrations low compared to metabolites from well-defined and readily extractable sources such as whole tissues, biofluids or cell-cultures. Consequently, the few direct environmental metabolomic studies of microbes performed to date have been limited to culture-based or easily defined high-density ecosystems such as host-symbiont systems, constructed co-cultures or manipulations of the gut environment where stable isotope labeling can be additionally used to enhance NMR signals7,8,9,10,11,12. Methods that facilitate the concentration and collection of environmental metabolites at concentrations suitable for NMR are lacking. Since recent attention has been given to the environmental metabolomics of organisms within the aquatic environment, where much of the energy and material flow is mediated by the planktonic community13,14, we have developed a method for the concentration and extraction of whole-community metabolites from planktonic microbial systems by filtration. Commercially available hydrophilic poly-1,1-difluoroethene (PVDF) filters are specially treated to completely remove extractables, which can otherwise appear as contaminants in subsequent analyses. These treated filters are then used to filter environmental or experimental samples of interest. Filters containing the wet sample material are lyophilized and aqueous-soluble metabolites are extracted directly for conventional NMR spectroscopy using a standardized potassium phosphate extraction buffer2. Data derived from these methods can be analyzed statistically to identify meaningful patterns, or integrated with other omics levels for comprehensive understanding of community and ecosystem function.
Molecular Biology, Issue 62, environmental metabolomics, metabolic profiling, microbial ecology, plankton, NMR spectroscopy, PCA
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The Analysis of Purkinje Cell Dendritic Morphology in Organotypic Slice Cultures
Authors: Josef P. Kapfhammer, Olivia S. Gugger.
Institutions: University of Basel.
Purkinje cells are an attractive model system for studying dendritic development, because they have an impressive dendritic tree which is strictly oriented in the sagittal plane and develops mostly in the postnatal period in small rodents 3. Furthermore, several antibodies are available which selectively and intensively label Purkinje cells including all processes, with anti-Calbindin D28K being the most widely used. For viewing of dendrites in living cells, mice expressing EGFP selectively in Purkinje cells 11 are available through Jackson labs. Organotypic cerebellar slice cultures cells allow easy experimental manipulation of Purkinje cell dendritic development because most of the dendritic expansion of the Purkinje cell dendritic tree is actually taking place during the culture period 4. We present here a short, reliable and easy protocol for viewing and analyzing the dendritic morphology of Purkinje cells grown in organotypic cerebellar slice cultures. For many purposes, a quantitative evaluation of the Purkinje cell dendritic tree is desirable. We focus here on two parameters, dendritic tree size and branch point numbers, which can be rapidly and easily determined from anti-calbindin stained cerebellar slice cultures. These two parameters yield a reliable and sensitive measure of changes of the Purkinje cell dendritic tree. Using the example of treatments with the protein kinase C (PKC) activator PMA and the metabotropic glutamate receptor 1 (mGluR1) we demonstrate how differences in the dendritic development are visualized and quantitatively assessed. The combination of the presence of an extensive dendritic tree, selective and intense immunostaining methods, organotypic slice cultures which cover the period of dendritic growth and a mouse model with Purkinje cell specific EGFP expression make Purkinje cells a powerful model system for revealing the mechanisms of dendritic development.
Neuroscience, Issue 61, dendritic development, dendritic branching, cerebellum, Purkinje cells
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The ITS2 Database
Authors: Benjamin Merget, Christian Koetschan, Thomas Hackl, Frank Förster, Thomas Dandekar, Tobias Müller, Jörg Schultz, Matthias Wolf.
Institutions: University of Würzburg, University of Würzburg.
The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation2-8. The ITS2 Database9 presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank11 accurately reannotated10. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold12 (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling13. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold. The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST14 search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE15,16 and ProfDistS17 for multiple sequence-structure alignment calculation and Neighbor Joining18 tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure. In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
Genetics, Issue 61, alignment, internal transcribed spacer 2, molecular systematics, secondary structure, ribosomal RNA, phylogenetic tree, homology modeling, phylogeny
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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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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
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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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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Authors: Rangaraj M. Rangayyan, Shantanu Banik, J.E. Leo Desautels.
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion. Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
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Biology of Microbial Communities - Interview
Authors: Roberto Kolter.
Institutions: Harvard Medical School.
Microbiology, issue 4, microbial community, DNA, extraction, gut, termit
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Microbial Communities in Nature and Laboratory - Interview
Authors: Edward F. DeLong.
Institutions: MIT - Massachusetts Institute of Technology.
Microbiology, issue 4, microbial community, biofilm, genome
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Investigating the Microbial Community in the Termite Hindgut - Interview
Authors: Jared Leadbetter.
Institutions: California Institute of Technology - Caltech.
Jared Leadbetter explains why the termite-gut microbial community is an excellent system for studying the complex interactions between microbes. The symbiotic relationship existing between the host insect and lignocellulose-degrading gut microbes is explained, as well as the industrial uses of these microbes for degrading plant biomass and generating biofuels.
Microbiology, issue 4, microbial community, diversity
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Extracting DNA from the Gut Microbes of the Termite (Zootermopsis Angusticollis) and Visualizing Gut Microbes
Authors: Eric Matson, Elizabeth Ottesen, Jared Leadbetter.
Institutions: California Institute of Technology - Caltech.
Termites are among the few animals known to have the capacity to subsist solely by consuming wood. The termite gut tract contains a dense and species-rich microbial population that assists in the degradation of lignocellulose predominantly into acetate, the key nutrient fueling termite metabolism (Odelson & Breznak, 1983). Within these microbial populations are bacteria, methanogenic archaea and, in some ("lower") termites, eukaryotic protozoa. Thus, termites are excellent research subjects for studying the interactions among microbial species and the numerous biochemical functions they perform to the benefit of their host. The species composition of microbial populations in termite guts as well as key genes involved in various biochemical processes has been explored using molecular techniques (Kudo et al., 1998; Schmit-Wagner et al., 2003; Salmassi & Leadbetter, 2003). These techniques depend on the extraction and purification of high-quality nucleic acids from the termite gut environment. The extraction technique described in this video is a modified compilation of protocols developed for extraction and purification of nucleic acids from environmental samples (Mor et al., 1994; Berthelet et al., 1996; Purdy et al., 1996; Salmassi & Leadbetter, 2003; Ottesen et al. 2006) and it produces DNA from termite hindgut material suitable for use as template for polymerase chain reaction (PCR).
Microbiology, issue 4, microbial community, DNA, extraction, gut, termite
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