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.
26 Related JoVE Articles!
Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
Institutions: Schulthess Clinic.
Spatial and temporal characteristics of human walking are frequently evaluated to identify possible gait impairments, mainly in orthopedic and neurological patients1-4
, but also in healthy older adults5,6
. The quantitative gait analysis described in this protocol is performed with a recently-introduced photoelectric system (see Materials table) which has the potential to be used in the clinic because it is portable, easy to set up (no subject preparation is required before a test), and does not require maintenance and sensor calibration. The photoelectric system consists of series of high-density floor-based photoelectric cells with light-emitting and light-receiving diodes that are placed parallel to each other to create a corridor, and are oriented perpendicular to the line of progression7
. The system simply detects interruptions in light signal, for instance due to the presence of feet within the recording area. Temporal gait parameters and 1D spatial coordinates of consecutive steps are subsequently calculated to provide common gait parameters such as step length, single limb support and walking velocity8
, whose validity against a criterion instrument has recently been demonstrated7,9
. The measurement procedures are very straightforward; a single patient can be tested in less than 5 min and a comprehensive report can be generated in less than 1 min.
Medicine, Issue 93, gait analysis, walking, floor-based photocells, spatiotemporal, elderly, orthopedic patients, neurological patients
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Institutions: University of Washington.
Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e
., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g
., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori
, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources.
Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising the sensor data from environmental and physiological contaminants. We will then outline the procedure for combining and mapping MEG/EEG sensor data onto the cortical space, thereby producing a family of time-series of cortical dipole activation on the brain surface (or "brain movies") related to each experimental condition. Finally, we will highlight a few statistical techniques that enable us to make scientific inference across a subject population (i.e
., perform group-level analysis) based on a common cortical coordinate space.
Neuroscience, Issue 68, Magnetoencephalography, MEG, Electroencephalography, EEG, audition, attention, inverse imaging
Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Institutions: Baylor College of Medicine, Michael E. DeBakey VA Medical Center, University of California, Los Angeles, University of California, Los Angeles.
Functional connectivity MRI (fcMRI) is an fMRI method that examines the connectivity of different brain areas based on the correlation of BOLD signal fluctuations over time. Temporal Lobe Epilepsy (TLE) is the most common type of adult epilepsy and involves multiple brain networks. The default mode network (DMN) is involved in conscious, resting state cognition and is thought to be affected in TLE where seizures cause impairment of consciousness. The DMN in epilepsy was examined using seed based fcMRI. The anterior and posterior hubs of the DMN were used as seeds in this analysis. The results show a disconnection between the anterior and posterior hubs of the DMN in TLE during the basal state. In addition, increased DMN connectivity to other brain regions in left TLE along with decreased connectivity in right TLE is revealed. The analysis demonstrates how seed-based fcMRI can be used to probe cerebral networks in brain disorders such as TLE.
Medicine, Issue 90, Default Mode Network (DMN), Temporal Lobe Epilepsy (TLE), fMRI, MRI, functional connectivity MRI (fcMRI), blood oxygenation level dependent (BOLD)
Determination of Lipid Raft Partitioning of Fluorescently-tagged Probes in Living Cells by Fluorescence Correlation Spectroscopy (FCS)
Institutions: Hôpital de la Pitié-Salpêtrière, Université Paris-Sud, Université Paris-Sud.
In the past fifteen years the notion that cell membranes are not homogenous and rely on microdomains to exert their functions has become widely accepted. Lipid rafts are membrane microdomains enriched in cholesterol and sphingolipids. They play a role in cellular physiological processes such as signalling, and trafficking1,2
but are also thought to be key players in several diseases including viral or bacterial infections and neurodegenerative diseases3
Yet their existence is still a matter of controversy4,5
. Indeed, lipid raft size has been estimated to be around 20 nm6
, far under the resolution limit of conventional microscopy (around 200 nm), thus precluding their direct imaging. Up to now, the main techniques used to assess the partition of proteins of interest inside lipid rafts were Detergent Resistant Membranes (DRMs) isolation and co-patching with antibodies. Though widely used because of their rather easy implementation, these techniques were prone to artefacts and thus criticized7,8
. Technical improvements were therefore necessary to overcome these artefacts and to be able to probe lipid rafts partition in living cells.
Here we present a method for the sensitive analysis of lipid rafts partition of fluorescently-tagged proteins or lipids in the plasma membrane of living cells. This method, termed Fluorescence Correlation Spectroscopy (FCS), relies on the disparity in diffusion times of fluorescent probes located inside or outside of lipid rafts. In fact, as evidenced in both artificial membranes and cell cultures, probes would diffuse much faster outside than inside dense lipid rafts9,10
. To determine diffusion times, minute fluorescence fluctuations are measured as a function of time in a focal volume (approximately 1 femtoliter), located at the plasma membrane of cells with a confocal microscope (Fig. 1
). The auto-correlation curves can then be drawn from these fluctuations and fitted with appropriate mathematical diffusion models11
FCS can be used to determine the lipid raft partitioning of various probes, as long as they are fluorescently tagged. Fluorescent tagging can be achieved by expression of fluorescent fusion proteins or by binding of fluorescent ligands. Moreover, FCS can be used not only in artificial membranes and cell lines but also in primary cultures, as described recently12
. It can also be used to follow the dynamics of lipid raft partitioning after drug addition or membrane lipid composition change12
Cellular Biology, Issue 62, Lipid rafts, plasma membrane, diffusion times, confocal microscopy, fluorescence correlation spectroscopy (FCS)
A Parasite Rescue and Transformation Assay for Antileishmanial Screening Against Intracellular Leishmania donovani Amastigotes in THP1 Human Acute Monocytic Leukemia Cell Line
Institutions: University of Mississippi, University of Mississippi.
Leishmaniasis is one of the world's most neglected diseases, largely affecting the poorest of the poor, mainly in developing countries. Over 350 million people are considered at risk of contracting leishmaniasis, and approximately 2 million new cases occur yearly1
. Leishmania donovani
is the causative agent for visceral leishmaniasis (VL), the most fatal form of the disease. The choice of drugs available to treat leishmaniasis is limited 2
;current treatments provide limited efficacy and many are toxic at therapeutic doses. In addition, most of the first line treatment drugs have already lost their utility due to increasing multiple drug resistance 3
. The current pipeline of anti-leishmanial drugs is also severely depleted. Sustained efforts are needed to enrich a new anti-leishmanial drug discovery pipeline, and this endeavor relies on the availability of suitable in vitro
and axenic amastigotes assays5
are primarily used for anti-leishmanial drug screening however, may not be appropriate due to significant cellular, physiological, biochemical and molecular differences in comparison to intracellular amastigotes. Assays with macrophage-amastigotes models are considered closest to the pathophysiological conditions of leishmaniasis, and are therefore the most appropriate for in vitro
screening. Differentiated, non-dividing human acute monocytic leukemia cells (THP1) (make an attractive) alternative to isolated primary macrophages and can be used for assaying anti-leishmanial activity of different compounds against intracellular amastigotes.
Here, we present a parasite-rescue and transformation assay with differentiated THP1 cells infected in vitro
with Leishmania donovani
for screening pure compounds and natural products extracts and determining the efficacy against the intracellular Leishmania
amastigotes. The assay involves the following steps: (1) differentiation of THP1 cells to non-dividing macrophages, (2) infection of macrophages with L. donovani
metacyclic promastigotes, (3) treatment of infected cells with test drugs, (4) controlled lysis of infected macrophages, (5) release/rescue of amastigotes and (6) transformation of live amastigotes to promastigotes. The assay was optimized using detergent treatment for controlled lysis of Leishmania
-infected THP1 cells to achieve almost complete rescue of viable intracellular amastigotes with minimal effect on their ability to transform to promastigotes. Different macrophage:promastigotes ratios were tested to achieve maximum infection. Quantification of the infection was performed through transformation of live, rescued Leishmania
amastigotes to promastigotes and evaluation of their growth by an alamarBlue fluorometric assay in 96-well microplates. This assay is comparable to the currently-used microscopic, transgenic reporter gene and digital-image analysis assays. This assay is robust and measures only the live intracellular amastigotes compared to reporter gene and image analysis assays, which may not differentiate between live and dead amastigotes. Also, the assay has been validated with a current panel of anti-leishmanial drugs and has been successfully applied to large-scale screening of pure compounds and a library of natural products fractions (Tekwani et al.
Infection, Issue 70, Immunology, Infectious Diseases, Molecular Biology, Cellular Biology, Pharmacology, Leishmania donovani, Visceral Leishmaniasis, THP1 cells, Drug Screening, Amastigotes, Antileishmanial drug assay
Measuring Intracellular Ca2+ Changes in Human Sperm using Four Techniques: Conventional Fluorometry, Stopped Flow Fluorometry, Flow Cytometry and Single Cell Imaging
Institutions: Instituto de Biotecnología-Universidad Nacional Autónoma de México, Edison State College.
Spermatozoa are male reproductive cells especially designed to reach, recognize and fuse with the egg. To perform these tasks, sperm cells must be prepared to face a constantly changing environment and to overcome several physical barriers. Being in essence transcriptionally and translationally silent, these motile cells rely profoundly on diverse signaling mechanisms to orient themselves and swim in a directed fashion, and to contend with challenging environmental conditions during their journey to find the egg. In particular, Ca2+
-mediated signaling is pivotal for several sperm functions: activation of motility, capacitation (a complex process that prepares sperm for the acrosome reaction) and the acrosome reaction (an exocytotic event that allows sperm-egg fusion). The use of fluorescent dyes to track intracellular fluctuations of this ion is of remarkable importance due to their ease of application, sensitivity, and versatility of detection. Using one single dye-loading protocol we utilize four different fluorometric techniques to monitor sperm Ca2+
dynamics. Each technique provides distinct information that enables spatial and/or temporal resolution, generating data both at single cell and cell population levels.
Cellular Biology, Issue 75, Medicine, Molecular Biology, Genetics, Biophysics, Anatomy, Physiology, Spermatozoa, Ion Channels, Cell Physiological Processes, Calcium Signaling, Reproductive Physiological Processes, fluorometry, Flow cytometry, stopped flow fluorometry, single-cell imaging, human sperm, sperm physiology, intracellular Ca2+, Ca2+ signaling, Ca2+ imaging, fluorescent dyes, imaging
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
Establishment of an In vitro System to Study Intracellular Behavior of Candida glabrata in Human THP-1 Macrophages
Institutions: Centre for DNA Fingerprinting and Diagnostics, Andhra Pradesh, India, Fiers-Schell-Van Montagu Building, Technologiepark 927, B-9052 Ghent (Zwijnaarde), Belgium.
A cell culture model system, if a close mimic of host environmental conditions, can serve as an inexpensive, reproducible and easily manipulatable alternative to animal model systems for the study of a specific step of microbial pathogen infection. A human monocytic cell line THP-1 which, upon phorbol ester treatment, is differentiated into macrophages, has previously been used to study virulence strategies of many intracellular pathogens including Mycobacterium tuberculosis.
Here, we discuss a protocol to enact an in vitro
cell culture model system using THP-1 macrophages to delineate the interaction of an opportunistic human yeast pathogen Candida glabrata
with host phagocytic cells. This model system is simple, fast, amenable to high-throughput mutant screens, and requires no sophisticated equipment. A typical THP-1 macrophage infection experiment takes approximately 24 hr with an additional 24-48 hr to allow recovered intracellular yeast to grow on rich medium for colony forming unit-based viability analysis. Like other in vitro
model systems, a possible limitation of this approach is difficulty in extrapolating the results obtained to a highly complex immune cell circuitry existing in the human host. However, despite this, the current protocol is very useful to elucidate the strategies that a fungal pathogen may employ to evade/counteract antimicrobial response and survive, adapt, and proliferate in the nutrient-poor environment of host immune cells.
Immunology, Issue 82, Candida glabrata, THP-1 macrophages, colony forming unit (CFU) assay, fluorescence microscopy, signature-tagged mutagenesis
A Tactile Automated Passive-Finger Stimulator (TAPS)
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
A Practical Guide to Phylogenetics for Nonexperts
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
A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures
Institutions: University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign.
The present paper describes a comprehensive protocol for manual tracing of the set of brain regions comprising the medial temporal lobe (MTL): amygdala, hippocampus, and the associated parahippocampal regions (perirhinal, entorhinal, and parahippocampal proper). Unlike most other tracing protocols available, typically focusing on certain MTL areas (e.g.
, amygdala and/or hippocampus), the integrative perspective adopted by the present tracing guidelines allows for clear localization of all MTL subregions. By integrating information from a variety of sources, including extant tracing protocols separately targeting various MTL structures, histological reports, and brain atlases, and with the complement of illustrative visual materials, the present protocol provides an accurate, intuitive, and convenient guide for understanding the MTL anatomy. The need for such tracing guidelines is also emphasized by illustrating possible differences between automatic and manual segmentation protocols. This knowledge can be applied toward research involving not only structural MRI investigations but also structural-functional colocalization and fMRI signal extraction from anatomically defined ROIs, in healthy and clinical groups alike.
Neuroscience, Issue 89, Anatomy, Segmentation, Medial Temporal Lobe, MRI, Manual Tracing, Amygdala, Hippocampus, Perirhinal Cortex, Entorhinal Cortex, Parahippocampal Cortex
Three Dimensional Cultures: A Tool To Study Normal Acinar Architecture vs. Malignant Transformation Of Breast Cells
Institutions: University of Michigan Comprehensive Cancer Center, University of Michigan Comprehensive Cancer Center.
Invasive breast carcinomas are a group of malignant epithelial tumors characterized by the invasion of adjacent tissues and propensity to metastasize. The interplay of signals between cancer cells and their microenvironment exerts a powerful influence on breast cancer growth and biological behavior1
. However, most of these signals from the extracellular matrix are lost or their relevance is understudied when cells are grown in two dimensional culture (2D) as a monolayer. In recent years, three dimensional (3D) culture on a reconstituted basement membrane has emerged as a method of choice to recapitulate the tissue architecture of benign and malignant breast cells. Cells grown in 3D retain the important cues from the extracellular matrix and provide a physiologically relevant ex vivo
. Of note, there is growing evidence suggesting that cells behave differently when grown in 3D as compared to 2D4
. 3D culture can be effectively used as a means to differentiate the malignant phenotype from the benign breast phenotype and for underpinning the cellular and molecular signaling involved3
. One of the distinguishing characteristics of benign epithelial cells is that they are polarized so that the apical cytoplasm is towards the lumen and the basal cytoplasm rests on the basement membrane. This apico-basal polarity is lost in invasive breast carcinomas, which are characterized by cellular disorganization and formation of anastomosing and branching tubules that haphazardly infiltrates the surrounding stroma. These histopathological differences between benign gland and invasive carcinoma can be reproduced in 3D6,7
. Using the appropriate read-outs like the quantitation of single round acinar structures, or differential expression of validated molecular markers for cell proliferation, polarity and apoptosis in combination with other molecular and cell biology techniques, 3D culture can provide an important tool to better understand the cellular changes during malignant transformation and for delineating the responsible signaling.
Medicine, Issue 86, pathological conditions, signs and symptoms, neoplasms, three dimensional cultures, Matrigel, breast cells, malignant phenotype, signaling
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
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 (https://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
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
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
Trajectory Data Analyses for Pedestrian Space-time Activity Study
Institutions: Kean University, University of Wisconsin-Madison.
It is well recognized that human movement in the spatial and temporal dimensions has direct influence on disease transmission1-3
. An infectious disease typically spreads via contact between infected and susceptible individuals in their overlapped activity spaces. Therefore, daily mobility-activity information can be used as an indicator to measure exposures to risk factors of infection. However, a major difficulty and thus the reason for paucity of studies of infectious disease transmission at the micro scale arise from the lack of detailed individual mobility data. Previously in transportation and tourism research detailed space-time activity data often relied on the time-space diary technique, which requires subjects to actively record their activities in time and space. This is highly demanding for the participants and collaboration from the participants greatly affects the quality of data4
Modern technologies such as GPS and mobile communications have made possible the automatic collection of trajectory data. The data collected, however, is not ideal for modeling human space-time activities, limited by the accuracies of existing devices. There is also no readily available tool for efficient processing of the data for human behavior study. We present here a suite of methods and an integrated ArcGIS desktop-based visual interface for the pre-processing and spatiotemporal analyses of trajectory data. We provide examples of how such processing may be used to model human space-time activities, especially with error-rich pedestrian trajectory data, that could be useful in public health studies such as infectious disease transmission modeling.
The procedure presented includes pre-processing, trajectory segmentation, activity space characterization, density estimation and visualization, and a few other exploratory analysis methods. Pre-processing is the cleaning of noisy raw trajectory data. We introduce an interactive visual pre-processing interface as well as an automatic module. Trajectory segmentation5
involves the identification of indoor and outdoor parts from pre-processed space-time tracks. Again, both interactive visual segmentation and automatic segmentation are supported. Segmented space-time tracks are then analyzed to derive characteristics of one's activity space such as activity radius etc.
Density estimation and visualization are used to examine large amount of trajectory data to model hot spots and interactions. We demonstrate both density surface mapping6
and density volume rendering7
. We also include a couple of other exploratory data analyses (EDA) and visualizations tools, such as Google Earth animation support and connection analysis. The suite of analytical as well as visual methods presented in this paper may be applied to any trajectory data for space-time activity studies.
Environmental Sciences, Issue 72, Computer Science, Behavior, Infectious Diseases, Geography, Cartography, Data Display, Disease Outbreaks, cartography, human behavior, Trajectory data, space-time activity, GPS, GIS, ArcGIS, spatiotemporal analysis, visualization, segmentation, density surface, density volume, exploratory data analysis, modelling
Modeling Mucosal Candidiasis in Larval Zebrafish by Swimbladder Injection
Institutions: University of Maine, University of Maine.
Early defense against mucosal pathogens consists of both an epithelial barrier and innate immune cells. The immunocompetency of both, and their intercommunication, are paramount for the protection against infections. The interactions of epithelial and innate immune cells with a pathogen are best investigated in vivo
, where complex behavior unfolds over time and space. However, existing models do not allow for easy spatio-temporal imaging of the battle with pathogens at the mucosal level.
The model developed here creates a mucosal infection by direct injection of the fungal pathogen, Candida albicans
, into the swimbladder of juvenile zebrafish. The resulting infection enables high-resolution imaging of epithelial and innate immune cell behavior throughout the development of mucosal disease. The versatility of this method allows for interrogation of the host to probe the detailed sequence of immune events leading to phagocyte recruitment and to examine the roles of particular cell types and molecular pathways in protection. In addition, the behavior of the pathogen as a function of immune attack can be imaged simultaneously by using fluorescent protein-expressing C. albicans
. Increased spatial resolution of the host-pathogen interaction is also possible using the described rapid swimbladder dissection technique.
The mucosal infection model described here is straightforward and highly reproducible, making it a valuable tool for the study of mucosal candidiasis. This system may also be broadly translatable to other mucosal pathogens such as mycobacterial, bacterial or viral microbes that normally infect through epithelial surfaces.
Immunology, Issue 93, Zebrafish, mucosal candidiasis, mucosal infection, epithelial barrier, epithelial cells, innate immunity, swimbladder, Candida albicans, in vivo.
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
Cortical Source Analysis of High-Density EEG Recordings in Children
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1
. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2
, because the composition and spatial configuration of head tissues changes dramatically over development3
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials
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
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
Institutions: University of Zurich.
Mori's Uncanny Valley Hypothesis1,2
proposes that the perception of humanlike characters such as robots and, by extension, avatars (computer-generated characters) can evoke negative or positive affect (valence) depending on the object's degree of visual and behavioral realism along a dimension of human likeness
) (Figure 1
). But studies of affective valence of subjective responses to variously realistic non-human characters have produced inconsistent findings 3, 4, 5, 6
. One of a number of reasons for this is that human likeness is not perceived as the hypothesis assumes. While the DHL can be defined following Mori's description as a smooth linear change in the degree of physical humanlike similarity, subjective perception of objects along the DHL can be understood in terms of the psychological effects of categorical perception (CP) 7
. Further behavioral and neuroimaging investigations of category processing and CP along the DHL and of the potential influence of the dimension's underlying category structure on affective experience are needed. This protocol therefore focuses on the DHL and allows examination of CP. Based on the protocol presented in the video as an example, issues surrounding the methodology in the protocol and the use in "uncanny" research of stimuli drawn from morph continua to represent the DHL are discussed in the article that accompanies the video. The use of neuroimaging and morph stimuli to represent the DHL in order to disentangle brain regions neurally responsive to physical human-like similarity from those responsive to category change and category processing is briefly illustrated.
Behavior, Issue 76, Neuroscience, Neurobiology, Molecular Biology, Psychology, Neuropsychology, uncanny valley, functional magnetic resonance imaging, fMRI, categorical perception, virtual reality, avatar, human likeness, Mori, uncanny valley hypothesis, perception, magnetic resonance imaging, MRI, imaging, clinical techniques
Basics of Multivariate Analysis in Neuroimaging Data
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9
. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
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
Yeast Colony Embedding Method
Institutions: University of Missouri - Kansas City.
Patterning of different cell types in embryos is a key mechanism in metazoan development. Communities of microorganisms, such as colonies and biofilms also display patterns of cell types. For example, in the yeast S. cerevisiae
, sporulated cells and pseudohyphal cells are not uniformly distributed in colonies. The functional importance of patterning and the molecular mechanisms that underlie these patterns are still poorly understood.
One challenge with respect to investigating patterns of cell types in fungal colonies is that unlike metazoan tissue, cells in colonies are relatively weakly attached to one another. In particular, fungal colonies do not contain the same extensive level of extracellular matrix found in most tissues . Here we report on a method for embedding and sectioning yeast colonies that reveals the interior patterns of cell types in these colonies. The method can be used to prepare thick sections (0.5 μ) useful for light microscopy and thin sections (0.1 μ) suitable for transmission electron microscopy. Asci and pseudohyphal cells can easily be distinguished from ovoid yeast cells by light microscopy , while the interior structure of these cells can be visualized by EM.
The method is based on surrounding colonies with agar, infiltrating them with Spurr's medium, and then sectioning. Colonies with a diameter in the range of 1-2 mm are suitable for this protocol. In addition to visualizing the interior of colonies, the method allows visualization of the region of the colony that invades the underlying agar.
Cellular Biology, Issue 49, yeast, Saccharomyces cerevisiae, colony, embedding, sporulation, pattern formation, organization
Brain Imaging Investigation of the Neural Correlates of Observing Virtual Social Interactions
Institutions: University of Alberta, University of Illinois, University of Alberta, University of Alberta, University of Alberta, University of Illinois at Urbana-Champaign, University of Illinois at Urbana-Champaign.
The ability to gauge social interactions is crucial in the assessment of others’ intentions. Factors such as facial expressions and body language affect our decisions in personal and professional life alike 1
. These "friend or foe
" judgements are often based on first impressions, which in turn may affect our decisions to "approach or avoid
". Previous studies investigating the neural correlates of social cognition tended to use static facial stimuli 2
. Here, we illustrate an experimental design in which whole-body animated characters were used in conjunction with functional magnetic resonance imaging (fMRI) recordings. Fifteen participants were presented with short movie-clips of guest-host interactions in a business setting, while fMRI data were recorded; at the end of each movie, participants also provided ratings of the host behaviour. This design mimics more closely real-life situations, and hence may contribute to better understanding of the neural mechanisms of social interactions in healthy behaviour, and to gaining insight into possible causes of deficits in social behaviour in such clinical conditions as social anxiety and autism 3
Neuroscience, Issue 53, Social Perception, Social Knowledge, Social Cognition Network, Non-Verbal Communication, Decision-Making, Event-Related fMRI