2,128 research outputs found

    Integration of deep transcriptome and proteome analyses reveals the components of alkaloid metabolism in opium poppy cell cultures

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    <p>Abstract</p> <p>Background</p> <p><it>Papaver somniferum </it>(opium poppy) is the source for several pharmaceutical benzylisoquinoline alkaloids including morphine, the codeine and sanguinarine. In response to treatment with a fungal elicitor, the biosynthesis and accumulation of sanguinarine is induced along with other plant defense responses in opium poppy cell cultures. The transcriptional induction of alkaloid metabolism in cultured cells provides an opportunity to identify components of this process via the integration of deep transcriptome and proteome databases generated using next-generation technologies.</p> <p>Results</p> <p>A cDNA library was prepared for opium poppy cell cultures treated with a fungal elicitor for 10 h. Using 454 GS-FLX Titanium pyrosequencing, 427,369 expressed sequence tags (ESTs) with an average length of 462 bp were generated. Assembly of these sequences yielded 93,723 unigenes, of which 23,753 were assigned Gene Ontology annotations. Transcripts encoding all known sanguinarine biosynthetic enzymes were identified in the EST database, 5 of which were represented among the 50 most abundant transcripts. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) of total protein extracts from cell cultures treated with a fungal elicitor for 50 h facilitated the identification of 1,004 proteins. Proteins were fractionated by one-dimensional SDS-PAGE and digested with trypsin prior to LC-MS/MS analysis. Query of an opium poppy-specific EST database substantially enhanced peptide identification. Eight out of 10 known sanguinarine biosynthetic enzymes and many relevant primary metabolic enzymes were represented in the peptide database.</p> <p>Conclusions</p> <p>The integration of deep transcriptome and proteome analyses provides an effective platform to catalogue the components of secondary metabolism, and to identify genes encoding uncharacterized enzymes. The establishment of corresponding transcript and protein databases generated by next-generation technologies in a system with a well-defined metabolite profile facilitates an improved linkage between genes, enzymes, and pathway components. The proteome database represents the most relevant alkaloid-producing enzymes, compared with the much deeper and more complete transcriptome library. The transcript database contained full-length mRNAs encoding most alkaloid biosynthetic enzymes, which is a key requirement for the functional characterization of novel gene candidates.</p

    Be outraged: there are alternatives

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    Pushed to extremes, austerity is bad economics, bad arithmetic, and ignores the lessons of history. We, an international group of economists and social scientists, are outraged at the narrow range of austerity policies which are bringing so many people around the world to their knees, especially in Europe. Austerity and cutbacks are reducing growth and worsening poverty. In our professional opinions, there are alternatives – for Britain, Europe and all countries that currently imagine that government cutbacks are the only way out of debt. The low-growth, no-growth trap means that the share of debt in GNP falls ever more slowly, if at all. It may even rise – as it has in some countries

    Diverse Durham collection phages demonstrate complex BREX defence responses

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    Bacteriophages (phages) outnumber bacteria ten-to-one and cause infections at a rate of 1025 per second. The ability of phages to reduce bacterial populations makes them attractive alternative antibacterials for use in combating the rise in antimicrobial resistance. This effort may be hindered due to bacterial defenses such as Bacteriophage Exclusion (BREX) that have arisen from the constant evolutionary battle between bacteria and phages. For phages to be widely accepted as therapeutics in Western medicine, more must be understood about bacteria–phage interactions and the outcomes of bacterial phage defense. Here, we present the annotated genomes of 12 novel bacteriophage species isolated from water sources in Durham, UK, during undergraduate practical classes. The collection includes diverse species from across known phylogenetic groups. Comparative analyses of two novel phages from the collection suggest they may be founding members of a new genus. Using this Durham phage collection, we determined that particular BREX defense systems were likely to confer a varied degree of resistance against an invading phage. We concluded that the number of BREX target motifs encoded in the phage genome was not proportional to the degree of susceptibility

    Multidimensional responses of grassland stability to eutrophication

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    Eutrophication usually impacts grassland biodiversity, community composition, and biomass production, but its impact on the stability of these community aspects is unclear. One challenge is that stability has many facets that can be tightly correlated (low dimensionality) or highly disparate (high dimensionality). Using standardized experiments in 55 grassland sites from a globally distributed experiment (NutNet), we quantify the effects of nutrient addition on five facets of stability (temporal invariability, resistance during dry and wet growing seasons, recovery after dry and wet growing seasons), measured on three community aspects (aboveground biomass, community composition, and species richness). Nutrient addition reduces the temporal invariability and resistance of species richness and community composition during dry and wet growing seasons, but does not affect those of biomass. Different stability measures are largely uncorrelated under both ambient and eutrophic conditions, indicating consistently high dimensionality. Harnessing the dimensionality of ecological stability provides insights for predicting grassland responses to global environmental change

    Perceptions, attitudes and knowledge of evidence-based medicine in primary care in Spain: a study protocol

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    <p>Abstract</p> <p>Background</p> <p>The philosophy of evidence-based medicine (EBM) was introduced in the early 90s as a new approach to the practice of medicine, using the best available evidence to make decisions about health care. Despite ongoing controversy, EBM has developed enormously and physicians' attitude towards it is generally positive. Nevertheless, in Spain little is known about this topic. We will therefore undertake a study to explore perceptions, attitudes and knowledge about EBM among primary care physicians.</p> <p>Methods and design</p> <p>A mixed-method study combining qualitative and quantitative designs will target family practitioners in Spain with the objective of evaluating current attitudes and perceptions about evidence-based medicine. The project will consist of two phases: a first phase running focus groups to identify perceptions and attitudes of participants, and a second phase assessing their attitudes and knowledge about EBM by means of a survey. Both phases will explore these issues in three different subgroups: family practitioners, with or without previous formal education in EBM; members of working groups that formulate healthcare recommendations; and physicians in charge of training family practice residents. Additionally, we will undertake a systematic review to identify and synthesize the available evidence on this topic.</p> <p>Discussion</p> <p>The study will identify and gain insight into the perceived problems and barriers to the practice of evidence-based medicine among general practitioners in Spain. The project will also evaluate the main knowledge gaps and training needs, and explore how evidence-based medicine is being taught to family medicine residents, the medical practitioners of the future. Our results will aid researchers and health care planners in developing strategies to improve the practice of evidence-based medicine in our country.</p

    Inferring gene regression networks with model trees

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    <p>Abstract</p> <p>Background</p> <p>Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities.</p> <p>Results</p> <p>We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named R<smcaps>EG</smcaps>N<smcaps>ET</smcaps>, is experimentally tested on two well-known data sets: <it>Saccharomyces Cerevisiae </it>and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database) is used as control to compare the results to that of a correlation-based method. This experiment shows that R<smcaps>EG</smcaps>N<smcaps>ET</smcaps> performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods.</p> <p>Conclusions</p> <p>R<smcaps>EG</smcaps>N<smcaps>ET</smcaps> generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear regressions to separate areas of the search space favoring to infer localized similarities over a more global similarity. Furthermore, experimental results show the good performance of R<smcaps>EG</smcaps>N<smcaps>ET</smcaps>.</p

    Linking changes in species composition and biomass in a globally distributed grassland experiment

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    Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.Fil: Ladouceur, Emma. Martin Luther University Halle-Wittenberg; Alemania. Universitat Leipzig; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; AlemaniaFil: Blowes, Shane A.. Martin Luther University Halle-Wittenberg; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; AlemaniaFil: Chase, Jonathan M.. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. Martin Luther University Halle-Wittenberg; AlemaniaFil: Clark, Adam T.. Martin Luther University Halle-Wittenberg; Alemania. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. University of Graz; AustriaFil: Garbowski, Magda. German Centre for Integrative Biodiversity Research (iDiv) Leipzig-Halle-Jena; Alemania. Universitat Leipzig; AlemaniaFil: Alberti, Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Arnillas, Carlos Alberto. University of Toronto; CanadáFil: Bakker, Jonathan. University of Washington; Estados UnidosFil: Barrio, Isabel C.. Agricultural University of Iceland; IslandiaFil: Bharath, Siddharth. Atria University; IndiaFil: Borer, Elizabeth. University of Minnesota; Estados UnidosFil: Brudvig, Lars A.. Michigan State University; Estados UnidosFil: Cadotte, Marc W.. University of Toronto; CanadáFil: Chen, Qingqing. Peking University; ChinaFil: Collins, Scott L.. University of New Mexico; Estados UnidosFil: Dickman, Christopher R.. The University Of Sydney; AustraliaFil: Donohue, Ian. Trinity College Dublin; IrlandaFil: Du, Guozhen. Lanzhou University; ChinaFil: Ebeling, Anne. Universitat Jena; AlemaniaFil: Eisenhauer, Nico. Martin Luther University Halle—Wittenberg; Alemania. German Centre For Integrative Biodiversity Research (idiv) Halle-jena-leipzig; AlemaniaFil: Fay, Philip A.. USDA-ARS Grassland Soil and Water Research Lab; Estados UnidosFil: Hagenah, Nicole. University Of Pretoria; SudáfricaFil: Hautier, Yann. University of Utrecht; Países BajosFil: Jentsch, Anke. University of Bayreuth; AlemaniaFil: Jónsdóttir, Ingibjörg S.. University of Iceland; IslandiaFil: Komatsu, Kimberly J.. Smithsonian Environmental Research Center; Estados UnidosFil: MacDougall, Andrew. University of Guelph; CanadáFil: Martina, Jason P.. Texas State University; Estados UnidosFil: Moore, Joslin L.. Arthur Rylah Institute For Environmental Research; Australia. Monash University; AustraliaFil: Morgan, John W.. La Trobe University; AustraliaFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin
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