Sorting live stem cells based on Sox2 mRNA expression.

PMCID: PMC3507951This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.While cell sorting usually relies on cell-surface protein markers, molecular beacons (MBs) offer the potential to sort cells based on the presence of any expressed mRNA and in principle could be extremely useful to sort rare cell populations from primary isolates. We show here how stem cells can be purified from mixed cell populations by sorting based on MBs. Specifically, we designed molecular beacons targeting Sox2, a well-known stem cell marker for murine embryonic (mES) and neural stem cells (NSC). One of our designed molecular beacons displayed an increase in fluorescence compared to a nonspecific molecular beacon both in vitro and in vivo when tested in mES and NSCs. We sorted Sox2-MB(+)SSEA1(+) cells from a mixed population of 4-day retinoic acid-treated mES cells and effectively isolated live undifferentiated stem cells. Additionally, Sox2-MB(+) cells isolated from primary mouse brains were sorted and generated neurospheres with higher efficiency than Sox2-MB(-) cells. These results demonstrate the utility of MBs for stem cell sorting in an mRNA-specific manner

Central Nervous System Parasitosis and Neuroinflammation Ameliorated by Systemic IL-10 Administration in Trypanosoma brucei-Infected Mice

Peer reviewedPublisher PD

The caCORE Software Development Kit: Streamlining construction of interoperable biomedical information services

BACKGROUND: Robust, programmatically accessible biomedical information services that syntactically and semantically interoperate with other resources are challenging to construct. Such systems require the adoption of common information models, data representations and terminology standards as well as documented application programming interfaces (APIs). The National Cancer Institute (NCI) developed the cancer common ontologic representation environment (caCORE) to provide the infrastructure necessary to achieve interoperability across the systems it develops or sponsors. The caCORE Software Development Kit (SDK) was designed to provide developers both within and outside the NCI with the tools needed to construct such interoperable software systems. RESULTS: The caCORE SDK requires a Unified Modeling Language (UML) tool to begin the development workflow with the construction of a domain information model in the form of a UML Class Diagram. Models are annotated with concepts and definitions from a description logic terminology source using the Semantic Connector component. The annotated model is registered in the Cancer Data Standards Repository (caDSR) using the UML Loader component. System software is automatically generated using the Codegen component, which produces middleware that runs on an application server. The caCORE SDK was initially tested and validated using a seven-class UML model, and has been used to generate the caCORE production system, which includes models with dozens of classes. The deployed system supports access through object-oriented APIs with consistent syntax for retrieval of any type of data object across all classes in the original UML model. The caCORE SDK is currently being used by several development teams, including by participants in the cancer biomedical informatics grid (caBIG) program, to create compatible data services. caBIG compatibility standards are based upon caCORE resources, and thus the caCORE SDK has emerged as a key enabling technology for caBIG. CONCLUSION: The caCORE SDK substantially lowers the barrier to implementing systems that are syntactically and semantically interoperable by providing workflow and automation tools that standardize and expedite modeling, development, and deployment. It has gained acceptance among developers in the caBIG program, and is expected to provide a common mechanism for creating data service nodes on the data grid that is under development

A Revised Design for Microarray Experiments to Account for Experimental Noise and Uncertainty of Probe Response

Background Although microarrays are analysis tools in biomedical research, they are known to yield noisy output that usually requires experimental confirmation. To tackle this problem, many studies have developed rules for optimizing probe design and devised complex statistical tools to analyze the output. However, less emphasis has been placed on systematically identifying the noise component as part of the experimental procedure. One source of noise is the variance in probe binding, which can be assessed by replicating array probes. The second source is poor probe performance, which can be assessed by calibrating the array based on a dilution series of target molecules. Using model experiments for copy number variation and gene expression measurements, we investigate here a revised design for microarray experiments that addresses both of these sources of variance. Results Two custom arrays were used to evaluate the revised design: one based on 25 mer probes from an Affymetrix design and the other based on 60 mer probes from an Agilent design. To assess experimental variance in probe binding, all probes were replicated ten times. To assess probe performance, the probes were calibrated using a dilution series of target molecules and the signal response was fitted to an adsorption model. We found that significant variance of the signal could be controlled by averaging across probes and removing probes that are nonresponsive or poorly responsive in the calibration experiment. Taking this into account, one can obtain a more reliable signal with the added option of obtaining absolute rather than relative measurements. Conclusion The assessment of technical variance within the experiments, combined with the calibration of probes allows to remove poorly responding probes and yields more reliable signals for the remaining ones. Once an array is properly calibrated, absolute quantification of signals becomes straight forward, alleviating the need for normalization and reference hybridizations

A statistical model for estimation of fish density including correlation in size, space, time and between species from research survey data

Trawl survey data with high spatial and seasonal coverage were analysed using a variant of the Log Gaussian Cox Process (LGCP) statistical model to estimate unbiased relative fish densities. The model estimates correlations between observations according to time, space, and fish size and includes zero observations and over-dispersion. The model utilises the fact the correlation between numbers of fish caught increases when the distance in space and time between the fish decreases, and the correlation between size groups in a haul increases when the difference in size decreases. Here the model is extended in two ways. Instead of assuming a natural scale size correlation, the model is further developed to allow for a transformed length scale. Furthermore, in the present application, the spatial- and size-dependent correlation between species was included. For cod (Gadus morhua) and whiting (Merlangius merlangus), a common structured size correlation was fitted, and a separable structure between the time and space-size correlation was found for each species, whereas more complex structures were required to describe the correlation between species (and space-size). The within-species time correlation is strong, whereas the correlations between the species are weaker over time but strong within the year

Melarsoprol cyclodextrin inclusion complexes as promising oral candidates for the treatment of human African trypanosomiasis

Human African trypanosomiasis (HAT), or sleeping sickness, results from infection with the protozoan parasites <i>Trypanosoma brucei</i> (<i>T.b.</i>) <i>gambiense</i> or <i>T.b.rhodesiense</i> and is invariably fatal if untreated. There are 60 million people at risk from the disease throughout sub-Saharan Africa. The infection progresses from the haemolymphatic stage where parasites invade the blood, lymphatics and peripheral organs, to the late encephalitic stage where they enter the central nervous system (CNS) to cause serious neurological disease. The trivalent arsenical drug melarsoprol (Arsobal) is the only currently available treatment for CNS-stage <i>T.b.rhodesiense</i> infection. However, it must be administered intravenously due to the presence of propylene glycol solvent and is associated with numerous adverse reactions. A severe post-treatment reactive encephalopathy occurs in about 10% of treated patients, half of whom die. Thus melarsoprol kills 5% of all patients receiving it. Cyclodextrins have been used to improve the solubility and reduce the toxicity of a wide variety of drugs. We therefore investigated two melarsoprol cyclodextrin inclusion complexes; melarsoprol hydroxypropyl-͎-cyclodextrin and melarsoprol randomly-methylated-β-cyclodextrin. We found that these compounds retain trypanocidal properties <i>in vitro</i> and cure CNS-stage murine infections when delivered orally, once per day for 7-days, at a dosage of 0.05 mmol/kg. No overt signs of toxicity were detected. Parasite load within the brain was rapidly reduced following treatment onset and magnetic resonance imaging showed restoration of normal blood-brain barrier integrity on completion of chemotherapy. These findings strongly suggest that complexed melarsoprol could be employed as an oral treatment for CNS-stage HAT, delivering considerable improvements over current parenteral chemotherapy

A metabolite-derived protein modification integrates glycolysis with KEAP1-NRF2 signalling.

Mechanisms that integrate the metabolic state of a cell with regulatory pathways are necessary to maintain cellular homeostasis. Endogenous, intrinsically reactive metabolites can form functional, covalent modifications on proteins without the aid of enzymes1,2, and regulate cellular functions such as metabolism3-5 and transcription6. An important 'sensor' protein that captures specific metabolic information and transforms it into an appropriate response is KEAP1, which contains reactive cysteine residues that collectively act as an electrophile sensor tuned to respond to reactive species resulting from endogenous and xenobiotic molecules. Covalent modification of KEAP1 results in reduced ubiquitination and the accumulation of NRF27,8, which then initiates the transcription of cytoprotective genes at antioxidant-response element loci. Here we identify a small-molecule inhibitor of the glycolytic enzyme PGK1, and reveal a direct link between glycolysis and NRF2 signalling. Inhibition of PGK1 results in accumulation of the reactive metabolite methylglyoxal, which selectively modifies KEAP1 to form a methylimidazole crosslink between proximal cysteine and arginine residues (MICA). This posttranslational modification results in the dimerization of KEAP1, the accumulation of NRF2 and activation of the NRF2 transcriptional program. These results demonstrate the existence of direct inter-pathway communication between glycolysis and the KEAP1-NRF2 transcriptional axis, provide insight into the metabolic regulation of the cellular stress response, and suggest a therapeutic strategy for controlling the cytoprotective antioxidant response in several human diseases

Optimal Conservation of Migratory Species

Background. Migratory animals comprise a significant portion of biodiversity worldwide with annual investment for their conservation exceeding several billion dollars. Designing effective conservation plans presents enormous challenges. Migratory species are influenced by multiple events across land and sea-regions that are often separated by thousands of kilometres and span international borders. To date, conservation strategies for migratory species fail to take into account how migratory animals are spatially connected between different periods of the annual cycle (i.e. migratory connectivity) bringing into question the utility and efficiency of current conservation efforts. Methodology/Principal Findings. Here, we report the first framework for determining an optimal conservation strategy for a migratory species. Employing a decision theoretic approach using dynamic optimization, we address the problem of how to allocate resources for habitat conservation for a Neotropical-Nearctic migratory bird, the American redstart Setophaga ruticilla, whose winter habitat is under threat. Our first conservation strategy used the acquisition of winter habitat based on land cost, relative bird density, and the rate of habitat loss to maximize the abundance of birds on the wintering grounds. Our second strategy maximized bird abundance across the entire range of the species by adding the constraint of maintaining a minimum percentage of birds within each breeding region in North America using information on migratory connectivity as estimated from stable-hydrogen isotopes in feathers. We show that failure to take into account migratory connectivity may doom some regional populations to extinction, whereas including information on migratory connectivity results in the protection of the species across its entire range. Conclusions/Significance. We demonstrate that conservation strategies for migratory animals depend critically upon two factors: knowledge of migratory connectivity and the correct statement of the conservation problem. Our framework can be used to identify efficient conservation strategies for migratory taxa worldwide, including insects, birds, mammals, and marine organisms