784 research outputs found

    Functional expression of the yeast alpha-factor receptor in Xenopus oocytes

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    The STE2 gene of the yeast Saccharomyces cerevisiae encodes a 431- residue polypeptide that has been shown by chemical cross-linking and genetic studies to be a component of the receptor for the peptide mating pheromone, alpha-factor. To demonstrate directly that the ligand binding site of the alpha-factor receptor is comprised solely of the STE2 gene product, the STE2 protein was expressed in Xenopus oocytes. Oocytes microinjected with synthetic STE2 mRNA displayed specific surface binding for 35S-labeled alpha-factor (up to 40 sites/micron2/ng RNA). Oocytes injected with either STE2 antisense RNA or heterologous receptor mRNA (nicotinic acetylcholine receptor alpha, beta, gamma, and delta subunit mRNAs) showed no binding activity (indistinguishable from uninjected control oocytes). The apparent KD (7 nM) of the alpha-factor binding sites expressed on the oocyte surface, determined by competition binding studies, agreed with the values reported for intact yeast cells and yeast plasma membrane fractions. These findings demonstrate that the STE2 gene product is the only yeast polypeptide required for biogenesis of a functional alpha-factor receptor. Electrophysiological measurements indicated that the membrane conductance of oocytes injected with STE2 mRNA, or with both STE2 and GPA1 (encoding a yeast G protein alpha-subunit) mRNAs, did not change and was not affected by pheromone binding. Thus, the alpha-factor receptor, like mammalian G protein-coupled receptors, apparently lacks activity as an intrinsic or ligand-gated ion channel. This report is the first instance in which a membrane-bound receptor from a unicellular eukaryote has been expressed in a vertebrate cell

    Absence of erythrocyte sequestration in a case of babesiosis in a splenectomized human patient

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    BACKGROUND: The importance of vascular occlusion in the pathogenesis of human haemoprotozoal disease is unresolved. METHODS: Giemsa-stained tissue sections from a human case of Babesia microti infection in a splenectomized patient with chronic lymphocytic leukaemia and colon cancer were examined to ascertain the distribution of parasitized erythrocytes within the vascular lumen. RESULTS: No evidence of sequestration was observed. CONCLUSION: This first report on the vascular location of B. microti in human tissue suggests that severe multi-organ failure due to babesiosis is independent of sequestration of parasitized erythrocytes. A similar pathogenesis may also cause multi-organ failure in other intraerythrocytic protozoal infections, including falciparum malaria

    The PAL1 gene product is a peroxisomal ATP-binding cassette transporter in the yeast Saccharomyces cerevisiae.

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    Abstract. The PAL1 gene was isolated using PCR and degenerate oligonucleotide primers corresponding to highly conserved amino acid sequence motifs diagnostic of the ATP-binding cassette domain of the superfamily of membrane-bound transport proteins typified by mammalian multidrug resistance transporter 1 and Saccharomyces cerevisiae Ste6. The deduced PAL1 gene product is similar in length to, has the same predicted topology as, and shares the highest degree of amino acid sequence identity with two human proteins, adrenoleukodyatrophy protein and peroxisomal membrane protein (70 kD), which are both presumptive ATP-binding cassette transporters thought to be constituents of the peroxisomal membrane. As judged by hybridization of a PAL1 probe to isolated RNA and b

    Automatic generation of alignments for 3D QSAR analyses

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    Many 3D QSAR methods require the alignment of the molecules in a dataset, which can require a fair amount of manual effort in deciding upon a rational basis for the superposition. This paper describes the use of FBSS, a pro-ram for field-based similarity searching in chemical databases, for generating such alignments automatically. The CoMFA and CoMSIA experiments with several literature datasets show that the QSAR models resulting from the FBSS alignments are broadly comparable in predictive performance with the models resulting from manual alignments

    Axial dipolar dynamo action in the Taylor-Green vortex

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    We present a numerical study of the magnetic field generated by the Taylor-Green vortex. We show that periodic boundary conditions can be used to mimic realistic boundary conditions by prescribing the symmetries of the velocity and magnetic fields. This gives insight in some problems of central interest for dynamos: the possible effect of velocity fluctuations on the dynamo threshold, the role of boundary conditions on the threshold and on the geometry of the magnetic field generated by dynamo action. In particular, we show that an axial dipolar dynamo similar to the one observed in a recent experiment can be obtained with an appropriate choice of the symmetries of the magnetic field. The nonlinear saturation is studied and a simple model explaining the magnetic Prandtl number dependence of the super/sub critical nature of the dynamo transition is given

    Network-Free Inference of Knockout Effects in Yeast

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    Perturbation experiments, in which a certain gene is knocked out and the expression levels of other genes are observed, constitute a fundamental step in uncovering the intricate wiring diagrams in the living cell and elucidating the causal roles of genes in signaling and regulation. Here we present a novel framework for analyzing large cohorts of gene knockout experiments and their genome-wide effects on expression levels. We devise clustering-like algorithms that identify groups of genes that behave similarly with respect to the knockout data, and utilize them to predict knockout effects and to annotate physical interactions between proteins as inhibiting or activating. Differing from previous approaches, our prediction approach does not depend on physical network information; the latter is used only for the annotation task. Consequently, it is both more efficient and of wider applicability than previous methods. We evaluate our approach using a large scale collection of gene knockout experiments in yeast, comparing it to the state-of-the-art SPINE algorithm. In cross validation tests, our algorithm exhibits superior prediction accuracy, while at the same time increasing the coverage by over 25-fold. Significant coverage gains are obtained also in the annotation of the physical network
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