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      Impact of growth pH and glucose concentrations on the CodY regulatory network in Streptococcus salivarius

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          Streptococcus salivarius is an abundant isolate of the human oral microbiota. Since both pH and glucose availability fluctuate frequently in the oral cavity, the goal of this study was to investigate regulation by CodY, a conserved pleiotropic regulator of Gram positive bacteria, in response to these two signals. The chemostat culture system was employed to precisely control the growth parameters, and the transcriptomes of wild-type S. salivarius 57.I and its CodY-null derivative (Δ codY) grown at pH 7 and 5.5, with limited and excessive glucose supply were determined.


          The transcriptomic analysis revealed that CodY was most active at pH 7 under conditions of glucose limitation. Based on whether a CodY binding consensus could be located in the 5′ flanking region of the identified target, the transcriptomic analysis also found that CodY shaped the transcriptome via both direct and indirect regulation. Inactivation of codY reduced the glycolytic capacity and the viability of S. salivarius at pH 5.5 or in the presence of H 2O 2. Studies using the Galleria mellonella larva model showed that CodY was essential for the toxicity generated from S. salivarius infection, suggesting that CodY regulation was critical for immune evasion and systemic infections. Furthermore, the CodY-null mutant strain exhibited a clumping phenotype and reduced attachment in biofilm assays, suggesting that CodY also modulates cell wall metabolism. Finally, the expression of genes belonging to the CovR regulon was affected by codY inactivation, but CodY and CovR regulated these genes in opposite directions.


          Metabolic adaptation in response to nutrient availability and growth pH is tightly linked to stress responses and virulence expression in S. salivarius. The regulation of metabolism by CodY allows for the maximal utilization of available nutrients and ATP production. The counteractive regulation of the CovR regulon could fine tune the transcriptomes in response to environmental changes.

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          The online version of this article (10.1186/s12864-018-4781-z) contains supplementary material, which is available to authorized users.

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          Most cited references 60

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          edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

          Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site ( Contact:
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            MEME Suite: tools for motif discovery and searching

            The MEME Suite web server provides a unified portal for online discovery and analysis of sequence motifs representing features such as DNA binding sites and protein interaction domains. The popular MEME motif discovery algorithm is now complemented by the GLAM2 algorithm which allows discovery of motifs containing gaps. Three sequence scanning algorithms—MAST, FIMO and GLAM2SCAN—allow scanning numerous DNA and protein sequence databases for motifs discovered by MEME and GLAM2. Transcription factor motifs (including those discovered using MEME) can be compared with motifs in many popular motif databases using the motif database scanning algorithm Tomtom. Transcription factor motifs can be further analyzed for putative function by association with Gene Ontology (GO) terms using the motif-GO term association tool GOMO. MEME output now contains sequence LOGOS for each discovered motif, as well as buttons to allow motifs to be conveniently submitted to the sequence and motif database scanning algorithms (MAST, FIMO and Tomtom), or to GOMO, for further analysis. GLAM2 output similarly contains buttons for further analysis using GLAM2SCAN and for rerunning GLAM2 with different parameters. All of the motif-based tools are now implemented as web services via Opal. Source code, binaries and a web server are freely available for noncommercial use at
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              Initiation of biofilm formation in Pseudomonas fluorescens WCS365 proceeds via multiple, convergent signalling pathways: a genetic analysis.

              Populations of surface-attached microorganisms comprising either single or multiple species are commonly referred to as biofilms. Using a simple assay for the initiation of biofilm formation (e.g. attachment to an abiotic surface) by Pseudomonas fluorescens strain WCS365, we have shown that: (i) P. fluorescens can form biofilms on an abiotic surface when grown on a range of nutrients; (ii) protein synthesis is required for the early events of biofilm formation; (iii) one (or more) extracytoplasmic protein plays a role in interactions with an abiotic surface; (iv) the osmolarity of the medium affects the ability of the cell to form biofilms. We have isolated transposon mutants defective for the initiation of biofilm formation, which we term surface attachment defective (sad). Molecular analysis of the sad mutants revealed that the ClpP protein (a component of the cytoplasmic Clp protease) participates in biofilm formation in this organism. Our genetic analyses suggest that biofilm formation can proceed via multiple, convergent signalling pathways, which are regulated by various environmental signals. Finally, of the 24 sad mutants analysed in this study, only three had defects in genes of known function. This result suggests that our screen is uncovering novel aspects of bacterial physiology.

                Author and article information

                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                23 May 2018
                23 May 2018
                : 19
                [1 ]ISNI 0000 0004 0644 6935, GRID grid.464209.d, Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, ; Beijing, China
                [2 ]GRID grid.145695.a, Department of Microbiology and Immunology, , College of Medicine, Chang Gung University, ; Taoyuan, Taiwan
                [3 ]GRID grid.145695.a, Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, ; Taoyuan, Taiwan
                [4 ]Molecular Infectious Disease Research Center, Chang Gung Memorial Hospital, Linkou, Taiwan
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

                Funded by: FundRef, Chang Gung Memorial Hospital, Linkou;
                Award ID: CMRPD1G0151
                Funded by: Ministry of Science and Technology (ROC)
                Award ID: MOST 105-2320-B-182-015-MY3
                Research Article
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                © The Author(s) 2018


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