350 research outputs found

    Pleosporales

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    One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae

    The Aspartate-Semialdehyde Dehydrogenase of Edwardsiella ictaluri and Its Use as Balanced-Lethal System in Fish Vaccinology

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    asdA mutants of Gram-negative bacteria have an obligate requirement for diaminopimelic acid (DAP), which is an essential constituent of the peptidoglycan layer of the cell wall of these organisms. In environments deprived of DAP, i.e., animal tissues, they will undergo lysis. Deletion of the asdA gene has previously been exploited to develop antibiotic-sensitive strains of live attenuated recombinant bacterial vaccines. Introduction of an Asd+ plasmid into a ΔasdA mutant makes the bacterial strain plasmid-dependent. This dependence on the Asd+ plasmid vector creates a balanced-lethal complementation between the bacterial strain and the recombinant plasmid. E. ictaluri is an enteric Gram-negative fish pathogen that causes enteric septicemia in catfish. Because E. ictaluri is a nasal/oral invasive intracellular pathogen, this bacterium is a candidate to develop a bath/oral live recombinant attenuated Edwardsiella vaccine (RAEV) for the catfish aquaculture industry. As a first step to develop an antibiotic-sensitive RAEV strain, we characterized and deleted the E. ictaluri asdA gene. E. ictaluri ΔasdA01 mutants exhibit an absolute requirement for DAP to grow. The asdA gene of E. ictaluri was complemented by the asdA gene from Salmonella. Several Asd+ expression vectors with different origins of replication were transformed into E. ictaluri ΔasdA01. Asd+ vectors were compatible with the pEI1 and pEI2 E. ictaluri native plasmids. The balanced-lethal system was satisfactorily evaluated in vivo. Recombinant GFP, PspA, and LcrV proteins were synthesized by E. ictaluri ΔasdA01 harboring Asd+ plasmids. Here we constructed a balanced-lethal system, which is the first step to develop an antibiotic-sensitive RAEV for the aquaculture industry

    A novel class of microRNA-recognition elements that function only within open reading frames.

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    MicroRNAs (miRNAs) are well known to target 3' untranslated regions (3' UTRs) in mRNAs, thereby silencing gene expression at the post-transcriptional level. Multiple reports have also indicated the ability of miRNAs to target protein-coding sequences (CDS); however, miRNAs have been generally believed to function through similar mechanisms regardless of the locations of their sites of action. Here, we report a class of miRNA-recognition elements (MREs) that function exclusively in CDS regions. Through functional and mechanistic characterization of these 'unusual' MREs, we demonstrate that CDS-targeted miRNAs require extensive base-pairing at the 3' side rather than the 5' seed; cause gene silencing in an Argonaute-dependent but GW182-independent manner; and repress translation by inducing transient ribosome stalling instead of mRNA destabilization. These findings reveal distinct mechanisms and functional consequences of miRNAs that target CDS versus the 3' UTR and suggest that CDS-targeted miRNAs may use a translational quality-control-related mechanism to regulate translation in mammalian cells

    An Integrated Approach to Identifying Cis-Regulatory Modules in the Human Genome

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    In eukaryotic genomes, it is challenging to accurately determine target sites of transcription factors (TFs) by only using sequence information. Previous efforts were made to tackle this task by considering the fact that TF binding sites tend to be more conserved than other functional sites and the binding sites of several TFs are often clustered. Recently, ChIP-chip and ChIP-sequencing experiments have been accumulated to identify TF binding sites as well as survey the chromatin modification patterns at the regulatory elements such as promoters and enhancers. We propose here a hidden Markov model (HMM) to incorporate sequence motif information, TF-DNA interaction data and chromatin modification patterns to precisely identify cis-regulatory modules (CRMs). We conducted ChIP-chip experiments on four TFs, CREB, E2F1, MAX, and YY1 in 1% of the human genome. We then trained a hidden Markov model (HMM) to identify the labels of the CRMs by incorporating the sequence motifs recognized by these TFs and the ChIP-chip ratio. Chromatin modification data was used to predict the functional sites and to further remove false positives. Cross-validation showed that our integrated HMM had a performance superior to other existing methods on predicting CRMs. Incorporating histone signature information successfully penalized false prediction and improved the whole performance. The dataset we used and the software are available at http://nash.ucsd.edu/CIS/

    Off-Target Effects of Psychoactive Drugs Revealed by Genome-Wide Assays in Yeast

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    To better understand off-target effects of widely prescribed psychoactive drugs, we performed a comprehensive series of chemogenomic screens using the budding yeast Saccharomyces cerevisiae as a model system. Because the known human targets of these drugs do not exist in yeast, we could employ the yeast gene deletion collections and parallel fitness profiling to explore potential off-target effects in a genome-wide manner. Among 214 tested, documented psychoactive drugs, we identified 81 compounds that inhibited wild-type yeast growth and were thus selected for genome-wide fitness profiling. Many of these drugs had a propensity to affect multiple cellular functions. The sensitivity profiles of half of the analyzed drugs were enriched for core cellular processes such as secretion, protein folding, RNA processing, and chromatin structure. Interestingly, fluoxetine (Prozac) interfered with establishment of cell polarity, cyproheptadine (Periactin) targeted essential genes with chromatin-remodeling roles, while paroxetine (Paxil) interfered with essential RNA metabolism genes, suggesting potential secondary drug targets. We also found that the more recently developed atypical antipsychotic clozapine (Clozaril) had no fewer off-target effects in yeast than the typical antipsychotics haloperidol (Haldol) and pimozide (Orap). Our results suggest that model organism pharmacogenetic studies provide a rational foundation for understanding the off-target effects of clinically important psychoactive agents and suggest a rational means both for devising compound derivatives with fewer side effects and for tailoring drug treatment to individual patient genotypes

    A Chemocentric Approach to the Identification of Cancer Targets

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    A novel chemocentric approach to identifying cancer-relevant targets is introduced. Starting with a large chemical collection, the strategy uses the list of small molecule hits arising from a differential cytotoxicity screening on tumor HCT116 and normal MRC-5 cell lines to identify proteins associated with cancer emerging from a differential virtual target profiling of the most selective compounds detected in both cell lines. It is shown that this smart combination of differential in vitro and in silico screenings (DIVISS) is capable of detecting a list of proteins that are already well accepted cancer drug targets, while complementing it with additional proteins that, targeted selectively or in combination with others, could lead to synergistic benefits for cancer therapeutics. The complete list of 115 proteins identified as being hit uniquely by compounds showing selective antiproliferative effects for tumor cell lines is provided

    The use of group dynamics strategies to enhance cohesion in a lifestyle intervention program for obese children

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    <p>Abstract</p> <p>Background</p> <p>Most research pertaining to childhood obesity has assessed the effectiveness of preventative interventions, while relatively little has been done to advance knowledge in the treatment of obesity. Thus, a 4-week family- and group-based intervention utilizing group dynamics strategies designed to increase cohesion was implemented to influence the lifestyles and physical activity levels of obese children.</p> <p>Methods/Design</p> <p>This paper provides an overview of the rationale for and implementation of the intervention for obese children and their families. Objectives of the intervention included the modification of health behaviors and cohesion levels through the use of group dynamics strategies. To date, a total of 15 children (7 boys and 8 girls, mean age = 10.5) and their families have completed the intervention (during the month of August 2008). Physiological and psychological outcomes were assessed throughout the 4-week intervention and at 3-, 6-, and 12-month follow-up periods.</p> <p>Discussion</p> <p>It is believed that the information provided will help researchers and health professionals develop similar obesity treatment interventions through the use of evidence-based group dynamics strategies. There is also a need for continued research in this area, and it is our hope that the Children's Health and Activity Modification Program (C.H.A.M.P.) will provide a strong base from which others may build.</p

    Salivary Glucose Oxidase from Caterpillars Mediates the Induction of Rapid and Delayed-Induced Defenses in the Tomato Plant

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    Caterpillars produce oral secretions that may serve as cues to elicit plant defenses, but in other cases these secretions have been shown to suppress plant defenses. Ongoing work in our laboratory has focused on the salivary secretions of the tomato fruitworm, Helicoverpa zea. In previous studies we have shown that saliva and its principal component glucose oxidase acts as an effector by suppressing defenses in tobacco. In this current study, we report that saliva elicits a burst of jasmonic acid (JA) and the induction of late responding defense genes such as proteinase inhibitor 2 (Pin2). Transcripts encoding early response genes associated with the JA pathway were not affected by saliva. We also observed a delayed response to saliva with increased densities of Type VI glandular trichomes in newly emerged leaves. Proteomic analysis of saliva revealed glucose oxidase (GOX) was the most abundant protein identified and we confirmed that it plays a primary role in the induction of defenses in tomato. These results suggest that the recognition of GOX in tomato may represent a case for effector-triggered immunity. Examination of saliva from other caterpillar species indicates that saliva from the noctuids Spodoptera exigua and Heliothis virescens also induced Pin2 transcripts

    Moving toward a system genetics view of disease

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    Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone

    Avian Pathogenic Escherichia coli (APEC) Infection Alters Bone Marrow Transcriptome in Chickens

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    Avian pathogenic Escherichia coli (APEC) is a major cause of disease impacting animal health. The bone marrow is the reservoir of immature immune cells; however, it has not been examined to date for gene expression related to developmental changes (cell differentiation, maturation, programming) after APEC infection. Here, we study gene expression in the bone marrow between infected and non-infected animals, and between infected animals with mild (resistant) versus severe (susceptible) pathology, at two times post-infection. We sequenced 24 bone marrow RNA libraries generated from the six different treatment groups with four replicates each, and obtained an average of 22 million single-end, 100-bp reads per library. Genes were detected as differentially expressed (DE) between APEC treatments (mild pathology, severe pathology, and mock-challenged) at a given time point, or DE between 1 and 5 days post-infection (dpi) within the same treatment group. Results demonstrate that many immune cells, genes and related pathways are key contributors to the different responses to APEC infection between susceptible and resistant birds and between susceptible and non-challenged birds, at both times post-infection. In susceptible birds, lymphocyte differentiation, proliferation, and maturation were greatly impaired, while the innate and adaptive immune responses, including dendritic cells, monocytes and killer cell activity, TLR- and NOD-like receptor signaling, as well as T helper cells and many cytokine activities, were markedly enhanced. The resistant birds’ immune system, however, was similar to that of non-challenged birds. The DE genes in the immune cells and identified signaling models are representative of activation and resolution of infection in susceptible birds at both post-infection days. These novel results characterizing transcriptomic response to APEC infection reveal that there is combinatorial activity of multiple genes controlling myeloid cells, and B and T cell lymphopoiesis, as well as immune responses occurring in the bone marrow in these early stages of response to infection
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