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Pubmed Article
Bayesian inference from count data using discrete uniform priors.
PUBLISHED: 01-01-2013
We consider a set of sample counts obtained by sampling arbitrary fractions of a finite volume containing an homogeneously dispersed population of identical objects. We report a Bayesian derivation of the posterior probability distribution of the population size using a binomial likelihood and non-conjugate, discrete uniform priors under sampling with or without replacement. Our derivation yields a computationally feasible formula that can prove useful in a variety of statistical problems involving absolute quantification under uncertainty. We implemented our algorithm in the R package dupiR and compared it with a previously proposed Bayesian method based on a Gamma prior. As a showcase, we demonstrate that our inference framework can be used to estimate bacterial survival curves from measurements characterized by extremely low or zero counts and rather high sampling fractions. All in all, we provide a versatile, general purpose algorithm to infer population sizes from count data, which can find application in a broad spectrum of biological and physical problems.
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.
19 Related JoVE Articles!
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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Authors: Haipeng Xing, Willey Liao, Yifan Mo, Michael Q. Zhang.
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work. Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized. Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types. To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
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Flying Insect Detection and Classification with Inexpensive Sensors
Authors: Yanping Chen, Adena Why, Gustavo Batista, Agenor Mafra-Neto, Eamonn Keogh.
Institutions: University of California, Riverside, University of California, Riverside, University of São Paulo - USP, ISCA Technologies.
An inexpensive, noninvasive system that could accurately classify flying insects would have important implications for entomological research, and allow for the development of many useful applications in vector and pest control for both medical and agricultural entomology. Given this, the last sixty years have seen many research efforts devoted to this task. To date, however, none of this research has had a lasting impact. In this work, we show that pseudo-acoustic optical sensors can produce superior data; that additional features, both intrinsic and extrinsic to the insect’s flight behavior, can be exploited to improve insect classification; that a Bayesian classification approach allows to efficiently learn classification models that are very robust to over-fitting, and a general classification framework allows to easily incorporate arbitrary number of features. We demonstrate the findings with large-scale experiments that dwarf all previous works combined, as measured by the number of insects and the number of species considered.
Bioengineering, Issue 92, flying insect detection, automatic insect classification, pseudo-acoustic optical sensors, Bayesian classification framework, flight sound, circadian rhythm
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Knowing What Counts: Unbiased Stereology in the Non-human Primate Brain
Authors: Mark Burke, Shahin Zangenehpour, Peter R. Mouton, Maurice Ptito.
Institutions: University of Montreal, University of Montreal, Stereology Resource Center.
The non-human primate is an important translational species for understanding the normal function and disease processes of the human brain. Unbiased stereology, the method accepted as state-of-the-art for quantification of biological objects in tissue sections2, generates reliable structural data for biological features in the mammalian brain3. The key components of the approach are unbiased (systematic-random) sampling of anatomically defined structures (reference spaces), combined with quantification of cell numbers and size, fiber and capillary lengths, surface areas, regional volumes and spatial distributions of biological objects within the reference space4. Among the advantages of these stereological approaches over previous methods is the avoidance of all known sources of systematic (non-random) error arising from faulty assumptions and non-verifiable models. This study documents a biological application of computerized stereology to estimate the total neuronal population in the frontal cortex of the vervet monkey brain (Chlorocebus aethiops sabeus), with assistance from two commercially available stereology programs, BioQuant Life Sciences and Stereologer (Figure 1). In addition to contrast and comparison of results from both the BioQuant and Stereologer systems, this study provides a detailed protocol for the Stereologer system.
Neuroscience, Issue 27, Stereology, brain bank, systematic sampling, non-human primate, cryostat, antigen preserve
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Determining Cell Number During Cell Culture using the Scepter Cell Counter
Authors: Kathleen Ongena, Chandreyee Das, Janet L. Smith, Sónia Gil, Grace Johnston.
Institutions: Millipore Inc.
Counting cells is often a necessary but tedious step for in vitro cell culture. Consistent cell concentrations ensure experimental reproducibility and accuracy. Cell counts are important for monitoring cell health and proliferation rate, assessing immortalization or transformation, seeding cells for subsequent experiments, transfection or infection, and preparing for cell-based assays. It is important that cell counts be accurate, consistent, and fast, particularly for quantitative measurements of cellular responses. Despite this need for speed and accuracy in cell counting, 71% of 400 researchers surveyed1 who count cells using a hemocytometer. While hemocytometry is inexpensive, it is laborious and subject to user bias and misuse, which results in inaccurate counts. Hemocytometers are made of special optical glass on which cell suspensions are loaded in specified volumes and counted under a microscope. Sources of errors in hemocytometry include: uneven cell distribution in the sample, too many or too few cells in the sample, subjective decisions as to whether a given cell falls within the defined counting area, contamination of the hemocytometer, user-to-user variation, and variation of hemocytometer filling rate2. To alleviate the tedium associated with manual counting, 29% of researchers count cells using automated cell counting devices; these include vision-based counters, systems that detect cells using the Coulter principle, or flow cytometry1. For most researchers, the main barrier to using an automated system is the price associated with these large benchtop instruments1. The Scepter cell counter is an automated handheld device that offers the automation and accuracy of Coulter counting at a relatively low cost. The system employs the Coulter principle of impedance-based particle detection3 in a miniaturized format using a combination of analog and digital hardware for sensing, signal processing, data storage, and graphical display. The disposable tip is engineered with a microfabricated, cell- sensing zone that enables discrimination by cell size and cell volume at sub-micron and sub-picoliter resolution. Enhanced with precision liquid-handling channels and electronics, the Scepter cell counter reports cell population statistics graphically displayed as a histogram.
Cellular Biology, Issue 45, Scepter, cell counting, cell culture, hemocytometer, Coulter, Impedance-based particle detection
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Determination of Mammalian Cell Counts, Cell Size and Cell Health Using the Moxi Z Mini Automated Cell Counter
Authors: Gregory M. Dittami, Manju Sethi, Richard D. Rabbitt, H. Edward Ayliffe.
Institutions: Orflo Technologies, University of Utah .
Particle and cell counting is used for a variety of applications including routine cell culture, hematological analysis, and industrial controls1-5. A critical breakthrough in cell/particle counting technologies was the development of the Coulter technique by Wallace Coulter over 50 years ago. The technique involves the application of an electric field across a micron-sized aperture and hydrodynamically focusing single particles through the aperture. The resulting occlusion of the aperture by the particles yields a measurable change in electric impedance that can be directly and precisely correlated to cell size/volume. The recognition of the approach as the benchmark in cell/particle counting stems from the extraordinary precision and accuracy of its particle sizing and counts, particularly as compared to manual and imaging based technologies (accuracies on the order of 98% for Coulter counters versus 75-80% for manual and vision-based systems). This can be attributed to the fact that, unlike imaging-based approaches to cell counting, the Coulter Technique makes a true three-dimensional (3-D) measurement of cells/particles which dramatically reduces count interference from debris and clustering by calculating precise volumetric information about the cells/particles. Overall this provides a means for enumerating and sizing cells in a more accurate, less tedious, less time-consuming, and less subjective means than other counting techniques6. Despite the prominence of the Coulter technique in cell counting, its widespread use in routine biological studies has been prohibitive due to the cost and size of traditional instruments. Although a less expensive Coulter-based instrument has been produced, it has limitations as compared to its more expensive counterparts in the correction for "coincidence events" in which two or more cells pass through the aperture and are measured simultaneously. Another limitation with existing Coulter technologies is the lack of metrics on the overall health of cell samples. Consequently, additional techniques must often be used in conjunction with Coulter counting to assess cell viability. This extends experimental setup time and cost since the traditional methods of viability assessment require cell staining and/or use of expensive and cumbersome equipment such as a flow cytometer. The Moxi Z mini automated cell counter, described here, is an ultra-small benchtop instrument that combines the accuracy of the Coulter Principle with a thin-film sensor technology to enable precise sizing and counting of particles ranging from 3-25 microns, depending on the cell counting cassette used. The M type cassette can be used to count particles from with average diameters of 4 - 25 microns (dynamic range 2 - 34 microns), and the Type S cassette can be used to count particles with and average diameter of 3 - 20 microns (dynamic range 2 - 26 microns). Since the system uses a volumetric measurement method, the 4-25 microns corresponds to a cell volume range of 34 - 8,180 fL and the 3 - 20 microns corresponds to a cell volume range of 14 - 4200 fL, which is relevant when non-spherical particles are being measured. To perform mammalian cell counts using the Moxi Z, the cells to be counted are first diluted with ORFLO or similar diluent. A cell counting cassette is inserted into the instrument, and the sample is loaded into the port of the cassette. Thousands of cells are pulled, single-file through a "Cell Sensing Zone" (CSZ) in the thin-film membrane over 8-15 seconds. Following the run, the instrument uses proprietary curve-fitting in conjunction with a proprietary software algorithm to provide coincidence event correction along with an assessment of overall culture health by determining the ratio of the number of cells in the population of interest to the total number of particles. The total particle counts include shrunken and broken down dead cells, as well as other debris and contaminants. The results are presented in histogram format with an automatic curve fit, with gates that can be adjusted manually as needed. Ultimately, the Moxi Z enables counting with a precision and accuracy comparable to a Coulter Z2, the current gold standard, while providing additional culture health information. Furthermore it achieves these results in less time, with a smaller footprint, with significantly easier operation and maintenance, and at a fraction of the cost of comparable technologies.
Cellular Biology, Issue 64, Molecular Biology, cell counting, coulter counting, cell culture health assessment, particle sizing, mammalian cells, Moxi Z
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A Noninvasive Hair Sampling Technique to Obtain High Quality DNA from Elusive Small Mammals
Authors: Philippe Henry, Alison Henry, Michael A. Russello.
Institutions: University of British Columbia, Okanagan Campus.
Noninvasive genetic sampling approaches are becoming increasingly important to study wildlife populations. A number of studies have reported using noninvasive sampling techniques to investigate population genetics and demography of wild populations1. This approach has proven to be especially useful when dealing with rare or elusive species2. While a number of these methods have been developed to sample hair, feces and other biological material from carnivores and medium-sized mammals, they have largely remained untested in elusive small mammals. In this video, we present a novel, inexpensive and noninvasive hair snare targeted at an elusive small mammal, the American pika (Ochotona princeps). We describe the general set-up of the hair snare, which consists of strips of packing tape arranged in a web-like fashion and placed along travelling routes in the pikas’ habitat. We illustrate the efficiency of the snare at collecting a large quantity of hair that can then be collected and brought back to the lab. We then demonstrate the use of the DNA IQ system (Promega) to isolate DNA and showcase the utility of this method to amplify commonly used molecular markers including nuclear microsatellites, amplified fragment length polymorphisms (AFLPs), mitochondrial sequences (800bp) as well as a molecular sexing marker. Overall, we demonstrate the utility of this novel noninvasive hair snare as a sampling technique for wildlife population biologists. We anticipate that this approach will be applicable to a variety of small mammals, opening up areas of investigation within natural populations, while minimizing impact to study organisms.
Genetics, Issue 49, Conservation genetics, noninvasive genetic sampling, Hair snares, Microsatellites, AFLPs, American pika, Ochotona princeps
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Assessing Differences in Sperm Competitive Ability in Drosophila
Authors: Shu-Dan Yeh, Carolus Chan, José M. Ranz.
Institutions: University of California, Irvine.
Competition among conspecific males for fertilizing the ova is one of the mechanisms of sexual selection, i.e. selection that operates on maximizing the number of successful mating events rather than on maximizing survival and viability 1. Sperm competition represents the competition between males after copulating with the same female 2, in which their sperm are coincidental in time and space. This phenomenon has been reported in multiple species of plants and animals 3. For example, wild-caught D. melanogaster females usually contain sperm from 2-3 males 4. The sperm are stored in specialized organs with limited storage capacity, which might lead to the direct competition of the sperm from different males 2,5. Comparing sperm competitive ability of different males of interest (experimental male types) has been performed through controlled double-mating experiments in the laboratory 6,7. Briefly, a single female is exposed to two different males consecutively, one experimental male and one cross-mating reference male. The same mating scheme is then followed using other experimental male types thus facilitating the indirect comparison of the competitive ability of their sperm through a common reference. The fraction of individuals fathered by the experimental and reference males is identified using markers, which allows one to estimate sperm competitive ability using simple mathematical expressions 7,8. In addition, sperm competitive ability can be estimated in two different scenarios depending on whether the experimental male is second or first to mate (offense and defense assay, respectively) 9, which is assumed to be reflective of different competence attributes. Here, we describe an approach that helps to interrogate the role of different genetic factors that putatively underlie the phenomenon of sperm competitive ability in D. melanogaster.
Developmental Biology, Issue 78, Molecular Biology, Cellular Biology, Genetics, Biochemistry, Spermatozoa, Drosophila melanogaster, Biological Evolution, Phenotype, genetics (animal and plant), animal biology, double-mating experiment, sperm competitive ability, male fertility, Drosophila, fruit fly, animal model
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A Tactile Automated Passive-Finger Stimulator (TAPS)
Authors: Daniel Goldreich, Michael Wong, Ryan M. Peters, Ingrid M. Kanics.
Institutions: Duquesne University, McMaster University.
Although tactile spatial acuity tests are used in both neuroscience research and clinical assessment, few automated devices exist for delivering controlled spatially structured stimuli to the skin. Consequently, investigators often apply tactile stimuli manually. Manual stimulus application is time consuming, requires great care and concentration on the part of the investigator, and leaves many stimulus parameters uncontrolled. We describe here a computer-controlled tactile stimulus system, the Tactile Automated Passive-finger Stimulator (TAPS), that applies spatially structured stimuli to the skin, controlling for onset velocity, contact force, and contact duration. TAPS is a versatile, programmable system, capable of efficiently conducting a variety of psychophysical procedures. We describe the components of TAPS, and show how TAPS is used to administer a two-interval forced-choice tactile grating orientation test. Corresponding Author: Daniel Goldreich
Medicine, Neuroscience, Issue 28, tactile, somatosensory, touch, cutaneous, acuity, psychophysics, Bayesian, grating orientation, sensory neuroscience, spatial discrimination
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Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae
Authors: Melissa N. Patterson, Patrick H. Maxwell.
Institutions: Rensselaer Polytechnic Institute.
Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on mutation accumulation to address mechanisms underlying genome instability during replicative aging.
Microbiology, Issue 92, Aging, mutations, genome instability, Saccharomyces cerevisiae, fluctuation test, magnetic sorting, mother cell, replicative aging
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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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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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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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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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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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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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Test Samples for Optimizing STORM Super-Resolution Microscopy
Authors: Daniel J. Metcalf, Rebecca Edwards, Neelam Kumarswami, Alex E. Knight.
Institutions: National Physical Laboratory.
STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.
Molecular Biology, Issue 79, Genetics, Bioengineering, Biomedical Engineering, Biophysics, Basic Protocols, HeLa Cells, Actin Cytoskeleton, Coated Vesicles, Receptor, Epidermal Growth Factor, Actins, Fluorescence, Endocytosis, Microscopy, STORM, super-resolution microscopy, nanoscopy, cell biology, fluorescence microscopy, test samples, resolution, actin filaments, fiducial markers, epidermal growth factor, cell, imaging
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Measurement of Lifespan in Drosophila melanogaster
Authors: Nancy J. Linford, Ceyda Bilgir, Jennifer Ro, Scott D. Pletcher.
Institutions: University of Michigan , University of Michigan .
Aging is a phenomenon that results in steady physiological deterioration in nearly all organisms in which it has been examined, leading to reduced physical performance and increased risk of disease. Individual aging is manifest at the population level as an increase in age-dependent mortality, which is often measured in the laboratory by observing lifespan in large cohorts of age-matched individuals. Experiments that seek to quantify the extent to which genetic or environmental manipulations impact lifespan in simple model organisms have been remarkably successful for understanding the aspects of aging that are conserved across taxa and for inspiring new strategies for extending lifespan and preventing age-associated disease in mammals. The vinegar fly, Drosophila melanogaster, is an attractive model organism for studying the mechanisms of aging due to its relatively short lifespan, convenient husbandry, and facile genetics. However, demographic measures of aging, including age-specific survival and mortality, are extraordinarily susceptible to even minor variations in experimental design and environment, and the maintenance of strict laboratory practices for the duration of aging experiments is required. These considerations, together with the need to practice careful control of genetic background, are essential for generating robust measurements. Indeed, there are many notable controversies surrounding inference from longevity experiments in yeast, worms, flies and mice that have been traced to environmental or genetic artifacts1-4. In this protocol, we describe a set of procedures that have been optimized over many years of measuring longevity in Drosophila using laboratory vials. We also describe the use of the dLife software, which was developed by our laboratory and is available for download ( dLife accelerates throughput and promotes good practices by incorporating optimal experimental design, simplifying fly handling and data collection, and standardizing data analysis. We will also discuss the many potential pitfalls in the design, collection, and interpretation of lifespan data, and we provide steps to avoid these dangers.
Developmental Biology, Issue 71, Cellular Biology, Molecular Biology, Anatomy, Physiology, Entomology, longevity, lifespan, aging, Drosophila melanogaster, fruit fly, Drosophila, mortality, animal model
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Predicting the Effectiveness of Population Replacement Strategy Using Mathematical Modeling
Authors: John Marshall, Koji Morikawa, Nicholas Manoukis, Charles Taylor.
Institutions: University of California, Los Angeles.
Charles Taylor and John Marshall explain the utility of mathematical modeling for evaluating the effectiveness of population replacement strategy. Insight is given into how computational models can provide information on the population dynamics of mosquitoes and the spread of transposable elements through A. gambiae subspecies. The ethical considerations of releasing genetically modified mosquitoes into the wild are discussed.
Cellular Biology, Issue 5, mosquito, malaria, popuulation, replacement, modeling, infectious disease
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Population Replacement Strategies for Controlling Vector Populations and the Use of Wolbachia pipientis for Genetic Drive
Authors: Jason Rasgon.
Institutions: Johns Hopkins University.
In this video, Jason Rasgon discusses population replacement strategies to control vector-borne diseases such as malaria and dengue. "Population replacement" is the replacement of wild vector populations (that are competent to transmit pathogens) with those that are not competent to transmit pathogens. There are several theoretical strategies to accomplish this. One is to exploit the maternally-inherited symbiotic bacteria Wolbachia pipientis. Wolbachia is a widespread reproductive parasite that spreads in a selfish manner at the extent of its host's fitness. Jason Rasgon discusses, in detail, the basic biology of this bacterial symbiont and various ways to use it for control of vector-borne diseases.
Cellular Biology, Issue 5, mosquito, malaria, genetics, infectious disease, Wolbachia
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