34 research outputs found

    Identification of Nucleases and Phosphatases by Direct Biochemical Screen of the Saccharomyces cerevisiae Proteome

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    The availability of yeast strain collections expressing individually tagged proteins to facilitate one-step purification provides a powerful approach to identify proteins with particular biochemical activities. To identify novel exo- and endo-nucleases that might function in DNA repair, we undertook a proteomic screen making use of the movable ORF (MORF) library of yeast expression plasmids. This library consists of 5,854 yeast strains each expressing a unique yeast ORF fused to a tripartite tag consisting of His6, an HA epitope, a protease 3C cleavage site, and the IgG-binding domain (ZZ) from protein A, under the control of the GAL1 promoter for inducible expression. Pools of proteins were partially purified on IgG sepharose and tested for nuclease activity using three different radiolabeled DNA substrates. Several known nucleases and phosphatases were identified, as well as two new members of the histidine phosphatase superfamily, which includes phosphoglycerate mutases and phosphatases. Subsequent characterization revealed YDR051c/Det1 to be an acid phosphatase with broad substrate specificity, whereas YOR283w has a broad pH range and hydrolyzes hydrophilic phosphorylated substrates. Although no new nuclease activities were identified from this screen, we did find phosphatase activity associated with a protein of unknown function, YOR283w, and with the recently characterized protein Det1. This knowledge should guide further genetic and biochemical characterization of these proteins

    The adipocyte: a model for integration of endocrine and metabolic signaling in energy metabolism regulation

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    The ability to ensure continuous availability of energy despite highly variable supplies in the environment is a major determinant of the survival of all species. In higher organisms, including mammals, the capacity to efficiently store excess energy as triglycerides in adipocytes, from which stored energy could be rapidly released for use at other sites, was developed. To orchestrate the processes of energy storage and release, highly integrated systems operating on several physiological levels have evolved. The adipocyte is no longer considered a passive bystander, because fat cells actively secrete many members of the cytokine family, such as leptin, tumor necrosis factor-alpha, and interleukin-6, among other cytokine signals, which influence peripheral fuel storage, mobilization, and combustion, as well as energy homeostasis. The existence of a network of adipose tissue signaling pathways, arranged in a hierarchical fashion, constitutes a metabolic repertoire that enables the organism to adapt to a wide range of different metabolic challenges, such as starvation, stress, infection, and short periods of gross energy excess

    FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

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    <p>Abstract</p> <p>Background</p> <p>The availability of sequence data of human pathogenic fungi generates opportunities to develop Bioinformatics tools and resources for vaccine development towards benefitting at-risk patients.</p> <p>Description</p> <p>We have developed a fungal adhesin predictor and an immunoinformatics database with predicted adhesins. Based on literature search and domain analysis, we prepared a positive dataset comprising adhesin protein sequences from human fungal pathogens <it>Candida albicans, Candida glabrata, Aspergillus fumigatus, Coccidioides immitis, Coccidioides posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Pneumocystis carinii, Pneumocystis jirovecii and Paracoccidioides brasiliensis</it>. The negative dataset consisted of proteins with high probability to function intracellularly. We have used 3945 compositional properties including frequencies of mono, doublet, triplet, and multiplets of amino acids and hydrophobic properties as input features of protein sequences to Support Vector Machine. Best classifiers were identified through an exhaustive search of 588 parameters and meeting the criteria of best Mathews Correlation Coefficient and lowest coefficient of variation among the 3 fold cross validation datasets. The "FungalRV adhesin predictor" was built on three models whose average Mathews Correlation Coefficient was in the range 0.89-0.90 and its coefficient of variation across three fold cross validation datasets in the range 1.2% - 2.74% at threshold score of 0. We obtained an overall MCC value of 0.8702 considering all 8 pathogens, namely, <it>C. albicans, C. glabrata, A. fumigatus, B. dermatitidis, C. immitis, C. posadasii, H. capsulatum </it>and <it>P. brasiliensis </it>thus showing high sensitivity and specificity at a threshold of 0.511. In case of <it>P. brasiliensis </it>the algorithm achieved a sensitivity of 66.67%. A total of 307 fungal adhesins and adhesin like proteins were predicted from the entire proteomes of eight human pathogenic fungal species. The immunoinformatics analysis data on these proteins were organized for easy user interface analysis. A Web interface was developed for analysis by users. The predicted adhesin sequences were processed through 18 immunoinformatics algorithms and these data have been organized into MySQL backend. A user friendly interface has been developed for experimental researchers for retrieving information from the database.</p> <p>Conclusion</p> <p>FungalRV webserver facilitating the discovery process for novel human pathogenic fungal adhesin vaccine has been developed.</p

    Fungal enzyme sets for plant polysaccharide degradation

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    Enzymatic degradation of plant polysaccharides has many industrial applications, such as within the paper, food, and feed industry and for sustainable production of fuels and chemicals. Cellulose, hemicelluloses, and pectins are the main components of plant cell wall polysaccharides. These polysaccharides are often tightly packed, contain many different sugar residues, and are branched with a diversity of structures. To enable efficient degradation of these polysaccharides, fungi produce an extensive set of carbohydrate-active enzymes. The variety of the enzyme set differs between fungi and often corresponds to the requirements of its habitat. Carbohydrate-active enzymes can be organized in different families based on the amino acid sequence of the structurally related catalytic modules. Fungal enzymes involved in plant polysaccharide degradation are assigned to at least 35 glycoside hydrolase families, three carbohydrate esterase families and six polysaccharide lyase families. This mini-review will discuss the enzymes needed for complete degradation of plant polysaccharides and will give an overview of the latest developments concerning fungal carbohydrate-active enzymes and their corresponding families

    The CCP4 suite: integrative software for macromolecular crystallography

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    The Collaborative Computational Project No. 4 (CCP4) is a UK-led international collective with a mission to develop, test, distribute and promote software for macromolecular crystallography. The CCP4 suite is a multiplatform collection of programs brought together by familiar execution routines, a set of common libraries and graphical interfaces. The CCP4 suite has experienced several considerable changes since its last reference article, involving new infrastructure, original programs and graphical interfaces. This article, which is intended as a general literature citation for the use of the CCP4 software suite in structure determination, will guide the reader through such transformations, offering a general overview of the new features and outlining future developments. As such, it aims to highlight the individual programs that comprise the suite and to provide the latest references to them for perusal by crystallographers around the world

    Satellite DNA beta overrides the pathogenicity phenotype of the C4 gene of tomato leaf curl virus but does not compensate for loss of function of the coat protein and V2 genes

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    We have investigated the ability of satellite DNA β to complement mutations in the CP, V2 and C4 genes of the monopartite begomovirus, tomato leaf curl virus, which are potentially involved in movement. A mutation in the coat protein was not complemented by DNA β. Mutations of the C4 and V2 genes attenuated and abolished symptoms, respectively. In the presence of the C4 mutant, but not the V2 mutant, DNA β induced typical symptoms, confirming that the satellite encodes a dominant symptom determinant. In contrast to the C4 mutant, DNA β did not enhance the viral DNA levels of the V2 mutant, suggesting that V2 is required for this phenomenon. The significance of these findings is discussed based on our present understanding of the functions of the viral genes and DNA β.M. Saeed, S. Mansoor, M. A. Rezaian, R. W. Briddon and J. W. Randle
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