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.
25 Related JoVE Articles!
Analysis of Translation Initiation During Stress Conditions by Polysome Profiling
Institutions: Laval University, CHU de Quebec Research Center.
Precise control of mRNA translation is fundamental for eukaryotic cell homeostasis, particularly in response to physiological and pathological stress. Alterations of this program can lead to the growth of damaged cells, a hallmark of cancer development, or to premature cell death such as seen in neurodegenerative diseases. Much of what is known concerning the molecular basis for translational control has been obtained from polysome analysis using a density gradient fractionation system. This technique relies on ultracentrifugation of cytoplasmic extracts on a linear sucrose gradient. Once the spin is completed, the system allows fractionation and quantification of centrifuged zones corresponding to different translating ribosomes populations, thus resulting in a polysome profile. Changes in the polysome profile are indicative of changes or defects in translation initiation that occur in response to various types of stress. This technique also allows to assess the role of specific proteins on translation initiation, and to measure translational activity of specific mRNAs. Here we describe our protocol to perform polysome profiles in order to assess translation initiation of eukaryotic cells and tissues under either normal or stress growth conditions.
Cellular Biology, Issue 87, Translation initiation, polysome profile, sucrose gradient, protein and RNA isolation, stress conditions
A Noninvasive Hair Sampling Technique to Obtain High Quality DNA from Elusive Small Mammals
Institutions: University of British Columbia, Okanagan Campus.
Noninvasive genetic sampling approaches are becoming increasingly important to study wildlife populations. A number of studies have reported using noninvasive sampling techniques to investigate population genetics and demography of wild populations1
. This approach has proven to be especially useful when dealing with rare or elusive species2
. While a number of these methods have been developed to sample hair, feces and other biological material from carnivores and medium-sized mammals, they have largely remained untested in elusive small mammals. In this video, we present a novel, inexpensive and noninvasive hair snare targeted at an elusive small mammal, the American pika (Ochotona princeps
). We describe the general set-up of the hair snare, which consists of strips of packing tape arranged in a web-like fashion and placed along travelling routes in the pikas’ habitat. We illustrate the efficiency of the snare at collecting a large quantity of hair that can then be collected and brought back to the lab. We then demonstrate the use of the DNA IQ system (Promega) to isolate DNA and showcase the utility of this method to amplify commonly used molecular markers including nuclear microsatellites, amplified fragment length polymorphisms (AFLPs), mitochondrial sequences (800bp) as well as a molecular sexing marker. Overall, we demonstrate the utility of this novel noninvasive hair snare as a sampling technique for wildlife population biologists. We anticipate that this approach will be applicable to a variety of small mammals, opening up areas of investigation within natural populations, while minimizing impact to study organisms.
Genetics, Issue 49, Conservation genetics, noninvasive genetic sampling, Hair snares, Microsatellites, AFLPs, American pika, Ochotona princeps
Studying Proteolysis of Cyclin B at the Single Cell Level in Whole Cell Populations
Institutions: University Medical Center Freiburg.
Equal distribution of chromosomes between the two daughter cells during cell division is a prerequisite for guaranteeing genetic stability 1
. Inaccuracies during chromosome separation are a hallmark of malignancy and associated with progressive disease 2-4
. The spindle assembly checkpoint (SAC) is a mitotic surveillance mechanism that holds back cells at metaphase until every single chromosome has established a stable bipolar attachment to the mitotic spindle1
. The SAC exerts its function by interference with the activating APC/C subunit Cdc20 to block proteolysis of securin and cyclin B and thus chromosome separation and mitotic exit. Improper attachment of chromosomes prevents silencing of SAC signaling and causes continued inhibition of APC/CCdc20
until the problem is solved to avoid chromosome missegregation, aneuploidy and malignant growths1
Most studies that addressed the influence of improper chromosomal attachment on APC/C-dependent proteolysis took advantage of spindle disruption using depolymerizing or microtubule-stabilizing drugs to interfere with chromosomal attachment to microtubules. Since interference with microtubule kinetics can affect the transport and localization of critical regulators, these procedures bear a risk of inducing artificial effects 5
To study how the SAC interferes with APC/C-dependent proteolysis of cyclin B during mitosis in unperturbed cell populations, we established a histone H2-GFP-based system which allowed the simultaneous monitoring of metaphase alignment of mitotic chromosomes and proteolysis of cyclin B 6
To depict proteolytic profiles, we generated a chimeric cyclin B reporter molecule with a C-terminal SNAP moiety 6
). In a self-labeling reaction, the SNAP-moiety is able to form covalent bonds with alkylguanine-carriers (SNAP substrate) 7,8
). SNAP substrate molecules are readily available and carry a broad spectrum of different fluorochromes. Chimeric cyclin B-SNAP molecules become labeled upon addition of the membrane-permeable SNAP substrate to the growth medium 7
). Following the labeling reaction, the cyclin B-SNAP fluorescence intensity drops in a pulse-chase reaction-like manner and fluorescence intensities reflect levels of cyclin B degradation 6
). Our system facilitates the monitoring of mitotic APC/C-dependent proteolysis in large numbers of cells (or several cell populations) in parallel. Thereby, the system may be a valuable tool to identify agents/small molecules that are able to interfere with proteolytic activity at the metaphase to anaphase transition. Moreover, as synthesis of cyclin B during mitosis has recently been suggested as an important mechanism in fostering a mitotic block in mice and humans by keeping cyclin B expression levels stable 9,10
, this system enabled us to analyze cyclin B proteolysis as one element of a balanced equilibrium 6
Genetics, Issue 67, Cellular Biology, Molecular Biology, Proteomics, Cyclin B, spindle assembly checkpoint, anaphase-promoting complex, mitosis, proteasome-dependent proteolysis, SNAP, cell cycle
Assessment of Immunologically Relevant Dynamic Tertiary Structural Features of the HIV-1 V3 Loop Crown R2 Sequence by ab initio Folding
Institutions: School of Medicine, New York University.
The antigenic diversity of HIV-1 has long been an obstacle to vaccine design, and this variability is especially pronounced in the V3 loop of the virus' surface envelope glycoprotein. We previously proposed that the crown of the V3 loop, although dynamic and sequence variable, is constrained throughout the population of HIV-1 viruses to an immunologically relevant β-hairpin tertiary structure. Importantly, there are thousands of different V3 loop crown sequences in circulating HIV-1 viruses, making 3D structural characterization of trends across the diversity of viruses difficult or impossible by crystallography or NMR. Our previous successful studies with folding of the V3 crown1, 2
used the ab initio
accessible in the ICM-Pro molecular modeling software package (Molsoft LLC, La Jolla, CA) and suggested that the crown of the V3 loop, specifically from positions 10 to 22, benefits sufficiently from the flexibility and length of its flanking stems to behave to a large degree as if it were an unconstrained peptide freely folding in solution. As such, rapid ab initio
folding of just this portion of the V3 loop of any individual strain of the 60,000+ circulating HIV-1 strains can be informative. Here, we folded the V3 loop of the R2 strain to gain insight into the structural basis of its unique properties. R2 bears a rare V3 loop sequence thought to be responsible for the exquisite sensitivity of this strain to neutralization by patient sera and monoclonal antibodies4, 5
. The strain mediates CD4-independent infection and appears to elicit broadly neutralizing antibodies. We demonstrate how evaluation of the results of the folding can be informative for associating observed structures in the folding with the immunological activities observed for R2.
Infection, Issue 43, HIV-1, structure-activity relationships, ab initio simulations, antibody-mediated neutralization, vaccine design
Knowing What Counts: Unbiased Stereology in the Non-human Primate Brain
Institutions: University of Montreal, University of Montreal, Stereology Resource Center.
The non-human primate is an important translational species for understanding the normal function and disease processes of the human brain. Unbiased stereology, the method accepted as state-of-the-art for quantification of biological objects in tissue sections2
, generates reliable structural data for biological features in the mammalian brain3
. The key components of the approach are unbiased (systematic-random) sampling of anatomically defined structures (reference spaces), combined with quantification of cell numbers and size, fiber and capillary lengths, surface areas, regional volumes and spatial distributions of biological objects within the reference space4
. Among the advantages of these stereological approaches over previous methods is the avoidance of all known sources of systematic (non-random) error arising from faulty assumptions and non-verifiable models. This study documents a biological application of computerized stereology to estimate the total neuronal population in the frontal cortex of the vervet monkey brain (Chlorocebus aethiops sabeus
), with assistance from two commercially available stereology programs, BioQuant Life Sciences and Stereologer (Figure 1). In addition to contrast and comparison of results from both the BioQuant and Stereologer
systems, this study provides a detailed protocol for the Stereologer
Neuroscience, Issue 27, Stereology, brain bank, systematic sampling, non-human primate, cryostat, antigen preserve
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
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
Creating Objects and Object Categories for Studying Perception and Perceptual Learning
Institutions: Georgia Health Sciences University, Georgia Health Sciences University, Georgia Health Sciences University, Palo Alto Research Center, Palo Alto Research Center, University of Minnesota .
In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1
. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes
) with such properties2
Many innovative and useful methods currently exist for creating novel objects and object categories3-6
(also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings.
First, shape variations are generally imposed by the experimenter5,9,10
, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints.
Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13
. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases.
Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms.
Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14
. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13
. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16
. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13
. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper.
We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have.
Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.
Neuroscience, Issue 69, machine learning, brain, classification, category learning, cross-modal perception, 3-D prototyping, inference
Live Cell Imaging of Bacillus subtilis and Streptococcus pneumoniae using Automated Time-lapse Microscopy
Institutions: University of Groningen.
During the last few years scientists became increasingly aware that average data obtained from microbial population based experiments are not representative of the behavior, status or phenotype of single cells. Due to this new insight the number of single cell studies rises continuously (for recent reviews see 1,2,3
). However, many of the single cell techniques applied do not allow monitoring the development and behavior of one specific single cell in time (e.g. flow cytometry or standard microscopy).
Here, we provide a detailed description of a microscopy method used in several recent studies 4, 5, 6, 7
, which allows following and recording (fluorescence of) individual bacterial cells of Bacillus subtilis
and Streptococcus pneumoniae
through growth and division for many generations. The resulting movies can be used to construct phylogenetic lineage trees by tracing back the history of a single cell within a population that originated from one common ancestor. This time-lapse fluorescence microscopy method cannot only be used to investigate growth, division and differentiation of individual cells, but also to analyze the effect of cell history and ancestry on specific cellular behavior. Furthermore, time-lapse microscopy is ideally suited to examine gene expression dynamics and protein localization during the bacterial cell cycle. The method explains how to prepare the bacterial cells and construct the microscope slide to enable the outgrowth of single cells into a microcolony. In short, single cells are spotted on a semi-solid surface consisting of growth medium supplemented with agarose on which they grow and divide under a fluorescence microscope within a temperature controlled environmental chamber. Images are captured at specific intervals and are later analyzed using the open source software ImageJ.
Immunology, Issue 53, time-lapse fluorescence microscopy, single cell analysis, cell history, cell growth, development, promoter activity, protein localization, GFP, Bacillus subtilis, Streptococcus pneumoniae
Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication
Institutions: University of Sydney, University of Hull, Hull and East Yorkshire Hospitals, Addenbrookes Hospital.
Computerized dynamic posturography with the EquiTest is an objective technique for measuring postural strategies under challenging static and dynamic conditions. As part of a diagnostic assessment, the early detection of postural deficits is important so that appropriate and targeted interventions can be prescribed. The Sensory Organization Test (SOT) on the EquiTest determines an individual's use of the sensory systems (somatosensory, visual, and vestibular) that are responsible for postural control. Somatosensory and visual input are altered by the calibrated sway-referenced support surface and visual surround, which move in the anterior-posterior direction in response to the individual's postural sway. This creates a conflicting sensory experience. The Motor Control Test (MCT) challenges postural control by creating unexpected postural disturbances in the form of backwards and forwards translations. The translations are graded in magnitude and the time to recover from the perturbation is computed.
Intermittent claudication, the most common symptom of peripheral arterial disease, is characterized by a cramping pain in the lower limbs and caused by muscle ischemia secondary to reduced blood flow to working muscles during physical exertion. Claudicants often display poor balance, making them susceptible to falls and activity avoidance. The Ankle Brachial Pressure Index (ABPI) is a noninvasive method for indicating the presence of peripheral arterial disease and intermittent claudication, a common symptom in the lower extremities. ABPI is measured as the highest systolic pressure from either the dorsalis pedis or posterior tibial artery divided by the highest brachial artery systolic pressure from either arm. This paper will focus on the use of computerized dynamic posturography in the assessment of balance in claudicants.
Medicine, Issue 82, Posture, Computerized dynamic posturography, Ankle brachial pressure index, Peripheral arterial disease, Intermittent claudication, Balance, Posture, EquiTest, Sensory Organization Test, Motor Control Test
The ITS2 Database
Institutions: University of Würzburg, University of Würzburg.
The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1
and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation2-8
The ITS2 Database9
presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank11
. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold12
(direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling13
. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold.
The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST14
search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE15,16
for multiple sequence-structure alignment calculation and Neighbor Joining18
tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure.
In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
Genetics, Issue 61, alignment, internal transcribed spacer 2, molecular systematics, secondary structure, ribosomal RNA, phylogenetic tree, homology modeling, phylogeny
Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
Institutions: Institut Pasteur .
RNA viruses use RNA dependent RNA polymerases to replicate their genomes. The intrinsically high error rate of these enzymes is a large contributor to the generation of extreme population diversity that facilitates virus adaptation and evolution. Increasing evidence shows that the intrinsic error rates, and the resulting mutation frequencies, of RNA viruses can be modulated by subtle amino acid changes to the viral polymerase. Although biochemical assays exist for some viral RNA polymerases that permit quantitative measure of incorporation fidelity, here we describe a simple method of measuring mutation frequencies of RNA viruses that has proven to be as accurate as biochemical approaches in identifying fidelity altering mutations. The approach uses conventional virological and sequencing techniques that can be performed in most biology laboratories. Based on our experience with a number of different viruses, we have identified the key steps that must be optimized to increase the likelihood of isolating fidelity variants and generating data of statistical significance. The isolation and characterization of fidelity altering mutations can provide new insights into polymerase structure and function1-3
. Furthermore, these fidelity variants can be useful tools in characterizing mechanisms of virus adaptation and evolution4-7
Immunology, Issue 52, Polymerase fidelity, RNA virus, mutation frequency, mutagen, RNA polymerase, viral evolution
Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae
Institutions: Rensselaer Polytechnic Institute.
has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae
has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on mutation accumulation to address mechanisms underlying genome instability during replicative aging.
Microbiology, Issue 92, Aging, mutations, genome instability, Saccharomyces cerevisiae, fluctuation test, magnetic sorting, mother cell, replicative aging
A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Institutions: Stony Brook University, Cold Spring Harbor Laboratory, University of Texas at Dallas.
ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1
. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2
. Reliably identifying these regions was the focus of our work.
Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5
to more rigorous statistical models, e.g.
Hidden Markov Models (HMMs)6-8
. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized.
Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types.
To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9
, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11
and epigenetic data12
to illustrate its usefulness.
Genetics, Issue 70, Bioinformatics, Genomics, Molecular Biology, Cellular Biology, Immunology, Chromatin immunoprecipitation, ChIP-Seq, histone modifications, segmentation, Bayesian, Hidden Markov Models, epigenetics
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
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
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)
High Efficiency Differentiation of Human Pluripotent Stem Cells to Cardiomyocytes and Characterization by Flow Cytometry
Institutions: Medical College of Wisconsin, Stanford University School of Medicine, Medical College of Wisconsin, Hong Kong University, Johns Hopkins University School of Medicine, Medical College of Wisconsin.
There is an urgent need to develop approaches for repairing the damaged heart, discovering new therapeutic drugs that do not have toxic effects on the heart, and improving strategies to accurately model heart disease. The potential of exploiting human induced pluripotent stem cell (hiPSC) technology to generate cardiac muscle “in a dish” for these applications continues to generate high enthusiasm. In recent years, the ability to efficiently generate cardiomyogenic cells from human pluripotent stem cells (hPSCs) has greatly improved, offering us new opportunities to model very early stages of human cardiac development not otherwise accessible. In contrast to many previous methods, the cardiomyocyte differentiation protocol described here does not require cell aggregation or the addition of Activin A or BMP4 and robustly generates cultures of cells that are highly positive for cardiac troponin I and T (TNNI3, TNNT2), iroquois-class homeodomain protein IRX-4 (IRX4), myosin regulatory light chain 2, ventricular/cardiac muscle isoform (MLC2v) and myosin regulatory light chain 2, atrial isoform (MLC2a) by day 10 across all human embryonic stem cell (hESC) and hiPSC lines tested to date. Cells can be passaged and maintained for more than 90 days in culture. The strategy is technically simple to implement and cost-effective. Characterization of cardiomyocytes derived from pluripotent cells often includes the analysis of reference markers, both at the mRNA and protein level. For protein analysis, flow cytometry is a powerful analytical tool for assessing quality of cells in culture and determining subpopulation homogeneity. However, technical variation in sample preparation can significantly affect quality of flow cytometry data. Thus, standardization of staining protocols should facilitate comparisons among various differentiation strategies. Accordingly, optimized staining protocols for the analysis of IRX4, MLC2v, MLC2a, TNNI3, and TNNT2 by flow cytometry are described.
Cellular Biology, Issue 91, human induced pluripotent stem cell, flow cytometry, directed differentiation, cardiomyocyte, IRX4, TNNI3, TNNT2, MCL2v, MLC2a
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g.
, signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation.
The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
Developing Neuroimaging Phenotypes of the Default Mode Network in PTSD: Integrating the Resting State, Working Memory, and Structural Connectivity
Institutions: Alpert Medical School, Brown University, University of Georgia.
Complementary structural and functional neuroimaging techniques used to examine the Default Mode Network (DMN) could potentially improve assessments of psychiatric illness severity and provide added validity to the clinical diagnostic process. Recent neuroimaging research suggests that DMN processes may be disrupted in a number of stress-related psychiatric illnesses, such as posttraumatic stress disorder (PTSD).
Although specific DMN functions remain under investigation, it is generally thought to be involved in introspection and self-processing. In healthy individuals it exhibits greatest activity during periods of rest, with less activity, observed as deactivation, during cognitive tasks, e.g.
, working memory. This network consists of the medial prefrontal cortex, posterior cingulate cortex/precuneus, lateral parietal cortices and medial temporal regions.
Multiple functional and structural imaging approaches have been developed to study the DMN. These have unprecedented potential to further the understanding of the function and dysfunction of this network. Functional approaches, such as the evaluation of resting state connectivity and task-induced deactivation, have excellent potential to identify targeted neurocognitive and neuroaffective (functional) diagnostic markers and may indicate illness severity and prognosis with increased accuracy or specificity. Structural approaches, such as evaluation of morphometry and connectivity, may provide unique markers of etiology and long-term outcomes. Combined, functional and structural methods provide strong multimodal, complementary and synergistic approaches to develop valid DMN-based imaging phenotypes in stress-related psychiatric conditions. This protocol aims to integrate these methods to investigate DMN structure and function in PTSD, relating findings to illness severity and relevant clinical factors.
Medicine, Issue 89, default mode network, neuroimaging, functional magnetic resonance imaging, diffusion tensor imaging, structural connectivity, functional connectivity, posttraumatic stress disorder
Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Institutions: Princeton University.
The aim of de novo
protein design is to find the amino acid sequences that will fold into a desired 3-dimensional structure with improvements in specific properties, such as binding affinity, agonist or antagonist behavior, or stability, relative to the native sequence. Protein design lies at the center of current advances drug design and discovery. Not only does protein design provide predictions for potentially useful drug targets, but it also enhances our understanding of the protein folding process and protein-protein interactions. Experimental methods such as directed evolution have shown success in protein design. However, such methods are restricted by the limited sequence space that can be searched tractably. In contrast, computational design strategies allow for the screening of a much larger set of sequences covering a wide variety of properties and functionality. We have developed a range of computational de novo
protein design methods capable of tackling several important areas of protein design. These include the design of monomeric proteins for increased stability and complexes for increased binding affinity.
To disseminate these methods for broader use we present Protein WISDOM (http://www.proteinwisdom.org), a tool that provides automated methods for a variety of protein design problems. Structural templates are submitted to initialize the design process. The first stage of design is an optimization sequence selection stage that aims at improving stability through minimization of potential energy in the sequence space. Selected sequences are then run through a fold specificity stage and a binding affinity stage. A rank-ordered list of the sequences for each step of the process, along with relevant designed structures, provides the user with a comprehensive quantitative assessment of the design. Here we provide the details of each design method, as well as several notable experimental successes attained through the use of the methods.
Genetics, Issue 77, Molecular Biology, Bioengineering, Biochemistry, Biomedical Engineering, Chemical Engineering, Computational Biology, Genomics, Proteomics, Protein, Protein Binding, Computational Biology, Drug Design, optimization (mathematics), Amino Acids, Peptides, and Proteins, De novo protein and peptide design, Drug design, In silico sequence selection, Optimization, Fold specificity, Binding affinity, sequencing
Population Replacement Strategies for Controlling Vector Populations and the Use of Wolbachia pipientis for Genetic Drive
Institutions: Johns Hopkins University.
In this video, Jason Rasgon discusses population replacement strategies to control vector-borne diseases such as malaria and dengue. "Population replacement" is the replacement of wild vector populations (that are competent to transmit pathogens) with those that are not competent to transmit pathogens. There are several theoretical strategies to accomplish this. One is to exploit the maternally-inherited symbiotic bacteria Wolbachia pipientis. Wolbachia is a widespread reproductive parasite that spreads in a selfish manner at the extent of its host's fitness. Jason Rasgon discusses, in detail, the basic biology of this bacterial symbiont and various ways to use it for control of vector-borne diseases.
Cellular Biology, Issue 5, mosquito, malaria, genetics, infectious disease, Wolbachia
Flow Cytometry Purification of Mouse Meiotic Cells
Institutions: The Scripps Research Institute, The Scripps Research Institute.
The heterogeneous nature of cell types in the testis and the absence of meiotic cell culture models have been significant hurdles to the study of the unique differentiation programs that are manifest during meiosis. Two principal methods have been developed to purify, to varying degrees, various meiotic fractions from both adult and immature animals: elutriation or Staput (sedimentation) using BSA and/or percoll gradients. Both of these methods rely on cell size and density to separate meiotic cells1-5
. Overall, except for few cell populations6
, these protocols fail to yield sufficient purity of the numerous meiotic cell populations that are necessary for detailed molecular analyses. Moreover, with such methods usually one type of meiotic cells can be purified at a given time, which adds an extra level of complexity regarding the reproducibility and homogeneity when comparing meiotic cell samples.
Here, we describe a refined method that allows one to easily visualize, identify, and purify meiotic cells, from germ cells to round spermatids, using FACS combined with Hoechst 33342 staining7,8
. This method provides an overall snapshot of the entire meiotic process and allows one to highly purify viable cells from most stage of meiosis. These purified cells can then be analyzed in detail for molecular changes that accompany progression through meiosis, for example changes in gene expression9,10
and the dynamics of nucleosome occupancy at hotspots of meiotic recombination11
Cellular Biology, Issue 50, meiosis, mouse, FACS, purification, testis
A Rapid Technique for the Visualization of Live Immobilized Yeast Cells
Institutions: Princeton University.
We present here a simple, rapid, and extremely flexible technique for the immobilization and visualization of growing yeast cells by epifluorescence microscopy. The technique is equally suited for visualization of static yeast populations, or time courses experiments up to ten hours in length. My microscopy investigates epigenetic inheritance at the silent mating loci in S. cerevisiae. There are two silent mating loci, HML and HMR, which are normally not expressed as they are packaged in heterochromatin. In the sir1 mutant background silencing is weakened such that each locus can either be in the expressed or silenced epigenetic state, so in the population as a whole there is a mix of cells of different epigenetic states for both HML and HMR. My microscopy demonstrated that there is no relationship between the epigenetic state of HML and HMR in an individual cell. sir1 cells stochastically switch epigenetic states, establishing silencing at a previously expressed locus or expressing a previously silenced locus. My time course microscopy tracked individual sir1 cells and their offspring to score the frequency of each of the four possible epigenetic switches, and thus the stability of each of the epigenetic states in sir1 cells. See also Xu et al., Mol. Cell 2006.
Microbiology, Issue 1, yeast, HML, HMR, epigenetic, loci, silencing, cerevisiae
Depletion of Specific Cell Populations by Complement Depletion
Institutions: Blood Research Institute.
The purification of immune cell populations is often required in order to study their unique functions. In particular, molecular approaches such as real-time PCR and microarray analysis require the isolation of cell populations with high purity. Commonly used purification strategies include fluorescent activated cell sorting (FACS), magnetic bead separation and complement depletion. Of the three strategies, complement depletion offers the advantages of being fast, inexpensive, gentle on the cells and a high cell yield. The complement system is composed of a large number of plasma proteins that when activated initiate a proteolytic cascade culminating in the formation of a membrane-attack complex that forms a pore on a cell surface resulting in cell death1
. The classical pathway is activated by IgM and IgG antibodies and was first described as a mechanism for killing bacteria. With the generation of monoclonal antibodies (mAb), the complement cascade can be used to lyse any cell population in an antigen-specific manner. Depletion of cells by the complement cascade is achieved by the addition of complement fixing antigen-specific antibodies and rabbit complement to the starting cell population. The cells are incubated for one hour at 37°C and the lysed cells are subsequently removed by two rounds of washing. MAb with a high efficiency for complement fixation typically deplete 95-100% of the targeted cell population. Depending on the purification strategy for the targeted cell population, complement depletion can be used for cell purification or for the enrichment of cell populations that then can be further purified by a subsequent method.
JoVE Immunology, Issue 36, rabbit, complement, cell isolation, cell depletion