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.
26 Related JoVE Articles!
Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
Institutions: Université Pierre et Marie Curie, Ecole Normale Supérieure, CNRS, East China Normal University, Universidade de São Paulo.
Engineering non-classical states of the electromagnetic field is a central quest for quantum optics1,2
. Beyond their fundamental significance, such states are indeed the resources for implementing various protocols, ranging from enhanced metrology to quantum communication and computing. A variety of devices can be used to generate non-classical states, such as single emitters, light-matter interfaces or non-linear systems3
. We focus here on the use of a continuous-wave optical parametric oscillator3,4
. This system is based on a non-linear χ2
crystal inserted inside an optical cavity and it is now well-known as a very efficient source of non-classical light, such as single-mode or two-mode squeezed vacuum depending on the crystal phase matching.
Squeezed vacuum is a Gaussian state as its quadrature distributions follow a Gaussian statistics. However, it has been shown that number of protocols require non-Gaussian states5
. Generating directly such states is a difficult task and would require strong χ3
non-linearities. Another procedure, probabilistic but heralded, consists in using a measurement-induced non-linearity via a conditional preparation technique operated on Gaussian states. Here, we detail this generation protocol for two non-Gaussian states, the single-photon state and a superposition of coherent states, using two differently phase-matched parametric oscillators as primary resources. This technique enables achievement of a high fidelity with the targeted state and generation of the state in a well-controlled spatiotemporal mode.
Physics, Issue 87, Optics, Quantum optics, Quantum state engineering, Optical parametric oscillator, Squeezed vacuum, Single photon, Coherent state superposition, Homodyne detection
MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
Institutions: Max Planck Institute for Biological Cybernetics, Collège de France - CNRS, Korea University.
Path integration is a process in which self-motion is integrated over time to obtain an estimate of one's current position relative to a starting point 1
. Humans can do path integration based exclusively on visual 2-3
, auditory 4
, or inertial cues 5
. However, with multiple cues present, inertial cues - particularly kinaesthetic - seem to dominate 6-7
. In the absence of vision, humans tend to overestimate short distances (<5 m) and turning angles (<30°), but underestimate longer ones 5
. Movement through physical space therefore does not seem to be accurately represented by the brain.
Extensive work has been done on evaluating path integration in the horizontal plane, but little is known about vertical movement (see 3
for virtual movement from vision alone). One reason for this is that traditional motion simulators have a small range of motion restricted mainly to the horizontal plane. Here we take advantage of a motion simulator 8-9
with a large range of motion to assess whether path integration is similar between horizontal and vertical planes. The relative contributions of inertial and visual cues for path navigation were also assessed.
16 observers sat upright in a seat mounted to the flange of a modified KUKA anthropomorphic robot arm. Sensory information was manipulated by providing visual (optic flow, limited lifetime star field), vestibular-kinaesthetic (passive self motion with eyes closed), or visual and vestibular-kinaesthetic motion cues. Movement trajectories in the horizontal, sagittal and frontal planes consisted of two segment lengths (1st: 0.4 m, 2nd: 1 m; ±0.24 m/s2
peak acceleration). The angle of the two segments was either 45° or 90°. Observers pointed back to their origin by moving an arrow that was superimposed on an avatar presented on the screen.
Observers were more likely to underestimate angle size for movement in the horizontal plane compared to the vertical planes. In the frontal plane observers were more likely to overestimate angle size while there was no such bias in the sagittal plane. Finally, observers responded slower when answering based on vestibular-kinaesthetic information alone. Human path integration based on vestibular-kinaesthetic information alone thus takes longer than when visual information is present. That pointing is consistent with underestimating and overestimating the angle one has moved through in the horizontal and vertical planes respectively, suggests that the neural representation of self-motion through space is non-symmetrical which may relate to the fact that humans experience movement mostly within the horizontal plane.
Neuroscience, Issue 63, Motion simulator, multisensory integration, path integration, space perception, vestibular, vision, robotics, cybernetics
An Inverse Analysis Approach to the Characterization of Chemical Transport in Paints
Institutions: U.S. Army Edgewood Chemical Biological Center, OptiMetrics, Inc., a DCS Company.
The ability to directly characterize chemical transport and interactions that occur within a material (i.e.
, subsurface dynamics) is a vital component in understanding contaminant mass transport and the ability to decontaminate materials. If a material is contaminated, over time, the transport of highly toxic chemicals (such as chemical warfare agent species) out of the material can result in vapor exposure or transfer to the skin, which can result in percutaneous exposure to personnel who interact with the material. Due to the high toxicity of chemical warfare agents, the release of trace chemical quantities is of significant concern. Mapping subsurface concentration distribution and transport characteristics of absorbed agents enables exposure hazards to be assessed in untested conditions. Furthermore, these tools can be used to characterize subsurface reaction dynamics to ultimately design improved decontaminants or decontamination procedures. To achieve this goal, an inverse analysis mass transport modeling approach was developed that utilizes time-resolved mass spectroscopy measurements of vapor emission from contaminated paint coatings as the input parameter for calculation of subsurface concentration profiles. Details are provided on sample preparation, including contaminant and material handling, the application of mass spectrometry for the measurement of emitted contaminant vapor, and the implementation of inverse analysis using a physics-based diffusion model to determine transport properties of live chemical warfare agents including distilled mustard (HD) and the nerve agent VX.
Chemistry, Issue 90, Vacuum, vapor emission, chemical warfare agent, contamination, mass transport, inverse analysis, volatile organic compound, paint, coating
High-throughput Fluorometric Measurement of Potential Soil Extracellular Enzyme Activities
Institutions: Colorado State University, Oak Ridge National Laboratory, University of Colorado.
Microbes in soils and other environments produce extracellular enzymes to depolymerize and hydrolyze organic macromolecules so that they can be assimilated for energy and nutrients. Measuring soil microbial enzyme activity is crucial in understanding soil ecosystem functional dynamics. The general concept of the fluorescence enzyme assay is that synthetic C-, N-, or P-rich substrates bound with a fluorescent dye are added to soil samples. When intact, the labeled substrates do not fluoresce. Enzyme activity is measured as the increase in fluorescence as the fluorescent dyes are cleaved from their substrates, which allows them to fluoresce. Enzyme measurements can be expressed in units of molarity or activity. To perform this assay, soil slurries are prepared by combining soil with a pH buffer. The pH buffer (typically a 50 mM sodium acetate or 50 mM Tris buffer), is chosen for the buffer's particular acid dissociation constant (pKa) to best match the soil sample pH. The soil slurries are inoculated with a nonlimiting amount of fluorescently labeled (i.e.
C-, N-, or P-rich) substrate. Using soil slurries in the assay serves to minimize limitations on enzyme and substrate diffusion. Therefore, this assay controls for differences in substrate limitation, diffusion rates, and soil pH conditions; thus detecting potential enzyme activity rates as a function of the difference in enzyme concentrations (per sample).
Fluorescence enzyme assays are typically more sensitive than spectrophotometric (i.e.
colorimetric) assays, but can suffer from interference caused by impurities and the instability of many fluorescent compounds when exposed to light; so caution is required when handling fluorescent substrates. Likewise, this method only assesses potential enzyme activities under laboratory conditions when substrates are not limiting. Caution should be used when interpreting the data representing cross-site comparisons with differing temperatures or soil types, as in situ
soil type and temperature can influence enzyme kinetics.
Environmental Sciences, Issue 81, Ecological and Environmental Phenomena, Environment, Biochemistry, Environmental Microbiology, Soil Microbiology, Ecology, Eukaryota, Archaea, Bacteria, Soil extracellular enzyme activities (EEAs), fluorometric enzyme assays, substrate degradation, 4-methylumbelliferone (MUB), 7-amino-4-methylcoumarin (MUC), enzyme temperature kinetics, soil
Preparation of Segmented Microtubules to Study Motions Driven by the Disassembling Microtubule Ends
Institutions: Russian Academy of Sciences, Federal Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russia, University of Pennsylvania.
Microtubule depolymerization can provide force to transport different protein complexes and protein-coated beads in vitro
. The underlying mechanisms are thought to play a vital role in the microtubule-dependent chromosome motions during cell division, but the relevant proteins and their exact roles are ill-defined. Thus, there is a growing need to develop assays with which to study such motility in vitro
using purified components and defined biochemical milieu. Microtubules, however, are inherently unstable polymers; their switching between growth and shortening is stochastic and difficult to control. The protocols we describe here take advantage of the segmented microtubules that are made with the photoablatable stabilizing caps. Depolymerization of such segmented microtubules can be triggered with high temporal and spatial resolution, thereby assisting studies of motility at the disassembling microtubule ends. This technique can be used to carry out a quantitative analysis of the number of molecules in the fluorescently-labeled protein complexes, which move processively with dynamic microtubule ends. To optimize a signal-to-noise ratio in this and other quantitative fluorescent assays, coverslips should be treated to reduce nonspecific absorption of soluble fluorescently-labeled proteins. Detailed protocols are provided to take into account the unevenness of fluorescent illumination, and determine the intensity of a single fluorophore using equidistant Gaussian fit. Finally, we describe the use of segmented microtubules to study microtubule-dependent motions of the protein-coated microbeads, providing insights into the ability of different motor and nonmotor proteins to couple microtubule depolymerization to processive cargo motion.
Basic Protocol, Issue 85, microscopy flow chamber, single-molecule fluorescence, laser trap, microtubule-binding protein, microtubule-dependent motor, microtubule tip-tracking
Measurement of Greenhouse Gas Flux from Agricultural Soils Using Static Chambers
Institutions: University of Wisconsin-Madison, University of Wisconsin-Madison, University of Wisconsin-Madison, University of Wisconsin-Madison, USDA-ARS Dairy Forage Research Center, USDA-ARS Pasture Systems Watershed Management Research Unit.
Measurement of greenhouse gas (GHG) fluxes between the soil and the atmosphere, in both managed and unmanaged ecosystems, is critical to understanding the biogeochemical drivers of climate change and to the development and evaluation of GHG mitigation strategies based on modulation of landscape management practices. The static chamber-based method described here is based on trapping gases emitted from the soil surface within a chamber and collecting samples from the chamber headspace at regular intervals for analysis by gas chromatography. Change in gas concentration over time is used to calculate flux. This method can be utilized to measure landscape-based flux of carbon dioxide, nitrous oxide, and methane, and to estimate differences between treatments or explore system dynamics over seasons or years. Infrastructure requirements are modest, but a comprehensive experimental design is essential. This method is easily deployed in the field, conforms to established guidelines, and produces data suitable to large-scale GHG emissions studies.
Environmental Sciences, Issue 90, greenhouse gas, trace gas, gas flux, static chamber, soil, field, agriculture, climate
Confocal Imaging of Confined Quiescent and Flowing Colloid-polymer Mixtures
Institutions: University of Houston.
The behavior of confined colloidal suspensions with attractive interparticle interactions is critical to the rational design of materials for directed assembly1-3
, drug delivery4
, improved hydrocarbon recovery5-7
, and flowable electrodes for energy storage8
. Suspensions containing fluorescent colloids and non-adsorbing polymers are appealing model systems, as the ratio of the polymer radius of gyration to the particle radius and concentration of polymer control the range and strength of the interparticle attraction, respectively. By tuning the polymer properties and the volume fraction of the colloids, colloid fluids, fluids of clusters, gels, crystals, and glasses can be obtained9
. Confocal microscopy, a variant of fluorescence microscopy, allows an optically transparent and fluorescent sample to be imaged with high spatial and temporal resolution in three dimensions. In this technique, a small pinhole or slit blocks the emitted fluorescent light from regions of the sample that are outside the focal volume of the microscope optical system. As a result, only a thin section of the sample in the focal plane is imaged. This technique is particularly well suited to probe the structure and dynamics in dense colloidal suspensions at the single-particle scale: the particles are large enough to be resolved using visible light and diffuse slowly enough to be captured at typical scan speeds of commercial confocal systems10
. Improvements in scan speeds and analysis algorithms have also enabled quantitative confocal imaging of flowing suspensions11-16,37
. In this paper, we demonstrate confocal microscopy experiments to probe the confined phase behavior and flow properties of colloid-polymer mixtures. We first prepare colloid-polymer mixtures that are density- and refractive-index matched. Next, we report a standard protocol for imaging quiescent dense colloid-polymer mixtures under varying confinement in thin wedge-shaped cells. Finally, we demonstrate a protocol for imaging colloid-polymer mixtures during microchannel flow.
Chemistry, Issue 87, confocal microscopy, particle tracking, colloids, suspensions, confinement, gelation, microfluidics, image correlation, dynamics, suspension flow
Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones
Institutions: Boston College.
Microtubule (MT) plus-end-tracking proteins (+TIPs) localize to the growing plus-ends of MTs and regulate MT dynamics1,2
. One of the most well-known and widely-utilized +TIPs for analyzing MT dynamics is the End-Binding protein, EB1, which binds all growing MT plus-ends, and thus, is a marker for MT polymerization1
. Many studies of EB1 behavior within growth cones have used time-consuming and biased computer-assisted, hand-tracking methods to analyze individual MTs1-3
. Our approach is to quantify global parameters of MT dynamics using the software package, plusTipTracker4
, following the acquisition of high-resolution, live images of tagged EB1 in cultured embryonic growth cones5
. This software is a MATLAB-based, open-source, user-friendly package that combines automated detection, tracking, visualization, and analysis for movies of fluorescently-labeled +TIPs. Here, we present the protocol for using plusTipTracker for the analysis of fluorescently-labeled +TIP comets in cultured Xenopus laevis
growth cones. However, this software can also be used to characterize MT dynamics in various cell types6-8
Molecular Biology, Issue 91, plusTipTracker, microtubule plus-end-tracking proteins, EB1, growth cone, Xenopus laevis, live cell imaging analysis, microtubule dynamics
Deriving the Time Course of Glutamate Clearance with a Deconvolution Analysis of Astrocytic Transporter Currents
Institutions: National Institutes of Health.
The highest density of glutamate transporters in the brain is found in astrocytes. Glutamate transporters couple the movement of glutamate across the membrane with the co-transport of 3 Na+
and 1 H+
and the counter-transport of 1 K+
. The stoichiometric current generated by the transport process can be monitored with whole-cell patch-clamp recordings from astrocytes. The time course of the recorded current is shaped by the time course of the glutamate concentration profile to which astrocytes are exposed, the kinetics of glutamate transporters, and the passive electrotonic properties of astrocytic membranes. Here we describe the experimental and analytical methods that can be used to record glutamate transporter currents in astrocytes and isolate the time course of glutamate clearance from all other factors that shape the waveform of astrocytic transporter currents. The methods described here can be used to estimate the lifetime of flash-uncaged and synaptically-released glutamate at astrocytic membranes in any region of the central nervous system during health and disease.
Neurobiology, Issue 78, Neuroscience, Biochemistry, Molecular Biology, Cellular Biology, Anatomy, Physiology, Biophysics, Astrocytes, Synapses, Glutamic Acid, Membrane Transport Proteins, Astrocytes, glutamate transporters, uptake, clearance, hippocampus, stratum radiatum, CA1, gene, brain, slice, animal model
Measuring Material Microstructure Under Flow Using 1-2 Plane Flow-Small Angle Neutron Scattering
Institutions: University of Delaware, National Institute of Standards and Technology, Institut Laue-Langevin.
A new small-angle neutron scattering (SANS) sample environment optimized for studying the microstructure of complex fluids under simple shear flow is presented. The SANS shear cell consists of a concentric cylinder Couette geometry that is sealed and rotating about a horizontal axis so that the vorticity direction of the flow field is aligned with the neutron beam enabling scattering from the 1-2 plane of shear (velocity-velocity gradient, respectively). This approach is an advance over previous shear cell sample environments as there is a strong coupling between the bulk rheology and microstructural features in the 1-2 plane of shear. Flow-instabilities, such as shear banding, can also be studied by spatially resolved measurements. This is accomplished in this sample environment by using a narrow aperture for the neutron beam and scanning along the velocity gradient direction. Time resolved experiments, such as flow start-ups and large amplitude oscillatory shear flow are also possible by synchronization of the shear motion and time-resolved detection of scattered neutrons. Representative results using the methods outlined here demonstrate the useful nature of spatial resolution for measuring the microstructure of a wormlike micelle solution that exhibits shear banding, a phenomenon that can only be investigated by resolving the structure along the velocity gradient direction. Finally, potential improvements to the current design are discussed along with suggestions for supplementary experiments as motivation for future experiments on a broad range of complex fluids in a variety of shear motions.
Physics, Issue 84, Surfactants, Rheology, Shear Banding, Nanostructure, Neutron Scattering, Complex Fluids, Flow-induced Structure
Formulations for Freeze-drying of Bacteria and Their Influence on Cell Survival
Institutions: Swedish University of Agricultural Sciences, Uppsala University.
Cellular water can be removed to reversibly inactivate microorganisms to facilitate storage. One such method of removal is freeze-drying, which is considered a gentle dehydration method. To facilitate cell survival during drying, the cells are often formulated beforehand. The formulation forms a matrix that embeds the cells and protects them from various harmful stresses imposed on the cells during freezing and drying. We present here a general method to evaluate the survival rate of cells after freeze-drying and we illustrate it by comparing the results obtained with four different formulations: the disaccharide sucrose, the sucrose derived polymer Ficoll PM400, and the respective polysaccharides hydroxyethyl cellulose (HEC) and hydroxypropyl methyl cellulose (HPMC), on two strains of bacteria, P. putida
KT2440 and A. chlorophenolicus
A6. In this work we illustrate how to prepare formulations for freeze-drying and how to investigate the mechanisms of cell survival after rehydration by characterizing the formulation using of differential scanning calorimetry (DSC), surface tension measurements, X-ray analysis, and electron microscopy and relating those data to survival rates. The polymers were chosen to get a monomeric structure of the respective polysaccharide resembling sucrose to a varying degrees. Using this method setup we showed that polymers can support cell survival as effectively as disaccharides if certain physical properties of the formulation are controlled1
Microbiology, Issue 78, Cellular Biology, Molecular Biology, Biochemistry, Biophysics, Basic Protocols, Cell survival, sucrose, polysaccharides, cellulose, Ficoll, freeze-drying, Pseudomonas putida, Arthrobacter chlorophenolicus, cells, cell culture
Flying Insect Detection and Classification with Inexpensive Sensors
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
Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
Institutions: Yale School of Medicine, Yale School of Medicine, New York University , New York University , New York University .
Most of the choices we make have uncertain consequences. In some cases the probabilities for different possible outcomes are precisely known, a condition termed "risky". In other cases when probabilities cannot be estimated, this is a condition described as "ambiguous". While most people are averse to both risk and ambiguity1,2
, the degree of those aversions vary substantially across individuals, such that the subjective value
of the same risky or ambiguous option can be very different for different individuals. We combine functional MRI (fMRI) with an experimental economics-based method3
to assess the neural representation of the subjective values of risky and ambiguous options4
. This technique can be now used to study these neural representations in different populations, such as different age groups and different patient populations.
In our experiment, subjects make consequential choices between two alternatives while their neural activation is tracked using fMRI. On each trial subjects choose between lotteries that vary in their monetary amount and in either the probability of winning that amount or the ambiguity level associated with winning. Our parametric design allows us to use each individual's choice behavior to estimate their attitudes towards risk and ambiguity, and thus to estimate the subjective values that each option held for them. Another important feature of the design is that the outcome of the chosen lottery is not revealed during the experiment, so that no learning can take place, and thus the ambiguous options remain ambiguous and risk attitudes are stable. Instead, at the end of the scanning session one or few trials are randomly selected and played for real money. Since subjects do not know beforehand which trials will be selected, they must treat each and every trial as if it and it alone was the one trial on which they will be paid. This design ensures that we can estimate the true subjective value of each option to each subject. We then look for areas in the brain whose activation is correlated with the subjective value of risky options and for areas whose activation is correlated with the subjective value of ambiguous options.
Neuroscience, Issue 67, Medicine, Molecular Biology, fMRI, magnetic resonance imaging, decision-making, value, uncertainty, risk, ambiguity
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Institutions: Princeton University.
The aim of de novo
protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo
protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.
To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
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
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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
Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study
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
From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
Institutions: Scuola Normale Superiore, Instituto Italiano di Tecnologia, University of California, Irvine.
It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn’t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn
-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.
Bioengineering, Issue 92, fluorescence, protein dynamics, lipid dynamics, membrane heterogeneity, transient confinement, single molecule, GFP
Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
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
Oscillation and Reaction Board Techniques for Estimating Inertial Properties of a Below-knee Prosthesis
Institutions: University of Northern Colorado, Arizona State University, Iowa State University.
The purpose of this study was two-fold: 1) demonstrate a technique that can be used to directly estimate the inertial properties of a below-knee prosthesis, and 2) contrast the effects of the proposed technique and that of using intact limb inertial properties on joint kinetic estimates during walking in unilateral, transtibial amputees. An oscillation and reaction board system was validated and shown to be reliable when measuring inertial properties of known geometrical solids. When direct measurements of inertial properties of the prosthesis were used in inverse dynamics modeling of the lower extremity compared with inertial estimates based on an intact shank and foot, joint kinetics at the hip and knee were significantly lower during the swing phase of walking. Differences in joint kinetics during stance, however, were smaller than those observed during swing. Therefore, researchers focusing on the swing phase of walking should consider the impact of prosthesis inertia property estimates on study outcomes. For stance, either one of the two inertial models investigated in our study would likely lead to similar outcomes with an inverse dynamics assessment.
Bioengineering, Issue 87, prosthesis inertia, amputee locomotion, below-knee prosthesis, transtibial amputee
Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking
Institutions: Yale University, Yale University, Yale University, Yale University, Massachusetts General Hospital, University of California, Irvine.
We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized.
We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters 1-7
. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique 'HYPR' spatial filter 8
that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on 11
C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model 7
to a conventional model 9
. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.
Behavior, Issue 78, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Medicine, Anatomy, Physiology, Image Processing, Computer-Assisted, Receptors, Dopamine, Dopamine, Functional Neuroimaging, Binding, Competitive, mathematical modeling (systems analysis), Neurotransmission, transient, dopamine release, PET, modeling, linear, time-invariant, smoking, F-test, ventral-striatum, clinical techniques
Determination of Protein-ligand Interactions Using Differential Scanning Fluorimetry
Institutions: University of Exeter.
A wide range of methods are currently available for determining the dissociation constant between a protein and interacting small molecules. However, most of these require access to specialist equipment, and often require a degree of expertise to effectively establish reliable experiments and analyze data. Differential scanning fluorimetry (DSF) is being increasingly used as a robust method for initial screening of proteins for interacting small molecules, either for identifying physiological partners or for hit discovery. This technique has the advantage that it requires only a PCR machine suitable for quantitative PCR, and so suitable instrumentation is available in most institutions; an excellent range of protocols are already available; and there are strong precedents in the literature for multiple uses of the method. Past work has proposed several means of calculating dissociation constants from DSF data, but these are mathematically demanding. Here, we demonstrate a method for estimating dissociation constants from a moderate amount of DSF experimental data. These data can typically be collected and analyzed within a single day. We demonstrate how different models can be used to fit data collected from simple binding events, and where cooperative binding or independent binding sites are present. Finally, we present an example of data analysis in a case where standard models do not apply. These methods are illustrated with data collected on commercially available control proteins, and two proteins from our research program. Overall, our method provides a straightforward way for researchers to rapidly gain further insight into protein-ligand interactions using DSF.
Biophysics, Issue 91, differential scanning fluorimetry, dissociation constant, protein-ligand interactions, StepOne, cooperativity, WcbI.
High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain
Institutions: The University of Texas at Austin.
Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon measuring activity on the surface of cerebral cortex rather than in subcortical regions such as midbrain and brainstem. Subcortical fMRI must overcome two challenges: spatial resolution and physiological noise. Here we describe an optimized set of techniques developed to perform high-resolution fMRI in human SC, a structure on the dorsal surface of the midbrain; the methods can also be used to image other brainstem and subcortical structures.
High-resolution (1.2 mm voxels) fMRI of the SC requires a non-conventional approach. The desired spatial sampling is obtained using a multi-shot (interleaved) spiral acquisition1
. Since, T2
* of SC tissue is longer than in cortex, a correspondingly longer echo time (TE
~ 40 msec) is used to maximize functional contrast. To cover the full extent of the SC, 8-10 slices are obtained. For each session a structural anatomy with the same slice prescription as the fMRI is also obtained, which is used to align the functional data to a high-resolution reference volume.
In a separate session, for each subject, we create a high-resolution (0.7 mm sampling) reference volume using a T1
-weighted sequence that gives good tissue contrast. In the reference volume, the midbrain region is segmented using the ITK-SNAP software application2
. This segmentation is used to create a 3D surface representation of the midbrain that is both smooth and accurate3
. The surface vertices and normals are used to create a map of depth from the midbrain surface within the tissue4
Functional data is transformed into the coordinate system of the segmented reference volume. Depth associations of the voxels enable the averaging of fMRI time series data within specified depth ranges to improve signal quality. Data is rendered on the 3D surface for visualization.
In our lab we use this technique for measuring topographic maps of visual stimulation and covert and overt visual attention within the SC1
. As an example, we demonstrate the topographic representation of polar angle to visual stimulation in SC.
Neuroscience, Issue 63, fMRI, midbrain, brainstem, colliculus, BOLD, brain, Magentic Resonance Imaging, MRI
Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Institutions: University of Washington, Iowa State University, North Carolina A&T University, Iowa Geological and Water Survey.
Finding the cost-efficient (i.e.
, lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.
) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization.
Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods3,4,9,10,13-15,17-19,22,23,25
. In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model7
with a multiobjective evolutionary algorithm SPEA226
, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.
Environmental Sciences, Issue 70, Plant Biology, Civil Engineering, Forest Sciences, Water quality, multiobjective optimization, evolutionary algorithms, cost efficiency, agriculture, development
Molecular Evolution of the Tre Recombinase
Institutions: Max Plank Institute for Molecular Cell Biology and Genetics, Dresden.
Here we report the generation of Tre recombinase through directed, molecular evolution. Tre recombinase recognizes a pre-defined target sequence within the LTR sequences of the HIV-1 provirus, resulting in the excision and eradication of the provirus from infected human cells.
We started with Cre, a 38-kDa recombinase, that recognizes a 34-bp double-stranded DNA sequence known as loxP. Because Cre can effectively eliminate genomic sequences, we set out to tailor a recombinase that could remove the sequence between the 5'-LTR and 3'-LTR of an integrated HIV-1 provirus. As a first step we identified sequences within the LTR sites that were similar to loxP and tested for recombination activity. Initially Cre and mutagenized Cre libraries failed to recombine the chosen loxLTR sites of the HIV-1 provirus. As the start of any directed molecular evolution process requires at least residual activity, the original asymmetric loxLTR sequences were split into subsets and tested again for recombination activity. Acting as intermediates, recombination activity was shown with the subsets. Next, recombinase libraries were enriched through reiterative evolution cycles. Subsequently, enriched libraries were shuffled and recombined. The combination of different mutations proved synergistic and recombinases were created that were able to recombine loxLTR1 and loxLTR2. This was evidence that an evolutionary strategy through intermediates can be successful. After a total of 126 evolution cycles individual recombinases were functionally and structurally analyzed. The most active recombinase -- Tre -- had 19 amino acid changes as compared to Cre. Tre recombinase was able to excise the HIV-1 provirus from the genome HIV-1 infected HeLa cells (see "HIV-1 Proviral DNA Excision Using an Evolved Recombinase", Hauber J., Heinrich-Pette-Institute for Experimental Virology and Immunology, Hamburg, Germany). While still in its infancy, directed molecular evolution will allow the creation of custom enzymes that will serve as tools of "molecular surgery" and molecular medicine.
Cell Biology, Issue 15, HIV-1, Tre recombinase, Site-specific recombination, molecular evolution
Functional Mapping with Simultaneous MEG and EEG
Institutions: MGH - Massachusetts General Hospital.
We use magnetoencephalography (MEG) and electroencephalography (EEG) to locate and determine the temporal evolution in brain areas involved in the processing of simple sensory stimuli. We will use somatosensory stimuli to locate the hand somatosensory areas, auditory stimuli to locate the auditory cortices, visual stimuli in four quadrants of the visual field to locate the early visual areas. These type of experiments are used for functional mapping in epileptic and brain tumor patients to locate eloquent cortices. In basic neuroscience similar experimental protocols are used to study the orchestration of cortical activity. The acquisition protocol includes quality assurance procedures, subject preparation for the combined MEG/EEG study, and acquisition of evoked-response data with somatosensory, auditory, and visual stimuli. We also demonstrate analysis of the data using the equivalent current dipole model and cortically-constrained minimum-norm estimates. Anatomical MRI data are employed in the analysis for visualization and for deriving boundaries of tissue boundaries for forward modeling and cortical location and orientation constraints for the minimum-norm estimates.
JoVE neuroscience, Issue 40, neuroscience, brain, MEG, EEG, functional imaging