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      Transcriptome analysis of thermophilic methylotrophic Bacillus methanolicus MGA3 using RNA-sequencing provides detailed insights into its previously uncharted transcriptional landscape

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          Abstract

          Background

          Bacillus methanolicus MGA3 is a thermophilic, facultative ribulose monophosphate (RuMP) cycle methylotroph. Together with its ability to produce high yields of amino acids, the relevance of this microorganism as a promising candidate for biotechnological applications is evident. The B. methanolicus MGA3 genome consists of a 3,337,035 nucleotides (nt) circular chromosome, the 19,174 nt plasmid pBM19 and the 68,999 nt plasmid pBM69. 3,218 protein-coding regions were annotated on the chromosome, 22 on pBM19 and 82 on pBM69. In the present study, the RNA-seq approach was used to comprehensively investigate the transcriptome of B. methanolicus MGA3 in order to improve the genome annotation, identify novel transcripts, analyze conserved sequence motifs involved in gene expression and reveal operon structures. For this aim, two different cDNA library preparation methods were applied: one which allows characterization of the whole transcriptome and another which includes enrichment of primary transcript 5′-ends.

          Results

          Analysis of the primary transcriptome data enabled the detection of 2,167 putative transcription start sites (TSSs) which were categorized into 1,642 TSSs located in the upstream region (5′-UTR) of known protein-coding genes and 525 TSSs of novel antisense, intragenic, or intergenic transcripts. Firstly, 14 wrongly annotated translation start sites (TLSs) were corrected based on primary transcriptome data. Further investigation of the identified 5′-UTRs resulted in the detailed characterization of their length distribution and the detection of 75 hitherto unknown cis-regulatory RNA elements. Moreover, the exact TSSs positions were utilized to define conserved sequence motifs for translation start sites, ribosome binding sites and promoters in B. methanolicus MGA3. Based on the whole transcriptome data set, novel transcripts, operon structures and mRNA abundances were determined. The analysis of the operon structures revealed that almost half of the genes are transcribed monocistronically (940), whereas 1,164 genes are organized in 381 operons. Several of the genes related to methylotrophy had highly abundant transcripts.

          Conclusion

          The extensive insights into the transcriptional landscape of B. methanolicus MGA3, gained in this study, represent a valuable foundation for further comparative quantitative transcriptome analyses and possibly also for the development of molecular biology tools which at present are very limited for this organism.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-015-1239-4) contains supplementary material, which is available to authorized users.

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          Most cited references 88

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          Rfam: an RNA family database.

          Rfam is a collection of multiple sequence alignments and covariance models representing non-coding RNA families. Rfam is available on the web in the UK at http://www.sanger.ac.uk/Software/Rfam/ and in the US at http://rfam.wustl.edu/. These websites allow the user to search a query sequence against a library of covariance models, and view multiple sequence alignments and family annotation. The database can also be downloaded in flatfile form and searched locally using the INFERNAL package (http://infernal.wustl.edu/). The first release of Rfam (1.0) contains 25 families, which annotate over 50 000 non-coding RNA genes in the taxonomic divisions of the EMBL nucleotide database.
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            RegulonDB (version 6.0): gene regulation model of Escherichia coli K-12 beyond transcription, active (experimental) annotated promoters and Textpresso navigation

            RegulonDB (http://regulondb.ccg.unam.mx/) is the primary reference database offering curated knowledge of the transcriptional regulatory network of Escherichia coli K12, currently the best-known electronically encoded database of the genetic regulatory network of any free-living organism. This paper summarizes the improvements, new biology and new features available in version 6.0. Curation of original literature is, from now on, up to date for every new release. All the objects are supported by their corresponding evidences, now classified as strong or weak. Transcription factors are classified by origin of their effectors and by gene ontology class. We have now computational predictions for σ54 and five different promoter types of the σ70 family, as well as their corresponding −10 and −35 boxes. In addition to those curated from the literature, we added about 300 experimentally mapped promoters coming from our own high-throughput mapping efforts. RegulonDB v.6.0 now expands beyond transcription initiation, including RNA regulatory elements, specifically riboswitches, attenuators and small RNAs, with their known associated targets. The data can be accessed through overviews of correlations about gene regulation. RegulonDB associated original literature, together with more than 4000 curation notes, can now be searched with the Textpresso text mining engine.
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              Control of gene expression by a natural metabolite-responsive ribozyme.

              Most biological catalysts are made of protein; however, eight classes of natural ribozymes have been discovered that catalyse fundamental biochemical reactions. The central functions of ribozymes in modern organisms support the hypothesis that life passed through an 'RNA world' before the emergence of proteins and DNA. We have identified a new class of ribozymes that cleaves the messenger RNA of the glmS gene in Gram-positive bacteria. The ribozyme is activated by glucosamine-6-phosphate (GlcN6P), which is the metabolic product of the GlmS enzyme. Additional data indicate that the ribozyme serves as a metabolite-responsive genetic switch that represses the glmS gene in response to rising GlcN6P concentrations. These findings demonstrate that ribozyme switches may have functioned as metabolite sensors in primitive organisms, and further suggest that modern cells retain some of these ancient genetic control systems.
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                Author and article information

                Contributors
                mairla@cebitec.uni-bielefeld.de
                armin.neshat@cebitec.uni-bielefeld.de
                trygve.brautaset@sintef.no
                christian.rueckert@cebitec.uni-bielefeld.de
                joern.kalinowski@cebitec.uni-bielefeld.de
                volker.wendisch@uni-bielefeld.de
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                14 February 2015
                14 February 2015
                2015
                : 16
                : 1
                Affiliations
                [ ]Genetics of Prokaryotes, Faculty of Biology & Center for Biotechnology, Bielefeld University, Universitätsstr. 25, 33615 Bielefeld, Germany
                [ ]Microbial Genomics and Biotechnology, Center for Biotechnology, Bielefeld University, Universitätstr. 27, 33615 Bielefeld, Germany
                [ ]Department of Molecular Biology, SINTEF Materials and Chemistry, Sem Selands vei 2, 7465 Trondheim, Norway
                [ ]Department of Biotechnology, Norwegian University of Science and Technology, Sem Sælands vei 6/8, 7491 Trondheim, Norway
                [ ]Technology Platform Genomics, Center for Biotechnology, Bielefeld University, Universitätsstr. 27, 33615 Bielefeld, Germany
                Article
                1239
                10.1186/s12864-015-1239-4
                4342826
                © Irla et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Categories
                Research Article
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                © The Author(s) 2015

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