906 research outputs found

    The Ribosomal Database Project (RDP-II): sequences and tools for high-throughput rRNA analysis

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    The Ribosomal Database Project (RDP-II) provides the research community with aligned and annotated rRNA gene sequences, along with analysis services and a phylogenetically consistent taxonomic framework for these data. Updated monthly, these services are made available through the RDP-II website (http://rdp.cme.msu.edu/). RDP-II release 9.21 (August 2004) contains 101 632 bacterial small subunit rRNA gene sequences in aligned and annotated format. High-throughput tools for initial taxonomic placement, identification of related sequences, probe and primer testing, data navigation and subalignment download are provided. The RDP-II email address for questions or comments is [email protected]

    The ribosomal database project (RDP-II): introducing myRDP space and quality controlled public data

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    Substantial new features have been implemented at the Ribosomal Database Project in response to the increased importance of high-throughput rRNA sequence analysis in microbial ecology and related disciplines. The most important changes include quality analysis, including chimera detection, for all available rRNA sequences and the introduction of myRDP Space, a new web component designed to help researchers place their own data in context with the RDP's data. In addition, new video tutorials describe how to use RDP features. Details about RDP data and analytical functions can be found at the RDP-II website ()

    Spectroscopic and Mechanistic Studies of Heterodimetallic Forms of Metallo-β-lactamase NDM-1

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    In an effort to characterize the roles of each metal ion in metallo-β-lactamase NDM-1, heterodimetallic analogues (CoCo-, ZnCo-, and CoCd-) of the enzyme were generated and characterized. UV–vis, 1H NMR, EPR, and EXAFS spectroscopies were used to confirm the fidelity of the metal substitutions, including the presence of a homogeneous, heterodimetallic cluster, with a single-atom bridge. This marks the first preparation of a metallo-β-lactamase selectively substituted with a paramagnetic metal ion, Co(II), either in the Zn1 (CoCd-NDM-1) or in the Zn2 site (ZnCo-NDM-1), as well as both (CoCo-NDM-1). We then used these metal-substituted forms of the enzyme to probe the reaction mechanism, using steady-state and stopped-flow kinetics, stopped-flow fluorescence, and rapid-freeze-quench EPR. Both metal sites show significant effects on the kinetic constants, and both paramagnetic variants (CoCd- and ZnCo-NDM-1) showed significant structural changes on reaction with substrate. These changes are discussed in terms of a minimal kinetic mechanism that incorporates all of the data

    Emergent complex neural dynamics

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    A large repertoire of spatiotemporal activity patterns in the brain is the basis for adaptive behaviour. Understanding the mechanism by which the brain's hundred billion neurons and hundred trillion synapses manage to produce such a range of cortical configurations in a flexible manner remains a fundamental problem in neuroscience. One plausible solution is the involvement of universal mechanisms of emergent complex phenomena evident in dynamical systems poised near a critical point of a second-order phase transition. We review recent theoretical and empirical results supporting the notion that the brain is naturally poised near criticality, as well as its implications for better understanding of the brain

    The Ribosomal Database Project: improved alignments and new tools for rRNA analysis

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    The Ribosomal Database Project (RDP) provides researchers with quality-controlled bacterial and archaeal small subunit rRNA alignments and analysis tools. An improved alignment strategy uses the Infernal secondary structure aware aligner to provide a more consistent higher quality alignment and faster processing of user sequences. Substantial new analysis features include a new Pyrosequencing Pipeline that provides tools to support analysis of ultra high-throughput rRNA sequencing data. This pipeline offers a collection of tools that automate the data processing and simplify the computationally intensive analysis of large sequencing libraries. In addition, a new Taxomatic visualization tool allows rapid visualization of taxonomic inconsistencies and suggests corrections, and a new class Assignment Generator provides instructors with a lesson plan and individualized teaching materials. Details about RDP data and analytical functions can be found at http://rdp.cme.msu.edu/

    Biophysical and electrochemical studies of protein-nucleic acid interactions

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    This review is devoted to biophysical and electrochemical methods used for studying protein-nucleic acid (NA) interactions. The importance of NA structure and protein-NA recognition for essential cellular processes, such as replication or transcription, is discussed to provide background for description of a range of biophysical chemistry methods that are applied to study a wide scope of protein-DNA and protein-RNA complexes. These techniques employ different detection principles with specific advantages and limitations and are often combined as mutually complementary approaches to provide a complete description of the interactions. Electrochemical methods have proven to be of great utility in such studies because they provide sensitive measurements and can be combined with other approaches that facilitate the protein-NA interactions. Recent applications of electrochemical methods in studies of protein-NA interactions are discussed in detail

    FLNC Gene Splice Mutations Cause Dilated\ua0Cardiomyopathy

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    OBJECTIVE: To identify novel dilated cardiomyopathy (DCM) causing genes, and to elucidate the pathological mechanism leading to DCM by utilizing zebrafish as a model organism. BACKGROUND: DCM, a major cause of heart failure, is frequently familial and caused by a genetic defect. However, only 50% of DCM cases can be attributed to a known DCM gene variant, motivating the ongoing search for novel disease genes. METHODS: We performed whole exome sequencing (WES) in two multigenerational Italian families and one US family with arrhythmogenic DCM without skeletal muscle defects, in whom prior genetic testing had been unrevealing. Pathogenic variants were sought by a combination of bioinformatic filtering and cosegregation testing among affected individuals within the families. We performed function assays and generated a zebrafish morpholino knockdown model. RESULTS: A novel filamin C gene splicing variant (FLNC c.7251+1 G>A) was identified by WES in all affected family members in the two Italian families. A separate novel splicing mutation (FLNC c.5669-1delG) was identified in the US family. Western blot analysis of cardiac heart tissue from an affected individual showed decreased FLNC protein, supporting a haploinsufficiency model of pathogenesis. To further analyze this model, a morpholino knockdown of the ortholog filamin Cb in zebrafish was created which resulted in abnormal cardiac function and ultrastructure. CONCLUSIONS: Using WES, we identified two novel FLNC splicing variants as the likely cause of DCM in three families. We provided protein expression and in vivo zebrafish data supporting haploinsufficiency as the pathogenic mechanism leading to DCM

    Big-Data-Driven Materials Science and its FAIR Data Infrastructure

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    This chapter addresses the forth paradigm of materials research -- big-data driven materials science. Its concepts and state-of-the-art are described, and its challenges and chances are discussed. For furthering the field, Open Data and an all-embracing sharing, an efficient data infrastructure, and the rich ecosystem of computer codes used in the community are of critical importance. For shaping this forth paradigm and contributing to the development or discovery of improved and novel materials, data must be what is now called FAIR -- Findable, Accessible, Interoperable and Re-purposable/Re-usable. This sets the stage for advances of methods from artificial intelligence that operate on large data sets to find trends and patterns that cannot be obtained from individual calculations and not even directly from high-throughput studies. Recent progress is reviewed and demonstrated, and the chapter is concluded by a forward-looking perspective, addressing important not yet solved challenges.Comment: submitted to the Handbook of Materials Modeling (eds. S. Yip and W. Andreoni), Springer 2018/201

    A novel malaria vaccine candidate antigen expressed in Tetrahymena thermophila

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    Development of effective malaria vaccines is hampered by the problem of producing correctly folded Plasmodium proteins for use as vaccine components. We have investigated the use of a novel ciliate expression system, Tetrahymena thermophila, as a P. falciparum vaccine antigen platform. A synthetic vaccine antigen composed of N-terminal and C-terminal regions of merozoite surface protein-1 (MSP-1) was expressed in Tetrahymena thermophila. The recombinant antigen was secreted into the culture medium and purified by monoclonal antibody (mAb) affinity chromatography. The vaccine was immunogenic in MF1 mice, eliciting high antibody titers against both N- and C-terminal components. Sera from immunized animals reacted strongly with P. falciparum parasites from three antigenically different strains by immunofluorescence assays, confirming that the antibodies produced are able to recognize parasite antigens in their native form. Epitope mapping of serum reactivity with a peptide library derived from all three MSP-1 Block 2 serotypes confirmed that the MSP-1 Block 2 hybrid component of the vaccine had effectively targeted all three serotypes of this polymorphic region of MSP-1. This study has successfully demonstrated the use of Tetrahymena thermophila as a recombinant protein expression platform for the production of malaria vaccine antigens
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