30 research outputs found

    BacillOndex: An Integrated Data Resource for Systems and Synthetic Biology

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    BacillOndex is an extension of the Ondex data integration system, providing a semantically annotated, integrated knowledge base for the model Gram-positive bacterium Bacillus subtilis. This application allows a user to mine a variety of B. subtilis data sources, and analyse the resulting integrated dataset, which contains data about genes, gene products and their interactions. The data can be analysed either manually, by browsing using Ondex, or computationally via a Web services interface. We describe the process of creating a BacillOndex instance, and describe the use of the system for the analysis of single nucleotide polymorphisms in B. subtilis Marburg. The Marburg strain is the progenitor of the widely-used laboratory strain B. subtilis 168. We identified 27 SNPs with predictable phenotypic effects, including genetic traits for known phenotypes. We conclude that BacillOndex is a valuable tool for the systems-level investigation of, and hypothesis generation about, this important biotechnology workhorse. Such understanding contributes to our ability to construct synthetic genetic circuits in this organism

    Multi-Messenger Astronomy with Extremely Large Telescopes

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    The field of time-domain astrophysics has entered the era of Multi-messenger Astronomy (MMA). One key science goal for the next decade (and beyond) will be to characterize gravitational wave (GW) and neutrino sources using the next generation of Extremely Large Telescopes (ELTs). These studies will have a broad impact across astrophysics, informing our knowledge of the production and enrichment history of the heaviest chemical elements, constrain the dense matter equation of state, provide independent constraints on cosmology, increase our understanding of particle acceleration in shocks and jets, and study the lives of black holes in the universe. Future GW detectors will greatly improve their sensitivity during the coming decade, as will near-infrared telescopes capable of independently finding kilonovae from neutron star mergers. However, the electromagnetic counterparts to high-frequency (LIGO/Virgo band) GW sources will be distant and faint and thus demand ELT capabilities for characterization. ELTs will be important and necessary contributors to an advanced and complete multi-messenger network.Comment: White paper submitted to the Astro2020 Decadal Surve

    Keratinocyte Apoptosis in Epidermal Remodeling and Clearance of Psoriasis Induced by UV Radiation

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    Psoriasis is a common chronic skin disorder, but the mechanisms involved in the resolution and clearance of plaques remain poorly defined. We investigated the mechanism of action of UVB, which is highly effective in clearing psoriasis and inducing remission, and tested the hypothesis that apoptosis is a key mechanism. To distinguish bystander effects, equal erythemal doses of two UVB wavelengths were compared following in vivo irradiation of psoriatic plaques; one is clinically effective (311 nm) and one has no therapeutic effect on psoriasis (290 nm). Only 311 nm UVB induced significant apoptosis in lesional epidermis, and most apoptotic cells were keratinocytes. To determine clinical relevance, we created a computational model of psoriatic epidermis. Modeling predicted apoptosis would occur in both stem and transit-amplifying cells to account for plaque clearance; this was confirmed and quantified experimentally. The median rate of keratinocyte apoptosis from onset to cell death was 20 minutes. These data were fed back into the model and demonstrated that the observed level of keratinocyte apoptosis was sufficient to explain UVB-induced plaque resolution. Our human studies combined with a systems biology approach demonstrate that keratinocyte apoptosis is a key mechanism in psoriatic plaques clearance, providing the basis for future molecular investigation and therapeutic development

    Clinically Actionable Hypercholesterolemia and Hypertriglyceridemia in Children with Nonalcoholic Fatty Liver Disease

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    OBJECTIVE: To determine the percentage of children with nonalcoholic fatty liver disease (NAFLD) in whom intervention for low-density lipoprotein cholesterol or triglycerides was indicated based on National Heart, Lung, and Blood Institute guidelines. STUDY DESIGN: This multicenter, longitudinal cohort study included children with NAFLD enrolled in the National Institute of Diabetes and Digestive and Kidney Diseases Nonalcoholic Steatohepatitis Clinical Research Network. Fasting lipid profiles were obtained at diagnosis. Standardized dietary recommendations were provided. After 1 year, lipid profiles were repeated and interpreted according to National Heart, Lung, and Blood Institute Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction. Main outcomes were meeting criteria for clinically actionable dyslipidemia at baseline, and either achieving lipid goal at follow-up or meeting criteria for ongoing intervention. RESULTS: There were 585 participants, with a mean age of 12.8 years. The prevalence of children warranting intervention for low-density lipoprotein cholesterol at baseline was 14%. After 1 year of recommended dietary changes, 51% achieved goal low-density lipoprotein cholesterol, 27% qualified for enhanced dietary and lifestyle modifications, and 22% met criteria for pharmacologic intervention. Elevated triglycerides were more prevalent, with 51% meeting criteria for intervention. At 1 year, 25% achieved goal triglycerides with diet and lifestyle changes, 38% met criteria for advanced dietary modifications, and 37% qualified for antihyperlipidemic medications. CONCLUSIONS: More than one-half of children with NAFLD met intervention thresholds for dyslipidemia. Based on the burden of clinically relevant dyslipidemia, lipid screening in children with NAFLD is warranted. Clinicians caring for children with NAFLD should be familiar with lipid management

    A Transcriptional Signature of Fatigue Derived from Patients with Primary Sjögren's Syndrome

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    BACKGROUND:Fatigue is a debilitating condition with a significant impact on patients' quality of life. Fatigue is frequently reported by patients suffering from primary Sjögren's Syndrome (pSS), a chronic autoimmune condition characterised by dryness of the eyes and the mouth. However, although fatigue is common in pSS, it does not manifest in all sufferers, providing an excellent model with which to explore the potential underpinning biological mechanisms. METHODS:Whole blood samples from 133 fully-phenotyped pSS patients stratified for the presence of fatigue, collected by the UK primary Sjögren's Syndrome Registry, were used for whole genome microarray. The resulting data were analysed both on a gene by gene basis and using pre-defined groups of genes. Finally, gene set enrichment analysis (GSEA) was used as a feature selection technique for input into a support vector machine (SVM) classifier. Classification was assessed using area under curve (AUC) of receiver operator characteristic and standard error of Wilcoxon statistic, SE(W). RESULTS:Although no genes were individually found to be associated with fatigue, 19 metabolic pathways were enriched in the high fatigue patient group using GSEA. Analysis revealed that these enrichments arose from the presence of a subset of 55 genes. A radial kernel SVM classifier with this subset of genes as input displayed significantly improved performance over classifiers using all pathway genes as input. The classifiers had AUCs of 0.866 (SE(W) 0.002) and 0.525 (SE(W) 0.006), respectively. CONCLUSIONS:Systematic analysis of gene expression data from pSS patients discordant for fatigue identified 55 genes which are predictive of fatigue level using SVM classification. This list represents the first step in understanding the underlying pathophysiological mechanisms of fatigue in patients with pSS

    Multi-Messenger Astronomy with Extremely Large Telescopes

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    The field of time-domain astrophysics has entered the era of Multi-messenger Astronomy (MMA). One key science goal for the next decade (and beyond) will be to characterize gravitational wave (GW) and neutrino sources using the next generation of Extremely Large Telescopes (ELTs). These studies will have a broad impact across astrophysics, informing our knowledge of the production and enrichment history of the heaviest chemical elements, constrain the dense matter equation of state, provide independent constraints on cosmology, increase our understanding of particle acceleration in shocks and jets, and study the lives of black holes in the universe. Future GW detectors will greatly improve their sensitivity during the coming decade, as will near-infrared telescopes capable of independently finding kilonovae from neutron star mergers. However, the electromagnetic counterparts to high-frequency (LIGO/Virgo band) GW sources will be distant and faint and thus demand ELT capabilities for characterization. ELTs will be important and necessary contributors to an advanced and complete multi-messenger network

    Cluster analysis of the p53 genetic regulatory network: topology and biology

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    We describe a network module detection approach which combines a rapid and robust clustering algorithm with an objective measure of the coherence of the modules identified. The approach is applied to the network of genetic regulatory interactions surrounding the tumor suppressor gene p53. This algorithm identifies ten clusters in the p53 network, which are visually coherent and biologically plausible

    Evolutionary computation for the design of a stochastic switch for synthetic genetic circuits

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    Biological systems are inherently stochastic, a fact which is often ignored when simulating genetic circuits. Synthetic biology aims to design genetic circuits de novo, and cannot therefore afford to ignore the effects of stochastic behavior. Since computational design tools will be essential for large-scale synthetic biology, it is important to develop an understanding of the role of stochasticity in molecular biology, and incorporate this understanding into computational tools for genetic circuit design. We report upon an investigation into the combination of evolutionary algorithms and stochastic simulation for genetic circuit design, to design regulatory systems based on the Bacillus subtilis sin operon.7 page(s
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