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Graphical representation of ribosomal RNA probe accessibility data using ARB software package

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      Abstract

      Background

      Taxon specific hybridization probes in combination with a variety of commonly used hybridization formats nowadays are standard tools in microbial identification. A frequently applied technology, fluorescence in situ hybridization (FISH), besides single cell identification, allows the localization and functional studies of the microbial community composition. Careful in silico design and evaluation of potential oligonucleotide probe targets is therefore crucial for performing successful hybridization experiments.

      Results

      The PROBE Design tools of the ARB software package take into consideration several criteria such as number, position and quality of diagnostic sequence differences while designing oligonucleotide probes. Additionally, new visualization tools were developed to enable the user to easily examine further sequence associated criteria such as higher order structure, conservation, G+C content, transition-transversion profiles and in situ target accessibility patterns. The different types of sequence associated information (SAI) can be visualized by user defined background colors within the ARB primary and secondary structure editors as well as in the PROBE Match tool.

      Conclusion

      Using this tool, in silico probe design and evaluation can be performed with respect to in situ probe accessibility data. The evaluation of proposed probe targets with respect to higher-order rRNA structure is of importance for successful design and performance of in situ hybridization experiments. The entire ARB software package along with the probe accessibility data is available from the ARB home page http://www.arb-home.de.

      Related collections

      Most cited references 21

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      ARB: a software environment for sequence data.

      The ARB (from Latin arbor, tree) project was initiated almost 10 years ago. The ARB program package comprises a variety of directly interacting software tools for sequence database maintenance and analysis which are controlled by a common graphical user interface. Although it was initially designed for ribosomal RNA data, it can be used for any nucleic and amino acid sequence data as well. A central database contains processed (aligned) primary structure data. Any additional descriptive data can be stored in database fields assigned to the individual sequences or linked via local or worldwide networks. A phylogenetic tree visualized in the main window can be used for data access and visualization. The package comprises additional tools for data import and export, sequence alignment, primary and secondary structure editing, profile and filter calculation, phylogenetic analyses, specific hybridization probe design and evaluation and other components for data analysis. Currently, the package is used by numerous working groups worldwide.
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        Phylogenetic identification and in situ detection of individual microbial cells without cultivation.

        The frequent discrepancy between direct microscopic counts and numbers of culturable bacteria from environmental samples is just one of several indications that we currently know only a minor part of the diversity of microorganisms in nature. A combination of direct retrieval of rRNA sequences and whole-cell oligonucleotide probing can be used to detect specific rRNA sequences of uncultured bacteria in natural samples and to microscopically identify individual cells. Studies have been performed with microbial assemblages of various complexities ranging from simple two-component bacterial endosymbiotic associations to multispecies enrichments containing magnetotactic bacteria to highly complex marine and soil communities. Phylogenetic analysis of the retrieved rRNA sequence of an uncultured microorganism reveals its closest culturable relatives and may, together with information on the physicochemical conditions of its natural habitat, facilitate more directed cultivation attempts. For the analysis of complex communities such as multispecies biofilms and activated-sludge flocs, a different approach has proven advantageous. Sets of probes specific to different taxonomic levels are applied consecutively beginning with the more general and ending with the more specific (a hierarchical top-to-bottom approach), thereby generating increasingly precise information on the structure of the community. Not only do rRNA-targeted whole-cell hybridizations yield data on cell morphology, specific cell counts, and in situ distributions of defined phylogenetic groups, but also the strength of the hybridization signal reflects the cellular rRNA content of individual cells. From the signal strength conferred by a specific probe, in situ growth rates and activities of individual cells might be estimated for known species. In many ecosystems, low cellular rRNA content and/or limited cell permeability, combined with background fluorescence, hinders in situ identification of autochthonous populations. Approaches to circumvent these problems are discussed in detail.
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          Structure of the 30S ribosomal subunit.

          Genetic information encoded in messenger RNA is translated into protein by the ribosome, which is a large nucleoprotein complex comprising two subunits, denoted 30S and 50S in bacteria. Here we report the crystal structure of the 30S subunit from Thermus thermophilus, refined to 3 A resolution. The final atomic model rationalizes over four decades of biochemical data on the ribosome, and provides a wealth of information about RNA and protein structure, protein-RNA interactions and ribosome assembly. It is also a structural basis for analysis of the functions of the 30S subunit, such as decoding, and for understanding the action of antibiotics. The structure will facilitate the interpretation in molecular terms of lower resolution structural data on several functional states of the ribosome from electron microscopy and crystallography.
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            Author and article information

            Affiliations
            [1 ]Lehrstuhl für Mikrobiologie, Technische Universität München, D-85350 Freising Germany
            [2 ]Max Plank Institute for Marine Microbiology, D-28359 Bremen, Germany
            [3 ]International University Bremen, D-28759 Bremen, Germany
            [4 ]Lehrstuhl für Rechnertechnik und Rechnerorganisation, Technische Universität München, D-85748 Garching, Germany
            Contributors
            Journal
            BMC Bioinformatics
            BMC Bioinformatics
            BioMed Central (London )
            1471-2105
            2005
            21 March 2005
            : 6
            : 61
            1274257
            1471-2105-6-61
            15777482
            10.1186/1471-2105-6-61
            Copyright © 2005 Kumar et al; licensee BioMed Central Ltd.

            This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            Categories
            Software

            Bioinformatics & Computational biology

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