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Methionine-mediated gene expression and characterization of the CmhR regulon in Streptococcus pneumoniae

1 , 2 , 3 , , 1

Microbial Genomics

Microbiology Society

Methionine, CmhR, Pneumococcus, MetE, MetQ

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      Abstract

      This study investigated the transcriptomic response of Streptococcus pneumoniae D39 to methionine. Transcriptome comparison of the S. pneumoniae D39 wild-type grown in chemically defined medium with 0–10 mM methionine revealed the elevated expression of various genes/operons involved in methionine synthesis and transport (fhs, folD, gshT, metA, metB-csd, metEF, metQ, tcyB, spd-0150, spd-0431 and spd-0618). Furthermore, β-galactosidase assays and quantitative RT-PCR studies demonstrated that the transcriptional regulator, CmhR (SPD-0588), acts as a transcriptional activator of the fhs, folD, metB-csd, metEF, metQ and spd-0431 genes. A putative regulatory site of CmhR was identified in the promoter region of CmhR-regulated genes and this CmhR site was further confirmed by promoter mutational experiments.

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      Most cited references 60

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      Analyzing real-time PCR data by the comparative CT method

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        Data, information, knowledge and principle: back to metabolism in KEGG

        In the hierarchy of data, information and knowledge, computational methods play a major role in the initial processing of data to extract information, but they alone become less effective to compile knowledge from information. The Kyoto Encyclopedia of Genes and Genomes (KEGG) resource (http://www.kegg.jp/ or http://www.genome.jp/kegg/) has been developed as a reference knowledge base to assist this latter process. In particular, the KEGG pathway maps are widely used for biological interpretation of genome sequences and other high-throughput data. The link from genomes to pathways is made through the KEGG Orthology system, a collection of manually defined ortholog groups identified by K numbers. To better automate this interpretation process the KEGG modules defined by Boolean expressions of K numbers have been expanded and improved. Once genes in a genome are annotated with K numbers, the KEGG modules can be computationally evaluated revealing metabolic capacities and other phenotypic features. The reaction modules, which represent chemical units of reactions, have been used to analyze design principles of metabolic networks and also to improve the definition of K numbers and associated annotations. For translational bioinformatics, the KEGG MEDICUS resource has been developed by integrating drug labels (package inserts) used in society.
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          Fitting a mixture model by expectation maximization to discover motifs in biopolymers.

          The algorithm described in this paper discovers one or more motifs in a collection of DNA or protein sequences by using the technique of expectation maximization to fit a two-component finite mixture model to the set of sequences. Multiple motifs are found by fitting a mixture model to the data, probabilistically erasing the occurrences of the motif thus found, and repeating the process to find successive motifs. The algorithm requires only a set of unaligned sequences and a number specifying the width of the motifs as input. It returns a model of each motif and a threshold which together can be used as a Bayes-optimal classifier for searching for occurrences of the motif in other databases. The algorithm estimates how many times each motif occurs in each sequence in the dataset and outputs an alignment of the occurrences of the motif. The algorithm is capable of discovering several different motifs with differing numbers of occurrences in a single dataset.
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            Author and article information

            Affiliations
            [ 1]Department of Molecular Genetics, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen , Nijenborgh 7, 9747 AG, Groningen, The Netherlands
            [ 2]Department of Bioinformatics and Biotechnology, G C University , Faisalabad, Pakistan
            [ 3]Department of Microbiology, Tumor and Cell Biology, , Karolinska Institutet , Nobels väg 16, Stockholm, SE-171 77, Sweden
            Author notes
            Correspondence Oscar P. Kuipers ( o.p.kuipers@ 123456rug.nl )

            All supporting data, code and protocols have been provided within the article or through supplementary data files.

            Journal
            Microb Genom
            MGen
            Microbial Genomics
            Microbiology Society
            2057-5858
            October 2016
            21 October 2016
            : 2
            : 10
            5359408
            mgen000091
            10.1099/mgen.0.000091
            © 2016 The Authors

            This is an open access article under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

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            Research Paper
            Systems Microbiology: Transcriptomics, proteomics, networks
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            metq, mete, pneumococcus, cmhr, methionine

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