Gene Circuit Analysis of the Terminal Gap Gene huckebein

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Mining phenotypes for gene function prediction

<p>Abstract</p> <p>Background</p> <p>Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In the past years, many technologies to systematically generate phenotypes in a high-throughput manner, such as RNA interference or gene knock-out, have been developed and used to decipher functions for genes. However, there have been relatively few efforts to make use of phenotype data beyond the single genotype-phenotype relationships.</p> <p>Results</p> <p>We present results on a study where we use a large set of phenotype data – in textual form – to predict gene annotation. To this end, we use text clustering to group genes based on their phenotype descriptions. We show that these clusters correlate well with several indicators for biological coherence in gene groups, such as functional annotations from the Gene Ontology (GO) and protein-protein interactions. We exploit these clusters for predicting gene function by carrying over annotations from well-annotated genes to other, less-characterized genes in the same cluster. For a subset of groups selected by applying objective criteria, we can predict GO-term annotations from the biological process sub-ontology with up to 72.6% precision and 16.7% recall, as evaluated by cross-validation. We manually verified some of these clusters and found them to exhibit high biological coherence, e.g. a group containing all available antennal Drosophila odorant receptors despite inconsistent GO-annotations.</p> <p>Conclusion</p> <p>The intrinsic nature of phenotypes to visibly reflect genetic activity underlines their usefulness in inferring new gene functions. Thus, systematically analyzing these data on a large scale offers many possibilities for inferring functional annotation of genes. We show that text clustering can play an important role in this process.</p

The “minimal boundary curve for endothermy” as a predictor of heterothermy in mammals and birds: a review

According to the concept of the “minimal boundary curve for endothermy”, mammals and birds with a basal metabolic rate (BMR) that falls below the curve are obligate heterotherms and must enter torpor. We examined the reliability of the boundary curve (on a double log plot transformed to a line) for predicting torpor as a function of body mass and BMR for birds and several groups of mammals. The boundary line correctly predicted heterothermy in 87.5% of marsupials (n = 64), 94% of bats (n = 85) and 82.3% of rodents (n = 157). Our analysis shows that the boundary line is not a reliable predictor for use of torpor. A discriminate analysis using body mass and BMR had a similar predictive power as the boundary line. However, there are sufficient exceptions to both methods of analysis to suggest that the relationship between body mass, BMR and heterothermy is not a causal one. Some homeothermic birds (e.g. silvereyes) and rodents (e.g. hopping mice) fall below the boundary line, and there are many examples of heterothermic species that fall above the boundary line. For marsupials and bats, but not for rodents, there was a highly significant phylogenetic pattern for heterothermy, suggesting that taxonomic affiliation is the biggest determinant of heterothermy for these mammalian groups. For rodents, heterothermic species had lower BMRs than homeothermic species. Low BMR and use of torpor both contribute to reducing energy expenditure and both physiological traits appear to be a response to the same selective pressure of fluctuating food supply, increasing fitness in endothermic species that are constrained by limited energy availability. Both the minimal boundary line and discriminate analysis were of little value for predicting the use of daily torpor or hibernation in heterotherms, presumably as both daily torpor and hibernation are precisely controlled processes, not an inability to thermoregulate

Transcriptome Profiling of Whole Blood Cells Identifies PLEK2 and C1QB in Human Melanoma

Developing analytical methodologies to identify biomarkers in easily accessible body fluids is highly valuable for the early diagnosis and management of cancer patients. Peripheral whole blood is a "nucleic acid-rich" and "inflammatory cell-rich" information reservoir and represents systemic processes altered by the presence of cancer cells.We conducted transcriptome profiling of whole blood cells from melanoma patients. To overcome challenges associated with blood-based transcriptome analysis, we used a PAXgene™ tube and NuGEN Ovation™ globin reduction system. The combined use of these systems in microarray resulted in the identification of 78 unique genes differentially expressed in the blood of melanoma patients. Of these, 68 genes were further analyzed by quantitative reverse transcriptase PCR using blood samples from 45 newly diagnosed melanoma patients (stage I to IV) and 50 healthy control individuals. Thirty-nine genes were verified to be differentially expressed in blood samples from melanoma patients. A stepwise logit analysis selected eighteen 2-gene signatures that distinguish melanoma from healthy controls. Of these, a 2-gene signature consisting of PLEK2 and C1QB led to the best result that correctly classified 93.3% melanoma patients and 90% healthy controls. Both genes were upregulated in blood samples of melanoma patients from all stages. Further analysis using blood fractionation showed that CD45(-) and CD45(+) populations were responsible for the altered expression levels of PLEK2 and C1QB, respectively.The current study provides the first analysis of whole blood-based transcriptome biomarkers for malignant melanoma. The expression of PLEK2, the strongest gene to classify melanoma patients, in CD45(-) subsets illustrates the importance of analyzing whole blood cells for biomarker studies. The study suggests that transcriptome profiling of blood cells could be used for both early detection of melanoma and monitoring of patients for residual disease

Host genetic signatures of susceptibility to fungal disease

Our relative inability to predict the development of fungal disease and its clinical outcome raises fundamental questions about its actual pathogenesis. Several clinical risk factors are described to predispose to fungal disease, particularly in immunocompromised and severely ill patients. However, these alone do not entirely explain why, under comparable clinical conditions, only some patients develop infection. Recent clinical and epidemiological studies have reported an expanding number of monogenic defects and common polymorphisms associated with fungal disease. By directly implicating genetic variation in the functional regulation of immune mediators and interacting pathways, these studies have provided critical insights into the human immunobiology of fungal disease. Most of the common genetic defects reported were described or suggested to impair fungal recognition by the innate immune system. Here, we review common genetic variation in pattern recognition receptors and its impact on the immune response against the two major fungal pathogens Candida albicans and Aspergillus fumigatus. In addition, we discuss potential strategies and opportunities for the clinical translation of genetic information in the field of medical mycology. These approaches are expected to transfigure current clinical practice by unleashing an unprecedented ability to personalize prophylaxis, therapy and monitoring for fungal disease.This work was supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER) (NORTE-01-0145-FEDER-000013), the Fundação para a Ciência e Tecnologia (FCT) (IF/00735/2014 to AC, and SFRH/BPD/96176/2013 to CC), the Institut Mérieux (Mérieux Research Grant 2017 to CC), and the European Society of Clinical Microbiology and Infectious Diseases (ESCMID Research Grant 2017 to AC)

The Transcriptome of the Nosocomial Pathogen Enterococcus faecalis V583 Reveals Adaptive Responses to Growth in Blood

gains access to the bloodstream and establishes a persistent infection is not well understood.. infections

In Vivo Methods to Study Uptake of Nanoparticles into the Brain

Several in vivo techniques have been developed to study and measure the uptake of CNS compounds into the brain. With these techniques, various parameters can be determined after drug administration, including the blood-to-brain influx constant (Kin), the permeability-surface area (PS) product, and the brain uptake index (BUI). These techniques have been mostly used for drugs that are expected to enter the brain via transmembrane diffusion or by carrier-mediated transcytosis. Drugs that have limitations in entering the brain via such pathways have been encapsulated in nanoparticles (based on lipids or synthetic polymers) to enhance brain uptake. Nanoparticles are different from CNS compounds in size, composition and uptake mechanisms. This has led to different methods and approaches to study brain uptake in vivo. Here we discuss the techniques generally used to measure nanoparticle uptake in addition to the techniques used for CNS compounds. Techniques include visualization methods, behavioral tests, and quantitative methods

Response time variability and response inhibition predict affective problems in adolescent girls, not in boys: the TRAILS study

The present study examines the relationship between neurocognitive functioning and affective problems through adolescence, in a cross-sectional and longitudinal perspective. Baseline response speed, response speed variability, response inhibition, attentional flexibility and working memory were assessed in a cohort of 2,179 adolescents (age 10–12 years) from the TRacking Adolescents’ Individual Lives Survey (TRAILS). Affective problems were measured with the DSM-oriented Affective Problems scale of the Youth Self Report at wave 1 (baseline assessment), wave 2 (after 2.5 years) and wave 3 (after 5 years). Cross-sectionally, baseline response speed, response time variability, response inhibition and working memory were associated with baseline affective problems in girls, but not in boys. Longitudinally, enhanced response time variability predicted affective problems after 2.5 and 5 years in girls, but not in boys. Decreased response inhibition predicted affective problems after 5 years follow-up in girls, and again not in boys. The results are discussed in light of recent insights in gender differences in adolescence and state–trait issues in depression