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      The Fur regulon in anaerobically grown Salmonella enterica sv. Typhimurium: identification of new Fur targets

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          Abstract

          Background

          The Ferric uptake regulator (Fur) is a transcriptional regulator that controls iron homeostasis in bacteria. Although the regulatory role of Fur in Escherichia coli is well characterized, most of the studies were conducted under routine culture conditions, i.e., in ambient oxygen concentration. To reveal potentially novel aspects of the Fur regulon in Salmonella enterica serovar Typhimurium under oxygen conditions similar to that encountered in the host, we compared the transcriptional profiles of the virulent wild-type strain (ATCC 14028s) and its isogenic Δ fur strain under anaerobic conditions.

          Results

          Microarray analysis of anaerobically grown Δ fur S. Typhimurium identified 298 differentially expressed genes. Expression of several genes controlled by Fnr and NsrR appeared to be also dependent on Fur. Furthermore, Fur was required for the activity of the cytoplasmic superoxide disumutases (MnSOD and FeSOD). The regulation of FeSOD gene, sodB, occurred via small RNAs (i.e., the ryhB homologs, rfrA and rfrB) with the aid of the RNA chaperone Hfq. The transcription of sodA was increased in Δ fur; however, the enzyme was inactive due to the incorporation of iron instead of manganese in SodA. Additionally, in Δ fur, the expression of the gene coding for the ferritin-like protein ( ftnB) was down-regulated, while the transcription of the gene coding for the nitric oxide (NO ·) detoxifying flavohemoglobin ( hmpA) was up-regulated. The promoters of ftnB and hmpA do not contain recognized Fur binding motifs, which indicated their probable indirect regulation by Fur. However, Fur activation of ftnB was independent of Fnr. In addition, the expression of the gene coding for the histone-like protein, H-NS ( hns) was increased in Δ fur. This may explain the observed down-regulation of the tdc operon, responsible for the anaerobic degradation of threonine, and ftnB in Δ fur.

          Conclusions

          This study determined that Fur is a positive factor in ftnB regulation, while serving to repress the expression of hmpA. Furthermore, Fur is required for the proper expression and activation of the antioxidant enzymes, FeSOD and MnSOD. Finally, this work identified twenty-six new targets of Fur regulation, and demonstrates that H-NS repressed genes are down-regulated in Δ fur.

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          Most cited references133

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          Gut inflammation provides a respiratory electron acceptor for Salmonella

          Salmonella enterica serotype Typhimurium (S. Typhimurium) causes acute gut inflammation by using its virulence factors to invade the intestinal epithelium and survive in mucosal macrophages. The inflammatory response enhances the transmission success of S. Typhimurium by promoting its outgrowth in the gut lumen through unknown mechanisms. Here we show that reactive oxygen species generated during inflammation reacted with endogenous, luminal sulphur compounds (thiosulfate) to form a new respiratory electron acceptor, tetrathionate. The genes conferring the ability to utilize tetrathionate as an electron acceptor produced a growth advantage for S. Typhimurium over the competing microbiota in the lumen of the inflamed gut. We conclude that S. Typhimurium virulence factors induce host-driven production of a new electron acceptor that allows the pathogen to use respiration to compete with fermenting gut microbes. Thus, the ability to trigger intestinal inflammation is crucial for the biology of this diarrhoeal pathogen.
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            A small RNA regulates the expression of genes involved in iron metabolism in Escherichia coli.

            A small RNA, RyhB, was found as part of a genomewide search for novel small RNAs in Escherichia coli. The RyhB 90-nt RNA down-regulates a set of iron-storage and iron-using proteins when iron is limiting; it is itself negatively regulated by the ferric uptake repressor protein, Fur (Ferric uptake regulator). RyhB RNA levels are inversely correlated with mRNA levels for the sdhCDAB operon, encoding succinate dehydrogenase, as well as five other genes previously shown to be positively regulated by Fur by an unknown mechanism. These include two other genes encoding enzymes in the tricarboxylic acid cycle, acnA and fumA, two ferritin genes, ftnA and bfr, and a gene for superoxide dismutase, sodB. Fur positive regulation of all these genes is fully reversed in an ryhB mutant. Our results explain the previously observed inability of fur mutants to grow on succinate. RyhB requires the RNA-binding protein, Hfq, for activity. Sequences within RyhB are complementary to regions within each of the target genes, suggesting that RyhB acts as an antisense RNA. In sdhCDAB, the complementary region is at the end of the first gene of the sdhCDAB operon; full-length sdhCDAB message disappears and a truncated message, equivalent in size to the region upstream of the complementarity, is detected when RyhB is expressed. RyhB provides a mechanism for the cell to down-regulate iron-storage proteins and nonessential iron-containing proteins when iron is limiting, thus modulating intracellular iron usage to supplement mechanisms for iron uptake directly regulated by Fur.
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              Identifying DNA and protein patterns with statistically significant alignments of multiple sequences.

              Molecular biologists frequently can obtain interesting insight by aligning a set of related DNA, RNA or protein sequences. Such alignments can be used to determine either evolutionary or functional relationships. Our interest is in identifying functional relationships. Unless the sequences are very similar, it is necessary to have a specific strategy for measuring-or scoring-the relatedness of the aligned sequences. If the alignment is not known, one can be determined by finding an alignment that optimizes the scoring scheme. We describe four components to our approach for determining alignments of multiple sequences. First, we review a log-likelihood scoring scheme we call information content. Second, we describe two methods for estimating the P value of an individual information content score: (i) a method that combines a technique from large-deviation statistics with numerical calculations; (ii) a method that is exclusively numerical. Third, we describe how we count the number of possible alignments given the overall amount of sequence data. This count is multiplied by the P value to determine the expected frequency of an information content score and, thus, the statistical significance of the corresponding alignment. Statistical significance can be used to compare alignments having differing widths and containing differing numbers of sequences. Fourth, we describe a greedy algorithm for determining alignments of functionally related sequences. Finally, we test the accuracy of our P value calculations, and give an example of using our algorithm to identify binding sites for the Escherichia coli CRP protein. Programs were developed under the UNIX operating system and are available by anonymous ftp from ftp://beagle.colorado.edu/pub/consensus.
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                Author and article information

                Journal
                BMC Microbiol
                BMC Microbiology
                BioMed Central
                1471-2180
                2011
                21 October 2011
                : 11
                : 236
                Affiliations
                [1 ]Department of Microbiology, North Carolina State University, Raleigh, NC 27695-7615, USA
                [2 ]The Vaccine Research Institute of San Diego, 10835 Road to the Cure, Suite 105, San Diego, CA 92121, USA
                [3 ]Department of Immunology and Microbiology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
                [4 ]Department of Food Science and Nutrition, University of Minnesota, St. Paul, MN 55108-1038, USA
                Article
                1471-2180-11-236
                10.1186/1471-2180-11-236
                3212961
                22017966
                d7fd9bb2-a0e7-4920-b4a9-d2f7fbea54a3
                Copyright ©2011 Troxell 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.

                History
                : 14 July 2011
                : 21 October 2011
                Categories
                Research Article

                Microbiology & Virology
                Microbiology & Virology

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