The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
23 Related JoVE Articles!
A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
Institutions: University of Western Ontario.
The ability to adjust behavior to sudden changes in the environment develops gradually in childhood and adolescence. For example, in the Dimensional Change Card Sort task, participants switch from sorting cards one way, such as shape, to sorting them a different way, such as color. Adjusting behavior in this way exacts a small performance cost, or switch cost, such that responses are typically slower and more error-prone on switch trials in which the sorting rule changes as compared to repeat trials in which the sorting rule remains the same. The ability to flexibly adjust behavior is often said to develop gradually, in part because behavioral costs such as switch costs typically decrease with increasing age. Why aspects of higher-order cognition, such as behavioral flexibility, develop so gradually remains an open question. One hypothesis is that these changes occur in association with functional changes in broad-scale cognitive control networks. On this view, complex mental operations, such as switching, involve rapid interactions between several distributed brain regions, including those that update and maintain task rules, re-orient attention, and select behaviors. With development, functional connections between these regions strengthen, leading to faster and more efficient switching operations. The current video describes a method of testing this hypothesis through the collection and multivariate analysis of fMRI data from participants of different ages.
Behavior, Issue 87, Neurosciences, fMRI, Cognitive Control, Development, Functional Connectivity
An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
Institutions: University of Oxford.
The number of significant genetic associations with common complex traits is constantly increasing. However, most of these associations have not been understood at molecular level. One of the mechanisms mediating the effect of DNA variants on phenotypes is gene expression, which has been shown to be particularly relevant for complex traits1
This method tests in a cellular context the effect of specific DNA sequences on gene expression. The principle is to measure the relative abundance of transcripts arising from the two alleles of a gene, analysing cells which carry one copy of the DNA sequences associated with disease (the risk variants)2,3
. Therefore, the cells used for this method should meet two fundamental genotypic requirements: they have to be heterozygous both for DNA risk variants and for DNA markers, typically coding polymorphisms, which can distinguish transcripts based on their chromosomal origin (Figure 1). DNA risk variants and DNA markers do not need to have the same allele frequency but the phase (haplotypic) relationship of the genetic markers needs to be understood. It is also important to choose cell types which express the gene of interest. This protocol refers specifically to the procedure adopted to extract nucleic acids from fibroblasts but the method is equally applicable to other cells types including primary cells.
DNA and RNA are extracted from the selected cell lines and cDNA is generated. DNA and cDNA are analysed with a primer extension assay, designed to target the coding DNA markers4
. The primer extension assay is carried out using the MassARRAY (Sequenom)5
platform according to the manufacturer's specifications. Primer extension products are then analysed by matrix-assisted laser desorption/ionization time of-flight mass spectrometry (MALDI-TOF/MS). Because the selected markers are heterozygous they will generate two peaks on the MS profiles. The area of each peak is proportional to the transcript abundance and can be measured with a function of the MassARRAY Typer software to generate an allelic ratio (allele 1: allele 2) calculation. The allelic ratio obtained for cDNA is normalized using that measured from genomic DNA, where the allelic ratio is expected to be 1:1 to correct for technical artifacts. Markers with a normalised allelic ratio significantly different to 1 indicate that the amount of transcript generated from the two chromosomes in the same cell is different, suggesting that the DNA variants associated with the phenotype have an effect on gene expression. Experimental controls should be used to confirm the results.
Cellular Biology, Issue 45, Gene expression, regulatory variant, haplotype, association study, primer extension, MALDI-TOF mass spectrometry, single nucleotide polymorphism, allele-specific
Automated Interactive Video Playback for Studies of Animal Communication
Institutions: Texas A&M University (TAMU), Texas A&M University (TAMU).
Video playback is a widely-used technique for the controlled manipulation and presentation of visual signals in animal communication. In particular, parameter-based computer animation offers the opportunity to independently manipulate any number of behavioral, morphological, or spectral characteristics in the context of realistic, moving images of animals on screen. A major limitation of conventional playback, however, is that the visual stimulus lacks the ability to interact with the live animal. Borrowing from video-game technology, we have created an automated, interactive system for video playback that controls animations in response to real-time signals from a video tracking system. We demonstrated this method by conducting mate-choice trials on female swordtail fish, Xiphophorus birchmanni
. Females were given a simultaneous choice between a courting male conspecific and a courting male heterospecific (X. malinche
) on opposite sides of an aquarium. The virtual male stimulus was programmed to track the horizontal position of the female, as courting males do in the wild. Mate-choice trials on wild-caught X. birchmanni
females were used to validate the prototype's ability to effectively generate a realistic visual stimulus.
Neuroscience, Issue 48, Computer animation, visual communication, mate choice, Xiphophorus birchmanni, tracking
Detection of the Genome and Transcripts of a Persistent DNA Virus in Neuronal Tissues by Fluorescent In situ Hybridization Combined with Immunostaining
Institutions: CNRS UMR 5534, Université de Lyon 1, LabEX DEVweCAN, CNRS UPR 3296, CNRS UMR 5286.
Single cell codetection of a gene, its RNA product and cellular regulatory proteins is critical to study gene expression regulation. This is a challenge in the field of virology; in particular for nuclear-replicating persistent DNA viruses that involve animal models for their study. Herpes simplex virus type 1 (HSV-1) establishes a life-long latent infection in peripheral neurons. Latent virus serves as reservoir, from which it reactivates and induces a new herpetic episode. The cell biology of HSV-1 latency remains poorly understood, in part due to the lack of methods to detect HSV-1 genomes in situ
in animal models. We describe a DNA-fluorescent in situ
hybridization (FISH) approach efficiently detecting low-copy viral genomes within sections of neuronal tissues from infected animal models. The method relies on heat-based antigen unmasking, and directly labeled home-made DNA probes, or commercially available probes. We developed a triple staining approach, combining DNA-FISH with RNA-FISH and immunofluorescence, using peroxidase based signal amplification to accommodate each staining requirement. A major improvement is the ability to obtain, within 10 µm tissue sections, low-background signals that can be imaged at high resolution by confocal microscopy and wide-field conventional epifluorescence. Additionally, the triple staining worked with a wide range of antibodies directed against cellular and viral proteins. The complete protocol takes 2.5 days to accommodate antibody and probe penetration within the tissue.
Neuroscience, Issue 83, Life Sciences (General), Virology, Herpes Simplex Virus (HSV), Latency, In situ hybridization, Nuclear organization, Gene expression, Microscopy
A Restriction Enzyme Based Cloning Method to Assess the In vitro Replication Capacity of HIV-1 Subtype C Gag-MJ4 Chimeric Viruses
Institutions: Emory University, Emory University.
The protective effect of many HLA class I alleles on HIV-1 pathogenesis and disease progression is, in part, attributed to their ability to target conserved portions of the HIV-1 genome that escape with difficulty. Sequence changes attributed to cellular immune pressure arise across the genome during infection, and if found within conserved regions of the genome such as Gag, can affect the ability of the virus to replicate in vitro
. Transmission of HLA-linked polymorphisms in Gag to HLA-mismatched recipients has been associated with reduced set point viral loads. We hypothesized this may be due to a reduced replication capacity of the virus. Here we present a novel method for assessing the in vitro
replication of HIV-1 as influenced by the gag
gene isolated from acute time points from subtype C infected Zambians. This method uses restriction enzyme based cloning to insert the gag
gene into a common subtype C HIV-1 proviral backbone, MJ4. This makes it more appropriate to the study of subtype C sequences than previous recombination based methods that have assessed the in vitro
replication of chronically derived gag-pro
sequences. Nevertheless, the protocol could be readily modified for studies of viruses from other subtypes. Moreover, this protocol details a robust and reproducible method for assessing the replication capacity of the Gag-MJ4 chimeric viruses on a CEM-based T cell line. This method was utilized for the study of Gag-MJ4 chimeric viruses derived from 149 subtype C acutely infected Zambians, and has allowed for the identification of residues in Gag that affect replication. More importantly, the implementation of this technique has facilitated a deeper understanding of how viral replication defines parameters of early HIV-1 pathogenesis such as set point viral load and longitudinal CD4+ T cell decline.
Infectious Diseases, Issue 90, HIV-1, Gag, viral replication, replication capacity, viral fitness, MJ4, CEM, GXR25
Infinium Assay for Large-scale SNP Genotyping Applications
Institutions: Oklahoma Medical Research Foundation.
Genotyping variants in the human genome has proven to be an efficient method to identify genetic associations with phenotypes. The distribution of variants within families or populations can facilitate identification of the genetic factors of disease. Illumina's panel of genotyping BeadChips allows investigators to genotype thousands or millions of single nucleotide polymorphisms (SNPs) or to analyze other genomic variants, such as copy number, across a large number of DNA samples. These SNPs can be spread throughout the genome or targeted in specific regions in order to maximize potential discovery. The Infinium assay has been optimized to yield high-quality, accurate results quickly. With proper setup, a single technician can process from a few hundred to over a thousand DNA samples per week, depending on the type of array. This assay guides users through every step, starting with genomic DNA and ending with the scanning of the array. Using propriety reagents, samples are amplified, fragmented, precipitated, resuspended, hybridized to the chip, extended by a single base, stained, and scanned on either an iScan or Hi Scan high-resolution optical imaging system. One overnight step is required to amplify the DNA. The DNA is denatured and isothermally amplified by whole-genome amplification; therefore, no PCR is required. Samples are hybridized to the arrays during a second overnight step. By the third day, the samples are ready to be scanned and analyzed. Amplified DNA may be stockpiled in large quantities, allowing bead arrays to be processed every day of the week, thereby maximizing throughput.
Basic Protocol, Issue 81, genomics, SNP, Genotyping, Infinium, iScan, HiScan, Illumina
Analysis of Nephron Composition and Function in the Adult Zebrafish Kidney
Institutions: University of Notre Dame.
The zebrafish model has emerged as a relevant system to study kidney development, regeneration and disease. Both the embryonic and adult zebrafish kidneys are composed of functional units known as nephrons, which are highly conserved with other vertebrates, including mammals. Research in zebrafish has recently demonstrated that two distinctive phenomena transpire after adult nephrons incur damage: first, there is robust regeneration within existing nephrons that replaces the destroyed tubule epithelial cells; second, entirely new nephrons are produced from renal progenitors in a process known as neonephrogenesis. In contrast, humans and other mammals seem to have only a limited ability for nephron epithelial regeneration. To date, the mechanisms responsible for these kidney regeneration phenomena remain poorly understood. Since adult zebrafish kidneys undergo both nephron epithelial regeneration and neonephrogenesis, they provide an outstanding experimental paradigm to study these events. Further, there is a wide range of genetic and pharmacological tools available in the zebrafish model that can be used to delineate the cellular and molecular mechanisms that regulate renal regeneration. One essential aspect of such research is the evaluation of nephron structure and function. This protocol describes a set of labeling techniques that can be used to gauge renal composition and test nephron functionality in the adult zebrafish kidney. Thus, these methods are widely applicable to the future phenotypic characterization of adult zebrafish kidney injury paradigms, which include but are not limited to, nephrotoxicant exposure regimes or genetic methods of targeted cell death such as the nitroreductase mediated cell ablation technique. Further, these methods could be used to study genetic perturbations in adult kidney formation and could also be applied to assess renal status during chronic disease modeling.
Cellular Biology, Issue 90,
zebrafish; kidney; nephron; nephrology; renal; regeneration; proximal tubule; distal tubule; segment; mesonephros; physiology; acute kidney injury (AKI)
Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
Institutions: New York University School of Medicine, New York University Center for Health Informatics and Bioinformatics, NYU Cancer Institute, Yale University School of Medicine .
Fluorescent in situ
hybridization using DNA probes on 3-dimensionally preserved nuclei followed by 3D confocal microscopy (3D DNA FISH) represents the most direct way to visualize the location of gene loci, chromosomal sub-regions or entire territories in individual cells. This type of analysis provides insight into the global architecture of the nucleus as well as the behavior of specific genomic loci and regions within the nuclear space. Immunofluorescence, on the other hand, permits the detection of nuclear proteins (modified histones, histone variants and modifiers, transcription machinery and factors, nuclear sub-compartments, etc). The major challenge in combining immunofluorescence and 3D DNA FISH is, on the one hand to preserve the epitope detected by the antibody as well as the 3D architecture of the nucleus, and on the other hand, to allow the penetration of the DNA probe to detect gene loci or chromosome territories 1-5
. Here we provide a protocol that combines visualization of chromatin modifications with genomic loci in 3D preserved nuclei.
Genetics, Issue 72, Molecular Biology, Bioinformatics, Cancer Biology, Pathology, Biomedical Engineering, Immunology, Intranuclear Space, Nuclear Matrix, Fluorescence in situ Hybridization, FISH, 3D DNA FISH, DNA, immunofluorescence, immuno-FISH, 3D microscopy, Nuclear organization, interphase nuclei, chromatin modifications
Isolation of mRNAs Associated with Yeast Mitochondria to Study Mechanisms of Localized Translation
Institutions: Technion - Israel Institute of Technology.
Most of mitochondrial proteins are encoded in the nucleus and need to be imported into the organelle. Import may occur while the protein is synthesized near the mitochondria. Support for this possibility is derived from recent studies, in which many mRNAs encoding mitochondrial proteins were shown to be localized to the mitochondria vicinity. Together with earlier demonstrations of ribosomes’ association with the outer membrane, these results suggest a localized translation process. Such localized translation may improve import efficiency, provide unique regulation sites and minimize cases of ectopic expression. Diverse methods have been used to characterize the factors and elements that mediate localized translation. Standard among these is subcellular fractionation by differential centrifugation. This protocol has the advantage of isolation of mRNAs, ribosomes and proteins in a single procedure. These can then be characterized by various molecular and biochemical methods. Furthermore, transcriptomics and proteomics methods can be applied to the resulting material, thereby allow genome-wide insights. The utilization of yeast as a model organism for such studies has the advantages of speed, costs and simplicity. Furthermore, the advanced genetic tools and available deletion strains facilitate verification of candidate factors.
Biochemistry, Issue 85, mitochondria, mRNA localization, Yeast, S. cerevisiae, microarray, localized translation, biochemical fractionation
Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale
Institutions: McGill University, Karolinska Institutet, McGill University.
mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. Accordingly, dysregulation of mRNA translation is considered to play a major role in a variety of pathological states including cancer. Ribosomes also host chaperones, which facilitate folding of nascent polypeptides, thereby modulating function and stability of newly synthesized polypeptides. In addition, emerging data indicate that ribosomes serve as a platform for a repertoire of signaling molecules, which are implicated in a variety of post-translational modifications of newly synthesized polypeptides as they emerge from the ribosome, and/or components of translational machinery. Herein, a well-established method of ribosome fractionation using sucrose density gradient centrifugation is described. In conjunction with the in-house developed “anota” algorithm this method allows direct determination of differential translation of individual mRNAs on a genome-wide scale. Moreover, this versatile protocol can be used for a variety of biochemical studies aiming to dissect the function of ribosome-associated protein complexes, including those that play a central role in folding and degradation of newly synthesized polypeptides.
Biochemistry, Issue 87, Cells, Eukaryota, Nutritional and Metabolic Diseases, Neoplasms, Metabolic Phenomena, Cell Physiological Phenomena, mRNA translation, ribosomes,
protein synthesis, genome-wide analysis, translatome, mTOR, eIF4E, 4E-BP1
Experimental Manipulation of Body Size to Estimate Morphological Scaling Relationships in Drosophila
Institutions: University of Houston, Michigan State University.
The scaling of body parts is a central feature of animal morphology1-7
. Within species, morphological traits need to be correctly proportioned to the body for the organism to function; larger individuals typically have larger body parts and smaller individuals generally have smaller body parts, such that overall body shape is maintained across a range of adult body sizes. The requirement for correct proportions means that individuals within species usually exhibit low variation in relative trait size. In contrast, relative trait size can vary dramatically among species and is a primary mechanism by which morphological diversity is produced. Over a century of comparative work has established these intra- and interspecific patterns3,4
Perhaps the most widely used approach to describe this variation is to calculate the scaling relationship between the size of two morphological traits using the allometric equation y=bxα, where x and y are the size of the two traits, such as organ and body size8,9
. This equation describes the within-group (e.g., species, population) scaling relationship between two traits as both vary in size. Log-transformation of this equation produces a simple linear equation, log(y) = log(b) + αlog(x) and log-log plots of the size of different traits among individuals of the same species typically reveal linear scaling with an intercept of log(b) and a slope of α, called the 'allometric coefficient'9,10
. Morphological variation among groups is described by differences in scaling relationship intercepts or slopes for a given trait pair. Consequently, variation in the parameters of the allometric equation (b and α) elegantly describes the shape variation captured in the relationship between organ and body size within and among biological groups (see 11,12
Not all traits scale linearly with each other or with body size (e.g., 13,14
) Hence, morphological scaling relationships are most informative when the data are taken from the full range of trait sizes. Here we describe how simple experimental manipulation of diet can be used to produce the full range of body size in insects. This permits an estimation of the full scaling relationship for any given pair of traits, allowing a complete description of how shape covaries with size and a robust comparison of scaling relationship parameters among biological groups. Although we focus on Drosophila
, our methodology should be applicable to nearly any fully metamorphic insect.
Developmental Biology, Issue 56, Drosophila, allometry, morphology, body size, scaling, insect
Generation of High Quality Chromatin Immunoprecipitation DNA Template for High-throughput Sequencing (ChIP-seq)
Institutions: Children's Hospital of Philadelphia Research Institute, University of Pennsylvania .
ChIP-sequencing (ChIP-seq) methods directly offer whole-genome coverage, where combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing can be utilized to identify the repertoire of mammalian DNA sequences bound by transcription factors in vivo
. "Next-generation" genome sequencing technologies provide 1-2 orders of magnitude increase in the amount of sequence that can be cost-effectively generated over older technologies thus allowing for ChIP-seq methods to directly provide whole-genome coverage for effective profiling of mammalian protein-DNA interactions.
For successful ChIP-seq approaches, one must generate high quality ChIP DNA template to obtain the best sequencing outcomes. The description is based around experience with the protein product of the gene most strongly implicated in the pathogenesis of type 2 diabetes, namely the transcription factor transcription factor 7-like 2 (TCF7L2). This factor has also been implicated in various cancers.
Outlined is how to generate high quality ChIP DNA template derived from the colorectal carcinoma cell line, HCT116, in order to build a high-resolution map through sequencing to determine the genes bound by TCF7L2, giving further insight in to its key role in the pathogenesis of complex traits.
Molecular Biology, Issue 74, Genetics, Biochemistry, Microbiology, Medicine, Proteins, DNA-Binding Proteins, Transcription Factors, Chromatin Immunoprecipitation, Genes, chromatin, immunoprecipitation, ChIP, DNA, PCR, sequencing, antibody, cross-link, cell culture, assay
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
Institutions: University of Pennsylvania.
It is now appreciated that condition-relevant information can be present within distributed patterns of functional magnetic resonance imaging (fMRI) brain activity, even for conditions with similar levels of univariate activation. Multi-voxel pattern (MVP) analysis has been used to decode this information with great success. FMRI investigators also often seek to understand how brain regions interact in interconnected networks, and use functional connectivity (FC) to identify regions that have correlated responses over time. Just as univariate analyses can be insensitive to information in MVPs, FC may not fully characterize the brain networks that process conditions with characteristic MVP signatures. The method described here, informational connectivity (IC), can identify regions with correlated changes in MVP-discriminability across time, revealing connectivity that is not accessible to FC. The method can be exploratory, using searchlights to identify seed-connected areas, or planned, between pre-selected regions-of-interest. The results can elucidate networks of regions that process MVP-related conditions, can breakdown MVPA searchlight maps into separate networks, or can be compared across tasks and patient groups.
Neuroscience, Issue 89, fMRI, MVPA, connectivity, informational connectivity, functional connectivity, networks, multi-voxel pattern analysis, decoding, classification, method, multivariate
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
Institutions: Washington University School of Medicine, Washington University School of Medicine, Washington University School of Medicine.
As DNA sequencing technology has markedly advanced in recent years2
, it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought3
. In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease4,5
. Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual's personal profile of rare or private DNA variants6-8
. However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today's platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators.
To address this need, we have developed a pooled sequencing approach1,9
and a novel software package1
for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis (http://www.ibridgenetwork.org/wustl/splinter). We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.
Genetics, Issue 64, Genomics, Cancer Biology, Bioinformatics, Pooled DNA sequencing, SPLINTER, rare genetic variants, genetic screening, phenotype, high throughput, computational analysis, DNA, PCR, primers
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
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
Training Synesthetic Letter-color Associations by Reading in Color
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
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
Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity
Institutions: Case Western Reserve University.
Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.
Environmental Sciences, Issue 85, Coexistence, community assembly, environmental drivers, plant-soil feedback, soil heterogeneity, soil microbial communities, soil patch
Quantification of Orofacial Phenotypes in Xenopus
Institutions: Virginia Commonwealth University.
has become an important tool for dissecting the mechanisms governing craniofacial development and defects. A method to quantify orofacial development will allow for more rigorous analysis of orofacial phenotypes upon abrogation with substances that can genetically or molecularly manipulate gene expression or protein function. Using two dimensional images of the embryonic heads, traditional size dimensions-such as orofacial width, height and area- are measured. In addition, a roundness measure of the embryonic mouth opening is used to describe the shape of the mouth. Geometric morphometrics of these two dimensional images is also performed to provide a more sophisticated view of changes in the shape of the orofacial region. Landmarks are assigned to specific points in the orofacial region and coordinates are created. A principle component analysis is used to reduce landmark coordinates to principle components that then discriminate the treatment groups. These results are displayed as a scatter plot in which individuals with similar orofacial shapes cluster together. It is also useful to perform a discriminant function analysis, which statistically compares the positions of the landmarks between two treatment groups. This analysis is displayed on a transformation grid where changes in landmark position are viewed as vectors. A grid is superimposed on these vectors so that a warping pattern is displayed to show where significant landmark positions have changed. Shape changes in the discriminant function analysis are based on a statistical measure, and therefore can be evaluated by a p-value. This analysis is simple and accessible, requiring only a stereoscope and freeware software, and thus will be a valuable research and teaching resource.
Developmental Biology, Issue 93, Orofacial quantification, geometric morphometrics, Xenopus, orofacial development, orofacial defects, shape changes, facial dimensions
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
Cross-Modal Multivariate Pattern Analysis
Institutions: University of Southern California.
Multivariate pattern analysis (MVPA) is an increasingly popular method of analyzing functional magnetic resonance imaging (fMRI) data1-4
. Typically, the method is used to identify a subject's perceptual experience from neural activity in certain regions of the brain. For instance, it has been employed to predict the orientation of visual gratings a subject perceives from activity in early visual cortices5
or, analogously, the content of speech from activity in early auditory cortices6
Here, we present an extension of the classical MVPA paradigm, according to which perceptual stimuli are not predicted within, but across sensory systems. Specifically, the method we describe addresses the question of whether stimuli that evoke memory associations in modalities other than the one through which they are presented induce content-specific activity patterns in the sensory cortices of those other modalities. For instance, seeing a muted video clip of a glass vase shattering on the ground automatically triggers in most observers an auditory image of the associated sound; is the experience of this image in the "mind's ear" correlated with a specific neural activity pattern in early auditory cortices? Furthermore, is this activity pattern distinct from the pattern that could be observed if the subject were, instead, watching a video clip of a howling dog?
In two previous studies7,8
, we were able to predict sound- and touch-implying video clips based on neural activity in early auditory and somatosensory cortices, respectively. Our results are in line with a neuroarchitectural framework proposed by Damasio9,10
, according to which the experience of mental images that are based on memories - such as hearing the shattering sound of a vase in the "mind's ear" upon seeing the corresponding video clip - is supported by the re-construction of content-specific neural activity patterns in early sensory cortices.
Neuroscience, Issue 57, perception, sensory, cross-modal, top-down, mental imagery, fMRI, MRI, neuroimaging, multivariate pattern analysis, MVPA
Tomato Analyzer: A Useful Software Application to Collect Accurate and Detailed Morphological and Colorimetric Data from Two-dimensional Objects
Institutions: The Ohio State University.
Measuring fruit morphology and color traits of vegetable and fruit crops in an objective and reproducible way is important for detailed phenotypic analyses of these traits. Tomato Analyzer (TA) is a software program that measures 37 attributes related to two-dimensional shape in a semi-automatic and reproducible manner1,2
. Many of these attributes, such as angles at the distal and proximal ends of the fruit and areas of indentation, are difficult to quantify manually. The attributes are organized in ten categories within the software: Basic Measurement, Fruit Shape Index, Blockiness, Homogeneity, Proximal Fruit End Shape, Distal Fruit End Shape, Asymmetry, Internal Eccentricity, Latitudinal Section and Morphometrics. The last category requires neither prior knowledge nor predetermined notions of the shape attributes, so morphometric analysis offers an unbiased option that may be better adapted to high-throughput analyses than attribute analysis. TA also offers the Color Test application that was designed to collect color measurements from scanned images and allow scanning devices to be calibrated using color standards3
TA provides several options to export and analyze shape attribute, morphometric, and color data. The data may be exported to an excel file in batch mode (more than 100 images at one time) or exported as individual images. The user can choose between output that displays the average for each attribute for the objects in each image (including standard deviation), or an output that displays the attribute values for each object on the image. TA has been a valuable and effective tool for indentifying and confirming tomato fruit shape Quantitative Trait Loci (QTL), as well as performing in-depth analyses of the effect of key fruit shape genes on plant morphology. Also, TA can be used to objectively classify fruit into various shape categories. Lastly, fruit shape and color traits in other plant species as well as other plant organs such as leaves and seeds can be evaluated with TA.
Plant Biology, Issue 37, morphology, color, image processing, quantitative trait loci, software