173 research outputs found

    Human Myeloma Marrow Cells in Immunologically Deficient Mice

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    Intact human bone marrow cells from 7 patients with myelomatosis were inoculated intravenously into adolescent CBA mice rendered immunologically deficient by thymectomy followed by total body irradiation (600 rad). Each inoculum of human myeloma marrow cells and subsequent passages of intact mouse marrow and spleen cells resulted in the presence of morphological changes in the marrow, spleen and peripheral blood of a proportion of these mice which were closely similar to those seen in the human donor. A substantial amount of human immunoglobulin (IgG and IgA) was detected in the sera of some of the mice showing morphological changes. Mice prepared identically but remaining uninoculated or receiving intact human bone marrow cells from 3 patients with no evidence of haematological malignancy showed none of these changes when examined after similar intervals

    JGromacs: A Java Package for Analyzing Protein Simulations

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    UNLABELLED: In this paper, we introduce JGromacs, a Java API (Application Programming Interface) that facilitates the development of cross-platform data analysis applications for Molecular Dynamics (MD) simulations. The API supports parsing and writing file formats applied by GROMACS (GROningen MAchine for Chemical Simulations), one of the most widely used MD simulation packages. JGromacs builds on the strengths of object-oriented programming in Java by providing a multilevel object-oriented representation of simulation data to integrate and interconvert sequence, structure, and dynamics information. The easy-to-learn, easy-to-use, and easy-to-extend framework is intended to simplify and accelerate the implementation and development of complex data analysis algorithms. Furthermore, a basic analysis toolkit is included in the package. The programmer is also provided with simple tools (e.g., XML-based configuration) to create applications with a user interface resembling the command-line interface of GROMACS applications. AVAILABILITY: JGromacs and detailed documentation is freely available from http://sbcb.bioch.ox.ac.uk/jgromacs under a GPLv3 license

    A Structure-Based Approach for Detection of Thiol Oxidoreductases and Their Catalytic Redox-Active Cysteine Residues

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    Cysteine (Cys) residues often play critical roles in proteins, for example, in the formation of structural disulfide bonds, metal binding, targeting proteins to the membranes, and various catalytic functions. However, the structural determinants for various Cys functions are not clear. Thiol oxidoreductases, which are enzymes containing catalytic redox-active Cys residues, have been extensively studied, but even for these proteins there is little understanding of what distinguishes their catalytic redox Cys from other Cys functions. Herein, we characterized thiol oxidoreductases at a structural level and developed an algorithm that can recognize these enzymes by (i) analyzing amino acid and secondary structure composition of the active site and its similarity to known active sites containing redox Cys and (ii) calculating accessibility, active site location, and reactivity of Cys. For proteins with known or modeled structures, this method can identify proteins with catalytic Cys residues and distinguish thiol oxidoreductases from the enzymes containing other catalytic Cys types. Furthermore, by applying this procedure to Saccharomyces cerevisiae proteins containing conserved Cys, we could identify the majority of known yeast thiol oxidoreductases. This study provides insights into the structural properties of catalytic redox-active Cys and should further help to recognize thiol oxidoreductases in protein sequence and structure databases

    Subcellular localization and formation of huntingtin aggregates correlates with symptom onset and progression in a Huntington's disease model

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    Huntington's disease is caused by the expansion of a CAG repeat within exon 1 of the HTT gene, which is unstable, leading to further expansion, the extent of which is brain region and peripheral tissue specific. The identification of DNA repair genes as genetic modifiers of Huntington's disease, that were known to abrogate somatic instability in Huntington's disease mouse models, demonstrated that somatic CAG expansion is central to disease pathogenesis, and that the CAG repeat threshold for pathogenesis in specific brain cells might not be known. We have previously shown that the HTT gene is incompletely spliced generating a small transcript that encodes the highly pathogenic exon 1 HTT protein. The longer the CAG repeat, the more of this toxic fragment is generated, providing a pathogenic consequence for somatic expansion. Here, we have used the R6/2 mouse model to investigate the molecular and behavioural consequences of expressing exon 1 HTT with 90 CAGs, a mutation that causes juvenile Huntington's disease, compared to R6/2 mice carrying ∼200 CAGs, a repeat expansion of a size rarely found in Huntington's disease patient's blood, but which has been detected in post-mortem brains as a consequence of somatic CAG repeat expansion. We show that nuclear aggregation occurred earlier in R6/2(CAG)(90) mice and that this correlated with the onset of transcriptional dysregulation. Whereas in R6/2(CAG)(200) mice, cytoplasmic aggregates accumulated rapidly and closely tracked with the progression of behavioural phenotypes and with end-stage disease. We find that aggregate species formed in the R6/2(CAG)(90) brains have different properties to those in the R6/2(CAG)(200) mice. Within the nucleus, they retain a diffuse punctate appearance throughout the course of the disease, can be partially solubilized by detergents and have a greater seeding potential in young mice. In contrast, aggregates from R6/2(CAG)(200) brains polymerize into larger structures that appear as inclusion bodies. These data emphasize that a subcellular analysis, using multiple complementary approaches, must be undertaken in order to draw any conclusions about the relationship between HTT aggregation and the onset and progression of disease phenotypes
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