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Transcriptomic analysis of aerobic respiratory and anaerobic photosynthetic states in Rhodobacter capsulatus and their modulation by global redox regulators RegA, FnrL and CrtJ

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      Abstract

      Anoxygenicphotosynthetic prokaryotes have simplified photosystems that represent ancient lineages that predate the more complex oxygen evolving photosystems present in cyanobacteria and chloroplasts. These organisms thrive under illuminated anaerobic photosynthetic conditions, but also have the ability to grow under dark aerobic respiratory conditions. This study provides a detailed snapshot of transcription ground states of both dark aerobic and anaerobic photosynthetic growth modes in the purple photosynthetic bacterium Rhodobactercapsulatus. Using 18 biological replicates for aerobic and photosynthetic states, we observed that 1834 genes (53 % of the genome) exhibited altered expression between aerobic and anaerobic growth. In comparison with aerobically grown cells, photosynthetically grown anaerobic cells showed decreased transcription of genes for cobalamin biosynthesis (−45 %), iron transport and homeostasis (−42 %), motility (−32 %), and glycolysis (−34 %). Conversely and more intuitively, the expression of genes involved in carbon fixation (547 %), bacteriochlorophyll biosynthesis (162 %) and carotenogenesis (114 %) were induced. We also analysed the relative contributions of known global redox transcription factors RegA, FnrL and CrtJ in regulating aerobic and anaerobic growth. Approximately 50 % of differentially expressed genes (913 of 1834) were affected by a deletion of RegA, while 33 % (598 out of 1834) were affected by FnrL, and just 7 % (136 out of 1834) by CrtJ. Numerous genes were also shown to be controlled by more than one redox responding regulator.

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      The operated Markov´s chains in economy (discrete chains of Markov with the income)

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        Primer3—new capabilities and interfaces

        Polymerase chain reaction (PCR) is a basic molecular biology technique with a multiplicity of uses, including deoxyribonucleic acid cloning and sequencing, functional analysis of genes, diagnosis of diseases, genotyping and discovery of genetic variants. Reliable primer design is crucial for successful PCR, and for over a decade, the open-source Primer3 software has been widely used for primer design, often in high-throughput genomics applications. It has also been incorporated into numerous publicly available software packages and web services. During this period, we have greatly expanded Primer3’s functionality. In this article, we describe Primer3’s current capabilities, emphasizing recent improvements. The most notable enhancements incorporate more accurate thermodynamic models in the primer design process, both to improve melting temperature prediction and to reduce the likelihood that primers will form hairpins or dimers. Additional enhancements include more precise control of primer placement—a change motivated partly by opportunities to use whole-genome sequences to improve primer specificity. We also added features to increase ease of use, including the ability to save and re-use parameter settings and the ability to require that individual primers not be used in more than one primer pair. We have made the core code more modular and provided cleaner programming interfaces to further ease integration with other software. These improvements position Primer3 for continued use with genome-scale data in the decade ahead.
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          Relative expression software tool (REST) for group-wise comparison and statistical analysis of relative expression results in real-time PCR.

          Real-time reverse transcription followed by polymerase chain reaction (RT-PCR) is the most suitable method for the detection and quantification of mRNA. It offers high sensitivity, good reproducibility and a wide quantification range. Today, relative expression is increasingly used, where the expression of a target gene is standardised by a non-regulated reference gene. Several mathematical algorithms have been developed to compute an expression ratio, based on real-time PCR efficiency and the crossing point deviation of an unknown sample versus a control. But all published equations and available models for the calculation of relative expression ratio allow only for the determination of a single transcription difference between one control and one sample. Therefore a new software tool was established, named REST (relative expression software tool), which compares two groups, with up to 16 data points in a sample and 16 in a control group, for reference and up to four target genes. The mathematical model used is based on the PCR efficiencies and the mean crossing point deviation between the sample and control group. Subsequently, the expression ratio results of the four investigated transcripts are tested for significance by a randomisation test. Herein, development and application of REST is explained and the usefulness of relative expression in real-time PCR using REST is discussed. The latest software version of REST and examples for the correct use can be downloaded at http://www.wzw.tum.de/gene-quantification/.
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            Author and article information

            Affiliations
            [ 1] Molecular and Cellular Biochemistry, Indiana University , Bloomington, USA
            [ 2] Biochemistry, Indiana University Bloomington , Simon Hall MSB, 212 S Hawthorne Dr, Bloomington, IN 47405-7003, USA
            Author notes
            *Correspondence: Carl E. Bauer, bauer@ 123456indiana.edu

            Data statement: We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Seven supplementary tables and five supplementary figures are available with the online Supplementary Material.

            Journal
            Microb Genom
            Microb Genom
            MGen
            Microbial Genomics
            Microbiology Society
            2057-5858
            September 2017
            8 July 2017
            : 3
            : 9
            5643017 mgen000125 10.1099/mgen.0.000125
            © 2017 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.

            Product
            Funding
            Funded by: National Institute of General Medical Sciences
            Award ID: GM040941
            Categories
            Research Article
            Systems Microbiology
            Transcriptomics
            Proteomics
            Networks
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            fnrl, crtj, rega, transcriptomics, redox regulation

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